A genetic neuro-model reference adaptive controller for petroleum wells drilling operations

Motivated by rising drilling operation costs, the oil industry has shown a trend towards real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated to parameters modeling. One of the drill-bit performance evaluators, the Rate of Penetration (ROP), has been used in the literature as a drilling control parameter. However, the relationships between the operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on the Auto-Regressive with Extra Input Signals model, or ARX model, to accomplish the system identification and on a Genetic Algorithm (GA) to provide a robust control for the ROP. Results of simulations run over a real offshore oil field data, consisted of seven wells drilled with equal diameter bits, are provided. © 2006 IEEE.

Intelligent alarm processing

This paper presents the analysis that have been carried out in the alarm system of the DCRanger EMS. The intention of this study is to present the problem of alarm processing in electric energy control centers, its various aspects and operational difficulties due to operator needs. Some tests are produced in order to identify the desirable features an alarm system should possess in order to be of effective help in the operative duty. © 2006 IEEE.

Distribution network reconfiguration using an efficient evolutionary algorithm

Network reconfiguration is an important tool to optimize the operating conditions of a distribution system. This is accomplished modifying the network structure of distribution feeders by changing the open/close status of sectionalizing switches. This not only reduces the power losses, but also relieves the overloading of the network components. Network reconfiguration belongs to a complex family of problems because of their combinatorial nature and multiple constraints. This paper proposes a solution to this problem, using a specialized evolutionary algorithm, with a novel codification, and a brand new way of implement the genetic operators considering the problem characteristics. The algorithm is presented and tested in a real distribution system, showing excellent results and computational efficiency. © 2007 IEEE.

Transmission network expansion planning considering uncertainty in generation and demand

This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering uncertainty in demand and generation. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The model presented results in an optimization problem that is solved using a specialized genetic algorithm. The results obtained for known systems from the literature show that cheaper plans can be found satisfying the uncertainty in demand and generation. ©2008 IEEE.

Um novo jogo para o estudo do raciocínio combinatório e do cálculo de probabilidade

We present an educational proposal for the study of combinatorial reasoning and calculation of probabilities based on a game and problem solving methodology, aiming to support the teaching of mathematical content. A review of the literature related to the teaching and learning of the concepts of combinatorial reasoning and probability is presented. The game is original, using a board game similar to Tic-tac-toe, and the movements of its parts have some similarities, in particular those made with the rook and pawn pieces of the game of chess. We formulate various activities (problems) involving the game which, in the process of solving them, using the problem solving methodology and with the appropriate intervention of the teacher, encourage students to develop strategies for counting, an indispensable tool in the initial study of Combinatorial Analysis and Calculation of Probabilities.

Uma proposta didático-pedagógica para o estudo da concepção clássica de probabilidade

We present in this paper a pedagogical-didactic proposal for the teaching of Laplace Probability. The starting point for building the concept of probability is a game situation associated with the methodology of problem-solving. The theoretical reference for the concept of game is constructivist teaching of mathematics. Mathematical knowledge is constructed based on problems that generate new concepts and / or new content. The proposed game is original. Our proposal can be used both in the last cycle of basic education but also in high school, and may inform the practice of teachers who teach basic concepts of probability.

An application of a modified constructive heuristic algorithm to transmission expansion planning

Transmission expansion planning (TEP) is a non-convex optimization problem that can be solved via different heuristic algorithms. A variety of classical as well as heuristic algorithms in literature are addressed to solve TEP problem. In this paper a modified constructive heuristic algorithm (CHA) is proposed for solving such a crucial problem. Most of research papers handle TEP problem by linearization of the non-linear mathematical model while in this research TEP problem is solved via CHA using non-linear model. The proposed methodology is based upon Garver's algorithm capable of applying to a DC model. Simulation studies and tests results on the well known transmission network such as: Garver and IEEE 24-bus systems are carried out to show the significant performance as well as the effectiveness of the proposed algorithm. © 2011 IEEE.

Image categorization through optimum path forest and visual words

Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE.

Pesquisa em Resolução de Problemas: caminhos, avanços e novas perspectivas

We discuss the knowledge that has been constructed regarding Problem Solving in Math Education as a result of research developed by GTERP - Work and Study Group in Problem Solving, UNESP-Rio Claro/SP. The research is guided by the following general questions: How do students construct mathematical knowledge and how do teachers implement the methodology of Math Teaching-Learning-Evaluation through Problem Solving? Historical aspects of Problem Solving are very important in the configuration of the current trends for Problem Solving. One of them is the Methodology of Math Teaching-Learning- Evaluation through Problem Solving, based on clear foundations and an approach of renewal. In addition to that methodology, two aspects have been developed by the group: The conception of Math as a science of pattern and order and Discrete Mathematics. The knowledge constructed and the scientific production of GTERP prove its relevant contribution to intensifying dialogues between research and educational practice, students and teachers, and to increasing the possibilities of that practice particularly in Math work.

An enhanced genetic algorithm to solve the static and multistage transmission network expansion planning

An enhanced genetic algorithm (EGA) is applied to solve the long-term transmission expansion planning (LTTEP) problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are presented, (1) generation of an initial population using fast, efficient heuristic algorithms, (2) better implementation of the local improvement phase and (3) efficient solution of linear programming problems (LPs). Critical comparative analysis is made between the proposed genetic algorithm and traditional genetic algorithms. Results using some known systems show that the proposed EGA presented higher efficiency in solving the static and multistage LTTEP problem, solving a smaller number of linear programming problems to find the optimal solutions and thus finding a better solution to the multistage LTTEP problem. Copyright © 2012 Luis A. Gallego et al.

Planejamento em saúde bucal no município de João Pessoa, Estado da Paraíba: o cirurgiãodentista enquanto protagonista da atenção básica

The aim was to identify the perception of Oral Health Planning (OHP) of basic care (BC) dental surgeons (DSs) in João Pessoa, Paraíba State, Brazil. Seventeen BC DSs from João Pessoa were interviewed. A qualitative analysis was performed using the Discourse of the Collective Subject (DCS) methodology. DCS obtained: Impact - My work is effective when the user's need remains at the BC. Social Control - The population participates in the organization of promotional activities, but I think it doesn't have enough maturity to opine on OHP. OHP Basis and Organization - The OHP has a diverse organization and is based on user needs. It can be concluded that the knowledge of the DSs on OHP is varied. There is limited understanding about problem-solving. Social control is considered incipient and weak. It is understood that the organization of the local OHP assumes a diverse character and should be based on user demands.

BBA: A binary bat algorithm for feature selection

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 in-viable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the bats behaviour, which has never been applied to this context so far. The wrapper approach combines the power of exploration of the bats 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 five public datasets have demonstrated that the proposed approach can outperform some well-known swarm-based techniques. © 2012 IEEE.

Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Qualidade de vida de crianças e adolescentes asmáticos: Sua relação com estratégias de enfrentamento materno

Objective: To evaluate the quality of life of asthmatic children and adolescents, its relation with sociodemographic and clinical variables, and maternal coping strategies. Methods: Cross-sectional study in which children and adolescents with asthma answered a quality of life questionnaire, and their mothers did the same with a coping scale. Results: Out of the 42 children and adolescents investigated, 74% were classified as having mild/severe persistent asthma; 19%, mild persistent asthma; and 7%, intermittent asthma. A total of 69% of the participants showed impaired quality of life with mean scores ranging between 4.7 and 3.5, with greater harm in the domain of symptoms (score=3.6). There was a significant association between maternal schooling and the general index of quality of life, whereas maternal coping strategies were not associated with the severity of asthma. A large number of strategies used by mothers to cope with their children's crises were related to the management of stressors or to religious practices, and the latter presented negative correlation with the children's quality of life general index, showing that mothers whose children had worse quality of life used more religious coping. Conclusions: Asthmatic children, particularly those with moderate/severe persistent asthma, showed significant alterations as to quality of life. The high percentage of mothers using religious strategies, particularly in face of more severe clinical conditions, seem to indicate that they feel powerless to act, thus requiring concrete and useful orientation to low income families.

Uma adaptação do método barreira penalidade quasi-Newton ao problema de fluxo de potência ótimo

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