hyper-igm syndromes are characterized by profound reduction of serum igg, iga, and ige levels with normal or increased concentrations of serum igm. cd40 ligand deficiency is x-linked form of the disease, which results in a lack of immunoglobulin class switching from igm to igg in b cells. in addition to the recurrent infections, a number of patients suffer from neutropenia. there are some evide...

In recent years, protocols that are based on the properties of random walks on graphs have found many applications in communication and information networks, such as wireless networks, peer-to-peer networks and the Web. For wireless networks (and other networks), graphs are actually not the correct model of the communication; instead hyper-graphs better capture the communication over a wireless...

Abstract. This paper presents an improved image hiding method based on a new hyper-chaotic system. The binary sequences that generated based on the new hyper-chaotic system are applied to pre-encrypt the image, including improved magiccube scrambling and pixels permutation; then further processing are used to hide the pre-encrypted image. The effect of hiding is also analyzed by using the metho...

In previous papers, evolution of dependence and ageing, for vectors of non-negative random variables, have been separately considered. Some analogies between the two evolutions emerge however in those studies. In the present paper, we propose a unified approach, based on semigroup arguments, explaining the origin of such analogies and relations among properties of stochastic dependence and ageing.

In this paper we present a radial basis function based extension to a recently proposed variational algorithm for approximate inference for diffusion processes. Inference, for state and in particular (hyper-) parameters, in diffusion processes is a challenging and crucial task. We show that the new radial basis function approximation based algorithm converges to the original algorithm and has b...

Many machine learning algorithms can be formulated as the minimization of a train ing criterion which involves training errors on each training example and some hyper parameters which are kept xed during this minimization When there is only a single hyper parameter one can easily explore how its value a ects a model selection criterion that is not the same as the training criterion and is used ...

There is a growing interest towards the design of reusable general purpose search methods that are applicable to different problems instead of tailored solutions to a single particular problem. Hyper-heuristics have emerged as such high level methods that explore the space formed by a set of heuristics (move operators) or heuristic components for solving computationally hard problems. A selecti...

We study the structure of multi-view images and review the notion of plenoptic hypervolumes. We then present a segmentation algorithm based on the level set method to extract such hyper-volumes and show how this segmentation can be used to dis-occlude hidden objects and to facilitate the understanding of the monitored scene. Finally, we highlight preliminary results on classification and cluste...

In this paper, a comparative study between proposed hyper kurtosis based modified duo-histogram equalization (HKMDHE) algorithm and contrast limited adaptive histogram enhancement (CLAHE) has been presented for the implementation of contrast enhancement and brightness preservation of low contrast human brain CT scan images. In HKMDHE algorithm, contrast enhancement is done on the hyper-kurtosis...