This work addresses the problem of error concealment in video transmission systems over noisy channels employing Bregman divergences along with regularization. Error concealment intends to improve the effects of disturbances at the reception due to bit-errors or cell loss in packet networks. Bregman regularization gives accurate answers after just some iterations with fast convergence, better a...

This paper seeks to develop an allocation of 0/1 data matrices to physical systems upon a Kullback-Leibler distance between probability distributions. The distributions are estimated from the contents of the data matrices. We discuss an ascending hierarchical classification method, a numerical example and mention an application with survey data concerning the level of development of the departm...

this study utilizes a decade long (2005-2014) monthly data of total column tropospheric ozone (tcto) in dubson units to evaluate the spatial and temporal trend of lao over some major cities of west africa, namely lagos, accra, niamey, abuja, bamako, dakar, agadez, conakry, kano, and ouagadougou which are either capital cites or major commercial hubs, where the population ranges from 0.09 millio...

Genetical genomics, a novel approach combining microarray technology and quantitative genetic analysis, aims to identify the expression quantitative trait loci (eQTLs), which may regulate the genome-wide expression pattern. In this article, we have studied yeast genomic eQTL data to investigate how the genetic eQTL regulation of ancestral gene has diverged since gene duplication. Our findings a...

Gene duplication is a widespread phenomenon in genome evolution, and it has been proposed to serve as an engine of evolutionary innovation. In the present study, we performed the first comprehensive analysis of duplicate genes in the bovine genome. A total of 3131 putative duplicated gene pairs were identified, including 712 cattle-specific duplicate gene pairs unevenly distributed across the g...

In this paper, we present an approach to clustering images for efficient retrieval using relative entropy. We start with the assumption that visual features are represented by probability densities and develop clustering algorithms for probability densities (for example, normalized histograms are crude approximations of probability densities). These clustering algorithms are then used for effic...

We present a novel technique for proving program termination which introduces a new dimension of modularity. Existing techniques use the program to incrementally construct a termination proof. While the proof keeps changing, the program remains the same. Our technique goes a step further. We show how to use the current partial proof to partition the transition relation into those behaviors know...

We present a constraint-based method for proving conditional termination of integer programs. Building on this, we construct a framework to prove (unconditional) program termination using a powerful mechanism to combine conditional termination proofs. Our key insight is that a conditional termination proof shows termination for a subset of program execution states which do not need to be consid...

Résumé. Dans cet article, il est question de clustering de courbes. Nous proposons une méthode non paramétrique qui segmente les courbes en clusters et discrétise en intervalles les variables continues décrivant les points de la courbe. Le produit cartésien de ces partitions forme une grille de données qui est inférée en utilisant une approche Bayésienne de sélection de modèle ne faisant aucune...

We demonstrate how information in the form of observable data and moment constraints are introduced into the method of Maximum relative Entropy (ME). A general example of updating with data and moments is shown. A specific econometric example is solved in detail which can then be used as a template for real world problems. A numerical example is compared to a large deviation solution which illu...