Otimização de sistemas DSL utilizando técnicas de gerenciamento de espectro

Esta dissertação apresenta contribuições à algumas modalidades de gerenciamento de espectro em redes DSL que tem recebido pouca atenção na literatura : minimização de potência e maximização de margem de ruído. Com relação a minimização de potência, cerca de 60% da potência total consumida pelos modems DSL é utilizada na transmissão. A contribuição dessa dissertação nesse âmbito foi provar matematicamente que os algoritmos de maximização de taxa também podem ser usados para minimizar potência. Dessa forma, praticamente se elimina o atraso histórico entre o estado da arte em maximização de taxa e minimização de potência, colocando-os no mesmo nível de desenvolvimento. A segunda contribuição dessa dissertação é sobre a modalidade de maximização de margem de ruído, de modo a otimizar a estabilidade de redes DSL. Nessa linha de pesquisa, essa dissertação apresenta um novo alogoritmo para a maximização de margem multiusuário, que apresenta desempenho superior a um algoritmo publicado anteriormente na literatura especializada.

GAIA - Uma proposta de agente inteligente acoplado a algoritmos evolucionários para ajuste dinâmico de parâmetros através de conceitos de design inteligente e lógica fuzzy

Há muitos anos, técnicas de Computação Evolucionária vem sendo aplicadas com sucesso na solução dos mais variados tipos de problemas de otimização. Na constante procura pelo ótimo global e por uma melhor exploração da superfície de busca, as escolhas para ajustar estes métodos podem ser exponencialmente complexas e requerem uma grande quantidade de intervenção humana. Estes modelos tradicionais darwinianos apóiam-se fortemente em aleatoriedade e escolhas heurísticas que se mantém fixas durante toda a execução, sem que acompanhem a variabilidade dos indivíduos e as eventuais mudanças necessárias. Dadas estas questões, o trabalho introduz a combinação de aspectos da Teoria do Design Inteligente a uma abordagem hibrida de algoritmo evolucionário, através da implementação de um agente inteligente o qual, utilizando lógica fuzzy, monitora e controla dinamicamente a população e seis parâmetros definidos de uma dada execução, ajustando-os para cada situação encontrada durante a busca. Na avaliação das proposições foi construído um protótipo sobre a implementação de um algoritmo genético para o problema do caixeiro viajante simétrico aplicado ao cenário de distância por estradas entre as capitais brasileiras, o que permitiu realizar 580 testes, simulações e comparações entre diferentes configurações apresentadas e resultados de outras técnicas. A intervenção inteligente entrega resultados que, com sucesso em muitos aspectos, superam as implementações tradicionais e abrem um vasto espaço para novas pesquisas e estudos nos aqui chamados: “Algoritmos Evolucionários Híbridos Auto-Adaptáveis”, ou mesmo, “Algoritmos Evolucionários Não-Darwinianos”.

Comparison between known propagation models using least squares tuning algorithm on 5.8 GHz in Amazon region cities

ABSTRACT: This paper presents a performance comparison between known propagation Models through least squares tuning algorithm for 5.8 GHz frequency band. The studied environment is based on the 12 cities located in Amazon Region. After adjustments and simulations, SUI Model showed the smaller RMS error and standard deviation when compared with COST231-Hata and ECC-33 models.

Development of computational 3D MoM algorithm for nanoplasmonics

In this paper, we present an algorithm for full-wave electromagnetic analysis of nanoplasmonic structures. We use the three-dimensional Method of Moments to solve the electric field integral equation. The computational algorithm is developed in the language C. As examples of application of the code, the problems of scattering from a nanosphere and a rectangular nanorod are analyzed. The calculated characteristics are the near field distribution and the spectral response of these nanoparticles. The convergence of the method for different discretization sizes is also discussed.

Global optimization using a genetic algorithm with hierarchically structured population

This paper applies a genetic algorithm with hierarchically structured population to solve unconstrained optimization problems. The population has individuals distributed in several overlapping clusters, each one with a leader and a variable number of support individuals. The hierarchy establishes that leaders must be fitter than its supporters with the topological organization of the clusters following a tree. Computational tests evaluate different population structures, population sizes and crossover operators for better algorithm performance. A set of known benchmark test problems is solved and the results found are compared with those obtained from other methods described in the literature, namely, two genetic algorithms, a simulated annealing, a differential evolution and a particle swarm optimization. The results indicate that the method employed is capable of achieving better performance than the previous approaches in regard as the two criteria usually employed for comparisons: the number of function evaluations and rate of success. The method also has a superior performance if the number of problems solved is taken into account. (C) 2013 Elsevier B.V. All rights reserved.

Wavelets based Algorithm for the Evaluation of Enhanced Liver Areas

Hepatocellular carcinoma (HCC) is a primary tumor of the liver. After local therapies, the tumor evaluation is based on the mRECIST criteria, which involves the measurement of the maximum diameter of the viable lesion. This paper describes a computed methodology to measure through the contrasted area of the lesions the maximum diameter of the tumor by a computational algorithm 63 computed tomography (CT) slices from 23 patients were assessed. Non-contrasted liver and HCC typical nodules were evaluated, and a virtual phantom was developed for this purpose. Optimization of the algorithm detection and quantification was made using the virtual phantom. After that, we compared the algorithm findings of maximum diameter of the target lesions against radiologist measures. Computed results of the maximum diameter are in good agreement with the results obtained by radiologist evaluation, indicating that the algorithm was able to detect properly the tumor limits A comparison of the estimated maximum diameter by radiologist versus the algorithm revealed differences on the order of 0.25 cm for large-sized tumors (diameter > 5 cm), whereas agreement lesser than 1.0cm was found for small-sized tumors. Differences between algorithm and radiologist measures were accurate for small-sized tumors with a trend to a small increase for tumors greater than 5 cm. Therefore, traditional methods for measuring lesion diameter should be complemented with non-subjective measurement methods, which would allow a more correct evaluation of the contrast-enhanced areas of HCC according to the mRECIST criteria.

A genetic algorithm/mathematical programming approach to solve a two-level soft drink production problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A genetic algorithm for the one-dimensional cutting stock problem with setups

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bio-Optical Properties of the Inner Continental Shelf off Santos Estuarine System, Southeastern Brazil, and their Implications for Ocean Color Algorithm Performance

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fast fault section estimation in distribution control centers using adaptive genetic algorithm

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

DEVELOPMENT OF AN ALGORITHM TO ANALYZE CARTOGRAPHIC FEATURES EXTRACTION METHODS IN DIGITAL IMAGES

The algorithm creates a buffer area around the cartographic features of interest in one of the images and compare it with the other one. During the comparison, the algorithm calculates the number of equals and different points and uses it to calculate the statistical values of the analysis. One calculated statistical value is the correctness, which shows the user the percentage of points that were correctly extracted. Another one is the completeness that shows the percentage of points that really belong to the interest feature. And the third value shows the idea of quality obtained by the extraction method, since that in order to calculate the quality the algorithm uses the correctness and completeness previously calculated. All the performed tests using this algorithm were possible to use the statistical values calculated to represent quantitatively the quality obtained by the extraction method executed. So, it is possible to say that the developed algorithm can be used to analyze extraction methods of cartographic features of interest, since that the results obtained were promising.

Measurement of the ratio of inclusive jet cross sections using the anti-k(T) algorithm with radius parameters R=0.5 and 0.7 in pp collisions at root s=7 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An Efficient Parallel Algorithm for Multiple Sequence Similarities Calculation Using a Low Complexity Method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Wavelet-based algorithm to the evaluation of contrasted hepatocellular carcinoma in CT-images after transarterial chemoembolization

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A Modified Branch and Bound Algorithm to Solve the Transmission Expansion Planning Problem

In this paper a novel Branch and Bound (B&B) algorithm to solve the transmission expansion planning which is a non-convex mixed integer nonlinear programming problem (MINLP) is presented. Based on defining the options of the separating variables and makes a search in breadth, we call this algorithm a B&BML algorithm. The proposed algorithm is implemented in AMPL and an open source Ipopt solver is used to solve the nonlinear programming (NLP) problems of all candidates in the B&B tree. Strategies have been developed to address the problem of non-linearity and non-convexity of the search region. The proposed algorithm is applied to the problem of long-term transmission expansion planning modeled as an MINLP problem. The proposed algorithm has carried out on five commonly used test systems such as Garver 6-Bus, IEEE 24-Bus, 46-Bus South Brazilian test systems, Bolivian 57-Bus, and Colombian 93-Bus. Results show that the proposed methodology not only can find the best known solution but it also yields a large reduction between 24% to 77.6% in the number of NLP problems regarding to the size of the systems.