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BlockchainEvents-CompositeJourney | hyperledger composer product auction network with events read this in other languages readme ko md readme cn md readme ja md warning this repository is no longer maintained warning this repository which contains assets to run a hyperledger composer application is not being actively maintained due to a shift to focus on hyperledger fabric this repository will not be updated the repository will be kept available in read only mode refer to https github com ibm auction events for a similar example welcome to part 3 of the hyperledger composer composite pattern this is a continuation of hyperledger composer product auction network https github com ibm blockchainsmartcontracttrading compositejourney this pattern shows how events can be emitted by hyperledger composer and subscribed by external applications audience level intermediate developers if you have an ibm cloud lite account you can also use the starter plan for 30 days to do this pattern included components hyperledger fabric hyperledger composer docker application workflow diagram workflow images arch blockchain events png start the hyperledger fabric network generate and deploy the business network archive start and connect the composer rest server to deployed business network start the web application steps 1 generate the business network archive bna 1 generate the business network archive bna 2 deploy the business network archive to local hyperledger fabric instance 2 deploy the business network archive on hyperledger fabric running locally 3 start the web ui 3 start the web ui 4 submit transactions 4 submit transactions 1 generate the business network archive bna make sure that you have installed the prerequisites for hyperledger composer https hyperledger github io composer latest installing installing prereqs also make sure that you have installed the development environment which includes hyperledger composer hyperledger fabric and the other node modules using these instructions https hyperledger github io composer latest installing development tools as a recap for those instructions you should have done the following installed hyperledger composer and it s related node modules using npm downloaded the docker images for hyperledger fabric started hyperledger fabric locally on your machine executed createpeeradmincard sh to create a network card that will be used to install the business network later in this exercise clone the repository git clone https github com ibm blockchainevents compositejourney to check that the structure of the files is valid you can now generate a business network archive bna file for your business network definition the bna file is the deployable unit a file that can be deployed to the hyperledger composer runtime for execution use the following command to generate the network archive cd blockchainevents compositejourney composer npm install you should see the following output mkdirp dist composer archive create sourcetype dir sourcename a dist events bna creating business network archive looking for package json of business network definition input directory users ishan documents demo blockchainevents compositejourney composer found description sample product auction network with events name events identifier events 0 0 1 written business network definition archive file to output file dist events bna command succeeded the composer archive create command has created a file called events bna in the dist folder you can test the business network definition against the embedded runtime that stores the state of the blockchain in memory in a node js process from your project working directory open the file test productauction js and run the following command npm test you should see the following output events 0 0 1 test users ishan documents demo blockchainevents compositejourney composer nyc mocha t 0 test js org acme product auction authorized owner should start the bidding 74ms members bid for the product 139ms close bid for the product 175ms 3 passing 2s file stmts branch funcs lines uncovered line s all files 0 0 0 0 2 deploy the business network archive to local hyperledger fabric instance make sure that you have started hyperledger fabric instance locally on your machine using these instructions https hyperledger github io composer latest installing development tools now change directory to the dist folder containing events bna file and execute the following commands to install deploy and start the business network on the local hyperledger fabric instance cd blockchainevents compositejourney composer dist composer network install c peeradmin hlfv1 a events bna composer network start c peeradmin hlfv1 n events v 0 0 1 a admin s adminpw f networkadmin card composer card import file networkadmin card you can verify that the network has been deployed by typing composer network ping card admin events you should see the the output as follows the connection to the network was successfully tested events the connection to the network was successfully tested events business network version 0 0 1 composer runtime version 0 19 5 participant org hyperledger composer system networkadmin admin identity org hyperledger composer system identity e7eaa3bc255f5ded89fd5c25748aca87959c9b3fc6ad6a94c65d679162db84fd command succeeded to create the rest api we need to launch the composer rest server and tell it how to connect to our deployed business network now launch the server by changing directory to the product auction folder and type cd blockchainevents compositejourney composer composer rest server enter the name of the business network card to use admin events specify if you want namespaces in the generated rest api never use namespaces specify if you want to use an api key to secure the rest api no specify if you want to enable authentication for the rest api using passport no specify if you want to enable event publication over websockets yes specify if you want to enable tls security for the rest api no test rest api if the composer rest server started successfully you should see these two lines are output web server listening at http localhost 3000 browse your rest api at http localhost 3000 explorer 3 start the web ui in a new terminal window navigate to web directory and launch the node server using command cd blockchainevents compositejourney web npm install node server js 4 submit transactions submit transactions for auction network using the instructions in hyperledger composer section https github com ibm blockchainsmartcontracttrading compositejourney 2 deploy the business network archive using composer playground events are emitted when user submits publishlisting makeoffer and closebidding transactions web ui for seller and buyer updates on the event emitted from the hyperledger fabric network you can submit the transactions either by using hyperledger composer rest api or hyperledger composer playground running locally using rest api open a web browser and navigate to http localhost 3000 explorer using composer playground you can install the hyperledger composer playground locally as shown below npm install g composer playground and run the hyperledger composer playground locally using composer playground navigate to http localhost 8000 seller html and http localhost 8000 buyer html to view the dashboards for seller and buyer events additional resources hyperledger fabric docs https hyperledger fabric readthedocs io hyperledger composer docs https hyperledger github io composer latest introduction introduction html license this code pattern is licensed under the apache software license version 2 separate third party code objects invoked within this code pattern are licensed by their respective providers pursuant to their own separate licenses contributions are subject to the developer certificate of origin version 1 1 dco https developercertificate org and the apache software license version 2 https www apache org licenses license 2 0 txt apache software license asl faq https www apache org foundation license faq html whatdoesitmean | ibm blockchain hyperledger-fabric hyperledger-composer ibmcode call-for-code | blockchain |
Honeypots-on-Blockchain | a pot of smart contract honeypots this repo contains almost all the ethereum smart contract honeypots that can be found in the first three pages of google search honeypot https imgur com 1canncx jpg the presentation slide made by the author is here https www slideshare net yaochiehhu smart contract honeypots on blockchain tutorials the phenomenon of smart contract honeypots https medium com coinmonks the phenomena of smart contract honeypots 755c1f943f7b an analysis of a couple ethereum honeypot contracts https medium com coinmonks an analysis of a couple ethereum honeypot contracts 5c07c95b0a8d hacking the hackers honeypots on ethereum network https hackernoon com hacking the hackers honeypots on ethereum network 5baa35a13577 dissecting an ethereum honey pot https medium com coinmonks dissecting an ethereum honey pot 7102d7def5e0 the sneakiest ethereum scam honeypot ever https hackernoon com the sneakiest ethereum scam ever 6dc138061235 repos thec00n smart contract honeypots https github com thec00n smart contract honeypots trailofbits not so smart contracts https github com trailofbits not so smart contracts tree master honeypots misterch0c solidlity vulnerable https github com misterch0c solidlity vulnerable news tricked by a honeypot contract or beaten by another hacker what happened https www reddit com r ethdev comments 7x5rwr tricked by a honeypot contract or beaten by clever ethereum honeypot lets coins come in but won t let them back out https techcrunch com 2018 02 16 clever ethereum honeypot lets coins come in but wont let them back out hack the hackers honeypot crypto scam targets would be coin thieves https www financemagnates com cryptocurrency news hack hackers honeypot crypto scam targets coin thieves | blockchain hack security smart-contracts ethereum honeypots | blockchain |
Mastering-Flask-Web-Development-Second-Edition | mastering flask web development second edition a href https www packtpub com web development hands web development flask second edition utm source github utm medium repository utm campaign 9781788995405 img src https www packtpub com media catalog product cache e4d64343b1bc593f1c5348fe05efa4a6 b 1 b10232 png alt mastering flask web development second edition height 256px align right a this is the code repository for mastering flask web development second edition https www packtpub com web development hands web development flask second edition utm source github utm medium repository utm campaign 9781788995405 published by packt build enterprise grade scalable python web applications what is this book about flask is a popular python framework known for its lightweight and modular design mastering flask web development will take you on a complete tour of the flask environment and teach you how to build a production ready application this book covers the following exciting features develop a flask extension using best practices implement various authentication methods ldap jwt database oauth and openid learn how to develop role based access security and become an expert on jinja2 templates build tests for your applications and apis install and configure a distributed task queue using celery and rabbitmq if you feel this book is for you get your copy https www amazon com dp 1788995406 today a href https www packtpub com utm source github utm medium banner utm campaign githubbanner img src https raw githubusercontent com packtpublishing github master github png alt https www packtpub com border 5 a instructions and navigations all of the code is organized into folders for example chapter02 the code will look like the following from flask import g set some key with some value on a request context g some key some value get a key v g some key get and remove a key v g pop some key default if not present following is what you need for this book the ideal target audience for this book would be python developers who want to use flask and its advanced features to create enterprise grade and lightweight applications the book is for those who have some exposure of flask and want to take it from introductory to master level with the following software and hardware list you can run all code files present in the book chapter 1 13 software and hardware list chapter software required os required 1 13 python windows mac os x and linux any related products other books you may enjoy python testing cookbook second edition packt https www packtpub com application development python testing cookbook second edition utm source github utm medium repository utm campaign 9781787122529 amazon https www amazon com dp 1787122522 building django 2 0 web applications packt https www packtpub com web development building django 20 web applications utm source github utm medium repository utm campaign 9781787286214 amazon https www amazon com dp 1787286215 get to know the author daniel gaspar is a programmer and devops engineer with more than 20 years experience he has worked in a wide range of sectors including government and finance he is currently working at miniclip the global leader in digital games he uses a wide range of tools in his daily work but flask caught his attention because of its excellently designed api and simplicity daniel is an oss and python enthusiast and has developed a widely used extension framework named flask appbuilder used by airbnb on superset and airflow suggestions and feedback click here https docs google com forms d e 1faipqlsdy7datc6qmel81fiuuymz0wy9vh1jhkvpy57oimekgqib ow viewform if you have any feedback or suggestions 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 9781788995405 https packt link free ebook 9781788995405 a p | front_end |
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blockchain | a simple blockchain sample in c for net a simple blockchain example in c using sha512 for hashing this lib can generate a block with data add that block to a chain in this case a list t create a hash for that block create a hash based non a nonce a proof of work or mining a block validate that hash and the hash of a previous block validate the whole chain enjoy usage as like in a console application using nl hyperdata blockchain using system using system linq namespace blockchainsample class program private static random random new random datetime now millisecond private static readonly iblock genesis new block new byte 0x00 0x00 0x00 0x00 0x00 0x00 0x00 0x00 proof of work https en wikipedia org wiki proof of work system is set here a hash needs 2 trailing zero bytes increase the number of bytes to reduce the number of valid hashes and increse the proof of work time private static readonly byte difficulty new byte 0x00 0x00 static void main string args initiate the chain set a difficulty for genarating the hash proof of work and define the genesis data not really important blockchain chain new blockchain difficulty genesis start mining 20 blocks in a loop for int i 0 i 20 i randomly generated dummy data var data enumerable range 0 256 select x byte random next add the fresh unhashed block with the data to the chain chain add new block data toarray blockchain magic happens here output the generated block details console writeline chain lastordefault tostring validate the chain ie is each block s hash valid and is the prevoius block has valid console writeline string format chain is valid 0 chain isvalid | blockchain hashing encryption csharp sample-code | blockchain |
design-system | div align center persona icon src public assets images logo svg persona design system npm scoped https img shields io npm v privyid persona style for the badge https www npmjs com package privyid persona ci https img shields io github actions workflow status privy open source design system ci yml style for the badge https github com privy open source design system actions workflows ci yml codecov https img shields io codecov c github privy open source design system style for the badge https codecov io gh privy open source design system codefactor https img shields io codefactor grade github privy open source design system main style for the badge https www codefactor io repository github privy open source design system installation https privy open source github io design system docs getting started html docs https privy open source github io design system try online https stackblitz com github privy open source persona starter tree dashboard div installation goto online docs https privy open source github io design system docs getting started html contribution see contributing guide contributing md thanks to a href https github com privy open source design system graphs contributors img src https contrib rocks image repo privy open source design system a license mit license license c 2022 privy identitas digital | nuxt-module nuxt3 vue-component-library vue-template vue3 scaffolding nuxt3-starter ui-components vue3-components | os |
AutoDAN | autodan the official implementation of our pre print paper autodan generating stealthy jailbreak prompts on aligned large language models paper https arxiv org abs 2310 04451 jailbreak attacks https img shields io badge jailbreak attacks yellow svg style plastic adversarial attacks https img shields io badge adversarial attacks orange svg style plastic large language models https img shields io badge largelanguage models green svg style plastic abstract the aligned large language models llms are powerful language understanding and decision making tools that are created through extensive alignment with human feedback however these large models remain susceptible to jailbreak attacks where adversaries manipulate prompts to elicit malicious outputs that should not be given by aligned llms investigating jailbreak prompts can lead us to delve into the limitations of llms and further guide us to secure them unfortunately existing jailbreak techniques suffer from either 1 scalability issues where attacks heavily rely on manual crafting of prompts or 2 stealthiness problems as attacks depend on token based algorithms to generate prompts that are often semantically meaningless making them susceptible to detection through basic perplexity testing in light of these challenges we intend to answer this question can we develop an approach that can automatically generate stealthy jailbreak prompts in this paper we introduce autodan a novel jailbreak attack against aligned llms autodan can automatically generate stealthy jailbreak prompts by the carefully designed hierarchical genetic algorithm extensive evaluations demonstrate that autodan not only automates the process while preserving semantic meaningfulness but also demonstrates superior attack strength in cross model transferability and cross sample universality compared with the baseline moreover we also compare autodan with perplexity based defense methods and show that autodan can bypass them effectively img src autodan png width 700 latest update 2023 10 11 we have released the quick implementation of autodan more instructions will be updated soon 2023 10 03 we have released our paper quick start get code shell git clone https github com sheltonliu n autodan git build environment shell cd autodan conda create n autodan python 3 9 conda activate autodan pip install r requirements txt download llms should have permissions when downloading llama2 see this page https ai meta com resources models and libraries llama downloads shell cd start python download models py autodan shell python autodan py with gpt mutation shell python autodan py api key your openai api key runing in low gpu memory 24gb will cost more time shell python autodan py api key your openai api key low memory 1 result snapshot from chat with llama2 https www llama2 ai llama2 7b img src snapshot png width 400 acknowledge some of our codes are built upon llm attack https github com llm attacks llm attacks bibtex bibtex misc liu2023autodan title autodan generating stealthy jailbreak prompts on aligned large language models author xiaogeng liu and nan xu and muhao chen and chaowei xiao year 2023 eprint 2310 04451 archiveprefix arxiv primaryclass cs cl | ai |
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design-system | the design system has moved to talend ui https github com talend ui tree master packages design system | design-system react reakit styled-components storybook cypress | os |
bit-repo_02 | octocat bit course frontend 01 course name bootcamp desarrollo web frontend start date 2022 10 25 end date 2023 03 10 learning objectives english web cli gui vcs vch pma tools html css ui ux framework bootstrap javascript json api library react initial requirements 1 desire and commitment to study and to learn 2 computer 3 internet connection documentation code sample open file folder 00git open file folder 01html open file folder 02css open file folder 03bootstrap open file folder 04javascript open file folder 05vanillaexamples open file folder 06react open file folder 07reactexamples guides guides guides md tasks tasks tasks md course page https javierandresgp github io bit course frontend 01 software developer built by javi https javierandres dev copyright 2022 2023 found a bug or have an idea contact me https javierandres dev | css git html javascript markdown react | front_end |
sql-challenge | homework assignment 7 database modeling and engineering description image erd erd layout png br this image shows the relationships between the data it is also located inside the erd folder the schemata are located inside schema schema sql for creating the tables based on the above relationships the analysis queries are located inside query query sql along with comments as to which condition they satisfy notes it probably would have been proper to set a composite key for dept managers same as dept emp but the data didn t require it and since the data was from the 1980 s 90 s nothing new should be added to it that would change that requirement the grading scale mentions a bonus analysis but either i wasn t able to find what that bonus analysis was supposed to be or directions for it weren t included so it hasn t been included here sources no code was copied reused from external sources | server |
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chat-gui | destinygg chat gui requirements node js development 1 install node js dependencies npm ci 2 create a copy of the example env file cp env example env 3 optional use the developer tools in your web browser to access your cookies and obtain your destiny gg session tokens sid and rememberme 4 optional add the tokens to your env file vim env note save and exit vim with wq 5 run the webpack development server npm run start development server navigate to https localhost 8282 in your web browser of choice to access a local instance of dgg chat gui connected to production destiny gg chat if you supplied your session tokens by following steps 3 and 4 above you ll be authenticated and can chat like normal note that the tokens will eventually expire and won t automatically renew in this environment query string parameters t embed type possible values embed for bigscreen chat stream for on stream chat default embed f chat font scale possible values an integer from 1 to 10 note only works for the stream embed type examples open the on stream chat with a font scale of 5 https localhost 8282 t stream f 5 | front_end |
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theHitProject | thehitproject cloud software engineering project amp labs year 2 semester1 cloud software engineering practical work to show understanding of spring framework | cloud |
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large-scale-lm-tutorials | large scale language modeling tutorials with pytorch images megatron 3d png tunib pytorch transformer github https github com tunib ai large scale lm tutorials br github nbviewer https nbviewer org github tunib ai large scale lm tutorials tree main notebooks contents 1 introduction https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 01 introduction ipynb 2 motivation https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 02 motivation ipynb 3 distributed programming https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 03 distributed programming ipynb 4 overview of parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 04 overview of parallelism ipynb 5 data parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 05 data parallelism ipynb 6 pipeline parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 06 pipeline parallelism ipynb 7 tensor parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 07 tensor parallelism ipynb 8 zero redundancy optimization https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 08 zero redundancy optimization ipynb 09 multi dimensional parallelism https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 09 multi dimensional parallelism ipynb 10 additional techniques https nbviewer org github tunib ai large scale lm tutorials blob main notebooks 10 additional techiques ipynb environments local environments linux ubuntu 18 04 lts 4 a100 gpu python 3 7 pytorch 1 9 0 cu111 docker environments docker pull pytorch pytorch 1 9 0 cuda11 1 cudnn8 devel shm size ipc host license copyright 2021 tunib inc licensed under the apache license version 2 0 the license you may not use this file except in compliance with the license you may obtain a copy of the license at http www apache org licenses license 2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license | ai |
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isc-iknow-extractor | information extraction demo app this is a sample application for demonstrating how iknow can not only be used to extract specific information elements from natural language text but also show which entities were involved and which other entities were related to those supposedly containing the information thereby often showing relevant contextual information how to set up this app assumes you already have an iknow domain configured although you can also enter input text manually simply refer your browser to http localhost 57772 csp user extractor csp 123 with 57772 user and 123 replaced by the appropriate port number namespace or web app name and domain id respectively extending the demo this demo app was made to be extensible through the addition of potentially code heavy extractor classes being designed for demo purposes there may obviously be more elegant architectures than the current one | intersystems iknow | server |
c-code-style | recommended c style and coding rules this document describes c code style used by projects and libraries of ms rtos general rules here are listed most obvious and important general rules please check them carefully before you continue with other chapters use c99 standard do not use tabs use spaces instead use 4 spaces per indent level use 1 space between keyword and opening bracket do not use space between function name and opening bracket c ms int32 t a sum 4 3 ok ms int32 t a sum 4 3 wrong use only lowercase characters for variables functions types with optional underscore char opening curly bracket is always at the same line as keyword for while do switch if c ms size t i for i 0 i 5 i ok for i 0 i 5 i wrong for i 0 i 5 i wrong use single space before and after comparison and assignment operators c ms int32 t a a 3 4 ok for a 0 a 5 a ok a 3 4 wrong a 3 4 wrong for a 0 a 5 a wrong use single space after every comma c func name 5 4 ok func name 4 3 wrong do not initialize static and global variables to 0 or ms null let compiler do it for you c static ms int32 t a ok static ms int32 t b 4 ok static ms int32 t a 0 wrong void my func void static ms int32 t ptr ok static char abc 0 wrong declare local variables in order 1 custom structures and enumerations 2 integer types wider unsigned type first 3 single double floating point c int my func void 1 my struct t my first custom structures my struct ptr t p pointers too 2 ms uint32 t a ms int32 t b ms uint16 t c ms int16 t g char h 3 double d float f always declare local variables at the beginning of the block before first executable statement don t declare counter variables in for loop c ok ms size t i for i 0 i 10 i wrong for ms size t i 0 i 10 i avoid variable assignment with function call in declaration except for single variables c void a void avoid function calls when declaring variable ms int32 t a b sum 1 2 use this ms int32 t a b b sum 1 2 this is ok ms uint8 t a 3 b 4 except char float or double always use types declared in stdint h library eg ms uint8 t for unsigned 8 bit etc do not use stdbool h library use ms true or ms false for true or false respectively c ok ms bool t status status ms true wrong include stdbool h bool status true never compare against true eg if check func 1 use if check func always compare pointers against ms null value c ms ptr t ptr ok compare against null if ptr ms null ptr ms null wrong if ptr ptr always use ms size t for length or size variables always use const for pointer if function should not modify memory pointed to by pointer always use const for function parameter or variable if it should not be modified c when d could be modified data pointed to by d could not be modified void my func ms const ptr t d when d and data pointed to by d both could not be modified void my func ms const ptr t const d not required it is advised void my func const ms size t len when d should not be modified inside function only data pointed to by d could be modified void my func ms ptr t const d when function may accept pointer of any type always use ms ptr t do not use ms uint8 t function must take care of proper casting in implementation c to send data function should not modify memory pointed to by data variable thus const keyword is important to send generic data or to write them to file any type may be passed for data thus use ms ptr t ok example void send data ms const ptr t data ms size t len ok do not cast ms ptr t or ms const ptr t const uint8 t d data function handles proper type for internal usage void send data ms const ptr t data int len wrong not not use int never use variable length array vla use dynamic memory allocation instead with standard c malloc and free functions or if library project provides custom memory allocation always use brackets with sizeof operator c ok include stdlib h void my func ms size t size ms int32 t arr arr malloc sizeof arr n ok allocate memory arr malloc sizeof arr n wrong brackets for sizeof operator are missing if arr ms null fail no memory free arr free memory after usage wrong void my func ms size t size int32 t arr size wrong do not use vla always compare variable against zero except if it is treated as boolean type never compare boolean treated variables against zero or one use not instead c ms size t length 5 counter variable ms uint8 t is ok 0 boolean treated variable if length wrong length is not treated as boolean if length 0 ok length is treated as counter variable containing multi values not only 0 or 1 if length 0 ok length is treated as counter variable containing multi values not only 0 or 1 if is ok ok variable is treated as boolean if is ok ok variable is treated as boolean if is ok 1 wrong never compare boolean variable against 1 if is ok 0 wrong use for negative check always use comment for comments even for single line comment always include check for c with extern keyword in header file every function must include doxygen enabled comment even if function is static use english names text for functions variables comments use lowercase characters for variables use underscore if variable contains multiple names eg force redraw do not use forceredraw never cast function returning ms ptr t eg ms uint8 t ptr ms uint8 t func returning void ptr as ms ptr t is safely promoted to any other pointer type use ms uint8 t ptr func returning void ptr instead always use and for c standard library include files eg include stdlib h always use for custom libraries eg include my library h when casting to pointer type always align asterix to closing bracket eg ms uint8 t t ms uint8 t var width diff type always respect code style already used in project or library comments comments starting with are not allowed always use comment even for single line comment c this is comment wrong this is comment ok for multi line comments use space asterisk for every line c this is multi line comments written in 2 lines ok wrong use double asterisk only for doxygen documentation single line comment without space before asterisk wrong single line comment in multi line configuration wrong single line comment ok use 12 indents 12 4 spaces offset when commenting if statement is larger than 12 indents make comment 4 spaces aligned examples below to next available indent c void my func void char a b a call func returning char a a this is comment with 12 4 spaces indent from beginning of line b call func returning char a but func name is very long a this is comment aligned to 4 spaces indent functions every function which may have access from outside its module must include function prototype or declaration function name must be lowercase optionally separated with underscore character c ok void my func void void myfunc void wrong void myfunc void void myfunc when function returns pointer align asterix to return type c ok const char my func void my struct t my func void wrong const char my func void const char my func void my struct t my func ms int32 t a ms int32 t b my struct t my func ms int32 t a ms int32 t b align all function prototypes with the same similar functionality for better readability c ok function names aligned void set ms int32 t a my type t get void my ptr t get ptr void wrong void set ms int32 t a const char get void function implementation must include return type and optional other keywords in same line c ok ms int32 t foo void return 0 wrong ms int32 t foo void return 0 wrong static const char get string void return hello world r n when function returns pointer asterisk character must be aligned to variables or function name c ok const char foo void return test wrong const char foo void return test variables make variable name all lowercase with optional underscore character c ok ms int32 t a ms int32 t my var ms int32 t myvar wrong ms int32 t a ms int32 t myvar ms int32 t myvar group local variables together by type c void foo void ms int32 t a b ok char a char b wrong char type already exists do not declare variable after first executable statement c void foo void ms int32 t a a bar ms int32 t b wrong there is already executable statement you may declare new variables inside next indent level c ms int32 t a b a foo if a ms int32 t c d ok c and d are in if statement scope c foo int32 t e wrong there was already executable statement inside block declare pointer variables with asterisk aligned to variables name c ok char a wrong char a char a when declaring multiple pointer variables you may declare them with asterisk aligned to variable name c ok char p n structures enumerations typedefs structure or enumeration name must be lowercase with optional underscore character between words structure or enumeration may contain typedef keyword all structure members must be lowercase all enumeration members must be uppercase structure enumeration must follow doxygen documentation syntax when structure is declared it may use one of 3 different options 1 when structure is declared with name only it must not contain t suffix after its name c struct struct name char a char b 2 when structure is declared with typedef only it has to contain t suffix after its name c typedef struct char a char b struct name t 3 when structure is declared with name and typedef it must not contain t for basic name and it has to contain t suffix after its name for typedef part c typedef struct struct name char a char b char c struct name t examples of bad declarations and their suggested corrections c a and b must be separated to 2 lines name of structure with typedef must include t suffix typedef struct ms int32 t a b a corrected version typedef struct ms int32 t a ms int32 t b a t wrong name it must not include t suffix struct name t ms int32 t a ms int32 t b wrong parameters must be all uppercase typedef enum my enum testa my enum testb my enum t when initializing structure on declaration use c99 initialization style c ok a t a a 4 b 5 wrong a t a 1 2 when new typedef is introduced for function handles use func t suffix c function accepts 2 parameters and returns ms uint8 t name of typedef has func t suffix typedef ms uint8 t my func func t ms uint8 t p1 const char p2 compound statements every compound statement must include opening and closing curly bracket even if it includes only 1 nested statement every compound statement must include single indent when nesting statements include 1 indent size for each nest c ok if c do a else do b wrong if c do a else do b wrong if c do a else do b in case of if or if else if statement else must be in the same line as closing bracket of first statement c ok if a else if b else wrong if a else wrong if a else in case of do while statement while part must be in the same line as closing bracket of do part c ok do ms int32 t a a do a do b a while check wrong do while check wrong do while check indentation is required for every opening bracket c if a do a else do b if c do c never do compound statement without curly bracket even in case of single statement examples below show bad practices c if a do b else do c if a do a else do b empty while do while or for loops must include brackets c ok while is register bit set wrong while is register bit set while is register bit set while is register bit set if while or for do while etc is empty it can be the case in embedded programming use empty two line brackets c wait for bit to be set in embedded hardware unit uint32 t addr hw periph register addr wait bit 13 to be ready while addr 1 13 ok empty loop contains no spaces inside curly brackets while addr 1 13 wrong while addr 1 13 wrong while addr 1 13 wrong curly brackets are missing can lead to compiler warnings or unintentional bugs always prefer using loops in this order for do while while avoid incrementing variables inside loop block if possible see examples c not recommended ms int32 t a 0 while a 10 a better ms size t a for a 0 a 10 a better if inc may not happen in every cycle ms size t a for a 0 a 10 if a switch statement add single indent for every case statement use additional single indent for break statement in each case or default c ok every case has single indent ok every break has additional indent switch check case 0 do a break case 1 do b break default break wrong case indent missing switch check case 0 do a break case 1 do b break default break wrong switch check case 0 do a break wrong break must have indent as it is under case case 1 do b wrong indent under case is missing break default break always include default statement c ok switch var case 0 do job break default break wrong default is missing switch var case 0 do job break if local variables are required use curly brackets and put break statement outside put opening curly bracket in the same line as case statement c switch a ok case 0 int32 t a b char c a 5 break wrong case 1 int32 t a break wrong break shall be outside case 2 int32 t a break macros and preprocessor directives always use macros instead of literal constants specially for numbers all macros must be fully uppercase with optional underscore character except if they are clearly marked as function which may be in the future replaced with regular function syntax c ok define my macro x x x wrong define square x x x always protect input parameters with parentheses c ok define min x y x y x y wrong define min x y x y x y always protect final macro evaluation with parenthesis c wrong define min x y x y x y define sum x y x y imagine result of this equation using wrong sum implementation ms int32 t x 5 sum 3 4 expected result is 5 7 35 ms int32 t x 5 3 4 it is evaluated to this final result 19 which is not what we expect correct implementation define min x y x y x y define sum x y x y when macro uses multiple statements protect it using do while ms false statement c typedef struct ms int32 t px py point t point t p define new point wrong implementation define macro to set point define set point p x y p px x p py y 2 statements last one should not implement semicolon set point p 3 4 set point to position 3 4 this evaluates to p px 3 p py 4 to this in this example this is not a problem consider this ugly code however it is valid by c standard not recommended if a if a is true if b if b is true set point p 3 4 set point to x 3 y 4 else set point p 5 6 set point to x 5 y 6 evaluates to code below do you see the problem if a if b p px 3 p py 4 else p px 5 p py 6 or if we rewrite it a little if a if b p px 3 p py 4 else p px 5 p py 6 ask yourself a question to which if statement else keyword belongs based on first part of code answer is straight forward to inner if statement when we check b condition actual answer compilation error as else belongs nowhere better and correct implementation of macro define set point p x y do p px x p py y while 0 2 statements no semicolon after while loop or even better define set point p x y do backslash indicates statement continues in new line p px x p py y while 0 2 statements no semicolon after while loop now original code evaluates to if a if b do p px 3 p py 4 while 0 else do p px 5 p py 6 while 0 every part of if or else contains only 1 inner statement do while hence this is valid evaluation to make code perfect use brackets for every if ifelse else statements if a if a is true if b if b is true set point p 3 4 set point to x 3 y 4 else set point p 5 6 set point to x 5 y 6 always write macro documentation as regular function with additional hideinitializer doxygen keyword c define my macro x x 2 avoid using ifdef or ifndef use defined or defined instead c ifdef xyz do something endif xyz always document if elif else endif statements c ok if defined xyz do if xyz defined else defined xyz do if xyz not defined endif defined xyz wrong if defined xyz do if xyz defined else do if xyz not defined endif do not indent sub statements inside if statement c ok if defined xyz if defined abc do when abc defined endif defined abc else defined xyz do when xyz not defined endif defined xyz wrong if defined xyz if defined abc do when abc defined endif defined abc else defined xyz do when xyz not defined endif defined xyz documentation documented code allows doxygen to parse and general html pdf latex output thus it is very important to do it properly use doxygen enabled documentation style for variables functions and structures enumerations always use 5x4 spaces 5 tabs offset from beginning of line for text c brief holds pointer to first entry in linked list beginning of this text is 5 tabs 20 spaces from beginning of line static type t list every structure enumeration member must include documentation use 12x4 spaces offset for beginning of comment c brief this is point struct note this structure is used to calculate all point related stuff typedef struct ms int32 t x point x coordinate ms int32 t y point y coordinate ms int32 t size point size since comment is very big you may go to next line point t brief point color enumeration typedef enum color red red color this comment has 12x4 spaces offset from beginning of line color green green color color blue blue color point color t documentation for functions must be written in function implementation source file usually function must include brief and all parameters documentation every parameter must be noted if it is in or out for input and output respectively function must include return parameter if it returns something this does not apply for void functions function can include other doxygen keywords such as note or warning use colon between parameter name and its description c brief sum 2 numbers param in a first number param in b second number return sum of input values ms int32 t sum ms int32 t a ms int32 t b return a b brief sum 2 numbers and write it to pointer note this function does not return value it stores it to pointer instead param in a first number param in b second number param out result output variable used to save result return n a void void sum ms int32 t a ms int32 t b ms int32 t result result a b if function returns member of enumeration use ref keyword to specify which one c brief my enumeration typedef enum my err error value my ok ok value my enum t brief check some value return ref my ok on success member of ref my enum t otherwise my enum t check value void return my ok use notation null null for constants or numbers c brief get data from input array param in in input data return pointer to output data on success null otherwise const void get data const void in return in documentation for macros must include hideinitializer doxygen command c brief get minimal value between x and y param in x first value param in y second value return minimal value between x and y hideinitializer define min x y x y x y header source files leave single empty line at the end of file every file must include doxygen annotation for file and brief description followed by empty line when using doxygen c file template h brief template include file here is empty line every file header or source must include license opening comment includes single asterisk as this must be ignored by doxygen use the same license as already used by project library c file template h brief template include file copyright c year xxx team all rights reserved detailed license information can be found in the license file file xxx c xxx author firstname lastname optional email example com header file must include guard ifndef header file must include c check include external header files outside c check include external header files with stl c files first followed by application custom files header file must include only every other header file in order to compile correctly but not more c should include the rest if required header file must only expose module public variables types functions use extern for global module variables in header file define them in source file later file h ifndef extern ms int32 t my variable this is global variable declaration in header endif file c ms int32 t my variable actually defined in source never include c files in another c file c file should first include corresponding h file later others unless otherwise explicitly necessary do not include module private declarations in header file header file example no license for sake of an example c license comes here ifndef template hdr h define template hdr h include headers ifdef cplusplus extern c endif cplusplus file content here ifdef cplusplus endif cplusplus endif template hdr h | os |
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Stereo-Webcam-Depth-Detection | stereo webcam depth detection computer vision project to get depth information from a pair of low cost webcams the developed code uses opencv and largely follows from work done by martin peris described by http martinperis blogspot com au 2011 01 opencv stereo camera calibration html the code is able to track colored objects and report their distance in real time a memory based algorithm in also developed to improve the stability of the depth image requirements visual studio 2012 was used for this project the project files are available with the source code the hardware requirement for the code is simply two usb webcams plugged into the pc as can be seen below as it is important that the webcams stay in a fixed position after calibration more about calibration below a clamp was fabricated during this project img src https github com mkokshoorn stereo webcam depth detection blob master device image jpg width 400 building the code the code was developed using visual studio 2012 and opencv 2 4 3 install both of these set the appropriate environment variables and open the sln file in the source code folder to open the project build the code in release mode to get cvstereodepth exe calibration to run the main program the stereo vision pair of webcams need to be calibrated this can be done by running cvstereodepth exe and passing an argument of the number of calibration capture frames desired as an additional argument for example to calibrate with 10 images cvstereodepth exe 10 the calibration code requires images of chessboard seen by both cameras to calculate intrinsic and extrinsic camera parameters the dimensions of chessboard need to be defined in stdafx h as nx and ny however the values currently correspond to an a4 printed version of the chessboard at http 1 bp blogspot com 0zx 4pm8hna tsltkqjxsci aaaaaaaaai0 45mjocs5 f8 s1600 opencv chessboard png and as follows img src http 1 bp blogspot com 0zx 4pm8hna tsltkqjxsci aaaaaaaaai0 45mjocs5 f8 s1600 opencv chessboard png width 400 when the calibration is running each frame can then be captured manual by pressing spacebar or initiate the auto capture sequence by pressing c this will take a shot every 0 5 seconds defined in stdafx h as seconds between captures once this is complete or at any time presses esc to finish capturing and begin calibration the program will then save the appropriate calibration matrices inside the release file here the frames used for calibration will also be saved the code can then be run by passing no argument to enter the stereo webcam system mode the program can then be terminated by pressing esc while one of the opencv windows is active for best results try to capture the chessboards in a range of different positions and angles running depth detection program once the calibration procedure has been run and the code is run from the command line parsing no arguments the system is then able to be used this will open seven windows including the command window these are explained as follows webcam one left webcam two right these two windows represent the rectified left and right stereo images respectively note if left is not left or right is not right either swap the usb connections or swap the 0 and 1 in the function call webcam init from scvstereodepth cpp raw disparity this represents the output image from the block matching stereo correspondence function dispariy this represents the memory disparity image that can be activated through bm stereo correspondance parameters bm stereo correspondance parameters allows the user to modify the parameters associated with the block matching algorithm red object finder shows the red threshold image for object tracking the main function is found within cvstereodepth cpp and carries out the following tasks calibration if specified enters a loop until esc is pressed rectifies left and right image carries out block matching correspondence update displays calculate depth if required depth detection can then be done in one of three ways 1 the first is automated and uses the red object tracking to overlay the distance to the red object on the left image this will only occur if there is a large blob of red that can be seen in the red object finder window 2 the second is simply to click on a pixel in the webcam one left window the calculated x y z co ordinate is then printed through the command window 3 tthe final method allows the user to manually correspond features in both images this is done by left right or middle the clicking on the feature in the left image and then again in the right image note that left click places a red dot right click places a blue dot and middle click places a green dot the disparity is calculated from the difference in positioning of the same coloured dots in each image to calculate the depth once the dots have been placed press space bar to print the information to the command window an example video of the program running can be seen in demowithtext mp4 a screenshot can also be seen as follows https github com mkokshoorn stereo webcam depth detection blob master programscreenshot png source code overview the stereo vision project source code consists of 6 modules they are briefly explained as follows cvstereodepth cpp this consists of the main function and scheduling of tasks previously outlined stereo calibrate cpp this is an open source piece of code provided by martin perris see academic paper for details it essentially carries out the calibration form a list of image file locations and the size of the chessboard cvstereocalibration cpp this is a higher level module for the calibration process to allow the auto capturing sequence globaldata cpp this module contains a name space in order for global data to be shared cvstereowebcam cpp deals with the capturing and acquiring of web cam images and also the display functions cvstereocorrespondance cpp this function deals with the block matching correspondence process and the calculations of depth associated with it additionally it sets up the block matching parameters windows parameters and slider interface known issues there appears to be a memory leak associated with the blob library causing the program to crash this can be removed by changing blob tracking defined in stdafx h from 1 to 0 the issue causes to program to crash after a long duration of time due to memory exhaustion it is important to note that the slider values for the block matching parameters do not exactly match those passed to the correspondence fucntion this is due to the sliders inability to go below zero therefore in the case of several of the values they are shifted and scaled i e a 0 to 100 slider may represent 100 to 100 | ai |
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AndroidTextApp | androidtextapp a basic android texting app with frontend and backend features using spring boot developed a better understanding of full stack development through this project | server |
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db-reengineer-and-extract | database reverse engineering and data extraction this repository contains a collection of simple tools to assisst with the task of database reverse engineering and data extraction the repository was motivated by a request to extract responses for a given set of questions in a coursera database dump | server |
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IISSI-Web-Project | iissi web project web project made for iissi subject introduction to software engineering and information systems in university of seville using php html and css and a sql database | server |
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MailWatch | mailscanner images mailwatch logo png raw true mailwatch for mailscanner mailwatch for mailscanner is a web based front end to mailscanner written in php mysql chart js and others usefull libraries this program is free software you can redistribute it and or modify it under the terms of the gnu general public license as published by the free software foundation either version 2 of the license or at your option any later version it comes with a customconfig modules for mailscanner which causes mailscanner to log all message data excluding body text email to a mysql database which is then queried by mailwatch for reporting and statistics features displays the inbound outbound mail queue size currently for exim postfix or sendmail load average and today s totals for messages spam viruses and blocked content on each page header colour coded display of recently processed mail drill down onto each message to see detailed information quarantine management allows you to release delete or run spamassasin sa learn across any quarantined messages reports with customisable filters and graphs by chart js tools to view virus scanner status mysql database status and to view the mailscanner configuration files utilities for postfix and sendmail to monitor and display the mail queue sizes and to record and display message relay information multiple user levels user domain and admin that limit the data and features available to each xml rpc support that allows multiple mailscanner mailwatch installations to act as one works with mysql 5 5 mariadb php 5 4 to php 8 and have been tested on most popular linux distributions debian ubuntu centos and redhat developed with the help of efa email filter appliance htmlpurifier ipset ircmaxell password compat chart js maxmind geoip pear mail pear pager php xmlrpc requests for php znk3r hash equals | php mysql viruses spam-filtering mailscanner webapp frontend | front_end |
lekanojulowo.github.io | lekanojulowo github io lekan ojulowo is a full stack developer dedicated to meet all your software needs website mobile and desktop application development and training | front_end |
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kava | p align center img src kava logo svg width 300 p div align center version https img shields io github tag kava labs kava svg https github com kava labs kava releases latest circleci https circleci com gh kava labs kava tree master svg style shield https circleci com gh kava labs kava tree master go report card https goreportcard com badge github com kava labs kava https goreportcard com report github com kava labs kava api reference https godoc org github com kava labs kava status svg https godoc org github com kava labs kava github https img shields io github license kava labs kava svg https github com kava labs kava blob master license md twitter follow https img shields io twitter follow kava chain svg label follow style social https twitter com kava chain discord chat https img shields io discord 704389840614981673 svg https discord com invite kqzh3uv div div align center telegram https t me kavalabs medium https medium com kava labs discord https discord gg jjynucx div reference implementation of kava a blockchain for cross chain defi built using the cosmos sdk https github com cosmos cosmos sdk mainnet the current recommended version of the software for mainnet is v0 24 0 https github com kava labs kava releases tag v0 24 0 the master branch of this repository often contains considerable development work since the last mainnet release and is not runnable on mainnet installation and setup for detailed instructions see the kava docs https docs kava io docs participate validator node bash git checkout v0 24 0 make install end to end tests of kava use a tool for generating networks with different configurations kvtool https github com kava labs kvtool this is included as a git submodule at tests e2e kvtool tests e2e kvtool when first cloning the repository if you intend to run the e2e integration tests you must also clone the submodules bash git clone recurse submodules https github com kava labs kava git or if you have already cloned the repo git submodule update init testnet for further information on joining the testnet head over to the testnet repo https github com kava labs kava testnets docs kava protocol and client documentation can be found in the kava docs https docs kava io if you have technical questions or concerns ask a developer or community member in the kava discord https discord com invite kqzh3uv security if you find a security issue please report it to security at kava io depending on the verification and severity a bug bounty may be available license copyright kava labs inc all rights reserved licensed under the apache v2 license license md | blockchain go cryptocurrency cosmos-sdk | blockchain |
BioIE-LLM | bioie llm biological information extraction from large language models llms this is the official code of the papers automated extraction of molecular interactions and pathway knowledge using large language model galactica opportunities and challenges https aclanthology org 2023 bionlp 1 22 comparative performance evaluation of large language models for extracting molecular interactions and pathway knowledge https arxiv org abs 2307 08813 installation the code was implemented on python version 3 8 and the versions of the dependencies are listed in requirements txt datasets string db https string db org the human homo sapiens protein network for performing a protein protein interaction ppi recognition task kegg db https www genome jp kegg the kegg human pathways which have been identified as being activated in response to low dose radiation exposure in a recent study https arxiv org abs 2301 01769 indra db http www indra bio a set of human gene regulatory relation statements that represent mechanistic interactions between biological agents reproduction to reproduce the results of the experiments use the bash script run sh scripts run sh you need to change model data paths accordingly results here are the results of the experiments the experiments were conducted on 8 nvidia v100 gpus note different number of gpus and batch size can produce slightly different results recognizing protein protein interactions string task1 precision for the generated binding proteins for 1k protein samples string task2 micro f scores for randomly selected positive and negative pairs i e 1k 500 pos 500 neg model prediction consistency between task1 and task2 table tr th model th th string task1 th th string task2 th th consistency th tr tr th galactica 6 7b th td 0 166 td td 0 552 td td 0 726 td tr tr th llama 7b th td 0 043 td td 0 484 td td 0 984 td tr tr th alpaca 7b th td 0 052 td td 0 521 td td 0 784 td tr tr th rst 11b th td 0 146 td td 0 529 td td 1 000 td tr tr th biogpt large 1 5b th td 0 100 td td 0 504 td td 0 814 td tr tr th biomedlm 2 7b th td 0 069 td td 0 643 td td 0 861 td tr table kegg pathway recognition kegg task1 precision for the generated genes that belong to the top 20 pathways relevant to low dose radiation exposure kegg task2 micro f scores for randomly selected positive and negative pairs i e 1k 500 pos 500 neg model prediction consistency between task1 and task2 table tr th model th th kegg task1 th th kegg task2 th th consistency th tr tr th galactica 6 7b th td 0 256 td td 0 564 td td 0 917 td tr tr th llama 7b th td 0 180 td td 0 562 td td 0 881 td tr tr th alpaca 7b th td 0 268 td td 0 522 td td 1 0 td tr tr th rst 11b th td 0 255 td td 0 514 td td 0 0 td tr tr th biogpt large 1 5b th td 0 550 td td 0 497 td td 0 923 td tr tr th biomedlm 2 7b th td 0 514 td td 0 568 td td 0 821 td tr table evaluating gene regulatory relations indra task micro f scores with 1k samples for each class table tr th model th th 2 class th th 3 class th th 4 class th th 5 class th th 6 class th tr tr th galactica 6 7b th td 0 704 td td 0 605 td td 0 567 td td 0 585 td td 0 597 td tr tr th llama 7b th td 0 351 td td 0 293 td td 0 254 td td 0 219 td td 0 212 td tr tr th alpaca 7b th td 0 736 td td 0 645 td td 0 556 td td 0 636 td td 0 535 td tr tr th rst 11b th td 0 640 td td 0 718 td td 0 597 td td 0 667 td td 0 614 td tr tr th biogpt large 1 5b th td 0 474 td td 0 390 td td 0 293 td td 0 328 td td 0 288 td tr tr th biomedlm 2 7b th td 0 542 td td 0 408 td td 0 307 td td 0 230 td td 0 195 td tr table citation bibtex inproceedings park2023automated title automated extraction of molecular interactions and pathway knowledge using large language model galactica opportunities and challenges author park gilchan and yoon byung jun and luo xihaier and lpez marrero vanessa and johnstone patrick and yoo shinjae and alexander francis booktitle the 22nd workshop on biomedical natural language processing and bionlp shared tasks pages 255 264 year 2023 inproceedings park2023comparativepe title comparative performance evaluation of large language models for extracting molecular interactions and pathway knowledge author gilchan park and byung jun yoon and xihaier luo and vanessa l opez marrero and patrick johnstone and shinjae yoo and francis j alexander year 2023 | ai |
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tpiuo | tpiuo ime marko prezime haralovi email mh53805 fer hr | cloud |
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livnlp.github.io | livnlp github io this is the website for the university of liverpool natural language processing group you must be a member of the livnlp github organisation to be able to commit to this site if you require permissions then contact danushka | nlp nlp-machine-learning | ai |
BioALBERT | bioalbert benchmarking for biomedical natural language processing tasks with a domain specific albert this repository provides the pre trained bioalbert models a biomedical language representation model trained on large domain specific biomedical corpora for designed for biomedical text mining tasks please refer to our paper https arxiv org abs 2107 04374 for more details download we provide eight versions of pre trained weights pre training was based on the original albert code and training details are described in our paper to be published currently available versions of pre trained weights are as follows 1 bioalbert base v1 0 pubmed https drive google com file d 1scu1vvsowowvakoowguc3zkraitlioxd view usp sharing based on albert base model 2 bioalbert base v1 0 pubmed pmc https drive google com file d 1n2uekxknqhbjqlbtipsm8rnpcafeg 2i view usp sharing based on albert base model 3 bioalbert base v1 0 pubmed mimic iii https drive google com file d 1t9xuvmxefrzvyu0m99nb9pipszwafx4v view usp sharing based on albert base model 4 bioalbert base v1 0 pubmed pmc mimic iii https drive google com file d 1sibd gethhmiz7bgmddpeudjojtn bh view usp sharing based on albert base model 5 bioalbert large v1 1 pubmed https drive google com file d 1ux5w8yamyjta3nit 3ayrl16te do8ew view usp sharing based on albert large model 6 bioalbert large v1 1 pubmed pmc https drive google com file d 1wjp7kbwxpa 3qwpsxcn95smy6v2rrbcx view usp sharing based on albert large model 7 bioalbert large v1 1 pubmed mimic iii https drive google com file d 1mzew 0iqscsin86cw xduagnvtnggxyp view usp sharing based on albert large model 8 bioalbert large v1 1 pubmed pmc mimic iii https drive google com file d 16krthf8meze2hcc4vk gunhg 9ly6 6p view usp sharing based on albert large model make sure to specify the version of the pre trained weights used in your work installation the following sections introduce the installation and fine tuning process of bioalbert based on pytorch python version 3 7 to fine tune bioalbert you need to download bioalbert pre training weights after downloading the pre trained weights install bioalbert using requirements txt as follows git clone https github com usmaann bioalbert git cd bioalbert pip install r requirements txt note that this repository is based on the albert https github com google research albert repository by google see requirements txt for other details quick links link detail paper https arxiv org abs 2107 04374 with bibtex misc naseem2021benchmarking title benchmarking for biomedical natural language processing tasks with a domain specific albert author usman naseem and adam g dunn and matloob khushi and jinman kim year 2021 eprint 2107 04374 archiveprefix arxiv primaryclass cs cl datasets we provide a pre processed version of benchmark datasets for each task as follows share clefe https drive google com drive folders 1zaki8xuw49qbrww82w2bxvfjbfdcwrtz usp sharing ddi https drive google com drive folders 1lk1j3ojitxgaut9w1ckb7iewy0spepiy usp sharing chemprot https drive google com drive folders 1iwagftahowflx7 mta9wttnokh w1c5u usp sharing i2b2 https drive google com drive folders 1yv4lioykzmlzouvo3uugfunghiauwmcr usp sharing biosses https drive google com drive folders 1djm2cu2hzhlx9 3znfjo dhcvpvyxkcj usp sharing medsts https drive google com drive folders 1x5l2ieyvkgmmqfnwqjlgpeohznczl0lw usp sharing mednli https drive google com drive folders 1ej9g m8ceiap0inkwsw0rvjnslso5hzw usp sharing hoc https drive google com drive folders 1 ilzzknrfnvr2kvooe40staqzmrxfd7t usp sharing named entity recognition ner bc2gm https drive google com drive folders 130ei5 99hkooahg9kjhvec7sjm1zw4 usp sharing bc4chemd https drive google com drive folders 1gasqyqodtt7ss2vxytvr6ewdgzffbxuj usp sharing bc5cdr disease https drive google com drive folders 1btedxwj1bwszfes8w 4s9mizldjtc4nj usp sharing bc5cdr chemical https drive google com drive folders 1b c vuoz7ae1queuxzjhdyrsrwgygvms usp sharing jnlpba https drive google com drive folders 1smm cy2xxksyhvcir2tent97n 3zyaxc usp sharing linnaeus https drive google com drive folders 1jqegdqadrweoh6vhsyeeowya7w1vdg2p usp sharing ncbi disease https drive google com drive folders 1esm cf3cu0zbkp2n8uximhz8wkarm kw usp sharing species 800 s800 https drive google com drive folders 1s2k1e7hnw1f9khov2aiefzyl0c0sibft usp sharing relation extraction re euadr https drive google com drive folders 1xuig7w93nce4cdld8eanenb7t4pboxcs usp sharing gad https drive google com drive folders 1dfc8eeqrtkf1nt8etaz3i4wyswuqt9c8 usp sharing question answering bioasq bioasq 4b bioasq 5b bioasq 6b open each links and download the datasets you need for bioasq datasets please refer to the biobert repository https github com dmis lab biobert datasets fine tuning biobert after downloading one of the pre trained weights unzip it to any directory you want we will denote it as bioalbert dir for example when using bioalbert base v1 0 pubmed set the bioalbert dir environment variable to export bioalbert dir bioalbert pubmed base echo bioalbert dir bioalbert pubmed base ner each datasets contains four files which are dev tsv test tsv train dev tsv and train tsv simply download a dataset from ner and put these files into the directory called ner dir also set output dir as a directory for ner outputs for example when fine tuning on the bc2gm dataset export ner dir datasets ner bc2gm export output dir ner outputs following command runs fine tuning code on ner with default arguments mkdir p output dir python run ner py do train true do eval true vocab file bioalbert dir vocab txt bert config file bioalbert dir bert config json init checkpoint bioalbert dir model ckpt 1000000 num train epochs 10 0 data dir ner dir output dir output dir re each datasets contains there files which are dev tsv test tsv and train tsv let re dir denote the folder of a single re data set task name denote the task name two options gad euadr and output dir denote the re output directory take gad as an example export re dir datasets re gad 1 export task name gad export output dir re outputs 1 following command runs fine tuning code on re with default arguments python run re py task name task name do train true do eval true do predict true vocab file biobert dir vocab txt bert config file biobert dir bert config json init checkpoint biobert dir model ckpt 1000000 max seq length 128 train batch size 32 learning rate 2e 5 num train epochs 3 0 do lower case false data dir re dir output dir output dir qa please refer to the biobert repository https github com dmis lab biobert question answering qa citation contact information if you have any questions please submit a github issue or contact usman naseem usman naseem sydney edu au | ai |
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ESClient | elasticsearch query client front end js for elasticsearch 1 4 and above users you need to enable cors in elasticsearch yml by setting below line http cors enabled true or http cors allow origin value accordingly for this tool to work elasticsearch client tool for easy search edit and delete index documents key features works with lucene as well as dsl query syntax as per configuration search results are presented in tabular format for easy reading through the results easy updating of documents easy delete of documents with simple button clicks protection against accidental dropping index mappings when trying to delete documents easy configuration of advanced elasticsearch search params in configuration tab json results view available if configured dropping index mapping supported if configured configuration configuration is done in the file config js found in the root folder default configuration looks like below js var config cluster url http localhost 9200 theme smoothness expand lowercase terms true analyze wildcard false search type query then fetch from 0 size 100 default operator or use lucene query type true enable index drop false show json resuls false show mapping info true just point to the location of your elasticsearch cluster cluster url and you are good to go alt tag https raw githubusercontent com rdpatil4 elastic search client master media esclient png after configuration is done follow below steps 1 click connect to connect to your elasticsearch cluster 2 select the index type you want to search on 3 select the fields you want to be displayed in the result table by default all the fields would be displayed in the result table so if you have lot of fields for your selected type then you may want to select only fields of your interest irrespective double click on the row in the table shows the whole json anyways 4 enter the lucene dsl query you want to use for searching 5 hit search to see the results displayed in tabular format alt tag https raw githubusercontent com rdpatil4 elastic search client master media searchresults png editing documents double click the row you want to edit you should see the raw json in the window click the edit button to edit the document if you are using routing while indexing then routing key value is required for updating the documents alt tag https raw githubusercontent com rdpatil4 elastic search client master media edit png deleting documents two ways to delete data 1 delete by id 2 delete by query care is taken for not allowing any accidental deletes you would be asked to confirm before deleting any data also care is taken to not accidentally drop the whole index with mappings delete by id single click on the row s you want to delete and hit delete button no accidental deletes you would be asked to confirm your selection to delete rows alt tag https raw githubusercontent com rdpatil4 elastic search client master media delete png delete by query you can delete multiple rows by query using the delete by query button the query entered in the search box would be used for deleting the rows again no accidental deletes you would be asked to confirm your selection before deleting the rows sorting documents select the field you want to sort and click search default sorting is on score known limitation no index alias supported author rajesh patil rdpatil4 yahoo com special thanks warfares for json formatter datatables for datatables ehynds for multiselect license licensed under the mit license mit mit http www opensource org licenses mit license php | front_end |
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PIC-Micro-controllers-using-Mikro-C-for-PIC16F877A-Basic-Exercises | basic exercises for pic micro controllers using mikro c for pic16f877a basic exercises for pic micro controllers using mikro c for pic16f877a | microcontroller microcontrollers microcontroller-boards pic-micro-controllers pic16f pic16f877a pic18f4550 pic18f2550 embedded embedded-systems embedded-c embedded-devices iot iot-platform iot-application iot-device iot-framework mikro mikroc mikrocpic | os |
FreeRtosExamples | freertos examples this project contains examples for using the freertos real time kernel a practical guide http www freertos org documentation rtos book html by richard barry build cmake the cmake build is mainly taken from https github com ryankurte efm32 base build status travis build status https travis ci org lukaswoodtli freertosexamples svg branch master https travis ci org lukaswoodtli freertosexamples personal notes here http lukaswoodtli github io freertos html are some of my notes for freertos examples chapter 1 task management example description done example 1 creating tasks example 2 using the task parameter example 3 experimenting with priorities example 4 using the blocked state to create a delay example 5 converting the example tasks to use vtaskdelayuntil example 6 combining blocking and non blocking tasks example 7 defining an idle task hook function example 8 changing task priorities example 9 deleting tasks chapter 2 queue management example description done example 10 blocking when receiving from a queue example 11 blocking when sending to a queue or sending structures on a queue chapter 3 interrupt management example description done example 12 using a binary semaphore to synchronize a task with an interrupt example 13 using a counting semaphore to synchronize a task with an interrupt example 14 sending and receiving on a queue from within an interrupt chapter 4 resource management example description done example 15 rewriting vprintstring to use a semaphore example 16 re writing vprintstring to use a gatekeeper task | os |
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nctu-ebds-2015 | nctu introduction to embedded systems design and implementation 2015 lab 2015 this is a step by step lab series about how to use arduino lab1 lab3 and cubieboard lab4 and laters the tutorials are highly recommended reports not included the code is just for studying purpose only arduino lab1 lab3 cubieboard lab4 tutorial | os |
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Arduino-mobile-development-with-Blynk | arduino mobile development with blynk the code repository for the course arduino mobile development with blynk from tech explorations | front_end |
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dart-dev | this project was bootstrapped with create react app https github com facebook create react app available scripts in the project directory you can run npm start runs the app in the development mode br open http localhost 3000 http localhost 3000 to view it in the browser the page will reload if you make edits br you will also see any lint errors in the console npm test launches the test runner in the interactive watch mode br see the section about running tests https facebook github io create react app docs running tests for more information npm run build builds the app for production to the build folder br it correctly bundles react in production mode and optimizes the build for the best performance the build is minified and the filenames include the hashes br your app is ready to be deployed see the section about deployment https facebook github io create react app docs deployment for more information npm run eject note this is a one way operation once you eject you can t go back if you aren t satisfied with the build tool and configuration choices you can eject at any time this command will remove the single build dependency from your project instead it will copy all the configuration files and the transitive dependencies webpack babel eslint etc right into your project so you have full control over them all of the commands except eject will still work but they will point to the copied scripts so you can tweak them at this point you re on your own you don t have to ever use eject the curated feature set is suitable for small and middle deployments and you shouldn t feel obligated to use this feature however we understand that this tool wouldn t be useful if you couldn t customize it when you are ready for it learn more you can learn more in the create react app documentation https facebook github io create react app docs getting started to learn react check out the react documentation https reactjs org code splitting this section has moved here https facebook github io create react app docs code splitting analyzing the bundle size this section has moved here https facebook github io create react app docs analyzing the bundle size making a progressive web app this section has moved here https facebook github io create react app docs making a progressive web app advanced configuration this section has moved here https facebook github io create react app docs advanced configuration deployment this section has moved here https facebook github io create react app docs deployment npm run build fails to minify this section has moved here https facebook github io create react app docs troubleshooting npm run build fails to minify | server |
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ESP32-CAM-wireless-computer-vision-objects-detection | esp32 cam wireless computer vision objects detection esp32 cam wireless computer vision objects detection deteccion de objetos con esp32 cam vision artificial python opencv yolov3 tiempo real se realiza con coco que se encuentra en el mismo directorio en la parte de python se hace referencia en las lineas 13 al 26 donde se realiza la configuraci n y pesos de yolov3 con la ayuda del modulo dnn de opencv el archivo coconames contiene los nombres de distintos objetos que se han entrenado para deteccion de objetos luego se almacena en classnames y as como net se basa en usar librer as para para capas de calculo de salida cargar y procesar qyue ya fueron implementados y m s informaci n se encuentra en internet image https user images githubusercontent com 62358739 115599752 90573200 a2a1 11eb 84f8 86e12ba0e09a png | ai |
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vagas | p align center img src https github com frontendbr brand blob main src png logo 600px horizontal color png width 400 alt front end brasil p h1 align center vagas h1 p align center microscope espa o para divulga o de vagas para front enders p vagas somente vagas de front end espa o para a divulga o de vagas para desenvolvedores via issues do github vagas dispon veis em https github com frontendbr vagas issues cadastrando uma vaga 1 abra uma issue e no t tulo desta issue coloque o nome da cidade entre colchetes seguido do nome da vaga e nome da empresa exemplo s o paulo front end developer na nome da empresa 2 informe quais labels devemos adicionar contendo o n vel de experi ncia desejada e a forma de contra o importante com o objetivo de manter a qualidade das vagas postadas e respeitar todas as pessoas e empresas n o aceitamos 1 vagas sem o nome da empresa 2 vagas de terceiros que n o informem o nome da empresa na qual o a candidato a ir trabalhar 3 vagas com informa es faltantes e ou fora do modelo da issue github issue template adicionar nova vaga md 4 mais do que 3 tr s vagas da mesma empresa por m s independente da vaga o que conta aqui o n mero de vagas da empresa por m s caso algum desses itens seja infringido a modera o poder alertar na issue deletar a issue ou at mesmo banir o usu rio da organiza o sem aviso pr vio obs sabemos que dificil controlar todas essas regras portanto pedimos que nos ajudem e que tenham bom senso cuide da sua vaga para evitar que poss veis candidatos enviem cvs para vagas j preenchidas d manuten o sua issue a cada 3 meses coloque um coment rio que continua procurando para a vaga ou feche a mesma comentando se a pessoa foi contratada atrav s do nosso grupo ou por fora caso a issue passe de 3 meses e n o tiver manuten o a mesma poder ser fechada por um moderador do reposit rio como receber atualiza es de novas vagas voc pode receber atualiza es das vagas no seu email ou via notifica es do github basta clicar em watch e em seguida clicar em watching voc pode modificar o modo de receber notifica es em notifications https github com settings notifications no pr prio github siga nosso twitter img src https cloud githubusercontent com assets 3603793 18564664 f0a4eb36 7b62 11e6 83f8 4eaebee644b0 png alt twitter width 30 todas as oportunidades ser o automaticamente compartilhadas no frontendbrvagas https twitter com frontendbrvagas outros reposit rios de vagas como esse reposit rio espec fico para a postagem de vagas de front end mas existem vagas para muitas outras reas nesse mercado algumas pessoas da comunidade forkaram esse reposit rio e criaram outras listas espec ficas para diferentes stacks e estados do pa s confira abaixo as outras listas onde voc poder postar sua vaga por rea vagas para desenvolvedores back end https github com backend br vagas vagas para desenvolvedores chat bot https github com chatbotbr vagas vagas para desenvolvedores front end https github com frontendbr vagas vagas para desenvolvedores web3 https github com web3br vagas vagas para ui ux https github com remotejobsbr design ux vagas vagas para qas https github com qa brasil vagas por tecnologia vagas para desenvolvedores android https github com androiddevbr vagas vagas para desenvolvedores ios e osx https github com cocoaheadsbrasil vagas vagas para desenvolvedores php https github com phpdevbr vagas vagas para desenvolvedores python https github com pydevbr vagas vagas para desenvolvedores vue js https github com vuejs br vagas vagas para desenvolvedores go golang https github com gommunity vagas vagas para flutter https github com flutter brazil vagas vagas para react react native https github com react brasil vagas vagas para desenvolvedores net https github com dotnetdevbr vagas vagas para desenvolvedores rust https github com rustdevbr vagas vagas para desenvolvedores elm https github com fidelisclayton elm jobs vagas para desenvolvedores kotlin https github com kotlin br vagas por localidade vagas para desenvolvedores no cear https github com cangaceirosdevels vagas de emprego vagas para desenvolvedores front end angola https github com frontend ao vagas vagas para desenvolvedores back end angola https github com backend ao vagas vagas para desenvolvedores front end portugal https github com frontend pt vagas vagas para desenvolvedores back end portugal https github com backend pt vagas licen a mit license copy frontendbr reposit rios da front end brasil f rum https github com frontendbr forum eventos https github com frontendbr eventos vagas https github com frontendbr vagas me contrata https github com frontendbr me contrata compra e venda https github com frontendbr compra e venda doe um livro https github com frontendbr doe um livro poste mais https github com frontendbr poste mais open source https github com frontendbr open source sugest es https github com frontendbr sugestoes | vagas vagas-para-desenvolvedores vagas-frontend frontend-jobs | front_end |
backpack-docs | backpack design system documentation backpack is a collection of design resources reusable components and guidelines for creating skyscanner s products build status https github com skyscanner backpack docs workflows backpack 20docs 20ci badge svg https github com skyscanner backpack docs actions this repository contains the code of the old backpack documentation site see our new docs at skyscanner design https www skyscanner design quick links documentation https backpack github io usage for information on using backpack components please refer to the platform specific repos backpack for web https github com skyscanner backpack backpack for react native https github com skyscanner backpack react native backpack for android https github com skyscanner backpack android backpack for ios https github com skyscanner backpack ios contributing to contribute please see contributing md contributing md contact backpack skyscanner net | os |
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db-capstone-project | db capstone project database engineering capstone project please follow below file list for exercises validation from criteria page was the github repo successfully created https github com jmrosales800 db capstone project is the appropriate project found in the github repo https github com jmrosales800 db capstone project does it include an appropriate er diagram showing the connections between the tables littlelemondm er diagram png additionally you can consult mysql workbench file littlelemondm mwb was the getmaxquantity procedure properly implemented for sql clause consult procedures sql for example result consult getmaxqtyproc png was the managebooking procedure properly implemented the procedure name was different on the exercise page i assume it means addvalidbooking procedure for sql clause consult bookingsys sql was the updatebooking procedure properly implemented for sql clause consult bookingsys2 sql was the addbooking procedure properly implemented for sql clause consult bookingsys2 sql was the cancelbooking procedure properly implemented for sql clause consult bookingsys2 sql database files sql clause for db creation forward engineering littlelemondbscript sql sql clause for db backup littlelemondbdump sql use mysqldump to restore data base https dev mysql com doc refman 8 0 en mysqldump copying database html tableau files files can be found on the tableau file folder tableau workbook capstone little lemondbr0 twb data source littlelemon data xlsx if not longer have a tableau trial period or license screenshots of task can be seen on presentation pptx or these files cuisine name and profit png customer sales png dashboard png profit chart png sales bubble char png python client use client ipynb | server |
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catalyst | nuget https img shields io nuget v catalyst svg maxage 0 colorb brightgreen https www nuget org packages catalyst build status https dev azure com curiosity ai mosaik apis build status catalyst branchname master https dev azure com curiosity ai mosaik build latest definitionid 10 branchname master img src https raw githubusercontent com curiosity ai catalyst master catalyst catalyst png token acdcoayaiml2kgjthtjp27c5kgcec a href https curiosity ai img src https curiosity ai media cat color square svg width 100 height 100 align right a catalyst is a c natural language processing library built for speed inspired by spacy s design https spacy io it brings pre trained models out of the box support for training word and document embeddings and flexible entity recognition models gitter https badges gitter im curiosityai catalyst svg https gitter im curiosityai catalyst utm source badge utm medium badge utm campaign pr badge utm content badge features fast modern pure c nlp library supporting net standard 2 0 https docs microsoft com en us dotnet standard net standard cross platform runs anywhere net core https dotnet microsoft com download is supported windows linux macos and even arm non destructive tokenization https github com curiosity ai catalyst blob master catalyst src models base fasttokenizer cs 99 9 regex free https blog codinghorror com regex performance 1m tokens s on a modern cpu named entity recognition gazeteer https github com curiosity ai catalyst blob master catalyst src models entityrecognition spotter cs rule based https github com curiosity ai catalyst blob master catalyst src models entityrecognition patternspotter cs perceptron based https github com curiosity ai catalyst blob master catalyst src models entityrecognition averageperceptronentityrecognizer cs pre trained models based on universal dependencies https universaldependencies org project custom models for learning abbreviations https github com curiosity ai catalyst blob master catalyst src models special abbreviationcapturer cs senses https github com curiosity ai catalyst blob master catalyst src models entityrecognition spotter cs l214 out of the box support for training fasttext https fasttext cc and starspace https github com facebookresearch starspace embeddings pre trained models coming soon part of speech tagging language detection using fasttext https github com curiosity ai catalyst blob master catalyst src models special fasttextlanguagedetector cs or cld3 https github com curiosity ai catalyst blob master catalyst src models special languagedetector cs efficient binary serialization based on messagepack https github com neuecc messagepack csharp pre built models for language packages https www nuget org packages q catalyst models lemmatization using lookup tables ported from spacy https github com explosion spacy lookups data new language packages we re migrating our model repository to use nuget packages for all language specific data and models you can find all new language packages here https www nuget org packages q catalyst models the new models are trained on the latest release of universal dependencies v2 7 https universaldependencies org this is technically not a breaking change yet but our online repository will be deprecated in the near future so you should migrate to the new nuget packages when using the new model packages you can usually remove this line from your code storage current new onlinerepositorystorage new diskstorage catalyst models or replace it with storage current new diskstorage catalyst models if you are storing your own models locally we ve also added the option to store and load models using streams csharp creates and stores the model var isapattern new patternspotter language english 0 tag is a pattern capturetag isa isapattern newpattern is noun mp mp add new patternunit p single withtoken is withpos partofspeech verb new patternunit p multiple withpos partofspeech noun partofspeech propn partofspeech aux partofspeech det partofspeech adj using var f file openwrite my pattern spotter bin await isapattern storeasync f load the model back from disk var isapattern2 new patternspotter language english 0 tag is a pattern capturetag isa using var f file openread my pattern spotter bin await isapattern2 loadasync f getting started using catalyst is as simple as installing its nuget package https www nuget org packages catalyst and setting the storage to use our online repository this way models will be lazy loaded either from disk or downloaded from our online repository check out also some of the sample projects https github com curiosity ai catalyst tree master samples for more examples on how to use catalyst csharp catalyst models english register you need to pre register each language and install the respective nuget packages storage current new diskstorage catalyst models var nlp await pipeline forasync language english var doc new document the quick brown fox jumps over the lazy dog language english nlp processsingle doc console writeline doc tojson you can also take advantage of c lazy evaluation and native multi threading support to process a large number of documents in parallel csharp var docs getdocuments var parsed nlp process docs dosomething parsed ienumerable idocument getdocuments generates a few documents to demonstrate multi threading lazy evaluation for int i 0 i 1000 i yield return new document the quick brown fox jumps over the lazy dog language english void dosomething ienumerable idocument docs foreach var doc in docs console writeline doc tojson training a new fasttext https fasttext cc word2vec https en wikipedia org wiki word2vec embedding model is as simple as this csharp var nlp await pipeline forasync language english var ft new fasttext language english 0 wiki word2vec ft data type fasttext modeltype cbow ft data loss fasttext losstype negativesampling ft train nlp process getdocs ft storeasync for fast embedding search we have also released a c version of the hierarchical navigable small world hnsw https arxiv org abs 1603 09320 algorithm on nuget https www nuget org packages hnsw based on our fork of microsoft s hnsw net https github com curiosity ai hnsw net we have also released a c version of the uniform manifold approximation and projection umap https umap learn readthedocs io en latest how umap works html algorithm for dimensionality reduction on github https github com curiosity ai umap csharp and on nuget https www nuget org packages umap links documentation contribute how to contribute to catalyst codebase samples sample projects demonstrating catalyst capabilities gitter https badges gitter im curiosityai catalyst svg https gitter im curiosityai catalyst utm source badge utm medium badge utm campaign pr badge utm content badge join our gitter channel contribute https github com curiosity ai catalyst blob master contributing md samples https github com curiosity ai catalyst tree master samples | nlp natural-language-processing artificial-intelligence embeddings csharp machine-learning natural-language-understanding ai | ai |
string2string | p align center img src https github com stanfordnlp string2string blob main fables string2string overview png class center p string2string pypi python version https img shields io pypi pyversions string2string https badge fury io py string2string pypi version https badge fury io py string2string svg https badge fury io py string2string downloads https pepy tech badge string2string https pepy tech project string2string license https img shields io github license stanfordnlp string2string svg https github com stanfordnlp string2string blob main license txt arxiv https img shields io badge arxiv 2304 14395 b31b1b svg https arxiv org abs 2304 14395 table of contents getting started getting started tutorials tutorials example usage example usage documentation https string2string readthedocs io en latest tests https github com stanfordnlp string2string tree main tests citation citation thanks thanks contributing contributing abstract the string2string library is an open source tool that offers a comprehensive suite of efficient algorithms for a broad range of string to string problems it includes both traditional algorithmic solutions and recent advanced neural approaches to address various problems in pairwise string alignment distance measurement lexical and semantic search and similarity analysis additionally the library provides several helpful visualization tools and metrics to facilitate the interpretation and analysis of these methods the library features notable algorithms such as the smith waterman algorithm https en wikipedia org wiki smith e2 80 93waterman algorithm for pairwise local alignment the hirschberg algorithm https en wikipedia org wiki hirschberg 27s algorithm for global alignment the wagner fisher algorithm https en wikipedia org wiki wagner e2 80 93fischer algorithm for edit distance https en wikipedia org wiki edit distance bartscore https github com neulab bartscore and bertscore https github com tiiiger bert score for similarity analysis the knuth morris pratt https en wikipedia org wiki knuth e2 80 93morris e2 80 93pratt algorithm algorithm for lexical search and faiss https github com facebookresearch faiss for semantic search https en wikipedia org wiki semantic search moreover it wraps existing highly efficient and widely used implementations of certain frameworks and metrics such as sacrebleu https github com mjpost sacrebleu and rouge https github com google research google research tree master rouge whenever it is appropriate and suitable in general the string2string https string2string readthedocs io en latest library seeks to provide extensive coverage and increased flexibility compared to existing libraries for strings it can be used for many downstream applications tasks and problems in natural language processing bioinformatics and computational social sciences with its comprehensive suite of algorithms visualization tools and metrics the string2string library is a valuable resource for researchers and practitioners in various fields getting started install the string2string library by running the following command in your terminal bash pip install string2string once the installation is complete you can import the library and start using its functionalities remark we recommend using python 3 7 for the library tutorials open in colab https colab research google com assets colab badge svg def1 tutorial alignment tasks and algorithms def1 open in colab https colab research google com assets colab badge svg def2 tutorial distance tasks and algorithms def2 open in colab https colab research google com assets colab badge svg def3 tutorial search tasks and algorithms def3 open in colab https colab research google com assets colab badge svg def4 tutorial similarity tasks and algorithms def4 open in colab https colab research google com assets colab badge svg def5 hands on tutorial semantic search and visualization of uspto patents def5 open in colab https colab research google com assets colab badge svg def6 hands on tutorial plagiarism detection of essays def6 example usage alignment in the following example we illustrate how to align two sequences of strings globally by using the needleman wunsch algorithm https en wikipedia org wiki needleman e2 80 93wunsch algorithm this algorithm along with other alignment techniques can be found in the alignment module of the library the code snippet below demonstrates how to apply the needleman wunsch algorithm to perform a global alignment of two given strings this example provides a practical illustration of how to use the needleman wunsch algorithm to solve the problem of sequence alignment which is a fundamental problem in bioinformatics python import the needlemanwunsch class from the alignment module from string2string alignment import needlemanwunsch create an instance of the needlemanwunsch class nw needlemanwunsch let s create a list of strings resembling dna sequences but they can be any strings e g words of course seq1 x att gc gc a a g seq2 att g gc gc a c g compute the alignment between two strings aligned seq1 aligned seq2 nw get alignment seq1 seq2 print the alignment between the sequences as computed by the needleman wunsch algorithm nw print alignment aligned seq1 aligned seq2 x att gc gc a a g att g gc gc a c g alg path alg seq1 parts alg seq2 parts nw get alignment strings and indices aligned seq1 aligned seq2 from string2string misc plotting functions import plot pairwise alignment plot pairwise alignment seq1 pieces alg seq1 parts seq2 pieces alg seq2 parts alignment alg path str2colordict lightgray att indianred gc darkseagreen a skyblue g palevioletred c steelblue title global alignment between two sequences of strings p align center img src https github com stanfordnlp string2string blob main fables alignment example png class center p distance the following code snippet demonstrates how to use the levenshtein edit distance algorithm https en wikipedia org wiki levenshtein distance to compute the edit distance between two strings at the character level and at the word level python let s create a levenshtein edit distance class instance with the default unit cost weights from the distance module from string2string distance import levenshteineditdistance edit dist levenshteineditdistance let s also create a tokenizer class instance with the default word delimiter i e space from string2string misc import tokenizer tokenizer tokenizer word delimiter let s create two strings text1 the quick brown fox jumps over the lazy dog text2 the kuack brown box jumps over the lazy dog get the edit distance between them at the character level edit dist score edit dist compute text1 text2 print f edit distance between these two texts at the character level is edit dist score edit distance between these two texts at the character level is 3 0 tokenize the two texts text1 tokens tokenizer tokenize text1 text2 tokens tokenizer tokenize text2 get the distance between them at the word level edit dist score edit dist compute text1 tokens text2 tokens print f edit distance between these two texts at the word level is edit dist score edit distance between these two texts at the word level is 2 0 search the following code snippet demonstrates how to use the knuth morrs pratt kmp search algorithm https en wikipedia org wiki knuth e2 80 93morris e2 80 93pratt algorithm to find the index of a pattern in a text python let s create a kmpsearch class instance from the search module from string2string search import kmpsearch knuth morris pratt kmpsearch let s define a pattern and a text pattern jane austen text sense and sensibility pride and prejudice emma mansfield park northanger abbey persuasion and lady susan were written by jane austen and are important works of english literature now let s find the index of the pattern in the text if it exists otherwise 1 is returned idx knuth morris pratt search pattern pattern text text print f the index of the pattern in the text is idx the index of the pattern in the text is 127 faiss semantic search the example below demonstrates how to use the faiss https github com facebookresearch faiss tool developed by fair to perform semantic search first we use the bart large model from hugging face https huggingface co facebook bart large to generate embeddings for a small corpus of 25 sentences to perform the search we first encode a query sentence using the same bart model and use it to search the corpus specifically we search for sentences that are most similar in meaning to the query sentence after performing the search we print the top thre sentences from the corpus that are most similar to the query sentence this approach can be useful in a variety of natural processing applications such as question answering and information retrieval where it is essential to find relevant information quickly and accurately python let s create a faisssearch class instance from the search module to perform semantic search from string2string search import faisssearch faiss search faisssearch model name or path facebook bart large let s create a corpus of strings e g sentences corpus text coffee is my go to drink in the morning i always try to make time for exercise learning something new every day keeps me motivated the sunsets in my hometown are breathtaking i am grateful for the support of my friends and family the book i m reading is incredibly captivating i love listening to music while i work i m excited to try the new restaurant in town taking a walk in nature always clears my mind i believe that kindness is the most important trait it s important to take breaks throughout the day i m looking forward to the weekend reading before bed helps me relax i try to stay positive even in difficult situations cooking is one of my favorite hobbies i m grateful for the opportunity to learn and grow every day i love traveling and experiencing new cultures i m proud of the progress i ve made so far a good night s sleep is essential for my well being spending time with loved ones always brings me joy i m grateful for the beauty of nature around me i try to live in the present moment and appreciate what i have i believe that honesty is always the best policy i enjoy challenging myself and pushing my limits i m excited to see what the future holds next we need to initialize and encode the corpus faiss search initialize corpus corpus corpus section text embedding type mean pooling let s define a query and the number of top results we want to retrieve then let s perform the semantic search query i like going for a run in the morning top k 5 top k results faiss search search query query k top k let s define a function to print the results of the search def print results query results top k let s first print the query print f query query n let s now print the top k results print f top top k most similar sentences in the corpus to the query smallest score is most similar for i in range top k print f i 1 results text i with a similarity score of top k results score i 2f print results query query results top k results top k top k query i like going for a run in the morning top 3 most similar sentences in the corpus to the query smallest score is most similar 1 i always try to make time for exercise with a similarity score of 170 65 2 the sunsets in my hometown are breathtaking with a similarity score of 238 20 3 coffee is my go to drink in the morning with a similarity score of 238 85 cosine similarity with glove and fasttext embeddings the following example demonstrates how to use pre trained glove embeddings https nlp stanford edu projects glove to calculate the cosine similarity between different pairs of words specifically we compute the cosine similarity between the embeddings of four words cat dog phone and computer we then create a similarity matrix and use the plot heatmap function in the visualization module to plot this matrix overall this example provides a practical demonstration of how to use pre trained embeddings such as glove https nlp stanford edu projects glove and fasttext https fasttext cc to quantify the semantic similarity between pairs of words which can be useful in a variety of natural language processing tasks python let s create a cosine similarity class instance from the similarity module from string2string similarity import cosinesimilarity cosine similarity cosinesimilarity let s also create an instance of the gloveembeddings class from the misc module to compute the embeddings of words from string2string misc import gloveembeddings glove gloveembeddings model glove 6b 200d dim 50 force download true dir models glove model let s define a list of words words cat dog phone computer let s create a list to store the embeddings of the words and compute them embeds for word in words embedding glove get embedding word embeds append embedding let s create a similarity matrix to store the cosine similarity between each pair of embeddings similarity matrix np zeros len words len words for i in range len embeds similarity matrix i i 1 for j in range i 1 len embeds result cosine similarity compute embeds i embeds j dim 1 item similarity matrix i j result similarity matrix j i result let s visualize the similarity matrix from string2string misc plotting functions import plot heatmap plot heatmap similarity matrix title similarity between glove embeddings x ticks words y ticks words x label words y label words valfmt x 2f cmap blues p align center img src https github com stanfordnlp string2string blob main fables similarity example png class center p metrics sacrebleu and rouge in the code snippet below you can see an example of how to employ the sacrebleu metric for calculating the bleu score this metric is implemented as a wrapper around the sacrebleu library https github com mjpost sacrebleu the computation is performed by providing a list of candidate sentences and a list of reference sentences as input and calling the compute method of the metric instance python let s import the sacrebleu metric from the metrics module and create an instance of it from string2string metrics import sacrebleu sbleu sacrebleu let s define a list of candidate sentences and a list of reference sentences candidates the sun is shining the birds are chirping she is playing the guitar he is cooking dinner references the sun is shining the sun is bright the birds are singing the harold is singing julie is playing the flute she is playing the piano chef is cooking dinner he is cooking lunch compute the sacrebleu score result sbleu compute candidates references print result score 67 92604743211312 counts 19 13 9 4 totals 21 17 13 9 precisions 90 47619047619048 76 47058823529412 69 23076923076923 44 44444444444444 bp 1 0 sys len 21 ref len 21 similarly we can use the rouge metric to calculate the rouge score this metric is implemented as a wrapper around the rouge library https github com google research google research tree master rouge python let s import the rouge metric from the metrics module and create an instance of it from string2string metrics import rouge rogue rouge let s define a list of candidate sentences and a list of reference sentences candidates the cat is sitting on the mat the dog is barking at the mailman the bird is singing in the tree references the cat is sitting on the mat the dog is barking at the postman the bird sings on the tree compute the rouge score result rogue compute candidates references print result rouge1 0 8241758241758242 rouge2 0 7323232323232324 rougel 0 8241758241758242 rougelsum 0 8241758241758242 bartscore and bertscore this code snippet shows how to utilize the bartscore and bertscore metrics to compute their corresponding scores these similarity metrics serve as wrappers around the bartscore and bertscore libraries python importing the bertscore and bartscore classes from the similarity module from string2string similarity import bertscore bartscore initializing the bartscore metric bart scorer bartscore model name or path facebook bart large cnn initializing the bertscore metric bert scorer bertscore lang en define the source and target sentences source sentences i m super happy today john von neumann was a mathematician and physicist target sentences i feel pretty wonderful today kurt vonnegut s slaughterhouse five had a profound impact on many people compute the bartscore score bart scorer compute source sentences target sentences agg mean batch size 4 print score score array 2 77911878 4 60774326 compute the bertscore score bert scorer compute source sentences target sentences print score precision array 0 943804 0 8559195 dtype float32 recall array 0 943804 0 85145634 dtype float32 f1 array 0 943804 0 8536821 dtype float32 potential future enhancements and improvements use the numba library https numba pydata org to accelerate the execution time of the algorithms include additional string based metrics in the miscellaneous module implement blast https blast ncbi nlm nih gov blast cgi and fasta https www ebi ac uk tools sss fasta algorithms work in progress add more customizable and useful visualization features citation bibtex article suzgun2023string2string title string2string a modern python library for string to string algorithms author suzgun mirac and shieber stuart m and jurafsky dan journal arxiv preprint arxiv 2304 14395 year 2023 thanks our project owes a debt of gratitude to the following individuals for their contributions comments and feedback federico bianchi corinna coupette sebastian gehrmann tayfun g r ule kahraman deniz kele luke melas kyriazi christopher manning tol lop g nr m alexander sasha rush kyle swanson and garrett tanzer contributing if you are interested in contributing to this library we encourage you to review our documentation https string2string readthedocs io en latest first to gain a better understanding of the codebase s format and structure once you are familiar with the codebase you are welcome to submit a pull request we are looking for new contributors to help us drive our efforts forward def1 https colab research google com drive 11dkisbukddmazwp tnx 64z7sn0uqd9c usp sharing def2 https colab research google com drive 1e8iwbka7q4xpmhtxst8 xa apx4vsb4j usp sharing def3 https colab research google com drive 1wu joyivxn 52sref2ukyy7xi4ufvuax usp sharing def4 https colab research google com drive 1qndikvcemovw4wysmzqbvrnazz4 zort usp sharing def5 https colab research google com drive 1lpxnqn2dsujb 0iq x3h jx 6 lagpnk usp sharing def6 https colab research google com drive 1tsmt3desgy4bnkk zrdal70crtqrqatb usp sharing | ai |
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video support developer api https docs invidious io api does not use official youtube apis no contributor license agreement cla quick start using invidious select a public instance from the list https instances invidious io and start watching videos right now hosting invidious follow the installation instructions https docs invidious io installation documentation the full documentation can be accessed online at https docs invidious io the documentation s source code is available in this repository https github com iv org documentation extensions we highly recommend the use of privacy redirect https github com simonbrazell privacy redirect get a browser extension that automatically redirects youtube urls to any invidious instance and replaces embedded youtube videos on other websites with invidious the documentation contains a list of browser extensions that we recommended to use along with invidious you can read more here https docs invidious io applications contribute code 1 fork it https github com iv org invidious fork 1 create your feature branch git checkout b my new feature 1 stage your files git add 1 commit your changes git commit am add some feature 1 push to the branch git push origin my new feature 1 create a new pull request https github com iv org invidious compare translations we use weblate https weblate org to manage invidious translations you can suggest new translations and or correction here https hosted weblate org engage invidious creating an account is not required but recommended especially if you want to contribute regularly weblate also allows you to log in with major sso providers like github gitlab bitbucket google projects using invidious freetube https github com freetubeapp freetube a libre software youtube app for privacy cloudtube https sr ht cadence tube a javascript rich alternate youtube player peertubeify https gitlab com cha de l peertubeify on youtube displays a link to the same video on peertube if it exists musicpiped https github com deep gaurav musicpiped a material design music player that streams music from youtube holoplay https github com stephane r holoplay pwa progressive web app connecting on invidious api s with search playlists and favorites watchtube https github com watchtubeteam watchtube powerful youtube client for apple watch yattee https github com yattee yattee alternative youtube frontend for iphone ipad mac and apple tv tubitui https codeberg org 777 tubitui a lightweight libre tui based youtube client ytfzf https github com pystardust ytfzf a posix script to find and watch youtube videos from the terminal without api playlet https github com ibicha playlet unofficial youtube client for roku tv clipious https github com lamarios clipious unofficial invidious client for android liability we take no responsibility for the use of our tool or external instances provided by third parties we strongly recommend you abide by the valid official regulations in your country furthermore we refuse 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dubbo-js | apache dubbo for ecmascript license https img shields io github license alibaba dubbo svg build https github com apache dubbo js blob dubbo3 github workflows node js yml badge svg https github com apache dubbo js blob dubbo3 github workflows node js yml apache dubbo is an easy to use web and rpc framework that provides different language implementations java https github com apache dubbo go https github com apache dubbo go rust https github com apache dubbo rust node js javascript for communication service discovery traffic management observability security tools and best practices for building enterprise ready microservices dubbo js is the typescript implementation of dubbo triple protocol a fully grpc compatible and http friendly protocol https dubbo apache org zh cn overview reference protocols triple spec which can be used for node js and web application development with dubbo js you can easily build applications working on browser and frontend that can communicate with backend services through http based protocol arc docs imgs arc png node js documentation https github com apache dubbo js blob dubbo3 example dubbo node example web documentation https github com apache dubbo js blob dubbo3 example dubbo web example get started the following two demos will guide you on how to create node js backend and web applications using dubbo js you can call backend dubbo services with type safe apis typescript const resp await client say sentence hello dubbo console log resp or you can curl them if you want shell curl header content type application json data sentence hello world http localhost 8080 apache dubbo demo example v1 exampleservice say get started on the web follow this guide to learn how to develop web applications that can access backend dubbo services and running on browser we support all modern web browsers that implement the widely available fetch api and the encoding api get started on node js follow this guide example dubbo node example here to learn how to develop and spin up a backend dubbo service in node js and call it from curl the web browser or a dubbo client in your terminal in addition dubbo integrates middlewares such as express fastify and next making it easier for users to build a dubbo distributed service framework using node js service governance features besides rpc protocol we plan to provide dubbo js rich service governance features so it can work seamlessly with other microservice architecture the features lsited below are still under development we will update each feature s status once ready construction service discovery nacos zookeeper kubernetes etc construction load balance random roundrobin leastactive consistenthash etc construction traffic routing traffic split circuit breaking canary release etc construction filter token accesslog rate limiting etc construction metrics prometheus construction tracing jaeger zipkin how to contribute please check contributing contributing md for how to contribute to this project connect us search dingding group number and join us 27690019068 credit this project is based on bufbuild connect es https github com bufbuild connect es an open source project released under apache license v2 comparing to connect es dubbo js removed the unused grpc web and connect protocol added support for dubbo protocol no idl programming api and many service governance features we have a announcement in our license file and keep all license headers of files come from connect es unchanged | http2 javascript microservices nodejs rpc service-mesh http typescript web | front_end |
CV-WINTER-CAMP-2020 | header docs header png lectures practices readme practices practices md docs microsoft visual studio https login microsoftonline com c vk com video 2139021 456239048 https vk com video 2139021 456239048 c optimization docs cpp optimization lecture img jpg https vk com video 2139021 456239048 vk com video 2139021 456239049 https vk com video 2139021 456239049 c optimization docs math libraries lecture img jpg https vk com video 2139021 456239049 opencv vk com video 2139021 456239050 https vk com video 2139021 456239050 c optimization docs opencv optimizations img jpg https vk com video 2139021 456239050 gitter https badges gitter im cv summer camp community svg https gitter im cv summer camp community utm source badge utm medium badge utm campaign pr badge https gitter im cv summer camp community https gitter im cv summer camp community | ai |
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mobile-apps-spring-2023 | welcome to mobile app development spring 2023 we will host all the code provided during the lectures and videos in this repository this course focuses on android development using java week 1 introduction to java week 2 introduction to android ui and event handling week 3 managing activities week 4 fragments week 5 managing scrollable lists weeks 6 and 7 making http connections and json parsing week 8 xml parsing week 9 midterm exam weeks 10 11 and 12 firebase and data storage week 13 local data storage week 14 google maps api week 15 location services week 16 google apis week 17 final exam | front_end |
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go-sero | go sero the sero system is the world s first blockchain platform to support con dential transactions based on zero knowledge proof and supports turing complete smart contracts what s sero https wiki sero cash en index html file home home from source code base on centos7 https wiki sero cash en index html file start from the sourcecode base on centos7 how to mine using gero https wiki sero cash en index html file start from the binary package now you don t need license anymore to mine sero how to use snapshots https wiki sero cash en index html file start sero chain snapshot list how to start sero staking on gero https wiki sero cash en index html file tutorial how to staking using gero decentralized light wallet pc https github com sero cash pullup mobile https sero cash app popup html pow pool list https wiki sero cash en index html file start sero pool list pos stake node list https wiki sero cash en index html file start stake node list contribution thank you for considering to help out with the source code we welcome contributions from anyone on the internet and are grateful for even the smallest of fixes if you d like to contribute to go sero please fork fix commit and send a pull request for the maintainers to review and merge into the main code base please make sure your contributions adhere to our coding guidelines code must adhere to the official go formatting https golang org doc effective go html formatting guidelines i e uses gofmt https golang org cmd gofmt code must be documented adhering to the official go commentary https golang org doc effective go html commentary guidelines pull requests need to be based on and opened against the master branch commit messages should be prefixed with the package s they modify e g sero rpc make trace configs optional please see the developers guide https github com sero cash go sero wiki developers guide for more details on configuring your environment managing project dependencies and testing procedures community resources wechat sero9413 discord https discord gg n5hvxe twitter https twitter com serodotcash telegram https t me seroofficial gitter https gitter im sero cash lobby utm source share link utm medium link utm campaign share link other resources official website https sero cash white paper http sero media s3 website ap southeast 1 amazonaws com sero eng v1 06 pdf wiki https wiki sero cash zh index html file home home block explorer https explorer web sero cash blocks html introduction video https v qq com x page s0792e921ok html license the go sero library i e all code outside of the cmd directory is licensed under the gnu lesser general public license v3 0 https www gnu org licenses lgpl 3 0 en html also included in our repository in the copying lesser file the go sero binaries i e all code inside of the cmd directory is licensed under the gnu general public license v3 0 https www gnu org licenses gpl 3 0 en html also included in our repository in the copying file note go sero inherit with licenses of ethereum | blockchain sero gero nizk go privacy zpk smart-contract | blockchain |
codespace-auth-22 | codespace auth 22 an auth system totally designed in github codespace | os |
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todo-demo-backend | todo app demo backend prerequisites node 12 yarn 1 22 x install yarn install run yarn start | todo express nodejs javascript | server |
Bus-reservation-System | img src https gst contracts s3 amazonaws com uploads bcc cms asset avatar 116426 banner banner psd jpg h1 style text align center ak bus reservation system h1 br bus ticket reservation system the bus reservation system is designed to automate online ticket purchasing through an easy to use online bus booking system embed our online bus ticketing system into your website and enable your customers to book tickets for various routes and destinations with the bus ticket reservation system you can manage reservations client data and passenger lists you can also schedule routes set seat availability etc br br h2 tech stacks used h2 br css br javascript br java br servlet br tomcat br jsp br br h2 administrators h2 br admin br user br br h2 functionality for users h2 br login br signup br see bookedtickets br cancel booked tickets br book and search tickets br br h2 functionality for admin h2 br login br add buses br delete buses br see all buses details br br h2 tables h2 br users br bookingrec br buses br h2 getting started h2 prerequisites to run this project you will need java development kit jdk 8 or later mysql server h2 installation h2 br clone the repository git clone https github com ayaz 01 aquatic beef 7375 git set up the mysql database using the mysql sql file included in the repository mysql u root p cims project101db sql update the database properties file with your mysql credentials compile the project javac java run the project java main usage the system is menu driven and user friendly simply follow the prompts to navigate the different options and perform various operations br h2 er diagram h2 img src https raw githubusercontent com ayaz 01 aquatic beef 7375 main screenshot 202023 04 06 20201150 png | css html javascript jdbc jsp mysql servlet | os |
hbui | hbui https repository images githubusercontent com 440312044 5e644c3a c7d5 49fc acc2 4076c6c8ba7f hbui the hummingbot design system this repository holds the source code and documentation of the hbui hummingbot design system https hummingbot ui netlify com visit the documentation site https hummingbot ui netlify com the flow the original design of this design system lives in a figma document https www figma com file hf03mn2cecwa1iouxlhg9p hummingbot design system 1 3 this package contains a custom script that extracts the design tokens from the figma document colors fonts spacings breakpoints shadows and saves them in a hbui tokens js file which is then used to create a custom tailwindcss https tailwindcss com configuration this project also uses twin macro https github com ben rogerson twin macro to make use of tailwindcss in a react friendly manner finally this project exports an npm module https www npmjs com package hummingbot hbui that is in turn consumed by other projects use or try out the hbui hummingbot design system to use the hbui design system all you need is the hbui npm module https www npmjs com package hummingbot hbui but we recommend you start from one of the hbui boilerplate projects below where everything is already set up for you we have four types of boilerplate projects available next js https github com hummingbot hbui boilerplate nextjs gatsby https github com hummingbot hbui boilerplate gatsby webpack https github com hummingbot hbui boilerplate webpack webpack typescript https github com hummingbot hbui boilerplate webpack ts these are ready to run apps with everything already configured and ready to go instructions to run this project if you wish to run the hbui documentation locally simply clone and run this project bash clone the project git clone git github com coinalpha hbui git hbui cd into the folder cd hbui install the dependencies yarn start up yarn develop the project will run on http localhost 8000 alternatively run this command to enable opening the site in the local network eg in your phone bash yarn develop m instructions to perform updates to the npm module to perform updates to the npm module a local script connects to the figma api v1 and downloads the updated design tokens into the file hbui tokens js to set up it is necessary to create an env file with the figma file id and a figma api access token these are the steps 1 5 first make sure the app is running without errors 2 5 get a figma api access token 3 5 create a file called env at the root of the project with the following content replace figma api access token with your own shell figma api token your access token figma file id hf03mn2cecwa1iouxlhg9p the figma file id in the code above is our original figma file for the hbui design system if you are trying this outside hummingbot and you want to create your own npm module you should make a copy of our figma file to get started grab the file id from your copy and replace the figma file id in the code above you will also have to change the module name author etc in the file npm module package json in order to publish your own npm module 4 5 you need to be logged into npm as a user with authorization to make updates to the hummingbot space or your own space if you re building your own npm module shell npm login 5 5 if all the above is done you are ready to make updates there are three types of updates available shell patch update npm run publish patch minor update npm run publish minor major update npm run publish major alternatively use the following script variant to automatically git commits the changes with a commit message that includes the new version number update npm module to x x x remember to push the changes to the appropriate branch pr shell patch update npm run publish patch and commit minor update npm run publish minor and commit major update npm run publish major and commit to simply update the design tokens if you just want to test the latest design tokens setup an env file like explained above pull the tokens and test the app shell pull the tokens yarn pull tokens test the app yarn develop relevant links to this project hbui hummingbot design system https hummingbot ui netlify com documentation hbui npm module https www npmjs com package hummingbot hbui next js https github com hummingbot hbui boilerplate nextjs hbui boilerplate gatsby https github com hummingbot hbui boilerplate gatsby hbui boilerplate webpack https github com hummingbot hbui boilerplate webpack hbui boilerplate webpack typescript https github com hummingbot hbui boilerplate webpack ts hbui boilerplate useful references next js documentation https nextjs org docs gatsby documentation https www gatsbyjs com docs tailwindcss documentation https tailwindcss com docs tailwindcss for react twin macro https github com ben rogerson twin macro todo make the build script compatible with windows | design system hummimgbot | os |
XBMC-Emustation | xbmc emustation front end for some emulators using xbmc this is a pet project of mine and its a combination of a skin python scripts and source edits to xbmc so don t expect something spectacular i wanted something that looked like emulationstation on the xbox and the only way to do that was to make a skin for xbmc and use it s built in feature to launch cut files but it wasn t that simple i wanted menu loading instant and there was no simple way to do that with over 700 roms or a few hundred games so i modified the xbmc source to bypass the folder check for xbe files this worked for games but not roms so again had to think outside of the box and came up with a workaround i create static menus when you scan your roms there are also a few other scripts i made to do other tasks but hopefully you like what i have made and get some use out of it contributions if you d like to say thanks by sending a small donation it d be a huge help and it ll allow me to keep spending time towards contributing to the xbox community in the future paypal https www paypalobjects com en us i btn btn donatecc lg gif https www paypal com cgi bin webscr cmd donations business 65njwu9puux7w lc gb currency code gbp bn pp 2ddonationsbf 3abtn donate lg 2egif 3anonhosted installation download prebuilt versions download xbmc emustation https drive google com open id 1timqzv2wjjrtf68brvy5rkubnq1thcs4 details summary build from source note this is only for advanced users summary download xbmc emustation https github com rocky5 xbmc emustation archive master zip and extract the xbmc emustation master folder to your desktop download the latest xbmc4xbox zip https drive google com drive folders 0b9znhncnuddtrvfbbhcwc2jczfe and extract the xbmc folder that is inside the zip to your desktop xbmc emustation master folder now double click the build xbmc emustation bat that s inside the xbmc emustation master folder and wait it will output a new folder named xbmc emustation ftp this new folder to your xbox and enjoy details roms and emulators you place your roms in the designated subdirectory in the emustation roms folder same exact thing for the emulators but in the emustation emulators folder note these paths can be customized in the other settings menu scanning roms press start on the main screen other settings auto scan roms press start on the main screen other settings update selected systems manual mode updating emulator list press start on the main screen other settings refresh emulator list note this is automatically done if any of the scan roms files options are run custom emulators media and roms paths press start on the main screen other settings scroll down note if you change any of these a rescan of your roms is required customize home press start on the main screen ui settings home screen customization downloader located in the options menu at the bottom this will allow you to download application homebrew dlc and many more things updated xbmc emustation to the latest version head to options downloader updates install xbmc emustation update files everything else the rest should be self explanatory its all in the menu acknowledgements buzz for maintaining xbmc4xbox over the years emulationstation folk for es theme simple github es theme simple https github com retropie es theme simple es theme carbon github es theme carbon https github com retropie es theme carbon i created a few new images to add to these great svg images tmntturtleguy for the awesome theme comicbook for emulationstation github es theme comicbook https github com tmntturtleguy es theme comicbook madmab for the emulators on the xbox madmab emulators http www emuxtras net dlsystem emuxtras website http www emuxtras net voidsentinel for the 3 cartridge images i used for the favourites logo deviantart https voidsentinel deviantart com gallery 43806141 video game icons grimdoomer thefallen93 for telling me how dlc is hashed on the xbox testers feedback and suggestions mikeaton jay yardley randyslim76 smithis also to anyone else i may have forgot note all other themes were recreated from scratch for the xbox all assets were make from scratch | front_end |
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ComputerVisionReadingList | computervisionreadinglist my reading list for topics in computer vision this list is divided into two main sections viz geometry based methods in vision and learning based methods in vision research papers sfm 1 multi stage sfm a coarse to fine approach for 3d reconstruction http arxiv org pdf 1512 06235 pdf 2 metrics for 3d rotation comparison and analysis http www cs cmu edu cga dynopt readings rmetric pdf 3 analyzing 3d objects in cluttered images nrsfm applied on cars https papers nips cc paper 4680 analyzing 3d objects in cluttered images pdf 4 nrsfm tutorial http users isr ist utl pt adb tutorial 2009 2011 iccv non rigid structure from motion lourdes pdf 5 shape and motion from image streams under orthography a factorization method seminal work on factorization based approaches for structure recovery https people eecs berkeley edu yang courses cs294 6 papers tomasic shape 20and 20motion 20from 20image 20streams 20under 20orthography pdf 6 recovering non rigid 3d shape from image streams seminal work on representing non rigid structure as a combination of basis http cims nyu edu bregler bhb cvpr00 pdf geometry based methods in vision course materials 1 mathematical foundations of graphics and vision good resources on the geometry of so 3 and on variational methods http lucaballan altervista org teaching html learning based methods in vision review notes 1 review lectures before you take a grad course in ml https www youtube com channel uc7goydyegxg1yih rc2lgow playlists books 1 computer vision models learning and inference http web4 cs ucl ac uk staff s prince book book pdf 2 computer vision models learning and inference algorithms booklet http www0 cs ucl ac uk external s prince book algorithms pdf 3 computer vision models learning and inference answers booklet for students http www0 cs ucl ac uk external s prince book answerbookletstudents pdf lecture notes gaussian mixture models and em 1 robert collin s lectures a gaussian mixtures and the em algorithm http www cse psu edu rtc12 cse586 lectures emlecturefeb3 pdf b em clarification http www cse psu edu rtc12 cse586 lectures emclarifypxz pdf c em derivation proof that em works http www cse psu edu rtc12 cse586 lectures cse586emderivation pdf d gmm and k means http www cse psu edu rtc12 cse586 lectures cse586gmmempart1 pdf e gmm and em intro http www cse psu edu rtc12 cse586 lectures cse586gmmempart2 pdf f mixture of gaussians lecture http www cse psu edu rtc12 cse586 lectures lecturemixgauintro pdf 2 mixture of gaussians tutorial reynolds http www ee iisc ernet in new people faculty prasantg downloads gmm tutorial reynolds pdf 3 mixture models and the em algorithm c bishop http mlg eng cam ac uk tutorials 06 cb pdf 4 estimating gaussian mixture densities with em a tutorial tomasi http www cse psu edu rtc12 cse586 papers emtomasitutorial pdf 5 a short tutorial on gmms http www computerrobotvision org 2010 tutorial day gmm said crv10 tutorial pdf 6 a gentle tutorial of the em algorithm and its application to parameter estimation for gmms and hmms http lasa epfl ch teaching lectures ml phd notes gp gmm pdf 7 tutorial on mixture models http www homepages ucl ac uk ucakche presentations cladagtutorial pdf 8 mixture models and em http www cs toronto edu kyros courses 2503 handouts mixturemodel pdf 9 mixture of gaussians tutorial https www spsc tugraz at system files mixtgaussian pdf 10 an introduction to mixture models frank picard http www informatica uniroma2 it upload 2009 im mixture tutorial pdf 11 mixture models http www stat cmu edu cshalizi uada 12 lectures ch20 pdf 12 a unifying review of linear gaussian models http mlg eng cam ac uk zoubin papers lds pdf introduction to graphical models 1 robert collin s lectures a introduction to graphical models belief propagation http www cse psu edu rtc12 cse586 lectures cse586gmplusmp pdf | ai |
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cryptometa | cryptometa public repository used by viewblock to display token information and compute score how to use in your app thanks to our auto updated cdn you can add any chain and token icons in your app seamlessly using the following url https meta viewblock io key logo the key accepts different formats chainsymbol chainname chainsymbol tokenhash for example img src https meta viewblock io btc logo img src https meta viewblock io zilliqa logo img src https meta viewblock io ar usjm4pcxud5mtaon7zc97 dt 3qf67ypyqgzlnlqk5a logo the cdn will automatically route to the right icon svg if existing or png fallback another cool thing is our dark support let s say you have a dark theme we have some icons specially made for this case you simply need to add the t dark query parameter img src https meta viewblock io ar usjm4pcxud5mtaon7zc97 dt 3qf67ypyqgzlnlqk5a logo t dark if the image has a dark alternative that s what you will get otherwise it will fallback to the default one specification param type required points notes name string true description string false a brief description of the project symbol string true web string false 5 websites should use https decimals number false supply number false email string false email of the team whitepaper string false 10 whitepaper not 3 paragraphs you put in a pdf just for that purpose holders bool false 10 only specify if more than 1000 holders without airdrops publicteam bool false 20 teams members with public verifiable profiles with history preferably more than 1 one linkedin product bool false 30 usable product on mainnet with decent activity users clear token utility token activity links research string false 10 either binance research tokendata or the like links github string false 10 org or account with repos related to the project not an empty one with just the cryptometa fork for example links linkedin string false 10 should have 1 or 2 members public on the page links twitter string false 5 links coinmarketcap string false links coingecko string false links medium string false links blog string false links telegram string false links discord string false links facebook string false links reddit string false links youtube string false links instagram string false donations object false ethereum 0x zilliqa zil1 upon disagreements as to which property a token has deserves remember that we ultimately have the final say in order to protect people as much as we can | cdn cryptocurrency ethereum arweave zilliqa thorchain thundercore | blockchain |
fitterbap | copyright 2014 2021 jetperch llc licensed under the apache license version 2 0 the license you may not use this file except in compliance with the license you may obtain a copy of the license at http www apache org licenses license 2 0 unless required by applicable law or agreed to in writing software distributed under the license is distributed on an as is basis without warranties or conditions of any kind either express or implied see the license for the specific language governing permissions and limitations under the license welcome windows https github com jetperch fitterbap actions workflows windows yml badge svg https github com jetperch fitterbap actions workflows windows yml welcome to fitterbap the fi rmware t oolkit t o e nable r eliable b est a rchitecture p ractices fitterbap provides common utilities useful for embedded systems that are often not included in an rtos or the standard c library fitterbap includes a distributed publish subscribe implementation for easy command control and configuration of your designs a high reliability data link protocol suitable for uarts common c macros including assert and design by contract host software and ui to accelerate firmware development and more this library is intended for use by software developers producing firmware for embedded devices based upon microcontrollers many features of the library use malloc but it avoids using free the fitterbap library is available under the permissive apache 2 0 license as of june 2021 the fitterbap library api is not yet stable and subject to change without notice getting started the easiest way to get started is to check out the fitterbap example stm32g4 https github com jetperch fitterbap example stm32g4 if you want to try distributed pubsub and the comm stack you can buy the stmicroelectronics nucleo g491re https www st com en evaluation tools nucleo g491re html development board when you first connect the nucleo board over usb it shows up as a mass storage device you can simply copy over the release binaries and start the host ui which looks like this fitterbap host comm ui doc host comm ui png known limitations pubsub hard coded maximum topic lengths no validation using provided topic metadata host win 10x64 only no macos or linux yet fbp fatal not properly implemented for pyfitterbap installation the fitterbap library uses cmake to generate the project make files for the c components since fitterbap is a library primarily targeted at embedded microcontrollers you will likely want to include compile it into your project projects using cmake can use externalproject add other build systems will likely need to include the source files directly consider using git subtrees or git submodules you will need to manually create the fitterbap config h and fitterbap platform h see include fitterbap config defaults h and include fitterbap platform dependencies h for details host python install 64 bit python 3 8 or newer on your system confirm that it is correctly installed python3 vv on windows python 3 is usually installed as python rather than python3 then install the pyfitterbap package from pypi pip install u pyfitterbap you can then run the pyfitterbap communication ui tools using either python3 m pyfitterbap comm ui or fitterbap comm ui ubuntu first install the build tools for your system sudo apt get install build essential cmake doxygen graphviz git then compile the fitterbap library cd project directory mkdir build cd cmake cmake build ctest you can also build and test the python library python3 setup py build ext inplace python3 m unittest to run the host comm ui python3 m pyfitterbap comm ui licenses the fitterbap library is available under the permissive apache 2 0 license this library includes all third party dependencies in the third party directory the dependencies are built along with this project these third party libraries are provided under their own licenses third party readme md more information the fitterbap api is documented using doxygen for a history of changes see the changelog changelog md alternatives fitterbap is a broad library that implements several distinct features here are some other libraries that you can consider full system pigweed https pigweed dev mbeddr http mbeddr com piconomic fw library https github com piconomix piconomix fwlib communication protocols luos https www luos io telemetry https github com overdrivr telemetry min https github com min protocol min serialfiller https github com gbmhunter serialfiller lasp https lasp lang readme io totally different scale stream control transmission protocol sctp https tools ietf org html rfc4960 tinyframe https github com mightypork tinyframe pubsub pubsub c https github com jaracil pubsub c command control microrl https github com helius microrl command line random number generation https en wikipedia org wiki xorshift http www pcg random org small http excamera com sphinx article xorshift html string mpaland s printf https github com mpaland printf | os |
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design-system-questionnaire | design system questionnaire a one page questionnaire to help your organization establish effective design systems and style guides the sections are broken down into the broad process of creating a successful design system 1 sell 2 kickoff 3 plan 4 design and build 5 launch 6 maintain 1 sell problems and opportunities why do you want to create a design system what problems does the design system need to address in your organization what are the goals you want to accomplish in establishing a design system the benefits of design systems http atomicdesign bradfrost com chapter 1 style guide benefits are many but what specifically are the goals of your organization s design system initiative what will happen if this initiative fails people who needs convinced which departments or people in your organization need convinced that establishing a design system is a good idea who s doing the convincing who is involved at convincing stakeholders management securing funding etc 2 kickoff user research who are the users and stakeholders of the design system it s important to understand the needs of the people who will be affected by the design system conducting interviews with makers users and stakeholders helps the team better understand what the design system needs to be in order to be successful who will conduct user stakeholder interviews who will be interviewed it s important to interview a healthy cross section of product teams disciplines skill levels and perspectives in order to ensure the design system initiative properly serves the organization what are the broad themes uncovered by the interviews what pain do people experience and how can the design system aliviate that pain kickoff workshop the kickoff workshop is used to kick off the design system initiative and establish a broad consensus about what the design system is and who needs to be present at the kickoff workshop the kickoff meeting attendees should be stakeholders who will influence and or be influenced by the design system who should be present to ensure proper representation across products and disciplines what are the shared outcomes and priorities of the design system initiative this is the result of the kickoff session and interviews who is responsible for taking the outcomes of the kickoff workshop and translating them into a plan of attack 3 plan principles what design principles does your design system embrace design principles underpin every aspect of the design system and influence its construction they should jive with your organization s broader mission and culture and your design principles should be easily understood by everyone doing work with the design system here are some good resources about design principles styleguides io examples http styleguides io examples html many public style guides showcase their design principles design principles ftw http www designprinciplesftw com a big collection of design principles design principle roundup https principles adactio com by jeremy keith rounds up a ton of principles from a ton of different fields creating design principles https articles uie com creating design principles jared spool talks about the qualities of effective design principles shaping our design principles https medium com building creative market shaping our design principles 3474d6f5204b products what products will the design system serve list the products the design system will be applied to are there products that will not be served by the design system why what will those products use instead list the products that won t make use of the design system and discuss why they won t utilize the design system what are the design system s pilot projects design system pilot projects put the design system through its paces as it s being constructed which projects keep in mind that pilot projects should provide a healthy cross section of components patterns technologies processes and people read dan mall s design system pilots and scorecards http danmall me articles design systems pilots scorecards for criteria for choosing design system scorecards technology what platforms does the design system apply to web ios android windows etc what web technologies does the design system need to consider react angular drupal wordpress handlebars twig jade etc etc code guidelines what frontend guidelines does the design system follow frontend guidelines for more information check out frontend guidelines questionnaire https github com bradfrost frontend guidelines questionnaire that s similar in format to this questionnaire code language style guides which backend technologies are in use at your organization php ruby net are there style guides available to help the team write more cohesive code together design tools what design tools are in use at the organization the design system should be integrated with the tools teams use in their day to day work what design tools will be used to const methodology does your team use a methodology to organize components such as atomic design http atomicdesign bradfrost com chapter 2 the atomic design methodology 4 design build do it 5 launch what is the name of the design system a catchy and memorable name can help your design system gain traction the name of the design system should embody the spirit of the organization and the system s underlying design principles fair warning naming is hard where does the style guide live the style guide the container that houses the guts of the design system should live at an easy to access and easy to remember url i e designsystem yourcompany com is your style guide publicly accessible yes no maybe eventually making a style guide public has many benefits http atomicdesign bradfrost com chapter 5 make it public what tool http styleguides io tools html are you using to house your style guide what tech is your style guide built on what s its relationship to the style guide website to the components that make up your design system what does the design system include a design system is a collection of components guidelines documentation points of view processes and tools what ingredients should your organization s design system contain no doubt your organization s structure processes and tools will all influence the design system s ingredients i recommend checking out nathan curtis s picking parts people and products https medium com eightshapes llc picking parts products people a06721e81742 iy6eas2rw for a great exercise to help prioritize what the system should include let s take a look at some of the parts that your design system can include brand identity where are brand identity guidelines managed these include brand wide elements such as logo typography color tagline marketing guidelines etc what is the relationship between the overall brand identity and ui components there may be a tight relationship between the brand guidelines and ui i e buttons and logo are and must be the same color or there may be a loose relationship i e material design s guidelines and google s brand guidelines are quite different are you using any third party tools or services to manage brand assets some of these tools include brand ai http brand ai frontify https frontify com high level guidelines what are some high level guidelines you want to provide in the design system some examples may include accessibility animation data display data entry data validation multi device design layout navigation performance while these topics will manifest themselves in more concrete ways at the component level it s often a good idea to explicitly express the organization s point of view on these topics at a high level content do you have over arching content strategy guidelines in place do you follow writing guidelines what conventions should people writing on behalf of your organization follow check out dalhousie university s writing for the web https www dal ca webteam web style guide writing for the web html guide for a great example do you have voice and tone guidelines in place what qualities does your brand s embrace how does your brand s tone change based on audience context and environment the answers to these questions should be embodied in the voice and tone guidelines for inspiration check out mailchimp s voice and tone http voiceandtone com mailchimp s content style guide http styleguide mailchimp com voice and tone voice and tone guidelines on styleguides io http styleguides io examples html voiceandtone the most misunderstood part of a design system https medium com alanweibel the most misunderstood part of a design system fba520c1d292 b1gju74ny take a closer look at the patterns in our language https clearleft com posts 442 great article by clearleft about establishing voice and tone principles and applying them to a product microcopy how does the team write effective microcopy https uxplanet org microcopy tiny words with a huge ux impact 90140acc6e42 pxaae93xy together color what are the brand s colors neutral palette utility palette what are the color accessibility guidelines design a light dark color system https medium com eightshapes llc light dark 9f8ea42c9081 mn7exfyhf typography what is the typography system used in the design system icons and imagery how are icons served in your products icon fonts inline svg svg sprites pngs where are icons sourced in house or third party open source or proprietary what s the process for updating an icon in the system what tools are used to create and manage icons this includes graphics programs like illustrator and sketch but also icon management services like icomoon https icomoon io motion what are your guidelines for using motion and animation in your design system animation in your style guide http valhead com 2015 07 09 animation in your style guide ui components what ui components are included in the system form fields cards tabs and much more can be present in your organization s design system which ui components that conducting an interface inventory http bradfrost com blog post conducting an interface inventory can be a good way to determine which ui components should be codified in the design system page templates what page templates should be included in the design system are there common page templates your organization creates time and time again templates for portals dashboards homepages blog posts etc may be good to codify workflows if ui components are the tools in the toolshed then workflows are the common tasks you perform with those tools what workflows should be included in the design system things like sign up authentication e commerce checkout multi step form etc announcement how will the design system be announced how will people find out about the new design system 6 maintain people who are the primary design system makers http atomicdesign bradfrost com chapter 5 design system makers who is responsible for creating and maintaining the design system provide names and roles who are the primary users of the design system who are the people that will be primarily be implementing the system s components reading guidelines and referencing the information in the style guide who are the secondary users of the design system secondary users are people who may not rely on the system for their day to day work but may find the documentation and information in the style guide useful are there teams or people in the organization that won t use the design system why what do they do instead how is the design system team structured solitary centralized federated how the design system team is structured influences its adoption and ongoing success for more info read team models for scaling a design system team https medium com eightshapes llc team models for scaling a design system 2cf9d03be6a0 u9d11mefp the salesforce team model for scaling a design system https medium com salesforce ux the salesforce team model for scaling a design system d89c2a2d404b akuqars3c establishing a design system team http atomicdesign bradfrost com chapter 5 establishing a design system team who is the primary owner of the design system who is the primary person responsible for the design system s success or failure this person is often in a senior leadership or director position who is responsible for allocating time budget and resources to the design system initiative who are the design system s key stakeholders are there other parties involved are there any players outside of the organization agencies consultants etc who will affect or be affected by the design system deployment how do the design system s components find their way into applications see chasing the holy grail strategies for distributing your pattern library and keeping it in sync https medium com marcelosomers chasing the holy grail bbc0b7cce365 3gjztlqve for various strategies on how to deploy design systems how is versioning handled what versioning conventions do you adhere to when rolling out new updates to the design system see semantic versioning http semver org for an example how are dependencies managed who manages the deployment process making changes who can contribute to the design system can every user directly contribute patterns or modifications to the design system s components and guidelines or is it only managed by a select few on the spectrum from wipe open to complete lockdown where does your design system stand what does the contribution process look like pull requests simple feature requests prototypes what process should people expect to follow in order to propose fixing a bug extending a pattern adding a new see modifying patterns http atomicdesign bradfrost com chapter 5 making changes to patterns for more info how do changes make their way into the design system when the system is updated what is the process for getting those changes into individual applications communication what communication channels are used to talk about the design system the design system should plug into the organization s existing communication structure slack yammer hipchat basecamp wikis blogs email newsletters what steps are taken when the design system is updated release notes blog post email newsletter smoke signals how are system changes communicated to end users how are users of your organization s applications notified when design system changes affect their experience this may include release notes blog posts guided tours videos overlays tweets etc | os |
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FreeRTOS_TM4C_Game | freertos tm4c game road fighter game using tm4c123 tiva c series launchpad nokia5110 lcd and freertos see wiki for more info | os |
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Data-Modelling-with-Apache-Cassandra | data modeling with apache cassandra img align right width 25 height 25 src https www programmersought net wp content uploads 2021 09 1200px cassandra logo svg png this project is part of the course nosql data modelling in the data engineering nanodegree on udacity the final version of the repository will be submitted to udacity for review and grading course topics non relational databases nosql distributed databases cap theorem denormalization in apache cassandra cassandra query language primary keys and clustering columns where clauses project description in this project i applied what you ve learned on data modeling with apache cassandra and complete an etl pipeline using python to complete the project i needed to model your data by creating tables in apache cassandra to run queries i used an etl pipeline which transfers data from a set of csv files within a directory to create a streamlined csv file to model and insert data into apache cassandra tables project context a startup called sparkify wants to analyze the data they ve been collecting on songs and user activity on their new music streaming app the analysis team is particularly interested in understanding what songs users are listening to currently there is no easy way to query the data to generate the results since the data reside in a directory of csv files on user activity on the app they d like a data engineer to create an apache cassandra database which can create queries on song play data to answer the questions and wish to bring you on the project your role is to create a database for this analysis you ll be able to test your database by running queries given to you by the analytics team from sparkify to create the results main dependencies pandas cassandra numpy files data modelling with apache cassandra project ipynb notebook containing the etl pipelines usage to use the code written to create the database and tables open the notebook data modelling with apache cassandra project ipynb contributing pull requests to show improvements of the existing code are welcome for major changes please open an issue first to discuss what you would like to change license mit https choosealicense com licenses mit | server |
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diptimanr.github.io | welcome to github pages you can use the editor on github https github com diptimanr diptimanr github io edit main 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 basic writing and formatting syntax https docs github com en github writing on github getting started with writing and formatting on github basic writing and formatting syntax 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 diptimanr diptimanr github io settings pages 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 docs github com categories github pages basics or contact support https support github com contact and we ll help you sort it out | cloud |
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Industrial-IoT-Workshop | intel industrial iot workshop setup guide welcome to the intel industrial iot workshop in this workshop we will explore industry 4 0 technologies through lectures and hands on labs by the end of the workshop you should have a solid understanding of different industry 4 0 technologies and have some working ideas of how to implement them in your place of business how do i use the lab material the links below will guide the workshop attendee through the slides videos and labs in the intel industrial iot workshop the first lab setup the up sup 2 sup board hardware https software intel com en us upsquared grove getting started guide is a preparatory lab to setup the hardware and software used in the rest of the labs and to deploy a sample program to be sure that the attendee has correct understood the workflow to write compile and deploy an application the protocol labs use the up2 board the sensors from the hardware kit and the arduino create environment to prototype a sensor use the mraa and upm libraries to create the interface between the sensor and the up2 board and then explore several different network protocols common to the iiot next we will spend some time talking about different types of automation and use a juypter notebook running python to build a rules based automation service lastly we will look at the smart video field where software and hardware are merging to produce new intelligent video systems the intel iot developer relations team hopes that you enjoy this iiot workshop social media and feedback if you are posting on social media the hashtags for the event are inteliot and commercialiot feel free to talk to any of the intel people at this event to leave feedback also if you find errors in the workshop material all of our labs are on github feel free to fork any repository and send us a pull request afterall that s why we are on github workshop agenda introduction to industrial internet of things slide deck introduction to industrial internet of things presentations 01 introduction to the industrial internet of things pdf video industrial applications https www intel com content www us en industrial automation overview html formalizing the industrial internet of things slides formalizing the industrial internet of things presentations 02 software defined industrial systems pdf video a new industrial revolution through the internet of things https www intel com content www us en industrial automation industrial vision video html lab setup the up sup 2 sup board hardware https software intel com en us upsquared grove getting started guide software defined industrial systems sensors slides sensor and actuators presentations 03 sensors and actuators pptx video input and output with mraa https www youtube com watch v hy4hudluvem lab sensors and actuators https ssg drd iot github io toc sensors software defined industrial systems protocols slides industrial protocols presentations 04 industrial protocols pptx lab publish sensor data over mqtt tls https ssg drd iot github io lab protocols mqtt arduino lab opc ua server and client https ssg drd iot github io lab sensors opc ua lab virtual sensor https ssg drd iot github io virtual sensor software defined industrial systems automation slides automation and the iiot presentations 05 automation pptx video beckhoff industrial solutions https www intel com content www us en industrial automation products and solutions intel beckhoff industrial solutions video html lab choose either lab building an automation service in python https ssg drd iot github io lab automation jupyter or building an automation service in javascript https ssg drd iot github io lab iot automation additional information lab extra infomration setup alternative ides https ssg drd iot github io doc alternative ides computer vision slides computer vision presentations 07 computer vision pptx video introduction to the movidious neural compute stick https www youtube com watch v viotpaycf98 video mouser product brief on movidious neural computer stick https www youtube com watch v gl ikyr9ekk demo movidius lane detection openvx lane detection lab opencv basics and lane detection lab https github com ssg drd iot lab opencv examples feedback survey and conclusion hardware used in this workshop intel offers scalable hardware solutions at different power performance and price points during these labs we will be using two different products that have intel hardware for the first part of this workshop we will use the up2 board and connect to the arduino create online development tool during the second part of this workshop we will use the intel nuc core i7 head up sup 2 sup board first is the up sup 2 sup board http www up board org upsquared it features a 40 pin i o connector multiple usb 3 0 ports double gigabit ethernet hdmi and more other features make it a perfect solution for different domains and products like robotics drone machine vision smart home education digital signage intelligent cars internet of things the compatibility with linux android and all the windows 10 distributions give you great flexibility scalability and quick time to market images up2 png up sup 2 sup ai vision kit this kit is available at up sup 2 sup board http www up board org upsquared it features a 40 pin i o connector multiple usb 3 0 ports double gigabit ethernet hdmi mini pci express and a movidius mini pci express card which make it a perfect solution for different domains and products like robotics drone machine vision smart home education digital signage intelligent cars internet of things the compatibility with linux android and all the windows 10 distributions give you great flexibility scalability and quick time to market images kit contents overlay png disclaimer intel and the intel logo are trademarks of intel corporation or its subsidiaries in the u s and or other countries other names and brands may be claimed as the property of others 1b3fbd55a077c1a6931245c7372661829fdec046 | server |
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chainlink-ruby | chainlink code climate https codeclimate com github oraclekit chainlink badges gpa svg https codeclimate com github oraclekit chainlink join the chat at https gitter im smartcontractkit chainlink lobby https badges gitter im smartcontractkit chainlink lobby svg https gitter im smartcontractkit chainlink lobby utm source badge utm medium badge utm campaign pr badge utm content badge api see the api documentation https chainlink docs smartcontract com for more details about the api overview assignments assignments are the main model for defining work to be done by chainlink an assignment specifies a series of processing steps subtasks which form a processing pipeline assignments include up front configuration for the subtask pipeline as well as instructions on when and how the assignment can be triggered to run snapshots whenever an assignment is triggered to run a snapshot is created the snapshot is the record of the work that was done and the steps taken along the way to reach the final snapshot result snapshots can be triggered either through upfront scheduling of the assignment and or by on demand requests through any of the adapters subtasks assignments are made up of a sequence of subtasks subtasks are small specialized processes designed to be modular and reusable with many other types of subtasks every time a snapshot is created it starts by processing the first subtask the result of each subtask is fed into the next subtask until the final subtask is processed the result of the final subtask becomes the result of the entire snapshot data is passed between subtasks as a json payload by convention the main field that information is read from is stored as the top level key value but other keys can be used and additional information can be stored in their payload subtasks are initially configured when an assignment is defined but they can also be dynamically configured with the data passed in from previous subtasks adapters the processing work for each subtask is handled by its adapter adapters are where the processing and communication with external services happens subtasks are specific configurations of how work is to be handled by an adapter chainlink ships with a few adapters built in but additional external adapters can be created to add custom functionality external adapters are external services which are communicated with via http external adapters allow for functionality of chainlink to be easily extended and can be written in which ever language is best suited conforming to a minimal http interface https chainlink docs smartcontract com adapter integration is the only requirement for creating your custom external adapters the adapters that ship with chainlink core are bitcoincomparisonjson https chainlink docs smartcontract com bitcoincomparisonjson returns a signed bitcoin transaction signs either a completion transaction or a failure transaction based on a value comparison of the input ethereumbytes32 https chainlink docs smartcontract com ethereumbytes32 formats the input as ethereum bytes32 value and writes it into the specified contract returns the unformatted value that was provided as input ethereumint256 https chainlink docs smartcontract com ethereumint256 formats the input as ethereum int256 value and writes it into the specified contract returns the unformatted value that was provided as input ethereumuint256 https chainlink docs smartcontract com ethereumuint256 formats the input as ethereum uint256 value and writes it into the specified contract returns the unformatted value that was provided as input ethereumformatted https chainlink docs smartcontract com ethereumformatted writes a preformatted ethereum hexadecimal value into the blockchain as configured returns the preformatted value that was provided as input ethereumlogwatcher https chainlink docs smartcontract com ethereumlogwatcher returns the data field of an ethereum event log if one is provided otherwise returns the value that was provided as the input requires weiwatchers https github com oraclekit wei watchers integration httpgetjson https chainlink docs smartcontract com httpgetjson retrieves json and returns the specific field selected in the configuration jsonreceiver https chainlink docs smartcontract com jsonreceiver generates a url for the oracle to receive json push notifications parses the pushed json and returns the specific field selected in the configuration if you are interested in other types of adapters feel free to reach out mailto support smartcontract com adapter schemas adapter schemas allow for adapters to be modular enough to be used with many types of adapters but still remain reliable when used with other adapters that may not even be defined yet adapter schemas are json schemas http json schema org that specify the input requirements and output formats of each adapter for more information on the various schemas used by chainlink check out the schemas repo https github com oraclekit schemas development requirements ruby v2 0 0 postgres v9 3 install git clone https github com oraclekit chainlink cd chainlink gem install bundler bundle rake db create db migrate start foreman start testing to run the full test suite including integration tests you need an instance of devnet running on your machine this requires first installing parity https github com paritytech parity once parity is installed run the following commands git clone https github com oraclekit devnet git cd devnet start then to run the full test suite run rake or test a specific test rspec spec models assignment spec rb 57 | ethereum bitcoin blockchain chainlink oracle | blockchain |
Supply-Chain-Gode-Blockchain | h1 align center br a img src https www mdpi com logistics logistics 03 00005 article deploy html images logistics 03 00005 g001 png width 200 a br supply chain dapp br h1 p align center a href https docs godechain com welcome img src https s3 coinmarketcap com static gravity thumbnail medium 12b1f4d9727b4aab83cd5398bf6e080d jpg width 35 height 35 a a href https soliditylang org img src https github com rishav4101 eth supplychain dapp blob main images solidity svg width 80 a a href https reactjs org img src https github com rishav4101 eth supplychain dapp blob main images react png width 80 a a href https www trufflesuite com img src https github com rishav4101 eth supplychain dapp blob main images trufflenew png width 50 a nbsp nbsp nbsp a href https www npmjs com package web3 img src https github com rishav4101 eth supplychain dapp blob main images web3 jpg width 60 a p h4 align center a simple supply chain setup with a href https docs soliditylang org en v0 8 4 target blank solidity a h4 p align center a img src https img shields io badge dependencies up 20to 20date brightgreen svg a p demo dapp link https www canva com design dafb i9v cm fk0pktuokfq5dfcpqxh w watch utm content dafb i9v cm utm campaign designshare utm medium link utm source publishsharelink description supply chain is always hard to manage and requires a lot of admistrative machinery however when managed with smart contracts using blockchain a lot of the paperwork is reduced also it leads to an increase in the transparency and helps to build an efficient root of trust supply chain dapp is such an implementation of a supply chain management system which uses blockchain to ensure a transparent and secure transfer of product from the manufacturer to the customer via the online e commerce websites architecture the smart contract is being written with solidity which is then compiled migrated and deployed using truffle js on the gode testnet blockchain network the frontend uses web3 js to communicate with the smart contract and gode testnet blockchain network and meta musk wallet is connect to gode test network to do transaction between each component in supply https raw githubusercontent com faizack619 supply chain gode blockchain master client public blank 20diagram png https raw githubusercontent com faizack619 supply chain gode blockchain master client public blank 20diagram png supply chain flow https cdn vectorstock com i 1000x1000 35 51 diagram of supply chain management vector 41743551 webp https cdn vectorstock com i 1000x1000 35 51 diagram of supply chain management vector 41743551 webp https cdn wordpress info futurelearn com info wp content uploads 8d54ad89 e86f 4d7c 8208 74455976a4a9 2 768x489 png smart contract working flow https raw githubusercontent com faizack619 supply chain gode blockchain master client public supply 20chain 20design 20 1 png token ghsat0aaaaaab52spat5yhi3aalnpfxl27ay7ou3iq https raw githubusercontent com faizack619 supply chain gode blockchain master client public supply 20chain 20design 20 1 png token ghsat0aaaaaab52spat5yhi3aalnpfxl27ay7ou3iq this is a supplychain smart contract written in solidity the contract models the various roles and stages involved in the supply chain of a pharmaceutical product the contract owner is the person who deploys the contract and is the only one who can authorize various roles like retailer manufacturer etc there are several roles involved in the supply chain of the pharmaceutical product these include the raw material supplier manufacturer distributor and retailer the smart contract stores information about the medicine such as its name description and current stage in the supply chain there is also a function to show the current stage of a medicine which can be used by client applications the smart contract also stores information about the various players in the supply chain such as their name address and place of operation the addrms addmanufacturer adddistributor and addretailer functions can be used by the contract owner to add new players to the supply chain overall this smart contract provides a way to track the various stages of a pharmaceutical product in the supply chain ensuring transparency and accountability setting up local development step1 installation and setup vscode vscode can be downloaded from https code visualstudio com node js download the latest version of lts node js from https nodejs org and after installation check version using terimal node v git download the latest version of git from the official website at https git scm com downloads and check version using terimal git version metamask can be installed as a browser extension from the chrome web store or firefox add ons store step 2 connect meta musk with gode testnet 1 connect metamask open metamask in your browser and click on the network dropdown in the top right corner https metamask zendesk com hc article attachments 10080831633947 https metamask zendesk com hc article attachments 10080831633947 1 after clicking on add network u will get interface to add network name rcp url chain id put same as shown in the image below and click on add or save https raw githubusercontent com faizack619 supply chain gode blockchain master client public network png https raw githubusercontent com faizack619 supply chain gode blockchain master client public network png 2 select gode network in the network drop down 3 click on account address to copy and paste your address in this url https tool godechain net faucet click on sent me https raw githubusercontent com faizack619 supply chain gode blockchain master client public get 20gode png https raw githubusercontent com faizack619 supply chain gode blockchain master client public get 20gode png 4 now you will get the 1 gode on your account and check in meta musk wallet step 3 compile deploy smart contract open vscode and open vscode terimal by ctrl clone project type the following command and press enter git clone https github com faizack619 supply chain gode blockchain git install truffle type the following command and press enter npm install g truffle install dependencies type the following command and press enter npm i file structure for dapp contracts this folder contains the solidity smart contracts for the dapp the migrations sol contract is automatically created by truffle and is used for managing migrations migrations this folder contains the javascript migration files used to deploy the smart contracts to the blockchain network test this folder contains the javascript test files used to test the smart contracts truffle config js this file contains the configuration for the truffle project including the blockchain network to be used and any necessary settings package jso n this file contains information about the dependencies and scripts used in the project package lock json this file is generated automatically and contains the exact version of each dependency used in the project client s this folder contains the client side code typically html css and javascript can be organized into a client folder mnemonic it requires mnemonic to be passed in for provider this is the seed phrase for the account you d like to deploy from create a new secret file in root directory and enter your 12 word mnemonic seed phrase to get started to get the seedwords from metamask wallet you can go to metamask settings then from the menu choose security and privacy where you will see a button that says reveal seed words refer here https metamask zendesk com hc en us articles 360015290032 how to reveal your secret recovery phrase for more details compile the smart contract in the terminal use the following command to compile the smart contract truffle compile configuring truffle for gode after compile we need to deploy our smart contract on blockchain in our case we are deploying on gode testnet which is testnet blockchain for development used to test and develop smart contracts https raw githubusercontent com faizack619 supply chain gode blockchain master client public capture png https raw githubusercontent com faizack619 supply chain gode blockchain master client public capture png we need to install hdwallet run this command in npm install truffle hdwallet provider as you can see we have testnet which has network id 5566 which identity gode testnet id truffle migrate network testnet command will deploye smart contract to gode blockchain it will take some time for deployment and u will able find transaction hash contract address and many more step 4 run dapp open terminal and enter the client folder cd client install all packages in the package json file npm i install web3 in the package json file npm install save web3 run this command npm run the app npm start the app gets hosted by default at port 3000 step 5 setup account for supply chain player 1 go to metamask click on the account icon in the top right corner select create account and name as raw material supplier and click create https miro medium com max 1400 1 27k5fr7h56to9z2jvobrha png https miro medium com max 1400 1 27k5fr7h56to9z2jvobrha png 2 add all participate raw material supplier manufacture retail by following above step 3 get gode for each player from this url https tool godechain net faucet in order to do transaction license this project uses an mit https opensource org licenses mit license documentation to help with solidity https docs soliditylang org en v0 8 4 documentation to help with react https reactjs org docs getting started html documentation to help with truffle https www trufflesuite com docs truffle reference configuration documentation to help with deployment on gode blockchain https docs godechain com welcome gode chain deploy smart contract using truffle for deploying smart contracts on gode | blockchain |
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iot-middleware-freertos-samples | azure iot samples using azure iot middleware for freertos markdown link check disable windows ci tests https github com azure samples iot middleware freertos samples actions workflows ms build yml badge svg branch main https github com azure samples iot middleware freertos samples actions workflows ms build yml linux ci tests https github com azure samples iot middleware freertos samples actions workflows ci tests linux yml badge svg branch main https github com azure samples iot middleware freertos samples actions workflows ci tests linux yml markdown link check enable getting started with azure iot middleware for freertos the azure iot middleware for freertos simplifies the connection of devices running freertos to the azure iot services it implements a modular approach that brings flexibility to iot developers by allowing them to bring their own network stack mqtt tls and socket the azure iot middleware for freertos repo https github com azure azure iot middleware freertos has the core functionalities of the middleware and no external dependencies however to implement the working samples we need to bring a network stack which is the objective of the samples in this repo we have two sets of samples azure iot hub these samples leverage azure iot hub dps device provisioning and plug and play azure iot central these samples leverage azure iot central azure dps device provisioning service and plug and play azure subscription is not required during the initial 7 days of the iot central free trial https azure microsoft com pricing details iot central pricing there are several other alternatives to get mcu based devices connected to azure see other azure iot sdks https learn microsoft com azure iot develop concepts using c sdk and embedded c sdk to learn more iot hub samples below you will find samples for development kits and simulators showing how to use the azure iot middleware for freertos connected to azure iot hub the following samples support these development kits espressif esp32 demos projects espressif esp32 esp32 azure iot kit demos projects espressif aziotkit nxp mimxrt1060 evk demos projects nxp mimxrt1060 stmicroelectronics b l475e iot01a demos projects st b l475e iot01a b l4s5i iot01a demos projects st b l4s5i iot01a stm32h745i disco demos projects st stm32h745i disco cm7 pc simulation linux demos projects pc linux windows demos projects pc windows for a video deep dive into this repo and the source code please see the microsoft developers video below img src docs resources deep dive video jpg width 50 https youtu be pnykfuj3vds azure device update you can interact with azure device update https github com azure azure iot middleware freertos blob main docs how to use adu client md remotely updating your azure iot hub devices through the samples below espressif esp32 demos projects espressif adu readme md nxp mimxrt1060 evk demos projects nxp mimxrt1060 adu md stmicroelectronics b l475e iot01a demos projects st b l475e iot01a adu md pc simulation linux demos projects pc linux adu md iot central samples below you will find samples for development kits showing how to use the azure iot middleware for freertos connected to azure iot central the following samples support these development kits espressif esp32 azure iot kit demos projects espressif aziotkit gsg md stmicroelectronics b l475e iot01a demos projects st b l475e iot01a gsg md plug and play sample the easiest way to interact with the plug and play sample from the iot service side is to use azure iot explorer to interact with the device sample install azure iot explorer https github com azure azure iot explorer plug and play download the thermostat model https github com azure opendigitaltwins dtdl blob master dtdl v2 samples thermostat json to a local directory start azure iot explorer and then configure your hub https github com azure azure iot explorer configure an iot hub connection once you ve created your thermostat device you should see it listed in the ux go to iot plug and play settings on the home screen select local folder for the location of the model definitions and point to the folder you downloaded the thermostat model go to the devices list and select your thermostat device now select iot plug and play components and then default component you will now be able to interact with the plug and play device additional instructions for using azure iot explorer are available here https github com azure azure iot explorer plug and play support if you need support please see our support md support md file contributing this project welcomes contributions and suggestions most contributions require you to agree to a contributor license agreement cla declaring that you have the right to and actually do grant us the rights to use your contribution for details visit https cla opensource microsoft com when you submit a pull request a cla bot will automatically determine whether you need to provide a cla and decorate the pr appropriately e g status check comment simply follow the instructions provided by the bot you will only need to do this once across all repos using our cla 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 trademarks this project may contain trademarks or logos for projects products or services authorized use of microsoft trademarks or logos is subject to and must follow microsoft s trademark brand guidelines https www microsoft com legal intellectualproperty trademarks usage general use of microsoft trademarks or logos in modified versions of this project must not cause confusion or imply microsoft sponsorship any use of third party trademarks or logos are subject to those third party s policies | server 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wokwi-elements | wokwi elements web components for arduino and various electronic parts npm version https img shields io npm v wokwi elements https www npmjs com package wokwi elements gitpod ready to code https img shields io badge gitpod ready to code blue logo gitpod https gitpod io https github com wokwi wokwi elements check out the component catalog https elements wokwi com note these elements only provide the presentation and display of the represented hardware they do not provide the functional simulation code of the hardware that is dependant on the application simulator that you wish to use these with and thus up to you to create using wokwi elements you can install the package with npm and then import it into your code js import wokwi elements alternatively you can load the wokwi elements bundle from unpkg s cdn html script src https unpkg com wokwi elements 0 48 3 dist wokwi elements bundle js script replace 0 48 3 with the latest version number you can find a list of all the versions in the releases https github com wokwi wokwi elements page local development to prepare for local development clone this repo and then install the dependencies npm install then start storybook npm run storybook this will open a local dev server at http localhost 6006 where you can interact with the elements and see your changes live similar to https elements wokwi com creating a new element the easiest way to create a new element is to run the generator npm run new element name demo this will generate a new element called demo it will also create a storybook file so you will be able to see the new element in storybook see the local development section above note updates the docstrings in the code will not be reflected in storybook s docs tab unless you restart storybook or run the following command manually and refresh the page npm run analyze components check out the contributing guide contributing md for more details learn how to create elements video tutorial the membrane keypad element live coding tutorial https www youtube com watch v gh27icnatwa walks through the complete process behind creating an element research drawing and writing the code stories blog posts recreating the arduino pushbutton using svg and lt lit element gt https www smashingmagazine com 2020 01 recreating arduino pushbutton svg turning arduino oled display into a web component https blog wokwi com making an arduino ssd1306 lit element license wokwi elements are released under the mit license license | lit-element arduino web-components electronics | server |
Curso-primeiros-passos-com-freeRTOS-Codigos | curso primeiros passos com o freertos aprenda a api do freertos e passe a usar rtos em seus projetos de sistemas embarcados esse curso visa introduzir os alunos no uso da api do freertos capacitando os para usar esse rtos em projetos futuros com microcontroladores usaremos como base o framework arduino e o kit esp32 por m ser apenas facilidade nos primeiros passos com o freertos o que voc aprender nesse curso o capacitar para aplicar o freertos em qualquer microcontrolador o que voc aprender nesse curso introdu o aos sistemas de tempo real setup do ambiente de programa o introdu o ao freertos tarefas filas sem foros software timers event groups task notifications nesse reposit rio est o os exemplos de c digos no curso que est publicado na udemy se voc tiver interesse em fazer o curso acesse primeiros passos com freertos https www udemy com course primeiros passos com o freertos referralcode 6aa6f6169b55a1cf24f1 | os |
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ITs | its informations technology | server |
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AECVision | aecvision aecvision is an object detection project for the construction industry the main goal is to deliver good models for various problems like detection elements on plans to allow automatized tasks speed up documentation analysis create tools for future computer vision projects information now project is base on yolov5 https github com ultralytics yolov5 repo but in the future i will try other types of model architectures input image resolution 1280x1280 image file jpg for tagging i use label studio https labelstud io training model in google colab https colab google detection images with using sahi https github com obss sahi folder structure modules project modules object detection detection screen module screen detection ipynb prepare data and training prepare data and training in google colab module dataset images test training validation labels labels reduce classes test training validation prepare data from pdf ipynb train model in google colab ipynb wall detection export export walls detection coordinates to csv and allow imports in other program files converted pdf exported csv upload pdf classes functions py wall detection export with sahi py wall detection export py train results available modules model 12classes model 12classes gray model walls model walls gray yolov5 cloned yolov5 repository license readme md requirements txt project pipeline image https github com pawelkinczyk aecvision assets 96824698 3a8048ff 2d91 4bd8 bc95 834dd4cc1ec7 available models name classes model architecture number of training images original augmented color model 12classes 12 classes see train results yolov5m6 252 1204 rgb model walls wall yolov5m6 252 1204 rgb model 12classes gray 12 classes see train results yolov5m6 252 1204 gray model walls gray wall yolov5m6 252 1204 gray mit license https img shields io badge license gplv3 blue svg https github com pawelkinczyk aecvision blob main license how it works the model was trained on clear plans and with annotation but remember that the best results you get without many symbols on construction plans detection confidence 0 5 za 5 projekt architektoniczno budowlany pdf2 2 3 https github com pawelkinczyk aecvision assets 96824698 f26e7b79 2da5 42d9 8490 d8eed6da295e confidence 0 8 za 5 projekt architektoniczno budowlany pdf2 2 31 https github com pawelkinczyk aecvision assets 96824698 3a28a1b9 8124 434c 8af8 8033a32b8e68 screen detection by using screen detection py https github com pawelkinczyk aecvision assets 96824698 0e60f9e4 a5dd 4fdc a695 ea3c943e4a7f objects import from detections press image to watch film this works with my pylab extension https github com pawelkinczyk pylab br watch the video https github production user asset 6210df s3 amazonaws com 96824698 258236845 3e0c66e2 2252 4651 92e7 3209384512f8 png https youtu be omx21mxyzci br project roadmap collect and tag more images up to 500 try to use grayscale than rgb change number of classes maybe only 3 wall window door evolve hyperparameters to get the best set in yolo use other model architecture than yolo think about switch from jpg file to png avoid converting data lost think about how to add more contexts to the model like you are in the kitchen if there are stove and there probably will be table summary problems first training data description walls are overrepresented because this is normal quantities in architectural plans image https github com pawelkinczyk aecvision assets 96824698 97386b7d 19fe 4136 962a 5b99707d823d maybe in future i need to create more plans with other categories to improve other classes detection learning process model has steadily improved up to the 272nd epoch and probably has further potential image https github com pawelkinczyk aecvision assets 96824698 abc451d1 2ea0 497d bbf7 9b5a6ca45d62 on the validation set an increase in obj loss was noted during the learning process image https github com pawelkinczyk aecvision assets 96824698 f1217a7b fc9f 4d62 a7b3 862025eedf28 confussion matrix show that all classes except background are correctly identified image https github com pawelkinczyk aecvision assets 96824698 f4c0b780 fff5 4bf7 a138 2e4333206a8f if you want to dig into training results see train results or write to me problems a small number of certain classes conversion from pdf default construction plans format to jpg results in a loss of image quality contributing contributions are always welcome i look for help in tagging and improving models feel free to improve this project thanks thanks yolov5 https github com ultralytics yolov5 and label studio https labelstud io for your project and tutorials special thanks to my brother marcin who help me with tagging a href https www buymeacoffee com produktywnl target blank img align center src https img shields io badge buy me a coffee ffdd00 style for the badge logo buy me a coffee logocolor black title buy me coffee alt height 50 a | aec-industry computer-vision engineering machine-learning python3 | ai |
mqtt | mqtt by mcxiaoke https github com mcxiaoke v1 0 6 2021 07 07 mqtt monitor https github com mcxiaoke mqtt monitor mqtt https blog mcxiaoke com mqtt gitbook https mcxiaoke gitbook io mqtt wiki https github com mcxiaoke mqtt wiki pdf epub https www gitbook com book mcxiaoke mqtt cn details https github com mcxiaoke mqtt mqtt m2m iot pr readme md mqtt 00 preface md mqtt 00 contents md mqtt mqtt 01 introduction md mqtt mqtt 02 controlpacketformat md mqtt mqtt 03 controlpackets md 3 1 connect mqtt 0301 connect md 3 2 connack mqtt 0302 connack md 3 3 publish mqtt 0303 publish md 3 4 puback mqtt 0304 puback md 3 5 pubrec qos 2 mqtt 0305 pubrec md 3 6 pubrel qos 2 mqtt 0306 pubrel md 3 7 pubcomp qos 2 mqtt 0307 pubcomp md 3 8 subscribe mqtt 0308 subscribe md 3 9 suback mqtt 0309 suback md 3 10 unsubscribe mqtt 0310 unsubscribe md 3 11 unsuback mqtt 0311 unsuback md 3 12 pingreq mqtt 0312 pingreq md 3 13 pingresp mqtt 0313 pingresp md 3 14 disconnect mqtt 0314 disconnect md mqtt 04 operationalbehavior md mqtt 05 security md websocket mqtt 06 websocket md mqtt 07 conformance md b mqtt 08 appendixb md gitbook v1 0 1 2015 10 22 html mqtt 3 1 1 http mcxiaoke github io mqtt protocol mqtt 3 1 1 cn html pdf mqtt 3 1 1 http mcxiaoke github io mqtt protocol mqtt 3 1 1 cn pdf html mqtt version 3 1 1 http docs oasis open org mqtt mqtt v3 1 1 mqtt v3 1 1 html pdf mqtt version 3 1 1 http docs oasis open org mqtt mqtt v3 1 1 mqtt v3 1 1 pdf 4 0 https creativecommons org licenses by nc sa 4 0 legalcode blog http blog mcxiaoke com github https github com mcxiaoke email github mcxiaoke com mailto github mcxiaoke com mqtt webclient https github com mcxiaoke mqtt monitor rx https github com mcxiaoke rxdocs mqtt https github com mcxiaoke mqtt awesome kotlin https github com mcxiaoke awesome kotlin kotlin koi https github com mcxiaoke kotlin koi next https github com mcxiaoke android next packerng https github com mcxiaoke packer ng plugin gradle https github com mcxiaoke gradle packer plugin eventbus xbus https github com mcxiaoke xbus | mqtt | server |
iOS | gunn engineering ios the gunn engineering club ios curriculum https developer apple com develop images develop hero large png develop for ios picture from apple website | os |
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modulz-original-design-system-archive | modulz an open source design system for building scalable responsive websites and applications getting started paste this line of code into the lt head gt of your html files html link rel stylesheet href https s3 amazonaws com modulz modulz min css or install with npm shell npm install modulz css documentation modulz docs https www modulz co overview installation test page for now to get started you will also need to html starter document just create a new folder create an index html file inside then paste in the code below and open it in a browser html doctype html html class oy scroll lang en style font size 62 5 head meta charset utf 8 meta name viewport content width device width initial scale 1 title modulz starter title link rel stylesheet href https s3 amazonaws com modulz modulz min css head body class ff sansserif color gray900 add your content here body html license mit you can use modulz as you see fit | css design-systems ui-components design html css-framework | os |
mslearn-cv-classify-bird-species | page type sample languages python products azure cognitive services custom vision description add 150 character max description urlfragment update this to unique url stub ms learn custom vision bird species classification guidelines on readme format https review docs microsoft com help onboard admin samples concepts readme template branch master guidance on onboarding samples to docs microsoft com samples https review docs microsoft com help onboard admin samples process onboarding branch master taxonomies for products and languages https review docs microsoft com new hope information architecture metadata taxonomies branch master this repo has the python source and sample dataset for the ms learn module to create a computer vision azure custom vision model the sample code is to create the project create the image tags based on the folder name bird species and upload the respective photos to the tag created in azure contents outline the file contents of the repository it helps users navigate the codebase build configuration and any related assets file folder description src sample source code gitignore define what to ignore at commit time changelog md list of changes to the sample contributing md guidelines for contributing to the sample readme md this readme file license the license for the sample prerequisites outline the required components and tools that a user might need to have on their machine in order to run the sample this can be anything from frameworks sdks os versions or ide releases setup explain how to prepare the sample once the user clones or downloads the repository the section should outline every step necessary to install dependencies and set up any settings for example api keys and output folders running the sample outline step by step instructions to execute the sample and see its output include steps for executing the sample from the ide starting specific services in the azure portal or anything related to the overall launch of the code key concepts provide users with more context on the tools and services used in the sample explain some of the code that is being used and how services interact with each other contributing this project welcomes contributions and suggestions most contributions require you to agree to a contributor license agreement cla declaring that you have the right to and actually do grant us the rights to use your contribution for details visit https cla opensource microsoft com when you submit a pull request a cla bot will automatically determine whether you need to provide a cla and decorate the pr appropriately e g status check comment simply follow the instructions provided by the bot you will only need to do this once across all repos using our cla 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 | ai |
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Web_ICP1 | 5590 mobile development this is requirement for class how to create web programming csee 5590 003 mobile web app | front_end |
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Wechat-IoT | iot wechat v2 3 smart tag sensoro iot sensoro iot sensoro iot smart tag smart tag iot rgb iot smart tag smart tag iot gb2312 c0b6c9ab smart tag smart tag iot gb2312 arduino d6 d7 io smart tag d6 d7 smart tag c0b6c9ab io sensoro iot sensoro iot rgb smart tag smart tag kit smart tag rx d6 tx d7 rgb scl a5 sda a4 anode d5 cathode d4 pin d3 1 usb 2 3 sensoro iot 4 5 arduino arduino http arduino cc arduino http www arduino cn arduino ide http arduino cc en main software 1 ide 2 demo wechat wechat hardware wechat hardware ino 3 wechat lib 4 gb2312 gb2312 cmd which is the gb2312 codes of the chinese character define gb ximie cfa8c3f0 define gb lanse c0b6c9ab 5 if memcmp cmd data gb ximie cmd len flag rgb blink false flag rgb rainbow false rgbled setcolorrgb 0 0 0 else if memcmp cmd data gb lanse cmd len flag rgb blink false flag rgb rainbow false rgbled setcolorrgb 0 0 255 6 7 softserial softserial http www sensoro com zh iot beijing sensoro com soho t1 b 2807 qq 361891407 400 400 686 3180 | server |
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bosket | h1 align center a href https elbywan github io bosket img alt bosket logo src https elbywan github io bosket assets bosket logo png width 100px a br bosket br a href https travis ci org elbywan bosket img alt travis badge src https travis ci org elbywan bosket svg branch master a a href https www npmjs com package bosket core img alt npm badge src https img shields io npm v bosket core svg height 20 a a href https github com elbywan bosket blob master license img alt license badge src https img shields io github license elbywan bosket svg height 20 a h1 h4 align center bosket is collection of tree views for front end frameworks h4 h5 align center a versatile powerful and simple way to display nested data h5 purpose bosket is a library of tree views implementations for front end reactive frameworks tree views which are basically an elegant way to display nested lists are very versatile and can for example be used as file explorers menus table of contents or category lists the core logic is written in plain javascript without any dependencies framework implementations rely on this very same code which makes new implementations easy to write and by extension new frameworks easy to support br div align center h6 i tree view example reactive nested lists i h6 br a href https elbywan github io bosket img alt bosket itemtree gif src https elbywan github io bosket assets bosket itemtree gif width 200px a div documentation please check out the bosket website https elbywan github io bosket for more details including the full documentation supported frameworks a href https facebook github io react img src https elbywan github io bosket assets react logo fat svg alt react logo width 30px a react https elbywan github io bosket react a href https angular io img src https elbywan github io bosket assets angular svg alt angular logo width 30px a angular https elbywan github io bosket angular a href https vuejs org img src https elbywan github io bosket assets vue svg alt vue logo width 30px a vue js https elbywan github io bosket vue a href http riotjs com img src https elbywan github io bosket assets riot logo svg alt riot logo width 30px a riot js https elbywan github io bosket riot license mit | treeview tree tree-view tree-structure tree-component bosket react vuejs angular riot riotjs | front_end |
MEAN-Stack-User-Registration-Front-End | mean stack user registration front end angular 6 this is a mean stack demo project to implement user registration with password encryption and proper validation content discussed design registration form using angular 6 client side validation node js api call from angular 6 get the code git clone https github com codaffection mean stack user registration front end git cd mean stack user registration front end angular6 npm install how it works scroll article on this topic url https goo gl 7w73su tv video tutorial on this same topic url https goo gl xivk4x a href http www youtube com watch feature player embedded v v9zdnfvs7z4 target blank img src http img youtube com vi v9zdnfvs7z4 0 jpg alt video tutorial for mean stack user registration form in angular 6 width 500 height 400 border 10 a related mean stack tutorial in order 1 crud operation insert update view and delete https goo gl lbq4bm 2 user registration br node js back end https goo gl cmnpwe br angular 6 front end https goo gl xivk4x this one 3 jwt authentication br node js back end http bit ly 31fkef6 angular front end http bit ly 2z6pmq5 bar chart list of tutorials moneybag support us angular http bit ly 2kqn9xf paypal https goo gl bpcyxw asp net core http bit ly 30fpdmg amazon affiliate https geni us jdzpe react http bit ly 325temf python http bit ly 2ws4utg point right follow us node js https goo gl vijcfs website http www codaffection com asp net mvc https goo gl gvjuj7 youtube https www youtube com codaffection flutter https bit ly 3ggmmjz facebook https www facebook com codaffection web api https goo gl itvayj twitter https twitter com codaffection mean stack https goo gl yjppah c tutorial https goo gl s1zjxo asp net webform https goo gl gxc2aj c winform https goo gl vhs9hd ms sql https goo gl mlys9e crystal report https goo gl 5vou7t cg exercises in c program https goo gl qewjcs | front_end |
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php-development-in-docker | pre requisites you must have docker installed for this code to work check the installation guide https docs docker com engine installation if you haven t got it installed it contains a basic lemp stack running with docker intented to be used for local web development get started clone the project and run docker compose bash git clone https github com jivoi php development in docker git cd php development in docker docker compose up d docker machine ip default docker compose d down description the different containers are described in docker compose yml https github com jivoi php development in docker blob master docker compose yml there are 6 of them a container for nginx a container for php fpm a container for mysql a container for phpmyadmin a container to make mysql data persistent a container for the application code all of them are using official images the current directory is mounted into the one served by nginx on the container so any update to the code is available without having to rebuild the container the mysql data sits in its own directory mounted into its own container to make it persistent the application is available on the port 80 of the host machine phpmyadmin is available on port 8080 | front_end |
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thesis-code | this is the source code pertaining to my master s thesis http links andidog de thesis about comparison and evaluation of cross platform frameworks for the development of mobile business applications it includes the sample application mobiprint implemented with titanium rhodes phonegap and sencha touch android native ios native iphone only source code for the test web service common files icons images development screenshots exported apk files for android of the first four frameworks version of 2012 07 24 can be installed if apps from unknown sources are allowed | front_end |
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RaspberrySurveillance | raspberrysurveillance surveillance system designed for raspberry pi check out this blog post for more information http bjurr se dummy camera made smart with raspberry pi it is a web interface that can show snapshot of camera setup motion triggering start and stop motion triggering save captured videos to disk save captured videos to webdav screenshot of web gui is available here https raw github com tomasbjerre raspberrysurveillance master doc software rbs png camera this is the hardware used to build the camera raspberry pi model b 512mb ram camera module for raspberry pi wifi usb nano openbox sky case 16gb sd cost approximately 900 sek 135 100 install these instructions are a work in progress i have developed this on archlinux i ll be writing instructions as if you are using archlinux and you ll have to translate it to your distribution required packages sudo pacman s extra php apc sudo pacman s core curl sudo pacman s bc sudo pacman s imagemagick php ini there are some extensions needed extension apc so extension sysvsem so permission echo subsystem vchiq group video mode 0660 etc udev rules d 10 vchiq permissions rules usermod a g video your username chmod a rw web api motion json chmod a rwx script monitor sh echo web api monitor log chmod a rw web api monitor log | os |
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IndstrlAndEmbdCompSysDsgn-PingPongGame | indstrlandembdcompsysdsgn pingponggame the ping pong game project developed for the industrial and embedded computer systems design course within the emecs masters date december 2016 purpose the purpose of this project is to create a computer controlled electromechanical ping pong game the electronic components game boards and development tools needed to realize the game were given the hardware components needed to be assembled and the software for the microcontrollers needed to be developed programming language c team 39 vitor ribeiro roriz jens mei ner alexandru cohal system the system was divided in 3 main parts node 1 based on the avr atmega 162 microcontroller node 2 based on the arduino mega 2560 board avr atmega 2560 microcontroller usb multifunction card containing an oled display a joystick and 4 touch sensors the connection between the nodes was done using a can bus for more information about the task see this document https github com alexandru cohal indstrlandembdcompsysdsgn pingponggame blob master documentation ttk4155termproject assignmenttext pdf results the final outcome can be seen in the following image imagefinalresult output photofinalresult jpg | os |
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cs733 | cs733 engineering a cloud assignments this repository contains the assignments for the course cs733 engineering a cloud at iit bombay | cloud |
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mldl | my blog https aichamp wordpress com https aichamp wordpress com my e books h2o user guide https github com avkash mldl blob master orgs h2o guide readme md motivation life career https github com avkash mldl blob master pages motivational md events 2017 https github com avkash mldl blob master dllibs master events md 2018 https github com avkash mldl blob master dllibs master events md 2019 https github com avkash mldl blob master dllibs master events md me stackoverflow https stackoverflow com users 1325423 avkashchauhan dzone https dzone com users 1425729 avkash html linkedin https www linkedin com in avkashchauhan medium https medium com avkashchauhan handbook of artificial intelligence and machine learning avkashchauhan visit everyday you get by avkashchauhan https github com avkash mldl blob master handbook readme md collection of content opencv org https opencv org ai courses by opencv deepai org https deepai org build with ai add cutting edge functionality to your apps with machine learning d2l ai https d2l ai dive into deep learning an interactive deep learning book with numpy and ndarray machine deep learning glossary a https github com avkash mldl blob master glossary def a md b https github com avkash mldl blob master glossary def b md c https github com avkash mldl blob master glossary def c md d https github com avkash mldl blob master glossary def d md e https github com avkash mldl blob master glossary def e md f https github com avkash mldl blob master glossary def f md g https github com avkash mldl blob master glossary def g md h https github com avkash mldl blob master glossary def h md i https github com avkash mldl blob master glossary def i md j https github com avkash mldl blob master glossary def j md k https github com avkash mldl blob master glossary def k md l https github com avkash mldl blob master glossary def l md m https github com avkash mldl blob master glossary def m md n https github com avkash mldl blob master glossary def n md o https github com avkash mldl blob master glossary def o md p https github com avkash mldl blob master glossary def p md q https github com avkash mldl blob master glossary def q md r https github com avkash mldl blob master glossary def r md s https github com avkash mldl blob master glossary def s md t https github com avkash mldl blob master glossary def t md u https github com avkash mldl blob master glossary def u md v https github com avkash mldl blob master glossary def v md w https github com avkash mldl blob master glossary def w md x https github com avkash mldl blob master glossary def x md y https github com avkash mldl blob master glossary def y md z https github com avkash mldl blob master glossary def z md all about ai algorithms programming deep learning organizations burning hot ai glm https github com avkash mldl blob master algos algo glm md gbm https github com avkash mldl blob master algos algo gbm md python https github com avkash mldl blob master pages master python md r https github com avkash mldl blob master dllibs master r md everything dl https github com avkash mldl blob master master dl md google https github com avkash mldl blob master orgs google readme md microsoft https github com avkash mldl blob master orgs microsoft readme md github top10 https github com search o desc q machine learning s stars type repositories utf8 e2 9c 93 automl https github com avkash mldl blob master master automl md ensembles https github com avkash mldl blob master pages ensembles md mynotebooks https github com avkash mldl blob master notebook readme md everything ml https github com avkash mldl blob master master ml md aws https github com avkash mldl blob master orgs aws readme md facebook https github com avkash mldl blob master orgs facebook readme md sas https github com avkash mldl blob master orgs sas md kdnuggets top10 http www kdnuggets com 2015 12 top 10 machine learning github html randomforest https github com avkash mldl blob master algos algo drf md java https github com avkash mldl blob master dllibs master java md scala https github com avkash mldl blob master pages master scala md self driving auto https github com avkash mldl blob master driverless readme md h2o https github com avkash mldl blob master orgs h2o readme md h2o4gpu https github com avkash mldl blob master orgs h2o h2o4gpu home md nvidia https github com avkash mldl blob master orgs nvidia readme md awesome deeplearning https github com christoschristofidis awesome deep learning deeplearning https github com avkash mldl blob master algos algo dl md spark https github com avkash mldl blob master pages master spark md gan https github com avkash mldl blob master pages mater gan md matlab https github com avkash mldl blob master orgs matlab mathworks md openai https openai com research dive into ml https github com hangtwenty dive into machine learning k means https github com avkash mldl blob master algos algo kmeans md feature engineering https github com avkash mldl blob master pages master feature engineering md model interpretability https github com avkash mldl blob master ml interpretability md ai2 http allenai org ml journal http www jmlr org partnership on ai https www partnershiponai org mlalgorithms https github com rushter mlalgorithms tree master examples naive bayes https github com avkash mldl blob master algos algo nb md answerbots https github com avkash mldl blob master pages master answerbot md time series https github com avkash mldl blob master dllibs timeseries md baidu http research baidu com berkeley ai http bair berkeley edu blog ml for se dev https github com zuzoovn machine learning for software engineers pca https github com avkash mldl blob master algos algo pca md glrm https github com avkash mldl blob master algos algo glrm md genetic programming https github com avkash mldl blob master dllibs master ga md model management https github com avkash mldl blob master pages master model mgmt md quora https github com avkash mldl blob master orgs quora ai md reddit https github com avkash mldl blob master orgs reddit ai md ml from scratch https github com eriklindernoren ml from scratch ensembles https github com avkash mldl blob master algos algo ensembles md code samples https github com avkash mldl blob master code readme md reinforcement learning https github com avkash mldl blob master pages rl all md kaggle https github com avkash mldl blob master kaggle master kaggle md analytics vidhya https www analyticsvidhya com evalai https evalai cloudcv org challanger ai https challenger ai lan en cheatsheet ai https github com kailashahirwar cheatsheets ai all about learning one thing at a time videos articles industry sw engineering cheatsheets youtube videos https github com avkash mldl blob master dllibs master videos md blogs https github com avkash mldl blob master dllibs master blogs md industry articles https github com avkash mldl blob master pages docs articles readme md data vis https github com avkash mldl blob master pages master datavis md keras https github com avkash mldl blob master pages refcards keras md scikit learn https github com avkash mldl blob master pages refcards scikit learn md podcast https github com avkash mldl blob master dllibs master videos md newsletters https github com avkash mldl blob master dllibs master blogs md industry reports https github com avkash mldl blob master pages docs industry readme md db rdbms https github com avkash mldl blob master code db programming md neural networks zoo https github com avkash mldl blob master pages refcards nn zoo md video turotials https github com avkash mldl blob master dllibs master videos md all books https github com avkash mldl blob master pages docs books readme md ai companies https github com avkash mldl blob master dllibs enterprise ai md react ui https github com avkash mldl blob master pages react css md ggplot https github com avkash mldl blob master pages refcards ggplot md matplotlib https github com avkash mldl blob master pages refcards matplotlib md researchers https github com avkash mldl blob master dllibs master personals md slide deck collection https github com avkash mldl blob master pages docs slidedecks readme md active links https github com avkash mldl blob master pages activelinks md docker containers https github com avkash mldl blob master pages containers all md pandas https github com avkash mldl blob master pages refcards pandas md numpy https github com avkash mldl blob master pages refcards numpy md scipy https github com avkash mldl blob master pages refcards scipy md all articles https github com avkash mldl blob master pages all articles md training resources https github com avkash mldl blob master pages master training md datasets https github com avkash mldl blob master pages master datasets md scripting https github com avkash mldl blob master code linux readme md nlp https github com avkash mldl blob master dllibs master nlp md chrome extension https github com avkash mldl blob master pages chrome ext md ai in japan https github com avkash mldl blob master orgs japan readme md ai projects https github com avkash mldl blob master myprojects ai projects md model interoperability https github com avkash mldl blob master pages model operability md my projects presentations forecasting gas and electricity utilization using facebook prophet https github com avkash mldl blob master pages forecasting prophet md tensorbeat building answerbot with keras and tensorflow slides https github com avkash mldl tree master tensorbeat answerbot artistic design with deep learning https github com avkash mldl blob master pages master art md visualizing h2o gbm and random forest mojo models trees in python https github com avkash mldl tree master myprojects h2o mojo tree visualization deep learning with tensorflow on raspberrypi https github com avkash mldl blob master rasp readme md computer vision and deep learning project https github com avkash mldl blob master myprojects dl with cv readme md tips and trics zsh on osx https github com avkash mldl blob master pages tips n tricks md multiple git accounts with ssh https github com avkash mldl blob master pages tips n tricks md adding proxy setting in react coreui to connect backend https github com avkash mldl blob master pages setupproxy md github tips tricks https github com avkash mldl blob master pages githubtipstricks md setting postgresql in docker https github com avkash mldl blob master pages postgresql docker md python tips and tricks https github com avkash mldl blob master pages pythontipstricks md books reports documents pdf title what is in it dive into deep learning ndarray https github com avkash mldl blob master pages docs 2020 d2l en ndarray pdf deep learning with ndarray https classic d2l ai dive into deep learning numpy https github com avkash mldl blob master pages docs 2020 d2l en numpy pdf deep learning with numpy https d2l ai ai4all https github com avkash mldl blob master pages docs 2020 ai4all pdf 1 ai 101 cheatsheet http montreal ai ai4all pdf computer vision resoucres https github com avkash mldl blob master pages docs 2020 computer vision resources pdf by satya malik https learnopencv com deep learning visual cheatsheat https github com avkash mldl blob master pages docs 2020 deep 20learning 20visual pdf collection of various cheat sheet collection handwritten deep learning notes https github com avkash mldl blob master pages docs 2020 ml art pdf handwritten notes in deep learning interpretable machine learning by christoph molnar https github com avkash mldl blob master pages docs 2020 interpretable machine learning pdf a guide for making black box models explainable book dzone ai research guide 2018 https github com avkash mldl blob master pages docs 2020 dzone2018 ai researchguide pdf a report from dzone on ai research driving digital transformation using ai and machine learning tdwi https github com avkash mldl blob master pages docs 2020 tdwi bpreport q319 web pdf a report by tdwi data scientist rerport by figure eight https github com avkash mldl blob master pages docs 2020 data scientist report figure8 pdf figure eight report launching ai project figure8 https github com avkash mldl blob master pages docs 2020 launching ai figure eight pdf a figure 8 report a book on churn https github com avkash mldl blob master pages docs 2020 churnebookfinal pdf a report by price intelligently disclaimer this site is a collection of resources from all over the internet some of the content is mine however most of the content is created by others and by no means i am claiming it to be mine i try my best to add proper links as needed however if i have missed something it is just a mistake please visit here https github com avkash mldl blob master pages individual res md for individual resources collection links | ai |
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CV | opencv pyqt5 dip go https github com lrioxh cv tree main dip gui https www bilibili com video bv1oz4y1y7dp unit1 unit2 unit3 unit4 unit5 unit6 dip main py go https github com lrioxh cv tree main scanner https www bilibili com video bv1rz4y1c7rg pc scanner main py sfm pmvs go https github com lrioxh cv tree main tdre openmvg cmvs pmvs https yongqi blog csdn net article details 110252018 pc flask | ai |
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local-web-server | view on npm https badgen net npm v local web server https www npmjs org package local web server npm module downloads https badgen net npm dt local web server https www npmjs org package local web server gihub repo dependents https badgen net github dependents repo lwsjs local web server https github com lwsjs local web server network dependents dependent type repository gihub package dependents https badgen net github dependents pkg lwsjs local web server https github com lwsjs local web server network dependents dependent type package node js ci https github com lwsjs local web server actions workflows node js yml badge svg https github com lwsjs local web server actions workflows node js yml coverage status https coveralls io repos github lwsjs local web server badge svg https coveralls io github lwsjs local web server js standard style https img shields io badge code 20style standard brightgreen svg https github com feross standard upgraders please read the release notes https github com lwsjs local web server releases for feedback discussion and support see here https github com lwsjs local web server discussions local web server a lean modular web server for rapid full stack development supports http https and http2 small and 100 personalisable load and use only the behaviour required by your project attach a custom view to personalise how activity is visualised programmatic and command line interfaces use this tool to build any type of front end web application static dynamic single page app progessive web app react etc prototype a back end service rest api microservice websocket server sent events service etc monitor activity analyse performance experiment with caching strategy etc local web server is a distribution of lws https github com lwsjs lws bundled with a starter pack of useful middleware synopsis this package installs the ws command line tool take a look at the usage guide https github com lwsjs local web server wiki cli usage static web site running ws without any arguments will host the current directory as a static web site navigating to the server will render a directory listing or your index html if that file exists sh ws listening on http mbp local 8000 http 127 0 0 1 8000 http 192 168 0 100 8000 static files tutorial https github com lwsjs local web server wiki how to serve static files this clip demonstrates static hosting plus a couple of log output formats dev and stats img src https s9 gifyu com images njc3poy imgur gif width 618px title static static log output single page application serving a single page application an app with client side routing e g a react or angular app is as trivial as specifying the name of your single page sh ws spa index html with a static site requests for typical spa paths e g user 1 login would return 404 not found as a file at that location does not exist however by marking index html as the spa you create this rule if a static file is requested e g css style css then serve it if not e g login then serve the specified spa and handle the route client side spa tutorial https github com lwsjs local web server wiki how to serve a single page application spa img src https s9 gifyu com images iqvmi8v imgur gif width 618px title spa url rewriting and proxied requests another common use case is to forward certain requests to a remote server the following command proxies blog post requests from any path beginning with posts to https jsonplaceholder typicode com posts for example a request for posts 1 would be proxied to https jsonplaceholder typicode com posts 1 sh ws rewrite posts https jsonplaceholder typicode com posts 1 rewrite tutorial https github com lwsjs local web server wiki how to rewrite urls to local or remote destinations this clip demonstrates the above plus use of static extensions to specify a default file extension and verbose to monitor activity img src https s9 gifyu com images 3flcbjn imgur gif width 618px title proxy json requests to remote resource https and http2 for https or http2 pass the https or http2 flags respectively see the wiki https github com lwsjs local web server wiki for further configuration options and a guide on how to get the green padlock in your browser ws http2 listening at https mba4 local 8000 https 127 0 0 1 8000 https 192 168 0 200 8000 built in middleware stack if you do not supply a custom middleware stack via the stack option the following default stack will be used it s designed to cover most typical web development scenarios name description basic auth https github com lwsjs basic auth password protect a server using basic authentication body parser https github com lwsjs body parser parses the request body making ctx request body available to downstream middleware request monitor https github com lwsjs request monitor feeds traffic information to the verbose output log https github com lwsjs log outputs an access log or stats view to the console cors https github com lwsjs cors support for setting cross origin resource sharing cors headers json https github com lwsjs json pretty prints json responses rewrite https github com lwsjs rewrite url rewriting use to re route requests to local or remote destinations blacklist https github com lwsjs blacklist forbid access to sensitive or private resources conditional get https github com lwsjs conditional get support for http conditional requests mime https github com lwsjs mime customise the mime type returned with any static resource compress https github com lwsjs compress compress responses using gzip spa https github com lwsjs spa support for single page applications static https github com lwsjs static serves static files index https github com lwsjs index serves directory listings further documentation see the wiki for plenty more documentation and tutorials https github com lwsjs local web server wiki install sh npm install g local web server copy 2013 23 lloyd brookes 75pound gmail com documented by jsdoc to markdown https github com jsdoc2md jsdoc to markdown | lws web-server backend webapp full-stack web-development server webapplication single-page-app progressive-web-app | front_end |
computer-vision | computer vision for xr this is a feature repo as defined in the proposals process that has been created for exploring computer vision apis for xr the conversation that led to the creation of this repo can be found in proposals issues 4 https github com immersive web proposals issues 4 blair macintyre blairmacintyre is coordinating the creation of the initial explainers top level documents in this repository the topic of computer vision support is broad and implementing support on the web even just within the context of devices supported by the webxr device api could be approached in a number of different ways in this repository we would like to capture and document the various ways this could be thought about even though the initial proposal will focus on a subset of the possible approaches and use cases there are 5 potential use cases we could consider working on intertwined but sufficiently separate we can talk about them separately these will be documents in separate explainers synchronous access to video frames from the camera in gpu memory particularly on video mixed reality devices e g phones running arkit arcore the scenario here is to support applications creating visual effects by having access to the video in gpu memory so the simple overlay graphics on video approach can be augmented with shadows reflection distortion and other effects it should be possible to implement more efficiently than would be possible if the video frames were first loaded into javascript buffers and there is the possibility to address privacy concerns if the implementation can arrange for gpu memory to not to be accessible in javascript documented in video effects md video effects md asynchronous access to video frames in the cpu and or gpu asynchronous because most non video mixed devices do not run the camera and display at the same frame rates so synchronized access may not be practical the scenario here is to do real time computer vision e g slam like 6d ai 8thwall etc are working on cv tracking algorithms like vuforia face and object detection in a platform independent way some of what will be done here might eventually make it into platforms and may already exist in some platforms such as image detection others would include custom algorithms that need to work everywhere to support web applications for art advertising games and so on documented in cv in page md cv in page md extending webrtc to support access to cameras on xr device sessions and streaming recording of video from xr devices one goal of this approach is to avoid duplicating functionality across web apis e g keep video device access in one place the core scenario here is a worker wants to allow an expert to see what they are seeing and overlay augmentations in their view this scenario applies to enterprise scenarios as well as consumer apps for consumers this is home owner wants to show home depot consultant something get guidance and order parts for repair this work will likely need to be done over in the webrtc wg as they work on the next version of webrtc but we should track it here in a document with relevant pointers to issues and capabilities documented in webrtc remote video md webrtc remote video md exposing native cross platform cv algorithms the browser can expose entire algorithms running on the camera video as suggested by the shape detection api proposal https wicg github io shape detection api we could start with very basic capabilities like detecting barcodes in 3d images perhaps faces some of the specific algorithms could be optional but it would be nice if there were very straightforward things like barcodes discussed in the shape detection api that could be implemented everywhere if video frames are available inside the web page it may be possible to polyfill them with wasm implementations developers and users would benefit strongly from having some common capabilities that are implemented natively when possible e g using arkit for image detection on ios and having an agreed upon approach for exposing platform specific capabilities that might be hard to implement in wasm like arkit arcore s more advanced features documented in cv in browser md cv in browser md exposing native computer vision building blocks and or components in a way that leverages native processing of video frames before sending the pre processed video frames and associated data into the web app either into the gpu or cpu perhaps leveraging a library like khronos openvx https www khronos org openvx in fact one way this could be thought about is by working with khronos to define webvx being able to leverage optimized platform capabilities for doing well known basic algorithms image pyramids simple feature extraction image conversion blur etc could speed up in app cv and also allow some of the effects that might be done in the synchronous gpu case to be done faster like the webrtc discussion if we wanted to pursue this we would want to do that elsewhere but the scenario has been brought up multiple times so we should document summarize and record it it here documented in webvx md webvx md the first two are the focus of this repository and share a common need to have the available cameras exposed and the developer request access to them they can likely be done in the same api e g request cameras direct data to cpu and or gpu guarantee that if the camera is synch with raf that the data will be available before raf and make this known if so but are separable if we only want to tackle one first | incubation webxr | ai |
maple | maple this project is alpha version forever installation firtst up you have to install the latest node js https nodejs org en next please type the following commands npm install g gulp cd path to maple npm install npm start taking future syntaxes javascript babel https babeljs io css cssnext http cssnext io some specs only | css | front_end |
ECISsystemProject | electronically controlled intelligent shelves ecis system pruned version introduction the design of ecis system prototype includes an array of ultrasonic sensors which can be retrofitted in existing shelves with minimal modifications or built in in to new shelves connected wirelessly to a central cloud server from where the inventory of goods on the shelf can be monitored in real time as well as data acquired from these sensors can be used to perform predictive analysis using data mining feature engineering and machine learning techniques to better predict future product sales and minimize inaccurate forecasting instances tl dr inventory automation prototype using nxp frdm k64f mcu ultrasonic sensors cloud server and predictive analytics using machine learning techniques developed by priyank kalgaonkar https priyankkalgaonkar com dependencies nxp frdm k64f development board keil studio cloud ide thingspeak cloud server 1 hc sr04 ultrasonic sensors esp8266 wi fi chip teraterm reporting bugs issues https github com priyankkalgaonkar ecissystemproject issues can be used to keep track of bugs enhancements or other requests for more information see creating an issue https docs github com en issues tracking your work with issues creating an issue you are encouraged to create an issue if you need to report a bug or request an enhancement discusstions github discussions is a collaborative communication forum you can ask and answer questions share updates have open ended conversations and follow along on relevant decisions click on the discussions https github com priyankkalgaonkar ecissystemproject discussions tab on the top to get strated contributions this repository is created and maintained by priyank kalgaonkar https priyankkalgaonkar com you can contribute by submitting pull requests from your fork to the upstream repository for more information see contributing to projects https docs github com en get started quickstart contributing to projects guide | automation keil-studio nxp k46f | os |
front-end-resources | introduction a collection of awe some resources mostly focused on front end web development you can find a list of all the resources in here https fe resources vercel app table of contents introduction introduction table of contents table of contents resources resources introduction introduction api api css css data structures and algorithms data structures and algorithms design design frontend resources frontend resources git github git github html html javascript javascript react react typescript typescript website website installation installation local development local development build build contributing contributing license license contributors contributors resources introduction docs intro md api public api s docs api api md css architectures methodologies docs css architectures methodologies md articles docs css articles md css in js docs css css in js md design systems docs css design systems md generators docs css generators md videos docs css videos md websites docs css websites md data structures and algorithms books docs data structures and algorithms books md challenges docs data structures and algorithms challenges md websites docs data structures and algorithms websites md design articles docs design articles md books docs design books md colors docs design colors md design systems docs design design systems md fonts docs design fonts md icons docs design icons md optimization tools docs design optimization tools md stock photos docs design stock photos md tools docs design tools md typography docs design typography md websites docs design websites md frontend resources articles docs frontend resources articles md blogs docs frontend resources blogs md books docs frontend resources books md challenges docs frontend resources challenges md discord communities docs frontend resources discord md documentations docs frontend resources documentations md games docs frontend resources games md interactive practices docs frontend resources interactive practices md mixed content docs frontend resources mixed md newsletters docs frontend resources newsletters md online cirriculums docs frontend resources online cirriculums md podcasts docs frontend resources podcasts md roadmaps docs frontend resources roadmaps md subreddits docs frontend resources subreddits md surveys docs frontend resources surveys md tools docs frontend resources tools md websites docs frontend resources websites md youtube channels docs frontend resources youtube channels md git github courses docs git github courses md tools docs git github tools md videos docs git github videos md websites docs git github websites md html accessibility docs html accessibility md articles docs html articles md checklists docs html checklists md tools docs html tools md javascript articles docs javascript articles md books docs javascript books md courses practices docs javascript courses practices md talks docs javascript talks md tools docs javascript tools md websites docs javascript websites md react articles docs react articles md frameworks docs react frameworks md hooks docs react hooks md state management docs react state management md tools docs react tools md videos docs react videos md typescript articles docs typescript articles md challenges docs typescript challenges md courses docs typescript courses md tools docs typescript tools md website this website is built using docusaurus 2 https docusaurus io a modern static website generator installation yarn local development yarn start this command starts a local development server and opens up a browser window most changes are reflected live without having to restart the server build yarn build this command generates static content into the build directory and can be served using any static contents hosting service contributing if you have any front end resources that you would like to share please feel free to open a pull request with your additions please make sure to follow the formatting of the existing resources and to add your resource to the appropriate section license this repository is licensed under the mit license see license for more information contributors a href https github com aycanogut front end resources graphs contributors img src https contrib rocks image repo aycanogut front end resources a | css design html javascript react resources typescript | front_end |
MCTE4342_EmbeddedSystemDesign | mcte4342 embeddedsystemdesign the compilation of programming example and exercises for mcte4342 embedded system design iium | os |
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Hands-On-Blockchain-for-Python-Developers | hands on blockchain for python developers a href https www packtpub com big data and business intelligence hands blockchain python developers utm source github utm medium repository utm campaign 9781788627856 img src https d1ldz4te4covpm cloudfront net sites default files imagecache ppv4 main book cover cover 7856 png alt hands on blockchain for python developers height 256px align right a this is the code repository for hands on blockchain for python developers https www packtpub com big data and business intelligence hands blockchain python developers utm source github utm medium repository utm campaign 9781788627856 published by packt gain blockchain programming skills to build decentralized applications using python what is this book about blockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions this book serves as a practical guide to developing a full fledged decentralized application with python to interact with the various building blocks of blockchain applications this book covers the following exciting features understand blockchain technology and what makes it an immutable database use the features of web3 py api to interact with the smart contract create your own cryptocurrency and token in ethereum using vyper use ipfs features to store content on the decentralized storage platform implement a twitter like decentralized application with a desktop frontend if you feel this book is for you get your copy https www amazon com dp 1788627857 today a href https www packtpub com utm source github utm medium banner utm campaign githubbanner img src https raw githubusercontent com packtpublishing github master github png alt https www packtpub com border 5 a instructions and navigations all of the code is organized into folders for example chapter02 the code will look like the following compilation backend class populus compilation backends vyperbackend contract source dirs contracts import remappings following is what you need for this book if you are a python developer who wants to enter the world of blockchain hands on blockchain for python developers is for you the book will be your go to guide to becoming well versed with the blockchain ecosystem and building your own decentralized applications using python and library support with the following software and hardware list you can run all code files present in the book chapter 1 15 software and hardware list chapter software required os required 1 12 python 3 6 anaconda 5 3 ganache and truffle framework linux any we also provide a pdf file that has color images of the screenshots diagrams used in this book click here to download it https www packtpub com sites default files downloads 9781788627856 colorimages pdf related products other books you may enjoy blockchain by example packt https www packtpub com big data and business intelligence blockchain example utm source github utm medium repository utm campaign 9781788475686 amazon https www amazon com dp 1788475682 foundations of blockchain packt https www packtpub com big data and business intelligence foundations blockchain utm source github utm medium repository utm campaign 9781789139396 amazon https www amazon com dp 1789139392 get to know the author arjuna sky kok has experience more than 10 years in expressing himself as a software engineer he has developed web applications using symfony laravel ruby on rails and django he also has built mobile applications on top of android and ios platforms currently he is researching ethereum technology other than that he teaches android and ios programming to students he graduated from bina nusantara university with majors in computer science and applied mathematics he always strives to become a holistic person by enjoying leisure activities such as dancing salsa learning french and playing starcraft 2 he lives quietly in the bustling city of jakarta suggestions and feedback click here https docs google com forms d e 1faipqlsdy7datc6qmel81fiuuymz0wy9vh1jhkvpy57oimekgqib ow viewform if you have any feedback or suggestions 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 9781788627856 https packt link free ebook 9781788627856 a p | blockchain |
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hypermix | hypermix code for our paper gpt3mix https arxiv org abs 2104 08826 and conducting classification experiments using gpt 3 prompt based data augmentation getting started installing packages the main depedencies can be installed via pip install r requirements txt usage the main code is run through main py check out help for full list of commands python main py help the code will automatically use the first gpu device if detected a typical command to run bert base 10 times on the 1 subsample set of the sst 2 dataset and computing the average of all run is as follows python main py datasets sst2 train subsample 0 01f classifier transformers model name bert base uncased num trials 1 augmenter none save dir out the script will create a directory named out in the current working directory and save the script log as out run log it will also save any augmentations created during the experiments if any augmentation is enabled to test gpt3mix prepare an openai api key as described at the bottom of this readme file then use the following command python main py datasets sst2 train subsample 0 01f classifier transformers model name bert base uncased num trials 1 augmenter gpt3 mix save dir out managing seeds in the command above the script will automatically generate seeds for sampling data and optimizing models the seed used to generate each individual seed is called master seed and can be set using master data seed and master exp seed options as evident from the option names they are responsible for sampling data and optimizing a freshly initialized models respectively sometimes we need to manually set the seeds and not rely on automatically generated seeds from the master seeds manually seeding can be achieved via data seeds option if this option is given the master data seed will be ignored we only support manualy data seeding for now openai key store openai api key under the current working directory as a file named openai key when running the main script it will automatically detect the api key api keys can be provided to the script by api key option not recommended or from a file named openai key in the current working directory other notes at the moment we only support data augmentation leveraging openai gpt 3 gpt3mix but we will release an update that supports hyperclova https arxiv org abs 2109 04650 as soon as it becomes available to the public hypermix citation to cite our code or work please use the following bibtex inproceedings yoo2021gpt3mix title gpt3mix leveraging large scale language models for text augmentation author yoo kang min and park dongju and kang jaewook and lee sang woo and park woomyoung booktitle findings of the association for computational linguistics emnlp 2021 month nov year 2021 publisher association for computational linguistics url https aclanthology org 2021 findings emnlp 192 pages 2225 2239 license hypermix copyright 2021 present naver corp permission is hereby granted free of charge to any person obtaining a copy of this software and associated documentation files the software to deal in the software without restriction including without limitation the rights to use copy modify merge publish distribute sublicense and or sell copies of the software and to permit persons to whom the software is furnished to do so subject to the following conditions the above copyright notice and this permission notice shall be included in all copies or substantial portions of the software the software is provided as is without warranty of any kind express or implied including but not limited to the warranties of merchantability fitness for a particular purpose and noninfringement in no event shall the authors or copyright holders be liable for any claim damages or other liability whether in an action of contract tort or otherwise arising from out of or in connection with the software or the use or other dealings in the software | ai |
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FreeRTOS | freertos my git copy freertos atmega2560 port | os |
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Measuring-Sustainability-Reporting | measuring sustainability reporting using web scraping and natural language processing overview nowadays the web represents a medium through which corporations can effectively disseminate and demonstrate their efforts to incorporate sustainability practices into their business processes this led to the idea of using the web as a source of data to measure how uk companies are progressing towards meeting the new sustainability requirements recently stipulated by the united nations with the sustainable development goals sdgs the aim of this research was to carry out an initial proof of concept for the indicator number of companies publishing sustainability reports by turnover band geography national or global company sector and number of employees this indicator relates to sdg target 12 6 https sustainabledevelopment un org content documents 11803official list of proposed sdg indicators pdf which is to encourage companies especially large and transnational companies to adopt sustainable practices and to integrate sustainability information into their reporting cycle this repository describes the steps taken to develop a web scraping program able to collect sustainability information from companies websites what does it do web scraping is a technique employed to extract data from websites programmatically without the need of a user interaction the scraper navigates through each company website accessing every internal link while recursively traversing websites the scraper flags sup 1 sup only the web pages that suggest sustainability content once a page is found it needs to be cleaned before it is saved in a mongodb database https www mongodb com in fact web pages are often cluttered with additional features such as navigation panels pop up ads and advertisements around the main textual content these noisy parts tend to affect the performances of nlp tasks negatively to avoid this content extraction methods exist to analyse the html behind a webpage and extract what is considered to be the important text in our scenario this task is integrated in the scraper architecture and assigned to the contentextractor component of the item pipeline the contentextractor receives the raw web page and extracts just the main textual content using the machine learning based library dragnet https github com seomoz dragnet the item then proceeds to the mongoconnector which checks its validity before sending it to a mongodb database a high level overview of the architecture of the scraper is shown in the next figure scraper flow chart scraper diagram png p sup 1 sup pages are flagged if at least one of the predefined keywords is found in the url address of the page or the text of the hyperlink leading to the page keywords were chosen by inspecting a sample of websites and looking at what were the most common words used to introduce sustainability content p how do i use it requirements pre requisites database mongodb local mode python modules required scrapy pymongo dragnet python version 2 7 how to run the project locally to put the spider to work go to the scraper s top level directory and run scrapy crawl sustainabilitybot project structure repository structure docs index html documentation sustainabilityrepoting ntts 2017 pptx sustainabilityrepoting pdf scraper diagram png scrapy cfg seeds txt reports items py pipelines py settings py spiders web py docs contains the html page https onsbigdata github io measuring sustainability reporting index html included in the scraper s user agent where to find out more information about the project documentation contains a 10 pages report on the pilot study conducted and the slides used for the talk given at the eurostat ntts 2017 conference https ec europa eu eurostat cros content ntts 2017 en scraper is a project based on scrapy which contains the web scraping program to search and extract sustainability related web pages from the companies listed in seeds txt data fields data types and description of the scraped pages stored as mongodb documents https docs mongodb com manual core document field data type description id objectid unique index automatically created by mongodb for each document company string company name this field is part of the compound key for this collection url string the url of the webpage this field is part of the compound key for this collection link text string the link text i e the text that was used to indicate the url on the page where the link was found content array the textual content of the webpage extracted using the dragnet library keywords array the list of unique keywords found either in the link text or in the link url an example of scraped page as stored in mongodb id objectid 57bc03269ff1021cbe014200 company john lewis partnership url http www johnlewispartnership co uk csr our environment environmental performance html link text environmental performance content we are committed to increasing the energy efficiency of our buildings procuring low carbon energy and finding more efficient ways to distribute our goods as well as encouraging innovation our overarching aim is to achieve a 65 reduction in carbon intensity tonnes per m sales by 2020 21 against a 2010 baseline and by 2020 we want to eliminate all of our operational waste going to landfill prior years data is reported in line with our financial reporting period 2015 data is reported on an approximate calendar year basis which comprises the period from 21 december 2014 to 26 december 2015 going forward the annual results will be prepared on an approximate calendar year basis keywords environment csr useful links additional details regarding the analysis of the content extracted by the scraper and about the results of the pilot study can be found in the documentation documentation folder contributors alessandra sozzi https github com alessandrasozzi working for the office for national statistics big data project https www ons gov uk aboutus whatwedo programmesandprojects theonsbigdataproject license released under the mit license license | ai |
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luos_engine | a href https luos io img src https uploads ssl webflow com 601a78a2b5d030260a40b7ad 603e0cc45afbb50963aa85f2 gif 20noir 20rect gif alt luos logo title luos align right height 100 a https github com luos io luos engine actions workflows build yml badge svg https img shields io github license luos io luos engine https github com luos io luos engine blob master license https img shields io badge luos documentation 34a3b4 https www luos io docs http certified luos io https www luos io platformio registry https badges registry platformio org packages luos library luos engine svg https registry platformio org libraries luos luos engine https img shields io discord 902486791658041364 label discord logo discord style social http bit ly joinluosdiscord https img shields io reddit subreddit subscribers luos style social https www reddit com r luos version 2 9 2 luos technology the most for the developer luos provides a simple way to think your hardware products as a group of independant features you can easily manage and share your hardware products features with your team external developers or with the community luos is an open source lightweight library that can be used on any mcu leading to free and fast multi electronic boards products development choosing luos to design a product will help you to develop debug validate monitor and manage it from the cloud the most for the community most of the embedded developments are made from scratch by using luos you will be able to capitalize on the development you your company or the luos community already did the re usability of features encapsulated in luos services will fasten the time your products reach the market and reassure the robustness and the universality of your applications join the luos discord server http discord gg luos join the luos subreddit https www reddit com r luos good practices with luos luos proposes organized and effective development practices guaranteeing development flexibility and evolutivity of your hardware product from the idea to the maintenance of the industrialized product fleet let s do this try on your own with the get started https www luos io tutorials get started consult the full documentation https www luos io docs disclaimer using platformio this library compilation send some anonymous information to luos allowing to improve luos engine experience to disable the telemetry please add dnotelemetry as a compilation flag on your platformio ini file | embedded-systems luos communication-protocol embedded microservice cicd real-time realtime edge freertos arduino raspberry-pi ros micro-ros iot platformio cyber-physical-systems digital-twins cyberphysical-systems digitaltwins | os |
fast-dat-parser | fast dat parser parses the blockchain about as fast as your io can pipe it out for a typical ssd this can be around 450 mib s all memory is allocated up front output goes to stdout stderr is used for logging warning not actively maintained use with caution usage a fast blk dat parser for bitcoin blockchain analysis j threads n threads for parallel computation default 1 m bytes memory usage default 209715200 bytes 200 mib t index transform function default 0 see pre packaged transforms below w filename whitelist file for omitting blocks from parsing important to note is that the implementation skips bitcoind allocated zero byte gaps and includes orphan blocks unless w omits them transforms t each of these pre included functions write their output as raw data binary not hex you can easily write your own though 0 outputs the unordered 80 byte block headers 1 outputs every script prefixed with a uint16 t length 2 displays the number of transaction inputs outputs and number of transactions in the blockchain 3 outputs height value for each output typically used for showing output balances over time use a whitelist see w to stop orphan blocks from being parsed see below for filtering by best chain examples output all scripts for the local best blockchain bash parse the local best blockchain cat bitcoin blocks blk dat parser t0 bestchain chain dat output every script found in the local best blockchain cat bitcoin blocks blk dat parser j4 t1 wchain dat bitcoin scripts dat useful tools these tools are for the cli but will aid in preparing using data produced by the above bestchain a best chain filter for block headers accepts 80 byte block headers until eof then finds the best chain in the set and outputs the best chain in the form of a sorted hash map see hmap k v https github com dcousens fast dat parser blob master include hvectors hpp license mit license the constants and getopstring function in include bitcoin ops hpp is copied from https github com bitcoin bitcoin | bitcoin blockchain fast-dat-parser cplusplus high-performance stream | blockchain |
flutter-tutorials-1-4-drawer-pageroute-navigator-useraccountsdrawerheader | flutter tutorials 1 4 drawer pageroute navigator useraccountsdrawerheader introduction welcome to himdeve development where we are preparing the best tutorials to make your mobile app development easier and more efficient goal 1 create a drawer for our application 2 use useraccountsdrawerheader and listtile for drawer 3 learn how to work with gesturedetector circleavatar alertdialog widgets 4 learn basic navigation between screens in the application page routing tutorial en https himdeve com flutter tutorials flutter tutorials 1 4 drawer pageroute navigator useraccountsdrawerheader tutorial sk cz https himdeve com flutter sk cz tutorialy flutter sk cz 1 4 drawer pageroute navigator useraccountsdrawerheader | front_end |
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StateOS-STM8SDiscovery | stateos ci https github com stateos stateos stm8sdiscovery actions workflows test yml badge svg https github com stateos stateos stm8sdiscovery actions workflows test yml free extremely simple amazingly tiny and very fast real time operating system rtos designed for deeply embedded applications template target stm8s discovery board license this project is licensed under the terms of mit license mit https opensource org licenses mit | stm8s-discovery cosmic-compiler stm8s-discovery-board | os |
Reliquum | reliquum information technology | server |
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awesome-mobile | awesome services for mobile development and marketing instruments services and companies for mobile marketing and development marketing tools a b testing onetwosplit http onetwosplit com splitmetrics http splitmetrics com analytics appsee http www appsee com apsalar https apsalar com capptain http www capptain com flurry http www flurry com game analytics http www gameanalytics com google analytics https www google ru analytics heap analytics https heapanalytics com installtracker http installtracker com kissmetrics http kissmetrics com localytics http localytics com mixpanel http mixpanel com metricscat http metricscat com upsight http www upsight com yandex appmetrika http appmetrika yandex ru ads and retargeting adroll https www adroll com appboy https www appboy com appoptim http www appoptim com appsfire http appsfire com everyads http www everyads com startapp http startapp com inapp games inappfuel http inappfuel com nextpeer https www nextpeer com marketing adjust https www adjust com appannie https www appannie com appsflyer http www appsflyer com deltadna http www deltadna com devtodev https www devtodev com dispply http dispply com jeapie https jeapie com kahuna https www kahuna com metricscat http metricscat com mobileapptracking http www mobileapptracking com mobio http mobioinc com tapstream https tapstream com urban airship http urbanairship com splitmetrics http splitmetrics com app reviews appcoins http appcoins mobi appstars http appstars ru apptools http www apptools ru few reviews http fewreview com metricscat http metricscat com shellback mobile http shellbackmobile com top4app http top4app com review monitoring appfollow http appfollow ru launchkit https launchkit io metricscat http metricscat com traffic appat http appat co appbooster http appbooster ru appcent http appcent ru appscoins http appscoins com appflow http appflow ru appia http www appia com cowall http cowall info uptop http uptop pro wakeapp https wakeapp ru ru development tools errors tracking acra https github com acra acra bugsnag http bugsnag com critercism http www crittercism com fabric http fabric io lookback http lookback io video recording for mobile device screen test fairy https www testfairy com push firebase https www firebase com inappblast https www inappblast com parse https parse com pubnub http www pubnub com pusher https pusher com pushwoosh https www pushwoosh com voice and video calls messaging nexmo http nexmo com twillio http twillio com payments paypal http paypal com stripe http stripe com adyen https www adyen com podcasts russian podcasts app in top https itunes apple com ru podcast appintop prodvizenie mobil id882670965 apptractor https itunes apple com ru podcast apptractor id908041901 android dev https itunes apple com ru podcast android dev podkast id1076856310 english podcasts app in top mobile app marketing https itunes apple com ru podcast appintop mobile app marketing id884500433 ideveloper https itunes apple com ru podcast the ideveloper podcast id400664935 nsbrief https itunes apple com ru podcast nsbrief id399822861 raywenderlich com https itunes apple com ru podcast raywenderlich com podcast id773910890 fragmented http fragmentedpodcast com android developers backstage http androidbackstage blogspot in the context https github com artem zinnatullin thecontext podcast todo add descriptions to all services other awesome lists other amazingly awesome lists can be found in the awesome awesomeness https github com bayandin awesome awesomeness list contributing your contributions are always welcome please submit a pull request or create an issue to add a new service tools blog or software to the list do not submit a project which hasn t been updated in the past 6 months or is not awesome | front_end |
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expo-react-native-mwa-proof-of-concept | solana mobile expo go proof of concept this repository is an example of how you can use solana mobile mobile wallet adapter protocol in an expo go project through the use of a custom expo development build https docs expo dev development create development builds background expo go bundles a hand picked set of native modules this is what expo has to say https github com expo fyi blob main whats in the sdk md if you want to use a module not on that list we only include native modules in the expo sdk if we believe they satisfy a wide range of needs or if we think that integrating them deeply into expo tools and services will provide additional value if you need a specific tool that isn t provided in the expo sdk which is a very common requirement then it s time to migrate from expo go to development builds quick start here s how to create an expo development build that includes the solana mobile stack s mobile wallet adapter protocol you will need an expo account https expo dev signup shell npm install npx eas build profile development platform android npm start | front_end |
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Fake-News-Detection | natural language processing nlp fake news detection the proliferation of fake news in recent times has led to more focused research in computational tools able to identify reliable and trustworthy news in this project we analyse and implement machine learning models for automatic fake news detection data consists of short statements of news releases interviews campaign speeches facebook posts and tweets made during the 2016 u s presidential campaign from politifact com we use various pre processing vectorisation parameter tuning methods across a range of classifiers to identufy fake news getting started download the fake news detection ipynb jupyter notebook file and the data into a folder on your system unzip the contents of the data zip file it consists of 3 tsv tab separated files from terminal cd into the folder and launch jupyter notebook you can view the results of the code already run by me in the notebook in this repository to rerun the code run restart and run all from the notebook the entire notebook will take approximately 80 minutes to execute prerequisites sklearn nltk and other libraries lumpy pandas seaborn etc needs to be installed if not already done they are called in the initial line of the code nltk stopwords nltk punkt nltk maxent treebank pos tagger needs to be downloaded all the classifiers used are available when sklearn is installed except xgradientboost algorithm for installing xgradientboost algorithm classifier please refer https xgboost readthedocs io en latest build html note a simple pip3 install xgboost will install it most of the times if not then please refer the above link license all the libraries and python code are open source the data has been made publicly available by the creator and hence does not need any license acknowledgements william wang for creating the liar dataset by collecting a decade long 12 8k manually labelled short statements from politifact com dataset data that we use for this project is the liar dataset a public available fake news detection corpus i have uploaded a zip file with the data download it to the folder having the fake news detection ipynb jupyter notebook it contains 3 tsv files namely train tsv test tsv and valid csv the data can also be downloaded online from liar dataset https sites cs ucsb edu william data liar dataset zip references wang w 2019 liar liar pants on fire a new benchmark dataset for fake news detection online arxiv org available at https arxiv org abs 1705 00648 wang w sites cs ucsb edu https sites cs ucsb edu william papers acl 2017 pdf horne b and adal s 2017 this just in fake news packs a lot in title uses simpler repetitive content in text body more similar to satire than real news online arxiv org available at https arxiv org pdf 1703 09398 rubin v l 2017 deception detection and rumor debunking for social media in sloan l quan haase a eds 2017 the sage handbook of social media research methods london sage https uk sagepub com en gb eur the sage handbook of social mediaresearch methods book245370 conroy n j rubin v l and chen y 2015 automatic deception detection meth ods for finding fake news proceedings of the association for information science and technology 52 1 pp 1 4 rashkin h choi e jang j y volkova s and choi y 2017 truth of varying shades analyzing language in fake news and politi cal fact checking in proceedings of the 2017 conference on empirical methods in natural language processing pp 2931 2937 shu k sliva a wang s tang j and liu h 2017 fake news detection on socialmedia a data mining perspective acm sigkdd explorations newsletter 19 1 pp 22 36 thorne j and vlachos a 2018 automated fact checking task formulations methods and future directions in proceedings of the 27th international conference on computa tional linguistics pp 3346 3359 long y lu q xiang r li m and huang c 2017 fake news detection through multi perspective speaker pro files online aclweb org available at https aclweb org anthology i17 2043 conroy n chen y and rubin v 2015 deception detection for news three types of fakes online available at https onlinelibrary wiley com doi pdf 10 1002 pra2 2015 145052010083 piccione a line github n d on available at https github com mikanikos ada project blob master data analysis ipynb politifact 2019 fact checking u s pol itics politifact online available at https www politifact com patel n 2019 nishitpatel01 fake news detection online github available at https github com nishitpatel01 fake news detection fotache c 2018 text classification in python pipelines nlp nltk tf idf xg boost and more online medium available at https medium com chrisfotache text classification in python pipelines nlp nltk tf idf xgboost and more b83451a327e0 bedi g 2018 simple guide to text clas sification nlp using svm and naive bayes with python online medium available at https medium com bedigunjit simple guide to text classification nlp using svm and naive bayes with python 421db3a72d34 | ai |
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Merlion | div align center img alt logo src https github com salesforce merlion raw main merlion logo svg width 80 div div align center a href https github com salesforce merlion actions img alt tests src https github com salesforce merlion actions workflows tests yml badge svg branch main a a href https github com salesforce merlion actions img alt coverage src https github com salesforce merlion raw badges coverage svg a a href https pypi python org pypi salesforce merlion img alt pypi version src https img shields io pypi v salesforce merlion svg a a href https opensource salesforce com merlion index html img alt docs src https github com salesforce merlion actions workflows docs yml badge svg a div merlion a machine learning library for time series table of contents 1 introduction introduction 1 comparison with related libraries comparison with related libraries 1 installation installation 1 documentation documentation 1 getting started getting started 1 anomaly detection anomaly detection 1 forecasting forecasting 1 evaluation and benchmarking evaluation and benchmarking 1 technical report and citing merlion technical report and citing merlion introduction merlion is a python library for time series intelligence it provides an end to end machine learning framework that includes loading and transforming data building and training models post processing model outputs and evaluating model performance it supports various time series learning tasks including forecasting anomaly detection and change point detection for both univariate and multivariate time series this library aims to provide engineers and researchers a one stop solution to rapidly develop models for their specific time series needs and benchmark them across multiple time series datasets merlion s key features are standardized and easily extensible data loading benchmarking for a wide range of forecasting and anomaly detection datasets this includes transparent support for custom datasets a library of diverse models for anomaly detection forecasting and change point detection all unified under a shared interface models include classic statistical methods tree ensembles and deep learning approaches advanced users may fully configure each model as desired abstract defaultdetector and defaultforecaster models that are efficient robustly achieve good performance and provide a starting point for new users automl for automated hyperaparameter tuning and model selection unified api for using a wide range of models to forecast with exogenous regressors https opensource salesforce com merlion tutorials forecast 3 forecastexogenous html practical industry inspired post processing rules for anomaly detectors that make anomaly scores more interpretable while also reducing the number of false positives easy to use ensembles that combine the outputs of multiple models to achieve more robust performance flexible evaluation pipelines that simulate the live deployment re training of a model in production and evaluate performance on both forecasting and anomaly detection native support for visualizing model predictions including with a clickable visual ui distributed computation backend https opensource salesforce com merlion merlion spark html using pyspark which can be used to serve time series applications at industrial scale comparison with related libraries the table below provides a visual overview of how merlion s key features compare to other libraries for time series anomaly detection and or forecasting merlion prophet alibi detect kats darts statsmodels nixtla gluonts rrcf stumpy greykite pmdarima univariate forecasting multivariate forecasting univariate anomaly detection multivariate anomaly detection pre processing post processing automl ensembles benchmarking visualization the following features are new in merlion 2 0 merlion prophet alibi detect kats darts statsmodels nixtla gluonts rrcf stumpy greykite pmdarima exogenous regressors change point detection clickable visual ui distributed backend installation merlion consists of two sub repos merlion implements the library s core time series intelligence features and ts datasets provides standardized data loaders for multiple time series datasets these loaders load time series as pandas dataframe s with accompanying metadata you can install merlion from pypi by calling pip install salesforce merlion you may install from source by cloning this repoand calling pip install merlion or pip install e merlion to install in editable mode you may install additional dependencies via pip install salesforce merlion all or by calling pip install merlion all if installing from source individually the optional dependencies include dashboard for a gui dashboard spark for a distributed computation backend with pyspark and deep learning for all deep learning models to install the data loading package ts datasets clone this repo and call pip install e merlion ts datasets this package must be installed in editable mode i e with the e flag if you don t want to manually specify the root directory of every dataset when initializing its data loader note the following external dependencies 1 some of our forecasting models depend on openmp if using conda please conda install c conda forge lightgbm before installing our package this will ensure that openmp is configured to work with the lightgbm package one of our dependencies in your conda environment if using mac please install homebrew https brew sh and call brew install libomp so that the openmp libary is available for the model 2 some of our anomaly detection models depend on the java development kit jdk for ubuntu call sudo apt get install openjdk 11 jdk for mac os install homebrew https brew sh and call brew tap adoptopenjdk openjdk brew install cask adoptopenjdk11 also ensure that java can be found on your path and that the java home environment variable is set documentation for example code and an introduction to merlion see the jupyter notebooks in examples https github com salesforce merlion tree main examples and the guided walkthrough here https opensource salesforce com merlion tutorials html you may find detailed api documentation including the example code here https opensource salesforce com merlion index html the technical report https arxiv org abs 2109 09265 outlines merlion s overall architecture and presents experimental results on time series anomaly detection forecasting for both univariate and multivariate time series getting started the easiest way to get started is to use the gui web based dashboard https opensource salesforce com merlion merlion dashboard html this dashboard provides a great way to quickly experiment with many models on your own custom datasets to use it install merlion with the optional dashboard dependency i e pip install salesforce merlion dashboard and call python m merlion dashboard from the command line you can view the dashboard at http localhost 8050 below we show some screenshots of the dashboard for both anomaly detection and forecasting anomaly dashboard https github com salesforce merlion raw main figures dashboard anomaly png forecast dashboard https github com salesforce merlion raw main figures dashboard forecast png to help you get started with using merlion in your own code we provide below some minimal examples using merlion default models for both anomaly detection and forecasting anomaly detection here we show the code to replicate the results from the anomaly detection dashboard above we begin by importing merlion s timeseries class and the data loader for the numenta anomaly benchmark nab we can then divide a specific time series from this dataset into training and testing splits python from merlion utils import timeseries from ts datasets anomaly import nab data loader returns pandas dataframes which we convert to merlion timeseries time series metadata nab subset realknowncause 3 train data timeseries from pd time series metadata trainval test data timeseries from pd time series metadata trainval test labels timeseries from pd metadata anomaly metadata trainval we can then initialize and train merlion s defaultdetector which is an anomaly detection model that balances performance with efficiency we also obtain its predictions on the test split python from merlion models defaults import defaultdetectorconfig defaultdetector model defaultdetector defaultdetectorconfig model train train data train data test pred model get anomaly label time series test data next we visualize the model s predictions python from merlion plot import plot anoms import matplotlib pyplot as plt fig ax model plot anomaly time series test data plot anoms ax ax anomaly labels test labels plt show anomaly figure https github com salesforce merlion raw main figures anom example png finally we can quantitatively evaluate the model the precision and recall come from the fact that the model fired 3 alarms with 2 true positives 1 false negative and 1 false positive we also evaluate the mean time the model took to detect each anomaly that it correctly detected python from merlion evaluate anomaly import tsadmetric p tsadmetric precision value ground truth test labels predict test pred r tsadmetric recall value ground truth test labels predict test pred f1 tsadmetric f1 value ground truth test labels predict test pred mttd tsadmetric meantimetodetect value ground truth test labels predict test pred print f precision p 4f recall r 4f f1 f1 4f n f mean time to detect mttd precision 0 6667 recall 0 6667 f1 0 6667 mean time to detect 1 days 10 22 30 forecasting here we show the code to replicate the results from the forecasting dashboard above we begin by importing merlion s timeseries class and the data loader for the m4 dataset we can then divide a specific time series from this dataset into training and testing splits python from merlion utils import timeseries from ts datasets forecast import m4 data loader returns pandas dataframes which we convert to merlion timeseries time series metadata m4 subset hourly 0 train data timeseries from pd time series metadata trainval test data timeseries from pd time series metadata trainval we can then initialize and train merlion s defaultforecaster which is an forecasting model that balances performance with efficiency we also obtain its predictions on the test split python from merlion models defaults import defaultforecasterconfig defaultforecaster model defaultforecaster defaultforecasterconfig model train train data train data test pred test err model forecast time stamps test data time stamps next we visualize the model s predictions python import matplotlib pyplot as plt fig ax model plot forecast time series test data plot forecast uncertainty true plt show forecast figure https github com salesforce merlion raw main figures forecast example png finally we quantitatively evaluate the model smape measures the error of the prediction on a scale of 0 to 100 lower is better while msis evaluates the quality of the 95 confidence band on a scale of 0 to 100 lower is better python evaluate the model s predictions quantitatively from scipy stats import norm from merlion evaluate forecast import forecastmetric compute the smape of the predictions 0 to 100 smaller is better smape forecastmetric smape value ground truth test data predict test pred compute the msis of the model s 95 confidence interval 0 to 100 smaller is better lb timeseries from pd test pred to pd norm ppf 0 025 test err to pd values ub timeseries from pd test pred to pd norm ppf 0 975 test err to pd values msis forecastmetric msis value ground truth test data predict test pred insample train data lb lb ub ub print f smape smape 4f msis msis 4f smape 4 1944 msis 18 9331 evaluation and benchmarking one of merlion s key features is an evaluation pipeline that simulates the live deployment of a model on historical data this enables you to compare models on the datasets relevant to them under the conditions that they may encounter in a production environment our evaluation pipeline proceeds as follows 1 train an initial model on recent historical training data designated as the training split of the time series 1 at a regular interval e g once per day retrain the entire model on the most recent data this can be either the entire history of the time series or a more limited window e g 4 weeks 1 obtain the model s predictions anomaly scores or forecasts for the time series values that occur between re trainings you may customize whether this should be done in batch predicting all values at once streaming updating the model s internal state after each data point without fully re training it or some intermediate cadence 1 compare the model s predictions against the ground truth labeled anomalies for anomaly detection or the actual time series values for forecasting and report quantitative evaluation metrics we provide scripts that allow you to use this pipeline to evaluate arbitrary models on arbitrary datasets for example invoking shell script python benchmark anomaly py dataset nab realawscloudwatch model isolationforest retrain freq 1d will evaluate the anomaly detection performance of the isolationforest retrained once a day on the realawscloudwatch subset of the nab dataset similarly invoking shell script python benchmark forecast py dataset m4 hourly model ets will evaluate the batch forecasting performance i e no retraining of ets on the hourly subset of the m4 dataset you can find the results produced by running these scripts in the experiments section of the technical report https arxiv org abs 2109 09265 technical report and citing merlion you can find more details in our technical report https arxiv org abs 2109 09265 if you re using merlion in your research or applications please cite using this bibtex article bhatnagar2021merlion title merlion a machine learning library for time series author aadyot bhatnagar and paul kassianik and chenghao liu and tian lan and wenzhuo yang and rowan cassius and doyen sahoo and devansh arpit and sri subramanian and gerald woo and amrita saha and arun kumar jagota and gokulakrishnan gopalakrishnan and manpreet singh and k c krithika and sukumar maddineni and daeki cho and bo zong and yingbo zhou and caiming xiong and silvio savarese and steven hoi and huan wang year 2021 eprint 2109 09265 archiveprefix arxiv primaryclass cs lg | time-series anomaly-detection forecasting machine-learning benchmarking automl ensemble-learning | ai |
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Kathamo | kathamo kathamo is a minimalist css framework for rapid amp mobile friendly development kathamo has a few easy ways to quickly get started each one appealing to a different skill level and use case deprecated this project is not actively maintained | front_end |
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rtos | rtos a very simple real time operating system for the arm cortex m4 ti msp432 this rtos was developed as a project for ut rtbn 12 01x a course on realtime bluetooth networks on edx org https courses edx org courses course v1 utaustinx ut rtbn 12 01x 3t2016 info note that this project does not compile as is this is just a stash of the source files i wrote during the course each lab is on a separate branch | os |
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junior | junior a framework for building html5 mobile apps with a native look and feel check out the github page http justspamjustin github com junior | front_end |
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