The surprising evolutionary history of South American deer

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

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables

EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

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

An Optimum-Path Forest framework for intrusion detection in computer networks

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

Efficient supervised optimum-path forest classification for large datasets

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

A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest

Nowadays, fraud detection is important to avoid nontechnical energy losses. Various electric companies around the world have been faced with such losses, mainly from industrial and commercial consumers. This problem has traditionally been dealt with using artificial intelligence techniques, although their use can result in difficulties such as a high computational burden in the training phase and problems with parameter optimization. A recently-developed pattern recognition technique called optimum-path forest (OPF), however, has been shown to be superior to state-of-the-art artificial intelligence techniques. In this paper, we proposed to use OPF for nontechnical losses detection, as well as to apply its learning and pruning algorithms to this purpose. Comparisons against neural networks and other techniques demonstrated the robustness of the OPF with respect to commercial losses automatic identification.

Evolutionary Changes in the Complexity of the Tectum of Nontetrapods: A Cladistic Approach

Background: The tectum is a structure localized in the roof of the midbrain in vertebrates, and is taken to be highly conserved in evolution. The present article assessed three hypotheses concerning the evolution of lamination and citoarchitecture of the tectum of nontetrapod animals: 1) There is a significant degree of phylogenetic inertia in both traits studied (number of cellular layers and number of cell classes in tectum); 2) Both traits are positively correlated accross evolution after correction for phylogeny; and 3) Different developmental pathways should generate different patterns of lamination and cytoarchitecture.Methodology/Principal Findings: The hypotheses were tested using analytical-computational tools for phylogenetic hypothesis testing. Both traits presented a considerably large phylogenetic signal and were positively associated. However, no difference was found between two clades classified as per the general developmental pathways of their brains.Conclusions/Significance: The evidence amassed points to more variation in the tectum than would be expected by phylogeny in three species from the taxa analysed; this variation is not better explained by differences in the main course of development, as would be predicted by the developmental clade hypothesis. Those findings shed new light on the evolution of an functionally important structure in nontetrapods, the most basal radiations of vertebrates.

Design of a simple detection cell with extended optical path length for capillary electrophoresis: Application to multiresidue pesticide analysis

Absorbance detection in capillary electrophoresis (CE), offers an excellent mass sensitivity, but poor concentration detection limits owing to very small injection volumes (normally I to 10 nL). This aspect can be a limiting factor in the applicability of CE/UV to detect species at trace levels, particularly pesticide residues. In the present work, the optical path length of an on-column detection cell was increased through a proper connection of the column (75 mu m i.d.) to a capillary detection cell of 180 mu m optical path length in order to improve detectability. It is shown that the cell with an extended optical path length results in a significant gain in terms of signal to noise ratio. The effect of the increase in the optical path length has been evaluated for six pesticides, namely, carbendazim, thiabendazole, imazalil, procymidone triadimefon, and prochloraz. The resulting optical enhancement of the detection cell provided detection limits of ca. 0.3 mu g/mL for the studied compounds, thus enabling the residue analysis by CE/UV.

Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem

The Capacitated Centered Clustering Problem (CCCP) consists of defining a set of p groups with minimum dissimilarity on a network with n points. Demand values are associated with each point and each group has a demand capacity. The problem is well known to be NP-hard and has many practical applications. In this paper, the hybrid method Clustering Search (CS) is implemented to solve the CCCP. This method identifies promising regions of the search space by generating solutions with a metaheuristic, such as Genetic Algorithm, and clustering them into clusters that are then explored further with local search heuristics. Computational results considering instances available in the literature are presented to demonstrate the efficacy of CS. (C) 2010 Elsevier Ltd. All rights reserved.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

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

Multi Objective Evolutionary Algorithm Applied to the Optimal Power Flow Problem

This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.

The temperature coefficient of the optical path length as a function of the temperature in different optical glasses

An interferometric technique was used to determine the temperature coefficient of the optical path length (dS/dT) as a function of the temperature in several optical glasses. The temperature range was between 25degreesC and 180degreesC. The studied samples included undoped and doped oxide glasses, such as low silica calcium aluminosilicate, phosphates, borates and also chalcogenides. The oxide glasses had dS/dT between 10 X 10(-6) K-1 and 20x10(-6) K-1, while for the chalcogenides, these were around 70 x 10(-6)K(-1). The results showed that dS/dTs increased with the temperature in all samples. For samples doped with Nd the dS/dT values were found to be independent of concentration. on the other hand, for the phosphate glass doped with Cr, dS/dT increased about 5% when compared with the Nd doped one. In conclusion, the used interferometric method, which is a considerably simpler and a lower cost technique, and is a useful tool to measure dS/dT in semi-transparent glasses as a function of the composition and temperature. (C) 2004 Elsevier B.V. All rights reserved.

Inversion in the temperature coefficient of the optical path length close to the glass transition temperature in tellurite glasses

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

O problema do Hiker Dice em tabuleiro compacto: um estudo algorítmico

The Hiker Dice was a game recently proposed in a software designed by Mara Kuzmich and Leonardo Goldbarg. In the game a dice is responsible for building a trail on an n x m board. As the dice waits upon a cell on the board, it prints the side that touches the surface. The game shows the Hamiltonian Path Problem Simple Maximum Hiker Dice (Hidi-CHS) in trays Compact Nth , this problem is then characterized by looking for a Hamiltonian Path that maximize the sum of marked sides on the board. The research now related, models the problem through Graphs, and proposes two classes of solution algorithms. The first class, belonging to the exact algorithms, is formed by a backtracking algorithm planed with a return through logical rules and limiting the best found solution. The second class of algorithms is composed by metaheuristics type Evolutionary Computing, Local Ramdomized search and GRASP (Greed Randomized Adaptative Search). Three specific operators for the algorithms were created as follows: restructuring, recombination with two solutions and random greedy constructive.The exact algorithm was teste on 4x4 to 8x8 boards exhausting the possibility of higher computational treatment of cases due to the explosion in processing time. The heuristics algorithms were tested on 5x5 to 14x14 boards. According to the applied methodology for evaluation, the results acheived by the heuristics algorithms suggests a better performance for the GRASP algorithm

Trophallaxis and reproductive conflicts in social bees

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