A Taxonomy for Locality Algorithms on Peer-to-Peer Networks

The continuous growth of peer-to-peer networks has made them responsible for a considerable portion of the current Internet traffic. For this reason, improvements in P2P network resources usage are of central importance. One effective approach for addressing this issue is the deployment of locality algorithms, which allow the system to optimize the peers` selection policy for different network situations and, thus, maximize performance. To date, several locality algorithms have been proposed for use in P2P networks. However, they usually adopt heterogeneous criteria for measuring the proximity between peers, which hinders a coherent comparison between the different solutions. In this paper, we develop a thoroughly review of popular locality algorithms, based on three main characteristics: the adopted network architecture, distance metric, and resulting peer selection algorithm. As result of this study, we propose a novel and generic taxonomy for locality algorithms in peer-to-peer networks, aiming to enable a better and more coherent evaluation of any individual locality algorithm.

Iterative strong coupling of dimensionally heterogeneous models

In this article we address decomposition strategies especially tailored to perform strong coupling of dimensionally heterogeneous models, under the hypothesis that one wants to solve each submodel separately and implement the interaction between subdomains by boundary conditions alone. The novel methodology takes full advantage of the small number of interface unknowns in this kind of problems. Existing algorithms can be viewed as variants of the `natural` staggered algorithm in which each domain transfers function values to the other, and receives fluxes (or forces), and vice versa. This natural algorithm is known as Dirichlet-to-Neumann in the Domain Decomposition literature. Essentially, we propose a framework in which this algorithm is equivalent to applying Gauss-Seidel iterations to a suitably defined (linear or nonlinear) system of equations. It is then immediate to switch to other iterative solvers such as GMRES or other Krylov-based method. which we assess through numerical experiments showing the significant gain that can be achieved. indeed. the benefit is that an extremely flexible, automatic coupling strategy can be developed, which in addition leads to iterative procedures that are parameter-free and rapidly converging. Further, in linear problems they have the finite termination property. Copyright (C) 2009 John Wiley & Sons, Ltd.

PARTITIONED ANALYSIS FOR DIMENSIONALLY-HETEROGENEOUS HYDRAULIC NETWORKS

In this work an iterative strategy is developed to tackle the problem of coupling dimensionally-heterogeneous models in the context of fluid mechanics. The procedure proposed here makes use of a reinterpretation of the original problem as a nonlinear interface problem for which classical nonlinear solvers can be applied. Strong coupling of the partitions is achieved while dealing with different codes for each partition, each code in black-box mode. The main application for which this procedure is envisaged arises when modeling hydraulic networks in which complex and simple subsystems are treated using detailed and simplified models, correspondingly. The potentialities and the performance of the strategy are assessed through several examples involving transient flows and complex network configurations.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.

Sisal cellulose acetates obtained from heterogeneous reactions

In the present work, cellulose obtained from sisal, which is a source of rapid growth, was used. Cellulose acetates were produced in heterogeneous medium, using acetic anhydride as esterifying agent and iodine as catalyst, to check if the procedure described in the literature for commercial cellulose also is adequate to sisal cellulose. The results indicated that iodine is an excellent catalyst to obtain sisal cellulose acetates, but the reaction is so fast as described in the literature when, instead of sisal, lower average molar weight cellulose (microcrystalline) is used. The crystallinity index (I(c)) of sisal cellulose acetates diminished compared to sisal cellulose, but there was no direct correlation between their degree of substitution (DS) and I(c). Probably acetyl groups were introduced more homogeneously along the short chains of microcrystalline cellulose, when compared to sisal cellulose, and then for microcrystalline cellulose acetates the Ic decreases as DS increases. Using the linear correlation that was found between degree of substitution (DS) and time reaction is possible to control the DS of sisal cellulose acetates, considering a large interval of degrees of substitution (0.3-2.8).

The accuracy of the Clock Drawing Test compared to that of standard screening tests for Alzheimer`s disease: results from a study of Brazilian elderly with heterogeneous educational backgrounds

Background: Although the Clock Drawing Test (CDT) is the second most used test in the world for the screening of dementia, there is still debate over its sensitivity specificity, application and interpretation in dementia diagnosis. This study has three main aims: to evaluate the sensitivity and specificity of the CDT in a sample composed of older adults with Alzheimer`s disease (AD) and normal controls; to compare CDT accuracy to the that of the Mini-mental State Examination (MMSE) and the Cambridge Cognitive Examination (CAMCOG), and to test whether the association of the MMSE with the CDT leads to higher or comparable accuracy as that reported for the CAMCOG. Methods: Cross-sectional assessment was carried out for 121 AD and 99 elderly controls with heterogeneous educational levels from a geriatric outpatient clinic who completed the Cambridge Examination for Mental Disorder of the Elderly (CAMDEX). The CDT was evaluated according to the Shulman, Mendez and Sunderland scales. Results: The CDT showed high sensitivity and specificity. There were significant correlations between the CDT and the MMSE (0.700-0.730; p < 0.001) and between the CDT and the CAMCOG (0.753-0.779; p < 0.001). The combination of the CDT with the MMSE improved sensitivity and specificity (SE = 89.2-90%; SP = 71.7-79.8%). Subgroup analysis indicated that for elderly people with lower education, sensitivity and specificity were both adequate and high. Conclusions: The CDT is a robust screening test when compared with the MMSE or the CAMCOG, independent of the scale used for its interpretation. The combination with the MMSE improves its performance significantly, becoming equivalent to the CAMCOG.

GOOAL: A routine based on Genetic Algorithms to track harmonics in electric power systems

Voltage and current waveforms of a distribution or transmission power system are not pure sinusoids. There are distortions in these waveforms that can be represented as a combination of the fundamental frequency, harmonics and high frequency transients. This paper presents a novel approach to identifying harmonics in power system distorted waveforms. The proposed method is based on Genetic Algorithms, which is an optimization technique inspired by genetics and natural evolution. GOOAL, a specially designed intelligent algorithm for optimization problems, was successfully implemented and tested. Two kinds of representations concerning chromosomes are utilized: binary and real. The results show that the proposed method is more precise than the traditional Fourier Transform, especially considering the real representation of the chromosomes.

Heterogeneous modeling of an anaerobic sequencing batch biofilm reactor (ASBBR)

The objective of this study was to estimate the first-order intrinsic kinetic constant (k(1)) and the liquid-phase mass transfer coefficient (k(c)) in a bench-scale anaerobic sequencing batch biofilm reactor (ASBBR) fed with glucose. A dynamic heterogeneous mathematical model, considering two phases (liquid and solid), was developed through mass balances in the liquid and solid phases. The model was adjusted to experimental data obtained from the ASBBR applied for the treatment of glucose-based synthetic wastewater with approximately 500 mg L-1 of glucose, operating in 8 h batch cycles, at 30 degrees C and 300 rpm. The values of the parameters obtained were 0.8911 min(-1) for k(1) and 0.7644 cm min(-1) for kc. The model was validated utilizing the estimated parameters with data obtained from the ASBBR operating in 3 h batch cycles, with a good representation of the experimental behavior. The solid-phase mass transfer flux was found to be the limiting step of the overall glucose conversion rate.

Solution of a heterogeneous modeling of a horizontal-flow anaerobic immobilized biomass (HAIB) reactor by the sequencing method

A modeling study was completed to develop a methodology that combines the sequencing and finite difference methods for the simulation of a heterogeneous model of a tubular reactor applied in the treatment of wastewater. The system included a liquid phase (convection diffusion transport) and a solid phase (diffusion reaction) that was obtained by completing a mass balance in the reactor and in the particle, respectively. The model was solved using a pilot-scale horizontal-flow anaerobic immobilized biomass (HAIB) reactor to treat domestic sewage, with the concentration results compared with the experimental data. A comparison of the behavior of the liquid phase concentration profile and the experimental results indicated that both the numerical methods offer a good description of the behavior of the concentration along the reactor. The advantage of the sequencing method over the finite difference method is that it is easier to apply and requires less computational time to model the dynamic simulation of outlet response of HAIB.

Hybrid Algorithms for Routing and Assignment Wavelengths in Optical Networks

This paper presents a strategy for the solution of the WDM optical networks planning. Specifically, the problem of Routing and Wavelength Allocation (RWA) in order to minimize the amount of wavelengths used. In this case, the problem is known as the Min-RWA. Two meta-heuristics (Tabu Search and Simulated Annealing) are applied to take solutions of good quality and high performance. The key point is the degradation of the maximum load on the virtual links in favor of minimization of number of wavelengths used; the objective is to find a good compromise between the metrics of virtual topology (load in Gb/s) and of the physical topology (quantity of wavelengths). The simulations suggest good results when compared to some existing in the literature.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

Reconfiguration of distribution networks to minimize loss and disruption costs using genetic algorithms

In this paper a computational implementation of an evolutionary algorithm (EA) is shown in order to tackle the problem of reconfiguring radial distribution systems. The developed module considers power quality indices such as long duration interruptions and customer process disruptions due to voltage sags, by using the Monte Carlo simulation method. Power quality costs are modeled into the mathematical problem formulation, which are added to the cost of network losses. As for the EA codification proposed, a decimal representation is used. The EA operators, namely selection, recombination and mutation, which are considered for the reconfiguration algorithm, are herein analyzed. A number of selection procedures are analyzed, namely tournament, elitism and a mixed technique using both elitism and tournament. The recombination operator was developed by considering a chromosome structure representation that maps the network branches and system radiality, and another structure that takes into account the network topology and feasibility of network operation to exchange genetic material. The topologies regarding the initial population are randomly produced so as radial configurations are produced through the Prim and Kruskal algorithms that rapidly build minimum spanning trees. (C) 2009 Elsevier B.V. All rights reserved.

Approximate algorithms for credal networks with binary variables

This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contain only binary variables. Such networks can represent incomplete or vague beliefs, lack of data, and disagreements among experts; they can also encode models based on belief functions and possibilistic measures. All algorithms for approximate inference in this paper rely on exact inferences in credal networks based on polytrees with binary variables, as these inferences have polynomial complexity. We are inspired by approximate algorithms for Bayesian networks; thus the Loopy 2U algorithm resembles Loopy Belief Propagation, while the Iterated Partial Evaluation and Structured Variational 2U algorithms are, respectively, based on Localized Partial Evaluation and variational techniques. (C) 2007 Elsevier Inc. All rights reserved.

Scatter search for a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries in Brazil

In this paper, we consider a real-life heterogeneous fleet vehicle routing problem with time windows and split deliveries that occurs in a major Brazilian retail group. A single depot attends 519 stores of the group distributed in 11 Brazilian states. To find good solutions to this problem, we propose heuristics as initial solutions and a scatter search (SS) approach. Next, the produced solutions are compared with the routes actually covered by the company. Our results show that the total distribution cost can be reduced significantly when such methods are used. Experimental testing with benchmark instances is used to assess the merit of our proposed procedure. (C) 2008 Published by Elsevier B.V.