Algoritmos científicos

The Scientific Algorithms are a new metaheuristics inspired in the scientific research process. The new method introduces the idea of theme to search the solution space of hard problems. The inspiration for this class of algorithms comes from the act of researching that comprises thinking, knowledge sharing and disclosing new ideas. The ideas of the new method are illustrated in the Traveling Salesman Problem. A computational experiment applies the proposed approach to a new variant of the Traveling Salesman Problem named Car Renter Salesman Problem. The results are compared to state-of-the-art algorithms for the latter problem

Algoritmos de agrupamentos fuzzy intervalares e índice de validação para agrupamento de dados simbólicos do tipo intervalo

Symbolic Data Analysis (SDA) main aims to provide tools for reducing large databases to extract knowledge and provide techniques to describe the unit of such data in complex units, as such, interval or histogram. The objective of this work is to extend classical clustering methods for symbolic interval data based on interval-based distance. The main advantage of using an interval-based distance for interval-based data lies on the fact that it preserves the underlying imprecision on intervals which is usually lost when real-valued distances are applied. This work includes an approach allow existing indices to be adapted to interval context. The proposed methods with interval-based distances are compared with distances punctual existing literature through experiments with simulated data and real data interval

Uma abordagem através de algoritmos transgenéticos para o problema da configuração do traçado de uma rede de distribuição de gás natural

Este trabalho apresenta um algoritmo transgenético híbrido para a solução de um Problema de Configuração de uma Rede de Distribuição de Gás Natural. O problema da configuração dessas redes requer a definição de um traçado por onde os dutos devem ser colocados para atender aos clientes. É estudada neste trabalho uma maneira de conectar os clientes em uma rede com arquitetura em forma de árvore. O objetivo é minimizar o custo de construção da rede, mesmo que para isso alguns clientes que não proporcionam lucros deixem de ser atendidos. Esse problema pode ser formulado computacionalmente através do Problema de Steiner com Prêmios. Este é um problema de otimização combinatória da classe dos NPÁrduos. Este trabalho apresenta um algoritmo heurístico para a solução do problema. A abordagem utilizada é chamada de Algoritmos Transgenéticos, que se enquadram na categoria dos algoritmos evolucionários. Para a geração de soluções inicias é utilizado um algoritmo primaldual, e pathrelinking é usado como intensificador

Uma abordagem dialógica para a utilização de atividades experimentais em sala de aula

The belief of using experimental activities in the teaching of Physics as a strategy to produce a more efficient teaching-learning process is great among teachers and the school community. However, there are many difficulties for their implementation and when it happens they do not contribute for an improvement in class efficiency due to the method used. In this work, we developed a proposal for using these activities in Physics classes in high school, from a critical-reflexive approach in which the constant dialogue between the participants in the teaching-learning process is fundamental. The work was developed in two ways. The first, where the author/writer created an educational material and applied it in classroom and a second one, where he presented the idea to other teachers and undergraduate students from the Physics course at UFRN and IFRN (former CEFET-RN) through an extended workshop entitled "The role of experimental activities in the Physics teaching". This workshop had the duration of 60 hours and was implemented in 4 steps: i) sensitization and formation, ii) material development, iii) material implementation and iv) evaluation by teachers and students from the classes where the material was applied. The goal of this workshop was to present the approach, evaluate how the participants received the idea and how they would apply it in real situations. The results of the application in classroom allowed us to reach some conclusions. This approach was well received by the students as well as by the workshop participants. Despite some difficulties in relation to the handling of the implementation results by the workshop participants, they indicated changes in these professionals teaching practice and the introduction of experimental activities has been an important subsidy to assist them in Physics class in high school

Algoritmos e Arquiteturas VLSI para Detectores MIMO com Decisão Suave

The use of Multiple Input Multiple Output (MIMO) systems has permitted the recent evolution of wireless communication standards. The Spatial Multiplexing MIMO technique, in particular, provides a linear gain at the transmission capacity with the minimum between the numbers of transmit and receive antennas. To obtain a near capacity performance in SM-MIMO systems a soft decision Maximum A Posteriori Probability MIMO detector is necessary. However, such detector is too complex for practical solutions. Hence, the goal of a MIMO detector algorithm aimed for implementation is to get a good approximation of the ideal detector while keeping an acceptable complexity. Moreover, the algorithm needs to be mapped to a VLSI architecture with small area and high data rate. Since Spatial Multiplexing is a recent technique, it is argued that there is still much room for development of related algorithms and architectures. Therefore, this thesis focused on the study of sub optimum algorithms and VLSI architectures for broadband MIMO detector with soft decision. As a result, novel algorithms have been developed starting from proposals of optimizations for already established algorithms. Based on these results, new MIMO detector architectures with configurable modulation and competitive area, performance and data rate parameters are here proposed. The developed algorithms have been extensively simulated and the architectures were synthesized so that the results can serve as a reference for other works in the area

Estratégias de busca reativa utilizando aprendizagem por reforço e algoritmos de busca local

Técnicas de otimização conhecidas como as metaheurísticas tem conseguido resolversatisfatoriamente problemas conhecidos, mas desenvolvimento das metaheurísticas écaracterizado por escolha de parâmetros para sua execução, na qual a opção apropriadadestes parâmetros (valores). Onde o ajuste de parâmetro é essencial testa-se os parâmetrosaté que resultados viáveis sejam obtidos, normalmente feita pelo desenvolvedor que estaimplementando a metaheuristica. A qualidade dos resultados de uma instância1 de testenão será transferida para outras instâncias a serem testadas e seu feedback pode requererum processo lento de “tentativa e erro” onde o algoritmo têm que ser ajustado para umaaplicação especifica. Diante deste contexto das metaheurísticas surgiu a Busca Reativaque defende a integração entre o aprendizado de máquina dentro de buscas heurísticaspara solucionar problemas de otimização complexos. A partir da integração que a BuscaReativa propõe entre o aprendizado de máquina e as metaheurísticas, surgiu a ideia dese colocar a Aprendizagem por Reforço mais especificamente o algoritmo Q-learning deforma reativa, para selecionar qual busca local é a mais indicada em determinado instanteda busca, para suceder uma outra busca local que não pode mais melhorar a soluçãocorrente na metaheurística VNS. Assim, neste trabalho propomos uma implementação reativa,utilizando aprendizado por reforço para o auto-tuning do algoritmo implementado,aplicado ao problema do caixeiro viajante simétrico e ao problema escalonamento sondaspara manutenção de poços.

Estudo da participação das espécies fortemente oxidantes produzidas durante a oxidação eletroquímica de corantes usando eletrodo de diamante dopado com boro: função das propriedades eletroquímicas do eletrodo e condições experimentais

The textile industry is one of the most polluting in the world (AHMEDCHEKKAT et al. 2011), generating wastewater with high organic loading. Among the pollutants present in these effluents are dyes, substances with complex structures, toxic and carcinogenic characteristics, besides having a strong staining. Improper disposal of these substances to the environment, without performing a pre-treatment can cause major environmental impacts. The objective this thesis to use a technique of electrochemical oxidation of boron doped diamond anode, BDD, for the treatment of a synthetic dye and a textile real effluent. In addition to studying the behavior of different electrolytes (HClO4, H3PO4, NaCl and Na2SO4) and current densities (15, 60, 90 and 120 mA.cm-2 ), and compare the methods with Rhodamine B (RhB) photolysis, electrolysis and photoelectrocatalytic using H3PO4 and Na2SO4. Electrochemical oxidation studies were performed in different ratio sp3 /sp2 of BDD with solution of RhB. To achieve these objectives, analysis of pH, conductivity, UV-visible, TOC, HPLC and GC-MS were developed. Based on the results with the Rhodamine B, it was observed that in all cases occurred at mineralization, independent of electrolyte and current density, but these parameters affect the speed and efficiency of mineralization. The radiation of light was favorable during the electrolysis of RhB with phosphate and sulfate. Regarding the oxidation in BDD anode with different ratio sp3 /sp2 (165, 176, 206, 220, 262 e 329), with lower carbon-sp3 had a longer favoring the electrochemical conversion of RhB, instead of combustion. The greater the carbon content on the anodes BDD took the biggest favor of direct electrochemical oxidation

Formulações e algoritmos para o problema das p-medianas heterogêneo livre de penalidade

This work presents a new model for the Heterogeneous p-median Problem (HPM), proposed to recover the hidden category structures present in the data provided by a sorting task procedure, a popular approach to understand heterogeneous individual’s perception of products and brands. This new model is named as the Penalty-free Heterogeneous p-median Problem (PFHPM), a single-objective version of the original problem, the HPM. The main parameter in the HPM is also eliminated, the penalty factor. It is responsible for the weighting of the objective function terms. The adjusting of this parameter controls the way that the model recovers the hidden category structures present in data, and depends on a broad knowledge of the problem. Additionally, two complementary formulations for the PFHPM are shown, both mixed integer linear programming problems. From these additional formulations lower-bounds were obtained for the PFHPM. These values were used to validate a specialized Variable Neighborhood Search (VNS) algorithm, proposed to solve the PFHPM. This algorithm provided good quality solutions for the PFHPM, solving artificial generated instances from a Monte Carlo Simulation and real data instances, even with limited computational resources. Statistical analyses presented in this work suggest that the new algorithm and model, the PFHPM, can recover more accurately the original category structures related to heterogeneous individual’s perceptions than the original model and algorithm, the HPM. Finally, an illustrative application of the PFHPM is presented, as well as some insights about some new possibilities for it, extending the new model to fuzzy environments

Sobre a integração indefinida de funções racionais complexas: teoria e implementação de algoritmos racionais

We present indefinite integration algorithms for rational functions over subfields of the complex numbers, through an algebraic approach. We study the local algorithm of Bernoulli and rational algorithms for the class of functions in concern, namely, the algorithms of Hermite; Horowitz-Ostrogradsky; Rothstein-Trager and Lazard-Rioboo-Trager. We also study the algorithm of Rioboo for conversion of logarithms involving complex extensions into real arctangent functions, when these logarithms arise from the integration of rational functions with real coefficients. We conclude presenting pseudocodes and codes for implementation in the software Maxima concerning the algorithms studied in this work, as well as to algorithms for polynomial gcd computation; partial fraction decomposition; squarefree factorization; subresultant computation, among other side algorithms for the work. We also present the algorithm of Zeilberger-Almkvist for integration of hyperexpontential functions, as well as its pseudocode and code for Maxima. As an alternative for the algorithms of Rothstein-Trager and Lazard-Rioboo-Trager, we yet present a code for Benoulli’s algorithm for square-free denominators; and another for Czichowski’s algorithm, although this one is not studied in detail in the present work, due to the theoretical basis necessary to understand it, which is beyond this work’s scope. Several examples are provided in order to illustrate the working of the integration algorithms in this text

Avaliação anti-inflamatória e antipeçonhenta das espécies Hancornia speciosa e Mimosa tenuiflora em modelos experimentais de inflamação e envenenamento induzidos por Bothrops jararaca e Tityus serrulatus

Accidents caused by venomous animals represents a significant and serious public health problem in certain regions of Brazil, as well as in other parts of the world by the frequency with which they occur and the mortality they cause. The use of plant extracts as an antidote for poisoning cases is an ancient practice used in many communities that have no access to antivenom. Medicinal plants represent an important source of obtaining bioactive compounds able to assist directly in the treatment of poisoning or indirectly supplementing serum therapy currently used. The aim of this study was to evaluate the effect of extracts, fractions and isolated compounds from M. tenuiflora and H. speciosa in the inflammatory process induced by carrageenan and the venom of B. jararaca and T. serrulatus. The results showed that both M. tenuiflora and H. speciosa were capable of inhibiting cell migration and cytokines levels in peritonitis induced by carrageenin and venom of T. serrulatus. In poisoning by B. jararaca model, mice treated with the plants in studies decreased the leukocyte influx into the peritoneal cavity. Finally the M. tenuiflora and H. speciosa had antiphlogistic activity, reducing edema formation and exerted inhibitory action of leukocyte migration in local inflammation induced by the venom of B. jararaca. Through of Thin Layer Chromatography (TLC) analysis was possible identified the presence of flavonoids ,saponins and/or terpenes in aqueous extract of M. tenuiflora. By High Performance Liquid Chromatography analysis, it was possible to identify the presence of rutin and chlorogenic acid in aqueous extract of H. speciosa. We conclude that the administration of extracts, fractions and isolated compounds of H. speciosa and M. tenuiflora resulted in inhibition of the inflammatory process in different experimental models. This study demonstrates for the first time the effect of M. tenuiflora and H. speciosa in inhibition of the inflammation caused by B. jararaca and T. serrulatus venom.

Distribuição de derivados de petróleo por redes de polidutos: uma abordagem através de algoritmos evolucionários híbridos para um problema triobjetivo

An important problem faced by the oil industry is to distribute multiple oil products through pipelines. Distribution is done in a network composed of refineries (source nodes), storage parks (intermediate nodes), and terminals (demand nodes) interconnected by a set of pipelines transporting oil and derivatives between adjacent areas. Constraints related to storage limits, delivery time, sources availability, sending and receiving limits, among others, must be satisfied. Some researchers deal with this problem under a discrete viewpoint in which the flow in the network is seen as batches sending. Usually, there is no separation device between batches of different products and the losses due to interfaces may be significant. Minimizing delivery time is a typical objective adopted by engineers when scheduling products sending in pipeline networks. However, costs incurred due to losses in interfaces cannot be disregarded. The cost also depends on pumping expenses, which are mostly due to the electricity cost. Since industrial electricity tariff varies over the day, pumping at different time periods have different cost. This work presents an experimental investigation of computational methods designed to deal with the problem of distributing oil derivatives in networks considering three minimization objectives simultaneously: delivery time, losses due to interfaces and electricity cost. The problem is NP-hard and is addressed with hybrid evolutionary algorithms. Hybridizations are mainly focused on Transgenetic Algorithms and classical multi-objective evolutionary algorithm architectures such as MOEA/D, NSGA2 and SPEA2. Three architectures named MOTA/D, NSTA and SPETA are applied to the problem. An experimental study compares the algorithms on thirty test cases. To analyse the results obtained with the algorithms Pareto-compliant quality indicators are used and the significance of the results evaluated with non-parametric statistical tests.

Metodologia de estimação de estados para tratamento de medições errôneas e registros não sincronizados em algoritmos de localização de faltas em linhas de transmissão

The performance of algorithms for fault location i n transmission lines is directly related to the accuracy of its input data. Thus, fa ctors such as errors in the line parameters, failures in synchronization of oscillographic recor ds and errors in measurements of voltage and current can significantly influence the accurac y of algorithms that use bad data to indicate the fault location. This work presents a new method ology for fault location in transmission lines based on the theory of state estimation in or der to determine the location of faults more accurately by considering realistic systematic erro rs that may be present in measurements of voltage and current. The methodology was implemente d in two stages: pre-fault and post- fault. In the first step, assuming non-synchronized data, the synchronization angle and positive sequence line parameters are estimated, an d in the second, the fault distance is estimated. Besides calculating the most likely faul t distance obtained from measurement errors, the variance associated with the distance f ound is also determined, using the errors theory. This is one of the main contributions of th is work, since, with the proposed algorithm, it is possible to determine a most likely zone of f ault incidence, with approximately 95,45% of confidence. Tests for evaluation and validation of the proposed algorithm were realized from actual records of faults and from simulations of fictitious transmission systems using ATP software. The obtained results are relevant to show that the proposed estimation approach works even adopting realistic variances, c ompatible with real equipments errors.

Análise de desempenho de algoritmos de compressão de dados com perda para aplicações industriais

The great amount of data generated as the result of the automation and process supervision in industry implies in two problems: a big demand of storage in discs and the difficulty in streaming this data through a telecommunications link. The lossy data compression algorithms were born in the 90’s with the goal of solving these problems and, by consequence, industries started to use those algorithms in industrial supervision systems to compress data in real time. These algorithms were projected to eliminate redundant and undesired information in a efficient and simple way. However, those algorithms parameters must be set for each process variable, becoming impracticable to configure this parameters for each variable in case of systems that monitor thousands of them. In that context, this paper propose the algorithm Adaptive Swinging Door Trending that consists in a adaptation of the Swinging Door Trending, as this main parameters are adjusted dynamically by the analysis of the signal tendencies in real time. It’s also proposed a comparative analysis of performance in lossy data compression algorithms applied on time series process variables and dynamometer cards. The algorithms used to compare were the piecewise linear and the transforms.

Algoritmo modificado de PSO matricial aplicado a identificação de sistemas com análise de convergência

Recentemente diversas técnicas de computação evolucionárias têm sido utilizadas em áreas como estimação de parâmetros de processos dinâmicos lineares e não lineares ou até sujeitos a incertezas. Isso motiva a utilização de algoritmos como o otimizador por nuvem de partículas (PSO) nas referidas áreas do conhecimento. Porém, pouco se sabe sobre a convergência desse algoritmo e, principalmente, as análises e estudos realizados têm se concentrado em resultados experimentais. Por isso, é objetivo deste trabalho propor uma nova estrutura para o PSO que permita analisar melhor a convergência do algoritmo de forma analítica. Para isso, o PSO é reestruturado para assumir uma forma matricial e reformulado como um sistema linear por partes. As partes serão analisadas de forma separada e será proposta a inserção de um fator de esquecimento que garante que a parte mais significativa deste sistema possua autovalores dentro do círculo de raio unitário. Também será realizada a análise da convergência do algoritmo como um todo, utilizando um critério de convergência quase certa, aplicável a sistemas chaveados. Na sequência, serão realizados testes experimentais de maneira a verificar o comportamento dos autovalores após a inserção do fator de esquecimento. Posteriormente, os algoritmos de identificação de parâmetros tradicionais serão combinados com o PSO matricial, de maneira a tornar os resultados da identificação tão bons ou melhores que a identificação apenas com o PSO ou, apenas com os algoritmos tradicionais. Os resultados mostram a convergência das partículas em uma região delimitada e que as funções obtidas após a combinação do algoritmo PSO matricial com os algoritmos convencionais, apresentam maior generalização para o sistema apresentado. As conclusões a que se chega é que a hibridização, apesar de limitar a busca por uma partícula mais apta do PSO, permite um desempenho mínimo para o algoritmo e ainda possibilita melhorar o resultado obtido com os algoritmos tradicionais, permitindo a representação do sistema aproximado em quantidades maiores de frequências.

Evoluções nas modelagens de substratos artificiais (metamateriais) com práticas experimentais em antenas de microfita

Esse trabalho tem como objetivo apresentar configurações de substratos dielétricos inovadores projetados e fabricados a partir de estruturas metamateriais. Para isso, são avaliados diversos fatores que podem influenciar no seu desempenho. A princípio, foi feito um levantamento bibliográfico a respeito dos temas, que estão relacionados com as pesquisas sobre: materiais dielétricos, metamateriais e interferometria óptica. São estudados, pesquisados e desenvolvidos dois projetos experimentais propostos, que comprovam a eficiência de métodos, para se alcançar a permeabilidade magnética negativa na formação de metamateriais. O primeiro projeto é a produção de uma nova estrutura, com u anel ressoador triangular equilateral (Split Equilateral Triangle Resonator - SETR). O segundo projeto: aplica os princípios da interferometria óptica, especialmente, com o interferômetro de Fabry-Perot. Técnicas para obtenção dos dispositivos que complementam a placa metamaterial como substrato foram pesquisadas na literatura e exemplificadas principalmente por meio de simulações e medições. Foram feitas comparações, simulações e medições de estruturas convencionais e especiais. As experiências se concentram nas evoluções e modelagens de substratos metamateriais com aplicações em antenas de microfita. As melhorias de alguns parâmetros de desempenho de antenas também são relatadas. As simulações das antenas foram feitas nos programas computacionais comerciais. Os resultados medidos foram obtidos com um analisador vetorial de redes da Rhode and Schwarz modelo ZVB 14.