Improved geometric parameterisation techniques for continuation power flow

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Structural studies of prephenate dehydratase from Mycobacterium tuberculosis H37Rv by SAXS, ultracentrifugation, and computational analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The application of preprocessing and cutting plane techniques for a class of production planning problems

This paper investigates properties of integer programming models for a class of production planning problems. The models are developed within a decision support system to advise a sales team of the products on which to focus their efforts in gaining new orders in the short term. The products generally require processing on several manufacturing cells and involve precedence relationships. The cells are already (partially) committed with products for stock and to satisfy existing orders and therefore only the residual capacities of each cell in each time period of the planning horizon are considered. The determination of production recommendations to the sales team that make use of residual capacities is a nontrivial optimization problem. Solving such models is computationally demanding and techniques for speeding up solution times are highly desirable. An integer programming model is developed and various preprocessing techniques are investigated and evaluated. In addition, a number of cutting plane approaches have been applied. The performance of these approaches which are both general and application specific is examined.

Combining artificial intelligence and human problem solving: Proposing a new architecture for ITS's

This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

Industrial Robotics Applied to Education

This work describes a ludic proposal for programming learning of industrial robots to be developed by groups of engineering students. Two projects are presented: Tic-tac-toe Opponent Robot and Environmentalist Robot. The first project use competitive search techniques of the Artificial Intelligence, computational vision, electronic and pneumatic concepts for ability decision making for a robotic agent on the tic-tae-toe game. The second project consists of a game that contains a questions and answers database about environmental themes. An algorithm selects the group of questions to be answered by the player, analyses the answers and sends the result to a industrial robot through serial port. According with the player performance, the robot makes congratulation movements and giving a gift to the winner player. Otherwise, the robot makes movements, disapproving the player performance.

Combined use of modeling techniques for the development of the conceptual model in simulation projects

The objective of this paper is to utilize the SIPOC, flowchart and IDEF0 modeling techniques combined to elaborate the conceptual model of a simulation project. It is intended to identify the contribution of these techniques in the elaboration of the computational model. To illustrate such application, a practical case of a high-end technology enterprise is presented. The paper concludes that the proposed approach eases the elaboration of the computational model. © 2008 IEEE.

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

Binary Bat Algorithm for Feature Selection

Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.

On computational aspects of discrete Sobolev inner products on the unit circle

In this paper, we show how to compute in O(n2) steps the Fourier coefficients associated with the Gelfand-Levitan approach for discrete Sobolev orthogonal polynomials on the unit circle when the support of the discrete component involving derivatives is located outside the closed unit disk. As a consequence, we deduce the outer relative asymptotics of these polynomials in terms of those associated with the original orthogonality measure. Moreover, we show how to recover the discrete part of our Sobolev inner product. © 2013 Elsevier Inc. All rights reserved.

Previsão de cargas elétricas através de uma Rede Neural Híbrida Back-ART Fuzzy

Pós-graduação em Engenharia Elétrica - FEIS

As contribuições da ciência cognitiva à composição musical

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

Uma abordagem nebulosa de raciocínio baseado em casos para recomendação de sistemas marítimos de produção de petróleo

Pós-graduação em Ciência da Computação - IBILCE

Geoprocessamento e computação inteligente: possibilidades, vantagens e necessidades

Pós-graduação em Geografia - IGCE

Model selection for discriminative restricted boltzmann machines through meta-heuristic techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)