Wireless Biosensing Network for Drivers' Health Monitoring

Biosensors integrated into the vehicle controller area network are used for detecting symptoms such as anxiety, pain, and fatigue that may affect driving safety. The proposed system provides a flexible option for implementation in a diverse range of mass-produced automotive accessories without affecting the driver's movement

Precise Descriptions of VLC Synchronization with CSP Semantic Models

Variable length codes (VLC) have found widespread applications due to their inherent coding efficiency. However, encoder-decoder synchronization becomes critically important for VLC to operate properly. Traditional treebased techniques lack the scalability to analyse the synchronization behaviours of VLC, and simulation techniques are typically used instead for large code sets. Building on an initial paper in which we first described an application of CSP to this domain, we present further advances in this paper. The contributions of this paper are twofold. First, we describe a novel application of the CSP stable failure model to completely describe the VLC synchronization mechanisms. Consequently, we concisely characterize bit patterns that can bring about rapid synchronization. The overall goal is to advance our understanding in this important area of research through an established formal description technique originally developed and used within the computing research community

Conceptual Analysis for Timely Social Media-Informed Personalized Recommendations

Integrating sensor networks and human social networks can provide rich data for many consumer applications. Conceptual analysis offers a way to reason about real-world concepts, which can assist in discovering hidden knowledge from the fused data. Knowledge discovered from such data can be used to provide mobile users with location-based, personalized and timely recommendations. Taking a multi-tier approach that separates concerns of data gathering, representation, aggregation and analysis, this paper presents a conceptual analysis framework that takes unified aggregated data as an input and generates semantically meaningful knowledge as an output. Preliminary experiments suggest that a fusion of sensor network and social media data improves the overall results compared to using either source of data alone

Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

Interoperability Optimization and Service Enhancement in Vehicle Onboard Infortainment Systems

This paper presents an overview on optimizing interoperability between different applications for enhanced return-on-investment through utilization of business intelligence in conjunction with prognostics and health management methodology. Such implementation is particularly suitable for deployment in mass-produced vehicle onboard diagnostics system

Modeling Paying Behavior in Game Social Networks

Online gaming is one of the largest industries on the Internet, generating tens of billions of dollars in revenues annually. One core problem in online game is to find and convert free users into paying customers, which is of great importance for the sustainable development of almost all online games. Although much research has been conducted, there are still several challenges that remain largely unsolved: What are the fundamental factors that trigger the users to pay? How does users? paying behavior influence each other in the game social network? How to design a prediction model to recognize those potential users who are likely to pay? In this paper, employing two large online games as the basis, we study how a user becomes a new paying user in the games. In particular, we examine how users' paying behavior influences each other in the game social network. We study this problem from various sociological perspectives including strong/weak ties, social structural diversity and social influence. Based on the discovered patterns, we propose a learning framework to predict potential new payers. The framework can learn a model using features associated with users and then use the social relationships between users to refine the learned model. We test the proposed framework using nearly 50 billion user activities from two real games. Our experiments show that the proposed framework significantly improves the prediction accuracy by up to 3-11% compared to several alternative methods. The study also unveils several intriguing social phenomena from the data. For example, influence indeed exists among users for the paying behavior. The likelihood of a user becoming a new paying user is 5 times higher than chance when he has 5 paying neighbors of strong tie. We have deployed the proposed algorithm into the game, and the Lift_Ratio has been improved up to 196% compared to the prior strategy

Managing Resources in the Software Development Process

A triangular business model can be applied to the software industry. The vertices of the triangle are the customer, resources and profits. Companies that harness their resources and satisfy their customer's needs enhance their profitability. Many software organizations already have an advanced software development process (SDP), but further efficiency gains can enhance the opportunity for business success. This paper identifies some strategies for improving the management of resources as a continued improvement process

Outdoor wireless networks for healthcare applications: reliability optimization through prognostics and health management

No abstract available

Engineering the Software Workforce for the 21st Century

No abstract available