Optimization procedures in the design of continuous induction hardening and tempering installations for magnetic steel bars

An inverse problem concerning the industrial process of steel bars hardening and tempering is considered. The associated optimization problem is formulated in terms of membership functions and, for the sake of comparison, also in terms of quadratic residuals; both geometric and electromagnetic design variables have been considered. The numerical solution is achieved by coupling a finite difference procedure for the calculation of the electromagnetic and thermal fields to a deterministic strategy of minimization based on modified Flctcher and Reeves method. © 1998 IEEE.

Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders

This paper proposes a new approach for optimal phasor measurement units placement for fault location on electric power distribution systems using Greedy Randomized Adaptive Search Procedure metaheuristic and Monte Carlo simulation. The optimized placement model herein proposed is a general methodology that can be used to place devices aiming to record the voltage sag magnitudes for any fault location algorithm that uses voltage information measured at a limited set of nodes along the feeder. An overhead, three-phase, three-wire, 13.8 kV, 134-node, real-life feeder model is used to evaluate the algorithm. Tests show that the results of the fault location methodology were improved thanks to the new optimized allocation of the meters pinpointed using this methodology. © 2011 IEEE.

Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

Planejamento da expansão de sistemas de transmissão usando a metaheurística de busca em vizinhança variável

Pós-graduação em Engenharia Elétrica - FEIS

Empilhamento sísmico por superfície de reflexão comum: um novo algoritmo usando otimização global e local

O método de empilhamento sísmico por Superfície de Reflexão Comum (ou empilhamento SRC) produz a simulação de seções com afastamento nulo (NA) a partir dos dados de cobertura múltipla. Para meios 2D, o operador de empilhamento SRC depende de três parâmetros que são: o ângulo de emergência do raio central com fonte-receptor nulo (β₀), o raio de curvatura da onda ponto de incidência normal (R_NIP) e o raio de curvatura da onda normal (R_N). O problema crucial para a implementação do método de empilhamento SRC consiste na determinação, a partir dos dados sísmicos, dos três parâmetros ótimos associados a cada ponto de amostragem da seção AN a ser simulada. No presente trabalho foi desenvolvido uma nova sequência de processamento para a simulação de seções AN por meio do método de empilhamento SRC. Neste novo algoritmo, a determinação dos três parâmetros ótimos que definem o operador de empilhamento SRC é realizada em três etapas: na primeira etapa são estimados dois parâmetros (β°₀ e R°_NIP) por meio de uma busca global bidimensional nos dados de cobertura múltipla. Na segunda etapa é usado o valor de β°₀ estimado para determinar-se o terceiro parâmetro (R°_N) através de uma busca global unidimensional na seção AN resultante da primeira etapa. Em ambas etapas as buscas globais são realizadas aplicando o método de otimização Simulated Annealing (SA). Na terceira etapa são determinados os três parâmetros finais (β₀, R_NIP e R_N) através uma busca local tridimensional aplicando o método de otimização Variable Metric (VM) nos dados de cobertura múltipla. Nesta última etapa é usado o trio de parâmetros (β°₀, R°_NIP, R°_N) estimado nas duas etapas anteriores como aproximação inicial. Com o propósito de simular corretamente os eventos com mergulhos conflitantes, este novo algoritmo prevê a determinação de dois trios de parâmetros associados a pontos de amostragem da seção AN onde há intersecção de eventos. Em outras palavras, nos pontos da seção AN onde dois eventos sísmicos se cruzam são determinados dois trios de parâmetros SRC, os quais serão usados conjuntamente na simulação dos eventos com mergulhos conflitantes. Para avaliar a precisão e eficiência do novo algoritmo, este foi aplicado em dados sintéticos de dois modelos: um com interfaces contínuas e outro com uma interface descontinua. As seções AN simuladas têm elevada razão sinal-ruído e mostram uma clara definição dos eventos refletidos e difratados. A comparação das seções AN simuladas com as suas similares obtidas por modelamento direto mostra uma correta simulação de reflexões e difrações. Além disso, a comparação dos valores dos três parâmetros otimizados com os seus correspondentes valores exatos calculados por modelamento direto revela também um alto grau de precisão. Usando a aproximação hiperbólica dos tempos de trânsito, porém sob a condição de R_NIP = R_N, foi desenvolvido um novo algoritmo para a simulação de seções AN contendo predominantemente campos de ondas difratados. De forma similar ao algoritmo de empilhamento SRC, este algoritmo denominado empilhamento por Superfícies de Difração Comum (SDC) também usa os métodos de otimização SA e VM para determinar a dupla de parâmetros ótimos (β₀, R_NIP) que definem o melhor operador de empilhamento SDC. Na primeira etapa utiliza-se o método de otimização SA para determinar os parâmetros iniciais β°₀ e R°_NIP usando o operador de empilhamento com grande abertura. Na segunda etapa, usando os valores estimados de β°₀ e R°_NIP, são melhorados as estimativas do parâmetro R_NIP por meio da aplicação do algoritmo VM na seção AN resultante da primeira etapa. Na terceira etapa são determinados os melhores valores de β°₀ e R°_NIP por meio da aplicação do algoritmo VM nos dados de cobertura múltipla. Vale salientar que a aparente repetição de processos tem como efeito a atenuação progressiva dos eventos refletidos. A aplicação do algoritmo de empilhamento SDC em dados sintéticos contendo campos de ondas refletidos e difratados, produz como resultado principal uma seção AN simulada contendo eventos difratados claramente definidos. Como uma aplicação direta deste resultado na interpretação de dados sísmicos, a migração pós-empilhamento em profundidade da seção AN simulada produz uma seção com a localização correta dos pontos difratores associados às descontinuidades do modelo.

Práticas de leitura e escrita em contexto acadêmico: relações (hiper)textuais singulares

The present article aims at reflecting about the discursive practices of writing and reading on the net, more specifically about the writing and reading methods used by the undergraduate and graduated teachers, based on an internet search engine. It’s of interest to investigate: i) the (hyper) textual relations established in the context thought as permitted by the electronic resources; ii) the discursive marks that arise (are arisen) in a singular way of reading (and/or writing). The set of material was produced during a university extension course about reading and cyberspace, whose context consisted of a drawing production of the reading process on an internet search engine, on the basis of the signifier “apple”. Based on the French Discourse Analysis and assumptions from the New Literacy Studies, we intended to discuss the operating procedures of the internet search and the effects of meanings produced by the subject during his/her reading/writing process.

On the optical flow model selection through metaheuristics

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

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Seeing beyond reading: a survey on visual text analytics

We review recent visualization techniques aimed at supporting tasks that require the analysis of text documents, from approaches targeted at visually summarizing the relevant content of a single document to those aimed at assisting exploratory investigation of whole collections of documents.Techniques are organized considering their target input materialeither single texts or collections of textsand their focus, which may be at displaying content, emphasizing relevant relationships, highlighting the temporal evolution of a document or collection, or helping users to handle results from a query posed to a search engine.We describe the approaches adopted by distinct techniques and briefly review the strategies they employ to obtain meaningful text models, discuss how they extract the information required to produce representative visualizations, the tasks they intend to support and the interaction issues involved, and strengths and limitations. Finally, we show a summary of techniques, highlighting their goals and distinguishing characteristics. We also briefly discuss some open problems and research directions in the fields of visual text mining and text analytics.

Proteomic analysis of Porphyromonas gingivalis exposed to nicotine and cotinine

Cogo K, de Andrade A, Labate CA, Bergamaschi CC, Berto LA, Franco GCN, Goncalves RB, Groppo FC. Proteomic analysis of Porphyromonas gingivalis exposed to nicotine and cotinine. J Periodont Res 2012; 47: 766775. (c) 2012 John Wiley & Sons A/S Background and Objective: Smokers are more predisposed than nonsmokers to infection with Porphyromonas gingivalis, one of the most important pathogens involved in the onset and development of periodontitis. It has also been observed that tobacco, and tobacco derivatives such as nicotine and cotinine, can induce modifications to P. gingivalis virulence. However, the effect of the major compounds derived from cigarettes on expression of protein by P.gingivalis is poorly understood. Therefore, this study aimed to evaluate and compare the effects of nicotine and cotinine on the P.gingivalis proteomic profile. Material and Methods: Total proteins of P gingivalis exposed to nicotine and cotinine were extracted and separated by two-dimensional electrophoresis. Proteins differentially expressed were successfully identified through liquid chromatography-mass spectrometry and primary sequence databases using MASCOT search engine, and gene ontology was carried out using DAVID tools. Results: Of the approximately 410 protein spots that were reproducibly detected on each gel, 23 were differentially expressed in at least one of the treatments. A particular increase was seen in proteins involved in metabolism, virulence and acquisition of peptides, protein synthesis and folding, transcription and oxidative stress. Few proteins showed significant decreases in expression; those that did are involved in cell envelope biosynthesis and proteolysis and also in metabolism. Conclusion: Our results characterized the changes in the proteome of P.gingivalis following exposure to nicotine and cotinine, suggesting that these substances may modulate, with minor changes, protein expression. The present study is, in part, a step toward understanding the potential smokepathogen interaction that may occur in smokers with periodontitis.

Electronic Properties of Water in Liquid Environment. A Sequential QM/MM Study Using the Free Energy Gradient Method

There is a continuous search for theoretical methods that are able to describe the effects of the liquid environment on molecular systems. Different methods emphasize different aspects, and the treatment of both the local and bulk properties is still a great challenge. In this work, the electronic properties of a water molecule in liquid environment is studied by performing a relaxation of the geometry and electronic distribution using the free energy gradient method. This is made using a series of steps in each of which we run a purely molecular mechanical (MM) Monte Carlo Metropolis simulation of liquid water and subsequently perform a quantum mechanical/molecular mechanical (QM/MM) calculation of the ensemble averages of the charge distribution, atomic forces, and second derivatives. The MP2/aug-cc-pV5Z level is used to describe the electronic properties of the QM water. B3LYP with specially designed basis functions are used for the magnetic properties. Very good agreement is found for the local properties of water, such as geometry, vibrational frequencies, dipole moment, dipole polarizability, chemical shift, and spin-spin coupling constants. The very good performance of the free energy method combined with a QM/MM approach along with the possible limitations are briefly discussed.

Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning to Optimization of Broad-Band Reflector Antennas Satellite

This paper aims to provide an improved NSGA-II (Non-Dominated Sorting Genetic Algorithm-version II) which incorporates a parameter-free self-tuning approach by reinforcement learning technique, called Non-Dominated Sorting Genetic Algorithm Based on Reinforcement Learning (NSGA-RL). The proposed method is particularly compared with the classical NSGA-II when applied to a satellite coverage problem. Furthermore, not only the optimization results are compared with results obtained by other multiobjective optimization methods, but also guarantee the advantage of no time-spending and complex parameter tuning.

Proteomic profiling of the rat hypothalamus

Background: The hypothalamus plays a pivotal role in numerous mechanisms highly relevant to the maintenance of body homeostasis, such as the control of food intake and energy expenditure. Impairment of these mechanisms has been associated with the metabolic disturbances involved in the pathogenesis of obesity. Since rodent species constitute important models for metabolism studies and the rat hypothalamus is poorly characterized by proteomic strategies, we performed experiments aimed at constructing a two-dimensional gel electrophoresis (2-DE) profile of rat hypothalamus proteins. Results: As a first step, we established the best conditions for tissue collection and protein extraction, quantification and separation. The extraction buffer composition selected for proteome characterization of rat hypothalamus was urea 7 M, thiourea 2 M, CHAPS 4%, Triton X-100 0.5%, followed by a precipitation step with chloroform/methanol. Two-dimensional (2-D) gels of hypothalamic extracts from four-month-old rats were analyzed; the protein spots were digested and identified by using tandem mass spectrometry and database query using the protein search engine MASCOT. Eighty-six hypothalamic proteins were identified, the majority of which were classified as participating in metabolic processes, consistent with the finding of a large number of proteins with catalytic activity. Genes encoding proteins identified in this study have been related to obesity development. Conclusion: The present results indicate that the 2-DE technique will be useful for nutritional studies focusing on hypothalamic proteins. The data presented herein will serve as a reference database for studies testing the effects of dietary manipulations on hypothalamic proteome. We trust that these experiments will lead to important knowledge on protein targets of nutritional variables potentially able to affect the complex central nervous system control of energy homeostasis.

Metodi di ottimizzazione morfologica nel progetto preliminare di propulsori aeronautici avanzati

The aim of this Doctoral Thesis is to develop a genetic algorithm based optimization methods to find the best conceptual design architecture of an aero-piston-engine, for given design specifications. Nowadays, the conceptual design of turbine airplanes starts with the aircraft specifications, then the most suited turbofan or turbo propeller for the specific application is chosen. In the aeronautical piston engines field, which has been dormant for several decades, as interest shifted towards turboaircraft, new materials with increased performance and properties have opened new possibilities for development. Moreover, the engine’s modularity given by the cylinder unit, makes it possible to design a specific engine for a given application. In many real engineering problems the amount of design variables may be very high, characterized by several non-linearities needed to describe the behaviour of the phenomena. In this case the objective function has many local extremes, but the designer is usually interested in the global one. The stochastic and the evolutionary optimization techniques, such as the genetic algorithms method, may offer reliable solutions to the design problems, within acceptable computational time. The optimization algorithm developed here can be employed in the first phase of the preliminary project of an aeronautical piston engine design. It’s a mono-objective genetic algorithm, which, starting from the given design specifications, finds the engine propulsive system configuration which possesses minimum mass while satisfying the geometrical, structural and performance constraints. The algorithm reads the project specifications as input data, namely the maximum values of crankshaft and propeller shaft speed and the maximal pressure value in the combustion chamber. The design variables bounds, that describe the solution domain from the geometrical point of view, are introduced too. In the Matlab® Optimization environment the objective function to be minimized is defined as the sum of the masses of the engine propulsive components. Each individual that is generated by the genetic algorithm is the assembly of the flywheel, the vibration damper and so many pistons, connecting rods, cranks, as the number of the cylinders. The fitness is evaluated for each individual of the population, then the rules of the genetic operators are applied, such as reproduction, mutation, selection, crossover. In the reproduction step the elitist method is applied, in order to save the fittest individuals from a contingent mutation and recombination disruption, making it undamaged survive until the next generation. Finally, as the best individual is found, the optimal dimensions values of the components are saved to an Excel® file, in order to build a CAD-automatic-3D-model for each component of the propulsive system, having a direct pre-visualization of the final product, still in the engine’s preliminary project design phase. With the purpose of showing the performance of the algorithm and validating this optimization method, an actual engine is taken, as a case study: it’s the 1900 JTD Fiat Avio, 4 cylinders, 4T, Diesel. Many verifications are made on the mechanical components of the engine, in order to test their feasibility and to decide their survival through generations. A system of inequalities is used to describe the non-linear relations between the design variables, and is used for components checking for static and dynamic loads configurations. The design variables geometrical boundaries are taken from actual engines data and similar design cases. Among the many simulations run for algorithm testing, twelve of them have been chosen as representative of the distribution of the individuals. Then, as an example, for each simulation, the corresponding 3D models of the crankshaft and the connecting rod, have been automatically built. In spite of morphological differences among the component the mass is almost the same. The results show a significant mass reduction (almost 20% for the crankshaft) in comparison to the original configuration, and an acceptable robustness of the method have been shown. The algorithm here developed is shown to be a valid method for an aeronautical-piston-engine preliminary project design optimization. In particular the procedure is able to analyze quite a wide range of design solutions, rejecting the ones that cannot fulfill the feasibility design specifications. This optimization algorithm could increase the aeronautical-piston-engine development, speeding up the production rate and joining modern computation performances and technological awareness to the long lasting traditional design experiences.

Problem-specific design of metaheuristics for constrained spanning tree problems

When designing metaheuristic optimization methods, there is a trade-off between application range and effectiveness. For large real-world instances of combinatorial optimization problems out-of-the-box metaheuristics often fail, and optimization methods need to be adapted to the problem at hand. Knowledge about the structure of high-quality solutions can be exploited by introducing a so called bias into one of the components of the metaheuristic used. These problem-specific adaptations allow to increase search performance. This thesis analyzes the characteristics of high-quality solutions for three constrained spanning tree problems: the optimal communication spanning tree problem, the quadratic minimum spanning tree problem and the bounded diameter minimum spanning tree problem. Several relevant tree properties, that should be explored when analyzing a constrained spanning tree problem, are identified. Based on the gained insights on the structure of high-quality solutions, efficient and robust solution approaches are designed for each of the three problems. Experimental studies analyze the performance of the developed approaches compared to the current state-of-the-art.