Estratégia de navegação com planejamento dinâmico e algoritmo genético aplicada a robôs móveis terrestres

This work proposes a new autonomous navigation strategy assisted by genetic algorithm with dynamic planning for terrestrial mobile robots, called DPNA-GA (Dynamic Planning Navigation Algorithm optimized with Genetic Algorithm). The strategy was applied in environments - both static and dynamic - in which the location and shape of the obstacles is not known in advance. In each shift event, a control algorithm minimizes the distance between the robot and the object and maximizes the distance from the obstacles, rescheduling the route. Using a spatial location sensor and a set of distance sensors, the proposed navigation strategy is able to dynamically plan optimal collision-free paths. Simulations performed in different environments demonstrated that the technique provides a high degree of flexibility and robustness. For this, there were applied several variations of genetic parameters such as: crossing rate, population size, among others. Finally, the simulation results successfully demonstrate the effectiveness and robustness of DPNA-GA technique, validating it for real applications in terrestrial mobile robots.

Implementação do algoritmo (RTM) para processamento sísmico em arquiteturas não convencionais

With the growth of energy consumption worldwide, conventional reservoirs, the reservoirs called "easy exploration and production" are not meeting the global energy demand. This has led many researchers to develop projects that will address these needs, companies in the oil sector has invested in techniques that helping in locating and drilling wells. One of the techniques employed in oil exploration process is the reverse time migration (RTM), in English, Reverse Time Migration, which is a method of seismic imaging that produces excellent image of the subsurface. It is algorithm based in calculation on the wave equation. RTM is considered one of the most advanced seismic imaging techniques. The economic value of the oil reserves that require RTM to be localized is very high, this means that the development of these algorithms becomes a competitive differentiator for companies seismic processing. But, it requires great computational power, that it still somehow harms its practical success. The objective of this work is to explore the implementation of this algorithm in unconventional architectures, specifically GPUs using the CUDA by making an analysis of the difficulties in developing the same, as well as the performance of the algorithm in the sequential and parallel version

Diagnóstico, estadiamento e tratamento cirúrgico do adenocarcinoma de pâncreas

O adenocarcinoma pancreático é um dos tumores sólidos de pior prognóstico, sendo o tratamento cirúrgico o único potencialmente curativo. Na grande maioria dos pacientes o tumor é diagnosticado em fase avançada, comumente na presença de doença metastática. A introdução de modernos métodos diagnósticos associados ao aperfeiçoamento dos já existentes tem gerado controvérsia quanto à melhor maneira de se estabelecer o diagnóstico e estadiamento do tumor. Da mesma forma, o papel da cirurgia na paliação e aspectos técnicos da ressecção de lesões localizadas estão longe de alcançarem consenso na prática. Método - Revisão da literatura sobre os aspectos controversos relacionados ao tema e um algoritmo para a abordagem dos pacientes com suspeita de tumor de pâncreas são apresentados. Foram utilizados os descritores: “adenocarcinoma” e “pâncreas” para pesquisa no PubMed (www.pubmed.com) e na Bireme (www.bireme.br) e a seguir selecionadas as publicações pertinentes a cada tópico escolhido com atenção especial para metanálises, estudos clínicos controlados, revisões sitemáticas e ainda publicações de grandes centros especializados em doenças pancreáticas. Conclusões - Na suspeita de adenocarcinoma de pâncreas é possível realizar estadiamento muito próximo do real sem a necessidade da exploração cirúrgica sistemática em virtude da disponibilidade na prática de exames modernos e eficientes. Isso permite que paliação menos invasiva seja praticada na maioria dos pacientes com lesões avançadas e incuráveis. Nos em que a cura é possível, a operação deve ser realizada objetivando-se, essencialmente, a remoção da lesão com margens livres e com aceitáveis índices de morbi-mortalidade

A Geração de inovação na carcinicultura do RN: Uma análise a partir da imersão social

This dissertation examines the organizational innovation as a nonlinear process, which occurs in a social and political context and, therefore, socially immersed. Examines the case of shrimp in the state of RN, starting from the following problem: although the norteriograndense shrimp occupies the largest producer of farmed shrimp from Brazil, has a series of bottlenecks concerning the generation of industry innovation, concerning the social relationships and policies between the various actors in the network, whether private or public, and its consequences in terms of opportunity and limits generated for the innovative dynamics. The objective of the research is to understand how the social embeddedness of political actors affects norteriograndense shrimp within the context of structural relations, the industry generation of innovation, throughout its technological trajectory . The approach of social embeddedness balances atomised perspectives, undersocialized and oversocialized, of economic action, considering both the human capacity to act as sources of constraint, whose mechanisms are analyzed the structural and political. In methodological terms this is a case study, analyzed from the research literature, documentary and experimental. Primary data were collected through semi-structured interviews and analyzed in depth by the technique of content analysis. Was adopted a longitudinal approach, seeking to understand the phenomenon from the perspective of the subjects, describing it in an inductive process of investigation. After characterizing the sector and defining their technological trajectory, the analysis of the results followed its four stages: (1) Introduction of Technology: 1973-1980, (2) Intensification of Research: 1981-1991, (3) Technological Adaptation, 1992 -2003, (4) Technological Crisis: 2004-2009. A cross-sectional analysis along the evolutionary trajectory revealed the character of structural changes and policies over time, and implications on the generating process of innovation. Note that, the technological limit to which the sector reached requires changes in technology standards, but is more likely that the potiguar shrimp is entering a new phase of his career in technology rather than a new technological paradigm

Estudo e implementação de algoritmos inteligentes para detecção e classificação de falhas na medição de gás natural

This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is developed to reproduce the sensor output dynamic behavior, in such a way that its output is compared to the real sensor output. A recurrent neural network is used for this purpose, because of its ability to deal with dynamic information. The real sensor output and the estimated predictor output work as the basis for the creation of possible sensor fault detection and diagnosis strategies. Two competitive neural network architectures are investigated and their capabilities are used to classify different kinds of faults. The prediction algorithm and the fault detection classification strategies, as well as the obtained results, are presented

Correlações nos dfa de diversos perfis geológicos. estudo de caso: Bacia de Campos - RJ

This work aims to study the fluctuation structure of physical properties of oil well profiles. It was used as technique the analysis of fluctuations without trend (Detrended Fluctuation Analysis - DFA). It has been made part of the study 54 oil wells in the Campo de Namorado located in the Campos Basin in Rio de Janeiro. We studied five sections, namely: sonic, density, porosity, resistivity and gamma rays. For most of the profiles , DFA analysis was available in the literature, though the sonic perfile was estimated with the aid of a standard algorithm. The comparison between the exponents of DFA of the five profiles was performed using linear correlation of variables, so we had 10 comparisons of profiles. Our null hypothesis is that the values of DFA for the various physical properties are independent. The main result indicates that no refutation of the null hypothesis. That is, the fluctuations observed by DFA in the profiles do not have a universal character, that is, in general the quantities display a floating structure of their own. From the ten correlations studied only the profiles of density and sonic one showed a significant correlation (p> 0.05). Finally these results indicate that one should use the data from DFA with caution, because, in general, based on geological analysis DFA different profiles can lead to disparate conclusions

Simulador de escoamento multifásico em poços de petróleo (SEMPP)

The multiphase flow occurrence in the oil and gas industry is common throughout fluid path, production, transportation and refining. The multiphase flow is defined as flow simultaneously composed of two or more phases with different properties and immiscible. An important computational tool for the design, planning and optimization production systems is multiphase flow simulation in pipelines and porous media, usually made by multiphase flow commercial simulators. The main purpose of the multiphase flow simulators is predicting pressure and temperature at any point at the production system. This work proposes the development of a multiphase flow simulator able to predict the dynamic pressure and temperature gradient in vertical, directional and horizontal wells. The prediction of pressure and temperature profiles was made by numerical integration using marching algorithm with empirical correlations and mechanistic model to predict pressure gradient. The development of this tool involved set of routines implemented through software programming Embarcadero C++ Builder® 2010 version, which allowed the creation of executable file compatible with Microsoft Windows® operating systems. The simulator validation was conduct by computational experiments and comparison the results with the PIPESIM®. In general, the developed simulator achieved excellent results compared with those obtained by PIPESIM and can be used as a tool to assist production systems development

Um Modelo híbrido para previsão de curvas de produção de petróleo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Controle aplicado a poços com método de elevação e bombeio centrífugo submerso

The Electrical Submersible Pumping is an artificial lift method for oil wells employed in onshore and offshore areas. The economic revenue of the petroleum production in a well depends on the oil flow and the availability of lifting equipment. The fewer the failures, the lower the revenue shortfall and costs to repair it. The frequency with which failures occur depends on the operating conditions to which the pumps are submitted. In high-productivity offshore wells monitoring is done by operators with engineering support 24h/day, which is not economically viable for the land areas. In this context, the automation of onshore wells has clear economic advantages. This work proposes a system capable of automatically control the operation of electrical submersible pumps, installed in oil wells, by an adjustment at the electric motor rotation based on signals provided by sensors installed on the surface and subsurface, keeping the pump operating within the recommended range, closest to the well s potential. Techniques are developed to estimate unmeasured variables, enabling the automation of wells that do not have all the required sensors. The automatic adjustment, according to an algorithm that runs on a programmable logic controller maintains the flow and submergence within acceptable parameters avoiding undesirable operating conditions, as the gas interference and high engine temperature, without need to resort to stopping the engine, which would reduce the its useful life. The control strategy described, based on modeling of physical phenomena and operational experience reported in literature, is materialized in terms of a fuzzy controller based on rules, and all generated information can be accompanied by a supervisory system

Modelo de gerenciamento de estoques de peças de reposição para empresas de transporte urbano de passageiros

This work searches to offer a model to improve spare parts stock management for companies of urban passenger transport by bus, with the consequent progress in their maintenance management. Also known as MRO items (Maintenance, Repair and Operations), these spare parts, according their consumption and demand features, cost, criticity to operation, lead-time, quantity of suppliers, among other parameters, shouldn´t have managed their inventory like normal production items (work in process e final products), that because their features, are managed by more predictable models based, for example, in economic order quantity. In the case specifically of companies of urban passenger transport by bus, items MRO have significant importance in their assets and a bad management of these inventories can cause serious losses to company, leading it even bankrupticy business, in more severe situations which missing spare part provokes vehicles shutdown indefinitely. Given slight attention to the issue, which translates in little literature available about it when compared to that literature about normal items stocks, and due the fact that MRO items be critical to bus urban transport of passengers companies´, it is necessary, so, deepen in this theme searching to give technical and scientific subsidies to companies that work, in many times, empirically, with these so decisive inputs to their business. As a typical portfolio problem, in which there are n items, separated into critical and noncritical, while competing for the same resource, it was developed a new algorithm to aid in a better inventory management of spare parts used only in corrective maintenance (whose failures are unpredictable and random), by analyzing the cost-benefit ratio, which compares the level of service versus cost of each item. The model was tested in a company of urban passenger transport by bus from the city of Natal, who anonymously provided their real data to application in this work

Uma abordagem híbrida para o problema de seleção de fornecedores em cadeia de suprimentos

This work presents a hybrid approach for the supplier selection problem in Supply Chain Management. We joined decision-making philosophy by researchers from business school and researchers from engineering in order to deal with the problem more extensively. We utilized traditional multicriteria decision-making methods, like AHP and TOPSIS, in order to evaluate alternatives according decision maker s preferences. The both techiniques were modeled by using definitions from the Fuzzy Sets Theory to deal with imprecise data. Additionally, we proposed a multiobjetive GRASP algorithm to perform an order allocation procedure between all pre-selected alternatives. These alternatives must to be pre-qualified on the basis of the AHP and TOPSIS methods before entering the LCR. Our allocation procedure has presented low CPU times for five pseudorandom instances, containing up to 1000 alternatives, as well as good values for all considered objectives. This way, we consider the proposed model as appropriate to solve the supplier selection problem in the SCM context. It can be used to help decision makers in reducing lead times, cost and risks in their supply chain. The proposed model can also improve firm s efficiency in relation to business strategies, according decision makers, even when a large number of alternatives must be considered, differently from classical models in purchasing literature

Desenvolvimento de um modelo computacional para a ampliação do atendimento do Programa de Acessibilidade Especial Porta a Porta - PRAE

Worldwide, the demand for transportation services for persons with disabilities, the elderly, and persons with reduced mobility have increased in recent years. The population is aging, governments need to adapt to this reality, and this fact could mean business opportunities for companies. Within this context is inserted the Programa de Acessibilidade Especial porta a porta PRAE, a door to door public transportation service from the city of Natal-RN in Brazil. The research presented in this dissertation seeks to develop a programming model which can assist the process of decision making of managers of the shuttle. To that end, it was created an algorithm based on methods of generating approximate solutions known as heuristics. The purpose of the model is to increase the number of people served by the PRAE, given the available fleet, generating optimized schedules routes. The PRAE is a problem of vehicle routing and scheduling of dial-a-ride - DARP, the most complex type among the routing problems. The validation of the method of resolution was made by comparing the results derived by the model and the currently programming method. It is expected that the model is able to increase the current capacity of the service requests of transport

Algoritmos de otimização para decisões de localização de facilidades e distribuição em sistemas multiníveis de transporte rodoviário de carga

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Estabilidade e robustez de um controlador adaptativo indireto por um modelo de referência e estrutura variável

In this thesis, it is developed the robustness and stability analysis of a variable structure model reference adaptive controller considering the presence of disturbances and unmodeled dynamics. The controller is applied to uncertain, monovariable, linear time-invariant plants with relative degree one, and its development is based on the indirect adaptive control. In the direct approach, well known in the literature, the switching laws are designed for the controller parameters. In the indirect one, they are designed for the plant parameters and, thus, the selection of the relays upper bounds becomes more intuitive, whereas they are related to physical parameters, which present uncertainties that can be known easier, such as resistances, capacitances, inertia moments and friction coefficients. Two versions for the controller algorithm with the stability analysis are presented. The global asymptotic stability with respect to a compact set is guaranteed for both cases. Simulation results under adverse operation conditions in order to verify the theoretical results and to show the performance and robustness of the proposed controller are showed. Moreover, for practical purposes, some simplifications on the original algorithm are developed

Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column