Apostila - “Construção de algoritmos”

Este material contém a apostila “Construção de algoritmos” da disciplina Algoritmos e programação I do curso de Sistemas de informação. O conteúdo programático a ser abordado é composto de 11 unidades, sendo: “Unidade 1: Conceitos básicos sobre algoritmos”; “Unidade 2: Conceitos básicos para o desenvolvimento de algoritmos”; “Unidade 3: Expressões algorítmicas”; “Unidade 4: Estratégia de desenvolvimento de algoritmos”; “Unidade 5: Comandos condicionais”; “Unidade 6: Comandos de repetição”; “Unidade 7: Ponteiros”; “Unidade 8: Estruturas compostas heterogêneas: registros”; “Unidade 9: Sub-rotinas”; “Unidade 10: Estruturas compostas homogêneas: arranjos”; “Unidade 11: Estruturas compostas mistas: homogêneas e heterogêneas”. O material possui figuras ilustrativas, algoritmos usados como exemplos e tabelas

Introdução à análise de algoritmos

Vídeo de introdução ao tema Análise de algoritmos. Neste vídeo são expostos os objetivos principais da análise de algoritmos, apresentando ao aluno o que é a análise de algoritmos e o que é a análise assintótica. É apresentado também o propósito da análise de algoritmos, a saber, para comparar dois ou mais algoritmos que fazem a mesma tarefa e decidir qual é o melhor. Para este tema, é apresentada a definição matemática relacionada ao assunto e também alguns exemplos visuais.

Introdução à análise de algoritmos [Audiodescrição]

Versão acessível do vídeo com audiodescrição.

Introdução a algoritmos: visão geral

A videoaula traz uma visão geral, conceitos e principais características dos algorítimos computacionais. Algoritmos correspondem a uma sequencia finita de ações que, quando executadas, levam à solução de um problema em um tempo finito. A partir de um problema, passa-se pela aplicação de uma sequência de ações e no final o problema é resolvido. Algoritmos possuem como características a execução sequencial das instruções; cada instrução é executada por completo antes de se proceder para a próxima, não sendo ambíguas e dependentes de interpretação.

Introdução à análise de algoritmos

A videoaula traz uma introdução sobre análise de algoritmos e análise assintótica. A análise de algoritmos possibilita a compreensão do comportamento do algoritmo quando há muito o que processar, e a comparação entre algoritmos diferentes que resolvem um mesmo problema. A análise é feita por causa do tempo de execução, sendo possível fazer uma análise pelo espaço requerido.

Exemplos de análise de algoritmos

A videoaula traz exemplos sobre análise de algoritmos, explanando sobre a análise de trechos com tempo constante, análise de trechos com repetições de incremento constante, e análise de trechos com multiplicação ou divisão do controle de repetição.

Medidas da complexidade da estrutura de algoritmos codificados em C

Nesta dissertação defendemos uma forma nova de medir o produto de software com base nas medidas usadas na teoria dos sistemas complexos. Consideramos o uso dessas medidas vantajoso em relação ao uso das medidas tradicionais da engenharia de software. A inovação desta dissertação sintetiza-se em considerar o produto de software como um sistema complexo, dotado de uma estrutura que comporta vários níveis e na proposta da correlação de gama longa como medida da complexidade de estrutura de programas fontes. Essa medida, invariante para a escala de cada nível da estrutura, pode ser calculada automaticamente. Na dissertação, primeiro descrevemos o processo de desenvolvimento do software e as medidas existentes para medir o referido processo e produto e introduzimos a teoria dos sistemas complexos. Concluímos que o processo tem características de sistema complexo e propomos que seja medido como tal. Seguidamente, estudamos a estrutura do produto e a dinâmica do seu. processo de desenvolvimento. Apresentamos um estudo experimental sobre algoritmos codificados em C, que usamos para validar hipóteses sobre a complexidade da estrutura do produto. Propomos a correlação de gama longa como medida da complexidade da estrutura. Estendemos essa medida a uma amostra codificada em Java. Concluímos, evidenciando as limitações e as potencialidades dessa medida e a sua aplicação em Engenharia de Software.

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

Natural infection of gastrointestinal nematodes in long-nosed armadillos Dasypus novemcinctus Linnaeus, 1758 from Pantanal wetlands, Aquidauana sub-region, Mato Grosso do Sul State, with the description of Hadrostrongylus speciosum n. gen. et n. sp (Molineidae : Anoplostrongylinae)

This study evaluated the gastrointestinal helminth fauna of long-nosed armadillos, Dasypus novemcinctus, from the Pantanal wetlands, Aquidauana sub-region, Aquidauana County, Mato Grosso do Sul State, Brazil. Thirteen species of nematodes, comprising seven genera and four families, were recovered from their gastrointestinal tracts. The following descriptors of infection were determined: prevalence, variation of intensity, average intensity and abundance. Hadrostrongylus speciosum n. gen. et n. sp. is first described here. (c) 2006 Published by Elsevier B.V.

Rede Água: instrumento de construção colaborativa e democratização do conhecimento, direcionado as cadeias produtivas da pesca e da aqüicultura Proposta de metodologia

This paper proposes a methodology for building Information Technology solutions in the form of virtual environments that allow for collaborative construction and democratization of knowledge for and about supply chains, providing tools for collaboration iteration and the social actors involved, valuing its environmental variables and assisting in its development. The scope of supply chains of aquaculture and fisheries and www.redeagua.com.br were the objects of research and prototyping of this paper. AVA Moodle was chosen to create the environment in question by their full fitness the socio-cultural characteristics of the target audience and the structure of existing digital inclusion, making necessary the development of strategies to generate interest from productive agents in their effective participation as collaborators and not just as recipients of content. The structure of this survey work will be qualitative-quantitative, using both traditional elements such as forms and interviews as sources typical of virtual environments, such as statistical reports of visitation and placement in search engines on the Internet

Algoritmos para o problema de localização de uma facilidade com distâncias limitadas e restrições de atendimento

The objective in the facility location problem with limited distances is to minimize the sum of distance functions from the facility to the customers, but with a limit on each distance, after which the corresponding function becomes constant. The problem has applications in situations where the service provided by the facility is insensitive after a given threshold distance (eg. fire station location). In this work, we propose a global optimization algorithm for the case in which there are lower and upper limits on the numbers of customers that can be served

Gestão ambiental em cadeias produtivas agroindustriais: um estudo em um aglomerado produtivo da caprinovinocultura no Estado do Rio Grande do Norte

This thesis aims to investigate the perception and behavior of goat and sheep rural producers from Central Cabugi Region of Rio Grande do Norte state, in terms of the sector competitiveness, the cooperation mechanisms, information and environmental practices integration in the supply chain, including their customers, and also among the local producers and other institutions that support this agribusiness cluster. The research problem is related to the environmental impacts from goat and sheep breeding. This problem can also be intensified by the organization of producers in a cluster. Then, it is important to examine how the environmental issues are considered by the rural producers and their perception of their suppliers, customers and the institutions that support this activity. The methodology used in this work involved literature review of the topics of supply chain management, green supply chain, clusters development and sustainable livestock. An exploratory survey research was also conducted by personal interviews using questionnaires. Three statistic techniques were used to compile the gathered data: descriptive statistics, cluster analysis, and Chi-square tests. Two clusters were found in this study, however, the entire sample believes the sector of goat and sheep breeding is a medium competitive activity. On the other hand, for the variables of the importance of environmental practices for competitiveness , perception of environmental impacts and environmental benefits from farm vegetation management , the research found 2 distinct groups of individuals when those variables were analyzed together the green supply chain management group of variables in the cluster analysis. Beyond competitiveness perception, no degree of difference was found for the use of insecticides too. The chi-square tests present that producers having at least elementary education, lands bigger 100 hectares and located in the cities of Angicos or Lajes tend to have a higher perception to supply chain management and environmental awareness issues than those with no or incomplete first-level education, producing in lands smaller than 100 hectares and located in the cities of Afonso Bezerra or Pedro Avelino. The chi-square tests also show the amount of milk produced, family s income and associational condition are not related with the variables used in the clusters composition. In this context, this work contributes to planning clusters development strategies and enhancing the production chain sustainability. This Master of Science Thesis can also help to introduce the environmental variable in the project, assessment and monitoring of development policies as well

Algoritmo Q-learning como estratégia de exploração e/ou explotação para metaheurísticas GRASP e algoritmo genético

Techniques of optimization known as metaheuristics have achieved success in the resolution of many problems classified as NP-Hard. These methods use non deterministic approaches that reach very good solutions which, however, don t guarantee the determination of the global optimum. Beyond the inherent difficulties related to the complexity that characterizes the optimization problems, the metaheuristics still face the dilemma of xploration/exploitation, which consists of choosing between a greedy search and a wider exploration of the solution space. A way to guide such algorithms during the searching of better solutions is supplying them with more knowledge of the problem through the use of a intelligent agent, able to recognize promising regions and also identify when they should diversify the direction of the search. This way, this work proposes the use of Reinforcement Learning technique - Q-learning Algorithm - as exploration/exploitation strategy for the metaheuristics GRASP (Greedy Randomized Adaptive Search Procedure) and Genetic Algorithm. The GRASP metaheuristic uses Q-learning instead of the traditional greedy-random algorithm in the construction phase. This replacement has the purpose of improving the quality of the initial solutions that are used in the local search phase of the GRASP, and also provides for the metaheuristic an adaptive memory mechanism that allows the reuse of good previous decisions and also avoids the repetition of bad decisions. In the Genetic Algorithm, the Q-learning algorithm was used to generate an initial population of high fitness, and after a determined number of generations, where the rate of diversity of the population is less than a certain limit L, it also was applied to supply one of the parents to be used in the genetic crossover operator. Another significant change in the hybrid genetic algorithm is the proposal of a mutually interactive cooperation process between the genetic operators and the Q-learning algorithm. In this interactive/cooperative process, the Q-learning algorithm receives an additional update in the matrix of Q-values based on the current best solution of the Genetic Algorithm. The computational experiments presented in this thesis compares the results obtained with the implementation of traditional versions of GRASP metaheuristic and Genetic Algorithm, with those obtained using the proposed hybrid methods. Both algorithms had been applied successfully to the symmetrical Traveling Salesman Problem, which was modeled as a Markov decision process

Análise e otimização de superfícies seletivas de Frequência utilizando redes neurais artificiais e algoritmos de otimização natural

The bidimensional periodic structures called frequency selective surfaces have been well investigated because of their filtering properties. Similar to the filters that work at the traditional radiofrequency band, such structures can behave as band-stop or pass-band filters, depending on the elements of the array (patch or aperture, respectively) and can be used for a variety of applications, such as: radomes, dichroic reflectors, waveguide filters, artificial magnetic conductors, microwave absorbers etc. To provide high-performance filtering properties at microwave bands, electromagnetic engineers have investigated various types of periodic structures: reconfigurable frequency selective screens, multilayered selective filters, as well as periodic arrays printed on anisotropic dielectric substrates and composed by fractal elements. In general, there is no closed form solution directly from a given desired frequency response to a corresponding device; thus, the analysis of its scattering characteristics requires the application of rigorous full-wave techniques. Besides that, due to the computational complexity of using a full-wave simulator to evaluate the frequency selective surface scattering variables, many electromagnetic engineers still use trial-and-error process until to achieve a given design criterion. As this procedure is very laborious and human dependent, optimization techniques are required to design practical periodic structures with desired filter specifications. Some authors have been employed neural networks and natural optimization algorithms, such as the genetic algorithms and the particle swarm optimization for the frequency selective surface design and optimization. This work has as objective the accomplishment of a rigorous study about the electromagnetic behavior of the periodic structures, enabling the design of efficient devices applied to microwave band. For this, artificial neural networks are used together with natural optimization techniques, allowing the accurate and efficient investigation of various types of frequency selective surfaces, in a simple and fast manner, becoming a powerful tool for the design and optimization of such structures