Inferring the intensity of positive selection in protein-coding genes is important since it is used to shed light on the process of adaptation. Recently, it has been reported that overlapping genes, which are ubiquitous in all domains of life, seem to exhibit inordinate degrees of positive selection. Here, we present a new method for the simultaneous estimation of selection intensities in overl...

The strength of gait, compared to other biometrics, is that it does not require cooperative subjects. Previoius gait recognition approaches were evaluated using a gallery set consisting of gait sequences of people under similar covariate conditions (i.e. clothing, surface, carrying, and view conditions). This evaluation procedure, however, implies that the gait data are collected in a cooperati...

The imprint of natural selection on protein coding genes is often difficult to identify because selection is frequently transient or episodic, i.e. it affects only a subset of lineages. Existing computational techniques, which are designed to identify sites subject to pervasive selection, may fail to recognize sites where selection is episodic: a large proportion of positively selected sites. W...

We consider the problem of estimating the integral of the square of a density f from the observation of a n sample. Our method to estimate ∫ R f(x)dx is based on model selection via some penalized criterion. We prove that our estimator achieves the adaptive rates established by Efroimovich and Low on classes of smooth functions. A key point of the proof is an exponential inequality for U -stati...

The generalized estimating equation (GEE) has been a popular tool for marginal regression analysis with longitudinal data, and its extension, the weighted GEE approach, can further accommodate data that are missing at random (MAR). Model selection methodologies for GEE, however, have not been systematically developed to allow for missing data. We propose the missing longitudinal information cri...

One of the most challenging problems encountered when analysing multidimensional datasets is overabundance of features. In order to remove irrelevant, redundant, and noisy information from the data, some feature selection algorithms are used. The two-level feature selection analysed method contains Wrapper and Filter based feature search and evaluation. The experiments were performed on a datab...

through the last three decades different seismological and engineering approaches for the generation of artificial earthquakes have been proposed. selection of an appropriate method for the generation of applicable artificial earthquake accelerograms (aeas) has been a challenging subject in the time history analysis of the structures in the case of the absence of sufficient recorded accelerogra...

A method for verbal expression of degree of uncertainty is described. It requires the subject to select a phrase from a list that spans the full range of probabilities. In a second, optional, step, the subject indicates the numerical meaning of each phrase. The method avoids two problems of verbal probabilities-the indefinitely large lexicon and the individual differences in the interpretation ...

Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular...