In this paper, we develop and evaluate a Localization Anomaly Detection (LAD) scheme for non-flat surfaces for wireless sensor networks. The beacon-less grid localization scheme proposed for non-flat terrains in [1] is used for localization and the localization anomaly detection uses observations of the sensor node at two different reception ranges. Moreover, a new Signal Strength (SS) Metric i...

We deal with nonparametric estimation in a nonlinear cointegration model whose regressor and dependent variable can be contemporaneously correlated. The asymptotic properties of the Nadaraya-Watson estimator are already examined in the literature. In this paper, we consider nonparametric least absolute deviation (LAD) regression and derive the asymptotic distributions of the local constant and ...

This paper discusses some asymptotic uniform linearity results of randomly weighted empirical processes based on long range dependent random variables+ These results are subsequently used to linearize nonlinear regression quantiles in a nonlinear regression model with long range dependent errors, where the design variables can be either random or nonrandom+ These, in turn, yield the limiting be...

The increased use of prefabricated components, the complexity of new building shapes, and the speeding up of production in construction, demand an efficient and precise dimensional control. Meanwhile Information and Communication Technology (ICT) increasingly supports construction, among others, CAD systems and Total Stations, are being used for the purpose of dimensional control. In order to i...

Various chromatography systems are today widely applied for both analysis and preparation of chemical compounds from complex mixtures. Current trends aim at the miniaturization of such systems, for instance on microchips. One approach is to arrange arrays of small pillars in a micro channel. The pillar surfaces are functionalized such as to adsorb specific substances from a bulk fluid which flo...

A fast adaptive multiscale algorithm has been devised to characterize a random set of points spanning a high dimensional Euclidean space, but concentrated around special lower dimensional subsets. It has been adapted to analyze gene expression data from microarray experiments. We present here the simplest version of this “multi-strip” algorithm applied to a set of points in R concentrated aroun...