A data mining approach to classify serum creatinine values in patients undergoing continuous ambulatory peritoneal dialysis

Wireless Networks - Continuous ambulatory peritoneal dialysis (CAPD) is a treatment used by patients in the end-stage of chronic kidney diseases. Those patients need to be monitored using blood...     

Autogestion de Réseaux de Capteurs Sans Fil : Services, Fonctions, Modèles et Étude de Cas

The wireless sensor networks (Wsn) are a novel technology that has appeared after great advancements in the development of intelligent sensors, powerful microprocessors, and communication protocols, their basic components. This kind of network is composed by hundreds to thousands of elements and has the objective of data collecting, processing, and disseminating to a point of interest. The network elements, named sensors nodes, have small dimensions and resource restrictions, especially the energy, the processing, and the communication capacities. It is expected that theWsn are intelligent, autonomic, and context aware. To reach such an objective, they are supposed to perform the management of themselves, i.e., be self-managed. In this article, we propose a management solution for such a sort of network, based on the autonomic computing paradigm. In order to show that self-management can improve the productivity of the network and control the quality of the provided services, we present a case study of a heterogeneous and hierarchicWsn that collects and disseminates data continuously.     

Lethal effect of electric fields on isolated ventricular myocytes

Defibrillator-type shocks may cause electric and contractile dysfunction. In this study, we determined the relationship between probability of lethal injury and electric field intensity ($E$ ) in isolated rat ventricular myocytes, with emphasis on field orientation and stimulus waveform. This relationship was sigmoidal with irreversible injury for $E ≫ hbox{50 V/cm}$ . During both threshold and lethal stimulation, cells were twofold more sensitive to the field when it was applied longitudinally (versus transversally) to the cell major axis. For a given $E$, the estimated maximum variation of transmembrane potential ( $Delta V_{max }$) was greater for longitudinal stimuli, which might account for the greater sensitivity to the field. Cell death, however, occurred at lower maximum $Delta V_{max }$ values for transversal shocks. This might be explained by a less steep spatial decay of transmembrane potential predicted for transversal stimulation, which would possibly result in occurrence of electroporation in a larger membrane area. For the same stimulus duration, cells were less sensitive to field-induced injury when shocks were biphasic (versus monophasic). Ours results indicate that, although significant myocyte death may occur in the $E$ range expected during clinical defibrillation, biphasic shocks are less likely to produce irreversible cell injury.      

Process modeling and simulation for Hg1-xCdxTe. Part II: Self-diffusion,interdiffusion, and fundamental mechanisms of point-defect interactions in Hg1-xCdxTe

The Hg_0.8Cd_0.2Te type-conversion, Hg self-diffusion and interdiffusion processes are analyzed in the context of a first order reaction kinetics approach. Sets of nonlinear, stiffly coupled continuity equations are presented which describe the underlying physics, and their solutions model the observed macroscopic behavior. It is demonstrated that the Frenkel pair mechanism interactions dominated by the cation sublattice, in conjunction with basic diffusive and drift properties of the ionized point defects, comprise the basic processes which effect all macroscopic phenomena discussed. Existing experimental results are reviewed and apparent discrepancies discussed. Use is made of the Stanford University mercury cadmium telluride process simulator to provide quantitative and insightful examples of important results.     

Dispersion characteristics of asymmetric coupled anisotropic dielectric waveguides using FDFD

The formulation is developed in the frequency domain and the finite difference method is used for the numerical solution of the scalar wave equation, written in terms of the transverse components of the magnetic field. As a result a conventional eigenvalue problem is obtained without the presence of spurious modes due to the implicit inclusion of the divergence of the magnetic field equal to zero. The formulation is developed to include biaxial anisotropic dielectrics with an index profile varying arbitrarily in the cross section of the waveguide under analysis. This formulation is then applied to the analysis of the influence on the dispersion characteristics of the dimensions of asymmetric coupled rectangular uniaxial anisotropic dielectric waveguides. As expected, the reduction of the height or the width of one of the rectangular dielectric waveguides causes the dispersion curves to move towards higher frequencies.     

Dispersion in finlines on semiconductor and the S-parameters of a step discontinuity

The Transverse Transmission Line method is used for the characterization of bilateral and unilateral finlines on a semiconductor substrate and in conjunction with the modal method, for the calculation of the scattering parameters due to a step discontinuity on a unilateral finline with a lossless dielectric substrate. Numerical results of the effective dielectric constant, attenuation constant and characteristic impedance for the bilateral and unilateral finlines on semiconductor substrates, and results of scattering parameters of a step discontinuity for unilateral finline, are presented.     

Crystal Size,Morphology, and Growth Mechanism in Bio‐Inspired Apatite Nanocrystals

Bio‐inspired apatite nanoparticles precipitated in the presence of citrate ions at increasing maturation times are characterized in terms of structure, size, morphology, and composition through advanced X‐ray total scattering techniques. The origin of the platy crystal morphology, breaking the hexagonal symmetry, and the role of citrate ions is explored. By cross‐coupling the size and shape information of crystal domains with those obtained by atomic force microscopy on multidomain nanoparticles, a plausible mechanism underlying the amorphous‐to‐crystal transformation is reconstructed. In the present study, citrate plays the distinct roles of inducing the platy morphology of the amorphous precursor and controlling the thickness of the Ca‐deficient apatite nanocrystals. These findings can open new scenarios also in bone mineralization, where citrate might have a broader role to play than has been thought to date.     

SDN-based architecture for providing quality of service to high-performance distributed applications

The specification of quality of service (QoS) requirements in most of the existing networks is still challenging. In part, traditional network environments are limited by their high administrative cost, although software-defined networks (SDNs), a newer network paradigm, simplify the management of the whole network infrastructure. In fact, SDN provides a simple way to effectively develop QoS provisioning mechanisms. In this sense, we explore the SDN model and its flexibility to develop a QoS provisioning architecture. Through the use of our new architecture, network operators are able to specify QoS levels in a simple way. Each individual data flow can be addressed, and the architecture we propose also negotiates the QoS requirements between the network controller and applications. On the other hand, the network controller continuously monitors the network environment. Then, it allocates network elements resources and prioritizes traffic, adjusting the network performance. We evaluate the feasibility of our QoS provisioning mechanism by presenting three experimental setups under realistic scenarios. For example, for a given scenario where we evaluate file transfers, our results indicate that the additional SDN modules present negligible overhead. Moreover, for a given setup, we observe a reduction of up to 82% in the file transfer times.     

Image modeling based on a 2-D stochastic subspace system identification algorithm

Fitting a causal dynamic model to an image is a fundamental problem in image processing, pattern recognition, and computer vision. In image restoration, for instance, the goal is to recover an estimate of the true image, preferably in the form of a parametric model, given an image that has been degraded by a combination of blur and additive white Gaussian noise. In texture analysis, on the other hand, a model of a particular texture image can serve as a tool for simulating texture patterns. Finally, in image enhancement one computes a model of the true image and the residuals between the image and the modeled image can be interpreted as the result of applying a de-noising filter. There are numerous other applications within the field of image processing that require a causal dynamic model. Such is the case in scene analysis, machined parts inspection, and biometric analysis, to name only a few. There are many types of causal dynamic models that have been proposed in the literature, among which the autoregressive moving average and state-space models (i.e., Kalman filter) are the most commonly used. In this paper we introduce a 2-D stochastic state-space system identification algorithm for fitting a quarter plane causal dynamic Roesser model to an image. The algorithm constructs a causal, recursive, and separable-in-denominator 2-D Kalman filter model. The algorithm is tested with three real images and the quality of the estimated images are assessed.     

Probabilistic linear models for multiresolution estimation in gray-level images

A multiresolution analysis of digital gray-level images is presented. A gray-level multi-scale framework is determined from two main assumptions: the gray scale is binary at the finest spatial resolution, and the gray levels of composed regions are obtained additively. In order to interrelate the gray-level histograms of the same image at different resolutions, probabilistic linear models are developed, which are then applied for estimation. Linear-optimization theory is used as a way of constructing such models. A general procedure for image processing is sketched, based on gray-level estimation. A versatile algorithm for nonlinear filtering is derived. Some examples of prospective applications are given.This work was partially supported by grant TIC91-646 from the DGYCIT of the Spanish Government.