Método Fuzzy para auxílio ao diagnóstico de câncer de mama em ambiente inteligente de telediagnóstico colaborativo para apoio à tomada de decisão

Breast cancer, despite being one of the leading causes of death among women worldwide is a disease that can be cured if diagnosed early. One of the main techniques used in the detection of breast cancer is the Fine Needle Aspirate FNA (aspiration puncture by thin needle) which, depending on the clinical case, requires the analysis of several medical specialists for the diagnosis development. However, such diagnosis and second opinions have been hampered by geographical dispersion of physicians and/or the difficulty in reconciling time to undertake work together. Within this reality, this PhD thesis uses computational intelligence in medical decision-making support for remote diagnosis. For that purpose, it presents a fuzzy method to assist the diagnosis of breast cancer, able to process and sort data extracted from breast tissue obtained by FNA. This method is integrated into a virtual environment for collaborative remote diagnosis, whose model was developed providing for the incorporation of prerequisite Modules for Pre Diagnosis to support medical decision. On the fuzzy Method Development, the process of knowledge acquisition was carried out by extraction and analysis of numerical data in gold standard data base and by interviews and discussions with medical experts. The method has been tested and validated with real cases and, according to the sensitivity and specificity achieved (correct diagnosis of tumors, malignant and benign respectively), the results obtained were satisfactory, considering the opinions of doctors and the quality standards for diagnosis of breast cancer and comparing them with other studies involving breast cancer diagnosis by FNA.

Otimização do Uso das Águas da Barragem Santa Cruz-RN

The semiarid potiguar presents a quite discrepant. It is a region with one of the highest rates of artificial lake the world, but the policy of building dams to mitigate the problem of water scarcity does not solve, given that they have not demonstrated the ability to ensure supply human priority during periods of great drought and fail to solve the widespread demand existent in the semiarid. This work aims to present the optimal allocation of water, according to multiple uses and limited availability of water resources in the reservoir, from the simulation of the operation of the same, with the application of techniques to support decision making and performance evaluation alternatives for water use. The reservoir of Santa Cruz, the second largest reservoir of RN with storage capacity of approximately 600 million cubic meters, located about 20 km from the town of Apodi in RN, was conceived as a way to promote economic development in the region as well as the water supply of nearby towns. The techniques used are the simulation model of network flow ACQUANET and also the set of performance indicators. The results showed that the container has the capacity to serve up to 3,83m3/s flow required by existing uses, without any compromising the same. However, it was also observed that all anticipated future demands are implemented it will generate failures in meeting some uses

Sistema inteligente para apoio à decisão na operação de uma malha de escoamento de petróleo

The petroleum production pipeline networks are inherently complex, usually decentralized systems. Strict operational constraints are applied in order to prevent serious problems like environmental disasters or production losses. This paper describes an intelligent system to support decisions in the operation of these networks, proposing a staggering for the pumps of transfer stations that compose them. The intelligent system is formed by blocks which interconnect to process the information and generate the suggestions to the operator. The main block of the system uses fuzzy logic to provide a control based on rules, which incorporate knowledge from experts. Tests performed in the simulation environment provided good results, indicating the applicability of the system in a real oil production environment. The use of the stagger proposed by the system allows a prioritization of the transfer in the network and a flow programming

Análise de desempenho de vendas em telecomunicações utilizando técnicas de mineração de dados

Nowadays, telecommunications is one of the most dynamic and strategic areas in the world. Organizations are always seeking to find new management practices within an ever increasing competitive environment where resources are getting scarce. In this scenario, data obtained from business and corporate processes have even greater importance, although this data is not yet adequately explored. Knowledge Discovery in Databases (KDD) appears then, as an option to allow the study of complex problems in different areas of management. This work proposes both a systematization of KDD activities using concepts from different methodologies, such as CRISP-DM, SEMMA and FAYYAD approaches and a study concerning the viability of multivariate regression analysis models to explain corporative telecommunications sales using performance indicators. Thus, statistical methods were outlined to analyze the effects of such indicators on the behavior of business productivity. According to business and standard statistical analysis, equations were defined and fit to their respective determination coefficients. Tests of hypotheses were also conducted on parameters with the purpose of validating the regression models. The results show that there is a relationship between these development indicators and the amount of sales

Sistema inteligente para apoio à decisão na operação de uma malha de escoamento de petróleo

The petroleum production pipeline networks are inherently complex, usually decentralized systems. Strict operational constraints are applied in order to prevent serious problems like environmental disasters or production losses. This paper describes an intelligent system to support decisions in the operation of these networks, proposing a staggering for the pumps of transfer stations that compose them. The intelligent system is formed by blocks which interconnect to process the information and generate the suggestions to the operator. The main block of the system uses fuzzy logic to provide a control based on rules, which incorporate knowledge from experts. Tests performed in the simulation environment provided good results, indicating the applicability of the system in a real oil production environment. The use of the stagger proposed by the system allows a prioritization of the transfer in the network and a flow programming

Apoio governamental à inovação Tecnológica: análise da indústria farmacêutica paraense

The transformations economical, cultural and social that happen in world ambit they are associated to the intense progress and expansion of new technologies, forcing governments, people, companies and nations to the introduction of new patterns of behavior, forcing, in that way, to the continuous renewal of products and technological processes to maintain the competitiveness, so much among nations, as in the managerial world. In that matter, the technological innovation is recognized as basic factor of maintainable economical competitiveness, being the responsible for the breaking and/or improvement of the techniques and production processes, what presupposes the systematization varied institutional arrangements that they involve firms, interaction nets among companies, government agencies, universities, research institutes, laboratories of companies and scientists and engineers activities. Those arrangements, to the if they articulate with the educational system, with the industrial and managerial section and, also, with the financial institutions, they take the form that Freeman (1987) it coined of national system of innovation, promoted through public politics of CT&I, which seek to induce and to support innovative initiatives in the companies, as well as to establish demands and to prioritize vocations and regional potentialities. In that context of government support to the technological innovation interferes this study, that it looked for to know the reasons of the fragility innovative in the pharmaceutical industry of State of Pará in Brazil, pointed for PINTEC (2005), starting from the point of view of the businessmen of that section. For such, the qualitative approach was used - with interviews directing semi and the technique of the content analysis. The results of the research pointed that the fragilities innovative of the section links to the ignorance of the government support to the technological innovation on the part of the businessmen of the pharmaceutical industry of State of Pará in Brazil

Modelo de decisão multicritério para seleções interciclo das universidades novas: estudo na Universidade Federal do Rio Grande do Norte

The discussions wherein develop proposals for university reform in Brazil include, among other things, the conception of the university titled "New University", whose structural origin comes from the bill of higher education reform and unification of the foundations of education European upper (Bologna process). At its core, the Bologna process has imposed a series of transformations, among which, the promotion of mobility, as a stimulus to interinstitutional cooperation to enable an better and bigger qualification of the students. Nevertheless, what we see is that this point is one of the main points made flawed by Brazilian institutions that have adopted this model of higher education. An example is the Bachelor of Science and Technology - BC&T, Federal University of Rio Grande do Norte - UFRN, where there are problems of the internal order, represented by the problem of the reusing of the disciplines, such also of external order, in cases of transfers interinstitutional. Because of this, and knowing that this is a typical problem in which multiple criteria are involved, the aim of this study is to propose a multicriteria model for selection of interciclo of the BC&T of the UFRN which addresses the issue of mobility. For this, this study was of exploratory and study case nature, use as tools of data collection, the bibliographic and documentary research, as well as semi-structured interviews. For the elaboration of the model, were used the five phases most commonly used in the modeling of problems in operational research in a sample of 91 students of BC&T. As a result, we obtained a model that addresses the issue of internal and external mobility of the school and that, moreover, was also more robust and fair than the current model of BC&T and also what is used in other courses of the UFRN, taking into consideration the expected results by the decision makers

Modelagem da decisão por pacotes de viagem: um estudo usando processo de hierarquia analítica AHP

The objective of this dissertation is to propose a Multi Criteria Decision Aid Model to be used by the costumers of the travel agencies and help them to choose the best package travel. The main objective is to contribute for the simplification of the travel package decision choice from the identification of the models of values and preference of the customers and applying them to the existing package. It is used the Analytic Hierarchy Process (AHP) method to structuralize a decision hierarchic model composed by six criteria (package cost, hotel category, security of the city, travel time, direct flight and position in ranking of the 10 most visited destination) and five real alternatives of packages for a holiday of three days created from travel agency data. The decision analysis was realized for the choice of a travel package by a group composed by two couples that regularly travels together, to which was asked to do a pairwise judgment of the criteria and the alternatives. The mains results show that, although been a group that travels together, there are different models of values in the weights of the criteria and a certain convergence in the scales of preferences of the alternatives in the criteria. It was not pointed a dominant alternative for all the members of the group separately, but an analysis of a total utility of the group shows a classification and an order of the travel packages and an alternative clearly in front of the others. The sensitivity analysis revels that there are changes in the ranking, but the two alternatives best classified in the normal analysis are the same ones in the sensitivity analysis, although with the positions changed. The analysis also led to a simplification of the process with the exclusion of alternatives dominated for the others ones. As main conclusion, it is evaluated that the model and method suggested allow a simplification of the decision process in the choice of travel packages

Análise de critérios de decisão em estratégia de arranjos produtivos locais: um estudo aplicando o processo de hierarquia analítica (AHP) no setor de cerâmica

This master thesis has the objective of investigating the strategic decision criteria of participants of Local Production Arrangements (LPA) in Brazil. The LPA s are an initiative of support agents to enterprises with the purpose of organizing joint actions for the development of groups (clusters) of enterprises. The choice of the actions is a decision of the participating enterprises and this paper aims at applying a Multi-criteria Analysis Method to analyze the criteria of entrepreneurs that are participating of a LPA. The used method is the Process of Analytical Hierarchy (PAH) and an application is presented along with questionnaires to participants of a ceramic LPA in the northeast of Brazil. The main results show that, in first place, from the implicit strategy of each enterprise there is only one objective for the LPA group and so, at the beginning, an action decided by all of them tends to favor some more than others. In second place, it was observed that there are general inconsistencies between the strategic objectives and the importance as to criteria, even though there have been cases of coherency. As the main conclusion it is pointed that the use of Methods of MCDA is useful to improve the decision making process and to bring more transparency to the logic of the found results

Fatores influenciadores da participação pública na tomada de decisão ambiental :o caso do programa de combate ao caramujo gigante (Achatina fulica) em Parnamirim/RN

The aim of this work is to investigate the factors which influence people s participation in the enviromental decision, in Parnamirim, Rio Grande do Norte, from the vision of the residents of that area, approaching the Plan of Control/Eradication of the African s Huge Snail (Achatina Fulica),with the jointly work of IBAMA and Municipal Town Hall of Parnamirim .The applied methodology consists of a research (Survey kind) including 395 interviews by people who live in that county, with minimum age of 18, within an universe of 124.690 residents. The choice of the county was due to a detection (made by IBAMA technicians and reported in a Technical Report) -which showed that the dangerous Snail is already spreading in 14 of 17 districts of the county-, as well as the support given by Parnamirim s Town Hall, with the implementation of the Plan Control/Eradication of the African s Huge Snail, widely known as Day C . The research tools used in that research consists of questionnaires with all sorts of questions. The results show us that most of the residents were feeling threatened by the presence of the animal as well as having had a little participation in the fight against the animal. It also shows us that residents believe that organizations (Town Hall, IBAMA and Local Community) involved are able to solve the problem and believe that the amounts which organization are supposed to take 89,4 %, 87,6% and 80,8%, in that order. As we check the results, we notice in 95%, the variety of threaten and frequency reunion and participation level

Avaliação da eficiência dos investimentos do programa Inova-RN em micro e pequenas empresas Uma integração da análise envoltória de dados e índice Malmquist

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Gestão ambiental e competitividade: um estudo sobre os fatores que afetam a decisão de compra de produtos orgânicos na cidade de Teresina-PI

The organic products represent one of the main trends of alimentary consumption in the new century. In Brazil, the answer is already well representative which it becomes the country, as a great consuming and exporting market of products of LVF type. The objective of this research was to investigate the factors capable to influence the food consumer in its purchase decision of organic products in the supermarkets of Teresina, capital of Piauí State. The methodology was exploratory and descriptive, using survey, with closed and opened questions in 542 interviewed. The questionnaire was based on projected scales to evaluate the factors that can influence the purchase decision of organic products, whose variable had been grouped in the following groups: behavior, knowledge, interest, competitiveness, importance, barrier and profile. The used statistical techniques were descriptive analysis and multiple regression analysis. The results demonstrate interest of the population in paying more for the organic product, due to better quality of life, however it lacks to one better spreading and greater sensitization to attract these consumers. Some recommendations and proposals are presented after the results, as suggestions for future research

Arquitetura inteligente fuzzy para monitoramento de sinais vitais de pacientes: um estudo de caso em UTI

The area of the hospital automation has been the subject a lot of research, addressing relevant issues which can be automated, such as: management and control (electronic medical records, scheduling appointments, hospitalization, among others); communication (tracking patients, staff and materials), development of medical, hospital and laboratory equipment; monitoring (patients, staff and materials); and aid to medical diagnosis (according to each speciality). This thesis presents an architecture for a patient monitoring and alert systems. This architecture is based on intelligent systems techniques and is applied in hospital automation, specifically in the Intensive Care Unit (ICU) for the patient monitoring in hospital environment. The main goal of this architecture is to transform the multiparameter monitor data into useful information, through the knowledge of specialists and normal parameters of vital signs based on fuzzy logic that allows to extract information about the clinical condition of ICU patients and give a pre-diagnosis. Finally, alerts are dispatched to medical professionals in case any abnormality is found during monitoring. After the validation of the architecture, the fuzzy logic inferences were applied to the trainning and validation of an Artificial Neural Network for classification of the cases that were validated a priori with the fuzzy system

Predição de promotores de Bacillus subtilis usando técnicas de aprendizado de máquina

One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database

Aplicação de técnicas de aprendizado de máquina no reconhecimento de classes estruturais de proteínas

Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated