Angle-of-arrival localization based on antenna arrays for wireless sensor networks

Among the large number of contributions concerning the localization techniques for wireless sensor networks (WSNs), there is still no simple, energy and cost efficient solution suitable in outdoor scenarios. In this paper, a technique based on antenna arrays and angle-of-arrival (AoA) measurements is carefully discussed. While the AoA algorithms are rarely considered for WSNs due to the large dimensions of directional antennas, some system configurations are investigated that can be easily incorporated in pocket-size wireless devices.A heuristic weighting function that enables decreasing the location errors is introduced. Also, the detailed performance analysis of the presented system is provided. The localization accuracy is validated through realistic Monte-Carlo simulations that take into account the specificity of propagation conditions in WSNs as well as the radio noise effects. Finally, trade-offs between the accuracy, localization time and the number of anchors in a network are addressed.     

Numerical method using cubic B-spline for the heat and wave equation

In the present paper, the cubic B-splines method is considered for solving one-dimensional heat and wave equations. A typical finite difference approach had been used to discretize the time derivative while the cubic B-spline is applied as an interpolation function in the space dimension. The accuracy of the method for both equations is discussed. The efficiency of the method is illustrated by some test problems. The numerical results are found to be in good agreement with the exact solution.     

Large scale multiple robot visual mapping with heterogeneous landmarks in semi-structured terrain

This paper addresses the cooperative localization and visual mapping problem with multiple heterogeneous robots. The approach is designed to deal with the challenging large semi-structured outdoors environments in which aerial/ground ensembles are to evolve. We propose the use of heterogeneous visual landmarks, points and line segments, to achieve effective cooperation in such environments. A large-scale SLAM algorithm is generalized to handle multiple robots, in which a global graph maintains the relative relationships between a series of local sub-maps built by the different robots. The key issue when dealing with multiple robots is to find the link between them, and to integrate these relations to maintain the overall geometric consistency; the events that introduce these links on the global graph are described in detail. Monocular cameras are considered as the primary extereoceptive sensor. In order to achieve the undelayed initialization required by the bearing-only observations, the well-known inverse-depth parametrization is adopted to estimate 3D points. Similarly, to estimate 3D line segments, we present a novel parametrization based on anchored Plücker coordinates, to which extensible endpoints are added. Extensive simulations show the proposed developments, and the overall approach is illustrated using real-data taken with a helicopter and a ground rover.     

Computational aspects of the expected differential probability of 4-round AES and AES-like ciphers

In this paper we study the security of the Advanced Encryption Standard (AES) and AES-like block ciphers against differential cryptanalysis. Differential cryptanalysis is one of the most powerful methods for analyzing the security of block ciphers. Even though no formal proofs for the security of AES against differential cryptanalysis have been provided to date, some attempts to compute the maximum expected differential probability (MEDP) for two and four rounds of AES have been presented recently. In this paper, we will improve upon existing approaches in order to derive better bounds on the EDP for two and four rounds of AES based on a slightly simplified S-box. More precisely, we are able to provide the complete distribution of the EDP for two rounds of this AES variant with five active S-boxes and methods to improve the estimates for the EDP in the case of six active S-boxes.     

The personal lift-assist device and lifting technique: a principal component analysis

The personal lift-assist device (PLAD) is a non-motorised, on-body device that acts as an external force generator using the concept of stored elastic energy. In this study, the effect of the PLAD on the lifting kinematics of male and female lifters was investigated using principal component analysis. Joint kinematic data of 15 males and 15 females were collected using an opto-electronic system during a freestyle, symmetrical-lifting protocol with and without wearing the PLAD. Of the 31 Principal Components (PCs) retained in the models, eight scores were significantly different between the PLAD and no-PLAD conditions. There were no main effects for gender and no significant interactions. Results indicated that the PLAD similarly affected the lifting kinematics of males and females; demonstrating significantly less lumbar and thoracic flexion and significantly greater hip and ankle flexion when wearing the PLAD. These findings add to the body of work that suggest the PLAD may be a safe and effective ergonomic aid. STATEMENT OF RELEVANCE: The PLAD is an ergonomic aid that has been shown to be effective at reducing low back demands during manual materials handling tasks. This body of work establishes that the PLAD encourages safe lifting practices without adversely affecting lifting technique.     

Adaptive soft k-nearest-neighbour classifiers

A novel classifier is introduced to overcome the limitations of the k-NN classification systems. It estimates the posterior class probabilities using a local Parzen window estimation with the k-nearest-neighbour prototypes (in the Euclidean sense) to the pattern to classify. A learning algorithm is also presented to reduce the number of data points to store. Experimental results in two hand-written classification problems demonstrate the potential of the proposed classification system.     

Long-term availability prediction for groups of volunteer resources

Volunteer computing uses the free resources in Internet and Intranet environments for large-scale computation and storage. Currently, 70 applications use over 12 PetaFLOPS of computing power from such platforms. However, these platforms are currently limited to embarrassingly parallel applications. In an effort to broaden the set of applications that can leverage volunteer computing, we focus on the problem of predicting if a group of resources will be continuously available for a relatively long time period. Ensuring the collective availability of volunteer resources is challenging due to their inherent volatility and autonomy. Collective availability is important for enabling parallel applications and workflows on volunteer computing platforms. We evaluate our predictive methods using real availability traces gathered from hundreds of thousands of hosts from the SETI@home volunteer computing project. We show our prediction methods can guarantee reliably the availability of collections of volunteer resources. We show that this is particularly useful for service deployments over volunteer computing environments.     

Examining cognitive function across the lifespan using a mobile application

Many studies conducted in a laboratory or university setting are limited by funding, personnel, space, and time constraints. In the present study, we introduce a method of data collection using a mobile application that circumvents these typical experiment administration issues. Using the application, we examined cross-sectional age differences in cognitive function. We obtained data from more than 15,000 participants and replicated specific patterns of age-related differences in cognition. Using a subset of these participants, we also examined the processing speed account of age-related cognitive differences, and the association of exercise and leisure activity with cognitive function across the lifespan. We discuss the relative advantages and disadvantages of data collection with a mobile application, and provide recommendations for the use of this method in research.     

Characterizing and improving HIV/AIDS knowledge among cocaine-dependent outpatients.

The present study was an experimental test of efficacy of a brief education intervention for increasing HIV/AIDS knowledge among cocaine-dependent outpatients. Participants were randomly assigned to an HIV/AIDS education intervention (experimental condition) or a sham intervention (control condition). Control participants were subsequently crossed over to the HIV/AIDS education intervention. Experimental participants had higher scores on tests of HIV/AIDS knowledge after receiving the education intervention than did control participants. Further supporting the intervention's efficacy, control participant scores also increased once participants were crossed over and received the education intervention. Scores at follow-up were lower than at postintervention but remained higher than baseline scores. Results support the intervention's efficacy for increasing HIV/AIDS knowledge among cocaine-dependent outpatients. This intervention is brief, inexpensive, and easily implemented. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

3-D high frequency computation of transformer R, L parameters

High frequency electrical machine modeling based on lumped parameter equivalent circuit requires that eddy currents effects be taken into account for R and L coefficient derivation. Substituting hysteretic materials (complex permeability) to conductive materials makes it possible to accurately approximate proximity losses and shielding effect while considering realistic meshes for finite element methods computation. Three-dimensional magnetodynamic simulations of transformer test-cases using anisotropic complex permeability for magnetic core and windings have shown a good agreement with the standard model results.