Efficient Multimedia Distribution in Source Constraint Networks

In recent years, the number of peer-to-peer (P2P) applications has increased significantly. One important problem in many P2P applications is how to efficiently disseminate data from a single source to multiple receivers on the Internet. A successful model used for analyzing this problem is a graph consisting of nodes and edges, with a capacity assigned to each edge. In some situations however, it is inconvenient to use this model. To that end, we propose to study the problem of efficient data dissemination in a source constraint network. A source constraint network is modeled as a graph in which, the capacity is associated with a node, rather than an edge. The contributions of this paper include (a) a quantitative data dissemination in any source constraint network, (b) a set of topologies suitable for data dissemination in P2P networks, and (c) an architecture and implementation of a P2P system based on the proposed optimal topologies. We will present the experimental results of our P2P system deployed on PlanetLab nodes demonstrating that our approach achieves near optimal throughput while providing scalability, low delay and bandwidth fairness among peers.     

Mild body cooling impairs attention via distraction from skin cooling

Many contemporary workers are routinely exposed to mild cold stress, which may compromise mental function and lead to accidents. A study investigated the effect of mild body cooling of 1.0 degree C rectal temperature (Tre) on vigilance (i.e. sustained attention) and the orienting of spatial attention (i.e. spatially selective processing of visual information). Vigilance and spatial attention tests were administered to 14 healthy males and six females at four stages (pre-immersion, deltaTre = 0, -0.5 and - 1.0 degree C ) of a gradual, head-out immersion cooling session (18-25 deltaC water), and in four time-matched stages of a contrast session, in which participants sat in an empty tub and no cooling took place. In the spatial attention test, target discrimination times were similar for all stages of the contrast session, but increased significantly in the cooling phase upon immersion (deltaTre = 0 degrees C), with no further increases at deltaTre = -0.5 and - 1.0 degree C. Despite global response slowing, cooling did not affect the normal pattern of spatial orienting. In the vigilance test, the variability of detection time was adversely affected in the cooling but not the contrast trials: variability increased at immersion but did not increase further with additional cooling. These findings suggest that attentional impairments are more closely linked to the distracting effects of cold skin temperature than decreases in body core temperature.     

A flexible encapsulated MEMS pressure sensor system for biomechanical applications

 The use of pressure sensors made of conductive polymers is common in biomechanical applications. Unfortunately, hysteresis, nonlinearity, non-repeatability and creep have a significant effect on the pressure readings when such conductive polymers are used. The objective of this paper is to explore the potential of a new flexible encapsulated micro electromechanical system (MEMS) pressure sensor system as an alternative for human interface pressure measurement. A prototype has been designed, fabricated, and characterized. Testing has shown that the proposed packaging approach shows very little degradation in the performance characteristics of the original MEMS pressure sensor. The much-needed characteristics of repeatability, linearity, low hysteresis, temperature independency are preserved. Thus the flexible encapsulated MEMS pressure sensor system is very promising and shows superiority over the commercially available conductive polymer film sensors for pressure measurement in biomechanical applications. Received: 1 December 1999/Accepted: 17 August 2000     

Regularized orthogonal linear discriminant analysis

In this paper the regularized orthogonal linear discriminant analysis (ROLDA) is studied. The major issue of the regularized linear discriminant analysis is to choose an appropriate regularization parameter. In existing regularized linear discriminant analysis methods, they all select the “best” regularization parameter from a given parameter candidate set by using cross-validation for classification. An obvious limitation of such regularized linear discriminant analysis methods is that it is not clear how to choose an appropriate candidate set. Therefore, up to now, there is no concrete mathematical theory available in selecting an appropriate regularization parameter in practical applications of the regularized linear discriminant analysis. The present work is to fill this gap. Here we derive the mathematical relationship between orthogonal linear discriminant analysis and the regularized orthogonal linear discriminant analysis first, and then by means of this relationship we find a mathematical criterion for selecting the regularization parameter in ROLDA and consequently we develop a new regularized orthogonal linear discriminant analysis method, in which no candidate set of regularization parameter is needed. The effectiveness of our proposed regularized orthogonal linear discriminant analysis is illustrated by some real-world data sets.     

Extending UML to model Web 2.0‐based context‐aware applications

Web 2.0 Mashups offer entirely new opportunities for context‐aware application (CAA) developers by integrating Web 2.0 technologies to facilitate interoperability among heterogeneous context‐aware systems. From a software engineering perspective, a visualized approach for Web 2.0‐based CAA modeling is crucial. Current CAA development, however, cannot provide a conceptual model for Web 2.0‐based CAA. Therefore, the development efficiency and potential for reuse are decreased. The UML is a general purpose modeling language with potential for use in many application domains. However, UML often lacks elements needed to model concepts in specific domains, such as Web 2.0‐based CAA modeling. To address the above issues, this study presents the Web 2.0‐based CAA UML profile, a UML profile for modeling Web 2.0‐based CAA. Copyright © 2011 John Wiley & Sons, Ltd.     

Polymeric carbon nanocomposites from multiwalled carbon nanotubes functionalized with segmented polyurethane

Multiwalled carbon nanotubes (MWNT) were functionalized with segmented polyurethanes (PU) by the “grafting to” approach. Raman and X‐ray photoelectron spectroscopy (XPS) spectra show that the sidewalls of MWNTs have been functionalized with acid treatment, and the amount of COOH increases with increasing acid treatment time. FTIR and X‐ray diffraction (XRD) spectra confirm that PU is covalently attached to the sidewalls of MWNTs by esterification reaction. Similar to the parent PU, the functionalized carbon nanotube samples are soluble in highly polar solvents, such as dimethyl sulfoxide (DMSO) and N,N‐dimethylformamide (DMF). The functionalized acid amount and the grafted PU amount were determined by thermogravimetric analyses (TGA). Comparative studies, based on SEM images between the PU‐functionalized and chemically defunctionalized MWNT samples, also reveal the covalent coating character. Dynamic mechanical analysis (DMA) of nanocomposite films prepared from PU and PU‐functionalized MWNTs show enhanced mechanical properties and increased soft segment T_g. Tensile properties indicate that PU‐functionalized MWNTs are effective reinforcing fillers for the polyurethane matrix. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Contractor as Trust Initiator in Construction Partnering—Prisoner’s Dilemma Perspective

Partnering has been advocated for use in construction as a project-delivery approach to curb dispute and enable a cooperative contracting environment. Successful construction partnering is perceived to derive benefits to both developers and contractors. In view of significant implications to successful project delivery, there has been a surge of research and studies on construction partnering. These studies typically focus on the partnering process as well as the identification of critical success factors. Among the various success factors that underpin partnering success, establishing trust among partners is considered the most important. Moreover, skeptics have been swift to point out that establishing trust in construction is daunting. A better understanding of the role of trust and its manifestation in partnering efforts is therefore of both academic and practical value. In this study, motivating trust in construction partnering is described within the classic framework of “the prisoner’s dilemma,” which suggests the trust cycle can be kick-started if construction partners put cooperation before competition and self-interest. This paper reports a study that is designed to suggest a suitable candidate for the trust initiator. As such, the critical trust factors for two groups of construction partners in Hong Kong—developers/consultants and contractors—are first identified. It is found that “performance” and “permeability” of partners are the two most critical trust factors. “Performance” describes the partner’s competence and problem-solving ability as perceived by their counterpart. “Permeability” reflects the partner’s openness in sharing information. The result of a multiple-regression analysis further suggests that the contractor is in a position to initiate trust through competent performance and maintaining effective communication with the client. In this manner, the trust cycle can expand with reciprocal trustworthiness from the client.     

Hybrid Subset Simulation method for reliability estimation of dynamical systems subject to stochastic excitation

A hybrid Subset Simulation approach is proposed for reliability estimation for general dynamical systems subject to stochastic excitation. This new stochastic simulation approach combines the advantages of the two previously proposed Subset Simulation methods, Subset Simulation with Markov Chain Monte Carlo (MCMC) algorithm and Subset Simulation with splitting. The new method employs the MCMC algorithm before reaching an intermediate failure level and splitting after reaching the level to exploit the causality of dynamical systems. The statistical properties of the failure probability estimators are derived. Two examples are presented to demonstrate the effectiveness of the new approach and to compare with the previous two Subset Simulation methods. The results show that the new method is robust to the choice of proposal distribution for the MCMC algorithm and to the intermediate failure events selected for Subset Simulation.     

Image reconstruction of a buried perfectly conducting cylinder illuminated by transverse electric waves

This article presents a computational approach to the image reconstruction of a perfectly conducting cylinder illuminated by transverse electric waves. A perfectly conducting cylinder of unknown shape buried in one half‐space and scatters the incident wave from another half‐space where the scattered field is recorded. Based on the boundary condition and the measured scattered field, a set of nonlinear integral equations is derived, and the imaging problem is reformulated into an optimization problem. The steady state genetic algorithm is then employed to find out the global extreme solution of the cost function. Numerical results demonstrated that, even when the initial guess is far away from the exact one, good reconstruction can be obtained. In such a case, the gradient‐based methods often get trapped in a local extreme. In addition, the effect of different noise on the reconstruction is investigated. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 15, 261–265, 2005