Efeito do ethephon sobre a brotação e vigor dos ramos da videira 'Niagara Rosada' (Vitis labrusca L.)

A produção da videira 'Niagara Rosada' em regiões tropicais e subtropicais do Brasil tem sido freqüentemente prejudicada, principalmente devido à dificuldade de emissão e desenvolvimento das brotações após a poda de produção, realizada nos meses de ocorrência de temperaturas mais baixas, o que tem causado redução nas produções e desestímulo aos viticultores. Para solucionar esse problema, foram conduzidos três experimentos, em pomares comerciais localizados na região Noroeste do Estado de São Paulo, com o objetivo de estudar o efeito do Ethephon, aplicado antes da poda de produção, na emissão e desenvolvimento das novas brotações e na duração do período da poda até a floração. Foram testadas quatro doses de ethephon (0 mg.L-1; 720 mg.L-1; 1.440 mg.L-1; 2.160 mg.L-1) aplicadas via foliar antes da poda de produção, nos meses de junho e julho de 2002. Observou-se que a aplicação de Ethephon proporcionou maior número de gemas brotadas, maior comprimento e diâmetro do ramo e não alterou o período da poda à floração. Especialmente quando da ocorrência de condições climáticas desfavoráveis e quando as plantas apresentaram satisfatório grau de enfolhamento, a aplicação de ethephon, na dose de 2.160 mg.L-1, foi a mais efetiva.

Análise de Agrupamentos Com Base na Teoria da Informação: Uma Abordagem Representativa

Currently, one of the biggest challenges for the field of data mining is to perform cluster analysis on complex data. Several techniques have been proposed but, in general, they can only achieve good results within specific areas providing no consensus of what would be the best way to group this kind of data. In general, these techniques fail due to non-realistic assumptions about the true probability distribution of the data. Based on this, this thesis proposes a new measure based on Cross Information Potential that uses representative points of the dataset and statistics extracted directly from data to measure the interaction between groups. The proposed approach allows us to use all advantages of this information-theoretic descriptor and solves the limitations imposed on it by its own nature. From this, two cost functions and three algorithms have been proposed to perform cluster analysis. As the use of Information Theory captures the relationship between different patterns, regardless of assumptions about the nature of this relationship, the proposed approach was able to achieve a better performance than the main algorithms in literature. These results apply to the context of synthetic data designed to test the algorithms in specific situations and to real data extracted from problems of different fields

Antenas de microfita com patch quase-fractal para aplicações em Redes WPAN/WLAN

The microstrip antennas are in constant evidence in current researches due to several advantages that it presents. Fractal geometry coupled with good performance and convenience of the planar structures are an excellent combination for design and analysis of structures with ever smaller features and multi-resonant and broadband. This geometry has been applied in such patch microstrip antennas to reduce its size and highlight its multi-band behavior. Compared with the conventional microstrip antennas, the quasifractal patch antennas have lower frequencies of resonance, enabling the manufacture of more compact antennas. The aim of this work is the design of quasi-fractal patch antennas through the use of Koch and Minkowski fractal curves applied to radiating and nonradiating antenna s edges of conventional rectangular patch fed by microstrip inset-fed line, initially designed for the frequency of 2.45 GHz. The inset-fed technique is investigated for the impedance matching of fractal antennas, which are fed through lines of microstrip. The efficiency of this technique is investigated experimentally and compared with simulations carried out by commercial software Ansoft Designer used for precise analysis of the electromagnetic behavior of antennas by the method of moments and the neural model proposed. In this dissertation a study of literature on theory of microstrip antennas is done, the same study is performed on the fractal geometry, giving more emphasis to its various forms, techniques for generation of fractals and its applicability. This work also presents a study on artificial neural networks, showing the types/architecture of networks used and their characteristics as well as the training algorithms that were used for their implementation. The equations of settings of the parameters for networks used in this study were derived from the gradient method. It will also be carried out research with emphasis on miniaturization of the proposed new structures, showing how an antenna designed with contours fractals is capable of a miniaturized antenna conventional rectangular patch. The study also consists of a modeling through artificial neural networks of the various parameters of the electromagnetic near-fractal antennas. The presented results demonstrate the excellent capacity of modeling techniques for neural microstrip antennas and all algorithms used in this work in achieving the proposed models were implemented in commercial software simulation of Matlab 7. In order to validate the results, several prototypes of antennas were built, measured on a vector network analyzer and simulated in software for comparison

Uma implementação paralela híbrida para o problema do caixeiro viajante usando algoritmos genéticos, GRASP e aprendizagem por reforço

The metaheuristics techiniques are known to solve optimization problems classified as NP-complete and are successful in obtaining good quality solutions. They use non-deterministic approaches to generate solutions that are close to the optimal, without the guarantee of finding the global optimum. Motivated by the difficulties in the resolution of these problems, this work proposes the development of parallel hybrid methods using the reinforcement learning, the metaheuristics GRASP and Genetic Algorithms. With the use of these techniques, we aim to contribute to improved efficiency in obtaining efficient solutions. In this case, instead of using the Q-learning algorithm by reinforcement learning, just as a technique for generating the initial solutions of metaheuristics, we use it in a cooperative and competitive approach with the Genetic Algorithm and GRASP, in an parallel implementation. In this context, was possible to verify that the implementations in this study showed satisfactory results, in both strategies, that is, in cooperation and competition between them and the cooperation and competition between groups. In some instances were found the global optimum, in others theses implementations reach close to it. In this sense was an analyze of the performance for this proposed approach was done and it shows a good performance on the requeriments that prove the efficiency and speedup (gain in speed with the parallel processing) of the implementations performed

Técnicas inteligentes hídridas para o controle de sistemas não lineares

A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristics

Interferência de plantas daninhas no cultivo da melancia

A cultura da melancia é uma atividade explorada regionalmente, sendo uma das mais importantes fontes de renda familiar de pequenos municípios do médio Paranapanema, onde mudanças significativas no processo produtivo são atualmente constatadas, passando de mão-de-obra intensiva para uso de tecnologias promissoras, como é o caso do manejo de plantas daninhas. Um experimento foi conduzido no município de Oscar Bressani (SP), em área de produção comercial, com objetivo de estudar a interferência de plantas daninhas, no cultivo da melancia, na safra 2002/2003. O delineamento experimental utilizado foi de blocos ao acaso com dez tratamentos e quatro repetições, representadas por parcelas com área útil de 18 m², contendo quatro plantas de melancia e infestação prevalecente das espécies Sidaspp, Brachiaria humidicola, Commelina benghalensise Portulaca oleracea. A infestação das plantas daninhas foi estimada através de amostragens aleatórias das parcelas utilizando-se quadro vazado de ferro com 0,5 m de lado. Os tratamentos constaram de testemunhas capinadas e sem capina e diferentes épocas de controle da infestação, de forma que a cultura foi mantida na presença ou ausência das plantas daninhas até 7; 14; 28; 56 e 63 dias após a sua emergência (DAE). A ocorrência do período inicial de convivência possível maior que o período final estabeleceu o Período Crítico de Prevenção da Interferência do 9º ao 13º dias (PCPI= 9-13 DAE). A redução média da produtividade em função da interferência das plantas daninhas durante todo o ciclo da melancia foi de 41,4%. As características diâmetro e espessura da casca dos frutos também foram influenciadas pela convivência com a infestação durante todo o ciclo com decréscimos, de 7,9% e 23,3%, respectivamente, em média, ao contrário do comprimento e diâmetro de ramas e do ºBrix da polpa dos frutos, onde não foram constatadas diferenças significativas.

Características da pulverização em citros em função do volume de calda aplicado com turbopulverizador

Este trabalho teve como objetivo avaliar o efeito do volume de calda aplicado por um turbopulverizador sobre a deposição e a cobertura em folhas, ramos e frutos de citros. A pulverização foi realizada com um pulverizador tratorizado Arbus 2000/Valência em pomar de laranja 'Natal', com porte médio de 4,0 m, sendo avaliados seis volumes de calda (50; 70; 85; 100; 150 e 200% do volume-padrão utilizado pelo produtor, de 28 L planta-1). Após a pulverização de plantas uniformes com calda contendo cobre e o traçador fluorescente Poliglow 830 YLSS, amostras foram coletadas em nove setores da planta, sendo a avaliação da deposição feita usando-se análise do íon cobre por espectrofotômetro de absorção atômica, e a da cobertura, por meio de imagens digitalizadas analisadas pelo programa para computador IDRISI. A análise estatística mostrou que, na avaliação da cobertura e deposição em citros, a utilização de frutos como estrutura de amostragem tendeu a evidenciar melhor o efeito dos tratamentos. Tanto a deposição quanto a cobertura tenderam a ser maiores nos setores frontal e saia da planta. Tanto a deposição quanto a cobertura não foram prejudicadas pela utilização do volume de 70% (19,6 L planta-1), indicando que tal volume pode substituir o volume de 100% (28 L planta-1) sem prejuízos ao controle de pragas.

A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest

Nowadays, fraud detection is important to avoid nontechnical energy losses. Various electric companies around the world have been faced with such losses, mainly from industrial and commercial consumers. This problem has traditionally been dealt with using artificial intelligence techniques, although their use can result in difficulties such as a high computational burden in the training phase and problems with parameter optimization. A recently-developed pattern recognition technique called optimum-path forest (OPF), however, has been shown to be superior to state-of-the-art artificial intelligence techniques. In this paper, we proposed to use OPF for nontechnical losses detection, as well as to apply its learning and pruning algorithms to this purpose. Comparisons against neural networks and other techniques demonstrated the robustness of the OPF with respect to commercial losses automatic identification.

A fuzzy logic system applied in lightning models

This paper describes a novel approach for mapping lightning processes using fuzzy logic. The estimation process is carried out using a fuzzy system based on Sugeno's architecture. Simulation results confirm that proposed approach can be efficiently used in these types of problem.

A Bilevel Approach to Transmission Expansion Planning Within a Market Environment

We present a bilevel model for transmission expansion planning within a market environment, where producers and consumers trade freely electric energy through a pool. The target of the transmission planner, modeled through the upper-level problem, is to minimize network investment cost while facilitating energy trading. This upper-level problem is constrained by a collection of lower-level market clearing problems representing pool trading, and whose individual objective functions correspond to social welfare. Using the duality theory the proposed bilevel model is recast as a mixed-integer linear programming problem, which is solvable using branch-and-cut solvers. Detailed results from an illustrative example and a case study are presented and discussed. Finally, some relevant conclusions are drawn.

Uma nova forma de calcular os centros dos Clusters em algoritmos de agrupamento tipo fuzzy c-means

Clustering data is a very important task in data mining, image processing and pattern recognition problems. One of the most popular clustering algorithms is the Fuzzy C-Means (FCM). This thesis proposes to implement a new way of calculating the cluster centers in the procedure of FCM algorithm which are called ckMeans, and in some variants of FCM, in particular, here we apply it for those variants that use other distances. The goal of this change is to reduce the number of iterations and processing time of these algorithms without affecting the quality of the partition, or even to improve the number of correct classifications in some cases. Also, we developed an algorithm based on ckMeans to manipulate interval data considering interval membership degrees. This algorithm allows the representation of data without converting interval data into punctual ones, as it happens to other extensions of FCM that deal with interval data. In order to validate the proposed methodologies it was made a comparison between a clustering for ckMeans, K-Means and FCM algorithms (since the algorithm proposed in this paper to calculate the centers is similar to the K-Means) considering three different distances. We used several known databases. In this case, the results of Interval ckMeans were compared with the results of other clustering algorithms when applied to an interval database with minimum and maximum temperature of the month for a given year, referring to 37 cities distributed across continents

Utilizando mapas de conectividade fuzzy no desenvolvimento de algoritmos reparadores de imagens binárias 3D

A 3D binary image is considered well-composed if, and only if, the union of the faces shared by the foreground and background voxels of the image is a surface in R3. Wellcomposed images have some desirable topological properties, which allow us to simplify and optimize algorithms that are widely used in computer graphics, computer vision and image processing. These advantages have fostered the development of algorithms to repair bi-dimensional (2D) and three-dimensional (3D) images that are not well-composed. These algorithms are known as repairing algorithms. In this dissertation, we propose two repairing algorithms, one randomized and one deterministic. Both algorithms are capable of making topological repairs in 3D binary images, producing well-composed images similar to the original images. The key idea behind both algorithms is to iteratively change the assigned color of some points in the input image from 0 (background)to 1 (foreground) until the image becomes well-composed. The points whose colors are changed by the algorithms are chosen according to their values in the fuzzy connectivity map resulting from the image segmentation process. The use of the fuzzy connectivity map ensures that a subset of points chosen by the algorithm at any given iteration is the one with the least affinity with the background among all possible choices

Uma investigação de algoritmos exatos e metaheurísticos aplicados ao nonograma

Nonogram is a logical puzzle whose associated decision problem is NP-complete. It has applications in pattern recognition problems and data compression, among others. The puzzle consists in determining an assignment of colors to pixels distributed in a N  M matrix that satisfies line and column constraints. A Nonogram is encoded by a vector whose elements specify the number of pixels in each row and column of a figure without specifying their coordinates. This work presents exact and heuristic approaches to solve Nonograms. The depth first search was one of the chosen exact approaches because it is a typical example of brute search algorithm that is easy to implement. Another implemented exact approach was based on the Las Vegas algorithm, so that we intend to investigate whether the randomness introduce by the Las Vegas-based algorithm would be an advantage over the depth first search. The Nonogram is also transformed into a Constraint Satisfaction Problem. Three heuristics approaches are proposed: a Tabu Search and two memetic algorithms. A new function to calculate the objective function is proposed. The approaches are applied on 234 instances, the size of the instances ranging from 5 x 5 to 100 x 100 size, and including logical and random Nonograms

Novos métodos determinísticos para gerar centros iniciais dos grupos no algoritmo fuzzy C-Means e variantes

Data clustering is applied to various fields such as data mining, image processing and pattern recognition technique. Clustering algorithms splits a data set into clusters such that elements within the same cluster have a high degree of similarity, while elements belonging to different clusters have a high degree of dissimilarity. The Fuzzy C-Means Algorithm (FCM) is a fuzzy clustering algorithm most used and discussed in the literature. The performance of the FCM is strongly affected by the selection of the initial centers of the clusters. Therefore, the choice of a good set of initial cluster centers is very important for the performance of the algorithm. However, in FCM, the choice of initial centers is made randomly, making it difficult to find a good set. This paper proposes three new methods to obtain initial cluster centers, deterministically, the FCM algorithm, and can also be used in variants of the FCM. In this work these initialization methods were applied in variant ckMeans.With the proposed methods, we intend to obtain a set of initial centers which are close to the real cluster centers. With these new approaches startup if you want to reduce the number of iterations to converge these algorithms and processing time without affecting the quality of the cluster or even improve the quality in some cases. Accordingly, cluster validation indices were used to measure the quality of the clusters obtained by the modified FCM and ckMeans algorithms with the proposed initialization methods when applied to various data sets

A mineração artesanal e de pequena escala em pegmatitos e cerâmica no município de Parelhas, região do Seridó/Rio Grande do Norte

The working conditions, occupational health, occupational illness and workers quality of life, usually referring to the artisanal activities and the workers with a poor professional support. Because this reality is still present in locals without good infrastructure of social and economic attention, there is a need for a broad knowledge of problems related to the productive processes that include features of unsanitary and unhealthy. Despite the intense process of industrialization promoted by globalization and the growth of developing nations like Brazil, the activities of artisanal and small-scale mining are still suffering from the marginalization of their production processes and their workers. This dissertation deals with the description of mineral-based activities (MBA), especially the activities related to production processes of extraction and processing of red pottery and minerals in pegmatites in Parelhas city, Seridó, Rio Grande do Norte, which are conducted by small mining companies or artisanal miners. The study of the work process was based on direct observation, photographic documentation, ergonomics, health and occupational safety analysis, interviews and structured questionnaire with workers of the two activities. The results indicate the need for improvement in both workplaces (red pottery and pegmatites), adaptation of workers to safety standards specific to the workplace, more attention and care related to ergonomics and occupational safety, greater importance to economic and social relations among performed activities, workers and firms of mineral branch and better and greater integration of social policies, supported by different sectors of society with the intention of transforming the current social, cultural, labor and education situation