Scalable and flexible wireless distributed architecture for intelligent video surveillance systems

Multimedia Tools and Applications - This paper presents a novel distributed intelligent video surveillance architecture based on Wireless Multimedia Sensor Networks (WMSNs). This architecture is...     

Computational and mathematical models meet heterogeneous computing

The Journal of Supercomputing -     

An optimization method for learning statistical classifiers in structural reliability

Monte Carlo simulation is a general and robust method for structural reliability analysis, affected by the serious efficiency problem consisting in the need of computing the limit state function a very large number of times. In order to reduce this computational effort the use of several kinds of solver surrogates has been proposed in the recent past. Proposals include the Response Surface Method (RSM), Neural Networks (NN), Support Vector Machines (SVM) and several other methods developed in the burgeoning field of Statistical Learning (SL). Many of these techniques can be employed either for function approximation (regression approach) or for pattern recognition (classification approach). This paper concerns the use of these devices for discriminating samples into safe and failure classes using the classification approach, because it constitutes the core of Monte Carlo simulation as applied to reliability analysis as such. Due to the flexibility of most SL methods, a critical step in their use is the generation of the learning population, as it affects the generalization capacity of the surrogate. To this end it is first demonstrated that the optimal population from the information viewpoint lies around in the vicinity of the limit state function. Next, an optimization method assuring a small as well as highly informative learning population is proposed on this basis. It consists in generating a small initial quasi-random population using Sobol sequence for triggering a Particle Swarm Optimization (PSO) performed over an iteration-dependent cost function defined in terms of the limit state function. The method is evaluated using SVM classifiers, but it can be readily applied also to other statistical classification techniques because the distinctive feature of the SVM, i.e. the margin band, is not actively used in the algorithm. The results show that the method yields results for the probability of failure that are in very close agreement with Monte Carlo simulation performed on the original limit state function and requiring a small number of learning samples.     

Effect of Temperature on the Viscosity of Honey

Influence of temperature on the viscosity of honeys was analysed in the present work. The viscosity value decreased with the increase of temperature. The effect caused by temperature in the range studied was more important in the low range of temperature, whereas at high temperature, the viscosity showed less variation. Water activity and glass transition temperature was determined to relate these characteristics. Four experimental viscosity models were checked using the experimental data to correlate the influence of temperature upon honey viscosity.     

Error modeling for an untethered ultra-wideband system for construction indoor asset tracking

This paper analyzes the performance of an ultra-wideband (UWB) wireless network system for mobile asset tracking at a dynamic construction site. Static and dynamic error tests were performed on a commercial UWB system in different building spaces including open/closed spaces, steel/wood framed construction sites, and a closed office area. All tests were carried out with an untethered UWB configuration for more flexible deployment of the UWB system at construction sites. Statistical approaches including regression analysis, outlier detection, and Kalman filtering were used to build an error model. The research found that each site has a unique pattern of producing errors caused by various types of interference, e.g., electromagnetic interference, multi-path propagation, fading and scattering of signals. Approximately 25% of the errors were reduced by using the proposed error modeling process. The paper concludes that a statistically developed error model process can significantly reduce random errors and improve position accuracy for indoor mobile asset tracking applications in construction.     

Stress–strain relationship in axial compression for concrete using recycled saturated coarse aggregate

In this work the stress–strain curve of the recycled concretes was determined by replacing different percentages of the natural coarse aggregate with recycled coarse aggregate (20%, 50% and 100%). The results made it possible to establish the differences between the stress–strain relationship of a conventional concrete and this relationship for a recycled concrete depending on the percentage of replacement. In this way, it was found that the longitudinal strain of the recycled concretes increases with the percentage of recycled coarse aggregate used.Finally, using the experimental results, an analytical expression of the stress–strain curve accounting for the percentage of replacement was developed. The verification of the proposed model equation was done by comparing it to the experimental data. The results show that the proposed model equation satisfactorily describes the effect of the recycled aggregate on the stress–strain curve.     

Anisotropy of point defect diffusion in alpha-zirconium

Two types of intrinsic defect, i.e., vacancy and self-interstitial atom (SIA), are formed in metals during irradiation with energetic particles. The evolution of defect population leads to significant changes in microstructure and causes a number of radiation-induced property changes. Some phenomena, such as radiation growth of anisotropic materials, are due to anisotropy in the atomic mass transport by point defects. Detailed information on atomic-scale mechanisms is, therefore, necessary to understand such phenomena. In this article, we present results of a computer simulation study of mass transport via point defects in alpha-zirconium. The matrix of self-diffusion coefficients and activation energies for vacancy and SIA defects have been obtained, and different methods of treatment of diffusion have been tested. Molecular dynamics (MD) shows that vacancy diffusion is approximately isotropic in the temperature range studied (1050 to 1650 K), although some preference for basalplane diffusion was observed at the lower end of the range. The mechanism of interstitial diffusion changes from one-dimensional (1-D) in a 〈11 0〉 direction at low temperature (<300 K) to two-dimensional (2-D) in the basal plane and, then, three-dimensional (3-D) at higher temperatures. This article is based on a presentation made in the symposium entitled “Defect Properties and Mechanical Behavior of HCP Metals and Alloys” at the TMS Annual Meeting, February 11–15, 2001, in New Orleans, Louisiana, under the auspices of the following ASM committees: Materials Science Critical Technology Sector, Structural Materials Division, Electronic, Magnetic & Photonic Materials Division, Chemistry & Physics of Materials Committee, Joint Nuclear Materials Committee, and Titanium Committee.