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wagtail-alt-generator | pypi version https badge fury io py wagtailaltgenerator svg https badge fury io py wagtailaltgenerator build status https travis ci org marteinn wagtail alt generator svg branch develop https travis ci org marteinn wagtail alt generator wagtail alt generator generate image description and tags with the help of computer vision inspired by altify https github com parhamp altify blob master altify altify screen1 https raw githubusercontent com marteinn wagtail alt generator develop img screenshot png https www youtube com watch v 1jecjkx0lko screencast demo https www youtube com watch v 1jecjkx0lko features create image descriptions using computer vision generate image tags using computer vision support for multiple service providers azure cognitive services aws rekognition and google vision translate descriptions to your native language using google translate documentation getting started docs getting started md settings docs settings md adding supported provider adding azure cognitive services as a provider docs adding azure cognitive services md adding aws rekognition as a provider docs adding aws rekognition md adding google vision as a provider docs adding google vision md translating description tags docs adding google translate md contributing want to contribute awesome just send a pull request license wagtail alt generator is released under the mit license http www opensource org licenses mit | wagtail django computer-vision | ai |
blockchain-academy | blockchain academy the purpose of this documentation is to provide a shortcut for people who are interested in learning about blockchain to more easily find free quality content on the subject we will divide it into three sections in the first one basics basics we will cover the basic concept of blockchain after that in common blockchains common blockchains we ll delve deeper into blockchains that are most present in real life projects that customers ask for lastly we will have code code content and tutorials to develop better programming skills in blockchain context we will also have a section where people who want to be mentors mentors make their contacts available to answer questions from those who have them feel free to suggest or create prs with changes and additions as well as open discussions in the issues section a id basics a basics in this section you will find content about what is blockchain its architecture and how it works in the real world after you finish that you should be able to explain what blockchain is where to apply it and the problems it solves reading 1 what is blockchain https www investopedia com terms b blockchain asp 2 blockchain explained in under 100 words https www2 deloitte com ch en pages strategy operations articles blockchain explained html 3 but how does bitcoin actually work https www youtube com watch v bbc nxj3ng4 ab channel 3blue1brown video 4 blockchain history https en wikipedia org wiki blockchain history 5 types of blockchain https en wikipedia org wiki blockchain types 6 how blockchain data is stored and secured https www euromoney com learning blockchain explained how blockchain data is stored and secured 7 how does a transaction get into the blockchain https www euromoney com learning blockchain explained how transactions get into the blockchain 8 proof of work vs proof of stake https medium com swissborg proof of work vs proof of stake translated by hashiva pedro lima c136e3b5faaa pt br 9 what are smart contracts by ibm https www ibm com topics smart contracts 10 what is defi https forkast news explainer decentralized finance defi guide 11 what is dao https coinmarketcap com alexandria article what is a dao 12 what are nfts https www forbes com advisor investing nft non fungible token 13 blockchain applied on our lives 30 startups https builtin com blockchain blockchain applications courses and videos 1 blockchain theory 101 https www udemy com course blockchain theory 101 course 2 smart contracts course by coursera https www coursera org learn smarter contracts course 3 dapp university https www youtube com channel ucy0xl8v6nzzfcwzhcgb8orq youtube a id common blockchains a common blockchains ethereum https ethereum org reading 1 ethereum official site https ethereum org 2 what is ethereum https www investopedia com terms e ethereum asp 3 what is ether https ethereum org en eth 4 how to use ethereum https www coindesk com learn ethereum 101 how to use ethereum 5 ethereum virtual machine evm https ethereum org en developers docs evm 6 main and test networks https ethereum org en developers docs networks 7 gas and fees https ethereum org en developers docs gas 8 oracles https ethereum org en developers docs oracles 9 programming language solidity https docs soliditylang org en v0 8 6 10 solidity official site https docs soliditylang org en v0 8 6 courses and videos 1 ethereum explained to beginners https www youtube com watch v jxlkbjozkby ab channel 99bitcoins video 2 oracles explained simply https www youtube com watch v m64dlrjj9bs ab channel hashoshi video 3 cryptozombies https cryptozombies io learn to code blockchain apps by building simple games course tools 1 solidity https docs soliditylang org en v0 8 6 the ethereum programming language 2 remix online ide https remix ethereum org ideal to test compile and use your smart contracts without the need of install and configure an entire local environment 3 openzeppelin https openzeppelin com the best abstraction to your smart contracts to prevent you from rewriting patterns like erc20 erc721 and erc1155 just extending as inheritance 4 hardhat https hardhat org an ethereum development environment to deploy debug and test your smart contracts wax eos https on wax io wax io a blockchain focused on nfts reading 1 wax official site https on wax io wax io 2 what is wax https academy ivanontech com blog exploring the worldwide asset exchange wax 3 top 5 wax dapps https www youtube com watch v 3evvwhg8oeg ab channel liteliger courses and videos 1 create smart contracts on wax blockchain https tetacourse com development 892 create a smart contract on wax blockchain including nft rng html course tools 1 eos studio https app eosstudio io an eos online ide a id code a code ethereum https ethereum org 1 solidity full tutorial https www tutorialspoint com solidity index htm documentation 2 solidity by example https solidity by example org course 3 how to create an nft https docs alchemy com alchemy tutorials how to create an nft tutorial wax eos https on wax io wax io a blockchain focused on nfts 1 create nft on wax https developer wax io dapps create non fungible tokens nfts tutorial 2 create your own dapp on wax https developer wax io dapps deploy your dapp on wax tutorial a id mentors a mentors igor louren o twitter https twitter com igorlourenco | blockchain |
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Ontirandoc | ontirandoc an integrated methodology for ontology construction we designed a tentative model of an integrated system called ontirandoc which can be used for ontology construction from three types of knowledge sources ontirandoc is not only a tool for creating and editing ontology files but also a methodology that contains detailed process guideline methods algorithms and an integrated modular software to support the process we implemented our algorithms in an open source php web application after passing several rounds of suggestion development evaluation cycle we reached our final integrated system this system has a modular design and is open source to enable other researchers to upgrade or customize it according their especial needs the architecture of the system is shown in following picture the model was designed by archimate language that is one of the architecture description languages in iso iec ieee 4210 ontorandoc architechture https github com milanifard ontirandoc blob master ontirandoc png the proposed architecture covers main activities for ontology construction and also provides a platform for collaborative ontology development several software modules were designed and implemented in an integrated system to support main activities and persian language the modularity design allows to upgrade or customize each module independently ontirandoc activities and related modules 1 requirement specification almost all ontology construction methodologies consider this activity for which the result is a document that specifies the goal scope and requirements of the product 2 knowledge sources identification environment study and feasibility test are two main tasks that are mentioned in on to knowledge and neon methodology in ontirandoc these tasks are decomposed into four activities existing ontologies identification domain expert identification related text documents identification and related database identification 3 terms extraction in this activity ontology developers extract terms based on open coding technique in content analysis methods 47 the first time a term is identified by a developer he can add it and its location page paragraph and sentence into the terms vocabulary by using ontirandoc register terms user interface the location will be used in co occurance analysis if developers identify an existing term in the text they can select it from vocabulary and add its new location so the system can calculate tf idf of each term some modules are designed and implemented in order to help developers to identify previously extracted terms suggest similar existing terms before adding a new one this module will show both structuarl and semantic similarity semantic similarity is identified by using wordnet in our case we used a persian wordnet called ferdowsnet and structure similarity is identified by levenshtein distance and prefix suffix analysis merge similar terms 4 terms conceptualization the goal of this activity is transfering terms to ontology entities developers may create a new ontology entity for a term or just map the term to an existing ontology elements a software module calculates tf idf value of extracted terms and shows them as a sorted list to developer a term with larger tf idf is more important in that domain the following software modules help developers in this activity showing a term references in texts by selecting each term this module shows all paragraphs that have this term showing semantic related terms in the current version just synonyms hyponyms and hypernyms for each selected term by using wordnet and ferdowsnet these lists would help developers to identify hierarchical or non hierarchical relations in the ontology showing similar terms structural similarity for each selected term this list helps developers to identify relations between classes or properties of classes showing similar ontology elements in existing ontologies it assists developers to select a better ontology element type by knowing other s modeling view performing co occurrence analysis to identify relation between terms and their mapped ontology elements after conceptualizing all the terms following software modules would help developers to refine the result ontology showing all classes that have similar child classes and asking the developer if he wants to merge them showing redundant properties relations exists in both parent and child class and asking the developer if he wants to remove them showing similar relations between two classes and asking the developer if he wants to merge them 5 database re engineering this activity is designed in two steps preparation and extraction ontirandoc relies on a rich meta data therefore the preparation step is designed to prepare such data a rich meta data should have the following information about database elements all elements should have clear and meaningful labels that describe their content and existence reason these labels can be defined in any language ontirandoc current implementation supports persian and english languages relatedness of each elements to business domains should be specified all table relations should be specified some of these relations are defined in the database schema and some of them are hidden in applications code to support enrichment of meta data several modules were designed and implemented in ontirandoc table content investigator researchers have proposed a few solutions to extract the meaning of tables by analyzing their contents such as 34 and 48 however these solutions are not efficient for large tables such as the case of our database the table content investigator module in ontirandoc does not apply any specific data mining or other data processing algorithms and only allows ontology developers to investigate table contents by applying horizontal and vertical filters source code investigator most of the ambiguities in database entities meaning can be resolved by investigating application source code 24 some table relations might also be hidden in the source code this module proposes a practical solution to complete the meta data by investigating application source code ontology developers can use this module through a user interface that allows them to complete meta data of a table through following features showing all source files that send queries with specific table names to the dbms it assumes that this module has access to query log files ontology developers can trace usage of a table in source files and identify the meaning of that table by reading the related source codes showing contnet of a source code file to the developer showing source code files evolution history it assumes that this module has access to the software project management data history of a source file helps ontology developers to find the reason of creation and evolution of a source code that is related to a table it also helps software developers who work on that source file and may need to refer to software developers and ask them about usage of a table investigating the software configuration information systems usually organize their features in system menus relation between software menus and source code files is a good knowledge source about the meaning of tables this module helps ontology developers to trace a menu from the source files that use specific tables description of menus can tell ontology developers about the meaning of tables and also ontology developers can refer to those menus in functional systems and extract the meaning from their ui suggesting table relations the structural similarity between a field name in one table and primary key in another table may reveals a foreign key that is not defined in the database schema 6 merging existing ontologies this activity has four steps labeling ontology elements mapping similar ontology elements merging ontologies and refining the result four software modules were designed in correspondence to these steps labeling step will provide localize each element has a persian label and consistent all same elements have same label ontologies ontirandoc software modules and ui help ontology developers to navigate between ontologies and their elements view structural and semantically similar elements and add proper labels because of the difference in naming and modeling view finding similar elements in different ontologies cannot be fully automated and needs user intervention 7 evaluation researchers have proposed several methods to evaluate an ontology these methods can be classified into three approaches 50 comparing ontology with a golden standard based on the user based on application of ontology and based on comparing with the source of data in our methodology the evaluation activity is designed based on two approaches comparing with a golden standard precision and recall are two main measures that should be calculated 51 a software module was designed and implemented to calculate these parameters note that before comparing two ontologies their elements must be labeled by using ontirandoc tools as we discussed before based on user assertions technique is one of the methods in this approach this would allow users to investigate data model details by viewing them in a list of natural language assertions 52 we adapted this technique customized it to support persian language and implemented a web based software module to show an ontology details in persian language assertions and get users opinion and comments the user s feedbacks is aggregated and shown to developers for updating the ontology in addition to checking validity of ontology by applying above approaches we designed and implemented a software module to calculate the quality of target ontology based on the framework presented in 53 ontology quality measures that are implemented in this modules are number of properties nop average properties per class ap c average fanout of classes af c number of roots nor and average fanout of root classes af r installation guide 1 extract ontirandoc database rar wordnet rar ferdowsnet rar 2 create database using ontirandoc database sql 3 populate wordnet and ferdowsnet databases using wordnet sql and ferdowsnet sql 5 set database username and password in shares config class php and mysql config php 6 you can change ui language constant in shares definitions php to select persian or english user interface 7 set following keys in php ini short open tag on error reporting e all e deprecated e strict use login php page for login default username omid password omid3000 this software has a persian user manual ontirandocusermanual docx https github com milanifard ontirandoc blob master ontirandocusermanual docx raw true | front_end |
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anchor | div align center img height 170x src https pbs twimg com media fvuvao9xeaaulvk format png name small h1 anchor h1 p strong solana sealevel framework strong p p a href https github com coral xyz anchor actions img alt build status src https github com coral xyz anchor actions workflows tests yaml badge svg a a href https anchor lang com img alt tutorials src https img shields io badge docs tutorials blueviolet a a href https discord gg nhhgsxanxk img alt discord chat src https img shields io discord 889577356681945098 color blueviolet a a href https opensource org licenses apache 2 0 img alt license src https img shields io github license coral xyz anchor color blueviolet a p div anchor is a framework for solana s sealevel https medium com solana labs sealevel parallel processing thousands of smart contracts d814b378192 runtime providing several convenient developer tools for writing smart contracts rust edsl for writing solana programs idl https en wikipedia org wiki interface description language specification typescript package for generating clients from idl cli and workspace management for developing complete applications if you re familiar with developing in ethereum s solidity https docs soliditylang org en v0 7 4 truffle https www trufflesuite com web3 js https github com ethereum web3 js then the experience will be familiar although the dsl syntax and semantics are targeted at solana the high level flow of writing rpc request handlers emitting an idl and generating clients from idl is the same getting started for a quickstart guide and in depth tutorials see the anchor book https book anchor lang com and the older documentation https anchor lang com that is being phased out to jump straight to examples go here https github com coral xyz anchor tree master examples for the latest rust and typescript api documentation see docs rs https docs rs anchor lang and the typedoc https coral xyz github io anchor ts index html packages package description version docs anchor lang rust primitives for writing programs on solana crates io https img shields io crates v anchor lang color blue https crates io crates anchor lang docs rs https docs rs anchor lang badge svg https docs rs anchor lang anchor spl cpi clients for spl programs on solana crates https img shields io crates v anchor spl color blue docs rs https docs rs anchor spl badge svg https docs rs anchor spl anchor client rust client for anchor programs crates https img shields io crates v anchor client color blue docs rs https docs rs anchor client badge svg https docs rs anchor client coral xyz anchor typescript client for anchor programs npm https img shields io npm v coral xyz anchor svg color blue https www npmjs com package coral xyz anchor docs https img shields io badge docs typedoc blue https coral xyz github io anchor ts index html coral xyz anchor cli cli to support building and managing an anchor workspace npm https img shields io npm v coral xyz anchor cli svg color blue https www npmjs com package coral xyz anchor cli docs https img shields io badge docs typedoc blue https coral xyz github io anchor cli commands html note anchor is in active development so all apis are subject to change this code is unaudited use at your own risk examples here s a counter program where only the designated authority can increment the count rust use anchor lang prelude declare id fg6pafpogxkysidmpwtk6w2bez7fefcykg476zpfslns program mod counter use super pub fn initialize ctx context initialize start u64 result let counter mut ctx accounts counter counter authority ctx accounts authority key counter count start ok pub fn increment ctx context increment result let counter mut ctx accounts counter counter count 1 ok derive accounts pub struct initialize info account init payer authority space 48 pub counter account info counter pub authority signer info pub system program program info system derive accounts pub struct increment info account mut has one authority pub counter account info counter pub authority signer info account pub struct counter pub authority pubkey pub count u64 for more see the examples https github com coral xyz anchor tree master examples and tests https github com coral xyz anchor tree master tests directories license anchor is licensed under apache 2 0 license unless you explicitly state otherwise any contribution intentionally submitted for inclusion in anchor by you as defined in the apache 2 0 license shall be licensed as above without any additional terms or conditions contribution thank you for your interest in contributing to anchor please see the contributing md contributing md to learn how thanks div align center a href https github com coral xyz anchor graphs contributors img src https contrib rocks image repo coral xyz anchor width 100 a div | solana rust blockchain smart-contracts coral | blockchain |
howtousellms | how to use llms for text analysis this guide introduces large language models llm as a highly versatile text analysis method within the social sciences as llms are easy to use cheap fast and applicable on a broad range of text analysis tasks ranging from text annotation and classification to sentiment analysis and critical discourse analysis many scholars believe that llms will transform how we do text analysis this how to guide is aimed at students and researchers with limited programming experience and offers a simple introduction to how llms can be used for text analysis in your own research project as well as advice on best practices we will go through each of the steps of analyzing textual data with llms using python installing the software setting up the api loading the data developing an analysis prompt analyzing the text and validating the results as an illustrative example we will use the challenging task of identifying populism in political texts and show how llms move beyond the existing state of the art | ai |
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TextSentimentAnalysis | text sentiment analysis python version https img shields io badge python 3 7 6 red tensorflow version https img shields io badge tensorflow 2 3 0 lime keras version https img shields io badge keras 2 4 3 orange pypi version https img shields io badge pypi 20 0 2 yellow hits https hitcounter pythonanywhere com count tag svg url https 3a 2f 2fgithub com 2fkhanfarhan10 2ftextsentimentanalysis github issues open https img shields io github issues raw khanfarhan10 textsentimentanalysis github issues closed https img shields io github issues closed raw khanfarhan10 textsentimentanalysis github open pull requests https img shields io github issues pr raw khanfarhan10 textsentimentanalysis github closed pull requests https img shields io github issues pr closed raw khanfarhan10 textsentimentanalysis github forks https img shields io github forks khanfarhan10 textsentimentanalysis github stars https img shields io github stars khanfarhan10 textsentimentanalysis github license https img shields io github license khanfarhan10 textsentimentanalysis shoutout to https shields io for these wonderful badges text sentiment analysis in python using natural language processing nlp for negative positive content predictions deployed on the cloud using streamlit on the heroku platform winter of code 2020 view project ideas https github com dsc iem woc project ideas text sentiment analysis or view issues to solve https github com khanfarhan10 textsentimentanalysis issues web application demo view the deployed webapp on heroku http sentimentproject herokuapp com nlpsentiment installation setting up the application locally dependencies run the command code pip install r requirements txt code on your cmd python terminal it is highly recommended to create a new virtual environment https docs python org 3 library venv html first before running the above commands the instructions for doing the same is provided below creating virtual environments for python development in visual studio code for this project deployment use streamlit app code streamlit run textsentimentapp py code if there is no popup window opening in the browser you can paste the following address http localhost 8501 http localhost 8501 creating virtual environments for python development in visual studio code for this project a guide to creating virtual environments into python and using them effectively clone the text sentiment analysis repo head over to our github repository https github com khanfarhan10 textsentimentanalysis fork the repo to your github account clone the repository into your local machine initial setup open cmd powershell from the vscode terminal it should display an output like the following cmd code microsoft windows version 10 0 18363 1198 c 2019 microsoft corporation all rights reserved c users farha documents github textsentimentanalysis code or powershell code windows powershell copyright c microsoft corporation all rights reserved try the new cross platform powershell https aka ms pscore6 code check for the python version you re running code c users farha documents github textsentimentanalysis python version python 3 7 6 code check for the python packaging index pypi version you re running code c users farha documents github textsentimentanalysis pip version pip 20 0 2 from c programdata anaconda3 lib site packages pip python 3 7 code install the virtualenv module from pip code c users farha documents github textsentimentanalysis pip install virtualenv code create a project environment directory with yourawesomeprojectnameenvironment code c users farha documents github textsentimentanalysis mkdir textsentimentenv code create a new empty virtual environment in yourawesomeprojectnameenvironment code c users farha documents github textsentimentanalysis virtualenv textsentimentenv code users for other python versions may install python 3 7 6 https www python org downloads release python 376 first and then run the following command to choose the correct python interpreter with the correct path code virtualenv python python3 7 6 textsentimentenv code note if you have problems with this step try followng the debugging options provided below useful links for debugging enter into the newly created empty virtual environment in yourawesomeprojectnameenvironment code c users farha documents github textsentimentanalysis textsentimentenv scripts activate code you will notice a yourawesomeprojectnameenvironment appearing in the command line interface code textsentimentenv c users farha documents github textsentimentanalysis code wohoooo you re now in your virtual environment install dependencies okay great we ve got our virtualenv setup but it s empty right now lets install some modules into it for this we will be needing a txt file noting all the dependency requirements for a project under the project directory this file contains packages in the following naming fashion and can be obtained using code pip freeze requirements txt code or using code conda list explicit reqs txt code when you ve obtained the requirements file do the following with your environment activated code pip install r requirements txt code you are now happy to go forth coding and running your app with code streamlit run textsentimentapp py code useful links for debugging https github com continuumio anaconda issues issues 10822 https dev to idrisrampurawala setting up python workspace in visual studio code vscode 149p https dev to idrisrampurawala flask boilerplate structuring flask app 3kcd voila magic if you have further issues queries regarding the project feel free to contact us farhan hai khan njrfarhandasilva10 gmail com tannistha pal paltannistha gmail com using the streamlit app to start using the streamlit application follow these steps 1 clone the repo git clone https github com khanfarhan10 textsentimentanalysis git 2 start the streamlit app cd textsentimentanalysis streamlit streamlit run sentiment py 3 start the flask server cd textsentimentanalysis server python server py usage of paraphrase and summarization utilities in the streamlit application you can enter the text and in the sidebar you can choose the task you want to perform and hit the button for the corresponding inference cli tool usage please follow the steps to use the cli tool for text sentiment analysis and for summarization 1 clone the repo git clone https github com khanfarhan10 textsentimentanalysis git 2 change directory into the application folder cd textsentimentanalysis txt cli 3 install the cli through pip pip3 install 4 usage of the cli txt option inputfilepath outputfilepath 5 options option tsa text sentiment analysis sum summarization inputfilepath path to a csv file containing texts in the first column outputfilepath path to an empty csv file | text-sentiment-analysis natural-language-processing nlp streamlit hate-speech-predictions content-detection | ai |
hello-world | hello world an information technology student | server |
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IoT | iot all things iot this is my general iot repository | server |
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data | data sets for machine learning practice name description source iris https github com dataprofessor data blob master iris csv 150 flowers rows belonging to the 3 species setosa is versicolor and virginica of the iris genus the dataset consists of 4 input variables sepal length sepal width petal length and petal width and 1 output variable the class label of the iris species as being setosa is versicolor and virginica 1 https archive ics uci edu ml datasets iris dhfr https github com dataprofessor data blob master dhfr csv 325 molecules rows with biological activity against the dhfr enzyme an anti marial drug target the dataset consists of 228 input variables molecular descriptors describing the physicochemical properties of the molecule and 1 output variable the biological activity as being either active or inactive 2 https www rdocumentation org packages caret versions 6 0 84 topics dhfr heart disease cleveland https github com dataprofessor data blob master heart disease cleveland csv 303 patients rows who have been diagnosed as having diagnosis score of 1 2 3 or 4 or not having diagnosis score of 0 heart disease the dataset consists of 13 input variables the health parameters and 1 output variable diagnosis 3 https archive ics uci edu ml datasets heart disease | ai |
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malware-url-lookup | malware url lookup coding exercise problem statement we have an http proxy that is scanning traffic looking for malware urls before allowing http connections to be made this proxy asks a service that maintains several databases of malware urls if the resource being requested is known to contain malware write a small web service that responds to get requests where the caller passes in a url and the service responds with some information about that url the get requests would look like this get v1 urlinfo resource url with query string the caller wants to know if it is safe to access that url or not quickstart guide ensure you have the required dependencies installed git docker make go if you want to run client for example build and run necessary containers bash cd malware url lookup make build make run perform url lookups or updates bash perform desired api calls small client script included for convinience go run cmd client main go what to expect when you run the client 1 uploads 5000 dummy urls url0 com url4999 com should return success true 2 checks for existence of urls url1 com should return safe false url2500 com should return safe false url4999 com should return safe false 3 checks for non existence of urls url5000 com should return safe true clean up bash make i clean api schema check if url is a known source of malware get v1 urlinfo resource url with query string returns an application json reponse object indicating whether or not the url is safe json safe true submit url s that are a known source of malware post v1 urlinfo accepts urls to be added to the malware database expects them as an application json object in the body of a post request as defined below json urls url1 com url2 com urln com bonus features the size of the url list could grow infinitely how might you scale this beyond the memory capacity of the system bonus if you implement this there are two dimensions to this questions the first being reducing the storage footprint memory requirements of the system and the second being given the system is optimized how does it scale for the latter my choice would be to use a distributed cloud based database which would scale automatically given the needs of the system again i will tackle this if i have time for the former i made the design decision to only include known malicious urls in the database since their non existence in the database implies their safety i also took some time to consider the database best suited for this job a relational database e g mysql is not needed at time of writing since we need not know any details related to the url in question we need only a single column yet even a columnar database e g cassandra is suboptimal since it strives to make the data data ranges query able we are looking for something which offers a one to one does it exist type of functionality our data is not suited for a graph database nor do we need the flexibility of a document database the best choice for this problem is a key value database i have further refined this selection to my final choice redis because of its aptitude to run as a container and because it runs in memory i e ram which is well suited for this application since it is highly latency sensitive the number of requests may exceed the capacity of this system how might you solve that bonus if you implement this this question is similar to the last in that we should examine the problem from the same 2 angles firstly for the system to function at optimal capacity we would need it to handle requests conncurrently i e non blocking so that it may accept incoming requests while it s still processing prior requests caching should also be added for optimal efficiency of retrieval a nuance of our caching system is that we are only storing the urls which are a known source of malware in the database however to truly optimize the system the cache should also contain commonly requested non malicious urls since this will help to reduce latency overall a further optimization may be possible for example with different caches for valid and invalid urls since depending on the source of the urls it may be more common for a url to be malicious or non malicious and therefore out compete those of the other type in the cache secondly given the system is already optimized my answer would be to load balance between distributed instances of the application runnning on different devices for example docker containers orchestrated by kubernetes what are some strategies you might use to update the service with new urls updates may be as many as 5000 urls a day with updates arriving every 10 minutes in my opinion the best way to handle these variably lengthed variably timed updates would be to receive them via api for the sake of the example i will assume they come from a trusted vetted source to mamiximize the system s optimization this update api could be decoupled from the previously defined lookup api to allow them to scale independently and without resource competition next steps and future improvements fully featured client allowing for user defined uploads queries unit testing decouple get and post apis into discrete microservices kubernetes manifests to help easily deploy at scale | cloud |
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Smart-Healthcare-System | smart healthcare system smart health system lamp stack how to run the code since it is dynamic web based system it requires to be hosted on a server i used localhost to host the system for localhost i am using wamp server follow the steps below to configure and run the code 1 create a new directory under wamp www and paste all the files from the root 2 start wamp server services 3 wait for the wamp server to change the icon color to green 4 open your browser preferably chrome 5 enter in the url 127 0 0 1 or localhost a localhost page will show up 6 either choose phpmyadmin manually or enter url 127 0 0 1 phpmyadmin 7 you will be directed to a database manager phpmyadmin it is used for creating and managing databases 8 click new and enter capstone in the create database field hit create 9 a new database must have been created and listed on the left click select it 10 on the right section of the manager click on the tab import 11 select the file capstone sql from the root directory 12 you have successfully completed the setup 13 enter this url in your browser 127 0 0 1 whatever you named your directiry in step 1 login php 14 enjoy | server |
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GuiaDesenvolvedoraWeb | o que o guia desenvolvedora web a name id1 a comece de onde voc est use o que voc tiver fa a o que voc puder arthur ashe fala devs tudo bem vulcan salute vim compartilhar com voc s como estou me tornando uma desenvolvedora front end dart decidi criar esse guia porque na internet existe muito conte do ao nosso dispor essa quantidade de material quando somos iniciantes muitas vezes pode nos confundir e at atrapalhar ao inv s de ajudar voc um colecionador de cursos https www youtube com watch v muqo8a1fdsm list plhz arehm4dk kke0ws7010x8 asu7twx index 1 o grande segredo para se tornar um bom programador deixar o imediatismo de lado e entender que seu c rebro vai precisar de tempo para absorver e entender as coisas se voc estiver fazendo algo e parecer que isso muito dif cil apenas pare reflita no pouco que conseguiu aprender sobre isso e volte mais tarde ou no outro dia voc ver que tudo quest o de ter paci ncia com o seu tempo natural de aprendizado e perceveran a nos estudos o que voc vai encontrar nesse guia a name id2 a cursos artigos v deos desafios id ias de projetos todo o material utilizado neste guia gratuito money with wings n o pule etapas o intuito desse guia justamente fornecer a ordem e um cronograma para seus estudos realize os exerc cios e desafios propostos rocket ndice o que o guia desenvolvedora web id1 o que voc vai encontrar nesse guia id2 como usar o guia id3 n o sinta que voc n o inteligente o suficiente id4 por que ser um programador id5 o que faz um programador front end id6 git e github id7 material de estudo git1 exercicios git2 desafios git3 html5 id8 material de estudo html1 exercicios html2 desafios html3 css3 id9 material de estudo css1 exercicios css2 desafios css3 design responsivo id10 material de estudo exercicios desafios logica de programa o id11 material de estudo exercicios desafios javascript id material de estudo exercicios desafios como usar esse guia books a name id3 a n o sinta que voc n o inteligente o 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tech https www youtube com watch v 1i8ylq4j ey the myth of the genius programmer https www youtube com watch v 0sarbwvhupq artigos ningu m simplesmente aprende a programar https www programaria org ninguem simplesmente aprende como programar programar n o requer talento ou paix o http kwan pt pt blog programar nao requer talento text 22o 20mito 20do 20 22programador 20g c3 a9nio 22 20 c3 a9 20extremamente 20perigoso text como 20resultado 2c 20os 20programadores 20t c3 aam enorme 20na 20qualidade 20de 20vida programar muito f cil https medium com julia maschion programar c3 a9 muito f c3 a1cil ddf610ca6f18 por que ser um programador desktop computer a name id5 a programa o uma linguagem assim como portugu s ou ingl s o idioma do computador mesmo que voc n o queira seguir uma carreira em tecnologia aprender a programar estimula o desenvolvimento de diversas habilidades abaixo listei alguns v deos e leituras que da aquele up pra come ar rocket v deos por que todos deveriam aprender a programar https www youtube com watch v mhw1hsqlp6a seja um programador https www youtube com watch v s9upnppgsgo como virar programador https www youtube com watch v r6ncg9gqcx0 artigos por que aprender a programar https recode org br por que aprender a programar por que dever amos saber programar mesmo se n o for trabalhar com isso https medium com codando por que deveriamos saber programar mesmo se n c3 a3o for trabalhar com isso d9ac0e900f7b o que faz um programador front end hippopotamus a name id6 a desenvolvimento web front end a pr tica de converter dados em uma interface gr fica atrav s do uso de html css e javascript para que os usu rios possam visualizar e interagir com esses dados wikipedia abaixo listei dois v deos para ajudar a entender o que faz um desenvolvedor front end o que um desenvolvedor front end https www youtube com watch v v0cn26 1d3i o que faz uma desenvolvedora front end https www youtube com watch v zy3 mfxvdew git e github trident a name id7 a bom finalmente depois de uma boa introdu o ao mundo da programa o chegamos ao primeiro curso espero que voc n o tenha pulado o cont udo acima triumph o primeiro curso deste guia o de git e github mas por qu antes de come ar de fato a criar projetos e aprender o conte do importante voc saber utilizar o git e como se comportar no github para tirar o maior proveito dessa rede e j come ar a demontrar suas habilidades para o mundo wink material de estudo a name git1 a video curso de git e github gr tis pratico e sem usar comandos no terminal https www youtube com playlist list plhz arehm4dm7zulpamadvnhh6vk9onza leitura slides https github com gustavoguanabara git github tree master slides aulas guia markdown https github com gustavoguanabara git github blob master manuais pdf guia markdown pdf a import ncia do github para desenvolvedores https willianjusten com br a importancia do github para desenvolvedores git e a import ncia de versionar um projeto https www hostgator com br blog git o sistema de controle como fazer um readme md bonit o https medium com raullesteves github como fazer um readme md bonit c3 a3o c85c8f154f8 exercicios a name git2 a crie sua conta no github https github com siga o meu perfil https github com milenacarecho d uma estrela no guia https github com milenacarecho guiadesenvolvedoraweb divulgue seu perfil https github com gustavoguanabara git github issues 3 desafios a name git3 a clone esse repositorio e utilize ele como cronograma a name id3 a html5 bone a name id8 a bom o que falar sobre nosso querido html5 html5 uma linguagem de marca o hipertexto utilizada para criar sites eu acho importante seguir a seguinte ordem para o estudo de html5 1 conhecer a internet e o funcionamento dela pra isso separei 3 videos do curso de html5 do curso em v deo e por l que voc come a 2 fazer o curso de html5 para iniciantes da nodestudio curso gratuido com certificado heart eyes 3 realizar os exerc cios e desafios 4 em paralelo realizar o curso de l gica de programa o id11 caso voc tenha alguma dificuldade na realiza o dos exerc cios consulte os documentos anexos no t pico leitura mag right tem muito conte do na internet de html5 muitos cursos gratuitos mas n o se prenda a eles a melhor forma de aprender colocando a m o na massa o curso linkado ja fornece a base necess ria para que voc aprenda a realizar suas buscas na documenta o da w3school ou na apostila de html relaxed material de estudo a name html1 a video hist ria da internet https www youtube com watch v rsfcvjr5yxc t 2s hist ria do html https www youtube com watch v nsmapcncsyi como funciona a internet https www youtube com watch v lmfez6xd0no t 3s curso de html5 para iniciantes https www nodestudio com br curso curso de html5 seo e meta tags sociais com html https www youtube com watch v yrglrfjh4fm html basics and good practices pt br https www youtube com watch v wi9jzjzysiy leitura entenda o que http https rockcontent com blog http como os navegadores funcionam https www 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desafio pra voc recomendo que reveja e procure mais sobre o tema para fixa o nerd face como funciona a internet o que http o que s o os navegadores e como eles funcionam o que dns e como ele funciona o que um nome de dominio o que hosting o que seo e como utilizar com html como ter acessibilidade com html exercicios a name html2 a exerc cio 01 https codepen io milenacarecho full pozrdme br clique aqui https github com gustavoguanabara html css blob master desafios d001 desafio mensagens pdf para mais informa es sobre o exerc cio 01 exerc cio 02 https github com milenacarecho guiadesenvolvedoraweb blob master cursos html5 exercicios exercicio2 png br clique aqui https github com gustavoguanabara html css blob master desafios d002 desafio imagens pdf para mais informa es sobre o exerc cio 02 exerc cio 03 https github com milenacarecho guiadesenvolvedoraweb blob master cursos html5 exercicios exercicio3 png br clique aqui https github com gustavoguanabara html css blob master desafios d003 desafio mapa mundi pdf para mais informa es sobre o exerc cio 03 exerc cio 04 https codepen io milenacarecho full onbyepl br clique aqui https github com gustavoguanabara html css blob master desafios d004 desafio emoji pdf para mais informa es sobre o exerc cio 04 exerc cio 05 br clique aqui https github com gustavoguanabara html css blob master desafios d005 desafio social pdf para mais informa es sobre o exerc cio 05 exerc cio 06 br clique aqui https github com gustavoguanabara html css blob master desafios d006 desafio tags pdf para mais informa es sobre o exerc cio 05 exerc cio 07 https codepen io milenacarecho full vweqdpq br clique aqui https github com milenacarecho guiadesenvolvedoraweb blob master cursos html5 exercicios exercicio7 pdf para mais informa es sobre o exerc cio 07 tente resolver o exercicio sozinha o n o v direto ao exercicio resolvido frowning face exercicio 01 resolvido https github com milenacarecho guiadesenvolvedoraweb tree master cursos html5 exerciciosresolvidos exercicio1 exercicio 02 resolvido https github com milenacarecho guiadesenvolvedoraweb tree master cursos html5 exerciciosresolvidos exercicio2 exercicio 03 resolvido https github com milenacarecho guiadesenvolvedoraweb tree master cursos html5 exerciciosresolvidos exercicio3 exercicio 04 resolvido https github com milenacarecho guiadesenvolvedoraweb tree master cursos html5 exerciciosresolvidos exercicio4 exercicio 05 resolvido https github com milenacarecho guiadesenvolvedoraweb tree master cursos html5 exerciciosresolvidos exercicio5 exercicio 06 resolvido https github com milenacarecho guiadesenvolvedoraweb tree master cursos html5 exerciciosresolvidos exercicio6 exercicio 07 resolvido https github com milenacarecho guiadesenvolvedoraweb tree html5 cursos html5 exerciciosresolvidos exercicio7 desafios a name html3 a n o vai ter desafios no m dulo html5 eu quis fazer o m dulo html mais curtinho porque melhor treinar ele com o complemento de css mas vou compensar isso colocando bastante desafios no m dulo css3 nerd face css3 nail care a name id a material de estudo a name css1 a video curso de css3 para iniciantes https www nodestudio com br curso curso de css3 leitura desafios a name css3 a desafio 30 dias de css https github com milenacarecho 30diasdecss desing responsivo a name id a material de estudo video curso de design responsivo https www nodestudio com br curso curso de design responsivo leitura logica de programa o a name id11 a material de estudo video leitura desafios javascript a name id a material de estudo video leitura desafios contribui o voc tem alguma sugest o de como podemos melhorar esse projeto em geral me informe gostaria muito de ouvir seus coment rios quaisquer contribui es s o muito apreciadas smile espalhe a palavra se as informa es deste reposit rio foram teis para voc de alguma forma certifique se de dar uma estrela dessa forma outras pessoas podem encontr lo e se beneficiar tamb m juntos podemos crescer e melhorar nossa comunidade | material-de-estudo web desenvolvimento-web web-development guia-de-estudo javascript css3 html5 | front_end |
CMPE243_EmbeddedSystem | sj2 c development environment an sj2 board is used at san jose state university sjsu to teach embedded systems courses part of this git repository also includes development environment for not just an arm controller but also support to compile and test software on your host machine such as windows mac etc the sample project of the sj2 board contains code written in c that anyone can understand easily it was designed to learn the low level workings of a microcontroller platform with an rtos project highlights fully implemented in c minimalistic design with little to no abstractions follows good coding principles such as yagni and dry infrastructure highlights supports mac linux windows out of the box version controlled toolchains and other supplementary tools no vms no wsl dependency on windows next steps build and flash project readme getting started md read more about scons readme scons md to figure out how to build projects videos we have made some videos that you may find useful comprehensive development environment https www youtube com watch v ebicummaim0 compile arm project https www youtube com watch v al0vkzvu8 build system we use scons https scons org as our build platform the developers of sj2 c applied experience of diverse set of build systems acquired over many years and resorted to this one the candidates were scons used at tesla and many other companies bazel used at google zoox and many other companies make scons discusses the advantages and disadvantages of other existing build systems build system comparison https github com scons scons wiki sconsvsotherbuildtools from experience we can state that bazel is really cool but hard to extend and problematic in windows scons dependencies are tricky but it is based on python and easy to understand and extend scons takes advantage of a python interpreter making it portable across multiple platforms mac linux windows history we wanted to build a strong foundational sample project for sj 2 development board that is used at sjsu originally preet created sj1 development board which meant that there was one development board across multiple classes at sjsu i was an enthusiast and created a hybrid project composed of c and c sources i love c a little more than c because i can express artistic designs in the language but a language is really a tool and you need to select the right tool for the job presently i work on embedded firmware code for automotive industry which is in c and software code in c because c is the right tool for firmware and c is the right tool for software sj2 original https github com kammce sjsu dev2 software was also designed by an enthusiast khalil who is a very talented person but expressing a starter project in c increased the complexity so much that many developers had a difficult time adopting it this is where the sj2 c was born which was completely re designed to write simple code that everyone could understand many students are new to programming and it was not expected that c would come naturally the code may appear less fancy but it is simple to understand and traceable with minimal abstractions the goal is to avoid designing yet another arduino platform there is no such thing as magic in the field of firmware engineering | os |
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Dissertation-Final | dissertation final python files main vf py main file to run the algorithm for mcgdm and fcs fcs py class with the fuzzy control system mcgdm py class with the mcgdm algorithm wellbeing py class with the variables and membership function for the variables monitored in wellbeing health py class with the variables and membership function for the variables monitored in health grid py file with which the grids for the final results is made matlab files health fis file with the rule set wb fis file with the rule set mf fis file used to print the mf examples graph wb m file to print the surface graphs for wellbeing graphmfunctions m file to print the output and input membership functions | os |
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Word-Cloud | word cloud test for our advanced data structure classes of our bachelor of business information technology of the university of applied sciences of neuch tel | server |
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serverless-cognitive | overview this guide will step you through deploying a multi part application which demonstrates using the serverless compute of azure functions combined with the pre built machine learning models of azure cognitive services with this application users can take photos using their phone and have these photos analysed using computer vision the results have a description of the image people s faces and also a set of tags the demo app stores this information and the results are dynamically updated displayed on a web page the system consists of four main parts camera web app two azure functions computer vision cognitive service viewer javascript webapp written in vue js architecture diagram of architecture docs diagram png framed application flow 0 user loads camera web app on mobile device via public url of an azure function and takes photo 1 image is http posted from camera app as base64 string back to same azure function 2 azure function decodes base64 data and stores resulting image in blob storage into photo in container 3 second azure function is triggered on a new blob arriving at photo in 4 function sends image to cognitive service api rest call and gets the json result 5 result is stored in photo out container as a blob of json 6 static html javascript viewer app polls photo out for new blobs and updates page dynamically by fetching and reading the json details are shown as overlays on the images such as the caption tags and location of faces using html5 canvas api example viewer results webapp demo docs demo png framed deployment setup the system requires a single function app storage account and cognitive services account using a consumption plan for the function app means the costs for deploying the system are extremely small deployment script a bash script deploy sh for fully automated deployment is provided in the etc directory this script will create everything and deploy all the functions code the default resource group is called demo serverlessvision and deploys to north europe you can modify the script to change these defaults to run the script you will need the azure cli installed and configured and either run the script locally under wsl bash or simply use the azure cloud shell step 1 go to shell azure com shell azure com and login step 2 run curl s https raw githubusercontent com benc uk serverless cognitive master etc deploy sh bash manual deployment all these steps use the azure portal and assume you already have an azure subscription 1 deploy a new azure function app using the portal click new compute function app pick any unique name for your app pick windows as the os opt to create a new resource group give it any name that you wish for the hosting plan select consumption plan for the runtime stack select javascript opt to create a new storage account and make a note of the name turn off application insights 2 deploy computer vision cognitive service click new ai machine learning computer vision you must pick west europe as the location and also f0 free as the pricing tier place in same resource group used for the function app once the computer vision cognitive service is deployed click into the resource and click on keys copy key 1 somewhere e g into a text file 3 deploy code to functions configure we will deploy the function code from the main source github repo https github com benc uk serverless cognitive click into your new function app from the portal you will be taken to the functions portal click platform features deployment options it is listed under code deployment click setup choose source external repository enter https github com benc uk serverless cognitive git as the url and the branch as master click ok it might take a few seconds but the view will refresh and you will see a tick indicating the code has deployed close the deployments view click the list of functions on the left side and two functions camerafunction and cognitivefunction should appear get the url of the camera app click on the camerafunction then click on get function url at the top copy this url somewhere as you will need to open it on your mobile creating a short link or sending it over to your phone as a message email will save you typing it in configure the functions to access your cognitive service return to the function app level view by clicking on the function app name with the yellow lighting bolt icon on the left click on overview tab in the top of the function portal and into application settings scroll down click add new setting call the setting vision api key and paste the key you copied previously as the value remember to scroll back up click save 4 setup blob storage return to the resource group you can do this via the breadcrumb trail at the top of the portal view click into the storage account that was created in step 1 with the function app click on blob service browse blobs click container call it photo in and set the access level to blob click container call it photo out and set the access level to container click on blob service cors and click add set the rule up with asterisk no quotes for allowed origins allowed headers and exposed headers select get as the allowed verbs and leave the max age as 0 usage open the camera web app on your phone using the url you got earlier it will be of the form https function app name azurewebsites net api camerafunction tap the button icon to take a photo or pick existing photo on your device and upload to azure triggering the whole flow described above open the viewer the viewer is currently hosted publicly on github pages http code benco io serverless cognitive viewer if you have cloned or downloaded the source repo https github com benc uk serverless cognitive just open viewer index html locally in your browser you will need to point the viewer at your storage account so enter your storage account name and click ok note the viewer automatically fetches new photos every 10 seconds and displays them so do not reload or refresh the page viewer if you want to host the viewer yourself in azure you can upload the viewer folder of this repo to blob storage give the container anonymous access and load the pages using the blob endpoint url e g https mystoreaccount blob core windows net viewer index html create an azure app service web app and upload the contents of the viewer folder to the root of your web app design notes being a demo app certain design choices were made that cut corners in order to simplify things using azure functions to return html pages is generally not a recommended use case as there are better ways to achieve that in azure web apps storage static sites etc storing json in blobs isn t optimal and something such as table storage or even cosmos db represents a better fit however the advantage of blobs is the option of anonymous access which simplifies viewing the results change log aug 2018 complete re design functions rewritten in node js for use with functions v2 viewer app rewritten in vue js | cognitive-services serverless azure-functions computer-vision | ai |
Music-Emotion-Recognition | music emotion recognition a video explanation of the repo and research problem domain https youtu be 5b5unjdikpo introduction the study of music and emotion seeks to understand the psychological relationship between human affect and music it is a branch of music psychology with numerous areas of study including the nature of emotional reactions to music how characteristics of the listener may determine which emotions are felt and which components of a musical composition or performance may elicit certain reactions 1 approach there exists 3 approaches to solve this problem thayers emotional model dataset annotation by music and emotion psychologist experts classification based on tags generated by the song results can be improved by weighting music lyrics music genre visualizations plukchik wheel of emotion plutchickwheelofemotion https upload wikimedia org wikipedia commons thumb c ce plutchik wheel svg 250px plutchik wheel svg png basic emotion wheel basicemotionwheel https upload wikimedia org wikipedia commons thumb 8 8d emotions 3 png 220px emotions 3 png 2d grid representation of emotion labels 2dgrid https upload wikimedia org wikipedia en thumb 6 62 two dimensions of emotion gif jpg 220px two dimensions of emotion gif jpg reference 1 wikipedia music and emotion https en wikipedia org wiki music and emotion 2 wikipedia emotion https en wikipedia org wiki emotion | machine-learning data-science feature-extraction feature-selection feature-scaling music-information-retrieval digital-signal-processing librosa | ai |
bolero | bolero build status https github com camshaft bolero workflows ci badge svg https github com camshaft bolero actions workflow ci latest version https img shields io crates v bolero svg https crates io crates bolero documentation https docs rs bolero badge svg https docs rs bolero license https img shields io crates l bolero svg https github com camshaft bolero blob master license fuzz and property testing front end for rust book a copy of the bolero book can be found here http camshaft github io bolero quick start 1 install subcommand and add a dependency console cargo add dev bolero cargo install f cargo bolero 2 write a test using bolero check https docs rs bolero latest bolero macro check html macro rust pub fn buggy add x u32 y u32 u32 if x 12976 y 14867 return x wrapping sub y return x wrapping add y test fn fuzz add bolero check with type cloned for each a b buggy add a b a wrapping add b 3 run the test with cargo bolero console cargo bolero test fuzz add some moments later test failure input 12976 14867 error test returned false linux installation cargo bolero needs a couple of libraries installed to compile if these libraries aren t available the requirement can be relaxed by executing cargo install cargo bolero no default features f debian ubuntu bash sudo apt install binutils dev libunwind dev | fuzz fuzz-testing property-testing libfuzzer honggfuzz afl | front_end |
ontology | h1 align center ontology h1 h4 align center version 2 2 0 bin 1 13 0 lib h4 godoc https godoc org github com ontio ontology status svg https godoc org github com ontio ontology go report card https goreportcard com badge github com ontio ontology https goreportcard com report github com ontio ontology travis https travis ci com ontio ontology svg branch master https travis ci com ontio ontology discord https img shields io discord 102860784329052160 svg https discord gg gdkucaq english readme cn md welcome to the official go implementation of the ontology https ont io blockchain ontology is a high performance public blockchain project and distributed trust collaboration platform it is highly customizable and suitable for all kinds of business requirements the ontology mainnet was launched on june 30th 2018 as a public blockchain project ontology is currently maintained by both the ontology core tech team and community members who can all support you in development there are many available tools for use for development sdks the smartx ide ontology blockchain explorer and more new features are still being rapidly developed therefore the master branch may be unstable stable versions can be found in the releases section https github com ontio ontology releases features scalable lightweight universal smart contracts scalable wasm contract support cross chain interactive protocol multiple encryption algorithms supported highly optimized transaction processing speed p2p link layer encryption optional module multiple consensus algorithms supported vbft dbft rbft sbft pow quick block generation time 1 30 seconds install from binaries you can download a stable compiled version of the ontology node software by either downloading the latest ontology binary file with curl https dev ont io ontology install sh downloading a specific version from the release section https github com ontio ontology releases build from source prerequisites golang https golang org doc install version 1 15 or later build note that the code in the master branch may not be stable git clone https github com ontio ontology git cd ontology make all after building the source code successfully you should see two executable programs ontology the primary ontology node application and cli tools sigsvr the ontology signature server sigsvr an rpc server for signing transactions detailed documentation can be found here https github com ontio documentation blob master docs pages doc en ontology sigsvr en md run ontology the ontology cli can run nodes for the mainnet testnet and local privatenet check out the ontology cli user guide https github com ontio ontology blob master docs specifications cli user guide md for a full list of commands mainnet sync node you can run an ontology mainnet node built from the source code with shell ontology linux ontology darwin amd64 macos start ontology windows amd64 exe windows testnet sync node you can run an ontology testnet node built from the source code with shell ontology networkid 2 linux ontology darwin amd64 networkid 2 macos start ontology windows amd64 exe networkid 2 windows local privatenet the ontology cli allows you to run a local privatenet on your computer before you can run the privatenet you will need to create a wallet file a wallet file named wallet dat can be generated by running shell ontology account add d to start the privatenet built from the source code with shell ontology testmode linux ontology darwin amd64 testmode macos start ontology windows amd64 exe testmode windows here s an example of the directory structure shell tree ontology ontology wallet dat run with docker you can run the ontology node software with docker 1 setup docker compose on your computer you will need the latest version of docker compose https docs docker com compose install 2 make a docker image in the root directory of the source code run make docker to make an ontology image 3 run the ontology image run the command docker run ontio ontology to start ontology run the command docker run ti ontio ontology to start ontology and allow interactive keyboard input if you need to keep the data generated by the image refer to docker s data persistence function you can add arguments to the ontology command such as with docker run ontio ontology networkid 2 examples ont transfer sample from transfer from to transfer to amount ont amount shell ontology asset transfer from arvvxbpgysl56cvsswfjrvvyzypnz7zp48 to aace8nvkmrabnp5ygejyz9e5kycxks2uce amount 10 if the asset transfer is successful the result will display as follows shell transfer ont from arvvxbpgysl56cvsswfjrvvyzypnz7zp48 to aace8nvkmrabnp5ygejyz9e5kycxks2uce amount 10 txhash 437bff5dee9a1894ad421d55b8c70a2b7f34c574de0225046531e32faa1f94ce txhash is the transfer transaction hash and we can query a transfer result by the txhash due to block time the transfer transaction will not be executed before the block is generated and added if you want to transfer ong just add asset ong flag note that ont is an integer and has no decimals whereas ong has 9 decimals for detailed info please read everything you need to know about ong https medium com ontologynetwork everything you need to know about ong 582ed216b870 shell ontology asset transfer from arvvxbpgysl56cvsswfjrvvyzypnz7zp48 to arvvxbpgysl56cvsswfjrvvyzypnz7zp48 amount 95 479777254 asset ong if transfer of the asset succeeds the result will display as follows shell transfer ong from arvvxbpgysl56cvsswfjrvvyzypnz7zp48 to aace8nvkmrabnp5ygejyz9e5kycxks2uce amount 95 479777254 txhash e4245d83607e6644c360b6007045017b5c5d89d9f0f5a9c3b37801018f789cc3 please note when you use the address of an account you can use the index or label of the account instead index is the sequence number of a particular account in the wallet the index starts from 1 and the label is the unique alias of an account in the wallet shell ontology asset transfer from 1 to 2 amount 10 query transfer status sample shell ontology info status txhash for example shell ontology info status 10dede8b57ce0b272b4d51ab282aaf0988a4005e980d25bd49685005cc76ba7f result shell transaction transfer success from axkdgfr9theqwmckpttqyaazjrwqzh48ec to ayitoldt2yzuns3pziexcdtpyc5vwqmfan amount 10 query account balance sample shell ontology asset balance address index label for example shell ontology asset balance arvvxbpgysl56cvsswfjrvvyzypnz7zp48 or shell ontology asset balance 1 result shell balanceof arvvxbpgysl56cvsswfjrvvyzypnz7zp48 ont 989979697 ong 28165900 for further examples please refer to the cli user guide https ontio github io documentation cli user guide en html contributions contributors to ontology are very welcome before beginning please take a look at our contributing guidelines contributing md you can open an issue by clicking here https github com ontio ontology issues new if you have any issues getting setup open an issue or reach out in the ontology discord https discordapp com invite 4tqujhj license the ontology source code is available under the lgpl 3 0 license license | ontology blockchain distributed-ledger golang high-performance | blockchain |
ComputerVision | computer vision uiuc hitcount http hits dwyl io namanuiuc https githubcom namanuiuc computervision svg http hits dwyl io namanuiuc https githubcom namanuiuc computervision this project contains detailed computer vision techiniques the lecture slides and assignments are from cs543 uiuc spring 2018 http slazebni cs illinois edu spring18 instructor svetlana lazebnik slazebni at illinois edu p align center img width 50 height 50 src utils logo png p overview in the simplest terms computer vision is the discipline of teaching machines how to see this field dates back more than fifty years but the recent explosive growth of digital imaging and machine learning technologies makes the problems of automated image interpretation more exciting and relevant than ever there are two major themes in the computer vision literature 3d geometry and recognition the first theme is about using vision as a source of metric 3d information given one or more images of a scene taken by a camera with known or unknown parameters how can we go from 2d to 3d and how much can we tell about the 3d structure of the environment pictured in those images the second theme by contrast is all about vision as a source of semantic information can we recognize the objects people or activities pictured in the images and understand the structure and relationships of different scene components just as a human would this course will provide a coherent perspective on the different aspects of computer vision and give students the ability to understand state of the art vision literature and implement components that are fundamental to many modern vision systems prerequisites basic knowledge of probability linear algebra and calculus matlab programming experience and previous exposure to image processing are highly desirable syllabus 1 image formation and low level vision 1 camera models 2 light and color 3 linear filters and edges 4 feature extraction 5 optical flow and feature tracking 2 grouping and fitting 1 hough transform 2 ransac 3 alignment image stitching 3 geometric vision 1 camera calibration 2 epipolar geometry 3 two view and multi view stereo 4 structure from motion 4 recognition and beyond 1 statistical learning framework 2 image classification 3 deep convolutional neural networks 4 object detection 5 segmentation course content db i have create a database to download the lecture materials from the course to download the material git clone https github com namanuiuc computervision git cd computervision bash course material db sh demo p align center img width 50 height 50 src utils db png p machine problems colorizing prokudin gorskii images of the russian empire src 1 colorizing prokudin gorskii images of the russian empire background sergei mikhailovich prokudin gorskii http en wikipedia org wiki prokudin gorskii 1863 1944 was a photographer who between the years 1909 1915 traveled the russian empire and took thousands of photos of everything he saw he used an early color technology that involved recording three exposures of every scene onto a glass plate using a red green and blue filter back then there was no way to print such photos and they had to be displayed using a special projector prokudin gorskii left russia in 1918 his glass plate negatives survived and were purchased by the library of congress in 1948 today a digitized version of the prokudin gorskii collection is available online http www loc gov exhibits empire gorskii html p align center img width 50 height 50 src utils outs 1 colorizing prokudin gorskii images of the russian empire collage 6 jpg p overview the goal of this assignment is to learn to work with images by taking the digitized prokudin gorskii glass plate images and automatically producing a color image with as few visual artifacts as possible in order to do this you will need to extract the three color channel images place them on top of each other and align them so that they form a single rgb color image some starter matlab code is available here http slazebni cs illinois edu spring18 assignment0 sample code m though you are not required to use it shape from shading src 2 shape from shading overview the goal of this assignment is to implement shape from shading as described in lecture 4 see also section 2 2 4 of forsyth ponce 2nd edition 1 download the sample code and data http slazebni cs illinois edu spring18 assignment1 assignment1 materials zip the data in the croppedyale directory consists of 64 images each of four subjects from the yale face database http www cad zju edu cn home dengcai data facedata html the light source directions are encoded in the file names the code consists of several m functions your task will be to add some code to the top level script run me m and to fill in the code in photometric stereo m and get surface m as explained below the remaining files are utilities to load the input data and display the output 2 for each subject subdirectory in croppedyale read in the images and light source directions this is accomplished by the function loadfaceimages m provided in the zip file which in turn calls getpgmraw m to read the pgm files loadfaceimages returns the images for the 64 light source directions and an ambient image i e image taken with all the light sources turned off 3 preprocess the data subtract the ambient image from each image in the light source stack set any negative values to zero rescale the resulting intensities to between 0 and 1 they are originally between 0 and 255 hint these operations can be done without using any loops whatsoever you may want to look into matlab s bsxfun function 4 estimate the albedo and surface normals for this you need to fill in code in photometric stereo m which is a function taking as input the image stack corresponding to the different light source directions and the matrix of of the light source directions and returning an albedo image and surface normal estimates the latter should be stored in a three dimensional matrix that is if your original image dimensions are h x w the surface normal matrix should be h x w x 3 where the third dimension corresponds to the x y and z components of the normals to solve for the albedo and the normals you will need to set up a linear system as shown in slide 20 of lecture 4 hints to get the least squares solution of a linear system use matlab s backslash operator that is the solution to ax b is given by x a b if you directly implement the formulation of slide 20 of the lecture you will have to loop over every image pixel and separately solve a linear system in each iteration there is a way to get all the solutions at once by stacking the unknown g vectors for every pixel into a 3 x npix matrix and getting all the solutions with a single application of the backslash operator you will most likely need to reshape your data in various ways before and after solving the linear system useful matlab functions for this include reshape and cat you may also need to use element wise operations for example for two equal size matrices x and y x y multiplies corresponding elements and x 2 squares every element as before bsxfun can also be a very useful function here 5 compute the surface height map by integration the method is shown in slide 23 of lecture 4 except that instead of continuous integration of the partial derivatives over a path you will simply be summing their discrete values your code implementing the integration should go in the get surface m file as stated in the slide to get the best results you should compute integrals over multiple paths and average the results you should implement the following variants of integration 1 integrating first the rows then the columns that is your path first goes along the same row as the pixel along the top and then goes vertically down to the pixel it is possible to implement this without nested loops using the cumsum function 2 integrating first along the columns then the rows 3 average of the first two options 4 average of multiple random paths for this it is fine to use nested loops you should determine the number of paths experimentally 6 display the results using functions display output and plot surface normals included in the zip archive p align center img width 250 height 250 src utils 3dface gif p blob detector src 3 scale space blob detection overview the goal of the assignment is to implement a laplacian blob detector as discussed in the this lecture http slazebni cs illinois edu spring18 lec09 sift pptx algorithm outline 1 generate a laplacian of gaussian filter 2 build a laplacian scale space starting with some initial scale and going for n iterations 1 filter image with scale normalized laplacian at current scale 2 save square of laplacian response for current level of scale space 3 increase scale by a factor k 3 perform nonmaximum suppression in scale space 4 display resulting circles at their characteristic scales p align center img width 50 height 50 src utils mp3 1 gif p test images here are four images http slazebni cs illinois edu spring18 assignment2 assignment2 images zip to test your code and sample output images http slazebni cs illinois edu spring18 assignment2 assignment2 sample output zip for your reference keep in mind though that your output may look different depending on your threshold range of scales and other implementation details in addition to the images provided also run your code on at least four images of your own choosing p align center img width 75 height 75 src utils mp3 2 jpg p robust estimation and geometric vision src 4 robust estimation and geometric vision the goal of this assignment is to implement robust homography and fundamental matrix estimation to register pairs of images as well as attempt triangulation and single view 3d measurements overview this assignment is divided into 3 parts contents 1 stitching pairs of images 2 fundamental matrix estimation and triangulation 3 single view geometry part 1 stitching pairs of images python code here and in part 2 by lavisha aggarwal the first step is to write code to stitch together a single pair of images for this part you will be working with a pair of images given 1 load both images convert to double and to grayscale 2 detect feature points in both images we provide harris detector code you can use matlab http slazebni cs illinois edu spring18 harris m python http slazebni cs illinois edu spring18 assignment3 harris py or feel free to use the blob detector you wrote for assignment 2 3 extract local neighborhoods around every keypoint in both images and form descriptors simply by flattening the pixel values in each neighborhood to one dimensional vectors experiment with different neighborhood sizes to see which one works the best if you re using your laplacian detector use the detected feature scales to define the neighborhood scales optionally feel free to experiment with sift descriptors matlab here is some basic code http slazebni cs illinois edu spring18 assignment3 find sift m for computing sift descriptors of circular regions such as the ones returned by the detector from assignment 2 python you can use the opencv library to extract keypoints through the function cv2 xfeatures2d sift create detect and compute descripters through the function cv2 xfeatures2d sift create compute this tutorial https docs opencv org 3 1 0 da df5 tutorial py sift intro html provides details about using sift in opencv 4 compute distances between every descriptor in one image and every descriptor in the other image in matlab you can use this code http slazebni cs illinois edu spring18 assignment3 dist2 m for fast computation of euclidean distance in python you can use scipy spatial distance cdist x y sqeuclidean for fast computation of euclidean distance if you are not using sift descriptors you should experiment with computing normalized correlation or euclidean distance after normalizing all descriptors to have zero mean and unit standard deviation 5 select putative matches based on the matrix of pairwise descriptor distances obtained above you can select all pairs whose descriptor distances are below a specified threshold or select the top few hundred descriptor pairs with the smallest pairwise distances 6 run ransac to estimate a homography mapping one image onto the other report the number of inliers and the average residual for the inliers squared distance between the point coordinates in one image and the transformed coordinates of the matching point in the other image also display the locations of inlier matches in both images 7 warp one image onto the other using the estimated transformation to do this in matlab you will need to learn about maketform and imtransform functions in python use skimage transform projectivetransform and skimage transform warp 8 create a new image big enough to hold the panorama and composite the two images into it you can composite by simply averaging the pixel values where the two images overlap your result should look something like this but hopefully with a more precise alignment p align center img width 50 height 50 src utils mp4 1 jpg p to checkout about the extra credit work and instructions here http slazebni cs illinois edu spring18 assignment3 html part 2 fundamental matrix estimation and triangulation download http slazebni cs illinois edu spring18 assignment3 assignment3 part2 data zip full size images matching points camera matrices and matlab sample code python sample code can be found here http slazebni cs illinois edu spring18 assignment3 part2 sample code python py 1 load the image pair and matching points file see sample code in the data file 2 fit a fundamental matrix to the matching points use the sample code provided to visualize the results implement both the normalized and the unnormalized algorithms see this lecture http slazebni cs illinois edu spring18 lec16 epipolar pptx for the methods in each case report your residual or the mean squared distance in pixels between points in both images and the corresponding epipolar lines 3 now use your putative match generation and ransac code from part 1 to estimate fundamental matrices without ground truth matches for this part only use the normalized algorithm report the number of inliers and the average residual for the inliers in your report compare the quality of the result with the one you get from ground truth matches 4 load the 3x4 camera matrices for the two images in matlab they can be loaded with the load command i e p1 load house1 camera txt in python use p1 numpy loadtxt house1 camera txt find the centers of the two cameras use linear least squares to triangulate the position of each matching pair of points given the two cameras see this lecture http slazebni cs illinois edu spring18 lec14 calibration pptx for the method display the two camera centers and reconstructed points in 3d also report the residuals between the observed 2d points and the projected 3d points in the two images note you do not need the camera centers to solve the triangulation problem they are used just for the visualization note 2 it is sufficient to only use the provided ground truth matches for this part but if you wish feel free to also generate and compare results with the inlier matches you have found in 3 above tips and details for fundamental matrix estimation don t forget to enforce the rank 2 constraint this can be done by taking the svd of f setting the smallest singular value to zero and recomputing f lecture 16 http slazebni cs illinois edu spring18 lec16 epipolar pptx shows two slightly different linear least squares setups for estimating the fundamental matrix one involves a homogeneous system and one involves a non homogeneous system you may want to compare the two and determine which one is better in terms of numerics recall that the camera centers are given by the null spaces of the matrices they can be found by taking the svd of the camera matrix and taking the last column of v for triangulation with linear least squares it is not necessary to use data normalization in my implementation normalization made very little difference for this part in matlab plotting in 3d can be done using the plot3 command use the axis equal option to avoid automatic nonuniform scaling of the 3d space in python use the axes3d function from mpl toolkits mplot3dplot3 library to show the structure clearly you may want to include snapshots from several viewpoints in the past some students have also been able to produce animated gif s and those have worked really well p align center img width 50 height 50 src utils mp4 2 gif p part 3 single view geometry adapted from derek hoiem by tom paine python code by hsiao ching chang 1 you will be working with the above image of the north quad save it to get the full resolution version first you need to estimate the three major orthogonal vanishing points use at least three manually selected lines to solve for each vanishing point this matlab code http slazebni cs illinois edu spring18 assignment3 getvanishingpoint shell m and this python code http slazebni cs illinois edu spring18 assignment3 assignment3 part3 ipynb provide an interface for selecting and drawing the lines but the code for computing the vanishing point needs to be inserted for details on estimating vanishing points see derek hoiem s book chapter http slazebni cs illinois edu spring16 3dscene book svg pdf section 4 you should also refer to this chapter and the single view metrology lecture http slazebni cs illinois edu spring18 lec15 single view pptx for details on the subsequent steps in your report you should plot the vps and the lines used to estimate them on the image plane using the provided code specify the vp pixel coordinates plot the ground horizon line and specify its parameters in the form a x b y c 0 normalize the parameters so that a 2 b 2 1 2 using the fact that the vanishing directions are orthogonal solve for the focal length and optical center principal point of the camera show all your work 3 compute the rotation matrix for the camera setting the vertical vanishing point as the y direction the right most vanishing point as the x direction and the left most vanishing point as the z direction 4 estimate the heights of a the csl building b the spike statue and c the lamp posts assuming that the person nearest to the spike is 5ft 6in tall in the report show all the lines and measurements used to perform the calculation how do the answers change if you assume the person is 6ft tall p align center img width 100 height 100 src utils mp4 3 jpg p | computer-vision vision image-classification image-processing | ai |
spike-rt | build https github com spike rt spike rt workflows build badge svg branch main https github com spike rt spike rt workflows build badge svg branch main for japanese document please see readme ja md readme ja md readme ja md readme ja md warning this is still pre release and unstable breaking changes maybe introduced without notifications spike rt an rtos based software platform for lego education spike prime https education lego com en us products lego education spike prime set 45678 spike e2 84 a2 prime features toppers asp3 real time operating system a itron like rtos c programming environment supported device hub 5x5 led matrix display single led button gyro sensor speaker battery charging usb serial bluetooth pup device angular motor color sensor ultrasonic sensor force sensor flash application by usb dfu api asp3 api toppers asp3 is an implementation of the toppers 3rd generation kernel itron based specification an extension of the itron4 0 specification sorry but the api document is japanaese https www toppers jp docs tech tgki spec 350 pdf only for now for english reference itron 4 0 document http www ertl jp itron spec file mitron 400e pdf the base of the toppers specification may be helpful c standard library newlib spike api an api for controlling device from applications see the document https spike rt github io spike rt en html modules html usage for more information see docs en docs en contribution see docs en contributing md docs en contributing md language both english and japanese are available on github | lego-spike asp3 toppers | os |
full-blockchain-solidity-course-py | big update new sepolia faucet located here https sepoliafaucet com kovan ropsten and rinkeby have been deprecated goerli still works but we highly recommend sepolia as its proof of stake based you ll need to verify via twitter to get eth link you can find backup faucets here https docs chain link docs link token contracts goerli additionally lesson 7 uses chainlink vrf v1 instead of v2 you can find the docs for chainlink vrfv1 here https docs chain link vrf v1 examples get a random number youtube video https www youtube com watch v m576wgidbdq br p align center a href https www youtube com watch v m576wgidbdq target blank img src img youtube thumbnail jpeg width 350 alt solidity blockchain and smart contract course beginner to expert python tutorial a p br welcome to the repository for the ultimate solidity blockchain and smart contract beginner to expert full course python edition freecodecamp course table of contents table of contents table of contents resources for this course resources for this course questions questions windows support windows support hiccups issues from the video hiccupsissues from the video lesson 0 welcome to blockchain lesson 0 welcome to blockchain what is a blockchain what is a blockchain making your first transaction making your first transaction how do blockchains work how do blockchains work consensus consensus the future the future miscellaneous miscellaneous lesson 1 welcome to remix simple storage lesson 1 welcome to remix simple storage everything in this section can be read about in the solidity documentation everything in this section can be read about in the solidity documentation remix remix basic solidity basic solidity deploying to a live network deploying to a live network lesson 2 storage factory lesson 2 storage factory inheritance factory pattern and interacting with external contracts inheritance factory pattern and interacting with external contracts lesson 3 fund me lesson 3 fund me payable msg sender msg value units of measure payable msgsender msgvalue units of measure chainlink oracles chainlink oracles importing from npm and advanced solidity importing from npm and advanced solidity lesson 4 web3 py simple storage lesson 4 web3py simple storage installing vscode python and web3 installing vscode python and web3 our first python script with web3 py deploying a contract our first python script with web3py deploying a contract interacting with our contract in python web3 py interacting with our contract in python web3py lesson 5 brownie simple storage lesson 5 brownie simple storage brownie introduction brownie introduction installing brownie installing brownie brownie simple storage project brownie simple storage project testing basics testing basics brownie console brownie console lesson 6 brownie fund me lesson 6 brownie fund me introduction introduction dependencies deploying and networks dependencies deploying and networks funding and withdrawing python scripts funding and withdrawing python scripts testing across networks testing across networks git git compatibility with ganache ui compatibility with ganache ui lesson 7 smartcontract lottery lesson 7 smartcontract lottery introduction introduction 1 lottery sol lotterysol testing lottery sol testing lotterysol lottery sol testnet deployment lotterysol testnet deployment lesson 8 chainlink mix lesson 8 chainlink mix brownie mixes brownie mixes lesson 9 erc20s eips and token standards lesson 9 erc20s eips and token standards lesson 10 defi aave lesson 10 defi aave defi intro defi intro aave ui aave ui programmatic interactions with aave programmatic interactions with aave testing testing lesson 11 nfts lesson 11 nfts non technical explainer non technical explainer simple nft simple nft simplecollectible testing simplecollectible testing advanced nft advanced nft advanced deploy and create advanced deploy and create creating metadata ipfs creating metadata ipfs lesson 12 upgrades lesson 12 upgrades introduction to upgrading smart contracts introduction to upgrading smart contracts upgrades mix and code upgrades mix and code testing upgrades testing upgrades upgrades on a testnet upgrades on a testnet bonus lesson 13 full stack defi bonus lesson 13 full stack defi defi stake yield brownie scripts tests defi stake yield brownie scripts tests testing our defi stake yield brownie dapp testing our defi stake yield brownie dapp front end full stack front end full stack closing and summary closing and summary security security where do i go now where do i go now learning more learning more community community hackathons hackathons vyper vyper resources for this course questions github discussions https github com smartcontractkit full blockchain solidity course py discussions ask questions and chat about the course here stack exchange ethereum https ethereum stackexchange com great place for asking technical questions about ethereum stackoverflow https stackoverflow com great place for asking technical questions overall windows support setup your windows environment https medium com cromewar how to setup windows 10 11 for smart contract development and brownie e7d8d13555b3 learn how to install all the tools you will need for this course on a windows machine hiccups issues from the video chronological issues from the video https github com smartcontractkit full blockchain solidity course py blob main chronological issues from video md a list of known hiccups issues you may encounter while implementing the content from the video lesson 0 welcome to blockchain what is a blockchain bitcoin whitepaper https bitcoin org bitcoin pdf ethereum whitepaper https ethereum org en whitepaper hybrid smart contracts https blog chain link hybrid smart contracts explained blockchain oracles https betterprogramming pub what is a blockchain oracle f5ccab8dbd72 source friends link sk d921a38466df8a9176ed8dd767d8c77d what is a blockchain https www investopedia com terms b blockchain asp making your first transaction metamask https metamask io etherscan https etherscan io goerli etherscan https goerli etherscan io kovan etherscan https kovan etherscan io goerli faucet https faucets chain link goerli sepolia faucet https sepoliafaucet com sepolia etherscan https sepolia etherscan io rinkeby faucet check the link token contracts page https docs chain link docs link token contracts rinkeby note you can always find the most up to date faucets at faucets chain link https faucets chain link or use the kovan eth faucet https faucets chain link just be sure to swap your metamask to kovan gas and gas fees https ethereum org en developers docs gas wei gwei and ether converter https eth converter com eth gas station https ethgasstation info how do blockchains work blockchain demo https andersbrownworth com blockchain public private keys https andersbrownworth com blockchain public private keys keys layer 2 and rollups https ethereum org en developers docs scaling layer 2 rollups decentralized blockchain oracles https blog chain link what is the blockchain oracle problem block rewards https www investopedia com terms b block reward asp run your own ethereum node https geth ethereum org docs getting started consensus consensus https wiki polkadot network docs learn consensus proof of stake https ethereum org en developers docs consensus mechanisms pos proof of work https ethereum org en developers docs consensus mechanisms pow nakamoto consensus https blockonomi com nakamoto consensus the future ethereum 2 https ethereum org en eth2 miscellaneous daos https www investopedia com tech what dao lesson 1 welcome to remix simple storage https github com patrickalphac simple storage code https github com patrickalphac simple storage everything in this section can be read about in the solidity documentation https docs soliditylang org en v0 8 6 index html remix https remix ethereum org basic solidity versioning compiling contract declaration types declaring variables https docs soliditylang org en v0 8 6 types html uint256 int256 bool string address bytes32 default initializations comments functions deploying a contract calling a public state changing function visibility https docs soliditylang org en v0 7 3 contracts html visibility and getters scope view pure functions structs intro to storage arrays dynamic fixed sized compiler errors and warnings memory mappings spdx license recap deploying to a live network a testnet or mainnet find a faucet here https faucets chain link connecting metamask interacting with deployed contracts the evm lesson 2 storage factory https github com patrickalphac storage factory code https github com patrickalphac storage factory inheritance factory pattern and interacting with external contracts factory pattern imports deploy a contract from a contract interact with a deployed contract recap lesson 3 fund me https github com patrickalphac fund me code https github com patrickalphac fund me payable msg sender msg value units of measure payable wei gwei eth converter https eth converter com msg sender msg value chainlink oracles decentralized oracle network chainlink blockchains can t make api calls centralized nodes are points of failure data chain link https data chain link getting external data with chainlink oracles chainlink https docs chain link faucets and contract addresses https docs chain link docs link token contracts kovan https docs chain link docs link token contracts kovan getting price information https docs chain link docs get the latest price importing from npm and advanced solidity decimals floating point numbers in solidity latestrounddata importing from npm in remix interfaces introduction to abis getting price feed addresses https docs chain link docs reference contracts getprice tuples unused tuple variables matching units wei gwei eth getconversionrate matching units continued safemath integer overflow using keyword libraries https docs soliditylang org en v0 8 6 contracts html libraries safemath psa setting a threshold require revert withdraw function transfer balance this contract owners constructor modifiers resetting for loop array length forcing a transaction recap lesson 4 web3 py simple storage https github com patrickalphac web3 py simple storage code https github com patrickalphac web3 py simple storage installing vscode python and web3 developer bootcamp setup instructions metamask vscode python nodejs https chain link bootcamp brownie setup instructions vscode https code visualstudio com download vscode crash course https www youtube com watch v wpqxp klzpo extensions short cuts vscode shortcuts https code visualstudio com docs getstarted keybindings vscode macos shortcuts https code visualstudio com shortcuts keyboard shortcuts macos pdf python https www python org downloads install troubleshooting terminal making a directory folder opening the folder up with vscode creating a new file syntax highlights remember to save setting linting compile version vscode solidity settings formatting format on save solidity prettier python black https pypi org project black pip https pypi org project pip our first python script with web3 py deploying a contract reading our solidity file running a python script in the terminal maxos shortcuts https code visualstudio com shortcuts keyboard shortcuts macos pdf windows shortcuts https code visualstudio com shortcuts keyboard shortcuts windows pdf linux shortcuts https code visualstudio com shortcuts keyboard shortcuts linux pdf compiling in python py solc x https pypi org project py solc x compile standard colorized brackets json abi saving compiled code formatting json deploying in python 1 get bytecode 2 get abi 3 choose blockchain to deploy to local ganache chain ganache ui https www trufflesuite com ganache ganache command line https github com trufflesuite ganache cli web3 py https web3py readthedocs io en stable http rpc provider private keys must start with 0x contract object building a transaction account nonce calling constructor transaction parameters signing the transaction never put your private key directly in your code setting environment variables windows linux macos https www twilio com blog 2017 01 how to set environment variables html more on windows environment variables https www youtube com watch v tqwdiu8a4gc t 40s exported environment variables only last the duration of the shell terminal private key psa env file gitignore loading env file in python python dotenv https pypi org project python dotenv viewing our transaction deployment in ganache waiting for block confirmations interacting with our contract in python web3 py 2 things you always need 1 contract address 2 contract abi getting address from transaction receipt calling a view function with web3 py call vs transact updating state with web3 py ganache cli https github com trufflesuite ganache cli installing ganache install nodejs https nodejs org en install yarn https classic yarnpkg com en docs install working with ganache cli open a new terminal in the same window deploying to a testnet infura https infura io alchemy https www alchemy com using infura rpc url http provider chain ids https chainlist org wow this seems like a lot of work is there a better way lesson 5 brownie simple storage https github com patrickalphac brownie simple storage code https github com patrickalphac brownie simple storage brownie introduction some users https yearn finance https curve fi https badger finance installing brownie installing brownie https eth brownie readthedocs io en stable install html install pipx pipx install eth brownie testing successful install brownie simple storage project a new brownie project with brownie init project basic explanation adding simplestorage sol to the contracts folder compiling with brownie compile brownie deploy script def main is brownie s entry point brownie defaults to a development ganache chain that it creates placing functions outside of the main function brownie accounts 3 ways to add accounts 1 accounts 0 brownie s default ganache accounts only works for local ganache 2 accounts load brownie s encrypted command line most secure run brownie accounts new name and enter your private key and a password 3 accounts add config wallets from key storing private keys as an environment variable and pulling from our brownie config yaml you ll need to add dotenv env to your brownie config yaml and have a env file importing a contract contract deploy view function call in brownie state changing function call in brownie contract interaction transaction wait 1 testing basics test simple storage py arrange act assert assert https docs pytest org en 6 2 x assert html brownie test test updating storage pytest brownie test tips https docs pytest org en 6 2 x deploy to a testnet brownie networks list development vs ethereum development is temporary ethereum networks persist rpc url http provider in brownie the network flag list index out of range get account networks show active build deployments accessing previous deployments interacting with contracts deployed in our brownie project brownie console brownie console lesson 6 brownie fund me https github com patrickalphac brownie fund me code https github com patrickalphac brownie fund me introduction setup dependencies deploying and networks dependencies chainlink brownie contracts https github com smartcontractkit chainlink brownie contracts remappings deploy script v1 helpful scripts py init py deploy to rinkeby contract verification publish source the manual way flattening the programmatic way getting an etherscan api key https etherscan io apis etherscan token interacting with etherscan deploying to local chains introduction to mocking constructor parameters networks in our brownie config yaml copying mock contracts from chainlink mix https github com smartcontractkit chainlink mix deploying and using our mock refactoring deploying to a persistent ganache brownie attach adding a persistent brownie network resetting a network build funding and withdrawing python scripts whoops let s fix an issue fund script withdraw script testing across networks test can fund and withdraw default networks pytest pip install pytest pytest skip brownie exceptions mainnet fork custom mainnet fork adding a development brownie network brownie networks add development mainnet fork dev cmd ganache cli host http 127 0 0 1 fork https infura io v3 web3 infura project id accounts 10 mnemonic brownie port 8545 alchemy https www alchemy com brownie test network mainnet fork brownie ganache vs local ganache vs mainnet fork vs testnet git installing git https git scm com book en v2 getting started installing git creating a repository first time with git https git scm com book en v2 getting started first time git setup adding our project to github https docs github com en github importing your projects to github importing source code to github adding an existing project to github using the command line tweet it out compatibility with ganache ui test only owner can withdraw gives below error if the selected network is ganache ui e valueerror execution reverted during call vm exception while processing transaction revert this transaction will likely revert if you wish to broadcast include allow revert true as a transaction parameter more information here https ethereum stackexchange com questions 114889 deploying ganache local w brownie vm exception while processing transaction in lesson 7 smartcontract lottery https github com patrickalphac smartcontract lottery code https github com patrickalphac smartcontract lottery chainlink vrf v1 docs https docs chain link vrf v1 examples get a random number introduction add a readme md defining the project is it decentralized lottery sol basic setup main functions address payable getentrancefee setup chainlink price feed https docs chain link docs get the latest price brownie config spdx matching units of measure can t just divide test early and often quick math sanity check deleting networks alchemy https www alchemy com again enum startlottery openzeppelin https openzeppelin com contracts is this the first openzeppelin reference openzeppelin contracts github https github com openzeppelin openzeppelin contracts randomness pseudorandomness block keyword block difficulty block timestamp keccack256 true randomness with chainlink vrf https docs chain link docs get a random number chainlink vrf remix version inheriting constructors oracle gas transaction gas why didn t we pay gas on the price feeds https ethereum stackexchange com questions 87473 is chainlinks price reference data free to consume chainlink node fees request and receive introduction https docs chain link docs architecture request model kovan faucets https docs chain link docs link token contracts kovan funding chainlink contracts request and receive explanation https docs chain link docs architecture request model a clarification endlottery returns type variablename fulfillrandomness override modulo operation mod operation paying the lottery winner resetting the lottery testing lottery sol deploy lottery py get account refactored get contract contract to mock contract from abi adding the parameters to deploying to lottery vrfcoordinatormock and adding mocks linktoken and mocks successful ganache deployment python lottery scripts functions start lottery brownie tip remember to tx wait 1 your last transaction enter lottery end lottery funding with link brownie interfaces waiting for callback integration tests unit tests test all lines of code test get entrance fee pytest skip again test cant enter unless started test can start and enter lottery test can pick winner correctly events and logs callbackwithrandomness lottery sol testnet deployment topics conftest py https stackoverflow com questions 34466027 in pytest what is the use of conftest py files lesson 8 chainlink mix https github com smartcontractkit chainlink mix code https github com smartcontractkit chainlink mix brownie mixes https github com brownie mix lesson 9 erc20s eips and token standards https github com patrickalphac erc20 brownie py code https github com patrickalphac erc20 brownie py erc20 eip20 standard https eips ethereum org eips eip 20 what is an erc20 creating an erc20 openzeppelin erc20 https docs openzeppelin com contracts 2 x api token erc20 solidity 0 8 https docs soliditylang org en breaking 080 breaking changes html i challenge you to code this yourself deploy token py copy paste helpful scripts py viewing our token in metamask adding to an exchange lesson 10 defi aave https github com patrickalphac aave brownie py freecode note this repo is now archived as kovan is no longer supported you can still follow along with the learning but know the code may not work the same on a different testnet code https github com patrickalphac aave brownie py freecode defi intro defipulse https defipulse com defillama https defillama com aave testnet site https staging aave com paraswap https paraswap io decentralized exchange aave ui kovan eth https docs chain link docs link token contracts kovan what is aave borrowing and lending connecting to aave depositing tokens lending checking your transaction is correct weth gateway interest bearing token atoken collateral dai https makerdao com en stablecoin https www investopedia com terms s stablecoin asp wrapped bitcoin wbtc https www gemini com cryptopedia wrapped bitcoin what can you do why borrow tokens https docs aave com faq borrowing blockchain fintech tutorial https blog chain link blockchain fintech defi tutorial lending borrowing python disclaimer about borrowing borrowing tokens liquidations https docs aave com faq liquidations your health factor must be above 1 solvent https www investopedia com terms s solvency asp stable vs variable interest rate https docs aave com faq borrowing what is the difference between stable and variable rate repaying our borrows loans reward token governance token governance programmatic interactions with aave https github com patrickalphac aave brownie py freecode quant defi engineer aave documentation https docs aave com developers setup converting eth weth get weth py iweth https github com patrickalphac aave brownie py blob main interfaces wethinterface sol kovan weth token address 0xd0a1e359811322d97991e03f863a0c30c2cf029c https kovan etherscan io token 0xd0a1e359811322d97991e03f863a0c30c2cf029c mainnet weth token address 0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2 https etherscan io token 0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2 converting weth eth with withdraw aave borrow py lendingpool https docs aave com developers the core protocol lendingpool lendingpooladdressprovider https docs aave com developers the core protocol addresses provider lendingpool and lendingpooladdressprovider addresses https docs aave com developers deployed contracts deployed contracts fixing import dependencies aave github https github com aave protocol v2 erc20 approve function https medium com ethex market erc20 approve allow explained 88d6de921ce9 ierc20 from patrick s repo https github com patrickalphac aave brownie py blob main interfaces ierc20 sol deposit getuseraccountdata https docs aave com developers the core protocol lendingpool getuseraccountdata liquidation threshold risk parameters https docs aave com risk asset risk risk parameters borrowing dai getting dai conversion rate chainlink price feeds https docs chain link docs reference contracts aggregatorv3interface https github com patrickalphac aave brownie py blob main interfaces aggregatorv3interface sol borrow https docs aave com developers the core protocol lendingpool borrow mainnet dai address 0x6b175474e89094c44da98b954eedeac495271d0f https etherscan io token 0x6b175474e89094c44da98b954eedeac495271d0f aave testnet token addresses https aave github io aave addresses kovan json repaying kovan run viewing the transactions testing lesson 11 nfts https github com patrickalphac nft demo code https github com patrickalphac nft demo non technical explainer end to end article https www freecodecamp org news how to make an nft and render on opensea marketplace what is an nft erc721 https eips ethereum org eips eip 721 token uri token metadata example https docs opensea io docs 2 adding metadata ipfs https ipfs io simple nft brownie mix https github com patrickalphac nft mix initial setup simplecollectible sol openzeppelin erc721 https docs openzeppelin com contracts 3 x pug image https github com patrickalphac nft mix blob main img pug png nft constructor nft is a type of factory pattern createcollectible safemint tokenuri metadata opensea listing example is this decentralized ethereum size and dstorage ethereum size https ycharts com indicators ethereum chain full sync data size dstorage solutions https ethereum org en developers docs storage ipfs https www ipfs com you need to have your nft attributes both on chain and inside your tokenuri metadata deploy and create py tokenuri used for the demo https ipfs io ipfs qmd9mcgtdvz2minumbhdbvj8bigsgtwnr4sbyh6dnnpwdt filename 0 pug json https ipfs io ipfs qmd9mcgtdvz2minumbhdbvj8bigsgtwnr4sbyh6dnnpwdt filename 0 pug json ipfs companion https chrome google com webstore detail ipfs companion nibjojkomfdiaoajekhjakgkdhaomnch hl en rinkeby deployment opensea example https testnets opensea io assets 0x8acb7ca932892eb83e4411b59309d44dddbc4cdf 0 simplecollectible testing what else with nfts advanced nft advancedcollectible sol dungeons and dragons example https github com patrickalphac dungeons and dragons nft double inherited constructors createcollectible advanced tokenidtobreed working with in flight chainlink vrf requests download the nft images from the nft mix https github com patrickalphac nft mix settokenuri isapprovedorowner emit events when you update mappings indexed event keyword https ethereum stackexchange com questions 8658 what does the indexed keyword do 8659 advanced deploy and create move opensea url to helpful scripts deploying advancedcollectible opensea testnet is only compatible with rinkeby rinkeby chainlink vrf contract addresses https docs chain link docs vrf contracts rinkeby speeding through adding functions from previous projects deploy to rinkeby create collectible py a quick unit test a quick integration test creating metadata ipfs create metadata py get breed metadata folder metadata template nft metadata attributes checking if metadata file already exists uploading to ipfs upload to ipfs download ipfs command line https docs ipfs io install command line download ipfs desktop https docs ipfs io install ipfs desktop http ipfs docs https docs ipfs io reference http api ipfs daemon pinata https app pinata cloud pinata docs https docs pinata cloud refactoring to not re upload to ipfs setting the tokenuri end to end manual testnet test viewing on opensea lesson 12 upgrades https github com patrickalphac upgrades mix code https github com patrickalphac upgrades mix introduction to upgrading smart contracts original video https www youtube com watch v bdxjmwajzry smart contracts can be upgraded does this mean they are not immutable trail of bits on upgradeable smart contracts https blog trailofbits com 2018 09 05 contract upgrade anti patterns the not really upgrading parameterization method the social yeet migration method contract migration https blog trailofbits com 2018 10 29 how contract migration works proxies delegatecall terminology implementation contract proxy contract user admin gotchas storage clashes function selector function selector clashes proxy patterns transparent proxy pattern https blog openzeppelin com the transparent proxy pattern universal upgrade proxy standard https eips ethereum org eips eip 1822 diamond multi facet proxy https eips ethereum org eips eip 2535 upgrades mix and code setup box sol boxv2 sol getting the proxy contracts openzeppelin proxy github https github com openzeppelin openzeppelin contracts tree master contracts proxy transparent 01 deploy box py hooking up a proxy to our implementation contract optional creating a gnosis safe https help gnosis safe io en articles 3876461 create a safe initializers encoding initializer function assigning abi to a proxy running the script upgrade python function testing upgrades testing our proxy testing our upgrades upgrades on a testnet bonus lesson 13 full stack defi https github com patrickalphac defi stake yield brownie freecode note this section is archived as kovan is now deprecated if you re looking to learn more full stack check out the full stack portions of the hardhat javascript video link to hardhat javascript video with more full stack examples https github com smartcontractkit full blockchain solidity course js code https github com patrickalphac defi stake yield brownie freecode freecodecamp react https www freecodecamp org news tag react what are we building setup dapptoken sol tokenfarm sol tokenisallowed addallowedtokens mapping of a mapping staketokens issuetokens getusertotalvalue getusersingletokenvalue gettokenvalue setpricefeedcontract unstaketokens can this be reentrancy attacked defi stake yield brownie scripts tests deploy py deploying dapptoken deploying tokenfarm adding allowed tokens erc20 kovan faucet https erc20faucet com if the link above does not work you can get another erc20 token using this faucet weenus erc20 faucet https github com bokkypoobah weenustokenfaucet mocking our erc20s testing our defi stake yield brownie dapp test set price feed contract test stake tokens fixtures test issue tokens now you try on tests front end full stack front end introduction typescript react https reactjs org usedapp https usedapp readthedocs io en latest npx https www npmjs com package npx yarn https classic yarnpkg com en docs install create react app layout testing front end https www freecodecamp org news testing react hooks yarn yarn start connecting our wallets install usedapp header component connect button material ui https material ui com making our button nicer main tsx sending brownie config build folder to our ui helper config typescript error suppression getting addresses ethers https docs ethers io v5 only support kovan yourwallet supportedtokens state hooks showing tokens walletbalance ethersproject units https www npmjs com package ethersproject units balancemsg stake form calling approve usecontractfunction useeffect notifications make it pretty alerts shoutout to matt https twitter com mdurkin92 for the help on the front end closing and summary security best practices https consensys github io smart contract best practices attacks https consensys github io smart contract best practices attacks oracle attacks https hackernoon com how dollar100m got stolen from defi in 2021 price oracle manipulation and flash loan attacks explained 3n6q33r1 re entrancy attacks https quantstamp com blog what is a re entrancy attack damn vulnerable defi https www damnvulnerabledefi xyz ethernaut https ethernaut openzeppelin com some auditors openzeppelin https openzeppelin com sigmaprime https sigmaprime io trail of bits https www trailofbits com where do i go now learning more cryptozombies https cryptozombies io dapp university https www youtube com channel ucy0xl8v6nzzfcwzhcgb8orq chainshot https www chainshot com courses ivan on tech https academy ivanontech com eat the blocks https www youtube com channel uczm8xqjnoyg2elppeutnasa patrick collins https www youtube com channel ucn 3f8tw e1jzvhuhatrowa austin griffith https www youtube com channel uc hi2i2peo1a stdg22gfsa nader dabit https www youtube com user boyindasouth ethereum org https ethereum org en community twitter brownie discord https discord gg 9zk7sntfwe ethereum discord https ethereum org en chainlink discord https discord gg 2yhsaey reddit ethdev https www reddit com r ethdev hackathons cl hackathon https chain link hackathon eth global https ethglobal co eth india https twitter com ethindiaco be sure to check out project grant programs vyper from solidity course to vyper https github com chalex eth from solidity course to vyper py and make today an amazing day | ethereum blockchain solidity smart-contracts dapp chainlink web3 | blockchain |
pablitoBDB | pablitobdb this project was born as a university project the main goal is designing and implementing a database from scratch thus we decided to contact an engineering firm to work with them and improve their workflow the reason we decided to contact them is the fact that they didn t work with any database and designing a database for that enviroment is challenging we like challenges you can find our report report report pdf inside the report directory report unluckily it s written in italian cause our professor wanted it that way don t blame us we might translate it soon the report was written using latex in the report directory you can find the tex file report report tex too we used mysql as dbms you can find the database dump sql dump sql inside the sql directory sql it contains fake data created using the python library faker https github com joke2k faker inside the sql directory you can find the script sql dummy py we wrote to create and insert the data the next goal of the project is designing and developing a web application and a management program that interface with the database stay tuned talking about the database this is the database logic scheme dblogicscheme img dbschemes ristrutturato jpg contributors name email github contributing linkedin began bajrami beganbajrami outlook it begbaj https github com begbaj dyrem https github com dyremm p align center 1 2 p align center https www linkedin com in begbaj rahmi el mechri rahmmi elmechri gmail com ot rax https github com ot rax p align center 1 2 p align center https www linkedin com in rahmi elmechri | server |
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cordova-mobile-app-ui-template | mobile app ui template for cordova or ionic capacitor simple and fully customizable user interface template design for mobile app development on apache cordova framework or ionic capacitor native runtime platforms ios android it reduces production costs and enables the project to be developed quickly br developed project it can run on android ios and the web br most of the javascript libraries can be used in the project br native functions can be used with cordova plugins br file system database bluetooth camera file transfer barcodescanner google maps etc br the syntax of the programming language is simple this makes learning easier br html and css codes are written automatically by the basic js library br it is designed with an object based logic close to software development experience br it has the same positioning logic as the interface design tools this too makes it easy to translate your design into an application br br installation run following command to install this template in your current folder bash npm i cordova mobile app template live preview https bug7a github io cordova mobile app ui template screenshots alt tag https bug7a github io cordova mobile app ui template mobile app ui template android ios png alt tag https bug7a github io cordova mobile app ui template mobile app template android png alt tag https bug7a github io cordova mobile app ui template mobile app template ios png br br contact started date 22 february 2022 br developer bugra ozden br email bugra ozden gmail com br web site http bugraozden com br br you can contact me for your mobile application projects br best regards br br license you are free br to share to copy distribute and transmit the work br to remix to adapt the work br to make commercial use of the work br https creativecommons org licenses by 4 0 br br | cordova mobile android ios cordova-plugin javascript ui-design ui-components uikit mobile-app cordova-android cordova-ios mobile-development html template cordova-template capacitor ionic | front_end |
mediamarket | typescript expor bootstrap base project starter this is a repository intended to serve as a starting point if you want to bootstrap an expo project in typescript features typescript https www typescriptlang org expo https expo dev jest https jestjs io with react testing library https testing library com docs dom testing library intro babel https babeljs io running the app bash install dependencies yarn install run in web mode yarn web run in android yarn android run in ios yarn ios testing jest with supertest bash yarn test | cloud |
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posgresSongPlays | posgressongplays database for udacity data engineering project 1 import os import glob import psycopg2 import pandas as pd from sql queries import def process song file cur filepath processes data song data files and inserts records into the song and artist tables open song file df pd read json filepath lines true insert song record song data df song id title artist id year duration song data song data values 0 cur execute song table insert song data insert artist record artist data df artist id artist name artist location artist latitude artist longitude artist data artist data values 0 cur execute artist table insert artist data def process log file cur filepath processes data log data files and inserts records into the time user and song select tables open log file df pd read json filepath lines true filter by nextsong action df df df page nextsong convert timestamp column to datetime t pd to datetime df ts unit ms insert time data records time table insert insert into time start time hour day week month year weekday values s s s s s s s time data t t dt hour t dt day t dt weekofyear t dt month t dt year t dt weekday column labels timestamp hour day week of year month year weekday time df column labels 0 time data 0 column labels 1 time data 1 column labels 2 time data 2 column labels 3 time data 3 column labels 4 time data 4 column labels 5 time data 5 column labels 6 time data 6 time df pd dataframe from dict time df for i row in time df iterrows cur execute time table insert list row load user table user df df userid firstname lastname gender level user df user df drop duplicates subset none insert user records for i row in user df iterrows cur execute user table insert row insert songplay records for index row in df iterrows get songid and artistid from song and artist tables cur execute song select row song row artist row length results cur fetchone if results songid artistid results else songid artistid none none insert songplay record songplay id start time user id levl song id artist id session id location user agent songplay data row ts row userid row level songid artistid row sessionid row location row useragent cur execute songplay table insert songplay data def process data cur conn filepath func loops through file directories and prints a number found get all files matching extension from directory all files for root dirs files in os walk filepath files glob glob os path join root json for f in files all files append os path abspath f get total number of files found num files len all files print files found in format num files filepath iterate over files and process for i datafile in enumerate all files 1 func cur datafile conn commit print files processed format i num files def main connects to psycopg2 database and executes methods conn psycopg2 connect host 127 0 0 1 dbname sparkifydb user student password student cur conn cursor process data cur conn filepath data song data func process song file process data cur conn filepath data log data func process log file conn close if name main main | server |
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blockchain-supply-chain-solution | blockchain supply chain overview this is the umbrella repository for blockchain supply chain solution the solution implements an end to end document and device data attestation scenario the office 365 outlook integration https github com azure supply chain office integration supports archiving retrieval and validations of attachments the core services https github com azure supply chain services provide an api to interact with the ethereum smart contract https github com azure supply chain smart contracts this contract implements the persistency of a proof such as a laboratory report of a produce the core service readme md https github com azure supply chain services blob master readme md explains the api in more detail in addition to the interaction with the smart contract the core services implement a key store which is used to encrypt the private parts of a proof architecture architecture overview diagrams architecture jpg cloning the repo git clone https github com azure blockchain supply chain solution git cd blockchain supply chain solution git submodule init git submodule update init remote git submodule foreach git checkout master getting started locally build and deploy the smart contract to the block chain https github com azure supply chain smart contracts blob master readme md for local development you either use testrpc or a local geth instance configure and run the core service https github com azure supply chain services update the configuration as described in the readme and run the service using npm start configure and run the office integration service https github com azure supply chain office integration follow the instructions in on configuration and running in localhost deploying the solution to azure to deploy the solution to azure follw the cloning the repo steps above and then follow these https github com azure blockchain supply chain solution tree master azure deployment instructions | blockchain outlook-addin ethereum azure supply-chain attestation | blockchain |
pulse | p align center img src https user images githubusercontent com 32125808 231166226 c636f344 fc3b 4c71 9181 49fe97491127 png width 320px p div align center go report card https goreportcard com badge github com gopulse pulse https goreportcard com report github com gopulse pulse github license https img shields io github license gopulse pulse license go reference https pkg go dev badge github com gopulse pulse svg https pkg go dev github com gopulse pulse go doc https img shields io badge f0 9f 93 9a 20godoc pkg 00acd7 svg color 00acd7 style flat square https pkg go dev github com gopulse pulse pkg overview discord online https img shields io discord 1095400462477426748 label discord logo discord logocolor white https discord gg jkctwzyj codecov https img shields io codecov c github gopulse pulse token rbxpy1wn2i https codecov io gh gopulse pulse circleci https img shields io circleci build github gopulse pulse master token 7eda4a74e26b544956b8333b372592ee09cd7f8b https dl circleci com status badge redirect gh gopulse pulse tree master div a golang framework for web development that keeps your web applications and services responsive with its fast and lightweight design features routing route groups static files simple and elegant api middleware support installation make sure you have go installed on your machine then run the following command initialize your project learn https go dev blog using go modules then install pulse with the go get command bash go get github com gopulse pulse benchmarks zap this test was performed by go web https github com smallnest go web framework benchmark img src https user images githubusercontent com 32125808 234717844 d7bf69f8 11cb 420f bd58 30a38769614e png alt pulse framework pipeline benchmark getting started go package main import github com gopulse pulse func main app pulse new router pulse newrouter app router router router get func c pulse context error c string hello world return nil app run 3000 examples routing supports get post put patch delete options head connect trace go package main import github com gopulse pulse func main app pulse new router pulse newrouter get hello router get func c pulse context error c string hello world return nil get hello name router get profile id func c pulse context error c string profile c param id return nil get user router get user func c pulse context error c string hello world return nil app router router app run 3000 route groups supports get post put patch delete options head connect trace go package main import github com gopulse pulse func main app pulse new router pulse newrouter api pulse group prefix api router router v1 api group v1 v1 get users func ctx context error ctx string users return nil app router router app run 3000 static files go package main import github com gopulse pulse time func main app pulse new router pulse newrouter static files static with cache duration 24 hours router static static pulse static compress true byterange false indexname index html cacheduration 24 time hour app router router app run 3000 middleware go package main import github com gopulse pulse func main app pulse new router pulse newrouter router get profile name func ctx pulse context error if ctx param name test ctx abort ctx status 404 return nil ctx string hello ctx next return nil app router router app run 3000 available middleware x cors middleware enable cross origin resource sharing cors with various options go package main import github com gopulse pulse func main app pulse new router pulse newrouter router get func ctx pulse context error return nil router use get pulse corsmiddleware app router router app run 3000 logger middleware log every request with configurable options coming soon encrypt cookie middleware encrypt and decrypt cookie values coming soon timeout middleware set a timeout for requests coming soon license pulse is licensed under the mit license see license license for the full license text contributing contributions are welcome please read the contribution guidelines contributing md first support if you want to say thank you and or support the active development of pulse 1 add a github star https github com gopulse pulse stargazers to the project 2 tweet about the project on your twitter https twitter com intent tweet text pulse 20is 20a 20 23web 20 23framework 20for 20the 20 23go 20programming 20language 20it 20is 20a 20lightweight 20framework 20that 20is 20 23easy 20to 20use 20and 20easy 20to 20learn 20it 20is 20designed 20to 20be 20a 20simple 20and 20elegant 20solution 20for 20building 20web 20applications 20and 20 23apis 20 f0 9f 9a 80 20https 3a 2f 2fgithub com 2fgopulse 2fpulse 3 write a review or tutorial on medium https medium com dev to https dev to reddit https www reddit com or personal blog 4 buy me a coffee https www buymeacoffee com gopulse contributors contributors start a href https github com gopulse pulse graphs contributors img src https contrib rocks image repo gopulse pulse columns 18 a contributors end stargarazers over time stargazers over time https starchart cc gopulse pulse svg https starchart cc gopulse pulse | golang golang-framework web gopulse go | front_end |
cecs453 | cecs453 mobile development | front_end |
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Data-Engineering | data engineering list of data engineering projects including spark kafka with google cloud platform | cloud |
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SEANLP | seanlp southeast asia natural language processing seanlp tcc thai character cluster kcc 1 tcc thai character cluster wittawat jitkrittum tcc https github com wittawatj jtcc git proposed in character cluster based thai information retrieval is a group of inseparable thai characters this inseparability derives from thai writing system which is independent of any context as a result tcc can be determined by a simple list of rules describing e g what characters need to follow precede other characters 2 tcc kcc tcc wittawat jitkrittum https github com wittawatj jtcc git 3 xmx 2g 4 5 6 7 https github com zhaoshiyu seanlp archive master zip wget https github com zhaoshiyu seanlp archive master zip unzip master zip cd seanlp master mvn clean package dmaven test skip true git clone git clone https github com zhaoshiyu seanlp git cd seanlp mvn clean package dmaven test skip true jar seanlp 1 1 0 jar https pan baidu com s 1nrqqrjcyplhop4oqvf8odq seanlp 1 1 0 sources jar https pan baidu com s 16qftu43yok swvu0wkjhaw seanlp seanlp seanlp xmx 2g demo demo br 1 https github com zhaoshiyu seanlp blob master src test java cn edu kmust seanlp demo segmentdemo java br 2 https github com zhaoshiyu seanlp blob master src test java cn edu kmust seanlp demo similaritydemo java br 3 https github com zhaoshiyu seanlp blob master src test java cn edu kmust seanlp demo extractdemo java br 1 package cn edu kmust seanlp demo import cn edu kmust seanlp seanlp demo author zhao shiyu public class segmentdemo public static void main string args string thtext system out println seanlp thai syllablesegment thtext system out println seanlp thai dcrfsegment thtext system out println seanlp thai gcrfsegment thtext system out println seanlp thai datsegment thtext system out println seanlp thai maxsegment thtext system out println seanlp thai minsegment thtext system out println seanlp thai remaxsegment thtext system out println seanlp thai reminsegment thtext string vitext h th ng t n d ng ng n h ng c ng t ng tr ng kh ng y c ng gi vai tr quan tr ng trong c c u kinh t th system out println seanlp vietnamese crfsegment vitext system out println seanlp vietnamese datsegment vitext system out println seanlp vietnamese maxsegment vitext system out println seanlp vietnamese minsegment vitext system out println seanlp vietnamese remaxsegment vitext system out println seanlp vietnamese reminsegment vitext string khtext system out println seanlp khmer crfsegment khtext system out println seanlp khmer datsegment khtext system out println seanlp khmer maxsegment khtext system out println seanlp khmer minsegment khtext system out println seanlp khmer remaxsegment khtext system out println seanlp khmer reminsegment khtext string lotext system out println seanlp lao datsegment lotext system out println seanlp lao maxsegment lotext system out println seanlp lao minsegment lotext system out println seanlp lao remaxsegment lotext system out println seanlp lao reminsegment lotext string butext system out println seanlp burmese datsegment butext system out println seanlp burmese maxsegment butext system out println seanlp burmese minsegment butext system out println seanlp burmese remaxsegment butext system out println seanlp burmese reminsegment butext system out println seanlp burmese syllablesegment butext 2 package cn edu kmust seanlp demo import cn edu kmust seanlp seanlp demo author zhao shiyu public class similaritydemo public static void main string args string thtext string vitext h th ng t n d ng ng n h ng c ng t ng tr ng kh ng y c ng gi vai tr quan tr ng trong c c u kinh t th string khtext string lotext string butext system out println seanlp thai sentencesimilarity thtext thtext system out println seanlp vietnamese sentencesimilarity vitext vitext system out println seanlp khmer sentencesimilarity khtext khtext system out println seanlp lao sentencesimilarity lotext lotext system out println seanlp burmese sentencesimilarity butext butext 3 package cn edu kmust seanlp demo import cn edu kmust seanlp seanlp demo author zhao shiyu public class extractdemo public static void main string args string thdocument n 19 n 18 n string vidocument i h i l n th xii c a ng h p phi n tr b nd t s ng 20 1 i h i i bi u to n qu c l n th xii c a ng h p phi n tr b ho n t t c ng t c chu n b c n thi t cho phi n khai m c s di n ra v o 8 gi s ng 21 1 m u phi n h p tr b ng ch l h ng anh y vi n b ch nh tr th ng tr c ban b th trung ng ng tuy n b l do ng ch tr ng t n sang y vi n b ch nh tr ch t ch n c i u khi n phi n h p ti p ch t ch n c tr ng t n sang xin ki n i h i th ng qua ch ng tr nh phi n h p tr b th ng qua quy ch l m vi c c a i h i i h i ho n th nh c c ph n vi c quan tr ng g m b u o n ch t ch o n th k ban th m tra t c ch i bi u th ng qua ch ng tr nh l m vi c c a i h i th ng qua quy ch b u c c a i h i v th ng qua b o c o th m tra t c ch i bi u bu i chi u c c i bi u nghi n c u t i li u t i o n ng y mai 21 1 i h i i bi u to n qu c l n th xii c a ng khai m c t i trung t m h i ngh qu c gia h n i i h i ti n h nh t ng y 21 n 28 1 2016 c nhi m v nh gi vi c th c hi n ngh quy t i h i xi c a ng v nh n l i ch ng ng 30 n m i m i t n c th o lu n th ng qua b o c o ch nh tr c a ban ch p h nh trung ng kh a xi c c b o c o nh gi k t qu th c hi n nhi m v ph t tri n kinh t x h i n m n m 2011 2015 v ph ng h ng nhi m v ph t tri n kinh t x h i n m n m 2016 2020 ki m i m s l nh o ch o c a ban ch p h nh trung ng kh a xi t ng k t thi h nh i u l ng kh a xi v xu t b sung s a i n u c vi c th c hi n ngh quy t t 4 kh a xi v x y d ng ng i h i b u ban ch p h nh trung ng kh a xii ch c a i h i l t ng c ng x y d ng ng trong s ch v ng m nh ph t huy s c m nh to n d n t c v d n ch x h i ch ngh a y m nh to n di n ng b c ng cu c i m i b o v v ng ch c t qu c gi v ng m i tr ng h a b nh n nh ph n u s m a n c ta c b n tr th nh n c c ng nghi p theo h ng hi n i tham d i h i xii c 1510 i bi u i di n cho h n 4 5 tri u ng vi n trong i bi u ng nhi n c 197 ng ch l y vi n trung ng ch nh th c v d khuy t kh a xi 1300 i bi u c b u t i c c i h i ng b tr c thu c trung ng 13 i bi u ch nh c ng t c chu n b i h i c ban ch p h nh trung ng tr c ti p l b ch nh tr ban b th ch o ch t ch n nay ho n t t string lodocument n 13 35 19 n 20 26 n string kmdocument n n n n n n n string budocument n system out println seanlp thai extractkeyword thdocument 6 system out println seanlp thai extractsummary thdocument 3 system out println seanlp lao extractkeyword lodocument 6 system out println seanlp lao extractsummary lodocument 3 system out println seanlp khmer extractkeyword kmdocument 6 system out println seanlp khmer extractsummary kmdocument 3 system out println seanlp vietnamese extractkeyword vidocument 6 system out println seanlp vietnamese extractsummary vidocument 3 system out println seanlp burmese extractkeyword budocument 6 system out println seanlp burmese extractsummary budocument 3 apache license version 2 0 https www apache org licenses license 2 0 html hanlp https github com hankcs hanlp zhao shiyu https github com zhaoshiyu | ai |
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eleventy-dev-server | p align center img src https www 11ty dev img logo github svg width 200 height 200 alt 11ty logo p eleventy dev server a minimal modern generic hot reloading local web server to help web developers documentation https www 11ty dev docs watch serve eleventy dev server please star eleventy on github https github com 11ty eleventy follow us on twitter eleven ty https twitter com eleven ty support 11ty on open collective https opencollective com 11ty 11ty on npm https www npmjs com org 11ty 11ty on github https github com 11ty npm version https img shields io npm v 11ty eleventy dev server svg style for the badge https www npmjs com package 11ty eleventy dev server installation this is bundled with 11ty eleventy and you do not need to install it separately in eleventy v2 0 cli eleventy dev server now also includes a cli the cli is for standalone non eleventy use only separate installation is unnecessary if you re using this server with 11ty eleventy sh npm install g 11ty eleventy dev server alternatively install locally into your project npm install 11ty eleventy dev server this package requires node 14 or newer cli usage sh serve the current directory npx 11ty eleventy dev server serve a different subdirectory also aliased as input npx 11ty eleventy dev server dir site disable the domdiff feature npx 11ty eleventy dev server domdiff false full command list in the help npx 11ty eleventy dev server help tests npm run test we use the ava javascript test runner https github com avajs ava assertions documentation https github com avajs ava blob master docs 03 assertions md | front_end |
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MAD-LAB-Programs | mad lab programs list sl no part a lab programs link 1 create an application to design a visiting card the visiting card should have a company logo at the top right corner the company name should be displayed in capital letters aligned to the center information like the name of the employee job title phone number address email fax and the website address is to be displayed insert a horizontal line between the job title and the phone number click here p1 visitingcard 2 develop an android application using controls like button textview edittext for designing a calculator having basic functionality like addition subtraction multiplication and division click here p2 simplecalculator 3 create a sign up activity with username and password validation of password should happen based on the following rules ul li password should contain uppercase and lowercase letters li li password should contain letters and numbers li li password should contain special characters li li minimum length of the password the default value is 8 li ul on successful sign up proceed to the next login activity here the user should sign in using the username and password created during signup activity if the username and password are matched then navigate to the next activity which displays a message saying successful login or else display a toast message saying login failed the user is given only two attempts and after that display a toast message saying failed login attempts and disable the sign in button use bundle to transfer information from one activity to another click here p3 loginactivity 4 develop an application to set an image as wallpaper on click of a button the wallpaper image should start to change randomly every 30 seconds click here p4 wallpaperapp 5 write a program to create an activity with two buttons start and stop on pressing the start button the activity must start the counter by displaying the numbers from one and the counter must keep on counting until the stop button is pressed display the counter value in a textview click here p5 counterapp 6 create two files of xml and json type with values for city name latitude longitude temperature and humidity develop an application to create an activity with two buttons to parse the xml and json files which when clicked should display the data in their respective layouts side by side click here p6 parsingxmlandjson 7 develop a simple application with one edittext so that the user can write some text in it create a button called convert text to speech that converts the user input text into voice click here p7 texttospeechapp 8 create an activity like a phone dialer with call and save buttons on pressing the call button it must call the phone number and on pressing the save button it must save the number to the phone contacts click here p8 callandsaveapp note the main https github com raghuvorkady mad lab programs tree main branch is maintained for only vtu external lab examination the update https github com raghuvorkady mad lab programs tree update branch is maintained for adding updating extra features references 1 to download latest android studio click here https developer android com studio 2 click here https youtu be 0zx efyhru0 t 371 to watch installation video 2 to enroll in android developer fundamentals course click here https developer android com courses fundamentals training overview v2 3 for android documentation click here https developer android com guide 4 click here lab manual 18csmp68 lab manual pdf for the lab manual | androidappdevelopment vtulabsolutions 18csmp68 vtulabprogrammes vtulab vtu mad-lab-programs | front_end |
Microsoft-Student-Partner-Workshop-Learning-Materials-AI-NLP | microsoft student partner workshop learning materials this repository contains all codes and materials of the current session it contains the required code on natural language processing artificial intelligence event 01 img src brochure 1 png img src brochure 2 png img src brochure 3 png img src brochure 4 png event 01 tweets img src tweets 1 png img src tweets 2 png img src tweets 3 png img src tweets 4 png img src tweets 5 png img src tweets 6 png img src tweets 7 png img src tweets 8 png img src tweets 9 png img src tweets 10 png img src tweets 11 png | microsoft workshop nlp ai cloud distributed-networking peer-to-peer | ai |
blinker-library | blinker library blinker library for embedded hardware works with arduino esp8266 esp32 why named blinker when we learn a new embedded hardware we usually started with the sketch blink we think blink is the hello world of embedded hardware we aim to build a easy learn iot solution project which like blink a led so we named this project blinker with this inspiration blinker blink led blink hello world blink led blinker what s blinker blinker https blinker app is a cross hardware cross platform solution for the iot it provides app device and server support and uses public cloud services for data transmission and storage it can be used in smart home data monitoring and other fields to help users build internet of things projects better and faster blinker https blinker app app reference en https github com blinker iot blinker doc wiki blinker arduino library reference cn https github com blinker iot blinker doc wiki blinker arduino e5 ba 93 e4 bd bf e7 94 a8 e6 89 8b e5 86 8c cn https diandeng tech doc thanks websockets https github com links2004 arduinowebsockets for blinker to build up a websocket server adafruit mqtt library https github com adafruit adafruit mqtt library for blinker to build up a mqtt client arduinojson https github com bblanchon arduinojson for blinker to format json data onebutton https github com mathertel onebutton for blinker to manage button painlessmesh https gitlab com painlessmesh painlessmesh tree master for blinker to build up a mesh network blynk https github com blynkkk blynk library due to frequent updates of versions individual items may not be added in time we hope to understand if you find out please let us know websockets https github com links2004 arduinowebsockets blinker websocket adafruit mqtt library https github com adafruit adafruit mqtt library blinker mqtt arduinojson https github com bblanchon arduinojson blinker json onebutton https github com mathertel onebutton blinker painlessmesh https gitlab com painlessmesh painlessmesh tree master blinker mesh blynk https github com blynkkk blynk library | arduino esp8266 esp32 blinker iot embedded hardware wifi websockets ble mqtt wifiduino nbiot | server |
MindMap | mindmap knowledge graph prompting sparks graph of thoughts in large language models this is the official codebase of the mindmap snowflake framework for eliciting the graph of thoughts reasoning capability in llms proposed in mindmap knowledge graph prompting sparks graph of thoughts in large language models https arxiv org pdf 2308 09729 pdf overview we present mindmap a plug and play prompting approach which enables llms to comprehend graphical inputs to build their own mind map that supports evidence grounded generation here is an overview of our model architecture https github com willing510 mindmap blob main fig mind 20map png https github com willing510 mindmap blob main fig mind 20map png run mindmap as the chatdoctor5k dataset for example first you need to create a blank sandbox on https sandbox neo4j com https sandbox neo4j com click connect via drivers find your url and user password then replace the following parts in mindmap py uri your url username your user password your password note that the data of cmckg is too large and it will take about two days to wait we recommend clicking extend your project in neo4j sandbox but don t worry the emckg used by chatdoctor5k will be ready to build on your facility in no time then don t forget to replace your openai key in mindmap py python mindmap py citation if you find this paper interesting please consider cite it through latex article wen2023mindmap title mindmap knowledge graph prompting sparks graph of thoughts in large language models author wen yilin and wang zifeng and sun jimeng journal arxiv preprint arxiv 2308 09729 year 2023 | ai |
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active-prompt | active prompt active prompting with chain of thought for large language models this is the official repo of active prompting with chain of thought for large language models https arxiv org abs 2302 12246 method actively and judiciously select the most helpful questions for llms existing cot studies largely rely on a fixed set of human annotated exemplars which are not necessarily the most effective ones a good performance requires human prompt engineering which is costly we identify the human prompt engineering as two complementary components question selection and prompt template engineering in this paper we offer a solution to the key problem of determining which questions are the most important and helpful ones to annotate from a pool of task specific queries by borrowing ideas from the related problem of uncertainty based active learning we introduce several metrics to characterize the uncertainty so as to select the most uncertain questions for annotation experimental results demonstrate the superiority of our proposed method on eight complex reasoning tasks with text davinci 002 active prompt improves upon self consistency by 7 67 9 74 9 the illustration of active prompt is shown in the figure below image info assets model arch png image info assets result png requirements pip install openai please put your openai api key to the api key variable of utils py then you are good to go quick start for a quick start you can directly run inference script with our provided prompts proposed in the paper shell python inference py dataset gsm8k model code davinci 002 method active cot qes limit 10 prompt path inference prompts gsm8k k 10 random seed 42 multipath 1 temperature 0 7 api time interval 2 reproduce procedure first run the uncertainty generation script to get the uncertainty for each question of the dataset uncertainty estimation shell python uncertainty estimation py dataset gsm8k model code davinci 002 method few shot cot qes limit 0 prompt path basic cot prompts math word problems random seed 42 num trails 10 sort by disagreement after select the most uncertain questions you can start annotation we provide our prompt files for your reference when you are writing your prompt file finally run the inference with your prompt file run inference script shell python inference py dataset gsm8k model code davinci 002 method active cot qes limit 0 prompt path your prompt file path random seed 42 multipath 40 temperature 0 7 api time interval 2 important arguments dataset the name of a dataset choices gsm8k svamp aqua csqa last letters strategyqa asdiv singleeq addsub multiarith model gpt 3 model choices text davinci 002 code davinci 002 method few shot cot or active cot qes limit number of test questions prompt path path of prompt file num trails number of trails for uncertainty estimation sort by the metric for uncertainty estimation multipath number of paths during generation api time interval the time interval when requesting gpt 3 api suggested interval is larger than 1 second to reproduce the results in our paper set qes limit 0 multipath 40 contact information for help or issues using active prompt please submit a github issue for personal communication related to active prompt please contact shizhe diao sdiaoaa connect ust hk citation if you use or extend our work please cite the following paper https arxiv org abs 2302 12246 misc diao2023active title active prompting with chain of thought for large language models author shizhe diao and pengcheng wang and yong lin and tong zhang year 2023 eprint 2302 12246 archiveprefix arxiv primaryclass cs cl | ai |
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E7020E-Project | e7020e project e toaster design and build a pcb to upgrade a toaster to an e toaster prerequisites archlinux visual studio implementation for the software part we will use rust to program the mcu build with cargo openocd components general 1 nucleo board to program our own board 1 usb mini b connector 1 bluetooth sensor rn 42 series class 2 1 stm32f411ret6 mcu 1 lm1117imp adj voltage converter 3 6pins header 1 temp sensor lmt84 1 lcd screen ea dogs102w 6 2 red leds 1 green led 2 pushbuttons 2 transistors 1 relay 5v 230v capacitors 2 4 7u 12 100n 5 1u 2 18p 1 0 01u 2 10u polarized resistors 2 4 7k 3 10k 5 100 1 5k 2 470 4 3 3k 2 1k 1 820 1 160 authors schrub valentin hardware design and realization romary lucas hardware design and realization frisenstam carl software implementation rimsby oscar software implementation grades grade 3 implement led push button temperature sensor and lcd screen grade 4 implement bluetooth functionality write software to enable remote start of toaster enable lcd screen to display relevant information grade 5 extend functionality of lcd screen additional information to be displayed improve remote functionality mobile application | os |
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BlockChain-Security-List | blockchain security list about cryptocurrency security reverse exploit fuzz list alt text https www slowmist com eth214 res img logo png alt text https avatars3 githubusercontent com u 25600994 s 400 u 5e75ba9b340d3148fd9b75ac6da7df7f1b47c4d7 v 4 tools mythril https github com consensys mythril security analysis tool for ethereum smart contracts manticore https github com trailofbits manticore symbolic execution tool slither https trailofbits wufoo com forms m1qfujq31qyj9ee slither combines a set of proprietary static analyses on solidity porosity https github com comaeio porosity decompiler and security analysis tool for blockchain based ethereum smart contracts echidna https github com trailofbits echidna ethereum fuzz testing framework oyente https github com melonproject oyente an analysis tool for smart contracts porosity https github com comaeio porosity decompiler and security analysis tool for blockchain based ethereum smart contracts mythril https github com consensys mythril security analysis tool for ethereum smart contracts maian https github com maian tool maian automatic tool for finding trace vulnerabilities in ethereum smart contracts echidna https github com trailofbits echidna ethereum fuzz testing framework manticore https github com trailofbits manticore manticore uses symbolic execution to simulate complex multi contract and multi transaction attacks against evm bytecode ethersplay https github com trailofbits ethersplay a graphical evm disassembler with advanced features binja oyente https github com melonproject oyente an automatic evm code analyzer based on symbolic execution and z3 smt solver ida evm https github com trailofbits ida evm ida processor module for the ethereum virtual machine evmdis https github com arachnid evmdis evm disassembler securify https securify ch formal verification of ethereum smart contracts rattle https trailofbits wufoo com forms m1qfujq31qyj9ee rattle is an evm static analyzer that analyzes the evm bytecode directly for vulnerabilities slither https trailofbits wufoo com forms m1qfujq31qyj9ee static analyses on solidity diligence https consensys net diligence security services tools and best practices for the ethereum ecosystem fuildai https fluidai co fluid is an ai that can automatically find and fix fatal security vulnerabilities in smart contracts blogs https bcsec org peckshield inc blog https www peckshield com blog html security archives ethereum blog https blog ethereum org category security blockchain sec https blockchain sec com https www cmcmbc com zh cn blog https blog csdn net u011721501 article category 7483965 trailofbits blockchain https blog trailofbits com category blockchain blackhat https cansecwest com slides 2018 blackhat 20ethereum 20 20ryan 20stortz 20and 20jay 20little 20trail 20of 20bits 20inc pdf blackhat ethereum solidified https medium com solidified parity hack how it happened and its aftermath 9bffb2105c0 parity hack arvanaghi 1 https arvanaghi com blog reversing ethereum smart contracts reversing ethereum smart contracts arvanaghi 2 https arvanaghi com blog reversing ethereum smart contracts pt2 reversing ethereum smart contracts 2 ret2 https blog ret2 io 2018 05 16 practical eth decompilation practical eth decompilation loom network https medium com loom network how to secure your smart contracts 6 solidity vulnerabilities and how to avoid them part 1 c33048d4d17d 6 vulnerabilities and how to avoid them part 1 eth assembly https medium com xjonathan reverse engineering ethereum smart contract lets talk assembly 10c38b8e3c2 lets talk assembly radare2 https blog positive com reversing evm bytecode with radare2 ab77247e5e53 reversing evm bytecode with radare2 etherum security tools https blog trailofbits com 2018 03 23 use our suite of ethereum security tools trailofbits ethereum security tools hackernoon https hackernoon com scanning ethereum smart contracts for vulnerabilities b5caefd995df analyzing ethereum smart contracts for vulnerabilities nccgroup https www nccgroup trust us our research discovering smart contract vulnerabilities with goatcasino style cyber security discovering smart contract vulnerabilities with goatcasino arseny reutov https blog positive com predicting random numbers in ethereum smart contracts e5358c6b8620 predicting random numbers in ethereum smart contracts funfair https funfair io randomness is a big deal randomness is a big deal training ethernaut https ethernaut zeppelin solutions level 0x6545df87f57d21cb096a0bfcc53a70464d062512 the ethernaut is a web3 solidity based wargame goatcasino https github com nccgroup goatcasino goatcasino is a truffle project which deploys a set of intentionally vulnerable smart contracts events blockchain graveyard https magoo github io blockchain graveyard coindesk https www coindesk com s search keyword like hack attack 36kr tag anquan https 36kr com tags anquan cnn bitcoin crime https www ccn com bitcoin crime scmagazineuk cryptocurrency https www scmagazineuk com cryptocurrency topic 48080 vulnerabilities dasp http www dasp co smart contract best practices https github com consensys smart contract best practices bitcoinwiki weaknesses https en bitcoin it wiki weaknesses bitcoinwiki cves https en bitcoin it wiki common vulnerabilities and exposures go ethereum issue vuln https github com ethereum go ethereum issues utf8 e2 9c 93 q label 3avuln examples of solidity security issues https github com trailofbits not so smart contracts scanning ethereum smart contracts for vulnerabilities https hackernoon com scanning ethereum smart contracts for vulnerabilities b5caefd995df smart contract security https blog ethereum org 2016 06 10 smart contract security solidity security considerations http solidity readthedocs io en latest security considerations html misc dasp http dasp co decentralized application security project or dasp top 10 of 2018 not so smart conracts https github com trailofbits not so smart contracts examples of solidity security issues evm opcodes https github com trailofbits evm opcodes ethereum opcodes and instruction reference threats go ethereum issue bug https github com ethereum go ethereum issues q is 3aopen is 3aissue label 3abug solidity issue bug https github com ethereum solidity issues utf8 e2 9c 93 q label 3abug reddit ethereum https www reddit com r ethereum bitcointalk https bitcointalk org index php board 6 0 stackexchange ethereum security https ethereum stackexchange com questions tagged security stackexchange bitcoin security https bitcoin stackexchange com questions tagged security paper https bcsec org blockchainsecurity v1 pdf https chaitin cn cn download blockchain security guide 20180507 pdf hacking blockchain https www rsaconference com writable presentations file upload fon4 t11 hacking blockchain pdf bgp hijacking https en wikipedia org wiki bgp hijacking safe wallet white paper https www cmcmbc com zh cn blog research 2018 04 18 79 html blockchains how to steal millions in 264 operations https research kudelskisecurity com 2018 01 16 blockchains how to steal millions in 264 operations quantum attacks on bitcoin and how to protect against them https arxiv org pdf 1710 10377 pdf eclipse attacks on bitcoin s peer to peer network http cs people bu edu heilman eclipse smarter https eprint iacr org 2016 633 pdf making smart contracts smarter yellow paper https ethereum github io yellowpaper paper pdf ethereum a secure decentralised generalised transaction ledger reports new allowanyone bug identified in multiple erc20 smart contracts https peckshield com 2018 05 29 eosoob analyzing and reproducing the eos out of bound write vulnerability in nodeos https peckshield com 2018 05 29 eosoob audit report of iohk s etc wallet https research kudelskisecurity com 2018 01 26 audit report of iohks etc wallet audit report of the waves platform https research kudelskisecurity com 2017 10 10 audit report of the waves platform awesomes solidity audit checklist https github com miguelmota solidity audit checklist eos bp nodes security checklist https github com slowmist eos bp nodes security checklist pentesting ethereum dapps https arvanaghi com blog pentesting ethereum dapps awesome https github com sindresorhus awesome awesome ethereum https github com btomashvili awesome ethereum awesome ethereum virtual machine https github com pirapira awesome ethereum virtual machine jobs slowmist https www slowmist com ethercasts https jobs ethercasts com solidified https solidified io codementor https www codementor io solidity developers iosiro https www iosiro com the author i m thanks to all blockchain security researchers | blockchain |
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PitfallsKnowledgeEditing | pitfallsknowledgeediting code will be released in the next few months | ai |
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uwimg | build your own vision library in this repository you will find instructions on how to build your own image processing computer vision library from mostly scratch the work is divided out into different homework assignments found in the src directory to get started make sure you have git a c compiler and make installed then run git clone https github com pjreddie uwimg cd uwimg make and check to see that everything compiles correctly then to get started open up the readme for homework 0 in src hw0 readme md or view it here src hw0 readme md good luck and have fun | ai |
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fram-challenge | fram challenge 2023 embedded systems hardware design fram challenge | os |
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reinvent2018-mob320 | aws re invent 2018 mob320 0 to 60 with aws appsync rapid development techniques for mobile apis this project accompanies the aws re invent 2018 chalk talk session of the same name in this project we prototype a mobile api using aws appsync https aws amazon com appsync to demonstrate the flexibility and benefits of appsync and graphql for rapid development our prototype is in support of a new mobile app for elastilodge a chain of boutique hotels in conjunction with app design our team will build the associated api across three phases of work 1 expose a legacy rest api represented by api gateway and lambda here 2 enhance the legacy data to include a new machine learning driven pricing api also represented by api gateway and lambda 3 implement a prototype of the reservation booking api 4 build an ios application as client of the api how to start 1 first follow the backend readme backend md instructions 2 then try the frontend readme frontend md instructions | aws aws-appsync graphql | front_end |
FlagScale | introduction flagscale https github com flagopen flagscale git is a large language model llm toolkit based on the megatron lm https github com nvidia megatron lm project which supports the llms from beijing academy of artificial intelligence baai our primary goal is to utilize the computation resources efficiently for llms without sacrificing the numerical stability and model effectiveness for now flagscale is still in its early stage and we will work with the community together to support different llms on various hardware architectures the reason why we start from megatron lm is that it can achieve a very high level resource utilization by combining the most comprehensive distributed training and accelerating techniques especially for training llms beyond ten billions of parameters highlights flagscale provides developers with the actual configurations optimization schemes and hyper parameter settings for llm training from baai it also assists developers in rapidly establishing a basic yet complete pipeline for llm including training fine tuning inference and serving it has several features as follows provide the training schemes of the aquila models form baai which can guaranteed training convergence support the model weight conversion to huggingface and the distributed optimizer repartition keep timely synchronization with the upstream megatron lm project news and updates 2023 10 11 we release the initial version by supporting the aquila models and also provide our actually used training schemes for aquila2 7b examples aquila 7b pretrain aquila 7b distributed a800 12n 80g sh and aquila2 34b examples aquila 34b pretrain aquila 34b distributed a100 64n 40g sh including the parallel strategies optimizations and hyper parameter settings quick start we highly recommend developers to follow the megatron lm usage readme original md contents here we provide instructions for aquila llms setup 1 install the megatron lm dependencies as the original link readme original md setup 2 install the requirements for flagscale git clone git gitee com baai opensp flagscale git cd flagscale pip install r requirements txt pretrain the aquila model 1 change to the aquila directory cd flagscale examples aquila 2 start a distributed training job bash dist start sh before running dist start sh you should provide the required information flagscale home the directory of the flagscale proj home the directory for saving checkpoints tensorboards and other information expname the name of the current training experiment data path the path of the training datasets following the megatron lm format readme original md data preprocessing for quickly running the pretraining process we also provide a small processed data bin https model ks3 cn beijing ksyuncs com nlpdata pile wikipedia demo bin and idx https model ks3 cn beijing ksyuncs com nlpdata pile wikipedia demo idx from the pile https pile eleuther ai dataset hostfile the hostfile of the nodes for the current training which consists of a list of hostnames and slot counts for example hostnames 1 ip 1 slots 8 hostnames 2 ip 2 slots 8 these hostnames or ips represent machines accessible via passwordless ssh and the slots specify the number of gpus available on that machine script file the actually used training script of the current job where you can change the specific configurations as needed for example you should change train samples to match the small demo dataset we provided above 3 stop a distributed training job bash dist stop sh before running dist stop sh you should provide the required information hostfile the hostfile of the nodes for the current training from flagscale to huggingface 1 change to the flagscale directory cd flagscale 2 merge the multiple checkpoints to a single checkpoint if needed python tools checkpoint util py model type gpt load dir load dir save dir save dir true vocab size 100008 vocab file flagscale home examples aquila tokenizer vocab json megatron path flagscale home target tensor parallel size 1 target pipeline parallel size 1 please set the following variables before running the command load dir the directory for loading the original checkpoint save dir the directory for saving the merged checkpoint flagscale home the directory of flagscale 3 convert the merged checkpoint to the huggingface format export pythonpath flagscale home pythonpath python scripts convert megatron unsharded to huggingface py input dir save dir iter iteration mp rank 00 output dir save dir iter iteration hf num layers 60 hidden size 6144 num attention heads 48 group query attention num query groups 8 data type bf16 multiple of 4096 hidden dim multiplier 1 3 please set the following variables before running the command flagscale home the directory of flagscale save dir the directory for loading the merged checkpoint iteration the iteration number from latest checkpointed iteration txt in save dir and need to be padded zeros to 7 digits note that the above configuration is for converting aquila 34b and you may need to change the model configurations such as num layers and hidden size as needed serve a model 1 change to the flagscale directory python cd flagscale 2 merge the multiple checkpoints to a single checkpoint as needed python tools checkpoint util py model type gpt load dir load dir save dir save dir true vocab size 100008 vocab file flagscale home examples aquila tokenizer vocab json megatron path flagscale home target tensor parallel size 1 target pipeline parallel size 1 please set the following variables before running the command load dir the directory for loading the original checkpoint save dir the directory for saving the merged checkpoint flagscale home the directory of flagscale 3 serve the aquila2 model by the below script here we take the aquila2 34b as an example and assume you have an a800 80g gpu python examples aquila 34b inference auto py server port server port master process master port device 0 iteration 1 checkpoint path ckpt dir model info aquila 34b please set the following variables before running the command server port the server port for serving the model master port the port of the master process ckpt dir the directory for loading the merged checkpoint 4 after you have served an aquila model successfully you can send a request to do the testing python tools test test api flask py repartition the distributed optimizer optional when using the distributed optimizer you can use the following tool to repartition the distributed optimizer if the parallel schemes is changed during the training 1 change to the flagscale directory cd flagscale 2 repartition the model weight python tools checkpoint util lite py conversion type weight model type gpt load dir load dir save dir save dir true vocab size 100008 vocab file flagscale home examples aquila tokenizer vocab json megatron path flagscale home target tensor parallel size tp target pipeline parallel size pp please set the following variables before running the command load dir the directory for loading the original checkpoint save dir the directory for saving the converted checkpoint flagscale home the directory of flagscale tp the target tensor parallel size pp the target pipeline parallel size 3 repartition the distributed optimizer python tools checkpoint util lite py conversion type optimizer model type gpt load dir load dir save dir save dir true vocab size 100008 vocab file flagscale home examples aquila tokenizer vocab json megatron path flagscale home target tensor parallel size tp target pipeline parallel size pp please set the following variables before running the command as these used in the model weight conversion load dir the directory for loading the original checkpoint save dir the directory for saving the converted checkpoint flagscale home the directory of flagscale tp the target tensor parallel size pp the target pipeline parallel size future work we will work with the community together on the following items release the actual used training schemes for more models from baai add customized optimizations and integrate techniques from other excellent open source projects like deepspeed and vllm etc support llms with different model structures support the model training with more hardware architectures license this project is mainly based on the megatron lm https github com nvidia megatron lm project and is licensed under the apache license version 2 0 https github com flagopen flagscale blob main license this project also contains other third party components under other open source licenses see the license https github com flagopen flagscale blob main license file for more information | ai |
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RTOS_workspace | freertos workspace hello this is my freertos workspace for you to use or improve what is a real time operating system rtos real time operating system rtos is an operating system intended to serve real time application that process data as it comes in mostly without buffer delay the full form of rtos is real time operating system in a rtos processing time requirement are calculated in tenths of seconds increments of time it is time bound system that can be defined as fixed time constraints in this type of system processing must be done inside the specified constraints otherwise the system will fail rtos is intended to serve real time application that process data as it comes in mostly without buffer delay it offers priority based scheduling which allows you to separate analytical processing from non critical processing components of rtos image https user images githubusercontent com 43001724 170870949 2064a6ca ee6b 4592 8360 1c4a0339f5cc png here are important component of rtos the scheduler this component of rtos tells that in which order the tasks can be executed which is generally based on the priority symmetric multiprocessing smp it is a number of multiple different tasks that can be handled by the rtos so that parallel processing can be done function library it is an important element of rtos that acts as an interface that helps you to connect kernel and application code this application allows you to send the requests to the kernel using a function library so that the application can give the desired results memory management this element is needed in the system to allocate memory to every program which is the most important element of the rtos fast dispatch latency it is an interval between the termination of the task that can be identified by the os and the actual time taken by the thread which is in the ready queue that has started processing user defined data objects and classes rtos system makes use of programming languages like c or c which should be organized according to their operation important components of rtos system are 1 the scheduler 2 symmetric multiprocessing 3 function library 4 memory management 5 fast dispatch latency 6 user defined data objects and classes three types of rtos 1 hard time 2 soft time 3 firm time rtos system occupy very less memory and consume fewer resources performance is the most important factor required to be considered while selecting for a rtos general purpose operating system gpos is used for desktop pc and laptop while real time operating system rtos only applied to the embedded application real time systems are used in airlines reservation system air traffic control system etc the biggest drawback of rtos is that the system only concentrates on a few tasks source guru99 resources link https drive google com file d 17fojfd6aaokzf2fazu5g6fvhqyxify q view usp sharing link configuration the configuration of the kernel is set in freertosconfig h configtotal heap size this must be enough space to allocate all tasks including the idle task if the kernel does t start it could be that the heap is too small examples description example 1 creating tasks example 2 led tasks example 3 led block task example 4 led periodic task example 5 led task notifty example 6 binary semaphore example 7 countingsemaphore example 8 queue timers task example 9 mutual exclusion example 10 queue management example 11 logging into sd card example 12 software timers example 13 ethernet udp server example 14 ethernet udp client note there is a problem about 001task and 002ledtasks exist a github submodule i will fix asap | freertos rtos linux | os |
vuetning | p align center img width 160 src https s3 amazonaws com arcthos com vuetning logo svg p vuetning vuetning https img shields io npm v vuetning svg https www npmjs org package vuetning npm downloads https img shields io npm dt vuetning svg https npmjs org package vuetning gzip size http img badgesize io https unpkg com vuetning dist vuetning common js compression gzip label gzip 20size introduction vuetning https marceloatg github io vuetning is a salesforce lightning design system framework for vue js 2 components name avaliability coverage documentation accordion src components slds accordion https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg activity timeline src components slds activity timeline https img shields io badge alpha yellow svg https img shields io badge 0 25 red svg https img shields io badge draft red svg alert src components slds alert https img shields io badge available green svg 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badge draft red svg menu src components slds menu https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg modal src components slds modal https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg multi picklist src components slds multi picklist https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg notifications src components slds notifications https img shields io badge mock red svg https img shields io badge 0 25 red svg https img shields io badge draft red svg page header src components slds page header https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg pagination src components slds pagination https img shields io badge available green svg https img shields io badge 0 25 red svg https img 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badge draft red svg tile src components slds tile https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg time picker src components slds time picker https img shields io badge mock red svg https img shields io badge 0 25 red svg https img shields io badge draft red svg toast src components slds toasts https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg tooltip src components slds tooltip https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg tree src components slds tree https img shields io badge mock red svg https img shields io badge 0 25 red svg https img shields io badge draft red svg tree grid src components slds tree grid https img shields io badge mock red svg https img shields io badge 0 25 red svg https img shields io badge draft red svg trial bar src components slds trial bar https img shields io badge mock red svg https img shields io badge 0 25 red svg https img shields io badge draft red svg vertical navigation src components slds vertical navigation https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg vertical tabs src components slds vertical tabs https img shields io badge mock red svg https img shields io badge 0 25 red svg https img shields io badge draft red svg virtual scroller src components slds virtual scroller https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg visual picker src components slds visual picker https img shields io badge mock red svg https img shields io badge 0 25 red svg https img shields io badge draft red svg welcome mat src components slds welcome mat https img shields io badge mock red svg https img shields io badge 0 25 red svg https img shields io badge draft red svg wide radio group src components slds wide radio group https img shields io badge available green svg https img shields io badge 0 25 red svg https img shields io badge draft red svg browser support vuetning is being developed in recent versions of chrome support for safari firefox edge and opera will be added in the future quick start cdn html doctype html html head link href https cdn jsdelivr net npm salesforce ux design system assets styles salesforce lightning design system min css rel stylesheet meta name viewport content width device width initial scale 1 maximum scale 1 user scalable no minimal ui head body div id app slds button brand label hello world div script src https cdn jsdelivr net npm vue dist vue js script script src https cdn jsdelivr net npm vuetning dist vuetning umd min js script script new vue el app script body html cdn links https cdn jsdelivr net npm vuetning dist vuetning umd min js https cdn jsdelivr net npm salesforce ux design system install inside a npm project vuetning is available as npm https www npmjs com package vuetning and yarn https yarnpkg com package vuetning packages bash npm npm install vuetning bash yarn yarn add vuetning usage in your main js or similar entry point install vuetning using all components javascript import vue from vue import vuetning from vuetning vue use vuetning or use individual components javascript import vue from vue import sldsbutton sldscombobox sldsmodal from vuetning vue use sldsbutton vue use sldscombobox vue use sldsmodal assets tbd license this project is licensed under the terms of the mit license license | vue slds salesforce lightning | os |
source-me | screenshot src assets images screenshot png source me source me is a cross platform desktop application which has some essential tools while making a project em version 0 2 1 em features strong material design colors by google https material io guidelines style color html strong the application contains a full stack of material designed colors created by google these can be very useful when one needs these colors at one place it uses a href https github com wwayne react tooltip react tooltip a to show the hex codes strong content delivery networks library by cdn https cdnjs com strong these are libraries provided by cdn in one place you can import the links to your project strong material designed icons by google https material io icons strong these are material designed icons made by google it is similar to the colors component strong epsum generator from bacon ipsum https baconipsum com strong a generator which generates standalone text which can be useful to your html mockups strong url shortner strong a url shortener which uses a free a href https is gd is gd a to shorten urls quickly strong emoji picker strong it is a picker which has a curated list of emojis click one of them amp you get the unicode strong image compressor strong a tool which compresses your images quickly it uses a href https github com xkeshi image compressor xkeshi image compressor a use a href https github com theiyd source me releases download the latest version of source me from the releases page a build the app can be used locally by following commands bash git clone https github com theiyd source me git cd source me npm install npm run dev strong the application has been abandoned and further updates have been stopped strong | electron-app javascript desktop-app jquery resourcepack html css | front_end |
pando-protocol | pando protocol pando protocol pando pando english document doc english document md pando pando pando pando sub device gateway internet pando command event status 1 pando 2 pando 3 pando coap mqtt mqtt http www pandocloud com img index 21 jpg 1 wifi 3g internet 2 spi usb images gateway flow png 1 internet 2 1 device id device key 2 product key 4 product key sn http api 5 product key device id device secret 4 3 1 device id device secret 2 http api doc http api md device id device secret device token access address device id device secret device id device secret 4 1 access address 2 device token device id device id device token device id token token 3 4 token token 5 1 i2c crc sequence ack ack sequence ack 3 sequence 1 sequence images hardeware data seq png internet ssl mqtt token 2 sub device id id id command num event num property num tlv type length value type value length value bytes string tlv device id id id timestamp token payload type payload length payload type payload length magic crc frame sequence flag 3 mqtt images data convert png 4 esp8266 stm32 esp8266 gpio gpio 3g internet 3g at stm32 5 doc universal event and command md c mqtt doc c mqtt implementation md pando embedded framework https github com pandocloud pando embedded framework linux issue https github com pandocloud pando protocol issues new issue https github com pandocloud pando protocol issues new qq 488074716 pando docs zh cn contribution work flow md doc universal event and command md c mqtt doc c mqtt implementation md http api doc http api md | server |
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predicting-poverty | combining satellite imagery and machine learning to predict poverty the data and code in this repository allows users to generate figures appearing in the main text of the paper combining satellite imagery and machine learning to predict poverty except for figure 2 which is constructed from specific satellite images paper figures may differ aesthetically due to post processing code was written in r 3 2 4 and python 2 7 users of these data should cite jean burke et al 2016 if you find an error or have a question please submit an issue links to related projects we are no longer maintaining this project but will link to related projects as we learn of them pytorch implementation https github com jmather625 predicting poverty replication description of folders data input and output data stored here figures notebooks used to generate figs 3 5 scripts scripts used to process data and produce fig 1 model store parameters for trained convolutional neural network packages required r r utils magrittr foreign raster readstata13 plyr rcolorbrewer sp lattice ggplot2 grid gridextra the user can run the following command to automatically install the r packages install packages c r utils magrittr foreign raster readstata13 plyr rcolorbrewer sp lattice ggplot2 grid gridextra dependencies t python numpy pandas scipy scikit learn seaborn geospatial data abstraction library gdal caffe caffe and pycaffe see caffe installation https github com bvlc caffe wiki installation we recommend using the open data science platform anaconda https www continuum io downloads instructions for processing survey data due to data access agreements users need to independently download data files from the world bank s living standards measurement surveys and the demographic and health surveys websites these two data sources require the user to fill in a data user agreement form in the case of the dhs data the user is also required to register for an account for all data processing scripts the user needs to set the working directory to the repository root folder 1 download lsms data 1 visit the host website for the world bank s lsms isa data http econ worldbank org wbsite external extdec extresearch extlsms 0 contentmdk 23512006 pagepk 64168445 pipk 64168309 thesitepk 3358997 00 html 2 download into data input lsms the files corresponding to the following country years 1 uganda 2011 2012 2 tanzania 2012 13 3 nigeria 2012 13 4 malawi 2013 update 08 02 2017 the lsms website has apparently recently removed two files from their database which contain crucial consumption aggregates for uganda 2011 12 and malawi 2013 since we are not at liberty to share those files ourselves this would inhibit replication of consumption analysis in those countries we have reached out and will update this page according to their response update 08 03 2017 the lsms has informed us these files were inadvertently removed and will be restored unchanged as soon as possible 3 unzip these files so that data input lsms contains the following folders of data 1 uga 2011 unps v01 m stata 2 tza 2012 lsms v01 m stata english labels 3 data formerly nga 2012 lsms v03 m stata before a re upload in january 2016 4 mwi 2013 ihps v01 m stata 2 download dhs data 1 visit the host website for the demographic and health surveys data http dhsprogram com data dataset admin download datasets cfm 2 download survey data into data input dhs the relevant data are from the standard dhs surveys corresponding to the following country years 1 uganda 2011 2 tanzania 2010 3 rwanda 2010 4 nigeria 2013 5 malawi 2010 3 for each survey the user should download its corresponding household recode files in stata format as well as its corresponding geographic datasets 4 unzip these files so that data input dhs contains the following folders of data 1 ug 2011 dhs 01202016 171 86173 2 tz 2010 dhs 01202016 173 86173 3 rw 2010 dhs 01312016 205 86173 4 ng 2013 dhs 01202016 1716 86173 5 mw 2010 dhs 01202016 1713 86173 note that the names of these folders may vary slightly depending on the date the data is downloaded 3 run the following files in the script folder 1 downloadpublicdata r 2 processsurveydata r 3 save survey data py instructions for extracting satellite image features 1 download the parameters of the trained cnn model here https www dropbox com s 4cmfgay9gm2fyj6 predicting poverty trained caffemodel dl 0 and save in the model directory 2 generate candidate locations to download using get image download locations py this will generate locations meant to download 1x1 km rgb satellite images of size 400x400 pixels for most of the countries locations for about 100 images in a 10x10 km area around the cluster is generated for nigeria and tanzania we generate about 25 evenly spaced points in the 10x10 km area the result of running this is a file for each country for each dataset named candidate download locs txt in the following format for every line image lat image long cluster lat cluster long for example a line in this file may be 4 163456 6 083456 4 123456 6 123456 note that this requires gdal and previously running downloadpublicdata r 3 download imagery from locations of interest e g cluster locations from nigeria dhs survey in this process successfully downloaded images must then have a corresponding line in a output metadata file named downloaded locs txt e g data output dhs nigeria downloaded locs txt there will be one of these metadata files for each country the format for each line of the metadata file must be for each line absolute path to image image lat image long cluster lat cluster long for example a line in this file may be abs path to img jpg 4 163456 6 083456 4 123456 6 123456 note that the last 4 fields in each line should be copied from the candidate download locs txt file for each country dataset pair 4 extract cluster features from satellite images using extract features py this will require installation of caffe and pycaffe see caffe installation https github com bvlc caffe wiki installation this may also require setting pycaffe in your pythonpath in each country s data folder e g data output dhs nigeria we save two numpy arrays conv features npy and image counts npy this process will be much faster if a sizable gpu is used with gpu true set in extract features py instructions for producing figures for all data processing scripts the user needs to set the working directory to the repository root folder if reproducing all figures the user does not need to rerun the data processing scripts or the image feature extraction process steps 1 2 for fig 1 steps 1 6 for figs 3 5 to generate figure 1 the user needs to run 1 downloadpublicdata r 2 processsurveydata r 3 fig1 r to generate figure 3 the user needs to run 1 downloadpublicdata r 2 processsurveydata r 3 save survey data py 4 get image download locations py 5 download images 6 extract features py 7 figure 3 ipynb https github com nealjean predicting poverty blob master figures figure 203 ipynb to generate figure 4 the user needs to run 1 downloadpublicdata r 2 processsurveydata r 3 save survey data py 4 get image download locations py 5 download images 6 extract features py 7 figure 4 ipynb https github com nealjean predicting poverty blob master figures figure 204 ipynb to generate figure 5 the user needs to run 1 downloadpublicdata r 2 processsurveydata r 3 save survey data py 4 get image download locations py 5 download images 6 extract features py 7 figure 5 ipynb https github com nealjean predicting poverty blob master figures figure 205 ipynb | ai |
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GwtMobile-PhoneGap | gwt mobile phonegap gwtmobile phonegap is a gwt wrapper of the phonegap http github com phonegap phonegap javascript library phonegap is a cross platform development framework that provides core mobile device features to web based mobile apps gwtmobile phonegap enables gwt mobile applications to use phonegap functions gwtmobile phonegap is part of gwt mobile http github com dennisjzh gwtmobile a gwt mobile development platform wrapped phonegap functions gwtmobile phonegap has wrapped the following phonegap functions accelerometer tap into the device s motion sensor camera capture a photo using the device s camera compass obtain the direction that the device is pointing contacts work with the device s contact database device gather device specific information events hook into native events through javascript file hook into native file system through javascript geolocation make your application location aware media record and play back audio files network quickly check the network state notification visual audible and tactile device notifications note the storage function is not currently wrapped as webkit browsers all support database now this function may become useful when phonegap works on windows mobile 7 phone which does not have in browser database support sample code the java code below showcases how to call phonegap functions in an gwt mobile application using gwtmobile phonegap for more code samples check out the kitchensink folder string watchid accelerometer watchacceleration new callback override public void onsuccess acceleration accel text settext watch acceleration nx accel getx ny accel gety nz accel getz override public void onerror text settext error new options frequency 100 apps that use gwt mobile phonegap gwt mobile phonegap a phonegap showcase app demonstrate all phonegap functions android market http market android com details id com gwtmobile phonegap itunes app store http itunes apple com us app gwt mobile phonegap showcase id419032500 mt 8 ls 1 fantasy predictor http www touchonmobile com manage all you fantasy football teams with the help of the fantasy predictor android market http market android com details id com touchonmobile fantasypredictor itunes app store http itunes apple com us app fantasy predictor id405605997 gwt mobile google group have a question post it on the gwt mobile google group http groups google com group gwtmobile | front_end |
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spark-design-system | build status https travis ci org sparkdesignsystem spark design system svg branch staging https travis ci org sparkdesignsystem spark design system spark design system welcome to the spark design system a product of rocket mortgage spark design system is where we collect our best solutions for how to design and build unified digital experiences for the rocket brands spark https www npmjs com package sparkdesignsystem spark contains the basic patterns and components that make up the visual and interaction design of the rocket mortgage family of fintech products if your application is expected to look and behave like a rocket mortgage application this package is the starting point when the spark sass and js setup files are imported into an application you will receive code for all of spark getting started spark assumes your project is using sass https sass lang com for styling and also that your project has a javascript build step that will transpile es6 and polyfill appropriately for browser support spark install the npm package npm install save dev sparkdesignsystem spark import the sass setup file in your sass build import node modules sparkdesignsystem spark styles spark scss this will bring all spark sass patterns into your build the spark classes are namespaced so they don t affect any existing css import the js setup file in your js build import spark from node modules sparkdesignsystem spark spark this will bring all spark js into your build contribution guide code organization spark is managed as a monorepo all of the spark source code lives in a single repo but is released as separate packages this repo consists of the design system packages wrapped in an instance of gatsby https www gatsbyjs org spark uses gatsby for our main documentation site and storybook https storybook js org for our component previews and developer documentation in the root there are three directories react angular and html these house the files that are published to npm dev environment if you want to run a copy of gatsby locally 1 navigate to the root directory of the project 2 run npm install 3 run npm start 4 open your browser to http localhost 8000 if you want to run a copy of gatsby and storybook locally 1 navigate to the root directory of the project 2 run npm run installall 3 run npm start to start gatsby then open your browser to http localhost 8000 4 run cd react npm run storybook to start storybook for react 5 run cd angular npm run storybook to start storybook for angular 6 run cd html npm run storybook to start storybook for html unit tests spark uses the jest https jestjs io test framework for unit tests to run unit tests in spark 1 navigate to the framework directory of your choice from the root cd react cd angular or cd html 2 run npm install if you have not already 3 run npm test 4 see test output in terminal to determine number of passing or failed tests code style standards spark follows specific coding styles for html css and javascript to ensure maintainability and scalability html two spaces for indentation for better code readability the attributes of elements should each be on their own line when the number of attributes makes that element exceed a line length of 80 characters css two spaces for indentation css is written in sass https sass lang com and preprocessed into css class naming conventions can be found here https sparkdesignsystem com docs class naming convention stylelint https github com stylelint stylelint is used to lint sass files and all of spark sass coding conventions can be found in the stylelint configuration file https github com sparkdesignsystem spark design system blob main stylelintrc js two spaces for indentation spark js will use new features from esnext and assumes applications using spark have a javascript compiler setup spark uses eslint https eslint org for js linting eslint is setup to use the airbnb javascript style guide https github com airbnb javascript and spark js coding conventions come from there data attributes on dom elements is the chosen method for dom selection react and angular for additionalclasses properties use the naming convention elementadditionalclasses for other elements that we offer additional classes support on besides the main element change workflow coming soon credit gatsby https www gatsbyjs org storybookjs https storybook js org | spark design-system design-patterns hacktoberfest | os |
Gardening-Store_Backend_MicroServices | gardening store backend microservices my mini project for app development course backend microservices implementation using springtool suite project overview an online store for organic veggies and fruits is a web application that allows customers to purchase fresh organic produce online it provides a platform for farmers suppliers or grocery stores specializing in organic products to showcase and sell their produce to consumers key features of online store for gardening typically includes 1 product catalog the web application features a comprehensive catalog of gardening products categorized into various sections such as tools equipment plants seeds fertilizers pesticides garden decor and more each product listing includes detailed information images pricing and customer reviews 2 search and filtering users can search for specific gardening products or use filtering options to narrow down their search based on categories brands prices ratings and other criteria this helps users find the desired products more efficiently 3 product details each product listing provides detailed information about the gardening items including specifications features usage instructions and customer reviews users can access this information to make informed purchase decisions 4 shopping cart and checkout users can add gardening products to their shopping cart as they browse through the catalog the web application allows users to review their cart adjust quantities and proceed to the secure checkout process users provide shipping details select a payment method and confirm the order 5 payment integration the web application integrates with secure payment gateways to facilitate smooth and secure online transactions customers can use various payment methods such as credit cards debit cards or digital wallets to complete their purchases 6 order tracking after completing a purchase users can track the status of their orders the web application provides order tracking functionality enabling users to monitor the progress of their shipments and receive updates on delivery dates 7 customer accounts customers can create accounts on the web application to save their delivery addresses track order history and manage preferences this feature provides a personalized experience and facilitates easy reordering in the future 8 reviews and ratings customers can leave reviews and ratings for products they purchase this feedback helps other customers make informed decisions and provides valuable insights to the store about the quality of their products 9 support and customer service the web application provides customer support and assistance to address any inquiries or concerns this can include faqs chat support or contact forms to ensure a positive shopping experience | backend feedback java microservices spring-boot springtoolsuite | server |
awry | are we rtos yet ci https github com newam awry workflows ci badge svg https github com newam awry actions this is the repository for arewertosyet com contributing pull requests are always welcome the website uses the rust mdbook check out their documentation for information on how to install and build the html from markdown mdbook https rust lang github io mdbook arewertosyet com https arewertosyet com | rtos rust embedded | os |
mern-starter | mern app starter template a simple mern app starter template | server |
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Kaggle-Computer-Vision-Competitions-List | kaggle computer vision competitions list list of kaggle competitions in the field of computer vision https www kaggle com c digit recognizer https www kaggle com c dogs vs cats submission disabled https www kaggle com c dogs vs cats redux kernels edition https github com mrgloom kaggle dogs vs cats solution digits caffe https www kaggle com c diabetic retinopathy detection https www kaggle com c facial keypoints detection https www kaggle com c datasciencebowl https www kaggle com c data science bowl 2018 to look at https github com amirassov data science bowl https www kaggle com c galaxy zoo the galaxy challenge https www kaggle com c challenges in representation learning facial expression recognition challenge https www kaggle com c challenges in representation learning the black box learning challenge https www kaggle com c challenges in representation learning multi modal learning https www kaggle com c yelp restaurant photo classification https www kaggle com c draper satellite image chronology https www kaggle com c wic2011 description https www kaggle com c awic2012 description https www kaggle com c avito duplicate ads detection https www kaggle com c state farm distracted driver detection https www kaggle com c noaa right whale recognition to look at https www kaggle com c noaa right whale recognition discussion 16328 https www kaggle com c shelter animal outcomes https www kaggle com c leaf classification https www kaggle com c the nature conservancy fisheries monitoring https www kaggle com c icdar2013 gender prediction from handwriting data https www kaggle com c multi modal gesture recognition https www kaggle com c ultrasound nerve segmentation https www kaggle com c second annual data science bowl https www kaggle com c dstl satellite imagery feature detection https www kaggle com c noaa fisheries steller sea lion population count https github com mrgloom kaggle sea lions solution keras https www kaggle com c planet understanding the amazon from space to look at https github com mratsim amazon forest computer vision https www kaggle com c intel mobileodt cervical cancer screening https www kaggle com c carvana image masking challenge to look at https github com asanakoy kaggle carvana segmentation to look at https github com petrosgk kaggle carvana image masking challenge to look at https github com lyakaap kaggle carvana 3rd place solution to look at https github com ternaus ternausnet to look at https github com killthekitten kaggle carvana 2017 https www kaggle com c cdiscount image classification challenge https www kaggle com c dog breed identification https www kaggle com c statoil iceberg classifier challenge https www kaggle com c data science bowl 2018 https www kaggle com c tgs salt identification challenge to look at https github com lromul argus tgs salt https www kaggle com c sp society camera model identification to look at https github com cepera ang kaggle sp society camera model identification https www kaggle com c humpback whale identification https www kaggle com c imet 2019 fgvc6 data to look at https github com lopuhin kaggle imet 2019 https www kaggle com c landmark retrieval challenge https www kaggle com c imaterialist fashion 2019 fgvc6 to look at https github com amirassov kaggle imaterialist https www kaggle com c siim acr pneumothorax segmentation https www kaggle com c severstal steel defect detection https www kaggle com c rsna intracranial hemorrhage detection https www kaggle com c airbus ship detection https www kaggle com c generative dog images https www kaggle com c gan getting started weakly related to computer vision https www kaggle com c two sigma connect rental listing inquiries https github com mrgloom kaggle two sigma connect rental listing inquiries feature visualization caffe sklearn other https github com iphysresearch datascicomp | ai |
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PYNQ-ComputerVision | pynq computer vision all pynq releases ship with the popular opencv https opencv org library pre installed the pynq computer vision overlays enable accelerating opencv components in programmable logic pl these overlays expose a subset xilinx xfopencv https github com xilinx xfopencv library a part of xilinx revision solution https www xilinx com products design tools embedded vision zone html at the python level combined with the support for hdmi input output pynq z1 and pynq z2 only webcam stream or file based input output remains available through the pre installed sw opencv on all pynq boards currently this package is compatible with pynq image v2 4 http www pynq io board block diagram png a number of prebuilt overlays are available for your pynq enabled board for example pynq z1 pynq z2 2d filter dilate accelerated 3x3 2d filter and 3x3 dilate see filter2d and dilate ipynb boards pynq z1 notebooks filter2d and dilate ipynb 2d filter remap accelerated 3x3 2d filter and remap see filter2d and remap ipynb boards pynq z1 notebooks filter2d and remap ipynb ultra96 2d filter dilate absdiff see 2 overlays filter2d and dilate ipynb boards ultra96 notebooks 2 overlays filter2d and dilate ipynb remap stereobm see 3a overlays stereo block matching ipynb boards ultra96 notebooks 3a overlays stereo block matching ipynb optical flow see 4 overlays opticalflow ipynb boards ultra96 notebooks 4 overlays opticalflow ipynb quick start to install the computer vision overlay example on your board open a terminal and run bash sudo pip3 install upgrade git https github com xilinx pynq computervision git after the setup new jupyter notebooks will be added under the pynqopencv folder ready to try out no additional steps are needed building your own overlay when after profiling the critical opencv modules in an application are identified the generation of a tailored overlay is easily done by specifying those modules as a list in a cmake project file after that building the tailored overlay only requires running cmake to generate the makefiles followed by make to build the overlay for detailed instructions building xfopencv overlays for pynq cmake based sds cross compilation overlays readme md currently this only supports building on the ultra96 with 2018 3 xilinx tools license source files 3 clause bsd license license sdsoc platform multiple license file https www xilinx com member forms download xef html filename pynq ultra96 dsa license ca txt sysroot license and copyrights info tar gzip https www xilinx com member forms download xef html filename pynq v2 3 license tar gz open components source code tar gzip https www xilinx com member forms download xef html filename pynq v2 3 open components tar gz | pynq | ai |
KnowledgeEditingPapers | knowledge editing for llms papers awesome https awesome re badge svg https github com zjunlp modeleditingpapers license mit https img shields io badge license mit green svg https opensource org licenses mit https img shields io github last commit zjunlp modeleditingpapers color green https img shields io badge prs welcome red must read papers on knowledge editing https arxiv org abs 2305 13172 for large language models news 2023 10 22 our paper can we edit multimodal large language models https arxiv org abs 2310 08475 has been accepted by emnlp 2023 2023 10 08 our paper editing large language models problems methods and opportunities https arxiv org abs 2305 13172 has been accepted by emnlp 2023 2023 8 15 we release the paper easyedit an easy to use knowledge editing framework for large language models https arxiv org abs 2308 07269 2023 07 we release easyedit https github com zjunlp easyedit an easy to use knowledge editing framework for llms 2023 06 we will provide a tutorial on editing large language models at aacl 2023 2023 05 we release a new analysis paper editing large language models problems methods and opportunities https arxiv org abs 2305 13172 based on this repository we are looking forward to any comments or discussions on this topic 2022 12 we create this repository to maintain a paper list on knowledge editing contents why knowledge editing why knowledge editing keywords keywords papers papers overview overview methods methods preserve parameters preserve parameters memory based memory based additional parameters additional parameters modify parameters modify parameters finetuning finetuning meta learning meta learning locate and edit locate and edit more related papers more related papers analysis analysis resources resources benchmarks and tasks benchmarks and tasks tools tools contribution contribution contributors contributors contributing to this paper list contributing to this paper list acknowledgement acknowledgement citation citation why knowledge editing knowledge editing is a compelling field of research that focuses on facilitating efficient modifications to the behavior of models particularly foundation models the aim is to implement these changes within a specified scope of interest without negatively affecting the model s performance across a broader range of inputs keywords knowledge editing has strong connections with following topics updating and fixing bugs for large language models language models as knowledge base locating knowledge in large language models lifelong learning unlearning and etc security and privacy for large language models papers this is a collection of research and review papers of knowledge editing any suggestions and pull requests are welcome for better sharing of latest research progress overview editing large language models problems methods and opportunities paper https arxiv org abs 2305 13172 div align center img src img overview jpg width 100 height 80 div methods preserve parameters memory based 1 memory based model editing at scale icml 2022 br eric mitchell charles lin antoine bosselut christopher d manning chelsea finn paper https arxiv org abs 2206 06520 code https github com eric mitchell serac demo https sites google com view serac editing 2 fixing model bugs with natural language patches emnlp 2022 br shikhar murty christopher d manning scott m lundberg marco t lio ribeiro paper https arxiv org abs 2211 03318 code https github com murtyshikhar languagepatching 3 memprompt memory assisted prompt editing with user feedback emnlp 2022 br aman madaan niket tandon peter clark yiming yang paper https arxiv org abs 2201 06009 code https github com madaan memprompt page https memprompt com video https www youtube com watch v ld7r02boinq t 1s 4 large language models with controllable working memory br daliang li ankit singh rawat manzil zaheer xin wang michal lukasik andreas veit felix yu sanjiv kumar paper https arxiv org abs 2211 05110 5 can we edit factual knowledge by in context learning br ce zheng lei li qingxiu dong yuxuan fan zhiyong wu jingjing xu baobao chang paper https arxiv org abs 2305 12740 6 can lms learn new entities from descriptions challenges in propagating injected knowledge br yasumasa onoe michael j q zhang shankar padmanabhan greg durrett eunsol choi paper https arxiv org abs 2305 01651 7 mquake assessing knowledge editing inlanguage models via multi hop questions br zexuan zhong zhengxuan wu christopher d manning christopher potts danqi chen br paper https arxiv org abs 2305 14795 additional parameters 1 calibrating factual knowledge in pretrained language models emnlp 2022 br qingxiu dong damai dai yifan song jingjing xu zhifang sui lei li paper https arxiv org abs 2210 03329 code https github com dqxiu calinet 2 transformer patcher one mistake worth one neuron iclr 2023 br zeyu huang yikang shen xiaofeng zhang jie zhou wenge rong zhang xiong paper https arxiv org abs 2301 09785 code https github com zeroyuhuang transformer patcher 3 aging with grace lifelong model editing with discrete key value adaptors br thomas hartvigsen swami sankaranarayanan hamid palangi yoon kim marzyeh ghassemi paper https arxiv org abs 2211 11031 code https github com thartvigsen grace 4 neural knowledge bank for pretrained transformers br damai dai wenbin jiang qingxiu dong yajuan lyu qiaoqiao she zhifang sui paper http arxiv org abs 2208 00399 change lm s representation space 1 inspecting and editing knowledge representations in language models br evan hernandez belinda z li jacob andreas paper http arxiv org abs 2304 00740 code https github com evandez remedi modify parameters finetuning 1 plug and play adaptation for continuously updated qa acl 2022 findings br kyungjae lee wookje han seung won hwang hwaran lee joonsuk park sang woo lee paper https arxiv org abs 2204 12785 code https github com wookjehan plug and play adaptation for continuously updated qa 2 modifying memories in transformer models br chen zhu ankit singh rawat manzil zaheer srinadh bhojanapalli daliang li felix yu sanjiv kumar paper https arxiv org abs 2012 00363 meta learning 1 editing factual knowledge in language models br nicola de cao wilker aziz ivan titov emnlp 2021 paper https arxiv org abs 2104 08164 code https github com nicola decao knowledgeeditor 2 fast model editing at scale iclr 2022 br eric mitchell charles lin antoine bosselut chelsea finn christopher d manning paper https arxiv org abs 2110 11309 code https github com eric mitchell mend page https sites google com view mend editing 3 editable neural networks iclr 2020 br anton sinitsin vsevolod plokhotnyuk dmitry v pyrkin sergei popov artem babenko paper https arxiv org abs 2004 00345 code https github com xtinkt editable locate and edit 1 editing a classifier by rewriting its prediction rules neurips 2021 br shibani santurkar dimitris tsipras mahalaxmi elango david bau antonio torralba aleksander madry paper https proceedings neurips cc paper 2021 hash c46489a2d5a9a9ecfc53b17610926ddd abstract html code https github com madrylab editingclassifiers 2 language anisotropic cross lingual model editing br yang xu yutai hou wanxiang che paper https arxiv org abs 2205 12677 3 repairing neural networks by leaving the right past behind br ryutaro tanno melanie f pradier aditya nori yingzhen li paper https arxiv org abs 2207 04806 4 locating and editing factual associations in gpt neurips 2022 br kevin meng david bau alex andonian yonatan belinkov paper https arxiv org abs 2202 05262 code https github com kmeng01 rome page https rome baulab info video https www youtube com watch v nmqyou2hto t 0 5 mass editing memory in a transformer br kevin meng arnab sen sharma alex andonian yonatan belinkov david bau paper https arxiv org abs 2210 07229 code https github com kmeng01 memit page https memit baulab info demo https memit baulab us 6 editing models with task arithmetic br gabriel ilharco marco tulio ribeiro mitchell wortsman ludwig schmidt hannaneh hajishirzi ali farhadi paper https openreview net pdf id 6t0kwf8 jrj 7 editing commonsense knowledge in gpt br anshita gupta debanjan mondal akshay krishna sheshadri wenlong zhao xiang lorraine li sarah wiegreffe niket tandon paper https arxiv org abs 2305 14956 8 do language models have beliefs methods for detecting updating and visualizing model beliefs br peter hase mona diab asli celikyilmaz xian li zornitsa kozareva veselin stoyanov mohit bansal srinivasan iyer paper https arxiv org pdf 2111 13654 pdf code https github com peterbhase slag belief updating 9 detecting edit failures in large language models an improved specificity benchmark br jason hoelscher obermaier julia persson esben kran ioannis konstas fazl barez paper https arxiv org abs 2305 17553 10 knowledge neurons in pretrained transformers acl 2022 br damai dai li dong yaru hao zhifang sui baobao chang furu wei paper http arxiv org abs 2104 08696 code https github com hunter ddm knowledge neurons code by eleutherai https github com eleutherai knowledge neurons 11 leace perfect linear concept erasure in closed form br nora belrose david schneider joseph shauli ravfogel ryan cotterell edward raff stella biderman paper https arxiv org abs 2306 03819 12 transformer feed forward layers are key value memories emnlp 2021 br mor geva roei schuster jonathan berant omer levy paper https arxiv org abs 2012 14913 13 transformer feed forward layers build predictions by promoting concepts in the vocabulary space emnlp 2022 br mor geva avi caciularu kevin ro wang yoav goldberg paper https arxiv org abs 2203 14680 14 pmet precise model editing in a transformer br xiaopeng li shasha li shezheng song jing yang jun ma jie yu paper https arxiv org abs 2308 08742 code https github com xpq tech pmet git 15 unlearning bias in language models by partitioning gradients acl 2023 findings br charles yu sullam jeoung anish kasi pengfei yu heng ji paper https aclanthology org 2023 findings acl 375 pdf code https github com charlesyu2000 pcgu unlearningbias more related papers 1 fruit faithfully reflecting updated information in text naacl 2022 br robert l logan iv alexandre passos sameer singh ming wei chang paper code 2 entailer answering questions with faithful and truthful chains of reasoning emnlp 2022 br oyvind tafjord bhavana dalvi mishra peter clark paper https arxiv org abs 2210 12217 code https github com allenai entailment bank video https www youtube com watch v gytj pxva7q 3 towards tracing factual knowledge in language models back to the training data br ekin aky rek tolga bolukbasi frederick liu binbin xiong ian tenney jacob andreas kelvin guu emnlp 2022 paper https arxiv org abs 2204 12785 4 prompting gpt 3 to be reliable br chenglei si zhe gan zhengyuan yang shuohang wang jianfeng wang jordan boyd graber lijuan wang paper https arxiv org abs 2210 09150 5 patching open vocabulary models by interpolating weights neurips 2022 br gabriel ilharco mitchell wortsman samir yitzhak gadre shuran song hannaneh hajishirzi simon kornblith ali farhadi ludwig schmidt paper https arxiv org abs 2208 05592 code https github com mlfoundations patching 6 decouple knowledge from paramters for plug and play language modeling acl2023 findings br xin cheng yankai lin xiuying chen dongyan zhao rui yan paper http arxiv org abs 2305 11564 code https github com hannibal046 pluglm 7 backpack language models br john hewitt john thickstun christopher d manning percy liang paper https arxiv org pdf 2305 16765 pdf 8 learning to model editing processes emnlp 2022 br machel reid graham neubig paper https aclanthology org 2022 findings emnlp 280 pdf analysis 1 does localization inform editing surprising differences in causality based localization vs knowledge editing in language models br peter hase mohit bansal been kim asma ghandeharioun paper https arxiv org pdf 2301 04213 pdf code https github com google belief localization 2 dissecting recall of factual associations in auto regressive language models br mor geva jasmijn bastings katja filippova amir globerson paper https arxiv org abs 2304 14767 3 evaluating the ripple effects of knowledge editing in language models br roi cohen eden biran ori yoran amir globerson mor geva paper https arxiv org abs 2307 12976 4 edit at your own risk evaluating the robustness of edited models to distribution shifts br davis brown charles godfrey cody nizinski jonathan tu henry kvinge paper https arxiv org abs 2303 00046 5 journey to the center of the knowledge neurons discoveries of language independent knowledge neurons and degenerate knowledge neurons br yuheng chen pengfei cao yubo chen kang liu jun zhao paper https arxiv org abs 2308 13198 6 linearity of relation decoding in transformer language models br evan hernandez martin wattenberg arnab sen sharma jacob andreas tal haklay yonatan belinkov kevin meng david bau paper https arxiv org pdf 2308 09124 pdf 7 klob a benchmark for assessing knowledge locating methods in language models br yiming ju zheng zhang paper http export arxiv org pdf 2309 16535 8 inference time intervention eliciting truthful answers from a language model neurips 2023 br kenneth li oam patel fernanda vi gas hanspeter pfister martin wattenberg paper https arxiv org abs 2306 03341 code https github com likenneth honest llama 9 emptying the ocean with a spoon should we edit models emnlp 2023 findings br yuval pinter and michael elhadad paper https arxiv org pdf 2310 11958 pdf 10 unveiling the pitfalls of knowledge editing for large language models br zhoubo li ningyu zhang yunzhi yao mengru wang xi chen and huajun chen paper https arxiv org pdf 2310 02129 pdf 10 editing personality for llms br shengyu mao ningyu zhang xiaohan wang mengru wang yunzhi yao yong jiang pengjun xie fei huang and huajun chen paper https arxiv org pdf 2310 02168 pdf resources benchmarks and tasks edit type benchmarks datasets fact knowledge zsre https github com nicola decao knowledgeeditor zsre plus https arxiv org abs 2305 13172 counterfact https rome baulab info counterfact plus https arxiv org abs 2305 13172 counterfact https arxiv org abs 2305 17553 ecbd https github com yasumasaonoe entity knowledge propagation mquake https github com yasumasaonoe entity knowledge propagation multi lingual bi zsre https arxiv org pdf 2309 08952 pdf eva kellm https arxiv org pdf 2308 09954 pdf sentiment convsent https arxiv org abs 2206 06520 bias bias in bios https arxiv org pdf 2304 00740 pdf hallucination wikibio https github com thartvigsen grace tree main commonsense memit sub csk sub https arxiv org abs 2305 14956 reasoning eva kellm https arxiv org pdf 2308 09954 pdf privacy infomation protect privqa https arxiv org abs 2310 02224 knowledge sanitation https arxiv org pdf 2309 11852 pdf toxic information realtoxicityprompts https arxiv org abs 2009 11462 multimodal mmedit https arxiv org abs 2310 08475 logical reasoning proofwriter https arxiv org abs 2012 13048 entailmentbank https arxiv org abs 2104 08661 ruletaker https www ijcai org proceedings 2020 537 clutrr https aclanthology org d19 1458 multimodal reasoning scienceqa https scienceqa github io others big bench https doi org 10 48550 arxiv 2206 04615 scan http proceedings mlr press v80 lake18a html chain of thought hub https arxiv org abs 2305 17306 tools easyedit https github com zjunlp easyedit an easy to use knowledge editing framework for large language models fastedit https github com hiyouga fastedit editing large language models within 10 seconds citation please cite our paper if find our work useful bibtex article dblp journals corr abs 2305 13172 author yunzhi yao and peng wang and bozhong tian and siyuan cheng and zhoubo li and shumin deng and huajun chen and ningyu zhang title editing large language models problems methods and opportunities journal corr volume abs 2305 13172 year 2023 url https doi org 10 48550 arxiv 2305 13172 doi 10 48550 arxiv 2305 13172 eprinttype arxiv eprint 2305 13172 timestamp tue 30 may 2023 17 04 46 0200 biburl https dblp org rec journals corr abs 2305 13172 bib bibsource dblp computer science bibliography https dblp org contribution contributors a href https github com zjunlp modeleditingpapers graphs contributors img src https contrib rocks image repo zjunlp modeleditingpapers a contributing to this paper list there are cases where we miss important works in this field please contribute to this repo thanks for the efforts in advance acknowledgement we would like to express our gratitude to longhui yu https yulonghui github io for the kind reminder about the missing papers | paper-list pre-trained-language-models pre-trained-model knowledge-editing model-editing large-language-models awsome-list foundation-models natural-language-processing review survey rome easyedit knowlm paper | ai |
ML-examples | ipython notebook br http blog csdn net han xiaoyang br hanxiaoyang ml gmail com | ai |
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NLPython | all the codes are related to my book entitled python natural language processing https www amazon com python natural language processing techniques dp 1787121429 ref mt paperback encoding utf8 me this repository contains the code related to natural language processing using python scripting language details of the book 1 introduction 2 practical understanding of corpus and data set 3 understanding structure of sentences 4 preprocessing 5 feature engineering and nlp algorithms 6 advance feature engineering and nlp algorithms 7 rule based system for nlp 8 machine learning for nlp problems 9 deep learning for nlu and nlg problems 10 appendix a 11 appendix b 12 appendix c nlpython join the chat at https gitter im nlpython lobby https badges gitter im nlpython lobby svg https gitter im nlpython lobby utm source badge utm medium badge utm campaign pr badge utm content badge you can join this gitter room for further discusstion | natural-language-processing python-scripting-language deep-learning text-mining parsing part-of-speech feature-engineering feature-extraction feature-selection python2 | ai |
Freeform-Tolerance-Specification-and-PCI-Analysis | code and data complement of a framework of tolerance specification for freeform point clouds and capability analysis for reverse engineering processes this repo includes all the code and jupyter notebooks for the paper a framework of tolerance specification for freeform point clouds and capability analysis for reverse engineering processes written by zhaohui geng arman sabbaghi and bopaya bidanda which to be published in the international journal of production research https doi org 10 1080 00207543 2022 2086083 due the size limitation of github the whole data grid is compressed please uncompress before implementing the code | cloud |
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ME_CE_Details | me ce details me cloud engineering some insights on how we can make a secure cloud environment | cloud |
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WebX | webx webx is a platform which focuses on providing various free web development tools and inspiration all at one place you can have a look at the website here https yashikabhargava github io webx built with img alt html5 src https img shields io badge html5 20 23e34f26 svg style for the badge logo html5 logocolor white img alt css3 src https img shields io badge css3 20 231572b6 svg style for the badge logo css3 logocolor white img alt javascript src https img shields io badge javascript 20 23323330 svg style for the badge logo javascript logocolor 23f7df1e contribution is fun in order to make a hassle free environment i implore you all while contributing to follow the code of conduct https github com yashikabhargava webx blob main code of conduct md and read the contribution guidelines https github com yashikabhargava webx blob main contributing md happy submissions screenshots img src src img screenshot1 png img src src img screenshot2 png img src src img screenshot3 png | css hacktoberfest html javascript hacktoberfest2022 | front_end |
auction | documentation status https readthedocs org projects itpeople blockchain auction badge version latest http itpeople blockchain auction readthedocs io en latest badge latest art auction blockchain application credits ratnakar asara nishi nidamarty ramesh thoomu adam gordon and mohan venkataraman disclaimer the images used in this sample poc application have been downloaded from publicly available images on the internet and the copyright belongs to the respective owners the usage here is strictly for non commercial purposes as sample data we recommend that users create their own sample data as appropriate all names addresses and accounts numbers used in the sample data are fictitous the information provided in this readme md is subject to change auction chaincode is migrated to fabric v1 0 and these changes being tested on fabric commit 5b59e0652f9edf5bd12a6ff7fd2e9991495190fe introduction this hyperledger fabric is an implementation of blockchain technology leveraging familiar and proven technologies it is a modular architecture allowing pluggable implementations of various function it features powerful container technology to host any mainstream language for smart contracts development chaincode smart contracts or blockchain applications run on the fabric chaincode is written in go language the original intention of this application was to understand how to write a go application on the hyperledger fabric this initial version was written to understand the different chaincode api s the boundary that separates what goes into the blockchain and what lives within the enterprise application usage of database features error management etc br br img src docs images auction chain png width 700 application description this application deals with auctioning art on the block chain the blockchain makes sense here as there are many different stakeholders and can leverage the benefits of the network effect this application deals with the following stake holders buyers and sellers or traders trd banks bnk insurance companies ins shipping and forwarding shp auction houses ah art dealers del artists art the typical business process is shown below business process docs images art process png registering stakeholder accounts artists traders dealers own assets items auction houses banks insurance companies and service providers play a role in the auction process to conduct business on the block chain the stakeholder has to open an account on the block chain in the production world prior to opening an account all of the stake holder details may be authenticated by another blockchain like an idaas identity as a service there are various stake holders as listed above each with a different interest registering assets or items the seller trader who owns assets must register the asset on the block chain in order to conduct business when an asset is submitted for registration the chaincode does the following checks if the owner has a registered account converts any presented certificate of authenticity or a credibly issued image to a byte stream generates a key encrypts the byte stream using the key and stores the image on the bc provides the key to the owner for safe keeping and future reference makes entries into the item history so that the lifecycle of the asset can be reviewed at any time making a request to auction an asset when the owner of an asset sees an opportunity to make money they would like to auction the asset they engage an auction house and make a request to auction the asset the request always specifies a reserve price sometimes the owner may additionally specify a buy it now price as well when the request is made the item owner and the auction house are all validated the chaincode simply validates that they are all registered on the bc the auction house will most likely behind the scene get the asset authenticated and determine the valuation before deciding to accept the item one of the ways by which they could do some preliminary authentication is to request the seller to enter his private key account id and the registered item number into the client application while the item number and account identifier is a straight validation the key will be used to decrypt and retrieve the stored certificate of authenticity or image the state of the auction is set to init at this point until the auction house is ready to open the asset for bids opening the auction for bids the auction house will choose a time frame to place the item on auction and open it up for accepting bids from potential buyers they may if applicable advertise the buyitnow price buy it now and accepting bids during the window of the auction potential buyers can place bids if a buyer wishes to exercise the buy it now they can buy the item right away provided there is no bid higher than the buyitnow price bids are accepted from buyers if the bids have are equal or greater than the reserve price the auction is still open the buyer has a registered account buy it now when a buyer chooses this option the chain code does the following validates the buyer checks if there are any bidders whose bid is higher than the buy it now price if so the offer is rejected if the buy it now price is applicable it immediately closes the auctions creates a transaction it assigns the asset to the new owner it also generates a new key re encrypts the certificate of ownership or image and provides the key to the new buyer the new price of the asset is set to the buy it now price if not higher auction expiry when the auction expires the auction house retrieves the highest bid and converts it to a transaction a transaction in the real world could mean creating insurance and shipping docs collecting payments and commissions issuing a new title or certificate to the new owner etc transfers ownership to the buyer and updates the price with the new hammer price it also generates a new key re encrypts the certificate of ownership or image and provides the key to the new buyer transfer an item to another user the chain code supports this scenario by allowing a owner of an asset to transfer ownership to another person the receiving person has to be registered on the block chain currently the chain code does not execute any regulatory or compliance rules validating asset ownership the chain code supports this in order to accomplish this it does preliminary authentication by requesting the seller to enter his private key account id and the registered item number while the item number and account identifier is a straight validation the key will be used to decrypt and view the stored certificate of authenticity or image if decryption fails then it assumes that the owner is not the legal owner of the asset apis available the following invoke and query apis are available from both cli and rest and have the following signature func stub shim chaincodestub function string args string byte error invoke ipostuser ipostitem ipostauctionrequest iposttransaction ipostbid iopenauctionforbids ibuyitnow itransferitem icloseauction icloseopenauctions query qgetitem qgetuser qgetauctionrequest qgettransaction qgetbid qgetlastbid qgethighestbid qgetnoofbidsreceived qgetlistofbids qgetitemlog qgetitemlistbycat qgetuserlistbycat qgetlistofitemsonauc qgetlistofopenaucs qvalidateitemownership qisitemonauction environment setup please review instructions on setting up the development environment https github com hyperledger fabric blob master docs source dev setup devenv rst as well as the setting up the sandbox environment https github com hyperledger fabric blob master docs source setup chaincode setup rst to execute the chaincode running the application fork and clone the fabric git clone https github com hyperledger fabric git cd gopath src github com hyperledger fabric fork auction git repository from here https github com itpeople blockchain auction git and clone from your remote auction repository git clone https github com username auction git execute below command to clear production data rm rf var hyperledger terminal 1 build peer and orderer binaries and start orderer cd gopath src github com hyperledger fabric make native orderer terminal 2 start peer cd gopath src github com hyperledger fabric peer node start o 127 0 0 1 7050 terminal 3 cd gopath src github com hyperledger fabric auction art scripts run env sh script to export core peer mspconfigpath source env sh run the following shell scripts the scripts are provided for the convenience of understanding how to use the application as well as testing in your specific cloned environment the scripts execute all api calls in cli mode in cli mode the peer and the chaincode live within the same container however these scripts will not work well in net mode to test the application in net mode follow the instructions on using the ui to make the api calls postusers the postusers script inserts a set of users into the database today the only validation done is to check if the user id is an integer todo in a future version the user identity will be validated against the idaas blockchain prior to inserting into the database postusers postitems the postitems script inserts a set of art assets into the database before inserting the asset the chaincode checks if the currentowner is registered as a user based on the image file name in future this could be a title or some ownership document is retrieved and converted to a byte array byte an aes key is generated the byte array is encrypted and both key and the byte array are saved in the database a log entry is made in the item log please see code for detailed comments postitems in the business process the owner user id 100 of the asset item 1000 requests an entity like an auction house user id 200 to put the item on auction before posting the auction request the asset is validated against the database the auction house id is verified in the user table a log entry is made in the item log todo in future the owner of the asset will present his key to help with validation the aes key will be used to un encrypt the stored image and authenticate asset ownership postauctionrequest when the asset owner of an item is ready to place his item on auction he she would identify an auction house determine what the reserve price should be and send a request to the auction house expressing interest in placing their item on the auction block postauctionrequest openauctionrequestforbids the auction house we assume will inspect the physical item the certificate of authenticity the ownership key and other details they would also run a valuation of the item to determine if the reserve price is valid the application assumes these have occurred outside of the scope of the application even though the asset owner has requested the auction house to place the item on auction the auction is not yet open for acceptance of user bids hence any bid submitted against the item will be rejected if the auction is not open this script opens the auction request for bids it sets the status of the auctionrequest to open it opens a timer for the duration of the auction which in the example is 3 minutes during this window any user can submit bids against the auctionid once the timer expires a script is created and saved called closeauction sh the script gets triggered closeauction the closeauction sh script invokes closeauction closeauction will first change the status of the auctionrequest to closed it then fetches the highest bid from the list of bids received and converts it to a transaction the transaction is posted the asset is retrieved from the database its price is set to the new hammer price and the currentowner is set to the new buyer the asset image is un encrypted with the old key a new key is generated and the image is encrypted with the new key the asset is updated in the database an log entry is made in the item log todo in future the transaction will be a business document that triggers payments shipping insurance and commissions openauctionrequestforbids opens the auction request for bids for 3 minutes auction request id used for testing is 1111 and item 1000 this opens a timer for 3 minutes and once timer expires writes a shell script to invoke closeauction as described above once the auction is open this script submits bids against that auctionid both the auctionid and the buyerid are validated before the bid is posted once the auction is closed new bids will be rejected submitbids submits a series of bids against auction 1111 and item 1000 submitqueries this is list of queries that can be issued and must be used via cut and paste on command line cli after the timer expires the close auction should get invoked and the highest bid should be posted as a transaction invoke apis and usage postuser this function is used to register an account for any of the stakeholders defined earlier usage cli mode the call takes 9 arguments user id record type name type address phone email bank name account routing peer chaincode invoke l golang n mycc c function postuser args 100 user ashley hart trd morrisville parkway 216 morrisville nc 27560 9198063535 ashley itpeople com suntrust 00017102345 0234678 postitem this function is used to register an asset with the blockchain the owner of the asset must have a registered account prior to registering the asset no validation of the user type is done by the chaincode and should be managed outside by the client the name of the image f6 png is uploaded by the chaincode from a pre determined directory converted to byte encrypted using aes and stored in the blockchain usage cli mode the call takes 12 arguments item id record type description detail date of origin original or reprint subject media size image file price current owner id peer chaincode invoke l golang n mycc c function postitem args 1400 artinv nature james thomas 19900115 original modern water color 12 x 17 in f6 png 1800 100 postauctionrequest this function is used by the owner of an asset to request an auction house to accept the asset for auction the auction house id the owner id and the asset id are all validated before a request can be posted posting a request does not mean bids can be accepted the auction has to be opened in order for bids to be accepted or buy it now to happen usage cli mode this call takes 11 argumnets auction id record type item id auction house id owner id date of request reserve price buy it now price status dummy open date dummy close date peer chaincode invoke l golang n mycc c function postauctionrequest args 1113 aucreq 1000 200 400 04012016 15000 16000 init 2016 05 20 11 00 00 3 0000 utc 2016 05 23 11 00 00 3 0000 utc the auction opendate and closedate are dummy dates and will be set when the auction is opened the auction id must be unique and cannot be repeated we assume that the client will generate a unique auction id prior to posting the request the state of the auction is init at this point openauctionforbids this function is assumed to be invoked by the role of auction house which is one of the types of accounts registered using postuser it allows the auctioner to open an auction for bids the auction request must be in init state to be open ed when the auction is opened for bids both the open and close date and time are set the following example opens the bid for 3 minutes auction open durations are currently provided in minutes to support testing usage cli mode the call takes 3 arguments auction id record type duration in minutes peer chaincode invoke l golang n mycc c function openauctionforbids args 1111 openauc 3 postbid this function allows a potential buyer to bid on the asset once the auction is open every bid is checked for valid auction id asset id and buyer id bids must be higher than reserve price bids are accepted as long as the auction is open bid numbers must be unique and generated by the client usage cli mode this call takes 6 arguments auction id record type bid number item id buyer id buyer offer price peer chaincode invoke l golang n mycc c function postbid args 1111 bid 5 1000 400 5000 posttransaction even though the transaction is automatically generated and posted when one of the following events occur auction closes after the auction timer expires only cli mode a message to close all expired auctions are close is issued by the client via closeopenauctions a buyitnow call is made which goes through this function is exposed as a matter of convenience just in case transactions don t get posted properly when a transaction is posted it updates the asset with the new buyer id re generates a new key and encrypts the image certificate and updates the asset price to the hammer price it also adds a new entry into the item history table usage cli mode this call takes 8 arguments auction id record type item id transaction type buyer id transaction time hammer time hammer price peer chaincode invoke l golang n mycc c function postbid args 1111 posttran 1000 sale 500 2016 05 24 11 00 00 2016 05 23 14 25 00 12000 buyitnow sometimes an asset owner can specify a buy it now price in addition to the reserve price while posting an auction request if an asset has a buy it now price a buyer can issue a buyitnow call if there are no bids higher than the buyitnow price the request will be rejected if the request goes through the auction is closed and a transaction is posted against the buyer usage cli mode this call is similar to the postbid except the price is set to the buy it now price peer chaincode invoke l golang n mycc c function buyitnow args 1111 bid 1 1000 300 1800 transferitem at any time the current owner of an asset can transfer the item at no additional cost or change in value to another user provided the asset is not initiated for auctions or is in the process of an auction smart contract rules may have to be written to comply with local regulations and taxes the current owner has to prove ownership by providing his key the owner id item id and the key are all validated before transfer can take place the new owner will receive a new key usage cli mode this call takes 5 arguments item id current owner id owner key transferee id record type peer chaincode invoke l golang n mycc c function transferitem args 1000 100 218mc ipisirdhe9tkxqg2nswl7kse59y3umwbzsrqo 300 xfer closeauction this function call closes an auction once the time expires this call is automatically issued in cli mode since the openauctionforbids call triggers a go routine that sleeps for the duration of the auction and the automatically issues a closeauction call this functions closes the auction request picks the highest bid and creates a transaction an then posts the transaction usage cli mode this call takes two arguments auction id record type peer chaincode invoke l golang n mycc c function closeauction args 1111 aucreq closeopenauctions this is a function designed specifically for bluemix situations where the peer and the chaincode run in different containers hence a call as shown in each of usage cli mode will not work this function is issued periodically by the client ui or applications consuming the blockchain as a rest call the functions checks for auctions whose time has run out and closes them usage cli mode this call takes two arguments 2016 record type peer chaincode invoke l golang n mycc c function closeopenauctions args 2016 clauc query apis and usage getitem retrieves an asset record by asset id usage cli mode peer chaincode query l golang n mycc c function getitem args 1000 getuser retrieves an user record by user or stakeholder id usage cli mode peer chaincode query l golang n mycc c function getuser args 100 getauctionrequest retrieves an auction request by auction request id usage cli mode peer chaincode query l golang n mycc c function getauctionrequest args 1111 gettransaction retrieves an transaction posted against an auction by auction request id and asset id usage cli mode peer chaincode query l golang n mycc c function gettransaction args 1111 1000 getbid retrieves a single bid by auction id and bid number usage cli mode peer chaincode query l golang n mycc c function getbid args 1111 5 getlastbid retrieves the last submitted bid since bids are submitted in random and the only requirement is that the bid price be higher than the reserve price the last received bid need not be the highest bid usage cli mode peer chaincode query l golang n mycc c function getlastbid args 1111 gethighestbid retrieves the highest bid submitted against the auction thus far if the auction has expired then the highest bid is the highest bid for the auction usage cli mode peer chaincode query l golang n mycc c function gethighestbid args 1111 getnoofbidsreceived retrieves the total number of bids received at any point in time if the auction has expired it represents the total number of bids received against that auction usage cli mode peer chaincode query l golang n mycc c function getnoofbidsreceived args 1111 getlistofbids retrieves all the bids received against an auction each row in the list represents a bid object usage cli mode peer chaincode query l golang n mycc c function getlistofbids args 1111 getitemlog retrieves the history of an asset the log is updated when an asset is registered put on auction post auction transfered etc usage cli mode peer chaincode query l golang n mycc c function getitemlog args 1000 getitemlistbycat retrieves a list of assets by asset category if only the first key is provided the query retrieves all assets 2016 is hard coded as a fixed first key this is a band aid solution to retrieve all records this is a band aid solution to retrieve all records the following query retrieves all assets of category modern usage cli mode peer chaincode query l golang n mycc c function getitemlistbycat args 2016 modern getuserlistbycat retrieves a list of stakeholders or account holders by stakeholder type if only the first key is provided the query retrieves all assets 2016 is hard coded as a fixed first key this is a band aid solution to retrieve all records the following query retrieves all stakeholders of type ah or auction houses usage cli mode peer chaincode query l golang n mycc c function getitemlistbycat args 2016 ah getlistofinitaucs this query retrieves all assets which have been submitted for auction their status is init the 2016 is a fixed key to denote all auctions in 2016 usage cli mode peer chaincode query l golang n mycc c function getlistofinitaucs args 2016 getlistofopenaucs this query retrieves a list of all assets whose auctions have been open ed for receiving bids the 2016 is a fixed key to denote all auctions in 2016 usage cli mode peer chaincode query l golang n mycc c function getlistofopenaucs args 2016 validateitemownership validates the ownership of an asset checks for valid account id asset id and retrieves asset from blockchain using the owners s key the arguments are item id current owner id and owner s key usage cli mode peer chaincode query l golang n mycc c function validateitemownership args 1000 500 avqx6jftnelay4mkrhor8p7vmz0h3aaiufgsgisd5uq isitemonauction checks whether an asset has an auction request posted or currently on auction and returns a boolean true or false usage cli mode peer chaincode query l golang n mycc c function isitemonauction args 1999 verify notes once an auction request is posted or an auction is open for bids there is no api to remove the auction request or close the auction prematurely and rejecting all bids received in the current version the image is encrypted and stored in the blockchain however in future it is envisioned that only the hash of the image along with the uri to the location of the image will be saved runnning the application using the web browser the chaincode functions can be accessed via the browser please refer auction app https github com itpeople blockchain auction app for more details | blockchain |
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BlockchainSharp | blockchainsharp generic blockchain implementation in c wip references understanding the ethereum trie https easythereentropy wordpress com 2014 06 04 understanding the ethereum trie what is the ghost protocol for ethereum https www cryptocompare com coins guides what is the ghost protocol for ethereum ethereum wire protocol https github com ethereum wiki wiki ethereum wire protocol how to build your own blockchain part 3 writing nodes that mine and talk https bigishdata com 2017 11 02 build your own blockchain part 3 writing nodes that mine license mit | blockchain |
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biomedical-blockchain | update on july 25th 2018 in a combined effort with elektra labs we released a piece in stat news about analysis conducted on these projects stat news july 2018 op ed https www statnews com 2018 07 25 blockchains biomedicine health care buyer be informed in parallel we also released an interactive version of this database healthcare biomedical blockchains https db biomedicalblockchain org this site will be updated going forward and has many extra features including live infographics and an easier project submission process we hope you continue to find it useful lastly we now have an official website of our own at center for biomedical blockchain research http biomedicalblockchain org biomedical blockchain initiatives map biomedical blockchain map png https api mapbox com styles v1 zimmeee cjfwus7rf1dbb2rmi78pn1ujw html fresh true title true access token pk eyj1ijoiemltbwvlzsisimeioijjaxa2nnl1m2owmdnvewjrbzb0bmfmcw9zin0 3uhax5marjawystcyhkvsw 1 7 31 444924 6 387816 0 there is tremendous interest and opportunity to apply blockchain technologies to problems in biology medicine and health we have created this repository to map all of the biomedical blockchain initiatives worldwide in order to track the evolution of this emerging technology check out this blog post http hd2i org blog 2018 04 05 mapping the biomedical blockchain html for a complete description of our approach and methodology contributions are welcome https github com hd2i biomedical blockchain blob master contributing md and encouraged legend criteria for mention code must be publicly available and non trivial white papers tokens token sales road maps forks without additional work etc are not considered demo must have a publicly available demo or working product private betas are not considered technical documentation docs must have a publicly available technical whitepaper specification non technical implementations are not considered professional investment mm usd raised from professional investors source list current total 93 site name category location code demo docs inv mm img src https aim aimedis com img logo new png width 80 https aim aimedis com aimedis aimedis marketplace steyl netherlands img src https d33wubrfki0l68 cloudfront net 9e1fb050865401a69f27b46683de38626a9372d0 9efc0 assets logo color 2 png width 80 https ambrosus com index html ambrosus ambrosus supply chain zug switzerland img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com ambrosus img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https ambrosus com assets ambrosus white paper v8 1 pdf img src https amchart io wp content themes amchart images logos logo png width 80 http amchart io amchart amchart patient data management austin tx usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png http amchart io white paper img src https token arnagenomics com wp content uploads 2018 01 logo min png width 80 https token arnagenomics com arna panacea arna panacea research and clinical trials moscow russia img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https token arnagenomics com arna whitepaper en pdf img src https beat org img logo light svg width 80 https beat org beat beat marketplace hamburg germany img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https beat org beat whitepaper pdf img src https bitmark com assets img logo header svg width 80 https bitmark com bitmark bitmark payments claims and other services taipei taiwan img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com project bitmark bitmark img src https raw githubusercontent com encharm font awesome svg png master black png 24 desktop png https bitmark com tools api 1 7 img src https blockmedx com static images svg header logo svg width 80 https blockmedx com en blockmedx blockmedx supply chain lexington ky usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com blockmedx img src https www blockrx com wp content uploads 2017 07 mark 2 darker png width 80 https www blockrx com blockrx blockrx supply chain philadelphia pennsylvania usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https www blockrx com wp content uploads 2017 10 whitepaper design extended pdf img src https bowheadhealth com images uploads bowhead png width 80 https bowheadhealth com bowheadhealth bowheadhealth digital medicine singapore img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https drive google com drive u 1 folders 0b2cimlh8gflnmzy0wefhrlbxslu img src https bron tech images logo brontech logo color png width 80 https bron tech bron tech bron tech patient data management sydney new south wales australia img src https raw githubusercontent com encharm font awesome svg png master black png 24 desktop png https www mybron com user 1 3 img src https www burstiq com wp content uploads 2016 01 burstiq logo retina png width 80 https www burstiq com burstiq burstiq interoperability denver colorado usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com burstiq img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https www burstiq com wp content uploads 2017 08 burstiq whitepaper 19jul2017reduced pdf 5 0 img src https pbs twimg com profile images 879697269846675459 jbjvox69 400x400 jpg width 80 https www carechain io carechain carechain advisory consortium stockholm sweden img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com carechain img src https raw githubusercontent com encharm font awesome svg png master black png 24 tablet png https github com carechain exposome img src https carefourme com wp content uploads thegem logos logo e68cad3508180ab819fb9e28801b83b8 2x png width 80 https carefourme com careme careme digital medicine miama florida usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com care4me img src https carex tech assets images logo png width 80 https carex tech carex blockchain platform carex blockchain platform payments claims and other services bellaire texas usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com carextech img src https citizenhealth io wp content uploads 2017 09 citizen health dark logo 214x60 png width 80 https citizenhealth io citizen health citizen health marketplace hattiesburg ms usa img src https bitcoincryptocurrency com wp content uploads 2018 02 clinicoin 696x449 jpg width 80 https clinicoin io en clinicoin clinicoin digital medicine seattle wa usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com clinicoin img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https www mosio com noidx clinicoin whitepaper 2018 pdf img src https bitcoincryptocurrency com wp content uploads 2018 01 coinhealth 696x449 jpg width 80 https coinhealth io coinhealth coinhealth patient data management dallas texas usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com coinhealth coinhealth img src https cdn images 1 medium com max 1600 1 qpl3fugulj8rmxvd0betew png width 80 https mycoralhealth com coralhealth coralhealth interoperability vancouver canada img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com mycoralhealth img src https raw githubusercontent com encharm font awesome svg png master black png 24 desktop png https tips mycoralhealth com img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https docsend com view 4xdqkp6 img src http kriorus ru sites kriorus files beb8f88c 98d3 4526 ade2 143453cf2688 png width 80 https en cryogen me cryogen cryogen digital medicine moscow russia img src https curecoin net wp content uploads 2016 05 carp png width 80 https curecoin net curecoin curecoin research and clinical trials usa img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com cygnusxi curecoinsource img src https raw githubusercontent com encharm font awesome svg png master black png 24 desktop png https curecoin net knowledge base folding for curecoin how do i start folding for curecoin quick img src https static wixstatic com media 6e4527 aa31af77b5d8470482c5e1672d33acb6 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addiction details category digital medicine location georgia usa money raised m method of funding github profile ico symbol network erc 20 223 white paper healpoint img src https healpoint io img man png width 200 http healpoint io second opinion platform for medical diagnostics details category digital medicine location los angeles california usa money raised m method of funding ico github profile ico symbol hlp network ethereum white paper health monitor img src https assets coingecko com coins images 1988 large hlc png 1514446359 width 200 http healthmonitor io non invasive diagnostics of blood glucose level lung cancer stomach ulcer and diabetes details category digital medicine location estajovice czech republic money raised m 0 5 method of funding ico github profile ico symbol hlc network ethereum white paper health wizz img src https d15shllkswkct0 cloudfront net wp content blogs dir 1 files 2017 11 health wizz logo icon feb 2017 1 jpg width 200 https www healthwizz com mobile platform to aggregate organize and share medical records notable ceo appeared on cnbc https www cnbc com video 2017 12 26 how we are using blockchain technology to secure your health records heath wizz ceo html details category patient data management location falls church virginia usa money raised m method of funding ico github profile ico symbol network white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https daks2k3a4ib2z cloudfront net 586ebe41ba9f9499729002dc 59e6211d76c4d200017c6dc5 healthwizz white 20paper pdf healthbase img src https i imgur com qcbtxih png width 200 http www healthbase digital utilizes blockchain to provide researchers care providers and patients access to health data details category patient data management location bonn germany money raised m method of funding github profile ico symbol network ethereum white paper healthcombix img src https pbs twimg com profile images 632665242644844544 ab733vqt 400x400 jpg width 200 http www healthcombix com healthcare blockchain distributed ledger and decentralized network strategy and product development company details category payments claims other services location nashville tennessee usa money raised m method of funding github profile ico symbol network white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png http www healthcombix com healthlinkages img src http healthlinkages com assets img hl logo hero svg width 200 http healthlinkages com uses blockchain inspired technology to allow healthcare institutions to trust and share data details category payments claims other services location mountain view california usa money raised m method of funding seed github profile ico symbol network white paper healthureum img src https tokenmarket net blockchain static ethereum assets healthureum logo big png width 200 https www healthureum io data consolidation and exchange doctor consult and 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profile ico symbol hit network nem white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https hit foundation wp content uploads whitepaper hit foundation pdf ingeniciel img src https pbs twimg com profile images 912409192761356288 g7ulxyfg 400x400 jpg width 200 http www ingeniciel com store and manage medical records details category patient data management location lyon france money raised m method of funding ico github profile img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com pibouv ingeniciel ico symbol ingcl network nxt white paper iryo img src https icobench com images icos icons iryo jpg width 200 https iryo io health record storage platform with an anonymous query interface controls for patient record access and tokens to incentivize consent enabling artificial intelligence ai research details category patient data management location kranj slovenia money raised m method of funding ico github profile img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com iryonetwork ico symbol iryo network eos white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https iryo io iryo whitepaper pdf linda healthcare img src https icolink com components com djclassifieds images item 698 ico link list linda healthcare thb jpg width 200 https linda healthcare primary care telemedicine a i chatbot details category digital medicine location palo alto california usa money raised m method of funding ico github profile ico symbol lnda network ethereum white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https linda healthcare media lindahealthcare whitepaper final revised pdf litra img src https www investitin com wp content uploads 2017 08 litra 1 png width 200 https litra site free 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com profile images 899631295520747520 ig5auco0 jpg width 200 https medcredits io telemedicine on the blockchain powered by a public decentralized registry of physicians notable partnered with civic https www coinspeaker com 2018 03 21 medcredits civic partner first blockchain powered physician registry details category digital medicine location berkley michigan money raised m method of funding ico github profile ico symbol medx network ethereum white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https medcredits io docs medcreditswhitepaper pdf medibloc img src https i1 wp com bitcoinexchangeguide com wp content uploads 2017 11 medibloc jpg resize 696 2c449 ssl 1 width 200 https medibloc org en a decentralized healthcare information ecosystem for patients healthcare providers and data researchers built on blockchain technology details category interoperability location seoul south korea money raised m method of funding ico 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https medicohealth io telemedicine platform that allows patients to share health data with doctors details category digital medicine location ljubljana slovenia money raised m method of funding seed ico github profile ico symbol mhp network ethereum white paper mediledger img src https i1 wp com bitcoinexchangeguide com wp content uploads 2018 02 mediledger jpg resize 696 2c449 ssl 1 width 200 https www mediledger com permissioned blockchain for tracking and tracing regulations to improve the operation of the supply chain in the pharmaceutical industry details category supply chain location san francisco ca usa money raised m 12 0 method of funding seed github profile img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com chronicled mediledger ico symbol network ethereum white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https uploads ssl webflow com 59f37d05831e85000160b9b4 5aa358c647bb6800017a018b mediledger 20project 202017 20progress 20report pdf mednetwork img src http c fastcdn co t 6efc847b 3c7a834d 1520966946 28382932 436x71x436x83x0x6 mednetwork logo png width 200 http www mednetwork io telemedicine platform for the sharing and analysis of medical images details category digital medicine location singapore money raised m method of funding ico github profile ico symbol medai network ethereum white paper medrec img src https medrec media mit edu images logo png width 200 https medrec media mit edu platform for patients to store manage and share electronic health records as well as allow researchers to receive anonymized medical data in return for sustaining the network notable a product of mit media labs details category patient data management location cambridge massachusetts usa money raised m method of funding github profile ico symbol network white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https medrec media mit edu technical medxchange img src https static wixstatic com media a6d7cc 573a7cdb21af47ccb79c6c0af5663160 mv2 png v1 fill w 212 h 212 al c usm 0 33 1 00 0 00 a6d7cc 573a7cdb21af47ccb79c6c0af5663160 mv2 png width 200 https www medxchange io a supply chain system for handling transactions data transfer and storage and payments of medical devices details category supply chain location hong kong china money raised m method of funding ico github profile ico symbol medcash network ethereum white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https docs wixstatic com ugd a6d7cc ccd72646ac6e4217be3b19d0c04d9025 pdf minthealth img src https www minthealth io wp content uploads 2018 03 minthealth logo color png width 200 https www minthealth io a global decentralized health platform that empowers patients with a self sovereign health identity and aligns patients providers and 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trials of aging therapies details category research and clinical trials location moscow russia money raised m method of funding ico github profile ico symbol year network ethereum white paper patientory img src https cdn images 1 medium com max 944 0 y0xaxchgf3emzmkb png width 200 https patientory com a healthcare peer to peer emr storage network details category patient data management location atlanta georgia usa money raised m 7 2 method of funding ico github profile ico symbol ptoy network ethereum white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https patientory com patientory whitepaper pdf pokitdok img src https www blockchaintechnology news com wp content uploads 2017 05 ximg pd peg png pagespeed ic 9q6wxcvwup png width 200 https pokitdok com provides platform as a service to enable healthcare organizations to develop new healthcare applications and services details category payments claims and other services 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https robomed io an ehr that allows for the management of a medical organization based on smart contracts that allow for the monitoring of all proccess of interaction with the patient details category payments claims and other services location russia money raised m 14 1 method of funding ico github profile ico symbol rbm network ethereum white paper scalamed img src https scontent fsnc1 1 fna fbcdn net v t1 0 1 20429931 1421973511226779 5207861906003401508 n png nc cat 0 oh 3838add2c2864478fbe144a29fc10f97 oe 5b2e5b0b width 200 https www scalamed com a mobile prescription exchange system for patients doctors and pharmacists to manage prescribe as well as dispense prescription medications details category payments claims and other services location sydney australia money raised m method of funding seed github profile ico symbol network white paper shivom img src https www icoexaminer com wp content uploads 2018 03 shivom logo jpg width 200 http shivom io a b2b and b2c platform to 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claims and other services location estonia money raised m 23 6 method of funding ico github profile img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com solvecare ico symbol can network ethereum white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https solve care solvecare documents l en spiritus img src https static1 squarespace com static 5a708340c027d82f766de3bd t 5a708f1bc83025e26582668c 1523267191078 format 1500w width 200 https www spirituspartners com solution to allow all involved parties to record evidence of service for critical assets and infrastructure details category supply chain location edinburgh united kingdom money raised m method of funding github profile ico symbol network white paper ssot health blockchain img src https static wixstatic com media 4b78ba 27700438c9724311abc1544cd684151b mv2 png v1 fill w 72 h 84 al c usm 0 66 1 00 0 01 4b78ba 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universal health coin png resize 228 2c251 ssl 1 width 200 https www universalhealthcoin com a privacy focused token based healthcare finance system that utilizes blockchain to arbitrage decentralize and provision payment of health services details category payments claims and other services location augusta georgia usa money raised m method of funding ico github profile ico symbol uhc network neo white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png http www universalhealthcoin com wp content uploads uhcwhitepaper v2 3 pdf veris foundation img src https i vimeocdn com video 655062420 640 jpg width 200 https www verisfoundation com the veris platform is a blockchain that specifically addresses the expenses in the american healthcare system the platform is open source and takes advantage of smart contracts to replace portions of the eligibility through remittance process in the provisioning of healthcare services details category payments claims and other services location jersey city new jersey usa money raised m method of funding ico github profile img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com verisfoundation ico symbol vrs network neo white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https veris docsend com view fbqysxf well img src https www coinstaker com wp content uploads 2018 01 well logo h teal cmyk jpg width 200 https joinwell io mobile healthcare marketplace for telehealth clinics personalized service and health data storage details category digital medicine location santa monica california usa money raised m 3 0 method of funding ico github profile ico symbol well network ethereum white paper youbase img src https ccn2017 wpengine com wp content uploads 2015 06 1 youbase png width 200 https www youbase io enables patients to create and maintain a personal data store on a distributed public network details category patient data management location englewood co usa money raised m method of funding seed github profile img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com youbase ico symbol network white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https paper youbase io content zenome img src https i imgur com njyuzs3 png width 200 https zenome io a marketplace for genomic data and services details category marketplace location moscow russia money raised m 0 6 method of funding ico github profile img src https raw githubusercontent com encharm font awesome svg png master black png 24 github png https github com zenome ico symbol zna network ethereum white paper img src https raw githubusercontent com encharm font awesome svg png master black png 24 file o png https zenome io download whitepaper pdf | health-data blockchain 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SQL-ORM | sql orm an orm object relational mapping is a technique in oop that allows us to interact with a sql database in java usually it s easier to use a orm to interact with a sql database than to write raw queries ourselves with this tool we can easily insert delete search and select data from a sql database using a langauge we already know | server |
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Udagram-Cloudapp | udagram image filtering application udagram is a simple cloud application developed alongside the udacity cloud engineering nanodegree it allows users to register and log into a web client post photos to the feed and process photos using an image filtering microservice the project is split into two parts 1 frontend angular web application built with ionic framework 2 backend restful api node express application getting started tip it s recommended that you start with getting the backend api running since the frontend web application depends on the api prerequisite 1 the depends on the node package manager npm you will need to download and install node from https nodejs com en download https nodejs org en download this will allow you to be able to run npm commands 2 environment variables will need to be set these environment variables include database connection details that should not be hard coded into the application code environment script a file named set env sh has been prepared as an optional tool to help you configure these variables on your local development environment we do not want your credentials to be stored in git after pulling this starter project run the following command to tell git to stop tracking the script in git but keep it stored locally this way you can use the script for your convenience and reduce risk of exposing your credentials git rm cached set env sh afterwards we can prevent the file from being included in your solution by adding the file to our gitignore file 1 database create a postgresql database either locally or on aws rds the database is used to store the application s metadata we will need to use password authentication for this project this means that a username and password is needed to authenticate and access the database the port number will need to be set as 5432 this is the typical port that is used by postgresql so it is usually set to this port by default once your database is set up set the config values for environment variables prefixed with postgres in set env sh if you set up a local database your postgres host is most likely localhost if you set up an rds database your postgres host is most likely in the following format us west 1 rds amazonaws com you can find this value in the aws console s rds dashboard 2 s3 create an aws s3 bucket the s3 bucket is used to store images that are displayed in udagram set the config values for environment variables prefixed with aws in set env sh 3 backend api launch the backend api locally the api is the application s interface to s3 and the database to download all the package dependencies run the command from the directory udagram api bash npm install to run the application locally run bash npm run dev you can visit http localhost 8080 api v0 feed in your web browser to verify that the application is running you should see a json payload feel free to play around with postman to test the api s 4 frontend app launch the frontend app locally to download all the package dependencies run the command from the directory udagram frontend bash npm install install ionic framework s command line tools for us to build and run the application bash npm install g ionic prepare your application by compiling them into static files bash ionic build run the application locally using files created from the ionic build command bash ionic serve you can visit http localhost 8100 in your web browser to verify that the application is running you should see a web interface tips 1 take a look at udagram api does it look like we can divide it into two modules to be deployed as separate microservices 2 the dockerignore file is included for your convenience to not copy node modules copying this over into a docker container might cause issues if your local environment is a different operating system than the docker image ex windows or macos vs linux 3 it s useful to lint your code so that changes in the codebase adhere to a coding standard this helps alleviate issues when developers use different styles of coding eslint has been set up for typescript in the codebase for you to lint your code run the following bash npx eslint ext js ts src to have your code fixed automatically run bash npx eslint ext js ts src fix 4 set env sh is really for your backend application frontend applications have a different notion of how to store configurations configurations for the application endpoints can be configured inside of the environments environment ts files 5 in set env sh environment variables are set with export var value setting it this way is not permanent every time you open a new terminal you will have to run set env sh to reconfigure your environment variables to verify if your environment variable is set you can check the variable with a command like echo postgres username | cloud |
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One-Pot_Multi-Frame_Denoising | one pot multi frame denoising the corresponding paper has been accepted as a spotlight at the 33rd british machine vision conference bmvc 2022 https bmvc2022 mpi inf mpg de 61 and an extended version is published on the international journal of computer vision ijcv https link springer com article 10 1007 s11263 023 01887 7 abstract the efficacy of learning based denoising techniques is heavily reliant on the quality of clean supervision unfortunately acquiring clean images in many scenarios is a challenging task conversely capturing multiple noisy frames of the same field of view is feasible and natural in real life scenarios thus it is imperative to explore the potential of noisy data in model training and avoid the limitations imposed by clean labels in this paper we propose a novel unsupervised learning strategy called one pot denoising opd which is the first unsupervised multi frame denoising method opd differs from traditional supervision schemes such as supervised noise2clean unsupervised noise2noise and self supervised noise2void as it employs mutual supervision among all the multiple frames this provides learning with more diverse supervision and allows models to better exploit the correlation among frames notably we reveal that noise2noise is a special case of the proposed opd we provide two specific implementations namely opd random coupling opd rc and opd alienation loss opd al to achieve opd during model training based on data allocation and loss refine respectively our experiments demonstrate that opd outperforms other unsupervised denoising methods and is comparable to non transformer based supervised n2c methods for several classic noise patterns including additive white gaussian noise signal dependent poisson noise and multiplicative bernoulli noise additionally opd shows remarkable performance in more challenging tasks such as mixed blind denoising denoising random valued impulse noise and text removal priciple comparison alt text img principle compare png denoising comparison method demonstration alt text img method demo png denoising comparison quantitative evaluation alt text img quantitative comparison png denoising comparison qualitative evaluation alt text img qualitative comparison png denoising comparison getting started the below sections detail how to get set up for training under the opd strategy including opd rc and opd al using the imagenet validation dataset python requirements this code is tested with python 3 8 here s how to create a clean environment and install library dependencies conda create n opd python 3 8 conda activate opd conda install pytorch gpu python m pip install upgrade pip pip install r requirements txt this will install pytorch and other dependencies used in this project preparing datasets for training and testing this section describes how to add simulated noise to clean datasets including imagenet bsd300 kodak and set14 firstly download and unzip the imagenet validation dataset http www image net org challenges lsvrc 2012 nnoupb ilsvrc2012 img val tar bsd300 dataset https www2 eecs berkeley edu research projects cs vision bsds bsds300 images tgz and kodak http r0k us graphics kodak into the corresponding directory under data set14 has been prepared as a demonstrative dataset here is how to add noise to the clean dataset try python add noise py help for available options python add noise py root dir data ilsvrc2012 img val tar dir data ilsvrc2012 img val noisy1 note that the above code needs to be repeated m times and the final index should be changed to generate noisy datasets of m frames training networks to train a modified u net on imagenet validation set under opd strategy try python train py help for available options python train py strategy rc datadir ilsvrc2012 img val noisy by default this invocation will train a gaussian denoising network using the imagenet validation set upon completion the training process produces a file called network final pth under the models opd rc ilsvrc2012val awgn directory in addition if you want to train under opd al change the strategy argument to al in the above invocation testing using a trained network once you ve trained a network you can run a testing dataset through the network suppose your training run results were stored under models opd rc ilsvrc2012val awgn here s how to run a set of images through this network python test py strategy rc testdata bsd300 srcpath bsd300 noisy tarpath bsd300 pre trained networks you can find pre trained networks for denoising awgn in the corresponding directory under the model a demo we provide a demo on the set14 dataset you only need to run the following command and the denoised images of set14 will be found in the results opd rc ilsvrc2012val awgn set14 directory for the demo under opd al the operation is similar python demo py | ai |
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Awesome-Hardware-and-IoT-Hacking | hardware hacking and iot awesome by joas my social networks https www linkedin com in joas antonio dos santos https twitter com c0d3cr4zy https drive google com drive u 0 folders 12mvq6ke2hjdwn2czhegwizywt87yunku awesome embedded and iot security https github com fkie cad awesome embedded and iot security software tools analysis frameworks expliot pentest framework like metasploit but specialized for iot fact the firmware analysis and comparison tool full featured static analysis framework including extraction of firmware analysis utilizing different plug ins and comparison of different firmware versions improving your firmware security analysis process with fact conference talk about fact fwanalyzer analyze security of firmware based on customized rules intended as additional step in devsecops similar to ci hal the hardware analyzer a comprehensive reverse engineering and manipulation framework for gate level netlists homepwn swiss army knife for pentesting of iot devices iotsecfuzz framework for automatisation of iot layers security analysis hardware software and communication killerbee framework for testing auditing zigbee and ieee 802 15 4 networks pret printer exploitation toolkit routersploit framework dedicated to exploit embedded devices analysis tools binwalk searches a binary for interesting stuff as well as extracts arbitrary files emba analyze linux based firmware of embedded devices firmadyne tries to emulate and pentest a firmware firmwalker searches extracted firmware images for interesting files and information firmware slap discovering vulnerabilities in firmware through concolic analysis and function clustering ghidra software reverse engineering suite handles arbitrary binaries if you provide cpu architecture and endianness of the binary radare2 software reverse engineering framework also handles popular formats and arbitrary binaries has an extensive command line toolset trommel searches extracted firmware images for interesting files and information extraction tools fact extractor detects container format automatically and executes the corresponding extraction tool firmware mod kit extraction tools for several container formats the srecord package collection of tools for manipulating eprom files can convert lots of binary formats support tools jtagenum add jtag capabilities to an arduino openocd free and open on chip debugging in system programming and boundary scan testing misc tools cotopaxi set of tools for security testing of internet of things devices using specific network iot protocols dumpflash low level nand flash dump and parsing utility flashrom tool for detecting reading writing verifying and erasing flash chips samsung firmware magic decrypt samsung ssd firmware updates hardware tools bus blaster detects and interacts with hardware debug ports like uart and jtag bus pirate detects and interacts with hardware debug ports like uart and jtag shikra detects and interacts with hardware debug ports like uart and jtag among other protocols jtagulator detects jtag pinouts fast saleae easy to use logic analyzer that support many protocols ikalogic alternative to saleae logic analyzers hydrabus open source multi tool hardware similar to the buspirate but with nfc capabilities chipwhisperer detects glitch side channel attacks glasgow tool for exploring and debugging different digital interfaces j link j link offers usb powered jtag debug probes for multiple different cpu cores bluetooth ble tools ubertooth one open source 2 4 ghz wireless development platform suitable for bluetooth experimentation bluefruit le sniffer easy to use bluetooth low energy sniffer zigbee tools apimote zigbee security research hardware for learning about and evaluating the security of ieee 802 15 4 zigbee systems killerbee compatible atmel rzusbstick discontinued product lucky if you have one tool for development debugging and demonstration of a wide range of low power wireless applications including ieee 802 15 4 6lowpan and zigbee networks killerbee compatible freakduino low cost battery operated wireless arduino board that can be turned into a ieee 802 15 4 protocol sniffer sdr tools rtl sdr cheapest sdr for beginners it is a computer based radio scanner for receiving live radio signals frequencies from 500 khz up to 1 75 ghz hackrf one software defined radio peripheral capable of transmission or reception of radio signals from 1 mhz to 6 ghz half duplex yardstick one half duplex sub 1 ghz wireless transceiver limesdr software defined radio peripheral capable of transmission or reception of radio signals from 100 khz to 3 8 ghz full duplex bladerf 2 0 software defined radio peripheral capable of transmission or reception of radio signals from 47 mhz to 6 ghz full duplex usrp b series software defined radio peripheral capable of transmission or reception of radio signals from 70 mhz to 6 ghz full duplex rfid nfc tools proxmark 3 rdv4 powerful general purpose rfid tool from low frequency 125khz to high frequency 13 56mhz tags chamaleonmini programmable portable tool for nfc security analysis hydranfc powerful 13 56mhz rfid nfc platform read write crack sniff emulate books 2020 fotios chantzis evangel deirme ioannis stais paulino calderon beau woods practical iot hacking 2020 jasper van woudenberg colin o flynn the hardware hacking handbook breaking embedded security with hardware attacks 2019 yago hansen the hacker s hardware toolkit the best collection of hardware gadgets for red team hackers pentesters and security researchers 2019 aditya gupta the iot hacker s handbook a practical guide to hacking the internet of things 2018 mark swarup tehranipoor hardware security a hands on learning approach 2018 mark carney pentesting hardware a practical handbook draft 2018 qing yang lin huang inside radio an attack and defense guide 2017 aditya gupta aaron guzman iot penetration testing cookbook 2017 andrew huang the hardware hacker adventures in making and breaking hardware 2016 craig smith the car hacker s handbook a guide for the penetration tester 2015 keng tiong ng the art of pcb reverse engineering 2015 nitesh dhanjan abusing the internet of things blackouts freakouts and stakeouts 2015 joshua wright johnny cache hacking wireless exposed 2014 debdeep mukhopadhyay hardware security design threats and safeguards 2014 jack ganssle the firmware handbook embedded technology 2013 andrew huang hacking the xbox research papers 2020 oser et al safer development and evaluation of an iot device risk assessment framework in a multinational organization 2019 agarwal et al detecting iot devices and how they put large heterogeneous networks at security risk 2019 almakhdhub et al benchiot a security benchmark for the internet of things 2019 alrawi et al sok security evaluation of home based iot deployments 2019 abbasi et al challenges in designing exploit mitigations for deeply embedded systems 2019 song et al periscope an effective probing and fuzzing framework for the hardware os boundary 2018 muench et al what you corrupt is not what you crash challenges in fuzzing embedded devices 2017 o meara et al embedded device vulnerability analysis case study using trommel 2017 jacob et al how to break secure boot on fpga socs through malicious hardware 2017 costin et al towards automated classification of firmware images and identification of embedded devices 2016 kammerstetter et al embedded security testing with peripheral device caching and runtime program state approximation 2016 chen et al towards automated dynamic analysis for linux based embedded firmware 2016 costin et al automated dynamic firmware analysis at scale a case study on embedded web interfaces 2015 shoshitaishvili et al firmalice automatic detection of authentication bypass vulnerabilities in binary firmware 2015 papp et al embedded systems security threats vulnerabilities and attack taxonomy 2014 zaddach et al avatar a framework to support dynamic security analysis of embedded systems firmwares 2014 alimi et al analysis of embedded applications by evolutionary fuzzing 2014 costin et al a large scale analysis of the security of embedded firmwares 2013 davidson et al fie on firmware finding vulnerabilities in embedded systems using symbolic execution case studies binary hardening in iot products cracking linksys encryption deadly sins of development conference talk presenting several real world examples on real bad implementations dumping firmware from a device s spi flash with a buspirate hacking the dsp w215 again hacking the ps4 introduction to ps4 s security iot security cern multiple vulnerabilities found in the d link dwr 932b pwning the dlink 850l routers and abusing the mydlink cloud protocol pwn xerox printers again reversing firmware with radare reversing the huawei hg533 free training csaw embedded security challenge 2019 csaw 2019 embedded security challenge esc embedded security ctf microcorruption embedded security ctf hardware hacking 101 workshop bsides munich 2019 iotgoat iotgoat is a deliberately insecure firmware based on openwrt rhme 2015 first riscure hack me hardware ctf challenge rhme 2016 riscure hack me 2 is a low level hardware ctf challenge rhme 2017 2018 riscure hack me 3 embedded hardware ctf 2017 2018 websites hacking printers wiki all things printer owasp embedded application security project development best practices and list of hardware and software tools owasp internet of things project iot common vulnerabilities and attack surfaces router passwords default login credential database sorted by manufacturer siliconpr0n a wiki archive of all things ic reversing blogs rtl sdr dev ttys0 s embedded device hacking exploiteers hackaday jcjc s hack the world quarkslab wrong baud firmware security pentestpartners attify patayu gracefulsecurity hardware tag black hills hardware hacking tag fundamentals https www incose org docs default source wasatch chapter documents the big 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internet of things security encyclopedia openbook applied cyber security and the smart grid ics gray hat hacking the ethical hacker s handbook fifth edition practical iot hacking blogs for iotpentest https payatu com blog http jcjc dev com https w00tsec blogspot in http www devttys0 com https wrongbaud github io https embeddedbits org https www rtl sdr com https keenlab tencent com en https courk cc https iotsecuritywiki com https cybergibbons com http firmware re http blog k3170makan com https blog tclaverie eu http blog besimaltinok com category iot pentest https ctrlu net http iotpentest com https blog attify com https duo com decipher http www sp3ctr3 me http blog 0x42424242 in https dantheiotman com https blog danman eu https quentinkaiser be https blog quarkslab com https blog ice9 us https labs f secure com https mg lol blog https cjhackerz net https github com sponsors bunnie https iotmyway wordpress com https www synacktiv com publications html http blog cr4 sh awesome cheatsheets hardware hacking nmap search engines for iot openly devices shodan fofa censys zoomeye onyphe ctf for iot and embeddded https github com hackgnar ble ctf https www microcorruption com https github com riscure rhme 2016 https github com riscure rhme 2017 https blog exploitlab net 2018 01 dvar damn vulnerable arm router html https github com scriptingxss iotgoat youtube channels for iot pentesting liveoverflow binary adventure eevblog jackktutorials craig smith iotpentest mr iot besim altinok iot hardware wireless ghidra ninja cyber gibbons scanline iot vulnerabilites checking guides reflecting upon owasp top 10 iot vulnerabilities owasp iot top 10 2018 mapping project hardware toolkits for iot security analysis iot gateway software webthings by mozilla raspberrypi iot pentesting oses sigint os lte imsi catcher instatn gnuradio os for radio signals testing attifyos iot pentest os by aditya gupta ubutnu best host linux for iot s use lts internet of things penetration testing 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uart using uart to connect to a chinese ip cam a journey into iot hardware hacking uart uartbruteforcer uart connections and dynamic analysis on linksys e1000 accessing and dumping firmware through uart jtag jtag explained finally buspirate jtag connections openocd sidechannel attacks and glitching attacks attacks on implementations of secure systems fuzzing binary analysis iot security and general exploitation nand glitching attack voltage glitching attack espressif esp32 bypassing encrypted secure boot cve 2020 13629 voltage glitching attack using syss icestick glitcher samy kamkar fpga glitching side channel attacks hardware power glitch attack fault injection rhme2 fiesta fi 100 breaking aes with chipwhisperer piece of scake side channel analysis 100 https www youtube com watch v 4urmitjkqqs ab channel stacksmashing awesome iot pentesting guides shodan pentesting guide car hacking practical guide 101 owasp firmware security testing methodology awesome bluetooth security firmware pentest guide follow the people jilles joe fitz aseem jakhar cybergibbons jasper dave jones bunnie ilya shaposhnikov mark c a a ron guzman arun mane yashin mehaboobe arun magesh red team hardware hacking toolkit lock picks pocket commonly used picks under the door tool canned air hand warmers request to exit bypass etc shove knife shrum tool crash bar tool dimple lock gun tubular lock picks fire emergency elevator key set usb keylogger and hak5 rubber ducky hak5 lan turtle pineapple nano lan tap wafer and warded pick set laptop or mobile device external hard drive fake letter of authorization as a plan b and to test incident response real letter of authorization props for guises if utilizing social engineering rfid thief cloner something that is easy to hide i often use a clipboard like the one shown in the picture above camera or just use your smartphone lock picks pocket common lock picks backpack expanded set under the door tool shove knife shrum tool crash bar tool snap gun with 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microsd cards smartphone earpiece if with a team body camera gopro ace cameras are sometimes handy with client approval extra power packs batteries small flashlight low lumen rtfm red team field manual analysis reports and slides internet of things research study hp 2014 report the internet of fails video cameras thermostats and home automation controllers hacking 14 iot devices hack all the things 20 devices in 45 minutes wiki video careful connections building security in the internet of things ftc analysis of iot honeypot data how devices are hacked type of infections and origin of attacks kaspersky lab 2018 communities iot villagetm builditsecure ly secure internet of things project stanford the open web application security project owasp iot hacks thingbots proofpoint uncovers internet of things iot cyberattack rfid vulnerabilities in first generation rfid enabled credit cards mit subway hack paper published on the web tampered card readers steal data via bluetooth home automation ioactive identifies vulnerabilities in belkin wemo s home automation cameras thermostats and home automation controllers hacking 14 iot devices popular home automation system backdoored via unpatched flaw connected doorbell cve 2015 4400 backdoorbot network configuration leak on a connected doorbell video hub twsl2013 023 lack of web and api authenticationvulnerability in insteon hub smart coffee reversing the smarter coffee iot machine protocol to make coffee using the terminal wearable how i hacked my smart bracelet smart plug hacking the d link dsp w215 smart plug reverse engineering the tp link hs110 hacking kankun smart wifi plug smart socket hack tutorial cameras trendnet cameras i always feel like somebody s watching me hacker hotshots eyes on izon surveilling ip camera security cameras thermostats and home automation controllers hacking 14 iot devices hacker shouts abuse via foscam baby monitoring camera urban surveillance camera systems lacking security twsl2014 007 multiple vulnerabilities in y cam ip cameras say cheese a snapshot of the massive ddos attacks coming from iot cameras samsung smartcam install php remote root command exec traffic lights green lights forever analyzing the security of traffic infrastructure hacking us and uk australia france etc traffic control systems automobiles hackers remotely attack a jeep on the highway comprehensive experimental analyses of automotive attack surfaces airplanes hackers could take control of a plane using in flight entertainment system light bulbs hacking into internet connected light bulbs hacking lightbulbs security evaluation of the philips hue personal wireless lighting system iot goes nuclear creating a zigbee chain reaction extended functionality attacks on iot devices the case of smart lights locks lockpicking in the iot smart scale fitbit aria wi fi smart scale smart meters solar power firm patches meters vulnerable to command injection attacks pacemaker pacemakers and implantable cardiac defibrillators software radio attacks and zero power defenses thermostats cameras thermostats and home automation controllers hacking 14 iot devices google nest exploiting dfu for root smart nest thermostat a smart spy in your home twsl2013 022 no authentication vulnerability in radio thermostat fridge proofpoint uncovers internet of things iot cyberattack spam emails from fridges hacking defcon 23 s iot village samsung fridge media player tv breaking secure boot on the roku google tv or how i learned to stop worrying and exploit secure boot chromecast exploiting the newest device by google ransomware ruins holiday by hijacking family s lg smart tv on christmas day firearms def con 25 plore popping a smart gun slides hacking a iot rifle blackhat 2015 36 slides hackers can disable a sniper rifle or change its target wired 2015 toilet twsl2013 020 hard coded bluetooth pin vulnerability in lixil satis toilet toys twsl2013 021 multiple vulnerabilities in karotz smart rabbit fisher price smart bear allowed hacking of children s biographical data cve 2015 8269 hello barbie initial security analysis security researcher ken munro discovers vulnerability in vivid toy s talking doll cayla data from connected cloudpets teddy bears leaked and ransomed exposing kids voice messages drones parrot drones hijacking rsa2018 video pedro cabrera march 2018 slides hacking the dji phantom 3 paolo stagno january 25 2017 phdays vi hacking syma x5c quadcopter pavel novikov and artur garipov june 9 2016 all your bebop drones still belong to us drone hijacking pedro cabrera 2016 shelling out on 3dr solo kevin finisterre june 15 2015 car hackinghttps github com jaredthecoder awesome vehicle security articles how to hack a car a quick crash course car enthusiast kenny kuchera illustrates just enough information to get you up and running an excellent resource for first timers stopping a jeep cherokee on the highway remotely chris valasek s and charlie miller s pivotal research on hacking into jeep s presented at defcon in 2015 troy hunt on controlling nissans troy hunt goes into controlling nissan vehicles tesla hackers explain how they did it at defcon overview of defcon 23 presentation on hacking into tesla cars anatomy of the rolljam wireless car hack overview of the rolljam rolling code exploitation device ioactive s tools and data chris valasek and charlie miller release some of their tools and data for hacking into vehicles in an effort to get more people into vehicle security research developments in car hacking via the sans reading room currie s paper analyses the risks and perils of smart vehicle technology car hacking on the cheap a whitepaper from chris valasek and ioactive on hacking your car when you don t have a lot of resources at your disposal car hacking the definitive source charlie miller and chris valasek publish all tools data research notes and papers for everyone for free car hacking on the cheap craig smith wrote a brief article on working with metasploit s hwbrige using elm327 bluetooth dongle researchers tackle autonomous vehicle security texas a m researchers develop intelligence system prototype how big data will impact car security in the proximate future concerns and solutions impact of big data on car security reverse engineering of the nitro obd2 reverse engineering of can diagnostic tools analysis of an old subaru impreza subaru select monitor v1 ssm1 digging into an old ecu through an old protocol and disabling a 1997 subaru impreza s speed limiter car hacking in 30 minutes or less using virtualbox and kali linux you can start car hacking using completely free open source software and tools including can utils icsim scantool wireshark and tcpdump presentations hopping on the can bus from blackhat asia 2015 a talk from blackhat asia 2015 that aims to enable the audience to gain an understanding of automotive systems but will also have the tools to attack them drive it like you hacked it from defcon 23 a talk and slides from samy kamkar s defcon 23 2015 talk that includes hacking garages exploiting automotive mobile apps and breaking rolling codes to unlock any vehicle with low cost tools samy kamkar on hacking vehicles with onstar samy kamkar the prolific hacker behind the samy worm on myspace explores hacking into vehicles with onstar systems remote exploitation of an unaltered passenger vehicle defcon 23 talk chris valasek and charlie miller give their now famous talk on hacking into a jeep remotely and stopping it dead in its tracks adventures in automotive networks and control units defcon 21 talk by chris valasek and charlie miller on automotive networks can you trust autonomous vehicles defcon 24 talk by jianhao liu chen yan wenyuan xu ken munro dave lodge hacking the mitsubishi outlander iot talk from bsides manchester 2016 by ken and dave of pen test partners a platform base on visualization for protecting can bus security syscan360 2016 sh talk by jianhao liu gateway internals of tesla motors zeronights 2016 talk by nie seng and liu ling car hacking 101 bugcrowd levelup 2017 by alan mond state of automotive cyber safety 2015 state of automotive hacking policy industry changes etc from i am the cavalry track at bsides las vegas 2015 state of automotive cyber safety 2016 state of automotive hacking policy industry changes etc from i am the cavalry track at bsides las vegas 2016 how to hack a tesla model s def con 23 talk by marc rogers and kevin mahaffey on hacking a tesla tesla co founder and cto jb straubel joins them to thank them and present a challenge coin car hacking videos a web page with a long list of videos 40 that are available online related to the topic of car hacking from a 2007 def con talk on modding engine ecus and onwards e g the 2017 keen security tesla hack self driving and connected cars fooling sensors and tracking drivers black hat talk by jonathan petit automated and connected vehicles are the next evolution in transportation and will improve safety traffic efficiency and driving experience this talk will be divided in two parts 1 security of autonomous automated vehicles and 2 privacy of connected vehicles 2015 a survey of remote automotive attack surfaces black hat talk by charlie miller and chris valasek automotive security concerns have gone from the fringe to the mainstream with security researchers showing the susceptibility of the modern vehicle to local and remote attacks discussion of vehicle attack surfaces 2014 pentesting vehicles with yacht yet another car hacking tool a presentation that discuesses different attack surfaces of a vehicle then continues to describe an approach to car hacking along with tools needed to analyse and gather useful information how to drift with any car introduction to can hacking and using a real car as an xbox controller car infotainment hacking methodology and attack surface scenario a guide on how to attack hunt bugs or hack your ivi by jay turla which was presented at the packet hacking village wall of sheep during def con 26 books 2014 car hacker s handbook free guide to hacking vehicles from 2014 you can also buy the book on amazon here 2016 car hacker s handbook latest version of the car hacker s handbook with updated information to hack your own vehicle and learning vehicle security for a physical copy as well unlimited pdf mobi and epub copies of the book buy it at no starch press sections are available online here a comprehensible guide to controller area network an older book from 2005 but still a comprehensive guide on can buses and networking in vehicles this book first introduced some basic knowledge of security for automotive r d personnel such as encryption and decryption security authentication digital signatures common attack types and methods then it introduced the working principles of some smart cars for security researchers such as the automotive intranet protocol network architecture principle of x by wire remote control system common potential attack surface etc finally a detailed analysis of some actual automotive attack or security test cases and defense analysis of the loopholes involved in the case during the analysis process controller area network prototyping with arduino this book guides you through prototyping can applications on arduinos which can help when working with can on your own car embedded networking with can and canopen from 2003 this book fills in gaps in can literature and will educate you further on can networks and working with embedded systems inside radio an attack and defense guidethis book discusses the security issues in a wide range of wireless devices and systems chapter 4 433 315mhz communication 4 3 4 4 4 5 is about car keys security research papers koscher et al experimental security analysis of a modern automobile 2010 comprehensive experimental analyses of automotive attack surfaces 2011 miller and valasek self proclaimed car hacking the definitive source adventures in automotive networks and control units aka car hacking car hacking for poories a survey of remote automotive attack surfaces 2014 remote compromise of an unaltered passenger vehicle aka the jeep hack 2015 advanced can message injection 2016 5 star automotive cyber safety framework 2015 a vulnerability in modern automotive standards and how we exploited it a car hacking experiment when connectivity meets vulnerability security issues and vulnerabilities in connected car systems automobile driver fingerprinting 2016 intrusion detection system based on the analysis of time intervals of can messages for in vehicle network 2016 modeling inter signal arrival times for accurate detection of can bus signal injection attacks courses udacity s self driving car engineer course the content for udacity s self driving car software engineer course the actual course on udacity s website is here blogs keen security lab blog blog created by keen security lab of tencent that posts research on car security websites opengarages provides public access documentation and tools necessary to understand today s modern vehicle systems defcon car hacking village car hacking exercises from defcon 24 canbushack hack your car course on vehicle hacking methodology owasp internet of things project owasp s project to secure iot from cars to medical devices and beyond i am the cavalry global grassroots eg volunteer initiative focused on the intersection of security and human life public safety issues such as cars participation from security researchers oems tier 1s and many others published automotive 5 star cyber safety framework carloop community community of people interested in car hacking and connecting vehicles to the cloud python security a website for browsing and buying python integrated cars having certain vehicular security features who to follow chris valasek security lead at uberatc twitter website charlie miller hacked the first apple iphone now does car security twitter samy kamkar created myspace worm rolljam ownstar twitter website justin seitz author of black hat python no starch press twitter troy hunt pluralsight author microsoft regional director and mvp for developer security creator of haveibeenpwned twitter website ken munro british researcher works at pen test partners major interest in vehicle security twitter opengarages initiative to created vehicle research labs around the world twitter website hackaday collaborative project hosting for hackers there are frequently car projects on here twitter pen test partners british penetration testing firm several posts concern their disclosed car security vulns twitter website i am the cavalry global grassroots eg volunteer initiative focused on the intersection of security and human life public safety issues such as cars twitter website discussion group car hacking village twitter website carfucar founder of car hacking village and speaker or trainer twitter ian tabor mintynet car hacker car hacking village staff twitter website podcasts and episodes podcasts security weekly excellent podcast covering all ranges of security with some episodes focusing portions on vehicle security from cars to drones trustedsec podcast from the people at trustedsec leaders in social engineering their episodes often go into recent vehicle vulnerabilities and exploits sans internet storm center the isc run a regular podcast going into the latest vulnerabilities and security news security ledger a podcast focusing on interviewing security experts about topics related to security episodes car hacking with craig smith software engineering daily did an amazing episode with craig smith author of the car hacking handbook above on hacking into vehicles big bugs podcast episode 1 auto bugs critical vulns found in cars with jason haddix jason haddix explores major vulnerabilities found in cars hacking under the hood and into your car chris valasek and charlie miller discuss with npr how they were able to hack into vehicles hacking connected vehicles with chris valasek of ioactive chris valasek talks about hacking into connected vehicles hackable cars are computers geoff siskind paired up with craig smith author of the car hacker s handbook to show us just how easy or not it is to hack a car miscellaneous https github com ps1337 automotive security research projects open vehicle monitoring system a community project building a hardware module for your car a server to talk to it and a mobile app to talk to the server in order to allow developers and enthusiasts to add more functionality to their car and control it remotely open source car control project the open source car control project is a hardware and software project detailing the conversion of a late model vehicle into an autonomous driving research and development vehicle hardware overview of hardware both open source and proprietary that you can use when conducting vehicle security research this article goes through many of the options below arduino arduino boards have a number of shields you can attach to connect to can enabled devices candiy shield chuangzhou can bus shield dfrobot can bus shield for arduino sparkfun can bus shield arduino canbus monitor no matter which shield is selected you will need your own sniffer this is implementation of standard lawicel slcan protocol for arduino any mcp can shield to use with many standard can bus analysis software packages or socketcan cantact the open source car tool designed to help you hack your car you can buy one or make your own following the guide here freematics obd ii telematics kit arduino based obd ii bluetooth adapter kit has both an obd ii device and a data logger and it comes with gps an accelerometer and gyro and temperature sensors elm327 the de facto chipset that s very cheap and can be used to connect to can devices goodthopter12 crafted by a well known hardware hacker this board is a general board that can be used for exploration of automotive networks usb2can cheap usb to can connector that will register a device on linux that you can use to get data from a can network intrepid tools expensive but extremely versatile tools specifically designed for reversing can and other vehicle communication protocols red pitaya replaces expensive measurement tools such as oscilloscopes signal generators and spectrum analyzers red pitaya has labview and matlab interfaces and you can write your own tools and applications for it it even supports extensions for things like arduino shields chipwhisperer a system for side channel attacks such as power analysis and clock glitching hackersdr a software defined radio peripheral capable of transmission or reception of radio signals from 1 mhz to 6 ghz designed to enable test and development of modern and next generation radio technologies carloop open source development kit that makes it easy to connect your car to the internet lowest cost car hacking tool that is compatible with socketcan and can utils no obd ii to serial cable required canbadger a tool for reverse engineering and testing automotive systems the canbadger consists of both hardware and software the main interface is a lpc1768 lpc1769 processor mounted on a custom pcb which offers two can interfaces sd card a blinky led some gpio pins power supply for peripherals and the ethernet port canspy a platform giving security auditors to audit can devices it can be used to block forward or modify can frames on the fly autonomously as well as interactively canbus triple general purpose controller area network swiss army knife and development platform usbtin usbtin is a simple usb to can interface it can monitor can busses and transmit can messages usbtin implements the usb cdc class and creates a virtual comport on the host computer openxc openxc is a combination of open source hardware and software that lets you extend your vehicle with custom applications and pluggable modules it uses standard well known tools to open up a wealth of data from the vehicle to developers started by researchers at ford it works for all 2002 and newer my vehicles standard obd ii interface researchers at ford motor company joined up to create a standard way of creating aftermarket software and hardware for vehicles macchina m2 macchina 2 0 is a complete overhaul of our 1 x generation of macchina the goals are still the same create an easy to use fully open and super compatible automotive interface pandwarf pandwarf is a pocket sized portable rf analysis tool operating the sub 1 ghz range it allows the capture analysis and re transmission of rf via an android device or a linux pc capture any data in ask ook msk 2 fsk gfsk modulation from the 300 928 mhz band can mitm bridge by muxscan a tool to mitm can messages allowing easy interaction with your car software applications software applications that will help you hack your car investigate it s signals and general tinkering with it wireshark wireshark can be used for reversing can communications kayak java application for can bus diagnosis and monitoring udsim gui tool that can monitor a can bus and automatically learn the devices attached to it by watching communications romraider an open source tuning suite for the subaru engine control unit that lets you view and log data and tune the ecu intrepid tools expensive but extremely versatile tools specifically designed for reversing can and other vehicle communication protocols o2oo works with the elm327 to record data to a sqlite database for graphing purposes it also supports reading gps data you can connect this to your car and have it map out using google maps kml data where you drive cantoolz cantoolz is a framework for analysing can networks and devices it is based on several modules which can be assembled in a pipeline busmaster an open source tool to simulate analyze and test data bus systems such as can lin flexray openxc currently openxc works with python and android with libraries provided to get started openpilot openpilot is an open source driving agent that performs the functions of adaptive cruise control acc and lane keeping assist system lkas for hondas and acuras openalpr an open source automatic license plate recognition library written in c with bindings in c java node js go and python metasploit the popular metasploit framework now supports hardware bridge sessions that extend the framework s capabilites onto hardware devices such as socketcan and sdr radios mazda aio tweaks all in one installer uninstaller for many available mazda mzd infotainment system tweaks mazda getinfo a poc that the usb port is an attack surface for a mazda car s infotainment system and how mazda hacks are made known bug in the cmu talking with cars can related scripts and scripts to use a car as a gamepad canalyzat0r a security analysis toolkit for proprietary car protocols libraries and tools custom applications sdk for mazda connect infotainment system a micro framework that allows you to write and deploy custom applications for the mazda infotainment system c socketcan utils userspace utilites for socketcan on linux vircar a virtual car userspace that sends can messages based on socketcan dbcc dbcc is a program for converting a dbc file primarily into into c code that can serialize and deserialize can messages with existing dbc files from a vehicle this file allows you to convert them to c code that extracts the can messages and properties of the can environment c high level viwi service high level volkswagen can signaling protocol implementation cancat a swiss army knife for interacting with live can data primary api interface in python but written in c python canard a python framework for controller area network applications caring caribou intended to be the nmap of vehicle security c0f a fingerprinting tool for can communications that can be used to find a specific signal on a can network when testing interactions with a vehicle python can python interface to various can implementations including socketcan allows you to use python 2 7 x or 3 3 x to communicate over can networks python obd a python module for handling realtime sensor data from obd ii vehicle ports works with elm327 obd ii adapters and is fit for the raspberry pi cancat a swiss army knife for interacting with live can data primary api interface in python but written in c scapy a python library to send receive edit raw packets supports can and automotive protocols see the automotive doc go cannibus a go server that allows a room full of researchers to simultaneously work on the same vehicle whether for instructional purposes or team reversing sessions can simulator a go based can simulator for the raspberry pi to be used with pican2 or the open source can simulator board javascript nodejs extension to socketcan allows you to communicate over can networks with simple javascript functions companies and jobs uberatc uber advanced technologies center info uberatc com tesla tesla hires security professionals for a variety of roles particularly securing their vehicles intrepid control systems embedded security company building tools for reversing vehicles rapid7 rapid7 does work in information computer and embedded security ioactive security consulting firm that does work on pentesting hardware and embedded systems coordinated disclosure general motors on hackerone coordinated disclosure submissions accepted fiat chrysler automobiles on bugcrowd coordinated disclosure submissions accepted paid bounties offered tesla motors on bugcrowd coordinated disclosure submissions accepted paid bounties offered talks and demonstration https www youtube com watch v k8rnq3mbzq4 https www youtube com watch v mk0srxbc1xs https www youtube com watch v 3jstabexgas t 7s https www youtube com watch v gzav1k5ksi4 https www youtube com watch v 1ripwqjg50c https www youtube com watch v 5csd8i396wo https www youtube com watch v fpqiwawxsri https www youtube com watch v caazxm5vsi0 t 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IoTClient.Examples | iotclient tool image https img shields io github license alienwow snowleopard svg iotclient tool iotclient https github com zhaopeiym iotclient iotclient tool 1 plc 2 iotclient https github com zhaopeiym iotclient visual studio 2019 qq 700324594 https jq qq com wv 1027 k tirmmgbt iotclient tool 1 https github com zhaopeiym iotclient examples releases download 1 0 3 iotclient exe 2 https download haojima net api iotclient download iotclient tool image https user images githubusercontent com 5820324 115138587 b7bebc80 a05f 11eb 9f7c 720a88bdca6e png image https user images githubusercontent com 5820324 115138592 bbeada00 a05f 11eb 9fc4 4b15a426cdb3 png image https user images githubusercontent com 5820324 115138594 bd1c0700 a05f 11eb 8d4b 34a567669e3d png image https user images githubusercontent com 5820324 115138596 bee5ca80 a05f 11eb 9878 9b05a4cfbc0b png image https user images githubusercontent com 5820324 115138597 c016f780 a05f 11eb 9d09 298a54f55266 png image https user images githubusercontent com 5820324 115138600 c2795180 a05f 11eb 92b0 1a1d278c20c8 png image https user images githubusercontent com 5820324 115138602 c3aa7e80 a05f 11eb 9cd7 be876735a26f png image https user images githubusercontent com 5820324 115138603 c5744200 a05f 11eb 9cdb a222aa9b7b25 png image https user images githubusercontent com 5820324 115138606 c73e0580 a05f 11eb 9ca1 5ece1bae8e71 png image https user images githubusercontent com 5820324 115138607 c86f3280 a05f 11eb 83f1 d1706331406a png | server |
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SmartNoteFils | smartnote todo list project team 1232 fils dragu andreea barbu bianca merdescu razvan ionita vlad javascript function mega cool encrypt string must make an aeray of all chars of the string var array for var i 0 i string length i array push string charat i we must have an array which contains the letters from our string var newstring console log array for var i 0 i array length i switch array i case 0 newstring z break case 1 newstring y break case 2 newstring x break case 3 newstring w break case 4 newstring v break case 5 newstring u break case 6 newstring t break case 7 newstring s break case 8 newstring r break case 9 newstring q break case a newstring p break case b newstring o break case c newstring n break case d newstring m break case e newstring l break case f newstring k break case g newstring j break case h newstring i break case i newstring h break case j newstring g break case k newstring f break case l newstring e break case m newstring d break case n newstring c break case o newstring b break case p newstring a break case q newstring 9 break case r newstring 8 break case s newstring 7 break case t newstring 6 break case u newstring 5 break case v newstring 4 break case w newstring 3 break case x newstring 2 break case y newstring 1 break case z newstring 0 break case newstring break default newstring array i break console log newstring function mega cool decrypt string must make an aeray of all chars of the string var array for var i 0 i string length i array push string charat i we must have an array which contains the letters from our string var newstring console log array for var i 0 i array length i switch array i case 0 newstring z break case 1 newstring y break case 2 newstring x break case 3 newstring w break case 4 newstring v break case 5 newstring u break case 6 newstring t break case 7 newstring s break case 8 newstring r break case 9 newstring q break case a newstring p break case b newstring o break case c newstring n break case d newstring m break case e newstring l break case f newstring k break case g newstring j break case h newstring i break case i newstring h break case j newstring g break case k newstring f break case l newstring e break case m newstring d break case n newstring c break case o newstring b break case p newstring a break case q newstring 9 break case r newstring 8 break case s newstring 7 break case t newstring 6 break case u newstring 5 break case v newstring 4 break case w newstring 3 break case x newstring 2 break case y newstring 1 break case z newstring 0 break case newstring break all the other cases default newstring array i break console log newstring mega cool encrypt mare bagabont | front_end |
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avalon | licensed under creative commons attribution 4 0 international license https creativecommons org licenses by 4 0 deprecation notice note this project is currently in deprecated state depending on your needs please refer to one of the following projects instead for core programming in enclave based confidential computation confidential computing consortium https confidentialcomputing io for using zero knowledge proofs in privacy preserving blockchain transactions hyperledger ursa https github com hyperledger ursa for achieving privacy using offchain data channels with blockchain coordination hyperledger firefly https github com hyperledger firefly for similar functionality private data objects https github com hyperledger labs private data objects a hyperledger lab for confidential smart contracts on hyperledger fabric hyperledger fabric private chaincode https github com hyperledger fabric private chaincode img src images hl avalon logo color png width 318 height 87 alt hyperledger avalon logo hyperledger avalon cii best practices https bestpractices coreinfrastructure org projects 3323 badge https bestpractices coreinfrastructure org projects 3323 hyperledger avalon formerly trusted compute framework enables privacy in blockchain transactions moving intensive processing from a main blockchain to improve scalability and latency and to support attested oracles the trusted compute specification was designed to help developers gain the benefits of computational trust and to mitigate its drawbacks in the case of the avalon a blockchain is used to enforce execution policies and ensure transaction auditability while associated off chain trusted compute resources execute transactions by using trusted off chain compute resources a developer can accelerate throughput and improve data privacy preservation of the integrity of execution and the enforcement of confidentiality guarantees come through the use of a trusted compute tc option e g zkp zero knowledge proof mpc multi party compute or a hardware based tee trusted execution environment while the approach will work with any tc option that guarantees integrity and confidentiality for code and data our initial implementation uses intel software guard extensions sgx hyperledger avalon leverages the existence of a distributed ledger to maintain a registry of the trusted workers including their attestation info provide a mechanism for submitting work orders from a client s to a worker preserve a log of work order receipts and acknowledgments hyperledger avalon uses the off chain trusted compute specification https entethalliance github io trusted computing spec html defined by enterprise ethereum alliance eea task force as a starting point to apply a consistent and compatible approach to all supported blockchains for more details on hyperledger avalon architecture see avalon arch pdf docs avalon arch pdf building to build hyperledger avalon follow instructions in the build document build md documentation hyperledger avalon documentation https hyperledger github io avalon contributing see the contributing document contributing md for information on how to contribute and the guidelines for contributions initial committers manjunath a c manju956 daniel anderson danintel thomas j barnes tombarnes srinath duraisamy srinathduraisamy manoj gopalakrishnan manojgop karthika murthy karthika ramakrishna srinivasamurthy ram srini yevgeniy y yarmosh eugeneyyy sponsor mic bowman cmickeyb tsc member license hyperledger avalon is released under the apache license version 2 0 software license see the license file license for more details hyperledger avalon documentation is licensed under the creative commons attribution 4 0 international license you may obtain a copy of the license at http creativecommons org licenses by 4 0 copyright 2019 2020 intel corporation | blockchain |
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book-mlearn-gyomu | python ai python ai tensorflow2 414 2020 10 22 isbn 10 4802612796 4802611641 isbn 13 978 4802612791 978 4802611640 apendix http amzn to 2hkmtyd https amzn to 2swamrm https kujirahand com blog go php 764 github code download zip n tensorflow1 https github com kujirahand book mlearn gyomu releases tag 1 0 0 ubuntu18 04 https github com kujirahand book mlearn gyomu blob master src vagrant ubuntu install sh pip install bash pip install upgrade scikit learn 0 22 2 post1 pip install upgrade opencv python 4 1 2 30 pip install upgrade tensorflow cpu 2 2 0 pip install upgrade keras 2 4 3 pip install upgrade flask 1 1 1 pip install upgrade pydot 1 4 1 pip install upgrade dlib 19 20 0 git git clone https github com kujirahand book mlearn gyomu git vagrant windows intel mac vagrant ubuntu vagrant ubuntu https kujirahand com blog go php 748 apple m1 mac 2021 11 01 tensorflow apple m1 rosetta pandas numpy scikit learn matplotlib https qiita com cheuora items c2111ed4d9956e804100 m1 mac https zenn dev karaage0703 articles 0ab9e654cfb0ec docker docker m1 mac deep learning https qiita com sonoisa items 6d6b4a81169397a96dd8 docker m1 mac https docs docker com desktop mac apple silicon docker pull sonoisa deep learning coding pytorch1 6 0 tensorflow2 3 0 cd src docker run it p 8888 8888 v pwd src sonoisa deep learning coding pytorch1 6 0 tensorflow2 3 0 docker cd src vagrant bash docker install sh pip seaborn wine import seaborn | ai |
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vue-architecture-boilerplate | p align center h2 align center vue architecture boilerplate h2 p align center vue js architecture for front end projects p p screenshot src assets screen png project setup sh install deps npm install compiles and hot reloads for development npm run serve compiles and minifies for production npm run build | front_end |
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Nodejs-Notes-App | nodejs notes app this is a simple notes app project aimed at learning backend development using node js and interacting with a mysql database the app allows users to create read update and delete notes additionally it includes user authentication with login and registration functionality input validation and user logout technologies used node js express framework mysql handlebars templating engine jwt json web tokens sass prerequisites before running the project ensure that you have the following prerequisites node js installed on your machine mysql server set up installation clone the repository sh git clone repository url navigate to the project directory sh cd notes app install dependencies sh npm install database setup create a new mysql database for the project import the database schema from the database schema sql file configuration create a new env file in the project s root directory configure the following environment variables in the env file sh port port database info db host db name db user jwt authentication jwt access key jwt refresh key usage run the application sh npm start access the app in your browser at http localhost 3000 | express handlebars jwt mysql nodejs | server |
ehr-blockchain | ehr 2 0 live live site hosted in firebase click here https ehr 2 0 web app for full working project apponitments br pdf upload br and much more br demo youtube https youtu be d pwoggdvs br setup youtube https youtube com playlist list pl54v i7zw55d1vkxekp9dcpt5k ze6m3x contact mail mailto tshamil90 gmail com subject ehr blockchain body hi tshamil90 gmail com 1 install nodejs node js https nodejs org en download 2 install ganache ganache truffle https www trufflesuite com ganache 3 download ipfs kubo ipfs kubo https dist ipfs tech go ipfs configure ipfs refer https github com shamil t ehr blockchain issues 15 issuecomment 1333342345 4 add metamask extension in browser metamask chrome https chrome google com webstore detail metamask nkbihfbeogaeaoehlefnkodbefgpgknn hl en us 5 open cmd in project directory npm install force 5 open cmd terminal as administrator and type npm install g truffle 6 open ganache new workspace addproject select truffle config js in project directory save workspace 7 compile and migrate contracts truffle migrate 8 run server npm start known issue https github com shamil t ehr blockchain issues 15 | ethereum-blockchain ethereum-contract ethereum-dapp reactjs medical-records ehr blockchain truffle-framework metamask ganache-cli ipfs ipfs-blockchain ipfs-api angular bootstrap5 | blockchain |
recipes | recipes some interesting for me notes on development practices at least to not forgot them heroku heroku create and deploy apps nodejs nodejs whatelse weaponsofmassdestruction 42 itseemsthatpeopleusesomethingelse | server |
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CHP05-Unity-step-by-step- | chp05 unity step by step unity in embedded system design and robotics a step by step guide | os |
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react-cool-starter | em b react cool starter b em a simple but feature rich starter boilerplate for creating your own universal https medium com mjackson universal javascript 4761051b7ae9 app it built on the top of react https facebook github io react redux https github com reactjs redux react router https reacttraining com react router and express https expressjs com includes all the hot stuff and modern web development tools such as redux toolkit https redux toolkit js org typescript https www typescriptlang org webpack https webpack js org babel https babeljs io postcss https github com postcss postcss loader react refresh https github com facebook react tree master packages react refresh jest https facebook github io jest and react testing library https github com testing library react testing library see the features features section for other awesome features you can expect i will maintain the starter boilerplate and keep all of the technologies on trend welcome to join me if you want hope you guys love it build status https img shields io github workflow status wellyshen react cool starter ci style flat square https github com wellyshen react cool starter actions query workflow 3aci coverage status https img shields io coveralls github wellyshen react cool starter style flat square https coveralls io github wellyshen react cool starter branch master dependencies status https img shields io david wellyshen react cool starter style flat square https david dm org wellyshen react cool starter devdependencies status https img shields io david dev wellyshen react cool starter style flat square https david dm org wellyshen react cool starter type dev code style prettier https img shields io badge code style prettier ff69b4 style flat square https github com prettier prettier all contributors https img shields io badge all contributors 22 orange style flat square contributors prs welcome https img shields io badge prs welcome brightgreen style flat square contributing md twitter url https img shields io twitter url style social url https 3a 2f 2fgithub com 2fwellyshen 2freact cool starter https twitter com intent tweet text with 20 react cool starter 20i 20can 20build 20my 20universal 20web 20app 20easily 20thanks 20 welly 20shen 20 real case study if you have built a production web app based on this starter please open a pr to add it here spinny https www spinny com is a fully inspected highest quality second hand cars with money back guarantee simple and transparent buying bam music https www bammusic com is a new generation of music platform for audio visual professionals filmmakers and content producers upgrade your soundtrack with great music that emphasizes your story rendah mag https www rendahmag com is a music magazine which exists to bring exposure to an ever growing community focusing on the latest halftime beats experimental news releases congrats for the amazing product dealdrop https www dealdrop com is the best place to find verified coupon codes deals promos and offers for thousands of stores brands you love never pay full price again beck friends https www beckfriends com is an international delivery service which is built based on this starter boilerplate congrats for successful migrating to react features really cool starter boilerplate with the most popular technologies universal https medium com mjackson universal javascript 4761051b7ae9 rendering with async data fetching react https facebook github io react as the view library redux https github com reactjs redux as the state management redux toolkit https redux toolkit js org for efficient redux development react router https reacttraining com react router as the router connected react router https github com supasate connected react router to bind redux with react router refer to document https github com supasate connected react router blob master faq md frequently asked questions to see how it works express https expressjs com server typescript https www typescriptlang org as the static type checker for javascript webpack https webpack js org for app bundling babel https babeljs io for transpile es6 to es5 react refresh https github com facebook react tree master packages react refresh to fast refresh components without losing their state nodemon https nodemon io to monitor for any changes in your node js application and automatically restart the server axios https axios http com as the promise based http client for the browser and node js react helmet https github com nfl react helmet to manage title meta styles and scripts tags on both server and client loadable component https github com smooth code loadable components to lazy load a component when needed reduce your bundle size without stress webpack dev middleware https github com webpack webpack dev middleware serves the files emitted from webpack over the express server webpack hot middleware https github com glenjamin webpack hot middleware allows you to add hot reloading into the express server webpack bundle analyzer https github com webpack contrib webpack bundle analyzer creates a visualize size of webpack output files with an interactive zoomable treemap helmet https github com helmetjs helmet hpp https github com analog nico hpp and compression https github com expressjs compression for server side security and performance server side security and performance morgan https github com expressjs morgan the http request logger for server side debugging eslint http eslint org to maintain a consistent typescript javascript code style with airbnb configuration stylelint http stylelint io to maintain a consistent css sass code style prettier https prettier io to format code and style css and sass support with postcss https github com postcss postcss loader for advanced transformations e g autoprefixer cssnext etc css modules https github com css modules css modules enabled image optimized compressed by imagemin webpack https github com webpack contrib image minimizer webpack plugin and font support minimize javascript by terser webpack plugin https github com webpack contrib terser webpack plugin and css by css minimizer webpack plugin https github com webpack contrib css minimizer webpack plugin bundles for you split vendor s libraries from client bundle no other view engines just javascript based html rendering component shared app configuration between development and production 404 error page and redirect handling integrate jest https facebook github io jest with react testing library https github com testing library react testing library as the solution for writing unit tests with code coverage support yarn https yarnpkg com lang en as the package manager who s the starter for they re several react frameworks today however this is a diy oriented start kit it shows you how to build a universal web app from scratch and how to test it if you re new to react or you want a ready to go solution i d recommend the following alternatives for you for client side rendering use create react app https create react app dev for server side rendering use next js https nextjs org requirements node https nodejs org en 12 0 npm https www npmjs com 6 0 looking for docker image you can find docker support version on this branch https github com wellyshen react cool starter tree docker getting started 1 you can start by cloning the repository on your local machine by running sh git clone https github com wellyshen react cool starter git cd react cool starter 2 install all of the dependencies sh yarn 3 start to run it sh yarn build building bundle yarn start running production server now the app should be running at http localhost 8080 http localhost 8080 note you can change the port that you want from the src config script commands i use cross env https github com kentcdodds cross env to set and use environment variables across platforms all of the scripts are listed as following yarn script description dev runs your app on the development server at localhost 3000 hmr will be enabled dev build bundles server side files in development mode and put it to the public server start runs your app on the production server only at localhost 8080 build bundles both server side and client side files build server bundles server side files in production mode and put it to the public server build client bundles client side files in production mode and put it to the public assets analyze server visualizes the bundle content of server side analyze client visualizes the bundle content of client side lint lints all tsx jsx and scss files lint code lints all tsx and jsx files with fix to auto fix eslint errors lint type runs type checking for tsx files lint style lints all scss files with fix to auto fix stylelint errors lint format formats all files except the file list of prettierignore test runs testing test watch runs an interactive test watcher test cov runs testing with code coverage reports test update updates jest snapshot app structure here is the structure of the app which serves as generally accepted guidelines and patterns for building scalable apps public express server static path and webpack bundles output favicon ico app favicon logo192 png app logo small logo512 png app logo large manifest json app favicon and logo manifest src app source code config app configuration by environments default ts default settings index ts configuration entry point prod ts production settings overrides the default components reusable components pages page components app app root component store redux store creator actions reducers a k a slice services api calls utils app wide utils e g mock store creator for testing etc static static assets e g images fonts etc theme app wide style and vendor css framework types app wide type definitions client app bootstrap and rendering webpack entry routes routes configuration for both client side and server side server express server with webpack dev and hot middlewares webpack webpack configurations jest jest configurations babel config js babel configuration tsconfig json typescript configuration postcss config js postcss configuration eslintrc js eslint configuration stylelintrc js stylelint configuration nodemon json nodemon configuration server side security and performance concerning the security and performance of express in production i already setup some middleware for you helmet https github com helmetjs helmet helps secure express server with various http headers hpp https github com analog nico hpp express middleware to protect against http parameter pollution attacks compression https github com expressjs compression gzip compression support for speeding up express server responses note it s just a basic protected mechanism for your app you can see the security best practices https expressjs com en advanced best practice security html for more advanced configuration develop with redux toolkit redux toolkit https redux toolkit js org is the official opinionated batteries included toolset for efficient redux development it includes several utility functions that simplify the most common redux use cases in a word we can do more work with less code start from the tutorial https redux toolkit js org tutorials basic tutorial to learn more about it supports redux devtools extension https github com zalmoxisus redux devtools extension you can follow the installation guide https github com zalmoxisus redux devtools extension installation to use it built ins most commonly used redux middlewares https redux toolkit js org api getdefaultmiddleware included default middleware for better dx such as redux thunk https github com reduxjs redux thunk immer https immerjs github io immer etc provides useful apis https redux toolkit js org api createreducer for better development efficiency we can even create entire slices https redux toolkit js org api createslice of state at once without writing any action creators or action types by hand integrates the reselect library https github com reduxjs reselect for optimizing the performance of your react redux app let s see how powerful it is by a simple asynchronous data fetching example js import createslice from reduxjs toolkit import axios from axios const initialstate readystatus invalid items error null const userlist createslice a name for action types name userlist initialstate an object of case reducers key names will be used to generate actions reducers getrequesting state write an immutable updated state by a mutable way thanks to the built in immer middleware state readystatus request getsuccess state payload state readystatus success state items payload getfailure state payload state readystatus failure state error payload we can get the reducer and actions from the slice instance export default userlist reducer const getrequesting getsuccess getfailure userlist actions export const fetchuserlist async dispatch dispatch getrequesting try const data await axios api users dispatch the action once data is ready via the built in redux thunk middleware dispatch getsuccess data catch error dispatch getfailure error message overview functional components and hooks react v16 8 introduced a series of hooks https reactjs org docs hooks intro html which let you use state and other react features without writing a class in the starter boilerplate you can see how i leverage the benefit of functional components https reactjs org docs components and props html function and class components hook apis to write a demo with clean code adding routes this starter use react router https reacttraining com react router library to manage our routes for the purpose of ssr with data pre fetched i put the routes in a centralized route config https reacttraining com react router web example route config you can setup your routes in the src routes index ts for example js import pagecomponent from pages pagecomponent export default define your route path path top path if the route matches the location pathname exactly or not used for index route usually exact true add your page component here component pagecomponent add your sub route component here routes path top path sub path component subcomponent other routes data fetching from server side strongly recommend to write redux actions and reducers via the createslice https redux toolkit js org api createslice api of redux toolkit start from the tutorial https redux toolkit js org tutorials basic tutorial if you are new the starter using axios https axios http com as the data fetcher it s quite simple and easy to use if the action is asynchronous then it will return a promise or a promise all in the inner function register the action s in the src routes index ts which have to be called from server side js export default path top path exact true component pagecomponent async actions in the loaddata function will be fetched from server side you can access the url parameters redux store http request and response by the event object loaddata params getstate req res myreduxaction more pre fetched actions the action s will be dispatched through the src server ssr tsx on server side js app get req res here s the method for loading data from server side const loadbranchdata const branch matchroutes routes req path const promises branch map route match if route loaddata return promise all route loaddata params match params getstate store getstate req res map item store dispatch item return promise resolve null return promise all promises in client side don t forget to invoke the action s in componentdidmount or useeffect hook this ensures that if the component is reached on the client then the same actions will be invoked it s up to the action s to figure out if fetches for data need to be made or not js use react class component componentdidmount invoke your redux action s for client rendering this props myreduxaction use functional component useeffect myreduxaction for better architecture we can centralize the data fetching methods in one place like how i did in the home src pages home home tsx page js const somepage fetch client side data here useeffect dispatch fetchuserlistifneed dispatch fetch server side data here the method will be used by the route config export const loaddata fetchuserlistifneed export default somepage code splitting one great feature of the web is that you don t have to make your visitors download the entire app before they can use it you can think of code splitting as incrementally downloading the app it divides your code into small pieces called chunks to reduce the size of bundle loaded by user reducing the size of a chunk makes it load and run faster to accomplish this i integrate loadable components https loadable components com into this starter the reason i choose the library is because of its design philosophy of ssr it works seamless with the starter rather than others let s see how we split our app by page i use the following folder file structure pages somepage pagecomponent tsx the page component index tsx wrap the component into async component the index tsx will be js import loadable from loadable component import error loading from components import loaddata from pagecomponent dynamically import your page component const asyncpage loadable import pagecomponent loading will be displayed when the component is being loaded fallback loading export default props wrap an errorboundary to catch the error of asyncpage via componentdidcatch life cycle errorboundary asyncpage props errorboundary export loaddata export ssr data fetching method as well then you can setup adding routes the route as usual note i just show a general case page based splitting however you can even split your app by component based depends on your needs for more advanced configuration please refer to the document https loadable components com docs getting started in additional loadable components supports webpack pre fetching pre loading https webpack js org guides code splitting prefetchingpreloading modules out of the box link rel preload and link rel prefetch can be added directly server side to improve performances managing title meta styles and scripts the src app index tsx app root component defines the base title and meta in a helmet config app component any sub component can override add properties supports meta link script style tags and html attributes see the react helmet https github com nfl react helmet document for more info app configuration you can store app settings under the src config by default the default ts will be loaded if the process env node env matches to production alias as dev the prod ts will be used instead and it inherits the properties of default ts you can access the correct configuration with js import config from config styles the starter supports css sass and css modules https github com css modules css modules is auto enabled for all files the name module naming convention i use postcss https github com postcss postcss loader plugin to parse css and add autoprefixer to your stylesheet you can access your stylesheet with two ways with css modules js import styles from styles module scss return div classname styles myclass the classname matches one of css classes in your scss file helmet title my title this rendercontent div without css modules js import styles scss return div classname myclass use the css class as normal helmet title my title this rendercontent div by the way if you want to use vendor css frameworks or global styles just import it through the src app index tsx file app root component for example js import theme normalize css import the vendor stylesheet first import styles from styles scss then your based stylesheet const app route image and font it s super easy to render the image and font both on client and server the usage would be like below using image js import logo from static logo svg img src logo alt logo role presentation using font awesome js with css modules import styles from styles scss return div div i classname styles iconuser welly div div without css modules import font awesome css return div div i classname fa fa icon welly div div for using css modules you have to set the proper font path in your scss sass file scss fa font path node modules font awesome fonts import node modules font awesome scss font awesome icon user extend fa extend fa user boost app performance in this starter you can see i use react purecomponent https reactjs org docs react api html reactpurecomponent and react memo https reactjs org blog 2018 10 23 react v 16 6 html reactmemo to demonstrate the basic performance optimizing for react app the two apis are used in different ways react purecomponent is used for react class components it can do shallow prop and state comparison for a performance boost js import purecomponent from react class mycomponent extends purecomponent only re renders if props change react memo is used for functional components it plays the same role as react purecomponent js import memo from react const mycomponent memo props only re renders if props change in addition you can also use react hooks like usememo https reactjs org docs hooks reference html usememo or usecallback https reactjs org docs hooks reference html usecallback to avoid expensive calculations on every render js import usememo usecallback from react performance optimizing via usememo const parentcomponent props div only re renders if a change usememo childcomponent someprop a a div performance optimizing via usecallback const parentcomponent props div return a memorized callback that only changes if a changed this is useful to prevent child component from unnecessary renders childcomponent callback usecallback dosomething a a div for more performance optimizing techniques please see the optimizing performance https reactjs org docs optimizing performance html topic typescript typescript https www typescriptlang org is a typed super set of javascript it s getting more and more popular in the front end world and being widely used by many libraries if you are new to typescript you can check out its document here https www typescriptlang org docs handbook typescript in 5 minutes html typescript has been integrated with our application to bring the following benefits type safety for components reducers state and actions many ides support the hints of typescript which give us a superior developer experience easy refactoring of typed code in general more types less bugs read this article https medium com javascript scene the typescript tax 132ff4cb175b to learn more code and style lint eslint http eslint org with airbnb configuration typescript eslint https github com typescript eslint typescript eslint stylelint http stylelint io prettier https prettier io and lint staged https github com okonet lint staged are integrated into this starter to maintain a consistent code style and give you a elegant code formatting you can configure your lint rules through the eslintrc js stylelintrc js and prettier configuration file https prettier io docs en configuration html unit testing this starter use jest https facebook github io jest as the testing framework we also use react testing library https github com testing library react testing library with jest dom https github com testing library jest dom give you a simple and complete react dom testing utilities that encourage good testing practices jest support the feature of snapshot testing https jestjs io docs en snapshot testing which is very powerful for testing react component give it a try you ll be impressed the unit testing focus on three parts as below components actions reducers by the way jest built in code coverage reports the report files are generated in the coverage folder you can configure the jest config js to define which files that you want to cover for example js module exports collectcoveragefrom src pages tsx define the files which want to be covered src pages index ts the files will be ignored by code coverage other configurations you can also use istanbul s ignore hints https github com gotwarlost istanbul blob master ignoring code for coverage md ignoring code for coverage purposes to specify specific lines of code in a javascript file to skip code coverage how to deploy to deploy you app to cloud service e g aws gcp azure etc you can follow the instructions below 1 build then install production dependencies sh yarn build building bundle rm rf node modules after building remove node modules yarn install production then install dependencies only 2 pack necessary folders files to your node js server public node modules package json 1 run your app sh yarn start ideally the above steps can be integrated into your ci i recommend you to pack the yarn lock file for yarn installation by ci troubleshooting if you encounter the markup mismatches error it s a react universal issue which usually occurs due to the non synchronized rendering result between client and server you can do restart the server to solve it or for v16 1 0 up you can use suppresshydrationwarning attribute for intentional client server text mismatches 11126 https github com facebook react pull 11126 if you are on windows and encounter the following error expected linebreaks to be lf but found crlf linebreak style the following rule must be added to eslintrc js rules linebreak style off other rules contributors thanks goes to these wonderful people emoji key https allcontributors org docs en emoji key all contributors list start do not remove or modify this section prettier ignore start markdownlint disable table tr td align center a href https wellyshen com img src https avatars1 githubusercontent com u 21308003 v 4 width 100px alt br sub b welly b sub a br a href https github com wellyshen react cool starter commits author wellyshen title code a a href https github com wellyshen react cool starter commits author wellyshen title documentation a a href maintenance wellyshen title maintenance a td td align center a href https github com microflow img src https avatars1 githubusercontent com u 15410443 v 4 width 100px alt br sub b microflow b sub a br a href translation microflow title translation a td td align center a href http bacchetta co img src https avatars0 githubusercontent com u 12591890 v 4 width 100px alt br sub b jason bacchetta b sub a br a href tool jabacchetta title tools a td td align center a href https github com xakep139 img src https avatars2 githubusercontent com u 6381023 v 4 width 100px alt br sub b nikita balabaev b sub a br a href https github com wellyshen react cool starter commits author xakep139 title code a td td align center a href https github com jmsherry img src https avatars1 githubusercontent com u 697341 v 4 width 100px alt br sub b james sherry b sub a br a href infra jmsherry title infrastructure hosting build tools etc a a href https github com wellyshen react cool starter issues q author 3ajmsherry title bug reports a td td align center a href https github com zace img src https avatars0 githubusercontent com u 3301615 v 4 width 100px alt br sub b zack pelz b sub a br a href translation zace title translation a td td align center a href https github com apapacy img src https avatars3 githubusercontent com u 4279840 v 4 width 100px alt br sub b apapacy b sub a br a href https github com wellyshen react cool starter commits author apapacy title code a td tr tr td align center a href https github com martin2786 img src https avatars3 githubusercontent com u 2111808 v 4 width 100px alt br sub b martin2786 b sub a br a href https github com wellyshen react cool starter commits author martin2786 title documentation a td td align center a href https github com iamacup img src https avatars2 githubusercontent com u 12894620 v 4 width 100px alt br sub b iamacup b sub a br a href tool iamacup title tools a td td align center a href http zhogov me img src https avatars1 githubusercontent com u 5165362 v 4 width 100px alt br sub b maxim b sub a br a href tool forwardomg title tools a td td align center a href http stackoverflow com users 451634 benny neugebauer img src https avatars3 githubusercontent com u 469989 v 4 width 100px alt br sub b benny neugebauer b sub a br a href translation bennyn title translation a td td align center a href https lapkov com img src https avatars2 githubusercontent com u 12545211 v 4 width 100px alt br sub b a s lapkov b sub a br a href https github com wellyshen react cool starter commits author aslapkov title code a td td align center a href https github com alirezavalizade img src https avatars0 githubusercontent com u 14992757 v 4 width 100px alt br sub b alireza valizade b sub a br a href https github com wellyshen react cool starter commits author alirezavalizade title code a td td align center a href https github com rid img src https avatars2 githubusercontent com u 3407496 v 4 width 100px alt br sub b grant millar b sub a br a href https github com wellyshen react cool starter issues q author 3arid title bug reports a a href https github com wellyshen react cool starter commits author rid title code a td tr tr td align center a href https github com bjvda img src https avatars3 githubusercontent com u 9120530 v 4 width 100px alt br sub b bart b sub a br a href https github com wellyshen react cool starter issues q author 3abjvda title bug reports a td td align center a href https stackoverflow com users 3078890 morteza tourani img src https avatars2 githubusercontent com u 2953251 v 4 width 100px alt br sub b morteza tourani b sub a br a href https github com wellyshen react cool starter commits author mortezat title code a td td align center a href http www tomkiernan co uk img src https avatars2 githubusercontent com u 13321712 v 4 width 100px alt br sub b tom kiernan b sub a br a href translation tomkiernan120 title translation a td td align 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denny64 title documentation a a href https github com wellyshen react cool starter commits author denny64 title code a td tr tr td align center a href https mattcarlotta io img src https avatars1 githubusercontent com u 22607722 v 4 width 100px alt br sub b matt carlotta b sub a br a href https github com wellyshen react cool starter commits author mattcarlotta title code a td tr table markdownlint enable prettier ignore end all contributors list end this project follows the all contributors https github com all contributors all contributors specification contributions of any kind welcome | redux express css-modules react-router webpack react redux-toolkit unit-testing boilerplate typescript es6 universal react-hooks performance security starter server-side-rendering jest testing-library-react code-splitting | front_end |
deeplearning-nlp2018 | ling530f deep learning for natural language processing dl nlp the university of british columbia year winter session i 2018 2019 time mon wed 13 30 15 00pm location west mall swing space room 408 instructor dr muhammad abdul mageed office location school of information ischool 494 office phone 6048 274 530 office hours mon 11 00am 1 00pm or by appointment i can also handle inquiries via email or skype e mail address muhammad mageed ubc ca student portal http canvas ubc ca 1 course rationale goal rationale background natural language processing nlp is the field focused at teaching computers to understand and generate human language dialog systems where the computer interacts with humans such as the amazon echo constitute an instance of both language understanding and generation as the machine attempts to identify the meaning of questions and generate meaningful answers recent advances in machine learning especially in deep learning a class of machine learning methods inspired by information processing in the human brain have boosted performance on several nlp tasks deep learning of natural language is in its infancy with expected breakthroughs ahead solving nlp problems directly contributes to the development of pervasive technologies with significant social and economic impacts and the potential to enhance the lives of millions of people given the central role that language plays in our lives advances in deep learning of natural language have implications across almost all fields of science and technology as well as many other disciplines like linguistics as nlp and deep learning are instrumental for making sense of the ever growing data collected in these fields goal this course provides a graduate level introduction to natural language processing with deep learning the goal of the course is to familiarize students with the major nlp problems and the primary deep learning methods being developed to solve them this includes problems at various linguistic levels e g word and sub word phrase clause and discourse methodologically this involves unsupervised distributed representations and supervised deep learning methods across these linguistic levels the course also includes providing an introductory level of hands on experience in using deep learning software as well as opportunities to develop advanced solutions for nlp problems in the context of a final project potential audiences for this course are students with a linguistics and or a computer science background interested in learning novel nlp methods with a focus on deep learning people interested in nlp text analytics information retrieval information visualization human information interaction machine learning and deep learning etc who want to prepare for or advance carrying out research in these fields exploiting deep learning of natural language methods 2 course objectives upon completion of this course students will be able to identify the inherent ambiguity in natural language and appreciate challenges associated with teaching machines to understand and generate it become aware of a core of nlp problems and demonstrate how these are relevant to the lives of diverse individuals communities and organizations become aware of the major deep learning methods being developed for solving nlp problems and be in a position to apply this deepened understanding in critical creative and novel ways collaborate effectively with peers through course assignments identify an nlp problem existing or novel and apply deep learning methods to develop a solution for it 3 course topics ambiguity in human language across different levels week 01 learning words phrases word vectors weeks 2 3 and sentences recurrent neural networks convolutional neural networks seq2seq models deep generative models auo encoders and generative adversarial networks applications pos tagging and morphological disambiguation learning in low resource languages language dialect identification emotion and sentiment analysis natural language inference machine translation 4 prerequisites have some familiarity with at least one linguistics field have some familiarity with basic linear algebra basic calculus and basic probability basic high school level have programming experience in python have access to a computer preferably with a gpu on a regular basis students lacking any of the above pre requisites must be open to learn outside their comfort zone to make up including investing time outside class learning these pre requisites on their own some relevant material across these pre requisites will be provided as part of the syllabus should you have questions about pre requisites please email the instructor 5 format of the course this course will involve lectures class hands on activities individual and group work and instructor peer and self assessment 6 course syllabus required books goodfellow i bengio y courville a bengio y 2016 deep learning vol 1 cambridge mit press available at link http www deeplearningbook org goldberg y 2017 neural network methods for natural language processing synthesis lectures on human language technologies 10 1 1 309 jurafsky d martin j h 2017 speech and language processing london pearson available at link https web stanford edu jurafsky slp3 ed3book pdf other recommended books bird s klein e loper e 2009 natural language processing with python o reilly media inc link http www nltk org book weekly readings will be assigned from materials available through the ubc library and online see readings section below 7 calendar weekly schedule tentative date slides related content what is due out mon sept 3 labor day ubc closed na wed sept 5 course overview na mon sept 10 guest speaker mam ecml emilie francis sfu misinformation linear algebra i dlb ch02 https www deeplearningbook org contents linear algebra html mit course https www youtube com watch v zk3o402wf1c list ple7ddd91010bc51f8 hw01 out canvas wed sept 12 guest speaker mam ecml michael przystupa ubc linear algebra ii class slides https github com ubc nlp deeplearning nlp2018 blob master slides linearalgpresentation ipynb dlb ch02 https www deeplearningbook org contents linear algebra html mon sept 17 probability i dl intro slides https github com ubc nlp deeplearning nlp2018 blob master slides deep learning intro pdf prob slides https github com ubc nlp deeplearning nlp2018 blob master slides probability pdf semeval2019 slides https github com ubc nlp deeplearning nlp2018 blob master slides semeval pdf dlb ch03 https www deeplearningbook org contents prob html ka https www khanacademy org math statistics probability probability probability geometry harvard stats https www youtube com playlist list pl2sou6wwxb0uwwh80ktq6ht66kwxbztio wed sept 19 probability ii dlb ch03 https www deeplearningbook org contents prob html kai https www khanacademy org computing computer science informationtheory info theory v intro information theory kaii https www khanacademy org computing computer science informationtheory mon sept 24 information theory machine learning basics i info theory slides https github com ubc nlp deeplearning nlp2018 blob master slides information theory pdf ml basics slides https github com ubc nlp deeplearning nlp2018 blob master slides ml basics pdf dlb ch05 https www deeplearningbook org contents ml html ka calculus https www youtube com watch v ekvhqc3qeow list pl19e79a0638c8d449 3b1b essence of calculus https www youtube com watch v wuvtyaankzm list plzhqobowtqdmsr9k rj53dwvrmyo3t5yr wed sept 26 machine learning basics ii same as last session mon oct 1 word meaning word meaning slides https github com ubc nlp deeplearning nlp2018 blob master slides word meaning pdf jm ch06 vector semantics https web stanford edu jurafsky slp3 6 pdf wed oct 3 language models language models slides https github com ubc nlp deeplearning nlp2018 blob master slides lang models pdf pytorch linear regression tutorial https github com ubc nlp deeplearning nlp2018 blob master slides linearregressionpytorchtutorial ipynb theano linear regression tutorial https github com ubc nlp deeplearning nlp2018 blob master slides logistic regression theano ipynb jm ch03 https web stanford edu jurafsky slp3 3 pdf a neural probabilistic language model http www cs ubc ca amuham01 ling530 papers bengio2003neural pdf hw01 due hw02 out mon oct 8 thanksgiving day ubc closed na wed oct 10 word vectors word2vec word2vec slides https github com ubc nlp deeplearning nlp2018 blob master slides word2vec pdf distributed representations of words and phrases and their compositionality http www cs ubc ca amuham01 ling530 papers mikolov2013distributed pdf efficient estimation of word representations in vector space http www cs ubc ca amuham01 ling530 papers mikolov2013efficient pdf linguistic regularities in continuous space word representations http www cs ubc ca amuham01 ling530 papers mikolov2013linguistic pdf enriching word vectors with subword information http www cs ubc ca amuham01 ling530 papers bojanowski2016enriching pdf mon oct 15 feedforward networks feed forward nets slides https github com ubc nlp deeplearning nlp2018 blob master slides feedforward nets pdf dlb ch06 https www deeplearningbook org contents mlp html wed oct 17 embeddings from language models guest speaker mark neuman ai2 semi supervised seq tagging with bidirectional models http www cs ubc ca amuham01 ling530 papers peters2017semi pdf elmo http www cs ubc ca amuham01 ling530 papers peterselmo2018 pdf dissecting contextual word embeddings http www cs ubc ca amuham01 ling530 papers peters2018dissecting pdf mon oct 22 recurrent neural networks i rnn slides https github com ubc nlp deeplearning nlp2018 blob master slides rnn pdf dlb ch10 https www deeplearningbook org contents rnn html wed oct 24 recurrent neural networks ii dlb ch10 https www deeplearningbook org contents rnn html mon oct 29 applications text classification project discussion application slides https github com ubc nlp deeplearning nlp2018 blob master slides applications pdf wed oct 31 gradient based optimization optimization slides https github com ubc nlp deeplearning nlp2018 blob master slides optimization pdf hw02 due mon nov 5 applications application slides https github com ubc nlp deeplearning nlp2018 blob master slides applications pdf hw03 a due wed nov 7 seq2seq neural machine translation rnn2 slides https github com ubc nlp deeplearning nlp2018 blob master slides rnn 2 pdf grammar as a foreign language http www cs ubc ca amuham01 ling530 papers vinyals2015grammar pdf asma a system for arabic morphosyntax http www aclweb org anthology r13 1001 mon nov 12 remembrance day ubc closed na wed nov 14 ai society guest speaker christine wolf ibm applications lexical dialectology backprobagation i christine slides https github com ubc nlp deeplearning nlp2018 blob master slides wolf ubc pptx backpropagation slides https github com ubc nlp deeplearning nlp2018 blob master slides backpropagation pdf deep models for arabic dialect identification on benchmarked data http www cs ubc ca amuham01 ling530 papers elarabydeepmodels2018 pdf a neural model for user geolocation and lexical dialectology http www cs ubc ca amuham01 ling530 papers rahimigeoloc2017 pdf mon nov 19 backprobagation ii convnets i backpropagation slides https github com ubc nlp deeplearning nlp2018 blob master slides backpropagation pdf convnet slides https github com ubc nlp deeplearning nlp2018 blob master slides cnns pdf dlb ch09 https www deeplearningbook org contents convnets html wed nov 21 convnets ii lstms grus cnn slides https github com ubc nlp deeplearning nlp2018 blob master slides cnns pdf lstm slides https github com ubc nlp deeplearning nlp2018 blob master slides lstm pdf mon nov 26 attention overview of variational auto encoders generative adversarial networks attention slides https github com ubc nlp deeplearning nlp2018 blob master slides attention pdf neural machine translation by jointly learning to align and translate http www cs ubc ca amuham01 ling530 papers bahdanau2014neural pdf dlb ch20 10 4 https www deeplearningbook org contents generative models html dlb ch14 https www deeplearningbook org contents autoencoders html dlb ch20 10 3 https www deeplearningbook org contents generative models html semi supervised sequence learning www cs ubc ca amuham01 ling530 papers dai2015semi pdf wed nov 28 projects autoenoders gans slides https github com ubc nlp deeplearning nlp2018 blob master slides overview autoencoders gans pdf mon dec 3 final project due hw03 b 8 readings see section 7 above additionally below is list of relevant interesting background papers this list will grow toward controlled generation of text http www cs ubc ca amuham01 ling530 papers hu2017toward pdf tutorial on variational autoencoders http www cs ubc ca amuham01 ling530 papers doersch2016tutorial pdf adversarially regularized autoencoders http www cs ubc ca amuham01 ling530 papers zhao2018adversarially pdf joint embedding of words and labels for text classification http www cs ubc ca amuham01 ling530 papers wang2018joint pdf learning adversarial networks for semi supervised text classification via policy gradient http www cs ubc ca amuham01 ling530 papers li2018learning pdf realistic evaluation of semi supervised learning algorithms http www cs ubc ca amuham01 ling530 papers oliver2018realistic pdf improving language understanding by generative pre training http www cs ubc ca amuham01 ling530 papers radford2018improving pdf automatic stance detection using end to end memory networks http www cs ubc ca amuham01 ling530 papers mohtarami2018automatic pdf neural machine translation by jointly learning to align and translate http www cs ubc ca amuham01 ling530 papers bahdanau2014neural pdf grammar as a foreign language http www cs ubc ca amuham01 ling530 papers vinyals2015grammar pdf deep models for arabic dialect identification on benchmarked data http www cs ubc ca amuham01 ling530 papers elarabydeepmodels2018 pdf a neural model for user geolocation and lexical dialectology http www cs ubc ca amuham01 ling530 papers rahimigeoloc2017 pdf deep contextualized word representations http www cs ubc ca amuham01 ling530 papers peterselmo2018 pdf emonet fine grained emotion detection with gated recurrent neural networks http www cs ubc ca amuham01 ling530 papers mageedemonet2017 pdf is statistical machine translation approach dead http www cs ubc ca amuham01 ling530 papers menacer2017statistical pdf neural machine translation and sequence to sequence models a tutorial http www cs ubc ca amuham01 ling530 papers neubig2017neural pdf adversarial training methods for semi supervised text classification http www cs ubc ca amuham01 ling530 papers miyato2016adversarial pdf learned in translation contextualized word vectors http www cs ubc ca amuham01 ling530 papers mccann2017learned pdf semi supervised sequence learning http www cs ubc ca amuham01 ling530 papers dai2015semi pdf auto encoding variational bayes http www cs ubc ca amuham01 ling530 papers kingma2013auto pdf sentiment transfer using seq2seq adversarial autoencoders http www cs ubc ca amuham01 ling530 papers singh2018sentiment pdf variational autoencoder for semi supervised text classification http www cs ubc ca amuham01 ling530 papers xu2017variational pdf phrase based neural unsupervised machine translation http www cs ubc ca amuham01 ling530 papers lample2018phrase pdf asma a system for automatic segmentation and morpho syntactic disambiguation of modern standard arabic http www aclweb org anthology r13 1001 9 course assignments grades assignment due date weight professionalization class participation throughout 15 assignment 1 individual assignment word embeddings oct 3 15 assignment 2 individual assignment text classification with rnns oct 24 20 assignment 3 a group assignment project proposal nov 5 5 assignment 3 b group assignment term project group of 3 dec 3 45 notes on assignments assignment 1 word embeddings in this assignment students will train a word embeddings model using either word2vec of fasttext on a dataset provided to them and use the trained model for a number of tasks the students will write a report using the jupyter platform describing their work the reprot will include both the code used and the results acquired in a step wise organized fashion the students are expected to use enabling python libraries e g nltk gensim scikit learn and illustrate their work with visualizations automatically generated from the data a rubric will be provided to walk students through the different steps deliverables jupyter notebook describing the work students carried out assignment 2 text classification with rnns for this assignment students will build a fully fledged text classifier using rnns and its variations e g lstms grus for this the students will be provided a labeled dataset as such the task is cast as supervised machine learning the students will need to demonstrate understanding of the theoritical part of the course for example a detailed description of pre processing data splits concepts like train dev and test sets and or n fold cross validation model capacity e g the architecture of the network used in terms of layers and number of units in each layer activation functions regularization cost functions baselines and meaningful comparisons which baselines are chosen and why etc deliverables a short paper 4 pages main body 2 pages references jupyter notebook students will then write a 4 page report 2 extra pages for references a maximum of 2 extra pages can be allowed without instructor permission but need to be justfied in a footnote in the report students will also need to submit an accompanying jupyter notebook with their code students will be provided an acl latex template to use for writing the report and a rubric walking them through some of the major details of how to write the report assignment 3 term project the purposes of this assignment include identifying and describing an interesting i e challenging novel socially relevant has practical applications nlp problem reviewing previous literature on relevant to the task showing a clear understanding of previous scholarship proposing and developing in the engineering sense via code a solution to the problem using deep learning clearly describing the work justifying decisons made in a way that lends work to replication developing oral and written communication skills through discussions with classmates and instructor demonstrating ability to work as part of a team including initiative taking integrity dependability and co operation and effective collaboration for this assignment each student is required to work as part of a group of of 3 on a project involving a practical task example projects will be discussed in class a group of a different size may be possible after consultation with the instructor deliverables proposal 1 2 pages in acl style latex who are the the group members what is the problem you are proposing a solution for what motivates your work why is it important or useful to undertake the chosen task how does your project compare to nlp and deep learning published research what are the different steps you will take to ensure success of the project what are the smaller segments of which the bigger task is composed and how will you conduct each small task how does the work bread down and what each member of the team be contributing timeline for completing the project including goals for each segment note you may like to provide a table breaking down who is doing what and when the latex files will be provided to you as part of the rubric for the final project final paper 6 8 pages acl style the final deliverable includes a detailed and clear description of your project including the necessary sections as appropriate for example you will need to include an abstract introduction possibly research questions a literature review a description of dataset collection splits methods implementation details experimental conditions settings comparisons baselines results in tables analysis of results e g with visulaizations error analyses and a conclusion describing limitations and future directions all data used whenever possible and or links to where the data are housed pointers to a live version of the project if any as appropriate you should situate your work within the wider context of published works and approaches with supporting arguments you will have an unlimited number of pages for references but you should plan to have at least 15 sources employment of figures tables and visualizations as appropriate to enhance argument and facilitate communicating your findings results 10 course policies attendance the ubc calendar states regular attendance is expected of students in all their classes including lectures laboratories tutorials seminars etc students who neglect their academic work and assignments may be excluded from the final examinations students who are unavoidably absent because of illness or disability should report to their instructors on return to classes evaluation all assignments will be marked using the evaluative criteria given in this syllabus access diversity access diversity works with the university to create an inclusive living and learning environment in which all students can thrive the university accommodates students with disabilities who have registered with the access and diversity unit https students ubc ca about student services access diversity you must register with the disability resource centre to be granted special accommodations for any on going conditions religious accommodation the university accommodates students whose religious obligations conflict with attendance submitting assignments or completing scheduled tests and examinations please let your instructor know in advance preferably in the first week of class if you will require any accommodation on these grounds students who plan to be absent for varsity athletics family obligations or other similar commitments cannot assume they will be accommodated and should discuss their commitments with the instructor before the course drop date ubc policy on religious holidays http www universitycounsel ubc ca policies policy65 pdf academic integrity plagiarism plagiarism is the most serious academic offence that a student can commit regardless of whether or not it was committed intentionally plagiarism has serious academic consequences and can result in expulsion from the university plagiarism involves the improper use of somebody else s words or ideas in one s work it is your responsibility to make sure you fully understand what plagiarism is many students who think they understand plagiarism do in fact commit what ubc calls reckless plagiarism below is an excerpt on reckless plagiarism from ubc faculty of arts leaflet plagiarism avoided taking responsibility for your work http www arts ubc ca arts students plagiarism avoided html the bulk of plagiarism falls into this category reckless plagiarism is often the result of careless research poor time management and a lack of confidence in your own ability to think critically examples of reckless plagiarism include taking phrases sentences paragraphs or statistical findings from a variety of sources and piecing them together into an essay piecemeal plagiarism taking the words of another author and failing to note clearly that they are not your own in other words you have not put a direct quotation within quotation marks using statistical findings without acknowledging your source taking another author s idea without your own critical analysis and failing to acknowledge that this idea is not yours paraphrasing i e rewording or rearranging words so that your work resembles but does not copy the original without acknowledging your source using footnotes or material quoted in other sources as if they were the results of your own research and submitting a piece of work with inaccurate text references sloppy footnotes or incomplete source bibliographic information bear in mind that this is only one example of the different forms of plagiarism before preparing for their written assignments students are strongly encouraged to familiarize themselves with the following source on plagiarism the academic integrity resource centre http help library ubc ca researching academic integrity if after reading these materials you still are unsure about how to properly use sources in your work please ask me for clarification students are held responsible for knowing and following all university regulations regarding academic dishonesty if a student does not know how to properly cite a source or what constitutes proper use of a source it is the student s personal responsibility to obtain the needed information and to apply it within university guidelines and policies if evidence of academic dishonesty is found in a course assignment previously submitted work in this course may be reviewed for possible academic dishonesty and grades modified as appropriate ubc policy requires that all suspected cases of academic dishonesty must be forwarded to the dean for possible action | deep-learning deeplearning natural-language-processing nlp machine-learning machinelearning ai ubc | ai |
Android-SoundCloud-Player | android soundcloud player final project android application for mobile application development 60 420 this is an android application that utilizes the soundcloud api to play your favourite music from soundcloud features a simple and clean design that is heavily influenced by google s material design philosophy third party libaries used android pulltorefresh by chrisbanes github https github com chrisbanes android pulltorefresh android universal image loader by nostra13 github https github com nostra13 android universal image loader built on eclipse android api level 19 current bugs cannot seek with default android player requires a lot of permissions to run sorry for you privacy fantics oh by the way this is open source feel free to contribute fork or even make it into your own | front_end |
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FBTT-Embedding | fbtt embedding fbtt embedding library provides functionality to compress sparse embedding tables commonly used in machine learning models such as recommendation and natural language processing the library can be used as a direct replacement to pytorch s embeddingbag https pytorch org docs stable generated torch nn embeddingbag html functionality it provides the forward and backward propagation functionality same as pytorch s embeddingbag with only difference of compression in addition our implementation includes a software cache to store a portion of the entries in the embedding tables or bag s in decompressed format for faster lookup and process removing the need for decompressing and compressing the entries every time it is accessed during the program execution of training or inference read more at tt rec tensor train compression for deep learning recommendation models https proceedings mlsys org paper 2021 file 979d472a84804b9f647bc185a877a8b5 paper pdf in the proceedings of conference on machine learning and systems mlsys 2021 https mlsys org installing fbtt embedding the implementation was compiled and tested with pytorch 1 6 and above with cuda 10 1 to install the library run setup py install in order to get the best performance specify gencode for nvcc in the setup py line 24 the corresponding compiler settings for each architecture can be found in cuda toolkit documentation for example volta https docs nvidia com cuda volta compatibility guide index html pascal https docs nvidia com cuda pascal compatibility guide index html install dependence cub https nvlabs github io cub a sample run of the code run tt embeddings benchmark py a sample output is shown below bash info root sparse true optimizer sgd info root p shapes 200 220 250 q shapes 4 4 4 ranks 32 32 info root b 512 e 11000000 d 64 nnz 10240 info root ttembeddingbag fwd bwd time nnz 0 416 usecs gflops 2657 631 bw 18 456 how fbtt embedding works parameters num embeddings int size of the dictionary of embeddings embedding dim int the length of each embedding vector tt ranks list int the ranks of tt cores tt p shapes optional list int the factorization of num embeddings where the product of all elements is not smaller than num embeddings tt q shapes optional list int the factorization of embedding dim where the product of all elements is equal to embedding dim sparse bool if true the weight update is fused with gradient calculation and gradients are not returned by backward propagation otherwise the gradient w r t tt cores or cache would be returned to external optimizer optimizer optimtype the type of optimizer when using fused kernel learning rate float learning rate of the optimizer eps float term added to the denominator to improve numerical stability for adagrad only use cache bool if true a software cache will be used to store the most frequently accessed embedding vectors cache size int the maximum number of embedding vectors to be stored in the cache hashtbl size int the maximum number of entries in the hash table for frequency count weight dist str uniform naive uniform approx uniform normal approx normal when using uniform or normal the weights of tt cores will be i i d from the specified distribution when using approx uniform or approx normal the tt cores are initialized in a way that the entries of full embedding table follow the specified distribution initialization the initialization of tt emb is similar to pytorch embeddingbag python tt emb ttembeddingbag num embeddings 1000000 embedding dim 64 tt p shapes 120 90 110 tt q shapes 4 4 4 tt ranks 12 14 sparse false use cache false weight dist uniform this method will generate tt cores representing an embedding table of size 1000000 by 64 num embeddings x embedding dim where each tt core is of size ranks i x tt p shapes i x tt q shapes i x ranks i 1 and ranks 1 tt rank 1 in this case the shape of the 3 tt cores are 1 x 120 x 4 x 12 12 x 90 x 4 x 16 and 14 x 110 x 4 x 1 when tt p shapes and tt q shapes are specified the product of tt p shapes needs be no smaller than num embeddings the product of tt q shapes must be equal to embedding dim when passing these 2 parameters as none ttembeddingbag will factor num embeddings and embedding dim automatically python an embedding module containing 10 tensors of size 3 embedding sum ttembeddingbag 10 3 none none tt ranks 2 2 sparse false use cache false a batch of 2 samples of 4 indices each input torch longtensor 1 2 4 5 4 3 2 9 offsets torch longtensor 0 4 embedding sum input offsets tensor 0 8861 5 4350 0 0523 1 1306 2 5798 1 0044 fused kernel tt emb supports fused gradient computation and weight updates for better efficiency where the weights of embedding tables are updated along with backward propagation if the network is trained with an external optimizer the gradients will no longer be returned to the optimizer to enable the fused kernel specify sparse true and pass the corresponding optimizer type and parameters to ttembeddingbag for example python tt emb ttembeddingbag num embeddings 1000000 embedding dim 64 tt p shapes 120 90 110 tt q shapes 4 4 4 tt ranks 12 14 sparse true optimizer optimtype sgd learning rate 0 05 eps 1 0e 10 for adagrad only use cache false software cache embedding lookup in tt rec requires explicitly computing the embedding vectors from tt cores via two consecutive matrix multiplications gemm similarly in backward propagation the gradient of each tensor core is calculated through a chain of matrix multiplications in reversed order to reduce the computation during training tt emb implements a software cache to store an uncompressed copy of the most frequently queried embedding vectors when such vectors are queried the vectors can be loaded directly from cache without computation the size of cache can be determined according to each hardware platform and dataset so that cached embedding rows capture as many embedding lookups as possible while minimizing the memory requirement during training we implemented a 32 way set associative least frequently used lfu cache using open addressing hash table for frequency count to enable cache for tt emb specify use cache true and set the appropriate cache size as the maximum number of embedding vectors to store in the cache and max hash table size python tt emb ttembeddingbag num embeddings 1000000 embedding dim 64 tt p shapes 120 90 110 tt q shapes 4 4 4 tt ranks 12 14 sparse true optimizer optimtype sgd learning rate 0 05 eps 1 0e 10 for adagrad only use cache true cache size 1000 hashtbl size 1000 during forward propagation the access frequency of embedding vectors will be updated however the cache will only be updated when tt emb cache populate is called the cached rows are determined by the access frequency of the embedding vectors and the value of each embedding vector would be initialized from tt cores tablebatchedttembeddingbag apart from ttembeddingbag demonstrated above the library also includes tablebatchedttembeddingbag which groups the lookup operation together for multiple tt embedding tables this can be more efficient than creating multiple instances of ttembeddingbag s when each of the ttembeddingbag has little computation involved to use that you simply need to initialize it as below python tt emb tablebatchedttembeddingbag num tables 100 num embeddings 1000000 embedding dim 64 tt p shapes 120 90 110 tt q shapes 4 4 4 tt ranks 12 14 sparse false use cache false weight dist uniform the above creates 100 tt embedding tables with the same dimensions underlying the only additional argument that needs to be passed is num tables currently there are some limitations to tablebatchedttembeddingbag the mutiple tables in tablebatchedttembeddingbag must share the same dimensions no support for software cache yet no support for approx uniform weight init yet no support for expanding to full weight yet license fbtt embedding is mit licensed as found in the license file | ai |
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thingsboard | thingsboard join the chat at https gitter im thingsboard chat https badges gitter im join 20chat svg https gitter im thingsboard chat utm source badge utm medium badge utm campaign pr badge utm content badge thingsboard builds server status https img shields io teamcity build e thingsboard build label tb 20builds 20server server https 3a 2f 2fbuilds thingsboard io logo data image png base64 ivborw0kggoaaaansuheugaaaeaaaabacayaaacqaxheaaaacxbiwxmaaalzaaac8whs6qoqaaaagxrfwhrtb2z0d2fyzqb3d3cuaw5rc2nhcguub3jnm 48ggaab9fjrefuejzvm3 mxuuvx7 zwwqetnrlwisq2lkvuisiqmsqycohpuhpegsfksjjts0qgigiisj 8cngyzsaekbqezuip7rgvbcvdpe0xykbwgi2rflzjzqwtfkobpfjh3pfdu7s3pvmzntv3 jnnr3boxpo z6zo3pumvmjfgeyjwmwpdmszks6vtiesv3zv29lwmgmubdvpgw7geobjcaayc 18fd2 zyqngawxdl7m9kesdummxgyh5r0larpsrpbwf62crldb8aas4hnaqp2eva1ybtwpubnwp46i70h dpwalas b5wbtcu3vyhijvg98dmx b bw1vavcanwdmap3t5hwfborxr5avwmparccydnnjancbr gd7hq9hzglfat4pub8azcv3f43dgctq6o rao43gtcl2da4w9tauwebhxipymrvcabar8etl 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tqn2y11muj6wa5v3z8hembjba 8n5stwjcdb9lyuei fde3meq1svnbkrvp32k lepyqd1z3xqjfsg3 sw gkellzev8tb8rnizpbemf1sdz06zbjn0saa kayqtv77qi6qnjf1njfnxdoebacixssvqb3yfcgrcczwenafmc8mmkgarnuvt28vubf4 nyzflx8jr8bvkr4tm83tzn5ek s8pm2snpt0gv8h283c wgtffhgtexqwqaaaabjru5erkjggg labelcolor 305680 https builds thingsboard io viewtype html buildtypeid thingsboard build guest 1 thingsboard is an open source iot platform for data collection processing visualization and device management img src img logo png raw true width 100 height 100 documentation thingsboard documentation is hosted on thingsboard io https thingsboard io docs iot use cases smart energy https thingsboard io smart energy smart energy https user images githubusercontent com 8308069 152984256 eb48564a 645c 468d 912b f554b63104a5 gif smart energy https thingsboard io smart energy fleet tracking https thingsboard io fleet tracking fleet tracking https user images githubusercontent com 8308069 152984528 0054ed55 8b8b 4cda ba45 02fe95a81222 gif fleet tracking https thingsboard io fleet tracking smart farming https thingsboard io smart farming smart farming https user images githubusercontent com 8308069 152984443 a98b7d3d ff7a 4037 9011 e71e1e6f755f gif smart farming https thingsboard io smart farming iot rule engine https thingsboard io docs user guide rule engine 2 0 re getting started iot rule engine https img thingsboard io demo send email rule chain gif iot rule engine https thingsboard io docs user guide rule engine 2 0 re getting started smart metering https thingsboard io smart metering smart metering https user images githubusercontent com 8308069 31455788 6888a948 aec1 11e7 9819 410e0ba785e0 gif smart metering https thingsboard io smart metering getting started collect and visualize your iot data in minutes by following this guide https thingsboard io docs getting started guides helloworld support community chat https gitter im thingsboard chat q a forum https groups google com forum forum thingsboard stackoverflow http stackoverflow com questions tagged thingsboard licenses this project is released under apache 2 0 license license | dashboard visualization iot iot-platform mqtt coap middleware netty websockets widgets thingsboard iot-analytics platform kafka lwm2m java snmp microservices cloud iot-solutions | server |
dotfiles | p align center img width 200 height 200 src https raw githubusercontent com gokulkrishh dotfiles master logo png p dotfiles setup your macos for web development at ease screenshot terminal screenshot terminal png steps 1 clone cd into bash git clone https github com gokulkrishh dotfiles git dotfiles cd dotfiles 2 install bash bash install sh note answer a few questions to setup github npm etc for you via command line comes with oh my zsh https github com robbyrussell oh my zsh shortcuts aliases docs aliases md homebrew http brew sh installs following apps brave browser visual studio code iterm 2 git wget nvm https github com lukechilds zsh nvm z jump around https github com robbyrussell oh my zsh tree master plugins z fonts firacode https github com tonsky firacode free monolisa https www monolisa dev paid extra tools i use https gokul site uses contributions if you wish to contribute to this repository fork it and send a pr and if you like the repo it mit licensed | dotfiles zsh osx bash dotfile atom sublime-text nodejs zshrc oh-my-zsh zsh-theme vscode dotfiles-setup dotfiles-macos nvm iterm2 iterm z-jump dotfiles-install dotfiles-resources | front_end |
FlaskAPI-GCP-Applications | project description goal run an app on the cloud for api users to make requests and store user information rationale to achieve the goal efficiently this project proceeds with the following path application write an app with features in user authentication and form submission connection create a cloud database for storing app information we need to ensure a secured connection between the app and the database deployment deploy the app and expose it to the internet technology overview images technology png flask the application is a simple api written using the flask framework flask offers extensions like database access template engine user authentication etc terraform terraform is an infrastructure as code iac service that allows users to provision cloud infrastructures with reusable codes it uses configuration language to provision cloud infrastrucutres and can simultaneously plan and manage resources from different cloud providers like aws gcp and azure using terraform can significantly improve efficiency and reduce time in provisioning resources circumventing issues like manually updating configurations on the console or on the command line google cloud platform gcp cloudsql we will create a postgresql database instance with a user defined root user password and database this will be the database for storing user info kubernetes engine kubernetes creates clusters with nodes each node in a cluster has pods that can be aggregated as a service to be exposed to the internet we will spin up a kubernetes cluster with a single master node which will run the pod where our application will be located kubernetes can store sensitive information like password and credentials as secrets we will store database username and password in the pod as secrets artifact registry this is a container registry for storing container images kubernetes looks for images from the repository and run them on pods cloud build this is google s equivalent of docker and we will build the application as a container image here and push it to the registry google service account gsa cloud resources require permission to interact with other resources in particular we need to generate credential keys from service accounts with the following priviledges owner role for machines or softwares to provision and interact with infrastructures on behalf of gcp cloudsql client role for kubernetes to establish a tcp connection between the sql database and the application inside the cluster architecture infrastructures application images architecture png infrastructure overview images terraform workflow png terraform plans and provisions infrastructures using the main tf terraform main tf file in the terraform folder with variables tf terraform variables tf as input file the terraform tfvars terraform terraform tfvars file specifies any variables from variables tf terraform variables tf that don t have a default parameters the artifact registry cloudsql and gke folders are sub modules implemented in a similar fashion we only create the cloudsql database instance the kubernetes cluster and the container repository here the actual containerization process using docker cloud build will take place using github actions the github action configuration can be found in the cloudbuilds gke yaml github workflows cloudbuilds gke yaml file application overview the flask application is a simple api exposing the users to get and post method post users can input text to submit information to be store in the backend cloudsql postgre instance images api post png get users can click on the check button to view all the previously entered data in a tabular format upon request the application retrieves all data stored in the database and return them as such on the following page images api get png all the data are stored in the backend database images query png running the project 0 preparation create a new project keep note of the project id determine and keep note of the region and zone https cloud google com compute docs regions zones available enable api for cloudsql kubernetes engine cloud build and artifact registry 1 create service accounts and download credentials go to iam and create a service account called owner sa with owner role download a new key in json format and rename it owner sa key json create another service account called cloudsql sa with cloud sql client role download a new key in json format and rename it cloudsql sa key json images service accounts png 2 project environment setup fork and clone this repository in a local terminal create a folder called service accounts in the terraform folder move both owner sa key json and cloudsql sa key json files to the service accounts folder set environment variable for grant terraform permission to provision gcp resources bash export google application credentials path to flaskapi gcp applications terraform service accounts owner sa key json 3 update configurations update the variables in terraform tfvars terraform terraform tfvars where a todo comment indicates update the variables in cloudbuilds gke yaml github workflows cloudbuilds gke yaml where a todo comment indicates 3 github actions setup go to the forked repository settings and select action secrets create a secret called gke project and put in your project id as value create a secret called gke sa key and paste the content of the owner sa key json in as value images github secrets png 4 install requirements and initialize install gcloud https cloud google com sdk docs install install kubectl https cloud google com kubernetes engine docs how to cluster access for kubectl install terraform https www terraform io downloads 5 provision the infrastructures bash gcloud init set up your project id region and zone terraform init make sure you are in the terraform folder terraform workspace new dev the default workspace is default we will work in the dev workspace terraform plan let you preview the infrastructure changes terraform apply auto approve once it finishes building the terminal will output a list of infrastructure info bash terraform output if no outputs printed 6 update kubernetes configurations take note of the cloudsql instance name outputed by terraform update the lines in the deployment yaml deployment yaml file where a todo comment indicates store database username password and cloudsql client role credential key as kubernetes secrets bash gcloud container clusters get credentials flask cluster get credentials for kubectl to work with the cluster bash kubectl create secret generic postgres secret from literal username sql user from literal password sql pass from literal database db name bash kubectl create secret generic cloudsql sa from file service account json service accounts cloudsql sa key json 7 deploy the application using github actions commit and push the changes previously made to the configurations the github action will be triggered when the changes are pushed it will automatically containerize the application using cloud build and store it in the repository then it will deploy the container image to kubernetes and expose it to the internet through a service 8 access the application bash kubectl get services you may find the status pending under the external ip column wait and keep running the previous command until an ip address shows up copy the external ip address of the service flask app and access it from another tab images external ip png you should see the following web page show up images api welcome png click on the start button and you will be directed to the application as shown in the application overview section above 9 clean up the project bash terraform destroy auto approve delete the owner sa and cloudsql sa service accounts optional delete the credential keys and gihub action secrets optional | server |
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design-system | groove storybook design system storybook https cdn jsdelivr net gh storybookjs brand master badge badge storybook svg https sds groovehq com groove storybook design system sds https sds groovehq com is a reusable component library that helps developers build groove branded consistent uis faster it s an ssot single source of truth for all ui components used across various groove applications running and developing sds locally clone the groove sds project https github com groovehq design system then start storybook to preview available components and develop locally yarn yarn start the storybook will be running at http localhost 9009 to avoid npm package release process and test things locally in your application yarn build pkg yarn link in your app yarn link groovehq design system building and deploying to build and preview static version of the storybook run yarn build to deploy storybook bundle install yarn deploy releasing a new version every time you want to release a new version of groove sds run yarn login yarn release note we use auto https github com intuit auto to generate a changelog and push it to github in order for this to work correctly an environment variable called gh token is needed that references a github personal access token https help github com en articles creating a personal access token for the command line with the appropriate permissions to update the repo using in your application to use groove storybook design system sds in your react applications follow the storybook design system getting started guide https sds groovehq com path docs design system getting started page resources intro to storybook https www learnstorybook com intro to storybook design system for developers https www learnstorybook com design systems for developers component story format https medium com storybookjs component story format 66f4c32366df storybook docs https storybook js org docs original storybook design system https github com storybookjs design system | os |
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camera-mounted-bluetooth-rc-car | camera mounted bluetooth model car embedded systems six person project known as wacky racers to design and implement a camera mounted bluetooth controlled model car the project had a requirement that three separate 4 layer boards 1 motor driver 2 camera driver and 3 main wifi communications were developed each with their own microcontroller and communicated over a common i2c bus stm32f4 microcontrollers were selected for the project camera board p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 camera schematics camera board photo jpg width 400 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 camera schematics camera analogue schematic jpg width 600 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 camera schematics camera digital schematic jpg width 600 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 camera schematics camera pcb jpg width 500 p communications board p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 comms schematics comms board photo jpg width 400 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 comms schematics comms schematic jpg width 600 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 comms schematics micro schematic jpg width 600 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 comms schematics debug schematic jpg width 600 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 comms schematics commspcb jpg width 500 p motor control power board p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 motor schematics motor board photo jpg width 400 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 motor schematics motor board schematic jpg width 600 p p align center img src https github com ianglass camera mounted bluetooth rc car blob master stm32 motor schematics motorpcb jpg width 500 p | altium c-programming stm32f4 bluetooth i2c | os |
Cinema-system-app | cinema system app full stack web application that combines the development of 2 rest api s for the backend and react amp redux for the client side the architecture of the app was divided into a business layer and data layer servers were built with node express mongodb amp mongoose for the database | server |
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esp-iot-solution | documentation status https dl espressif com ae docs docs latest svg https docs espressif com projects esp iot solution en espressif iot solution overview readme cn md esp iot solution contains device drivers and code frameworks for the development of iot systems providing extra components that enhance the capabilities of esp idf and greatly simplify the development process esp iot solution contains the following contents device drivers for sensors display audio input actuators etc framework and documentation for low power security storage etc guide for espressif open source solutions from practical application point documentation center https docs espressif com projects esp iot solution zh cn english https docs espressif com projects esp iot solution en quick reference development board you can choose any of the esp series development boards to use esp iot solution or choose one of the boards supported in boards component examples common components boards for a quick start powered by 40nm technology esp series soc provides a robust highly integrated platform which helps meet the continuous demands for efficient power usage compact design security high performance and reliability setup environment setup esp idf environment esp iot solution is developed based on esp idf functions and tools so esp idf development environment must be set up first you can refer setting up development environment https docs espressif com projects esp idf en latest esp32 get started index html setting up development environment for the detailed steps please note that different versions of esp iot solution may depend on different versions of esp idf please refer to the below table to select the correct version esp iot solution dependent esp idf major change user guide support state master v4 4 support component manager and new chips docs online https docs espressif com projects esp iot solution zh cn active new feature develop release v1 1 v4 0 1 idf version update remove no longer supported code v1 1 overview https github com espressif esp iot solution tree release v1 1 esp32 iot solution overview archived release v1 0 v3 2 2 legacy version v1 0 overview https github com espressif esp iot solution tree release v1 0 esp32 iot solution overview archived since the master branch uses the esp component manager to manager components each of them is a separate package and each package may support a different version of the esp idf which will be declared in the component s idf component yml file get components from esp component registry if you just want to use the components in esp iot solution we recommend you use it from the esp component registry https components espressif com the registered components in esp iot solution are listed below center component name version ble ota https components espressif com components espressif ble ota component registry https components espressif com components espressif ble ota badge svg https components espressif com components espressif ble ota bootloader support plus https components espressif com components espressif bootloader support plus component registry https components espressif com components espressif bootloader support plus badge svg https components espressif com components espressif bootloader support plus button https components espressif com components espressif button component registry https components espressif com components espressif button badge svg https components espressif com components espressif button cmake utilities https components espressif com components espressif cmake utilities component registry https components espressif com components espressif cmake utilities badge svg https components espressif com components espressif cmake utilities esp lcd gc9b71 https components espressif com components espressif esp lcd gc9b71 component registry https components espressif com components espressif esp lcd gc9b71 badge svg https components espressif com components 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espressif com components espressif extended vfs gprof https components espressif com components espressif gprof component registry https components espressif com components espressif gprof badge svg https components espressif com components espressif gprof iot usbh https components espressif com components espressif iot usbh component registry https components espressif com components espressif iot usbh badge svg https components espressif com components espressif iot usbh iot usbh cdc https components espressif com components espressif iot usbh cdc component registry https components espressif com components espressif iot usbh cdc badge svg https components espressif com components espressif iot usbh cdc iot usbh modem https components espressif com components espressif iot usbh modem component registry https components espressif com components espressif iot usbh modem badge svg https components espressif com components espressif iot usbh modem knob https components espressif com components espressif knob component registry https components espressif com components espressif knob badge svg https components espressif com components espressif knob led indicator https components espressif com components espressif led indicator component registry https components espressif com components espressif led indicator badge svg https components espressif com components espressif led indicator lightbulb driver https components espressif com components espressif lightbulb driver component registry https components espressif com components espressif lightbulb driver badge svg https components espressif com components espressif lightbulb driver openai https components espressif com components espressif openai component registry https components espressif com components espressif openai badge svg https components espressif com components espressif openai pwm audio https components espressif com components espressif pwm audio component registry https components espressif com components espressif pwm audio badge svg https components espressif com components espressif pwm audio usb device uvc https components espressif com components espressif usb device uvc component registry https components espressif com components espressif usb device uvc badge svg https components espressif com components espressif usb device uvc usb stream https components espressif com components espressif usb stream component registry https components espressif com components espressif usb stream badge svg https components espressif com components espressif usb stream xz https components espressif com components espressif xz component registry https components espressif com components espressif xz badge svg https components espressif com components espressif xz center you can directly add the components from the component registry to your project by using the idf py add dependency command under your project s root directory eg run idf py add dependency espressif usb stream to add the usb stream the component will be downloaded automatically during the cmake step please refer to idf component manager https docs espressif com projects esp idf en latest esp32 api guides tools idf component manager html for details get esp iot solution repository if you want to contribute https docs espressif com projects esp iot solution zh cn latest contribute index html to the components in esp iot solution or want to start from the examples in esp iot solution you can get the esp iot solution repository by following the steps if select the master version open the terminal and run the following command git clone recursive https github com espressif esp iot solution if select the release v1 1 version open the terminal and run the following command git clone b release v1 1 recursive https github com espressif esp iot solution build and flash examples we highly recommend you build your first project https docs espressif com projects esp idf en latest esp32 get started index html build your first project to get familiar with esp idf and make sure the environment is set up correctly there is no difference between building and flashing the examples in esp iot solution and in esp idf in most cases you can build and flash the examples in esp iot solution by following the steps 1 change the current directory to the example directory eg cd examples usb host usb audio player 2 run idf py set target target to set the target chip eg idf py set target esp32s3 to set the target chip to esp32 s3 3 run idf py build to build the example 4 run idf py p port flash monitor to flash the example and view the serial output eg idf py p dev ttyusb0 flash monitor to flash the example and view the serial output on dev ttyusb0 some examples may need extra steps to setup the esp iot solution environment you can run export iot solution path esp esp iot solution in linux macos or set iot solution path c esp esp iot solution in windows to setup the environment resources documentation for the latest version https docs espressif com projects esp iot solution this documentation is built from the docs directory docs of this repository esp idf programming guide https docs espressif com projects esp idf zh cn please refer to the version esp iot solution depends on the idf component registry https components espressif com is where you can find the components in esp iot solution and other registered components the esp32 com forum https www esp32 com is a place to ask questions and find community resources check the issues section on github https github com espressif esp iot solution issues if you find a bug or have a feature request please check existing issues before opening a new one if you re interested in contributing to esp idf please check the contributions guide contributing rst | server |
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neuron | neuron github release https img shields io github release emqx neuron color brightgreen label release https github com emqx neuron releases docker pulls https img shields io docker pulls emqx neuron label docker 20pulls https hub docker com r emqx neuron codecov https codecov io gh emqx neuron graph badge svg token x95rd0nut0 https codecov io gh emqx neuron slack https img shields io badge slack neuron 39ae85 logo slack https slack invite emqx io discord https img shields io discord 931086341838622751 label discord logo discord https discord gg xygf3fqnes twitter https img shields io badge follow emq 1da1f2 logo twitter https twitter com emqtech youtube https img shields io badge subscribe emq ff0000 logo youtube https www youtube com channel uc5fjr77eraxvzenewzqao5q neuron is an industrial iot iiot connectivity server for modern big data and ai ml technology to leverage the power of industrial 4 0 it supports one stop access to dozens of industrial protocols and converts them into mqtt protocol and realize the interconnection between iiot platforms and various industrial devices neuron overview docs pictures neuron final png the following are some important features of neuron edge native application with real time capability to leverage the low latency network of edge side loosely coupled modularity architecture design https neugates io docs en latest introduction architecture architecture html for extending more functional services by pluggable modules support hot plugins that can update device and application modules during runtime support numerous protocols for industrial devices including modbus opcua ethernet ip iec104 bacnet and more https neugates io docs en latest configuration south devices south devices html support simultaneous connection of a large number of industrial devices with different protocols combine with the rule engine function provided by ekuiper https www lfedge org projects ekuiper to quickly implement rule based device control or ai ml analytics support data access to industrial applications such as mes or erp scada historian and data analytics software via sparkplugb https neugates io docs en latest use cases use cases html mqtt sparkplugb solution solution has very low memory footprint less than 10m and cpu usage can run on limited resource hardware like arm x86 and risc v support installation of native executable or deployed in containerized enviornment control industrial devices and make changes to the parameters and data tags through http api https neugates io docs en latest http api http api html and mqtt api https neugates io docs en latest configuration north apps mqtt api html services highly integrated with other emq products including emqx https www emqx com en products emqx nanomq https nanomq io ekuiper https ekuiper org the code of the core framework and modbus mqtt and ekuiper are licensed under open source lgplv3 commercial modules require a emq license https neugates io docs en latest installation license install license install html to run for more information please visit neuron homepage https neugates io get started run neuron using docker docker run d name neuron p 7000 7000 p 7001 7001 p 9081 9081 privileged true restart always emqx neuron latest next please follow the getting started guide https neugates io docs en latest quick start hardware specifications html to tour the neuron features limitations neuron open source edition only includes modbus and mqtt drivers apply for a 15 day trial license https www emqx com en apply licenses neuron to load all drivers more installation options if you prefer to install and manage neuron yourself you can download the latest version from neugates io downloads os linux https neugates io downloads os linux for more installation options see the neuron installation documentation https neugates io docs en latest installation installation html documentation the neuron documentation is available at neugates io docs en latest https neugates io docs en latest get involved follow emqtech on twitter https twitter com emqtech if you have a specific question check out our discussion forums https github com emqx neuron discussions for general discussions join us on the official discord https discord gg xygf3fqnes team keep updated on emq youtube https www youtube com channel uc5fjr77eraxvzenewzqao5q by subscribing build from source install required dependencies install dependencies https github com emqx neuron blob main install dependencies md build git clone https github com emqx neuron cd neuron mkdir build cd build cmake make install dashboard download the latest neuron dashboard zip from the neuron dashboard https github com emqx neuron dashboard releases page unzip it and put it to the dist directory under the neuron executable directory run cd build neuron log level change the log level in the rules in the zlog conf file available levels include info debug notice warn error and fatal license see license license | iot plc c mqtt modbus opcua siemens-s7 omron mitsubishi dtu industrial-iot manufacturing iot-middleware industry-40 iiot iot-edge | server |
iot-edge-opc-publisher-v1 | important this repository is retired the opc publisher development is being continued in azure industrial iot https github com azure industrial iot please report all opc publisher related issues in azure industrial iot repository https github com azure industrial iot it contains the latest sources documentation and will be monitored regularly for issues reported around opc publisher please note this project has adopted the microsoft open source code of conduct https opensource microsoft com codeofconduct for more information see the code of conduct faq https opensource microsoft com codeofconduct faq or contact opencode microsoft com mailto opencode microsoft com with any additional questions or comments microsoft opc publisher opc publisher is a fully supported microsoft product developed in the open that bridges the gap between industrial assets and the microsoft azure cloud it does so by connecting to opc ua enabled assets or industrial connectivity software and publishes telemetry data to azure iot hub https azure microsoft com en us services iot hub in various formats including iec62541 opc ua pubsub standard format from version 2 6 onwards it runs on azure iot edge https azure microsoft com en us services iot edge as a module or on plain docker as a container since it leverages the net cross platform runtime https docs microsoft com en us dotnet core introduction it also runs natively on linux and windows 10 getting started please use our released docker containers for opc publisher available in the microsoft container registry rather than building from sources the easiest way to deploy opc publisher is through the azure marketplace https azuremarketplace microsoft com en us marketplace apps microsoft iot iotedge opc publisher img src image 20201028141833399 png style zoom 50 https azuremarketplace microsoft com en us marketplace apps microsoft iot iotedge opc publisher simply click the get it now button to log into the azure portal https portal azure com and deploy opc publisher the following steps are required 1 pick the azure subscription to use if no azure subscription is available one must be created 2 pick the iot hub the opc publisher is supposed to send data to if no iot hub is available one must be created 3 pick the iot edge device the opc publisher is supposed to run on or enter a name for a new iot edge device to be created 4 click create the set modules on device page for the selected iot edge device opens 5 click on opcpublisher to open the opc publisher s update iot edge module page and then select container create options 6 specify additional container create options based on your usage of opc publisher see next section below please note only one instance of opc publisher per iot edge deployment is currently supported accessing the microsoft container registry docker containers for opc publisher manually the latest released version of opc publisher can be run manually via docker run mcr microsoft com iotedge opc publisher latest name where name is the name for the container specifying container create options in the azure portal when deploying opc publisher through the azure portal container create options can be specified in the update iot edge module page of opc publisher these create options must be in json format the opc publisher command line arguments can be specified via the cmd key e g cmd pf publishednodes json aa a typical set of iot edge module container create options for opc publisher is hostname opcpublisher cmd pf publishednodes json aa hostconfig binds iiotedge appdata with these options specified opc publisher will read the configuration file publishednodes json the opc publisher s working directory is set to appdata at startup and thus opc publisher will read the file appdata publishednodes json inside its docker container opc publisher s log file will be written to appdata and the certificatestores directory used for opc ua certificates will also be created in this directory to make these files available in the iot edge host file system the container configuration requires a bind mount volume the iiotedge appdata bind will map the directory appdata to the host directory iiotedge which will be created by the iot edge runtime if it doesn t exist without this bind mount volume all opc publisher configuration files will be lost when the container is restarted a connection to an opc ua server using its hostname without a dns server configured on the network can be achieved by adding an extrahosts entry to the hostconfig section hostconfig extrahosts opctestsvr 192 168 178 26 configuring opc publisher opc publisher has several interfaces that can be used to configure it configuring security iot edge provides opc publisher with its security configuration for accessing iot hub automatically opc publisher can also run as a standalone docker container by specifying a device connection string for accessing iot hub via the dc command line parameter a device for iot hub can be created and its connection string retrieved through the azure portal for accessing opc ua enabled assets x 509 certificates and their associated private keys are used by opc ua this is called opc ua application authentication and in addition to opc ua user authentication opc publisher uses a file system based certificate store to manage all application certificates during startup opc publisher checks if there is a certificate it can use in this certificate stores and creates a new self signed certificate and new associated private key if there is none self signed certificates provide weak authentication since they are not signed by a trusted certificate authority but at least the communication to the opc ua enabled asset can be encrypted this way security is enabled in the configuration file via the usesecurity true flag the most secure endpoint available on the opc ua servers the opc publisher is supposed to connect to is automatically selected by default opc publisher uses anonymous user authentication in additional to the application authentication described above however opc publisher also supports user authentication using username and password this can be specificed via the rest api configuration interface described below or the configuration file as follows opcauthenticationmode usernamepassword opcauthenticationusername usr opcauthenticationpassword pwd in addition opc publisher version 2 5 and below encrypts the username and password in the configuration file version 2 6 and above only supports the username and password in plaintext this will be improved in the next version of opc publisher to persist the security configuration of opc publisher across restarts the certificate and private key located in the the certificate store directory must be mapped to the iot edge host os filesystem please see specifying container create options in the azure portal above configuration via configuration file the simplest way to configure opc publisher is via a configuration file an example configuration file is provided via the file publishednodes json https raw githubusercontent com azure iot edge opc publisher main opcpublisher publishednodes json in this repository configuration file syntax has changed over time and opc publisher still can read old formats but converts them into the latest format when persisting the configuration done regularly in an automated fashion a basic configuration file looks like this endpointurl opc tcp testserver 62541 quickstarts referenceserver usesecurity true opcnodes id i 2258 opcsamplinginterval 2000 opcpublishinginterval 5000 displayname current time opc ua assets optimizes network bandwidth by only sending data changes to opc publisher when the data has changed if data changes need to be published more often or at regular intervals opc publisher supports a heartbeat for every configured data item that can be enabled by additionally specifying the heartbeatinterval key in the data item s configuration the interval is specified in seconds heartbeatinterval 3600 an opc ua asset always send the current value of a data item when opc publisher first connects to it to prevent publishing this data to iot hub the skipfirst key can be additionally specified in the data item s configuration skipfirst true both settings can be enabled globally via command line options too configuration via command line arguments there are several command line arguments that can be used to set global settings for opc publisher they are described here docs commandlinearguments md configuration via the built in opc ua server interface please note this feature is only available in version 2 5 and below of opc publisher opc publisher has a built in opc ua server running on port 62222 it implements three opc ua methods publishnode unpublishnode getpublishednodes this interface can be accessed using an opc ua client application for example ua expert https www unified automation com products development tools uaexpert html configuration via iot hub direct methods please note this feature is only available in version 2 5 and below of opc publisher opc publisher implements the following iot hub direct methods https docs microsoft com en us azure iot hub iot hub devguide direct methods which can be called from an application from anywhere in the world leveraging the iot hub device sdk https docs microsoft com en us azure iot hub iot hub devguide sdks publishnodes unpublishnodes unpublishallnodes getconfiguredendpoints getconfigurednodesonendpoint getdiagnosticinfo getdiagnosticlog getdiagnosticstartuplog exitapplication getinfo we have provided a sample configuration application https github com azure samples iot edge opc publisher nodeconfiguration as well as an application for reading diagnostic information https github com azure samples iot edge opc publisher diagnostics from opc publisher open source leveraging this interface configuration via cloud based companion rest microservice please note this feature is only available in version 2 6 and above of opc publisher a cloud based companion microservice with a rest interface is described and available here https github com azure industrial iot blob master docs services publisher md it can be used to configure opc publisher via an openapi compatible interface for example through swagger opc publisher telemetry format opc publisher version 2 6 and above supports standardized opc ua pubsub json format as specified in part 14 of the opc ua specification https opcfoundation org developer tools specifications unified architecture part 14 pubsub and looks like this messageid 18 messagetype ua data publisherid uat46f9f8f82fd5c1b42a7de31b5dc2c11ef418a62f datasetclassid 78c4e91c 82cb 444e a8e0 6bbacc9a946d messages datasetwriterid uat46f9f8f82fd5c1b42a7de31b5dc2c11ef418a62f sequencenumber 18 metadataversion majorversion 1 minorversion 1 timestamp 2020 03 24t23 30 56 9597112z status null payload http test org ua data i 10845 value 99 sourcetimestamp 2020 03 24t23 30 55 9891469z servertimestamp 2020 03 24t23 30 55 9891469z http test org ua data i 10846 value 251 sourcetimestamp 2020 03 24t23 30 55 9891469z servertimestamp 2020 03 24t23 30 55 9891469z in addition all versions of opc publisher support a non standardized simple json telemetry format which is compatible with azure time series insights https azure microsoft com en us services time series insights and looks like this endpointurl opc tcp 192 168 178 3 49320 nodeid ns 2 s pump 234754a c63 b9601 monitoreditem applicationuri urn myfirstopcserver value value 973 sourcetimestamp 2020 11 30t07 21 31 2604024z statuscode 0 status good endpointurl opc tcp 192 168 178 4 49320 nodeid ns 2 s boiler 234754a c63 b9601 monitoreditem applicationuri urn mysecondopcserver value value 974 sourcetimestamp 2020 11 30t07 21 32 2625062z statuscode 0 status good configuration of the simple json telemetry format via separate configuration file please note this feature is only available in version 2 5 and below of opc publisher opc publisher allows filtering the parts of the non standardized simple telemetry format via a separate configuration file which can be specified via the tc command line option if no configuration file is specified the full json telemetry format is sent to iot hub the format of the separate telemetry configuration file is described here docs telemetryformatconfiguration md performance and memory tuning opc publisher when running opc publisher in production setups network performance requirements throughput and latency and memory resources must be considered opc publisher exposes the following command line parameters to help meet these requirements message queue capacity mq for version 2 5 and below not available in version 2 6 om for version 2 7 iot hub send interval si iot hub message size ms the mq om parameter controls the upper limit of the capacity of the internal message queue this queue buffers all messages before they are sent to iot hub the default size of the queue is up to 2 mb for opc publisher version 2 5 and below and 4000 iot hub messages for version 2 7 i e if the setting for the iot hub message size is 256 kb the size of the queue will be up to 1 gb if opc publisher is not able to send messages to iot hub fast enough the number of items in this queue increases if this happens during test runs one or both of the following can be done to mitigate decrease the iot hub send interval si increase the iot hub message size ms the maximum this can be set to is 256 kb if the queue keeps growing even though the si and ms parameters have been adjusted eventually the maximum queue capacity will be reached and messages will be lost this is due to the fact that both the si and ms parameter have physical limits and the internet connection between opc publisher and iot hub is simply not fast enough for the amount of messages that must be sent in a given scenario in that case only setting up several parallel opc publishers will help the mq om parameter also has the biggest impact on the memory consumption by opc publisher it must be noted that iot hub also has limits in terms of how many messages it will accept i e there are quotas for a given iot hub sku defined here https docs microsoft com en us azure iot hub iot hub devguide quotas throttling if this quota is exceeded opc publisher will generate an error trying to send the message to iot hub and the message will be lost the si parameter forces opc publisher to send messages to iot hub at the specified interval a message is sent either when the maximum iot hub message size of 256 kb of data is available triggering the send interval to reset or when the specified interval time has passed the ms parameter enables batching of messages sent to iot hub in most network setups the latency of sending a single message to iot hub is high compared to the time it takes to transmit the payload this is mainly due to quality of service qos requirements since messages are acknowledged only once they have been processed by iot hub therefore if a delay for the data to arrive at iot hub is acceptable opc publisher should be configured to use the maximal message size of 256 kb by setting the ms parameter to 0 it is also the most cost effective way to use opc publisher the default configuration sends data to iot hub every 10 seconds si 10 or when 256 kb of iot hub message data is available ms 0 this adds a maximum delay of 10 seconds but has low probability of losing data because of the large message size the metric monitored item notifications enqueue failure in opc publisher version 2 5 and below and messages lost in opc publisher version 2 7 shows how many messages were lost when both si and ms parameters are set to 0 opc publisher sends a message to iot hub as soon as data is available this results in an average iot hub message size of just over 200 bytes however the advantage of this configuration is that opc publisher sends the data from the connected asset without delay the number of lost messages will be high for use cases where a large amount of data must be published and hence this is not recommended for these scenarios to measure the performance of opc publisher the di parameter can be used to print performance metrics to the trace log in the interval specified in seconds local metrics dashboard for opc publisher to learn more about how to create a local metrics dashboard for opc publisher v2 7 please refer to the tutorial here docs prometheus metrics metricsdashboard md source code status branch status master build status https ci appveyor com api projects status 6t7ru6ow7t9uv74r branch master svg true https ci appveyor com project marcschier iot gateway opc ua r4ba5 branch master build status https travis ci org azure iot gateway opc ua svg branch master https travis ci org azure iot gateway opc ua | opc-publisher iot-edge opc-ua | server |
twitter-nlp | covid twitter project overview resources the following resources provide an overview of the project overview slides https docs google com presentation d 1ixgehix he sg2qoordjcvfgvfre5lfxisznnnndklg edit usp sharing idea poster https drive google com file d 1y66amfgijqbteux0rmq rpja1u7pewvj view usp sharing ug research symposium poster slides https drive google com file d 13u5hqektnfd3i1osdlsbvifxpj1xx5gf view usp sharing additional info for the health analytics challenge lab hacl can be found here hacl 20 md getting started on the rensselaer idea cluster 1 clone this repository to your preferred location on the cluster home directory etc 2 modify your local copies of semantic search rmd https github com therensselaeridea covid twitter blob master analysis semantic search rmd and twitter rmd https github com therensselaeridea covid twitter blob master analysis twitter rmd by inserting the hostname of the elasticsearch server into the line elasticsearch host see the project slack channel idea covid twitter to get the hostname it is pinned to the channel note the hostname should be removed before committing changes to this repository 3 in rstudio knit both of these notebooks they may take a few minutes to run depending on the search parameters on a local machine coming soon using the notebooks both semantic search rmd https github com therensselaeridea covid twitter blob master analysis semantic search rmd and twitter rmd https github com therensselaeridea covid twitter blob master analysis twitter rmd are meant to be knit to html only run the rmd directly in rstudio when working on parts of the code note that the html output will not render correctly in rstudio so results need to be viewed as dataframes instead when working in this mode common parameters both notebooks accept the following common parameters date range this filters the date range for which tweets will be retrieved in general larger date ranges take longer to run the query below retrieves tweets from april 1 to april 15 the rangeend parameter is exclusive meaning that tweets occuring at midnight april 16th are not returned r query start date time inclusive rangestart 2020 04 01 00 00 00 query end date time exclusive rangeend 2020 04 16 00 00 00 note when running on the idea cluster due to storage limitations not all collected tweets have their embeddings computed and stored in elasticsearch for best results restrict queries to dates within the following ranges on which there exist more than 100 000 embedded tweets per day march 17 april 16 inclusive april 23 april 25 inclusive this list will be updated when storage capacity increases and more tweets are embedded text filter a text filter limits the result set to only those tweets that pass the filter criteria r text filter restricts results to only those containing words phrases or meeting a boolean condition this query syntax is very flexible and supports a wide variety of filter scenarios words text filter cdc nih who contains cdc or nih or who phrase text filter vitamin c contains exact phrase vitamin c boolean condition cdc nih who vitamin c contains cdc or nih or who and exact phrase vitamin c full specification here https www elastic co guide en elasticsearch reference current query dsl simple query string query html text filter cure prevent location filter a location filter limits the result set to only those tweets originating from locations that pass the filter criteria locations can be provided by the tweet author s user profile or by geolocation r location filter acts like text filter except applied to the location of the tweet instead of its text body location filter louisiana geolocation filter a geolocation filter limits the result set to only those tweets which are geolocated r if false location filter considers both user povided and geotagged locations if true only geotagged locations are considered must have geo false semantic phrase a semantic phrase causes retrieved tweets to be ordered by cosine similarity with the embedding of this phrase r query semantic similarity phrase choose one of these examples or enter your own semantic phrase i lost my job because of covid 19 how am i going to be able to make rent result size number of tweets to retrieve r number of results to return to return all results set to na resultsize 10000 minimum number of results if less than this number of tweets are returned for the given search parameters raise an error r minimum number of results to return this should be set according to the needs of the analysis i e enough samples for statistical significance min results 500 parameters for semantic search rmd this notebook just uses the common search parameters however resultsize should be restricted to a number that can reasonably be displayed less than 1000 parameters for twitter rmd this notebook uses the common search parameters and an additional parameter for random sampling random sampling if semantic phrase is blank this flag indicates if tweets should be returned in ascending chronological order or as a random distribution across the date range it typically makes sense to enable this when not using a semantic phrase since in chronological order the first 10 000 tweets likely occur within the first minute of the date range r return results in chronological order or as a random sample within the range ignored if semantic phrase is not blank random sample true if using random sampling optionally specify a seed for reproducibility for no seed set to na random seed na temporary clustering settings change k and cluster k to change the number of k means clusters and subclusters respectively r number of high level clusters temporary until automatic selection implemented k if semantic phrase 15 else 5 number of subclusters per high level cluster temporary until automatic selection implemented cluster k 8 by default the k means elbow plot is not run but this can be enabled by uncommenting the line wssplot tweet vectors matrix these settings are intented to be removed when they are no longer necessary temporary display settings these settings show hide additional information about each cluster and subcluster it could be informative to knit the notebook at least once with all of these set to true r show hide extra info temporary until tabs are implemented show original subcluster plots false show regrouped subcluster plots true show word freqs false show center nn false tweetid dataset the tweetid dataset has been moved to its own repository https github com therensselaeridea covid tweetids | ai |
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wats3010-hello-world | hello world this is the hello world assignment repository for wats 3010 you will find everything you need to complete the hello world assignment here walkthrough video https youtu be lgbgkojjio in order to complete the assignment you must perform a series of tasks centered around getting used to working with git and github specifically we are going to practice forking and cloning repositories working with branches and how to use github pages before you begin this assignment you ll need to sign up for a github com account configure secure shell on your local machine install and configure visual studio code on your local machine to complete this assignment you must complete the following steps 1 fork this repo into your personal github account 1 create a projects directory on your local machine 1 clone your fork of this repo into the projects directory 1 open the directory created by cloning the repo in visual studio code 1 create an index html file in the root of the project directory 1 use the tab keystrokes to initialize your html file 1 modify the content of the title tag to be hello world 1 create a css directory in the root of your project 1 add a style css file to the css directory 1 add a link tag to import the css file into the index html file you can place the link tag directory under the title tag it should look like this link href css style css rel stylesheet 1 add an h1 header tag to the body of the index html file the content of the h1 tag should be hello world 1 in the style css file add text color and background color to your page with an entry like this body color red background color black 13 make sure all files are saved turn on auto save in vs code to help with this 14 preview your files locally with live server to make sure they are what you expect 15 open the terminal in vs code mac users will see a bash terminal by default windows users should configure git bash to be their default commmand line interface 16 stage commit and push your code to github com with these commands git add git commit m description of changes made git push 17 go to github com and find that our files our now posted on the web 18 go to github com setting for your repo and configure gh pages to host your master branch 19 view your hosted file and copy the link into your buffer and note that the domain is github io 20 go back to the code tab of github com and click on the edit button and paste the link into the website input box 21 submit both the github com and the github io links for your homework expected hosted file hello world helloworld png stretch goals add another html page try to add colors based on the h1 tag add headers content using h2 h6 you are encouraged to watch the video demo linked at the top of this page for more information about how to complete each of these steps you can also consult the wats faq https suwebdev github io wats lab faq pages for setting up git github https suwebdev github io wats lab faq first question html settign up visual studio code https suwebdev github io wats lab faq second question html | front_end |
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Natural-Language-Processing-and-Computational-Linguistics | natural language processing and computational linguistics this is the code repository for natural language processing and computational linguistics https www packtpub com application development beginning natural language processing utm source github utm medium repository utm campaign 9781788838535 published by packt it contains all the supporting project files necessary to work through the book from start to finish about the book modern text analysis is now very accessible using python and open source tools so discover how you can now perform modern text analysis in this era of textual data this book shows you how to use natural language processing and computational linguistics algorithms to make inferences and gain insights about data you have these algorithms are based on statistical machine learning and artificial intelligence techniques the tools to work with these algorithms are available to you right now with python and tools like gensim and spacy you ll start by learning about data cleaning and then how to perform computational linguistics from first concepts you re then ready to explore the more sophisticated areas of statistical nlp and deep learning using python with realistic language and text samples you ll learn to tag parse and model text using the best tools you ll gain hands on knowledge of the best frameworks to use and you ll know when to choose a tool like gensim for topic models and when to work with keras for deep learning this book balances theory and practical hands on examples so you can learn about and conduct your own natural language processing projects and computational linguistics you ll discover the rich ecosystem of python tools you have available to conduct nlp and enter the interesting world of modern text analysis instructions and navigations all of the code is organized into folders each folder starts with a number followed by the application name for example chapter02 the code will look like the following print build model model sequential model add embedding max features 128 model add lstm 128 dropout 0 2 recurrent dropout 0 2 model add dense 1 activation sigmoid related products natural language processing with tensorflow https www packtpub com application development natural language processing tensorflow utm source github utm medium repository utm campaign 9781788478311 deep learning with tensorflow second edition https www packtpub com big data and business intelligence deep learning tensorflow second edition utm source github utm medium repository utm campaign 9781788831109 download a free pdf i if you have already purchased a print or kindle version of this book you can get a drm free pdf version at no cost br simply click on the link to claim your free pdf i p align center a href https packt link free ebook 9781788838535 https packt link free ebook 9781788838535 a p | ai |
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2016-ml-contest | 2016 ml contest the contest is now closed thank you to everyone that participated final standings congratulations to la team the top teams based on the median f1 micro score from 100 realizations of their models were position team f1 algorithm language solution 1 la team mosser de la fuente 0 6388 boosted trees python notebook la team facies classification la team 05 validation ipynb 2 pa team petroanalytix http petroanalytix com 0 6250 boosted trees python notebook pa team pa team submission 8 xgb validation ipynb 3 ispl bestagini tuparo lipari 0 6231 boosted trees python notebook ispl facies classification try03 v2 validation ipynb 4 esateam https github com esa as earth analytics http www earthanalytics no index html 0 6225 boosted trees python notebook esateam esa submission01 validation ipynb i have stochastic scores for other teams and will continue to work through them but it seems unlikely that these top teams will change at this point hr welcome to the geophysical tutorial machine learning contest 2016 read all about the contest in the october 2016 issue http library seg org toc leedff 35 10 of the magazine look for brendon hall s tutorial on lithology prediction with machine learning you can run the notebooks in this repo in the cloud just click the badge below binder http mybinder org badge svg http mybinder org repo seg 2016 ml contest you can also clone or download this repo with the green button above or just read the documents index ipynb index ipynb mdash all about the contest facies classification ipynb facies classification ipynb mdash brendon s notebook with all the code you need to get started in machine learning in python leaderboard f1 scores of models against secret blind data in the stuart and crawford wells the logs for those wells are available in the repo https github com seg 2016 ml contest blob master validation data nofacies csv but contestants do not have access to the facies these are deterministic scores the final standings depend on stochastic scores see above team f1 algorithm language solution la team mosser de la fuente 0 641 boosted trees python notebook la team facies classification la team 05 ipynb ispl bestagini tuparo lipari 0 640 boosted trees python notebook ispl facies classification try03 v2 ipynb shandpr 0 631 boosted trees python notebook shandpr face classification shpr gradientboost ipynb houmath 0 630 boosted trees python notebook houmath face classification houmath xgb 06 ipynb esateam https github com esa as 0 629 boosted trees python notebook esateam esa submission01 ipynb pet stromatolite 0 625 boosted trees python notebook pet stromatolite facies classification draft7 ipynb pa team 0 623 boosted trees python notebook pa team pa team submission 8 xgb ipynb cc ml 0 619 boosted trees python notebook cc ml cc submission1 no neigh boosting refine4 ipynb geolearn 0 613 random forest python notebook geolearn submission 4 ovr rf ipynb ar4 https github com ar4 0 606 random forest python notebook ar4 ar4 submission2 ipynb houston j https github com houston j 0 600 boosted trees python notebook houston j houston j sub2 ipynb bird team 0 598 random forest python notebook bird team facies classification 4 ipynb gccrowther https github com gccrowther 0 589 random forest python notebook gcc faciesclassification 05 20 20facies 20determination ipynb thanish https github com thanish 0 580 random forest r code mendacium mendacium rf sub 10 r mandms 0 579 majority voting python notebook mandms 02 facies classification mandms plurality voting classifier ipynb evgenizer https github com evgenizer 0 578 boosted trees python notebook evgenys facies classification es ipynb jpoirier 0 574 random forest python notebook jpoirier jpoirier011 submission001 ipynb kr1m https github com kr1m 0 570 adaboosted trees python notebook kr1m kr1m seg ml attempt1 ipynb shiangyong https github com shiangyong 0 570 convnet python notebook shiangyong facies classification cnn ipynb carlosfuerte 0 570 multilayer perceptron python notebook carlosfuerte ml submission ipynb fvf1361 https github com fvf1361 0 568 majority voting python notebook fvf facies classification ipynb carthycraft https github com carthycraft 0 566 boosted trees python notebook admc mccarthy 202016 20ml 20v17 ipynb gganssle https github com gganssle 0 561 deep neural net lua notebook gram faye ipynb stodig 0 561 convnet python notebook stodig facies classification stodig 4 ipynb wouterk1mss https github com wouterk1mss 0 559 random forest python notebook mss xmas trees ml seg try1 ipynb anjum48 https github com anjum48 0 559 majority voting python notebook anjum48 anjum48 20facies 20classification 20v2 ipynb itwm 0 557 convnet python notebook itwm facies classification itwm 01 ipynb jjlowe https github com jjlowe 0 556 deep neural network python notebook jlowe jlowe nn ipynb adatum https github com adatum 0 552 majority voting r notebook adatum well partitioned facies classification rmd cesprey https github com cesprey 0 550 majority voting python notebook cesprey 20 20randomforest facies tree ensemble classifier ipynb osorensen https github com osorensen 0 549 boosted trees r notebook boostedxmas facies 20classification ipynb rkappius https github com rkappius 0 534 neural network python notebook rkappius facies w tf submit py jesperdramsch https github com jesperdramsch 0 530 random forest python notebook jesperdramsch facies classification xmas trees copy1 ipynb cako https github com cako 0 522 multi layer perceptron python notebook discerninghaggis discerning haggis facies classification sub3 ipynb bgc team 0 519 deep neural network python notebook bgc team facies 20prediction submit ipynb cannedgeo https github com cannedgeo 0 512 support vector machine python notebook cannedgeo facies classification bpage cannedgeo f1 56 validated ipynb aranzgeo 0 511 deep nerual network python code aranzgeo hypter py daghra https github com dagrha 0 506 k nearest neighbours python notebook dagrha knn submission 1 dagrha ipynb brendonhall https github com brendonhall 0 427 support vector machine python initial score in article getting started with python please refer to the user guide to the geophysical tutorials http library seg org doi abs 10 1190 tle35020190 1 for tips on getting started in python and find out more about jupyter notebooks find out more about the contest if you intend to enter this contest i suggest you check the open issues https github com seg 2016 ml contest issues and read through the closed issues https github com seg 2016 ml contest issues q is 3aissue is 3aclosed too there s some good info in there to find out more please read the article in the october issue http library seg org toc leedff 35 10 or read the manuscript in the tutorials 2016 https github com seg tutorials 2016 repo rules we ve never done anything like this before so there s a good chance these rules will become clearer as we go we aim to be fair at all times and reserve the right to make judgment calls for dealing with unforeseen circumstances important when this contest was first published we asked you to hold the shankle well blind this is no longer necessary you can use all the published wells in your training related i am removing the file of predicted facies for the stuart and crawford wells to reduce confusion they are not actual facies only those predicted by brendon s first model you must submit your result as code and we must be able to run your code entries will be scored by a comparison against known facies in the stuart and crawford wells which do not have labels in the contest dataset we will use the f1 cross validation score see issue 2 regarding this point https github com seg 2016 ml contest issues 2 the scores in the leaderboard reflect this where there is stochastic variance in the predictions the median average of 100 realizations will be used as the cross validation score see issue 114 regarding this point https github com seg 2016 ml contest issues 114 the scores in the leaderboard do not currently reflect this probably only the top entries will be scored in this way updated 23 jan the result we get with your code is the one that counts as your result to make it more likely that we can run it your code must be written in python or r or julia or lua updated 26 oct the contest is over at 23 59 59 ut i e midnight in london uk on 31 january 2017 pull requests made aftetr that time won t be eligible for the contest if you can do even better with code you don t wish to share fully that s really cool nice work but you can t enter it for the contest we invite you to share your result through your blog or other channels maybe a paper in the leading edge this document and documents it links to will be the channel for communication of the leading solution and everything else about the contest this document contains the rules our decision is final no purchase necessary please exploit artificial intelligence responsibly licenses please note that the dataset is not openly licensed we are working on this but for now please treat it as proprietary it is shared here exclusively for use on this problem in this contest we hope to have news about this in early 2017 if not before all code is the property of its author and subject to the terms of their choosing if in doubt ask them the information about the contest and the original article and everything in this repo published under the auspices of seg is licensed cc by and ok to use with attribution | machine-learning data-science geoscience contest geophysics fun | ai |
Airport-App | airport app | front_end |
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udacity-c2-frontend | udagram simple frontend udagram is a simple cloud application developed along side the udacity cloud engineering nanodegree it allows users to register and log into a web client post photos to the feed and process photos using an image filtering microservice the project is split into three parts 1 the simple frontend https github com udacity cloud developer tree master course 02 exercises udacity c2 frontend a basic ionic client web application which consumes the restapi backend 2 the restapi backend https github com udacity cloud developer tree master course 02 exercises udacity c2 restapi a node express server which can be deployed to a cloud service 3 the image filtering microservice https github com udacity cloud developer tree master course 02 project image filter starter code the final project for the course it is a node express application which runs a simple script to process images getting setup tip this frontend is designed to work with the restapi backend https github com grutt udacity c2 restapi it is recommended you stand up the backend first test using postman and then the frontend should integrate installing node and npm this project depends on nodejs and node package manager npm before continuing you must download and install node npm is included from https nodejs com en download https nodejs org en download installing ionic cli the ionic command line interface is required to serve and build the frontend instructions for installing the cli can be found in the ionic framework docs https ionicframework com docs installation cli installing project dependencies this project uses npm to manage software dependencies npm relies on the package json file located in the root of this repository after cloning open your terminal and run bash npm install tip npm i is shorthand for npm install configure the backend endpoint ionic uses enviornment files located in src enviornments enviornment ts to load configuration variables at runtime by default environment ts is used for development and enviornment prod ts is used for produciton the apihost variable should be set to your server url either locally or in the cloud running the development server ionic cli provides an easy to use development server to run and autoreload the frontend this allows you to make quick changes and see them in real time in your browser to run the development server open terminal and run bash ionic serve building the static frontend files ionic cli can build the frontend into static html css javascript files these files can be uploaded to a host to be consumed by users on the web build artifacts are located in www to build from source open terminal and run bash ionic build todo 2 tasks i setup a clone set up protected branches dev staging master b npm ionic cli c run tests npm test identify broken function fix the function d write tests for form validation and re run tests | cloud |
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python-nlp-ml-tutorial | a brief tutorial on machine learning with nltk python this is a tutorial on machine learning techniques using nltk in python it is based on python 3 6 and nltk you can see the example code in nltk ipynb nltk ipynb to run the code locally you need to have ipython https ipython org and jupyter http jupyter org notebook you ll also need the following python packages nltk scikit learn numpy once you have tools installed clone this repository to open up the tutorial notebook run jupyter from command line jupyter notebook path to nltk ipynb this will open the notebook on your web browser | ai |
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MobileDev-XamarinForms | welcome to github pages you can use the editor on github https github com universityofplymouthcomputing xamarin forms course edit master readme md to maintain and preview the content for your website in markdown files whenever you commit to this repository github pages will run jekyll https jekyllrb com to rebuild the pages in your site from the content in your markdown files markdown markdown is a lightweight and easy to use syntax for styling your writing it includes conventions for markdown syntax highlighted code block header 1 header 2 header 3 bulleted list 1 numbered 2 list bold and italic and code text link url and image src for more details see github flavored markdown https guides github com features mastering markdown jekyll themes your pages site will use the layout and styles from the jekyll theme you have selected in your repository settings https github com universityofplymouthcomputing xamarin forms course settings the name of this theme is saved in the jekyll config yml configuration file support or contact having trouble with pages check out our documentation https help github com categories github pages basics or contact support https github com contact and we ll help you sort it out | front_end |
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