A Self-organizing and Self-configuration Algorithm for Resource Management in Service-oriented Systems

With the ever increasing deployment of service-oriented distributed systems in large-scale and heterogeneous computing environments, clustering and communication overlay topology design has become more and more important to address several challenging issues and conflicting requirements, such as efficient scheduling and distribution of services among computing resources, reducing communication cost between services, high performance service and resource discovery while considering both inter-service and inter-node properties and also increasing the load distribution and the load balance. In this paper, a four-stage hierarchical clustering algorithm is proposed which automates the process of the optimally composing communicating groups in a dynamic way while preserving the proximity of the nodes. The simulation results show the performance of the algorithm with respect to load balance, scalability and efficiency

HARD: Hybrid Adaptive Resource Discovery for Jungle Computing

In recent years, Jungle Computing has emerged as a distributed computing paradigm based on simultaneous combination of various hierarchical and distributed computing environments which are composed by large number of heterogeneous resources. In such a computing environment, the resources and the underlying computation and communication infrastructures are highly-hierarchical and heterogeneous. This creates a lot of difficulty and complexity for finding the proper resources in a precise way in order to run a particular job on the system efficiently. This paper proposes Hybrid Adaptive Resource Discovery (HARD), a novel efficient and highly scalable resource-discovery approach which is built upon a virtual hierarchical overlay based on self-organization and self-adaptation of processing resources in the system, where the computing resources are organized into distributed hierarchies according to a proposed hierarchical multi-layered resource description model. The proposed approach supports distributed query processing within and across hierarchical layers by deploying various distributed resource discovery services and functionalities in the system which are implemented using different adapted algorithms and mechanisms in each level of hierarchy. The proposed approach addresses the requirements for resource discovery in Jungle Computing environments such as high-hierarchy, high-heterogeneity, high-scalability and dynamicity. Simulation results show significant scalability and efficiency of the proposed approach over highly heterogeneous, hierarchical and dynamic computing environments

A Specification-based Anycast Scheme for Scalable Resource Discovery in Distributed Systems

Anycast is a powerful paradigm for managing and locating resources in large scale distributed computing systems. This paper presents a novel specification-based anycasting scheme for resource discovery in such environments. The effectiveness of our proposal is demonstrated through simulation results, in which we observed a remarkable performance enhancement in different aspects (such as discovery latency, discovery cost, discovery load, etc.) over similar non-anycast based discovery methods

Modeling electrodialysis and a photochemical process for their integration in saline wastewater treatment.

Oxidation processes can be used to treat industrial wastewater containing non-biodegradable organic compounds. However, the presence of dissolved salts may inhibit or retard the treatment process. In this study, wastewater desalination by electrodialysis (ED) associated with an advanced oxidation process (photo-Fenton) was applied to an aqueous NaCl solution containing phenol. The influence of process variables on the demineralization factor was investigated for ED in pilot scale and a correlation was obtained between the phenol, salt and water fluxes with the driving force. The oxidation process was investigated in a laboratory batch reactor and a model based on artificial neural networks was developed by fitting the experimental data describing the reaction rate as a function of the input variables. With the experimental parameters of both processes, a dynamic model was developed for ED and a continuous model, using a plug flow reactor approach, for the oxidation process. Finally, the hybrid model simulation could validate different scenarios of the integrated system and can be used for process optimization

Resolution improvement of brain PET images using prior information from MRI: clinical application on refractory epilepsy

An important counterpart of clinical Positron Emission Tomography (PET) for early diagnosis of neurological diseases is its low resolution. This is particularly important when evaluating diseases related to small hypometabolisms such as epilepsy. The last years, new hybrid systems combining PET with Magnetic Resonance (MR) has been increasingly used for several different clinical applications. One of the advantages of MR is the production of high spatial resolution images and a potential application of PET-MR imaging is the improvement of PET resolution using MR information. A potential advantage of resolution recovery of PET images is the enhancement of contrast delivering at the same time better detectability of small lesions or hypometabolic areas and more accurate quantification over these areas. Recently, Shidahara et al (2009) proposed a new method using wavelet transforms in order to produce PET images with higher resolution. We optimised Shidahara’s method (SFS-RR) to take into account possible shortcomings on the particular clinical datasets, and applied it to a group of patients diagnosed with refractory epilepsy. FDG-PET and MRI images were acquired sequentially and then co-registered using software tools. A complete evaluation of the PET/MR images was performed before and after the correction, including different parameters related with PET quantification, such as atlas-based metabolism asymmetry coefficients and Statistical Parametric Mapping results comparing to a database of 87 healthy subjects. Furthermore, an experienced physician analyzed the results of non-corrected and corrected images in order to evaluate improvements of detectability on a visual inspection. Clinical outcome was used as a gold standard. SFS-RR demonstrated to have a positive impact on clinical diagnosis of small hypometabolisms. New lesions were detected providing additional clinically relevant information on the visual inspection. SPM sensitivity for the detection of small lesions was increased from 70% to 90%

Behavior of the flux-flow resistivity in mesoscopic superconductors

In this work we solved the time dependent Ginzburg-Landau equations numerically finding profiles of the flux-flow resistivity for different widths of superconducting stripes. We found vortex pinning induced by the surface superconductivity. This pinning avoids the movement of the vortex lattice preventing the generation of a voltage. We also found the existence of a mesoscopic region where the flux-flow resistivity shows size effects and we observed a transition to a macroscopic regime as the width increases.Fil: Sánchez Lotero, P.. Universidade Federal de Pernambuco; BrasilFil: Albino Aguiar, J.. Universidade Federal de Pernambuco; BrasilFil: Domínguez, Daniel. Comisión Nacional de Energía Atómica. Gerencia del Área Investigaciones y Aplicaciones No Nucleares. Gerencia de Física (CAB). Grupo de Teoría de Sólidos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentin

A conjugate for the Bargmann representation

In the Bargmann representation of quantum mechanics, physical states are mapped into entire functions of a complex variable z*, whereas the creation and annihilation operators $\hat{a}^\dagger$ and $\hat{a}$ play the role of multiplication and differentiation with respect to z*, respectively. In this paper we propose an alternative representation of quantum states, conjugate to the Bargmann representation, where the roles of $\hat{a}^\dagger$ and $\hat{a}$ are reversed, much like the roles of the position and momentum operators in their respective representations. We derive expressions for the inner product that maintain the usual notion of distance between states in the Hilbert space. Applications to simple systems and to the calculation of semiclassical propagators are presented.Comment: 15 page

cohort study with 6 months of Treatment follow-up

publishe