Mice and larvae tracking using a particle filter with an auto-adjustable observation model

This paper proposes a novel way to combine different observation models in a particle filter framework. This, so called, auto-adjustable observation model, enhance the particle filter accuracy when the tracked objects overlap without infringing a great runtime penalty to the whole tracking system. The approach has been tested under two important real world situations related to animal behavior: mice and larvae tracking. The proposal was compared to some state-of-art approaches and the results show, under the datasets tested, that a good trade-off between accuracy and runtime can be achieved using an auto-adjustable observation model. (C) 2009 Elsevier B.V. All rights reserved.

Unsupervised learning to cluster the disease stages in parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder (after Alzheimer's disease) and directly affects upto 5 million people worldwide. The stages (Hoehn and Yaar) of disease has been predicted by many methods which will be helpful for the doctors to give the dosage according to it. So these methods were brought up based on the data set which includes about seventy patients at nine clinics in Sweden. The purpose of the work is to analyze unsupervised technique with supervised neural network techniques in order to make sure the collected data sets are reliable to make decisions. The data which is available was preprocessed before calculating the features of it. One of the complex and efficient feature called wavelets has been calculated to present the data set to the network. The dimension of the final feature set has been reduced using principle component analysis. For unsupervised learning k-means gives the closer result around 76% while comparing with supervised techniques. Back propagation and J4 has been used as supervised model to classify the stages of Parkinson's disease where back propagation gives the variance percentage of 76-82%. The results of both these models have been analyzed. This proves that the data which are collected are reliable to predict the disease stages in Parkinson's disease.

A localização da indústria de transformação brasileira nas últimas três décadas

O propósito dessa dissertação é avaliar, numa perspectiva geográfica, os setores industriais no Brasil nas últimas três décadas. Numa primeira instância, o objetivo é verificar o nível de especialização e concentração dos estados brasileiros em termos industriais, utilizando-se os índices de Krugman e Gini, respectivamente. Com os resultados desses dois índices, os estados brasileiros são separados em quatro grupos, segundo o método de grupamento de médias K. Através de um produto interno usual entre o vetor da distribuição da produção industrial dos setores nos estados e vetores de algumas características desses setores (chamado de Viés das Características da Indústria - VCI), verifica-se em que tipos de indústrias os estados estão se especializando e/ou concentrando. Uma análise multivariada de componentes principais é feita com os VCI’s, na qual esses componentes principais são usados para verificar a similaridade dos estados. Sob outra perspectiva, busca-se investigar o nível de concentração geográfico dos setores industriais brasileiros. Para tanto, utilizaram-se o índice Gini e o índice de Venables. Nesse último, a distância entre os estados não é negligenciada para mensuração da concentração. Os setores industriais são separados em três grupos pelo método de grupamento de médias K, no qual as variáveis utilizadas são os componentes principais das características das indústrias. Utilizando outro produto interno, o Viés da Característica dos Estados (VCE), observa-se em que tipo de estados os setores industriais estão se concentrando ou não. Para visualizar como essas duas perspectivas, ou seja, como as características dos estados e das indústrias influenciam a localização dos setores industriais no território brasileiro, um modelo econométrico de dados cruzados de Midelfart-Knarvik e outros (2000) é estabelecido para o caso brasileiro. Neste modelo econométrico, é possível investigar como a interação das características das indústrias e dos estados podem determinar onde a indústria se localiza. Os principais resultados mostram que os fortes investimentos em infraestrutura na década de 70 e a abertura comercial na década de 90 foram marcantes para localização da indústria brasileira.

Análise de agrupamentos dos dados de DFA oriundos de perfis elétricos de indução de poços de petróleo

The main objective of this study is to apply recently developed methods of physical-statistic to time series analysis, particularly in electrical induction s profiles of oil wells data, to study the petrophysical similarity of those wells in a spatial distribution. For this, we used the DFA method in order to know if we can or not use this technique to characterize spatially the fields. After obtain the DFA values for all wells, we applied clustering analysis. To do these tests we used the non-hierarchical method called K-means. Usually based on the Euclidean distance, the K-means consists in dividing the elements of a data matrix N in k groups, so that the similarities among elements belonging to different groups are the smallest possible. In order to test if a dataset generated by the K-means method or randomly generated datasets form spatial patterns, we created the parameter Ω (index of neighborhood). High values of Ω reveals more aggregated data and low values of Ω show scattered data or data without spatial correlation. Thus we concluded that data from the DFA of 54 wells are grouped and can be used to characterize spatial fields. Applying contour level technique we confirm the results obtained by the K-means, confirming that DFA is effective to perform spatial analysis

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

Dinâmica espaço-temporal em uma guilda de borboletas frugívoras no limite norte da floresta atlântica nordestina

The extent of the Brazilian Atlantic rainforest, a global biodiversity hotspot, has been reduced to less than 7% of its original range. Yet, it contains one of the richest butterfly fauna in the world. Butterflies are commonly used as environmental indicators, mostly because of their strict association with host plants, microclimate and resource availability. This research describes diversity, composition and species richness of frugivorous butterflies in a forest fragment in the Brazilian Northeast. It compares communities in different physiognomies and seasons. The climate in the study area is classified as tropical rainy, with two well defined seasons. Butterfly captures were made with 60 Van Someren-Rydon traps, randomly located within six different habitat units (10 traps per unit) that varied from very open (e.g. coconut plantation) to forest interior. Sampling was made between January and December 2008, for five days each month. I captured 12090 individuals from 32 species. The most abundant species were Taygetis laches, Opsiphanes invirae and Hamadryas februa, which accounted for 70% of all captures. Similarity analysis identified two main groups, one of species associated with open or disturbed areas and a second by species associated with shaded areas. There was a strong seasonal component in species composition, with less species and lower abundance in the dry season and more species and higher abundance in the rainy season. K-means analysis indicates that choice of habitat units overestimated faunal perceptions, suggesting less distinct units. The species Taygetis virgilia, Hamadryas chloe, Callicore pygas e Morpho achilles were associated with less disturbed habitats, while Yphthimoides sp, Historis odius, H. acheronta, Hamadryas feronia e Siderone marthesia likey indicate open or disturbed habitats. This research brings important information for conservation of frugivorous butterflies, and will serve as baseline for future projects in environmental monitoring

Causas de variação nos preços de bovinos nelore elite no Brasil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise multivariada na compactação de um latossolo vermelho cultivado com milho

Os solos submetidos aos sistemas de produção sem preparo estão sujeitos à compactação, provocada pelo tráfego de máquinas, tornando necessário o acompanhamento das alterações do ambiente físico, que, quando desfavorável, restringe o crescimento radicular, podendo reduzir a produtividade das culturas. O objetivo do trabalho foi avaliar o efeito de diferentes intensidades de compactação na qualidade física de um Latossolo Vermelho textura média, localizado em Jaboticabal (SP), sob cultivo de milho, usando métodos de estatística multivariada. O delineamento experimental foi inteiramente casualizado, com seis intensidades de compactação e quatro repetições. Foram coletadas amostras indeformadas do solo nas camadas de 0,02-0,05, 0,08-0,11 e 0,15-0,18 m para determinação da densidade do solo (Ds), na camada de 0-0,20 m. As características da cultura avaliadas foram: densidade radicular, diâmetro radicular, matéria seca das raízes, altura das plantas, altura de inserção da primeira espiga, diâmetro do colmo e matéria seca das plantas. As análises de agrupamentos e componentes principais permitiram identificar três grupos de alta, média e baixa produtividade de plantas de milho, segundo variáveis do solo, do sistema radicular e da parte aérea das plantas. A classificação dos acessos em grupos foi feita por três métodos: método de agrupamentos hierárquico, método não-hierárquico k-means e análise de componentes principais. Os componentes principais evidenciaram que elevadas produtividades de milho estão correlacionadas com o bom crescimento da parte aérea das plantas, em condições de menor densidade do solo, proporcionando elevada produção de matéria seca das raízes, contudo, de pequeno diâmetro. A qualidade física do Latossolo Vermelho para o cultivo do milho foi assegurada até à densidade do solo de 1,38 Mg m-3.

Análise multivariada e variabilidade espacial na estimativa da erodibilidade de um argissolo vermelho-amarelo

A erodibilidade é um fator de extrema importância na caracterização da perda de solo, representando os processos que regulam a infiltração de água e sua resistência à desagregação e o transporte de partículas. Assim, por meio da análise de dependência espacial dos componentes principais da erodibilidade (fator K), objetivou-se estimar a erodibilidade do solo em uma área de nascentes da microbacia do Córrego do Tijuco, Monte Alto-SP, e analisar a variabilidade espacial das variáveis granulométricas do solo ao longo do relevo. A erodibilidade média da área foi considerada alta, e a análise de agrupamento k-means apontou para uma formação de cinco grupos: no primeiro, os altos teores de areia grossa (AG) e média (AM) condicionaram sua distribuição nas áreas planas; o segundo, caracterizado pelo alto teor de areia fina (AF), distribui-se nos declives mais convexos; o terceiro, com altos teores de silte e areia muito fina (AMF), concentrou-se nos maiores declives e concavidades; o quarto, com maior teor de argila, seguiu as zonas de escoamento de água; e o quinto, com alto teor de matéria orgânica (MO) e areia grossa (AG), distribui-se nas proximidades da zona urbana. A análise de componentes principais (ACP) mostrou quatro componentes com 87,4 % das informações, sendo o primeiro componente principal (CP1) discriminado pelo transporte seletivo de partículas principalmente em zonas pontuais de maior declividade e acúmulo de sedimentos; o segundo (CP2), discriminado pela baixa coesão entre as partículas, mostra acúmulo da areia fina nas áreas de menor cota em toda a área de concentração de água; o terceiro (CP3), discriminado pela maior agregação do solo, concentra-se principalmente nas bases de grandes declives; e o quarto (CP4), discriminado pela areia muito fina, distribui-se ao longo das declividades nas maiores altitudes. Os resultados sugerem o comportamento granulométrico do solo, que se mostra suscetível ao processo erosivo devido às condições texturais superficiais e à movimentação do relevo.

Estudo Comparativo de Métricas de Pontuação para Aprendizagem Estrutural de Redes Bayesianas

Bayesian networks are powerful tools as they represent probability distributions as graphs. They work with uncertainties of real systems. Since last decade there is a special interest in learning network structures from data. However learning the best network structure is a NP-Hard problem, so many heuristics algorithms to generate network structures from data were created. Many of these algorithms use score metrics to generate the network model. This thesis compare three of most used score metrics. The K-2 algorithm and two pattern benchmarks, ASIA and ALARM, were used to carry out the comparison. Results show that score metrics with hyperparameters that strength the tendency to select simpler network structures are better than score metrics with weaker tendency to select simpler network structures for both metrics (Heckerman-Geiger and modified MDL). Heckerman-Geiger Bayesian score metric works better than MDL with large datasets and MDL works better than Heckerman-Geiger with small datasets. The modified MDL gives similar results to Heckerman-Geiger for large datasets and close results to MDL for small datasets with stronger tendency to select simpler network structures

Estudo comportamental, hormonal e histopatológico de animais com perda de peso progressina (SEP) e da variável peso associada a uma nova classificação ontogenética em Callithrix jacchus

The use of non-human primates in scientific research has contributed significantly to the biomedical area and, in the case of Callithrix jacchus, has provided important evidence on physiological mechanisms that help explain its biology, making the species a valuable experimental model in different pathologies. However, raising non-human primates in captivity for long periods of time is accompanied by behavioral disorders and chronic diseases, as well as progressive weight loss in most of the animals. The Primatology Center of the Universidade Federal do Rio Grande do Norte (UFRN) has housed a colony of C. jacchus for nearly 30 years and during this period these animals have been weighed systematically to detect possible alterations in their clinical conditions. This procedure has generated a volume of data on the weight of animals at different age ranges. These data are of great importance in the study of this variable from different perspectives. Accordingly, this paper presents three studies using weight data collected over 15 years (1985-2000) as a way of verifying the health status and development of the animals. The first study produced the first article, which describes the histopathological findings of animals with probable diagnosis of permanent wasting marmoset syndrome (WMS). All the animals were carriers of trematode parasites (Platynosomum spp) and had obstruction in the hepatobiliary system; it is suggested that this agent is one of the etiological factors of the syndrome. In the second article, the analysis focused on comparing environmental profile and cortisol levels between the animals with normal weight curve evolution and those with WMS. We observed a marked decrease in locomotion, increased use of lower cage extracts and hypocortisolemia. The latter is likely associated to an adaptation of the mechanisms that make up the hypothalamus-hypophysis-adrenal axis, as observed in other mammals under conditions of chronic malnutrition. Finally, in the third study, the animals with weight alterations were excluded from the sample and, using computational tools (K-means and SOM) in a non-supervised way, we suggest found new ontogenetic development classes for C. jacchus. These were redimensioned from five to eight classes: infant I, infant II, infant III, juvenile I, juvenile II, sub-adult, young adult and elderly adult, in order to provide a more suitable classification for more detailed studies that require better control over the animal development

Perfil de mortalidade de idosos no Rio Grande do Norte: estudo comparativo entre duas faixas etárias e fatores relacionados

Measures of mortality represent one of the most important indicators of health conditions. For comprising the larger rate of deaths, the study of mortality in the elderly population is regarded as essential to understand the health situation. In this sense, the present study aims to analyze the mortality profile of the population from 60 to 69 (young elders) and older than 80 years old (oldest old) in the Rio Grande do Norte state (Brazil) in the period 2001 to 2011, and to identify the association with contextual factors and variables about the quality of the Mortality Information System (SIM). For this purpose, Mortality Proportional (MP) was calculated for the state and Specific Mortality Rate by Age (CMId) , according to chapters of ICD- 10, to the municipalities of Rio Grande do Norte , through data from the Mortality Information System (SIM) and the Brazilian Institute of Geography and Statistics (IGBE). In order to identify groups of municipalities with similar mortality profiles, Nonhierarchical Clustering K-means method was applied and the Factor Analysis by the Principal Components Analysis was resort to reduce contextual variables. The spatial distribution of these groups and the factors were visualized using the Spatial Analysis Areas technique. During the period investigated, 21,813 younger elders deaths were recorded , with a predominance of deaths from circulatory diseases (32.75%) and neoplasms (22.9 %) . Among the oldest old, 50,637 deaths were observed, which 35.26% occurred because of cardiovascular diseases and 17.27% of ill-defined causes. Clustering Analysis produced three clusters to the two age groups and Factor Analysis reduced the contextual variables into three factors, also the sum of the factor scores was considered. Among the younger elders, the groups are called misinformation profile, development profile and development paradox, which showed a statistically significant association with education and poverty and extreme poverty factors, factorial sum and the variable related to underreporting of deaths. Misinformation profile remained in the oldest old group, accompanied by the epidemiological transition profile and the epidemiological paradox, that were statistically associated with the development and health factor, as well as with the variables that indicate the SIM quality: proportion of blank fields about the schooling and underreporting. It proposed that the mortality profiles of the younger elders and oldest old differ on the importance of the basic causes and that are influenced by different contextual aspects , observing that 60 to 69 years group is more affected by such aspects. Health inequalities can be reduced by measures aimed to improve levels of education and poverty, especially in younger elders, and by optimizing the use of health services, which is more associated to the oldest old health situation. Furthermore, it is important to improve the quality of information for the two age groups

Algoritmos de agrupamento aplicados a dados de expressão gênica de câncer: um estudo comparativo

The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using classic clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context. This work presents the first large-scale analysis of seven different clustering methods and four proximity measures for the analysis of 35 cancer gene expression data sets. Results reveal that the finite mixture of Gaussians, followed closely by k-means, exhibited the best performance in terms of recovering the true structure of the data sets. These methods also exhibited, on average, the smallest difference between the actual number of classes in the data sets and the best number of clusters as indicated by our validation criteria. Furthermore, hierarchical methods, which have been widely used by the medical community, exhibited a poorer recovery performance than that of the other methods evaluated. Moreover, as a stable basis for the assessment and comparison of different clustering methods for cancer gene expression data, this study provides a common group of data sets (benchmark data sets) to be shared among researchers and used for comparisons with new methods

Aplicação do Sensoriamento Remoto e do Sistema de Informações Geográficas na Detecção de Manchas de Óleo na Região do Pólo de Exploração de Guamaré, R.N.

Objective to establish a methodology for the oil spill monitoring on the sea surface, located at the Submerged Exploration Area of the Polo Region of Guamaré, in the State of Rio Grande do Norte, using orbital images of Synthetic Aperture Radar (SAR integrated with meteoceanographycs products. This methodology was applied in the following stages: (1) the creation of a base map of the Exploration Area; (2) the processing of NOAA/AVHRR and ERS-2 images for generation of meteoceanographycs products; (3) the processing of RADARSAT-1 images for monitoring of oil spills; (4) the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products; and (5) the structuring of a data base. The Integration of RADARSAT-1 image of the Potiguar Basin of day 21.05.99 with the base map of the Exploration Area of the Polo Region of Guamaré for the identification of the probable sources of the oil spots, was used successfully in the detention of the probable spot of oil detected next to the exit to the submarine emissary in the Exploration Area of the Polo Region of Guamaré. To support the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products, a methodology was developed for the classification of oil spills identified by RADARSAT-1 images. For this, the following algorithms of classification not supervised were tested: K-means, Fuzzy k-means and Isodata. These algorithms are part of the PCI Geomatics software, which was used for the filtering of RADARSAT-1 images. For validation of the results, the oil spills submitted to the unsupervised classification were compared to the results of the Semivariogram Textural Classifier (STC). The mentioned classifier was developed especially for oil spill classification purposes and requires PCI software for the whole processing of RADARSAT-1 images. After all, the results of the classifications were analyzed through Visual Analysis; Calculation of Proportionality of Largeness and Analysis Statistics. Amongst the three algorithms of classifications tested, it was noted that there were no significant alterations in relation to the spills classified with the STC, in all of the analyses taken into consideration. Therefore, considering all the procedures, it has been shown that the described methodology can be successfully applied using the unsupervised classifiers tested, resulting in a decrease of time in the identification and classification processing of oil spills, if compared with the utilization of the STC classifier

Qualidade de vida na terceira idade: um conceito subjetivo

Tendo-se em conta a expectativa de vida cada vez mais alta, vários estudos têm sido desenvolvidos de modo a contribuir para a melhoria da qualidade de vida na terceira idade. Objetivou-se conhecer a opinião dos idosos de um município de porte médio do interior paulista sobre o que é qualidade de vida, através de uma pergunta aberta que foi incluída como parte de um inquérito populacional sobre estilo e qualidade de vida. A análise da referida questão foi realizada através do método de Análise de Conteúdo. Posteriormente calcularam-se as freqüências das categorias obtidas, agrupadas segundo o método de Ward, e em seguida os idosos foram agrupados segundo o método de k-médias. Os resultados indicaram a existência de três grupos de idosos segundo sua definição de qualidade de vida: o primeiro valorizou a questão afetiva e a família; o segundo priorizou a obtenção do prazer e conforto; o terceiro poderia ser sintetizado como o idoso que identifica a qualidade de vida colocando em prática o seu ideário de vida. Sugere-se que, na implementação de ações, se objetive melhorar a qualidade de vida do idoso, levando-se em conta as magnitudes e as diferenças de cada grupo.