In wireless sensor networks, node failures occur frequently. The effects of these failures can be reduced by using aggregated values of small groups of sensors instead of the values of individual sensors. However, most existing works have focused on computing the aggregation of all the nodes without grouping. Only a few approaches proposed the processing of grouped aggregate queries. However, s...

The paper is concerned with the problem of binary classification of data records, given an already classified training set of records. Among the various approaches to the problem, the methodology of the logical analysis of data (LAD) is considered. Such approach is based on discrete mathematics, with special emphasis on Boolean functions. With respect to the standard LAD procedure, enhancements...

We examine the set covering machine when it uses data-dependent half-spaces for its set of features and bound its generalization error in terms of the number of training errors and the number of half-spaces it achieves on the training data. We show that it provides a favorable alternative to data-dependent balls on some natural data sets. Compared to the support vector machine, the set covering...

Probing is a promising approach for network monitoring. An important problem that needs to be addressed while developing probing-based solutions is the selection of probe station nodes. Probe station nodes are the nodes that are instrumented with the functionality of sending probes and analyzing probe results. The placement of probe stations affects the diagnosis capability of the probes sent b...

We perform a review of model selection procedures, in particular various cross validation procedures and adaptive model selection. We cover important results for these procedures and explore the connections between different procedures and information criteria. INDEX WORDS: Model selection, Adaptive model selection, Cross validation, Information Criteria A REVIEW OF CROSS VALIDATION AND ADAPTIV...

land cover classification is one of the most important applications of polarimetric radar images, especially in urban areas. there are numerous features that can be extracted from these images for the use of their high potential, hence feature selection plays an important role in polsar image classification. in this study, three main steps are used to improve the classification: 1) feature extr...

Organizations (though the design of their employment application websites) have the option of prohibiting or allowing certain types of traditional applicant communications such as cover letters. However, while doing so may streamline recruiting processes, it may come at a price. This study hypothesizes that the opportunity to submit cover letters during a selection process should improve proced...

Animals selecting habitats often have to consider many factors, e.g., food and cover for safety. However, each habitat type often lacks an adequate mixture of these factors. Analyses of habitat selection using resource selection functions (RSFs) for animal radiotelemetry data typically ignore trade-offs, and the fact that these may change during an animal's daily foraging and resting rhythm on ...

Ensemble classification is an emerging approach to land cover mapping whereby the final classification output is a result of a ‘consensus’ of classifiers. Intuitively, an ensemble system should consist of base classifiers which are diverse i.e. classifiers whose decision boundaries err differently. In this paper ensemble feature selection is used to impose diversity in ensembles. The features o...