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A new kind of NURBS representation for periodic curves is introduced. The method for periodic curves is extended to derive a compact and symmetric representation of the sphere or the ellipsoid using a piecewise bi-quadratic NURBS surface with only eight distinct control vertices.

['Kaihuai Qin', 'Wenping Wang', 'Zesheng Tang']

Representing spheres and ellipsoids using periodic NURBS surfaces with fewer control vertices

Today's feature-rich multimedia products require embedded system solution with complex System-on-Chip (SoC) to meet market expectations of high performance at a low cost and lower energy consumption. The memory architecture of the embedded system strongly influences these parameters. Hence the embedded system designer performs a complete memory architecture exploration. This problem is a multi-objective optimization problem and can be tackled as a two-level optimization problem. The outer level explores various memory architecture while the inner level explores placement of data sections (data layout problem) to minimize memory stalls. Further, the designer would be interested in multiple optimal design points to address various market segments. However, tight time-to-market constraints enforces short design cycle time. In this paper we address the multi-level multi-objective memory architecture exploration problem through a combination of Multi-objective Genetic Algorithm (Memory Architecture exploration) and an efficient heuristic data placement algorithm. At the outer level the memory architecture exploration is done by picking memory modules directly from a ASIC memory Library. This helps in performing the memory architecture exploration in a integrated framework, where the memory allocation, memory exploration and data layout works in a tightly coupled way to yield optimal design points with respect to area, power and performance. We experimented our approach for 3 embedded applications and our approach explores several thousand memory architecture for each application, yielding a few hundred optimal design points in a few hours of computation time on a standard desktop

['T.S. Rajesh Kumar', 'C. P. Ravikumar', 'R. Govindarajan']

MAX: A Multi Objective Memory Architecture eXploration Framework for Embedded Systems-on-Chip

Vehicular Ad-hoc Networks (VANETs) are the special class of Mobile Ad-hoc Networks (MANETs) with high mobility and frequent changes of topology. Clustering is applied in VANETs to divide the network into smaller groups of mobile vehicles and improve routing, information dissemination and data gathering. In this paper, we propose a 2-layer stable clustering scheme based on adaptive multiple metric combining both the features of static and dynamic clustering methods. The cluster head is selected among the cluster members based on a new multiple metric called suitability value. It is derived from both mobility metrics such as relative speed, position and time to leave the road segment and Quality of Service metrics including available bandwidth, neighborhood degree and RSU link quality. Due to the proposed adaptive metric, the higher cluster stability as well as QoS is achieved. The simulation results clarify effectiveness of our proposed method in a highway scenario and show that our technique has better results and provides more stable cluster structure compared with the other related methods.

['Hamid Reza Arkian', 'Reza Ebrahimi Atani', 'Atefe Pourkhalili', 'Saman Kamali']

A Stable Clustering Scheme Based on Adaptive Multiple Metric in Vehicular Ad-hoc Networks

Bicircular Matroid Designs.

['Torina Lewis', 'Jennifer McNulty', 'Nancy Ann Neudauer', 'Talmage James Reid', 'Laura Sheppardson']

Bicircular Matroid Designs.

Throughout various complex processes within hospitals, context-aware services and applications can help to improve the quality of care and reduce costs. For example, sensors and radio frequency identification (RFID) technologies for e-health have been deployed to improve the flow of material, equipment, personal, and patient. Bed tracking, patient monitoring, real-time logistic analysis, and critical equipment tracking are famous applications of real-time location systems (RTLS) in hospitals. In fact, existing case studies show that RTLS can improve service quality and safety, and optimize emergency management and time critical processes. In this paper, we propose a robust system for position and orientation determination of equipment. Our system utilizes passive (RFID) technology mounted on flooring plates and several peripherals for sensor data interpretation. The system is implemented and tested through extensive experiments. The results show that our system's average positioning and orientation measurement outperforms existing systems in terms of accuracy. The details of the system as well as the experimental results are presented in this paper.

['Ali Asghar Nazari Shirehjini', 'Abdulsalam Yassine', 'Shervin Shirmohammadi']

Equipment Location in Hospitals Using RFID-Based Positioning System

This study was to systematically comprehend water quality status and its spatial pattern in Yancheng region, north of Jiangsu Province. According to the principle of fuzzy synthetic evaluation and GIS technology, water quality of the Yancheng region was analyzed based on 5 parameters which were selected from 39 monitoring sections. The spatial patterns of evaluation results of regional water quality was obtained to provide a Visual expression. The results indicated that river water quality varied significantly with different areas, the water quality of urban districts were inferior to that of rural areas; the primary contaminated rivers were Chuanchanghe and Xinyanggang; the water quality of upstream rivers inflow was not good, and only one of the six monitoring sections reached the functional zoning requirements. The water quality map could be used to identify the key water pollution area and put forward pollution prevention and management measures.

['Huihua Lv', 'Feng Zhou']

Identification of the Yancheng region water quality using GIS and fuzzy synthetic evaluation approach

The Online Social Network (OSN) sites have been getting more and more popular in recent years and there are interests of having a tool to automatically retrieve and analyze the information in order to understand their related social behavior. This paper presents a framework of D-miner Cloud (DMC) based on a cloud architecture which can provide collection of the information from heterogeneous OSN sites, managing and analyzing the collected information afterwards. It has 5 components consisting of frontend devices, service gateway, service unit, central repository and OSN sites. We present the approach to implement the framework, integrate DMC and the Application Program Interfaces (API) of OSN sites, organize the communications in DMC framework and implement the mobile frontend design.

['Li Ho Leung', 'Vincent Ng', 'Chen Chen']

Analyzing social networks with D-miner Cloud

Discrete Mathematics Software for K-12 Education.

['Nathaniel Dean', 'Yanxi Liu']

Discrete Mathematics Software for K-12 Education.

Recent years have witnessed the proliferation of mobile crowd sensing (MCS) systems that leverage the public crowd equipped with various mobile devices (e.g., smartphones, smartglasses, smartwatches) for large scale sensing tasks. Because of the importance of incentivizing worker participation in such MCS systems, several auction-based incentive mechanisms have been proposed in past literature. However, these mechanisms fail to consider the preservation of workers' bid privacy. Therefore, different from prior work, we propose a differentially private incentive mechanism that preserves the privacy of each worker's bid against the other honest-but-curious workers. The motivation of this design comes from the concern that a worker's bid usually contains her private information that should not be disclosed. We design our incentive mechanism based on the single-minded reverse combinatorial auction. Specifically, we design a differentially private, approximately truthful, individual rational, and computationally efficient mechanism that approximately minimizes the platform's total payment with a guaranteed approximation ratio. The advantageous properties of the proposed mechanism are justified through not only rigorous theoretical analysis but also extensive simulations.

['Haiming Jin', 'Lu Su', 'Bolin Ding', 'Klara Nahrstedt', 'Nikita Borisov']

Enabling Privacy-Preserving Incentives for Mobile Crowd Sensing Systems

With the development of mobile networks and positioning technologies, location based service is becoming more and more popular, such as location-aware emergency response, advertisement, and car navigation system etc. However, while people enjoy more convenient life provided by location based services, their location privacy may leak. To tackle this problem, many researchers propose different ways to make users' privacy preserving and most of them focus on how to confuse users' true identities, or hide users' exact position while a user is in a cloaking square. The representative method is K-anonymity method which requires not less than k users in the same square when a location based service request occurs. In case there are not enough users in this cloaking square, the condition of the k-anonymity is not satisfied and location privacy would be leak. In this paper, we would tackle the problem of location privacy in a different way by predicating a safe path to users. Our objective is to provide more guarantee of privacy preserving for users under the K-anonymity criteria. We propose a path predicting algorithm from a user's current position to his/her destination. Every point on such path satisfies a location privacy policy under K-anonymity criteria. We also consider an upper threshold so as to balance privacy requirement and performance. Furthermore, the path would be dynamic adjusted according to users' movement and environment changes. Experiments are performed to verify our method and the experiment results show that this method is correct and efficient.

['Guangjun Ji', 'Yuqing Sun', 'Xiaojun Ma']

Path planning for privacy preserving in location based service

In this paper, we propose an intelligent cane developed based on passive robotics concept for supporting the elderly and the disabled persons who have difficulty walking. The Intelligent Passive Cane (IP Cane) is controlled by servo brakes attached to the wheels and intrinsically safe for humans, because it cannot move unintentionally, i.e., it has no driving actuators. In addition, the IP Cane provides many kinds of functions by appropriately controlling the torque of wheels with servo brakes. In this paper, we propose an environmentally adaptive motion control algorithm that provides path following function, and a human adaptive motion control algorithm that changes motion characteristic of IP Cane to adapt to user difficulty and states.

['Shinji Suzuki', 'Yasuhisa Hirata', 'Kazuhiro Kosuge']

Development of Intelligent Passive Cane controlled by servo brakes

Intensity Estimation of the Real-World Facial Expression

['Yan Gao', 'Shan Li', 'Weihong Deng']

Intensity Estimation of the Real-World Facial Expression

Predictive modeling is the art of building statistical models that forecast probabilities and trends of future events. It has broad applications in industry across different domains. Some popular examples include user intention predictions, lead scoring, churn analysis, etc. In this tutorial, we will focus on the best practice of predictive modeling in the big data era and its applications in industry, with motivating examples across a range of business tasks and relevance products. We will start with an overview of how predictive modeling helps power and drive various key business use cases. We will introduce the essential concepts and state of the art in building end-to-end predictive modeling solutions, and discuss the challenges, key technologies, and lessons learned from our practice, including case studies of LinkedIn feed relevance and a platform for email response prediction. Moreover, we will discuss some practical solutions of building predictive modeling platform to scale the modeling efforts for data scientists and analysts, along with an overview of popular tools and platforms used across the industry.

['Qiang Zhu', 'Songtao Guo', 'Paul Ogilvie', 'Yan Liu']

Business Applications of Predictive Modeling at Scale

The performance of GMSK/DS spread-spectrum signaling with binary phase-shift-keying and two-bit differential detection operating in a fast Rayleigh frequency dispersive mobile channel is investigated. A generalized channel model, that takes into consideration the presence of faded cochannel interference signals, is used for analysis. Closed form expressions are derived for the average error probability and are numerically evaluated for many channel conditions. The results clearly show that the incorporation of DS signaling, with relatively small processing gain, highly improves the performance of GMSK in severe channel degradation environments.

['Said E. El-Khamy', 'El-Sayed A. Youssef', 'Abbas A. Elshamly']

GMSK/DS spread-spectrum signaling with two-bit differential detection over mobile channels with frequency-selective fading

Millimeter wave (mmWave) communications have been postulated as one of the most disruptive technologies for future 5G systems. Among mmWave bands the 60-GHz radio technology is specially suited for ultradense small cells and mobile data offloading scenarios. Many challenges remain to be addressed in mmWave communications but among them deafness, or misalignment between transmitter and receivers beams, and interference management lie among the most prominent ones. In the recent years, scenarios considering negligible interference on mmWave resource allocation have been rather common in literature. To this end, interestingly, many open issues still need to be addressed such as the applicability of noise-limited regime for mmWave. Furthermore, in mmWave the beam-steering mechanism imposes a forced silence period, in the course of which no data can be conveyed, that should not be neglected in throughput/delay calculations. This paper introduces mmWave enabled Small Cell Networks (SCNs) with relaying capabilities where as a result of a coordinated meta-heuristically optimized beamwidth/alignment-delay approach overall system throughput is optimized. Simulations have been conveyed for three transmitter densities under TDMA and naive 'all-on' scheduling producing average per node throughput increments of up to 248%. The paper further elaborates on the off-balancing impact of alignment delay and time-multiplexing strategies by illustrating how the foreseen transition that increasing the number of transmitters produces in the regime of a fixed-node size SCN in downlink operation fades out by a poor choice in the scheduling strategy.

['Cristina Perfecto', 'Javier Del Ser', 'Muhammad Ikram Ashraf', 'Miren Nekane Bilbao', 'Mehdi Bennis']

Beamwidth Optimization in Millimeter Wave Small Cell Networks with Relay Nodes: A Swarm Intelligence Approach

The paper presents the methodology of investigation of influence of grinding regimes on surface layer tension state. The mathematical model of creating the final tension in part, based on full factorial experiment is described. The main values of factors are chosen close to practical regimes of grinding for a given materials and intervals for factors changes are calculated from the real process conditions. The estimated parameters and their accuracy are verified by means of Student and Fisher statistical criterion. As the result of investigation is determined that the final stresses of surface after grinding depends mainly on feed.

['W. Hałas', 'V. Taranenko', 'Antoni Swic', 'Georgij Taranenko']

Investigation of Influence of Grinding Regimes on Surface Tension State

This article presents a work-in-progress version of a Dublin Core Application Profile (DCAP) developed to serve the Social and Solidarity Economy (SSE). Studies revealed that this community is interested in implementing both internal interoperability between their Web platforms to build a global SSE e-marketplace, and external interoperability among their Web platforms and external ones. The Dublin Core Application Profile for Social and Solidarity Economy (DCAP-SSE) serves this purpose. SSE organisations are submerged in the market economy but they have specificities not taken into account in this economy. The DCAP-SSE integrates terms from well-known metadata schemas, Resource Description Framework (RDF) vocabularies or ontologies, in order to enhance interoperability and take advantage of the benefits of the Linked Open Data ecosystem. It also integrates terms from the new essglobal RDF vocabulary which was created with the goal to respond to the SSE-specific needs. The DCAP-SSE also integrates five new Vocabulary Encoding Schemes to be used with DCAP-SSE properties. The DCAP development was based on a method for the development of application profiles (Me4MAP). We believe that this article has an educational value since it presents the idea that it is important to base DCAP developments on a method. This article shows the main results of applying such a method.

['Mariana Curado Malta', 'Ana Alice Baptista', 'Cristina Parente']

A DCAP for the social and solidarity economy

Graph databases implementing the property graph model provide schema-flexible storage and support complex, expressive queries like shortest path, reachability, and graph isomorphism queries. However, both the flexibility and expressiveness in these queries come with additional costs: queries can result in an unexpected, empty answer. To understand the reason of an empty answer, a user normally has to create alternative queries, which is a cumbersome and time-consuming task. To address this, we introduce di↵-queries, a new kind of graph queries, that give an answer about which part of a query graph is represented in a data graph and which part is missing. We propose a new algorithm for processing di↵-queries, which detects maximum common subgraphs between a query graph and a data graph and computes the di↵erence between them. In addition, we present several extensions and optimizations for an established maximum common subgraph algorithm for processing property graphs, which are the foundation of state of the art graph databases.

['Elena Vasilyeva', 'Maik Thiele', 'Christof Bornhövd', 'Wolfgang Lehner']

GraphMCS: Discover the Unknown in Large Data Graphs

As a key component of intelligent transport system (ITS), vehicular communication network (VCN) is expected to reduce traffic accidents by providing more information to drivers via wireless communication. However, it remains unknown how VCN affects traffic accident probabilities. Given a highway scenario where vicious rear-end collision accidents happen, this paper investigates the impact of VCN on the rear-end collision probability. Considering a three-vehicle chain on highway and assuming that VCN conveys braking messages, vehicle behaviors are analyzed. Based on these analyses, the average collision probability of the concerned vehicle can be derived as a function of the communication success probability and driving parameters such as reaction time and deceleration. The analyses show that the average distance of adjacent vehicles is critical to reduce the probability of collision, especially when there is no VCN. When VCN is introduced, the collision probability could be reduced in two ways. One is that the reaction time of the vehicle is decreased and the other is that VCN could provide more information to the vehicle so that it can take precautions to avoid collision. Moreover, due to the relatively short distance of interest (i.e., less than 500 meters) and favorable wireless channel conditions on highway, the communication between vehicles always success and the collision probability with non-ideal communication can be reasonably approximated by that with ideal communication. These analytical results are verified by numerical computation and simulations. It is also shown that given a transmit power of 10dBm, aided by VCN, the rear-end collision probability of the concerned vehicle on highway can be significantly reduced by 70% compared to that without communications.

['Hang Liu', 'Yiqing Zhou', 'Lin Tian', 'Jinglin Shi']

How Can Vehicular Communication Reduce Rear-End Collision Probability on Highway

An Algorithm to Construct Greedy Drawings of Triangulations

['Patrizio Angelini', 'Fabrizio Frati', 'Luca Grilli']

An Algorithm to Construct Greedy Drawings of Triangulations

Concerns have been raisedabout the decreased ability of Wikipedia to recruit editors and in to harness the effort of contributors to create new articles and improve existing articles. But, as Marwell & Oliver explained,in collective projects, in the initial stage of the project, people are few and efforts costly; in the diffusion phase, the number of participants grows as their efforts are rewarding; and in the mature phase, some inefficiency may appear as the number of contributors is more than the work requires. In this paper, thanks to original data we extract from 36 of the main language projects, we compare the efficiency of Wikipedia projects in different languages and at different states of development to examine this effect.

['Kevin Crowston', 'Nicolas Jullien', 'Felipe Ortega']

Is Wikipedia Inefficient? Modelling Effort and Participation in Wikipedia

Summary form only given. We analyze the average-case performance of an online scheduling algorithm for independent parallel tasks. We develop a method to calculate an analytical asymptotic average-case performance bound for arbitrary probability distribution of task sizes. In particular, we show that when task sizes are uniformly distributed in the range [1..C], an asymptotic average-case performance bound of M-(3-(1+1/C)/sup C+1/)C-1 can be achieved, where M is the number of processors. We also present extensive numerical and simulation data to demonstrate the accuracy of our analytical bound.

['Keqin Li']

Average-case performance analysis and validation of online scheduling of independent parallel tasks

In the paper, we introduce a kind of method to solve the nonlinear filtering problem. Firstly, we review the basic filtering problem and the reduction from robust Duncan-Mortensen-Zakai equation to Kolmogorov equation. Then we use the difference discrete method to solve the Kolmogorov equation. The result is given to prove that the solution of the difference scheme convergences pointwise to the solution of the initial-value problem of the Kolmogorov equation. At last, the numerical results show that the numerical method can give the exact result.

['Zhen Liu', 'Fangfang Dong', 'Luwei Ding']

Numerical Results of Nonlinear Filtering Problem from Yau-Yau Method

Governance Mechanisms as Substitutes and Complements – A Dynamic Perspective on the Interplay between Contractual and Relational Governance

['Thomas L. Huber', 'Thomas A. Fischer', 'Jens Dibbern']

Governance Mechanisms as Substitutes and Complements – A Dynamic Perspective on the Interplay between Contractual and Relational Governance

We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility measures. We then consider one application of plausibility measures: default reasoning. In recent years, a number of different semantics for defaults have been proposed, such as preferential structures, /spl epsiv/-semantics, possibilistic structures, and /spl kappa/-rankings, that have been shown to be characterized by the same set of axioms, known as the KLM properties. While this was viewed as a surprise, we show here that it is almost inevitable. In the framework of plausibility measures, we can give a necessary condition for the KLM axioms to be sound, and an additional condition necessary and sufficient to ensure that the KLM axioms are complete. This additional condition is so weak that it is almost always met whenever the axioms are sound. In particular, it is easily seen to hold for all the proposals made in the literature. Finally, we show that plausibility measures provide an appropriate basis for examining first-order default logics.

['Nir Friedman', 'Joseph Y. Halpern']

Plausibility measures and default reasoning: an overview

Transmitter diversity in the downlink of code-division multiple-access (CDMA) systems achieves similar performance gains to the mobile-station receiver diversity without the complexity of a mobile-station receiver antenna array. Pre-RAKE precoding at the transmitter can be employed to achieve the multipath diversity without the need of the RAKE receiver at the mobile station. We examine feasibility of several transmitter diversity techniques and precoding for the third-generation wideband CDMA (WCDMA) systems. In particular, selective transmit diversity, transmit adaptive array and space-time pre-RAKE (STPR) techniques are compared. It is demonstrated that the STPR method is the optimal method to combine antenna diversity and temporal precoding. This method achieves the gain of maximum ratio combining of all space and frequency diversity branches when perfect channel state information is available at the transmitter. We employ the long range fading prediction algorithm to enable transmitter diversity techniques for rapidly time varying multipath fading channels.

['Secin Guncavdi', 'Alexandra Duel-Hallen']

Performance analysis of space-time transmitter diversity techniques for WCDMA using long range prediction

A Telecube is a cubic module that has six prismatic degrees of freedom whose sides can expand more than twice its original length and has the ability to magnetically (de)attach to other modules. Many of these modules can be connected together to form a modular self-reconfigurable robot. The paper presents the intended functions, discusses the physical requirements of the modules and describes two key mechanical components: a compact telescoping linear actuator and a switching permanent magnet device.

['John W. Suh', 'Samuel B. Homans', 'Mark Yim']

Telecubes: mechanical design of a module for self-reconfigurable robotics

In this paper, we propose a fast algorithm for principal component analysis (PCA) dealing with large high-dimensional data sets. A large data set is firstly divided into several small data sets. Then, the traditional PCA method is applied on each small data set and several eigenspace models are obtained, where each eigenspace model is computed from a small data set. At last, these eigenspace models are merged into one eigenspace model which contains the PCA result of the original data set. Experiments on the FERET data set show that this algorithm is much faster than the traditional PCA method, while the principal components and the reconstruction errors are almost the same as that given by the traditional method.

['Liang Liu', 'Yunhong Wang', 'Qian Wang', 'Tieniu Tan']

Fast Principal Component Analysis using Eigenspace Merging

The paper presents a schema repository, an original repository containing different kinds of database schemas. The repository is part of a multidisciplinary approach for schema evolution called the predictive approach for database evolution. The schema repository has a dual role in the approach: (1) During the data-mining process, the repository identifies and analyzes trends on collected schemas belonging to the same domain. (2) The repository is used in the building of the requirements ontology - a domain ontology that contributes in the database design and its evolution. This paper presents both the design and a heuristic-based method to populate such a repository

['Hassina Bounif', 'Rachel Pottinger']

Schema Repository for Database Schema Evolution

Language-Independent Sentiment Analysis Using Subjectivity and Positional Information

['Veselin Raychev', 'Preslav Nakov']

Language-Independent Sentiment Analysis Using Subjectivity and Positional Information

Unwanted and malicious messages dominate email traffic and pose a great threat to the utility of email communications. Reputation systems have been getting momentum as the solution. Such systems extract email senders behavior data based on global sending distribution, analyze them and assign a value of trust to each IP address sending email messages. We build two models for the classification purpose. One is based on support vector machines (SVM) and the other is random forests(RF). Experimental results show that either classifier is effective. RF is slightly more accurate, but more expensive in terms of both time and space. SVM produces similar accuracy in a much faster manner if given modeling parameters. These classifiers can contribute to a reputation system as one source of analysis and increase its accuracy.

['Yuchun Tang', 'Sven Krasser', 'Yuanchen He', 'Weilai Yang', 'Dmitri Alperovitch']

Support Vector Machines and Random Forests Modeling for Spam Senders Behavior Analysis

After reviewing the information geometric channel identification algorithm (IGID) (A. Zia et al., 2003), the application of the algorithm for semi-blind identification of the MIMO channel with Gaussian input sources is discussed. The method is developed based on the results from information geometry; specifically, the alternating projections theorem first proved by Csiszar and G. Tusnady (1984) which provides an iterative method for minimizing the distance between two sets of probability distributions. Also, an EM-type identification algorithm (EM-MCMC) for which the necessary expectation computations are performed using Markov-chain Monte-Carlo (MCMC) method is introduced. The comparative analysis of channel identification using two methods for MIMO systems with ISI-free flat-fading channels is given. It is shown that the IGID method has a similar performance while benefiting from an analytical solution. Thus, complex multidimensional integrations usually necessary in similar EM-type methods are avoided. This characteristic provides very fast computation times relative to previous EM-type algorithms.

['Amin Zia', 'James P. Reilly', 'Shahram Shirani']

Information geometric approach to channel identification: a comparison with EM-MCMC algorithm

We derived an integral equation for reproducing the sound field of a virtual source inside an array of loudspeakers with reduced radiation to the outside. Reproduction of a sound field over a finite interior region inevitably generates sound waves that propagate outside the region. This undesirable radiation is reflected from walls and can induce artifacts in the interior region. In principle, the Kirchhoff-Helmholtz (KH) integral can be used to reproduce the interior sound field from an exterior virtual source without any external radiation. However, if there is a virtual source inside the array, the integral formula does not explicitly demonstrate how one can reproduce the sound field or minimize the external radiation. In this work, we derive an explicit formula for reproducing a sound field with minimal external radiation when a virtual source is located inside a loudspeaker array. The theory shows that external radiation can be effectively reduced without solving any inverse problem. The proposed formula follows the form of the KH integral and thus requires monopole and dipole sources. Although dipole sources are difficult to build in practice, the theory predicts that sound field reproduction with minimal external radiation is possible and that the room dependency of the sound field reproduction system can be decreased.

['Jung-Woo Choi', 'Yang-Hann Kim']

Sound Field Reproduction of a Virtual Source Inside a Loudspeaker Array With Minimal External Radiation

Remembering Nat Durlach

['Mel Slater']

Remembering Nat Durlach

Ground Truth 1995–2005

['John Pickles']

Ground Truth 1995–2005

Visual attention of human being refers to the process of selectively choosing a set of relevant visual information for further processing. Human eyes are always exposed to enormous amount of visual information, not all of which are relevant to the current mental/behavioral state. The attention system helps to focus on a relevant region of a scene or an object of interest and ease the information processing. This paper proposes a novel probabilistic model of visual attention using recursive Bayes filter and Gaussian Adaptive Resonance Theory (ART) while mimicking some of the major aspects of primates visual attention system (albeit reduced complexity). The target application of the proposed model is intelligent autonomous agent namely, a humanoid robot. The proposed model adopts the propositions of `Biased Competitive Hypothesis' [1]. Such a model will allow a humanoid robot to autonomously engage its attention to perceptually interesting and/or behaviorally relevant stimuli and learn about it. Preliminary experimental results demonstrate different aspects of the proposed visual attention model.

['Momotaz Begum', 'George K. I. Mann', 'Raymond G. Gosine']

A Biologically Inspired Bayesian Model of Visual Attention for Humanoid Robots

Recently, the dense binary pixel Gigavision camera had been introduced, emulating a digital version of the photographic film. While seems to be a promising solution for HDR imaging, its output is not directly usable and requires an image reconstruction process. In this work, we formulate this problem as the minimization of a convex objective combining a maximum-likelihood term with a sparse synthesis prior. We present MLNet - a novel feed-forward neural network, producing acceptable output quality at a fixed complexity and is two orders of magnitude faster than iterative algorithms. We present state of the art results in the abstract.

['Or Litany', 'Tal Remez', 'Alexander M. Bronstein']

Image reconstruction from dense binary pixels

Influential users or leaders in a social network play important roles in viral marketing by spreading news quickly to a large number of people. Hence, various organizations aim to discover these leaders as campaign targets for advertisement so as to maximize customer reachability. Existing approaches detect leaders from a static social network. However, as social networks are evolving, detecting leaders from dynamic streams of social network data is in demand. In this paper, we propose a sliding window-based leader detection (SWLD) algorithm for discovering leaders from streams of user actions in social networks. Experimental results show that SWLD is accurate, requires short runtime and a small amount of memory space.

['Quazi Marufur Rahman', 'Anna Fariha', 'Amit Mandal', 'Chowdhury Farhan Ahmed', 'Carson Kai-Sang Leung']

A Sliding Window-Based Algorithm for Detecting Leaders from Social Network Action Streams

Fair bandwidth allocation is critical in wireless communication networks, since the wireless channel is often shared by a number of stations in the same neighborhood. With fair scheduling, bandwidth can be shared by competing flows in proportion to their assigned weights. In this paper, we propose a credit-based distributed protocol for fair allocation of bandwidth in IEEE 802.11 wireless LANs. Our protocol is derived from the distributed coordination function in the IEEE 802.11 medium access control (MAC) protocol. Analytical and simulation results demonstrate that the protocol achieves the desired bandwidth allocations. An important feature of our protocol is its backward compatibility, which allows legacy IEEE 802.11 stations to coexist with stations adopting the new MAC protocol.

['Y. Q. Wu', 'Sonia Fahmy']

A credit-based distributed protocol for long-term fairness in IEEE 802.11 single-hop networks

This paper presents an approach for the modeling and formal validation of high-performance systems. The approach relies on the repetitive model of computation used to express the parallelism of such systems within the Gaspard framework, which is dedicated to the codesign of high-performance system-on-chip. The system descriptions obtained with this model are then projected on the synchronous model of computation. The result of this projection consists of an equational model that allows one to formally analyze clock synchronizability issues so as to guarantee the reliable deployment of systems on platforms.

['Abdoulaye Gamatié', 'Eric Rutten', 'Huafeng Yu', 'Pierre Boulet', 'Jean-Luc Dekeyser']

Modeling and Formal Validation of High-Performance Embedded Systems

Teaching Traffic Lights to Manage Themselves... and Protect the Environment.

['Dirk Helbing', 'Stefan Lämmer']

Teaching Traffic Lights to Manage Themselves... and Protect the Environment.

This paper presents a novel parametric vector quantization (PVQ) scheme as the secondary encoding to code perceptually salient percussive sounds such as drums in the time domain. It is deployed to improve the quality of service in the case of packet losses during percussive events. As a generalization and an improvement of our earlier system, the new scheme can achieve a better balance between bandwidth efficiency and error robustness. The proposed coding technique has been implemented with the MPEG-2 AAC (advanced audio coding) frame structure. Experimental results with music samples have shown the effectiveness of the proposed scheme.

['Ye Wang', 'Jian Tang', 'Ali Ahmaniemi', 'Markus Vaalgamaa']

Parametric vector quantization for coding percussive sounds in music

As the scale of Distributed Virtual Environments (DVEs) grows in terms of participants and virtual entities, using interest management schemes to reduce bandwidth consumption becomes increasingly common for DVE development. The interest matching process is essential for most of the interest management schemes which determines what data should be sent to the participants as well as what data should be filtered. However, if the computational overhead of interest matching is too high, it would be unsuitable for real-time DVEs for which runtime performance is important. This paper presents a new approach of interest matching which divides the workload of matching process among a cluster of computers. Experimental evidence shows that our approach is an effective solution for the real-time applications.

['Elvis S. Liu', 'Georgios K. Theodoropoulos']

A Parallel Interest Matching Algorithm for Distributed-Memory Systems

Top-k queries are widely studied for identifying a ranked set of the k most interesting objects based on the individual user preference. Reverse top-k queries are proposed from the perspective of the product manufacturer, which are essential for manufacturers to assess the potential market and impacts of their products. However, the existing approaches for reverse top-k queries are all based on the assumption that the underlying data are exact. Due to the intrinsic differences between uncertain and certain data, these methods are designed only in certain databases and cannot be applied to uncertain case directly. Motivated by this, in this paper, we firstly model the probabilistic reverse top-k queries in the context of uncertain data. Moreover, we formulate the challenging problem of processing queries that report l most favorite objects to users, where impact factor of an object is defined as the cardinality of the probabilistic reverse top-k query result set. For speeding up the query, we exploit several properties of probabilistic threshold top-k queries and probabilistic skyline queries to reduce the solution space of this problem. In addition, an upper bound of the potential users is estimated to reduce the cost of computing the probabilistic reverse top-k queries for the candidate objects. Furthermore, effective pruning heuristics are presented to further reduce the search space of query processing. Finally, efficient query algorithms are presented seamlessly with integration of the proposed pruning strategies. Extensive experiments demonstrate the efficiency and effectiveness of our proposed algorithms with various experimental settings.

['Guoqing Xiao', 'Kenli Li', 'Keqin Li']

Reporting L Most Favorite Objects in Uncertain Databases with Probabilistic Reverse Top-k Queries

In practical scenarios with random arrival and departure of primary users (PUs), existing simultaneous sensing and transmission schemes allocated the same weight to each sample, and did not consider low signal-to-noise ratio (SNR) situations. This paper proposes an adaptive weighted sensing scheme with simultaneous transmission for dynamic PU traffic. It uses a power function based on the corresponding sampling sequence and could reveal the actual PU state in near real time. The power exponent is further adjusted to the sensing situations to achieve lowest false alarm probability under a certain detection probability constraint. Then, an analytical model considering all possible PU state transitions is developed to evaluate achievable interference, throughput, and energy efficiency. Furthermore, the optimal frame duration yielding both optimal false alarm probability and throughput is computed. After that, a fast search algorithm is proposed to track the optimal duration at an exponential convergence rate. Simulation results are provided to validate the analytical model and demonstrate the improvement in low SNR. The results indicate that the proposed scheme can achieve lower false alarm probability and higher energy efficiency over a wide SNR range than that of the existing weighting schemes, which are based on probability, geometric sequence, and equal weighting.

['Min Deng', 'Bin-Jie Hu', 'Xiaohuan Li']

Adaptive Weighted Sensing With Simultaneous Transmission for Dynamic Primary User Traffic

In opportunistic networking, characterizing contact patterns between mobile users is essential for assessing feasibility and performance of opportunistic applications. There has been significant efforts in deriving this characterization, based on observations and trace analyses; however, most of the previously established results were obtained by studying contact opportunities at large spatial and temporal scales. Moreover, the user population is considered to be constant: no user can join or leave the system. Yet, there are many examples of scenarios which do not fully adhere to the previous assumption and cannot be accurately described at large scales. Urban environments, such as smaller city districts, are characterized by highly dynamic user populations. We believe that scenarios with varying population require further investigation. In this paper, we present a novel modeling approach to study operation of opportunistic applications in scenarios where the population size is subjected to frequent changes, that is, it exhibits churn. We examine two location-based content sharing schemes: a purely opportunistic case and an infrastructure-supported content sharing scheme, for which we provide stochastic models based on stochastic differential equations (SDEs). We validate our models in five scenarios: a city area, subway station, conference, campus, and a scenario with a synthetic mobility model and we show that the models provide good representations of the investigated scenarios.

['Ljubica Pajevic', 'Gunnar Karlsson']

Modeling opportunistic communication with churn

Conformal predictors are set predictors that are automatically valid in the sense of having coverage probability equal to or exceeding a given confidence level. Inductive conformal predictors are a computationally efficient version of conformal predictors satisfying the same property of validity. However, inductive conformal predictors have only been known to control unconditional coverage probability. This paper explores various versions of conditional validity and various ways to achieve them using inductive conformal predictors and their modifications. In particular, it discusses a convenient expression of one of the modifications in terms of ROC curves.

['Vladimir Vovk']

Conditional validity of inductive conformal predictors

Adaptive bitrate (ABR) streaming enables video users to adapt the playing bitrate to the real-time network conditions to achieve the desirable quality of experience (QoE). In this work, we propose a novel crowdsourced streaming framework for multi-user ABR video streaming over wireless networks. This framework enables the nearby mobile video users to crowdsource their radio links and resources for cooperative video streaming. We focus on analyzing the social welfare performance bound of the proposed crowdsourced streaming system. Directly solving this bound is challenging due to the asynchronous operations of users. To this end, we introduce a virtual time-slotted system with the synchronized operations, and formulate the associated social welfare optimization problem as a linear programming. We show that the optimal social welfare performance of the virtual system provides effective upper-bound and lower-bound for the optimal performance (bound) of the original asynchronous system, hence characterizes the feasible performance region of the proposed crowdsourced streaming system. The performance bounds derived in this work can serve as a benchmark for the future online algorithm design and incentive mechanism design.

['Lin Gao', 'Ming Tang', 'Haitian Pang', 'Jianwei Huang', 'Lifeng Sun']

Performance bound analysis for crowdsourced mobile video streaming

Shared access to airtime is a prominent mode of connectivity access in the developing world. We seek to understand airtime sharing among low-income microenterprises in India (small, low-capital businesses, such as flower sellers and milkmen), that constitute 90% of the total enterprises in India. We introduce social negotiation as the foundation of airtime sharing. We highlight negotiation mechanisms in the microenterprise, showing how shared resources are used towards personal interests amidst tensions and value conflicts, by adapting, modifying, subverting, and repurposing airtime. We then explore the design space of airtime and bandwidth sharing in low-income communities, including designing for negotiation and improving readability of airtime.

['Nithya Sambasivan', 'Edward Cutrell']

Understanding negotiation in airtime sharing in low-income microenterprises

A transmission policy for frequency-hopped spread-spectrum random-access communication systems in which the retransmission of a blocked packet at each station is determined as a function of that station's own collision experience is examined. For stability considerations and for channel throughput increase, the information packet is encoded by a Reed-Solomon code. An equilibrium analysis is used to show that undesirable bistable behaviour can be avoided if packets are rejected after a certain number of transmission attempts and the code rate is adjusted accordingly. The region of code rate and number of transmission attempt pairs that guarantees the network stability are investigated. The packet rejection probability, average packet delay, and maximum stable throughput are evaluated. >

['Sang Wu Kim']

Frequency-hopped spread-spectrum random access with retransmission cutoff and code rate adjustment

Data transmission using M-ary differential phase shift keying (MDPSK) over the nonselective Rayleigh fading channel with diversity reception is considered. While previous studies on error probability mostly assume no fading fluctuation, the author considers, exclusively, the case in which the fading process fluctuates from one symbol interval to the next. Exact bit error probability results for 2, 4, and 8 DPSK as well as tight upper bounds are derived. Some applications of the results are discussed. >

['Pooi Yuen Kam']

Bit error probabilities MDPSK over the nonselective Rayleigh fading channel with diversity reception

On the basis of n\geq 2 observations, confidence limits of the form X̄ \pm tS/ \sqrt{n} are constructed for the location (e.g., the median) of any distribution of known form with unknown location and dispersion (scale), where X̄ and S are the sample mean and "unbiased" standard deviation. Particular attention is given to the values of t needed for the Cauchy and uniform distributions. The latter t suffices for any (unknown) symmetric unimodal distribution if t \geq n - 1 . A table compares these values of t for n=2,3,4 , and 5 with those for the normal case, which are derived here very simply and are identical with those found by "Student." We are also able to include the case of a single observation (n=1) , where confidence intervals of various forms are made just wide enough for the least favorable dispersion. They, therefore, include the true location with at least but, in general, not exactly the desired probability; these intervals involve a predetermined value that plays a role reminiscent of but quite different from that of the prior distribution that would enter into a Bayesian analysis. In addition, upper confidence limits for the dispersion are constructed for n \geq 1 .

['Nelson M. Blachman', 'Robert E. Machol']

Confidence intervals based on one or more observations

A new tuning method for internal model controllers (IMCs) is presented. The parameters of an IMC can be structurally assigned to two groups: 1) parameters of the internal model and 2) parameters of the controller. The method described in this brief suggests a sequential tuning of the two parameter groups. For both groups, the parameter values are found by minimizing a predefined cost function. The optimization is run with a gradient-based minimization procedure where, analogously to the well-known iterative feedback tuning (IFT) scheme, the gradients are computed from signals obtained from closed-loop experiments. Thus, for the calculation of the gradient, the unknown plant is utilized, whereas other ?local? tuning methods suggest the replacement of the real plant by its model to calculate the gradient. The main advantages of the suggested algorithm are its inherent operation in the closed control loop and the fact that, for the tuning of the internal model, no information about the disturbance model is required. The method can be used either for an initial tuning of the controller or for autotuning during operation.

['Daniel Rupp', 'Lino Guzzella']

Iterative Tuning of Internal Model Controllers With Application to Air/Fuel Ratio Control

We present a performance model for an energy harvesting wireless sensor node in which data gathering and harvesting are slow random processes as compared to fast wireless communications. We assume that the system will use stored energy when collecting data in standby, and that energy will leak from capacitors and batteries. In the presence of these imperfections we derive the system's packet transmission capacity when its packet storage buffer and its energy storage unit have a finite capacity that may lead to both data packet overflows, and the loss of incoming energy in addition to standby losses. We also consider an infinite capacity model which operates in the presence of transmission errors due to channel noise and interference.

['Erol Gelenbe', 'Yasin Murat Kadioglu']

Energy loss through standby and leakage in energy harvesting wireless sensors

Elastic interaction models for active contours and surfaces

['Albert Chi Shing Chung', 'Yang Xiang', 'Jian Ye']

Elastic interaction models for active contours and surfaces

Chemical affinity involves the integration of two different types of interaction. One is the interaction operating between a pair of reactants while forming a chemical bond, and the other is the prior interaction between those reactants when they identify a reaction partner. The context of the environments under which chemical reactions proceed is identified by the interaction of the participating chemical reactants themselves unless the material process of internal measurement is substituted by theoretical artifacts in the form of imposed boundary conditions, as in the case, for example, of thermal equilibrium. The identification-interaction specific to each local participant serves as a preparation for the making of chemical bonds. The identification-interaction is intrinsically selective in precipitating those chemical bonds that are synthesized most rapidly among possible reactions. Once meta-stable products appear that mediate chemical syntheses and their partial decompositions without totally decomposing, those products would become selective because of their ongoing participation in the identification-interaction. One important natural example must have been the origin and evolution of life on Earth.

['Koichiro Matsuno', 'Stanley N. Salthe']

Chemical Affinity as Material Agency for Naturalizing Contextual Meaning

In less than five years, the number of mobile apps has grown exponentially, with more than 1 million available in the largest mobile app stores. One explanation for this growth could be the adoption of well-proven software engineering practices--in particular, software reuse despite the often conjectured lack of training among mobile app developers. A study of hundreds of thousands of Android apps across 30 different categories found substantial software reuse, indicating that while these apps benefit from increased productivity, they're also more dependent on the quality of the apps and libraries that they reuse.

['Israel J. Mojica', 'Bram Adams', 'Meiyappan Nagappan', 'Steffen Dienst', 'Thorsten Berger', 'Ahmed E. Hassan']

A Large-Scale Empirical Study on Software Reuse in Mobile Apps

Interest has been revived in the creation of a "bill of rights" for Internet users. This paper analyzes users' rights into ten broad principles, as a basis for assessing what users regard as important and for comparing different multi-issue Internet policy proposals. Stability of the principles is demonstrated in an experimental survey, which also shows that freedoms of users to participate in the design and coding of platforms appear to be viewed as inessential relative to other rights. An analysis of users' rights frameworks that have emerged over the past twenty years similarly shows that such proposals tend to leave out freedoms related to software platforms, as opposed to user data or public networks. Evaluating policy frameworks in a comparative analysis based on prior principles may help people to see what is missing and what is important as the future of the Internet continues to be debated.

['Todd Davies']

Digital Rights and Freedoms: A Framework for Surveying Users and Analyzing Policies

Pure Peer to Peer (P2P) network requires enhancing transportation of chunk video objects to the proxy server in the mesh network. The rapid growth of video on demand user brings congestion at the proxy server and on the overall network. The situation needs efficient content delivery procedure, to the video on demand viewer from the distributed storage. In general scenario, if the proxy server does not possess the required video stream or the chunk of that said video, then the same can be smoothly and rapidly streamed to the viewer. This paper has shown that multitier mesh shaped hybrid architecture composed of P2P and mesh architecture increase the number of requests served by the dynamic environment in comparison with the static environment. Optimized storage finding path search reduces the unnecessary query forward and hence increases the size of content delivery to the desired location.

['Soumen Kanrar', 'Niranjan Kumar Mandal']

Enhancement of video streaming in distributed hybrid architecture

Combined Congestion Control and Link Selection Strategies for Delay Tolerant Interplanetary Networks

['Igor Bisio', 'Tomaso de Cola', 'Fabio Lavagetto', 'Mario Marchese']

Combined Congestion Control and Link Selection Strategies for Delay Tolerant Interplanetary Networks

The treatment of patients with pituitary adenoma requires the assessment of various patient data by the clinician. Because of their heterogeneity, they are stored in different sub-information systems, limiting a fast and easy access. The objective of this paper is to apply and test the tools provided by the openEHR Foundation to model the patient data relevant for diagnosis and treatment of the disease with the future intention to implement a centralised standard-based information platform. This platform should support the clinician in the treatment of the disease and improve the information exchange with other healthcare institutions. Some results of the domain modeling, so far obtained, are presented, and the advantages of openEHR emphasized. The free tools and the large database of existing structured and standard archetypes facilitated the modeling task. The separation of the domain modeling from the application development will support the next step of development of the information platform.

['Claire Chalopin', 'Dirk Lindner', 'Stefan Kropf', 'Kerstin Denecke']

Archetype based patient data modeling to support treatment of pituitary adenomas.

microgrids (MGs) are a promising solution to global energy challenges. Robust and reliable operation while maximizing infeed from renewable sources and reducing the use of thermal generation are important objectives in the control of MGs. In this paper, two model predictive control strategies are applied to operate a grid-connected MG in the presence of bounded uncertainties in an optimal way. One is a certainty-equivalence and the other a minimax approach. They differ in the disturbance model used for renewable energy source infeed and load. To find an optimal operation strategy, a mixed-integer quadratic program is solved online. In a numerical case study, the results of two approaches are analyzed. The simulation shows, that compared to the performance of the certainty-equivalent case, the minimax approach is robust to disturbances and allows a secure operation of MGs in grid-connected mode.

['Han Zhou', 'Christian A. Hans', 'Weidong Zhang']

Minimax model predictive operation control of grid-connected microgrids

Rough sets theory has opened new trends for the development of the incomplete information theory. Inside this one, the notion of reduct is a very significant one, but to obtain a reduct in a decision system is an expensive computing process although very important in data analysis and knowledge discovery. Because of this, it has been necessary the development of different variants to calculate reducts. The present work look into the utility that offers rough sets model and information theory in feature selection and three methods are presented with the purpose of calculate good reducts. The first algorithm is MRSReduct, a variant of the method RSReduct; both methods consist of a greedy algorithm that uses heuristics to work out good reducts in acceptable times. In this paper we propose other method to find good reducts: RSRed*; this method combines several elements of rough set theory. The new methods are compared with others which are implemented inside pattern recognition, genetic algorithm and ant colony optimization algorithms and the results of the statistical tests are shown.

['Yailé Caballero', 'Delia Alvarez', 'Rafael Bello', 'María M. García']

Feature Selection Algorithms Using Rough Set Theory

With emerging multi-media wireless applications, there is a need for next-generation W-CDMA to be designed to support variable rate traffic. Several schemes have previously been proposed to support variable rate transmission, namely, variable spreading gain (VSG), multicode transmissions and fixed spreading gain (FSG). In this paper, a universal framework to evaluate and compare the various variable rate transmission schemes in terms of bit error rate (BER), power and required bandwidth is proposed. The framework also provides for the synthesis of the power assignment that delivers a specified BER to heterogeneous variable rate sources under each scheme.

['Pramod Immaneni', 'Jeffrey M. Capone']

A framework for analysis of VBR traffic over CDMA

Language and arithmetic are both lateralized to the left hemisphere in the majority of right-handed adults. Yet, does this similar lateralization reflect a single overall constraint of brain organization, such an overall "dominance" of the left hemisphere for all linguistic and symbolic operations? Is it related to the lateralization of specific cerebral subregions? Or is it merely coincidental? To shed light on this issue, we performed a "colateralization analysis" over 209 healthy subjects: We investigated whether normal variations in the degree of left hemispheric asymmetry in areas involved in sentence listening and reading are mirrored in the asymmetry of areas involved in mental arithmetic. Within the language network, a region-of-interest analysis disclosed partially dissociated patterns of lateralization, inconsistent with an overall "dominance" model. Only two of these areas presented a lateralization during sentence listening and reading which correlated strongly with the lateralization of two regions active during calculation. Specifically, the profile of asymmetry in the posterior superior temporal sulcus during sentence processing covaried with the asymmetry of calculation-induced activation in the intraparietal sulcus, and a similar colateralization linked the middle frontal gyrus with the superior posterior parietal lobule. Given recent neuroimaging results suggesting a late emergence of hemispheric asymmetries for symbolic arithmetic during childhood, we speculate that these colateralizations might constitute developmental traces of how the acquisition of linguistic symbols affects the cerebral organization of the arithmetic network.

['Philippe Pinel', 'Stanislas Dehaene']

Beyond hemispheric dominance: Brain regions underlying the joint lateralization of language and arithmetic to the left hemisphere

With the emergence of mobile multimedia services, such as unified messaging, click to dial, cross network multiparty conferencing and seamless multimedia streaming services, the fixed-mobile convergence and voice-data integration has started, leading to an overall Internet-Telecommunications merger. The IP multimedia subsystem (IMS) is considered as the next generation service delivery platform in this converge communication world. It consists of modular design with open interfaces and enables the flexibility for providing multimedia services over IP technology. At parallel this open based emerging technology has security challenges from multiple communication platforms like IP, SIP and RTP. In this article our objective is to develop security model to protect IMS service delivery platform (SDP) from different time independent attacks e.g. SQL injection and media flow attacks. These attacks ultimately downfall the value added services. At the end we shall present the performance results at Fokus Fraunhofer Testbed to see the proposed solution for real world applications.

['Muhammad Sher', 'Thomas Magedanz']

Protecting IP Multimedia Subsystem (IMS) Service Delivery Platform from Time Independent Attacks

This work proposes an advanced key-variable selecting method, the neural-network-based stepwise selection (NN-based SS) method, which can enhance the conjecture accuracy of the NN-based virtual metrology (VM) algorithms. Multi-regression-based (MR-based) SS method is widely applied in dealing with key-variable selecting problems despite that it may not guarantee finding the best model based on its selected variables. However, the variables selected by MR-based SS may be adopted as the initial set of variables for the proposed NN-based SS to reduce the SS process time. The backward elimination and forward selection procedures of the proposed NN-based SS are both performed by the designated NN algorithm used for VM conjecturing. Therefore, the key variables selected by NN-based SS will be more suitable for the said NN-based VM algorithm as far as conjecture accuracy is concerned. The etching process of semiconductor manufacturing is used as the illustrative example to test and verify the VM conjecture accuracy. One-hidden-layered back-propagation neural networks (BPNN-I) are adopted for establishing the NN models used in the NN-based SS method and the VM conjecture models. Test results show that the NN model created by the selected variables of NN-based SS can achieve better conjecture accuracy than that of MR-based SS. Simple recurrent neural networks (SRNN) are also tested and proved to be able to achieve similar results as those of BPNN-I.

['Tung-Ho Lin', 'Fan-Tien Cheng', 'Aeo-Juo Ye', 'Wei-Ming Wu', 'Min-Hsiung Hung']

A novel key-variable sifting algorithm for virtual metrology

We develop a Bayesian method that simultaneously registers and clusters functional data of interest. Unlike other existing methods, which often assume a simple translation in the time domain, our method uses a discrete approximation generated from the family of Dirichlet distributions to allow warping functions of great flexibility. Under this Bayesian framework, a MCMC algorithm is proposed for posterior sampling. We demonstrate this method via simulation studies and applications to growth curve data and cell cycle regulated yeast genes.

['Zizhen Wu', 'David B. Hitchcock']

A Bayesian method for simultaneous registration and clustering of functional observations

Refinement for Monadic Programs.

['Peter Lammich']

Refinement for Monadic Programs.

A system for the acquisition and analysis of the 3D mandibular movement to be used in dental medicine.

['Isa C. T. Santos', 'João Manuel R. S. Tavares', 'Joaquim Gabriel Mendes', 'Manuel Paulo']

A system for the acquisition and analysis of the 3D mandibular movement to be used in dental medicine.

Many sensor network applications require sensors' locations to function correctly. Despite the recent advances, location discovery for sensor networks in hostile environments has been mostly overlooked. Most of the existing localization protocols for sensor networks are vulnerable in hostile environments. The security of location discovery can certainly be enhanced by authentication. However, the possible node compromises and the fact that location determination uses certain physical features (e.g., received signal strength) of radio signals make authentication not as effective as in traditional security applications. This paper presents two methods to tolerate malicious attacks against beacon-based location discovery in sensor networks. The first method filters out malicious beacon signals on the basis of the "consistency" among multiple beacon signals, while the second method tolerates malicious beacon signals by adopting an iteratively refined voting scheme. Both methods can survive malicious attacks even if the attacks bypass authentication, provided that the benign beacon signals constitute the majority of the "consistent" beacon signals. This paper also presents the implementation of these techniques on MICA2 motes running TinyOS, and the evaluation through both simulation and field experiments. The experimental results demonstrate that the proposed methods are promising for the current generation of sensor networks.

['Donggang Liu', 'Peng Ning', 'Wenliang Kevin Du']

Attack-resistant location estimation in sensor networks

A Semantic Model for Personal Consent Management

['Özgü Can']

A Semantic Model for Personal Consent Management

Automated course recommendation can help deliver personalized and effective college advising and degree planning. Nearest neighbor and matrix factorization based collaborative filtering approaches have been applied to student-course grade data to help students select suitable courses. However, the student-course enrollment patterns exhibit grouping structures that are tied to the student and course academic features, which lead to grade data that are not missing at random (NMAR). Existing approaches for dealing with NMAR data, such as Response-aware and context-aware matrix factorization, do not model NMAR data in terms of the user and item features and are not designed with the characteristics of grade data in mind. In this work we investigate how the student and course academic features influence the enrollment patterns and we use these features to define student and course groups at various levels of granularity. We show how these groups can be used to design grade prediction and top-n course ranking models for neighborhood-based user collaborative filtering, matrix factorization and popularity-based ranking approaches. These methods give lower grade prediction error and more accurate top-n course rankings than the other methods that do not take domain knowledge into account.

['Asmaa Elbadrawy', 'George Karypis']

Domain-Aware Grade Prediction and Top-n Course Recommendation

Abstract: Distribution-free bootstrapping of the replicated responses of a given discreteevent simulation model gives bootstrapped Kriging (Gaussian process) metamodels; we require these metamodels to be either convex or monotonic. To illustrate monotonic Kriging, we use an M/M/1 queueing simulation with as output either the mean or the 90% quantile of the transient-state waiting times, and as input the traffic rate. In this example, monotonic bootstrapped Kriging enables better sensitivity analysis than classic Kriging; i.e., bootstrapping gives lower MSE and confidence intervals with higher coverage and the same length. To illustrate convex Kriging, we start with simulationoptimization of an (s, S) inventory model, but we next switch to a Monte Carlo experiment with a second-order polynomial inspired by this inventory simulation. We could not find truly convex Kriging metamodels, either classic or bootstrapped; nevertheless, our bootstrapped "nearly convex" Kriging does give a confidence interval for the optimal input combination.

['Jack P. C. Kleijnen', 'Ehsan Mehdad', 'W.C.M. van Beers']

Convex and Monotonic Bootstrapped Kriging

In spatial information data grid, the difference among metadata makes it difficult to re-organize data and share them. In this paper, a way named metadata adapter is proposed, to interpreter original metadata with different syntax and semantic rules to required metadata so that they can be organized as a distributed, heterogeneous, inherent features based, and one-stop served virtual remote sensing data catalogue. Based on the metadata adapter, SIG can build up a powerful and flexible data grid for spatial information applications. The experience of ldquoremote sensing data distribution system for WenChuan earthquake rescuingrdquo amazingly quick founding shows that metadata adapter is a powerful and economical way to solve the problem of metadata difference in spatial information data grid.

['Zhenchun Huang', 'Guoqing Li']

Metadata Adapters for Spatial Information Data Grid

This paper presents a method for designing semisupervised classifiers trained on labeled and unlabeled samples. We focus on a probabilistic semisupervised classifier design for multiclass and single-labeled classification problems and propose a hybrid approach that takes advantage of generative and discriminative approaches. In our approach, we first consider a generative model trained by using labeled samples and introduce a bias correction model, where these models belong to the same model family but have different parameters. Then, we construct a hybrid classifier by combining these models based on the maximum entropy principle. To enable us to apply our hybrid approach to text classification problems, we employed naive Bayes models as the generative and bias correction models. Our experimental results for four text data sets confirmed that the generalization ability of our hybrid classifier was much improved by using a large number of unlabeled samples for training when there were too few labeled samples to obtain good performance. We also confirmed that our hybrid approach significantly outperformed the generative and discriminative approaches when the performance of the generative and discriminative approaches was comparable. Moreover, we examined the performance of our hybrid classifier when the labeled and unlabeled data distributions were different.

['Akinori Fujino', 'Naonori Ueda', 'Kazumi Saito']

Semisupervised Learning for a Hybrid Generative/Discriminative Classifier based on the Maximum Entropy Principle

Human spinal cord injuries (SCI) disrupt the pathways between brain and spinal cord, resulting in substantial impairment and loss of function. Currently, we do not have the ability to precisely quantify the “functional” level of motor injury. The aim of this study is to determine if high-density surface electromyography imaging (SEI) can be used to characterize the location and extent of the spinal lesion. SEI is a safe and non-invasive technique, which uses several electrodes to provide a map of muscle activity. We applied the SEI technique to characterize muscle activity in individuals with chronic incomplete cervical SCI. Surface electromyogram signals (sEMG) from Biceps Brachii (BB) were recorded at submaximal levels (20%, 40%, and 60%) of maximum voluntary contractions (MVC) during isometric elbow flexion, shoulder flexion, and elbow abduction in two individuals with SCI. Through time-domain analysis of the collected data, we detected signs of de-innervation and re-innervations by analyzing the innervation zones (IZ) on the left and right BB muscles. We found that the distribution of IZs was different between the two sides. In addition, analysis of sEMG data collected at rest (no voluntary contraction) showed evidence of superficial active motor units that were active during rest (in the absence of spasms). These findings highlight the potential of SEI technique as a potential clinical tool to quantitatively describe the extent of the damage to motor spinal circuitry, and provide added precision to the clinical examinations and radiological findings.

['Babak Afsharipour', 'Milap S. Sandhu', 'Ghulam Rasool', 'Nina L. Suresh', 'William Z. Rymer']

Using surface electromyography to detect changes in innervation zones pattern after human cervical spinal cord injury

The pipelined adaptive Volterra filters (PAVFs) with a two-layer structure constitute a class of good low-complexity filters. They can efficiently reduce the computational complexity of the conventional adaptive Volterra filter. Their major drawbacks are low convergence rate and high steady-state error caused by the coupling effect between the two layers. In order to remove the coupling effect and improve the performance of PAVFs, we present a novel hierarchical pipelined adaptive Volterra filter (HPAVF)-based alternative update mechanism. The HPAVFs with hierarchical decoupled normalized least mean square (HDNLMS) algorithms are derived to adaptively update weights of its nonlinear and linear subsections. The computational complexity of HPAVF is also analyzed. Simulations of nonlinear system adaptive identification, nonlinear channel equalization, and speech prediction show that the proposed HPAVF with different independent weight vectors in nonlinear subsection has superior performance to conventional Volterra filters, diagonally truncated Volterra filters, and PAVFs in terms of initial convergence, steady-state error, and computational complexity.

['Yanjie Pang', 'Jiashu Zhang']

A hierarchical alternative updated adaptive Volterra filter with pipelined architecture

A novel solution for the efficiency problems encountered in static timing verification is presented. The LSP algorithm is submitted to a critical analysis. A new hierarchy based approach is presented and its advantages and limitations are highlighted. Finally, some results on real life circuits are presented. >

['P. Johannes', 'Luc Claesen', 'H. De Man']

On the use of hierarchy in timing verification with statically sensitizable paths

In this paper, we present a technique to synthesize featured textures easily and interactively.The main idea is to synthesize a new texture by copying irregular patches from the source to the target texture, each of which contains a complete feature.The interior part of the feature is not touched while the cutting and stitching is performed on the background texture between the features.The technique starts by selecting a feature in the source texture by the user, after which the algorithm finds the positions of other features, generates a similar distribution of features, and finally synthesizes the target texture by copying and stitching patches of the target's Voronoi cellular shapes from the source texture. The technique is fast enough to be used interactively to edit textures in a simple and easy way.

['Muath Sabha', 'Philip Dutré']

Feature-Based Texture Synthesis and Editing Using Voronoi Diagrams

Scribbler - Drawing Models in a Creative and Collaborative Environment: from Hand-Drawn Sketches to Domain Specific Models.

['Martin Vogel', 'Tim Warnecke', 'Christian Bartelt', 'Andreas Rausch']

Scribbler - Drawing Models in a Creative and Collaborative Environment: from Hand-Drawn Sketches to Domain Specific Models.

In this research, we propose a method of SLAM in a dynamic large outdoor environment using a laser scanner. Focus are cast on solving two major problems: 1) achieving global accuracy especially in non-cyclical environment, 2) tackling a mixture of data from both dynamic and static objects. Algorithms are developed, where GPS data and control inputs are used to diagnose pose error and guide to achieve a global accuracy; Classification of laser points and objects are conducted not in an independent module but across the processing in a framework of SLAM with moving object detection and tracking. Experiments are conducted using the data from two test-bed vehicles, and performance of the algorithms are demonstrated.

['Huijing Zhao', 'Masaki Chiba', 'Ryosuke Shibasaki', 'Xiaowei Shao', 'Jinshi Cui', 'Hongbin Zha']

SLAM in a dynamic large outdoor environment using a laser scanner

We propose a new coding technique based on nested coset codes and derive a new achievable rate region for a general three user discrete memoryless broadcast channel (DMBC). We identify an example of a three user binary broadcast channel for which the proposed achievable rate region strictly outperforms that obtained by a natural extension of Marton’s [1] rate region. As a step towards deriving the achievable rate region for the general three user DMBC, we introduce the new elements of our coding theorem through a new class of broadcast channels called 3-to-1 broadcast channels.

['Arun Padakandla', 'S. Sandeep Pradhan']

A new coding theorem for three user discrete memoryless broadcast channel

The paper presents the foundations for a packet forwarding floating point format and the design of a rounder ensuring compatibility between packet forwarding format and the standard binary IEEE 754 floating point format. The packet forwarding format and related addition and multiplication algorithms described in this series propose a new ALU pipeline paradigm for handling data hazards in pipelined floating point operations. The execution phases for the adder and multiplier packet forwarding pipelines are illustrated by a proposed implementation having four stages. The latter two stages in each pipeline employ the rounder described herein. The stages of the execution phase are intended to map to logic designs, with only some fifteen logic levels per stage allowing stages to be mapped to reasonably short cycles. The packet forwarding format provides for input and output in packet format with only two cycle effective latency between cooperating adder and multiplier pipelines. The designs we propose cut the effective latency in half and reduce the stall cycles by a factor of three compared to conventional forwarding pipelines processing data dependent operations. The speedup is realized, with preservation of IEEE 754 binary floating point compatibility.

['David W. Matula', 'Asger Munk Nielsen']

Pipelined packet-forwarding floating point. I. Foundations and a rounder

The paper presents a new algorithm for blocking artifacts reduction in low bit rate video. The algorithm addresses the blocking effect on block boundaries, as well as the one inside the blocks. The algorithm works with variety of coding schemes, and does not exploit any information from the coded bitstream. It has extremely low complexity and it is designed to work on a mobile platform in real time. It incorporates two parts: artifacts detection procedure, which decides whether the processing is required for the particular location in the video frame, and artifacts reduction procedure, which performs the actual filtering depending on local image characteristics. The experiments confirm the algorithms effectiveness, as well as its low computational complexity.

['Aleksandar Petrov', 'Tomislav Kartalov', 'Zoran A. Ivanovski']

Blocking effect reduction in low bitrate video on a mobile platform

Design Space Exploration for High Availability drFPGA Based Embedded Systems

['Shampa Chakraverty', 'Anubhav Agarwal', 'Amogh Agarwal', 'Anil Kumar', 'Abhinav Sikri']

Design Space Exploration for High Availability drFPGA Based Embedded Systems

An infrared ceiling sensor network system is reported in this study to realize behavior analysis and fall detection of a single person in the home environment. The sensors output multiple binary sequences from which we know the existence/non-existence of persons under the sensors. The short duration averages of the binary responses are shown to be able to be regarded as pixel values of a top-view camera, but more advantageous in the sense of preserving privacy. Using the “pixel values” as features, support vector machine classifiers succeeded in recognizing eight activities (walking, reading, etc.) performed by five subjects at an average recognition rate of 80.65%. In addition, we proposed a martingale framework for detecting falls in this system. The experimental results showed that we attained the best performance of 95.14% (F1 value), the FAR of 7.5% and the FRR of 2.0%. This accuracy is not sufficient in general but surprisingly high with such low-level information. In summary, it is shown that this system has the potential to be used in the home environment to provide personalized services and to detect abnormalities of elders who live alone.

['Shuai Tao', 'Mineichi Kudo', 'Hidetoshi Nonaka']

Privacy-preserved behavior analysis and fall detection by an infrared ceiling sensor network

Recently, multiple locomotion gaits of snake have been realized by snake robots. However, previous locomotion gaits are mainly limited on two-dimensional plane. In this study, we make a snake robot that can move in three-dimensional space by connecting several units serially. The each unit is composed by assembling one pitch axis and one yaw axis, and it can have two passive wheels. We realize previously achieved basic locomotion gaits and simple cylinder climbing locomotion. In addition, we also realize cylinder climbing locomotion with helical form by the snake robot using mathematical continuum model.

['Tetsushi Kamegawa', 'Takaaki Harada', 'Akio Gofuku']

Realization of cylinder climbing locomotion with helical form by a snake robot with passive wheels

In this paper, a spread spectrum clock generator (SSCG) with a process variation compensator for DisplayPort main link is presented. The process variation compensator not only reduces the error of spread ratio but also guarantees the reliability of the operation of an SSCG against process variation. The proposed SSCG has been implemented in 0.18-µm CMOS process and supports 10-phase 270 MHz and 162 MHz output clock. The experimental results show that the average rms jitter of 270 MHz output clock is 4.7 ps without spread spectrum clocking. 8.75 dBm of the peak reduction and 5000 ppm of spread ratio with the process variation compensator are achieved.

['Won-Young Lee', 'Lee-Sup Kim']

A spread spectrum clock generator with spread ratio error reduction scheme for DisplayPort main link

This paper presents the development of a lightweight component model that allows user to manage the introduction and arrangement of new interactive services and devices in the home. The model is responsive to ethnographic studies of the interplay between the Space-plan or interior layout and Stuff or artefacts placed within the fabric of the home. Interaction techniques developed through user-participation enable household members -- rather than designers -- to configure and reconfigure interactive devices and services to meet local needs. As a result, we have developed a tablet-based editor that discovers available ubiquitous components and presents these to users as 'jigsaw pieces' that can be dynamically assembled and recombined.

['Tom Rodden', 'Andy Crabtree', 'Terry Hemmings', 'Boriana Koleva', 'Jan Humble', 'Karl-Petter Åkesson', 'Pär Hansson']

Between the dazzle of a new building and its eventual corpse: assembling the ubiquitous home

Traffic generation in mobile networks is heavily dependent on user behavior because neither the place nor the time when users communicate is fixed. Therefore, when special events, such as fireworks displays or football matches, are held, many users concentrated in one location often generate unpredictable excessive traffic locally which can far exceed a network's capacity to handle it. As a way of controlling traffic to prevent congestion, we have proposed "Traffic Control by Influencing User Behavior". In this paper we describe the principles and method of traffic control by influencing user behavior. We also explain the method of multi-agent simulation we have developed as an evaluation tool. Finally, we describe the concept of and requirements for "Integrated User and Network Simulation", which will improve the simulation capability.

['Shigeru Kaneda', 'Yoshikazu Akinaga', 'Noriteru Shinagawa', 'Akira Miura', 'Mineo Takai']

Integrated user and network simulation for traffic control by influencing user behavior

In acute ischemic stroke treatment, prediction of tissue survival outcome plays a fundamental role in the clinical decision-making process, as it can be used to assess the balance of risk vs. possible benefit when considering endovascular clot-retrieval intervention. For the first time, we construct a deep learning model of tissue fate based on randomly sampled local patches from the hypoperfusion (Tmax) feature observed in MRI immediately after symptom onset. We evaluate the model with respect to the ground truth established by an expert neurologist four days after intervention. Experiments on 19 acute stroke patients evaluated the accuracy of the model in predicting tissue fate. Results show the superiority of the proposed regional learning framework versus a single-voxel-based regression model.

['Noah Stier', 'Nicholas Vincent', 'David S. Liebeskind', 'Fabien Scalzo']

Deep learning of tissue fate features in acute ischemic stroke

With the prevalence of car navigation systems, indoor navigation systems are increasingly attracting attention in the indoor research area. However, the available models for indoor navigation suffer from the problems that architectural constraints are not considered, route planning is only based on 2D planes, users are represented as points without considering their volumes, and different requirements asked for by different users are ignored. Consequently, the routes provided by existing models may not be suitable for different kinds of users like pedestrians, persons in wheelchairs, and persons driving indoor autos. This paper proposes a cube-based model to compute feasible routes for different users according to their widths, heights, and special requirements (e.g., users in wheelchairs prefer the routes without stairs). In this model, an indoor space is first represented by multiple cubes with different types. Then, according to the heights and types of the cubes, possible passages with the maximum widths and heights are generated by merging cubes into large blocks. Based on these blocks, feasible routes are computed by checking the availability of the connectors between different blocks.

['Wenjie Yuan', 'Markus Schneider']

Supporting 3D route planning in indoor space based on the LEGO representation

Summary: NAViGaTOR is a powerful graphing application for the 2D and 3D visualization of biological networks. NAViGaTOR includes a rich suite of visual mark-up tools for manual and automated annotation, fast and scalable layout algorithms and OpenGL hardware acceleration to facilitate the visualization of large graphs. Publication-quality images can be rendered through SVG graphics export. NAViGaTOR supports community-developed data formats (PSI-XML, BioPax and GML), is platform-independent and is extensible through a plug-in architecture.#R##N##R##N#Availability: NAViGaTOR is freely available to the research community from http://ophid.utoronto.ca/navigator/. Installers and documentation are provided for 32- and 64-bit Windows, Mac, Linux and Unix.#R##N##R##N#Contact: ac.otnorotu.ia@siruj#R##N##R##N#Supplementary information: Supplementary data are available at Bioinformatics online.

['Kevin R. Brown', 'David Otasek', 'Muhammad Ali', 'Michael J. McGuffin', 'Wing Xie', 'Baiju Devani', 'Ian Lawson van Toch', 'Igor Jurisica']

NAViGaTOR: Network Analysis, Visualization and Graphing Toronto

Arbiter Physically Unclonable Functions (PUFs) have been proposed as efficient hardware security primitives for generating device-unique authentication responses and cryptographic keys. However, the assumed possibility of modeling their underlying challenge-response behavior causes uncertainty about their actual applicability. In this work, we apply well-known machine learning techniques on challenge-response pairs (CRPs) from 64-stage Arbiter PUFs realized in 65nm CMOS, in order to evaluate the effectiveness of such modeling attacks on a modern silicon implementation. We show that a 90%-accurate model can be built from a training set of merely 500 CRPs, and that 5000 CRPs are sufficient to perfectly model the PUFs. To study the implications of these attacks, there is need for a new methodology to assess the security of PUFs suffering from modeling. We propose such a methodology and apply it to our machine learning results, yielding strict bounds on the usability of Arbiter PUFs. We conclude that plain 64-stage Arbiter PUFs are not secure for challenge-response authentication, and the number of extractable secret key bits is limited to at most 600.

['Gabriel Hospodar', 'Roel Maes', 'Ingrid Verbauwhede']

Machine learning attacks on 65nm Arbiter PUFs: Accurate modeling poses strict bounds on usability

High fidelity and interactive 3D characters abound in virtual and augmented reality. However, making one usually requires manual skeleton extraction and specification on how the body reacts with the translation and rotation of the bones. While there are previous works that already solve this problem, most systems have limitations with the input or the output cannot be directly used for animation. With the goal of bringing any humanoid toys to life, a pipeline is presented to automatically generate the toy's skeletal structure and skinning weights. First, the mesh is segmented into several parts using normal characteristic value (NCV) and global point signatures (GPS) as candidate points for segmentation. Then, joint locations are generated based on the segmentation results. Further-more, the skinning weights are generated by solving the Laplace diffusion equation. Experimental results show that our pipeline is robust enough to extract skeletal structures from graphic artists' models as well as from scanned models. In addition, our pipeline is deformation-invariant as it can generate the same skeletal structure of a model having different poses. Finally, our pipeline achieves both appealing virtual realism and fast speed. The output can be directly used to setup skeleton-based animations in games as well as real-time virtual and augmented reality applications within minutes.

['Ryan Anthony J. de Belen', 'Rowel O. Atienza']

Automatic skeleton generation using hierarchical mesh segmentation

The paper proposes several improvements on the Direction of Gradient (DOG) algorithm proposed in [1] for detecting and localizing a biochemical source with moving sensors. In particular, we show that the DOG algorithm can be turned into a distributed control scheme for a mobile sensing network, and that the maximum likelihood estimation proposed in the original algorithm can be replaced with more computationally efficient numerical procedures. Simulations on a single sensor and on a group of mobile sensors are provided that show that the proposed modifications simplify the original algorithm and improve its performance.

['Panos Tzanos', 'Milos Zefran', 'Arye Nehorai']

Information Based Distributed Control for Biochemical Source Detection and Localization

Opening up Government Data while Maintaining Data Privacy.

['Caroline Tudor', 'Philip Lowthian', 'Keith Spicer']

Opening up Government Data while Maintaining Data Privacy.

A method for automatically annotating objects in digital cultural heritage collections uses structured vocabulary concepts and their metadata schema roles.

['Tuukka Ruotsalo', 'Lora Aroyo', 'Guus Schreiber']

Knowledge-Based Linguistic Annotation of Digital Cultural Heritage Collections

Geometric Matching Algorithms for Two Realistic Terrains

['Sang Duk Yoon', 'Min-Gyu Kim', 'Wanbin Son', 'Hee-Kap Ahn']

Geometric Matching Algorithms for Two Realistic Terrains