Peer-assisted location authentication and access control for wireless networks

This paper presents the development and implementation of a location‐based, lightweight peer‐assisted authentication scheme for use in wireless networks. The notion of peer‐assisted authentication is based upon some target user equipment‐ (UE) seeking authentication and access to a network based upon its physical location. The target UE seeks authentication through the UE of peers in the same network. Compared with previous work, the approach in this paper does not rely on any cryptographic proofs from a central authentication infrastructure, thus avoiding complex infrastructure management. However, the peer‐assisted authentication consumes network channel resources which will impact on network performance. In this paper, we also present an access control algorithm for balancing the location authentication, network quality of service (QoS), network capacity and time delay. The results demonstrate that peer‐assisted authentication considering location authentication and system QoS through dynamic access control strategies can be effectively and efficiently implemented in a number of use cases

Can Zipf's law be adapted to normalize microarrays?

BACKGROUND: Normalization is the process of removing non-biological sources of variation between array experiments. Recent investigations of data in gene expression databases for varying organisms and tissues have shown that the majority of expressed genes exhibit a power-law distribution with an exponent close to -1 (i.e. obey Zipf's law). Based on the observation that our single channel and two channel microarray data sets also followed a power-law distribution, we were motivated to develop a normalization method based on this law, and examine how it compares with existing published techniques. A computationally simple and intuitively appealing technique based on this observation is presented. RESULTS: Using pairwise comparisons using MA plots (log ratio vs. log intensity), we compared this novel method to previously published normalization techniques, namely global normalization to the mean, the quantile method, and a variation on the loess normalization method designed specifically for boutique microarrays. Results indicated that, for single channel microarrays, the quantile method was superior with regard to eliminating intensity-dependent effects (banana curves), but Zipf's law normalization does minimize this effect by rotating the data distribution such that the maximal number of data points lie on the zero of the log ratio axis. For two channel boutique microarrays, the Zipf's law normalizations performed as well as, or better than existing techniques. CONCLUSION: Zipf's law normalization is a useful tool where the Quantile method cannot be applied, as is the case with microarrays containing functionally specific gene sets (boutique arrays)

Monte Carlo Simulation for Trading Under a L\'evy-Driven Mean-Reverting Framework

We present a Monte Carlo framework for pairs trading on mean-reverting spreads modeled by L\'evy-driven Ornstein-Uhlenbeck processes. Specifically, we focus on using a variance gamma driving process, an infinite activity pure jump process to allow for more flexible models of the price spread than is available in the classical model. However, this generalization comes at the cost of not having analytic formulas, so we apply Monte Carlo methods to determine optimal trading levels, and develop a variance reduction technique using control variates. Within this framework, we numerically examine how the optimal trading strategies are affected by the parameters of the model. In addition, we extend our method to bivariate spreads modeled using a weak variance alpha-gamma driving process, and explore the effect of correlation on these trades

The Evolution of Chinese Shopping Mall: An exploration on socio-spatial changes in Chinese shopping malls over 20 years

The rapid development of China has led to a transformation of its economic culture from traditional production to consumption. As the carrier of consumer behaviour, shopping malls present a rising trend in containing social activities in modern Chinese society, which see a functional evaluation towards mega, complex and clustering. This study focuses on the dynamic changes in the socio-spatial characteristics of Chinese shopping malls with a time-based reference, asking: what are the differences between the spatial layouts and behavioural patterns of shopping malls built in different periods? To what extent do these differences reflect the Chinese cultural and economic transformation? Does the spatial design make a difference to how the malls adapt to the contemporary consumer environment? The aim of this paper is to provide an evidence-based reference for the future spatial design of Chinese shopping malls. Based in Changsha, a Chinese central-south provincial city, this study investigates three shopping malls located in the city’s central business district (CBD) that are built in different periods from 1998 to 2016. These are Heiwado Mall, Hisense Plaza and ID Mall. Building on the graph theory in the field of retail research, this study conducts cross-comparison between the chosen malls to systemically examine the spatial/cultural changes over 20 years, including the analysis of spatial layout and on-site observation. The study suggests that understanding the target customer group and accordingly balancing the relationship between space and content are important factors for the successful operation of Chinese shopping malls. The conflict between spatial design and consumer orientation is argued to reduce the commercial value of shopping malls regardless of their advanced spatial design

Basic studies of baroclinic flows

Computations were completed of transition curves in the conventional annulus, including hysteresis effect. The model GEOSIM was used to compute the transition between axisymmetric flow and baroclinic wave flow in the conventional annulus experiments. Thorough testing and documentation of the GEOSIM code were also completed. The Spacelab 3 results from the Geophysical Fluid Flow Cell (GFFC) were reviewed and numerical modeling was performed of many of the cases with horizontal temperature gradients as well as heating from below, with different rates of rotation. A numerical study of the lower transition to axisymmetric flow in the baroclinic annulus was performed using GEOSIM

Thermal-mechanical modelling of power electronic module packaging

In this paper the reliability of the isolation substrate and chip mountdown solder interconnect of power modules under thermal-mechanical loading has been analysed using a numerical modelling approach. The damage indicators such as the peel stress and the accumulated plastic work density in solder interconnect are calculated for a range of geometrical design parameters, and the effects of these parameters on the reliability are studied by using a combination of the finite element analysis (FEA) method and optimisation techniques. The sensitivities of the reliability of the isolation substrate and solder interconnect to the changes of the design parameters are obtained and optimal designs are studied using response surface approximation and gradient optimization metho

Optimizing the reliability of power electronics module isolation substrates

Optimal design of a power electronics module isolation substrate is assessed using a combination of finite element structural mechanics analysis and response surface optimisation technique. Primary failure modes in power electronics modules include the loss of structural integrity in the ceramic substrate materials due to stresses induced through thermal cycling. Analysis of the influence of ceramic substrate design parameters is undertaken using a design of experiments approach. Finite element analysis is used to determine the stress distribution for each design, and the results are used to construct a quadratic response surface function. A particle swarm optimisation algorithm is then used to determine the optimal substrate design. Analysis of response surface function gradients is used to perform sensitivity analysis and develop isolation substrate design rules. The influence of design uncertainties introduced through manufacturing tolerances is assessed using a Monte-Carlo algorithm, resulting in a stress distribution histogram. The probability of failure caused by the violation of design constraints has been analyzed. Six geometric design parameters are considered in this work and the most important design parameters have been identified. Overall analysis results can be used to enhance the design and reliability of the component

A combination of spatiotemporal ica and euclidean features for face recognition

ICA decomposes a set of features into a basis whose components are statistically independent. It minimizes the statistical dependence between basis functions and searches for a linear transformation to express a set of features as a linear combination of statistically independent basis functions. Though ICA has found its application in face recognition, mostly spatial ICA was employed. Recently, we studied a joint spatial and temporal ICA method, and compared the performance of different ICA approaches by using our special face database collected by AcSys FRS Discovery system. In our study, we have found that spatiotemporal ICA apparently outperforms spatial ICA, and it can be much more robust with better performance than spatial ICA. These findings justify the promise of spatiotemporal ICA for face recognition. In this paper we report our progress and explore the possible combination of the Euclidean distance features and the ICA features to maximize the success rate of face recognitionIFIP International Conference on Artificial Intelligence in Theory and Practice - Machine VisionRed de Universidades con Carreras en Informática (RedUNCI

A combination of spatiotemporal ica and euclidean features for face recognition

ICA decomposes a set of features into a basis whose components are statistically independent. It minimizes the statistical dependence between basis functions and searches for a linear transformation to express a set of features as a linear combination of statistically independent basis functions. Though ICA has found its application in face recognition, mostly spatial ICA was employed. Recently, we studied a joint spatial and temporal ICA method, and compared the performance of different ICA approaches by using our special face database collected by AcSys FRS Discovery system. In our study, we have found that spatiotemporal ICA apparently outperforms spatial ICA, and it can be much more robust with better performance than spatial ICA. These findings justify the promise of spatiotemporal ICA for face recognition. In this paper we report our progress and explore the possible combination of the Euclidean distance features and the ICA features to maximize the success rate of face recognitionIFIP International Conference on Artificial Intelligence in Theory and Practice - Machine VisionRed de Universidades con Carreras en Informática (RedUNCI