Metrics to support the evaluation of association rule clustering

Many topics related to association mining have received attention in the research community, especially the ones focused on the discovery of interesting knowledge. A promising approach, related to this topic, is the application of clustering in the pre-processing step to aid the user to find the relevant associative patterns of the domain. In this paper, we propose nine metrics to support the evaluation of this kind of approach. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Some experiments were done in order to present how the metrics can be used and their usefulness. © 2013 Springer-Verlag GmbH.

Uso de equações de diferenças na obtenção de filtros para redução de ruído em sinais de voz no domínio wavelet

Pós-graduação em Engenharia Elétrica - FEIS

Teoria da ressonância adaptativa através da linguagem Java para detecção e classificação de e-mails indesejados

Pós-graduação em Engenharia Elétrica - FEIS

Simulação numérica de escoamentos hipersônicos sobre corpos rombudos pelo método de elementos finitos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Um sistema para extração automática de keyframes a partir de fluxos de vídeo direcionado à reconstrução tridimensional de cenários virtuais

Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

Previsão de séries temporais financeiras por meio de redes neurais dinâmicas e processos de transformação de dados: uma abordagem empírico-comparativa

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Sistema embarcado para monitoramento de harpia (Harpia harpyja)

Esta dissertação consiste no projeto e implementação parcial de um sistema integrado de monitoramento da ave Harpia (Harpia harpyja), espécie encontrada na Amazônia, Cerrado e Mata Atlântica. O sistema de monitoramento é estruturado em três etapas: coleta, armazenamento e transmissão de dados. A primeira etapa consiste na coleta de dados a partir de sensores, podendo detectar a presença de pássaros no ninho, também o sistema conta com o auxílio de uma câmera responsável pela captura de vídeo e áudio. A segunda etapa destina-se ao pré-processamento e armazenamento de todas as informações coletadas. A terceira etapa é responsável pela transmissão dos dados através de satélite, utilizando o Sistema Brasileiro de Coleta de Dados Ambientais (SBCDA). Além disso, foi realizado o desenvolvimento de um protótipo utilizado para o monitoramento. Técnicas de sistemas embarcados são expostas para o leitor e o processo de detecção desta espécie é avaliado.

Harvest managements and cultural practices in sugarcane

The presence of trash from the mechanical harvest of green cane on sugarcane plantations promotes changes in the agricultural management, for example, in the mechanical cultural practices of ratoon cane in-between the rows and nitrogen (N) fertilization. The goal of this study was to evaluate the performance of sugarcane in different harvest systems, associated to the mechanical cultural practices in interrows and N rates. The study was carried out on a sugarcane plantation in Sales Oliveira, São Paulo, Brazil, with the sugarcane variety SP81-3250, on soil classified as Acrudox, in a randomized block design with split-split plots and four replications. The main treatments consisted of harvest systems (harvesting green cane or burnt cane), the secondary treatment consisted of the mechanical cultural practices in the interrows and the tertiary treatments were N rates (0, 30, 60, 90, 120 and 160 kg ha-1), using ammonium nitrate (33 % N) as N source. The harvest systems did not differ in sugarcane yield (tons of cane per hectare - TCH), but in burnt cane, the pol percent and total sugar recovery (TSR) were higher. This could be explained by the higher quantity of plant impurities in the harvested raw material in the system without burning, which reduces the processing quality. Mechanical cultural practices in the interrows after harvest had no effect on cane yield and sugar quality, indicating that this operation can be omitted in areas with mechanical harvesting. The application of N fertilizer at rates of 88 and 144 kg ha-1 N, respectively, increased stalk height and TCH quadratically to the highest values for these variables. For the sugar yield per hectare (in pol %), N fertilization induced a linear increase.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

Reconhecimento de voz para aplicações em automação implementado em FPGA

In many movies of scientific fiction, machines were capable of speaking with humans. However mankind is still far away of getting those types of machines, like the famous character C3PO of Star Wars. During the last six decades the automatic speech recognition systems have been the target of many studies. Throughout these years many technics were developed to be used in applications of both software and hardware. There are many types of automatic speech recognition system, among which the one used in this work were the isolated word and independent of the speaker system, using Hidden Markov Models as the recognition system. The goals of this work is to project and synthesize the first two steps of the speech recognition system, the steps are: the speech signal acquisition and the pre-processing of the signal. Both steps were developed in a reprogrammable component named FPGA, using the VHDL hardware description language, owing to the high performance of this component and the flexibility of the language. In this work it is presented all the theory of digital signal processing, as Fast Fourier Transforms and digital filters and also all the theory of speech recognition using Hidden Markov Models and LPC processor. It is also presented all the results obtained for each one of the blocks synthesized e verified in hardware

Algorithms for automatic segmentation of bovine embryos produced

In vitro production has been employed in bovine embryos and quantification of lipids is fundamental to understand the metabolism of these embryos. This paper presents a unsupervised segmentation method for histological images of bovine embryos. In this method, the anisotropic filter was used in the differents RGB components. After pre-processing step, the thresholding technique based on maximum entropy was applied to separate lipid droplets in the histological slides in different stages: early cleavage, morula and blastocyst. In the postprocessing step, false positives are removed using the connected components technique that identify regions with excess of dye near pellucid zone. The proposed segmentation method was applied in 30 histological images of bovine embryos. Experiments were performed with the images and statistical measures of sensitivity, specificity and accuracy were calculated based on reference images (gold standard). The value of accuracy of the proposed method was 96% with standard deviation of 3%.

Segurança em redes sem fio: estudo sobre o desenvolvimento de conjuntos de dados para comparação de IDS

Pós-graduação em Engenharia Elétrica - FEIS

Estimation of croplands using indicator kriging and fuzzy classification

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Metrics for Association Rule Clustering Assessment

Issues related to association mining have received attention, especially the ones aiming to discover and facilitate the search for interesting patterns. A promising approach, in this context, is the application of clustering in the pre-processing step. In this paper, eleven metrics are proposed to provide an assessment procedure in order to support the evaluation of this kind of approach. To propose the metrics, a subjective evaluation was done. The metrics are important since they provide criteria to: (a) analyze the methodologies, (b) identify their positive and negative aspects, (c) carry out comparisons among them and, therefore, (d) help the users to select the most suitable solution for their problems. Besides, the metrics do the users think about aspects related to the problems and provide a flexible way to solve them. Some experiments were done in order to present how the metrics can be used and their usefulness.

Classification of intact açai (Euterpe oleracea Mart.) and jucara (Euterpe edulis Mart) fruits based on dry matter content by means of near infrared spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)