Identification of cause of impairment in spiral drawings, using non-stationary feature extraction approach

Parkinson’s disease is a clinical syndrome manifesting with slowness and instability. As it is a progressive disease with varying symptoms, repeated assessments are necessary to determine the outcome of treatment changes in the patient. In the recent past, a computer-based method was developed to rate impairment in spiral drawings. The downside of this method is that it cannot separate the bradykinetic and dyskinetic spiral drawings. This work intends to construct the computer method which can overcome this weakness by using the Hilbert-Huang Transform (HHT) of tangential velocity. The work is done under supervised learning, so a target class is used which is acquired from a neurologist using a web interface. After reducing the dimension of HHT features by using PCA, classification is performed. C4.5 classifier is used to perform the classification. Results of the classification are close to random guessing which shows that the computer method is unsuccessful in assessing the cause of drawing impairment in spirals when evaluated against human ratings. One promising reason is that there is no difference between the two classes of spiral drawings. Displaying patients self ratings along with the spirals in the web application is another possible reason for this, as the neurologist may have relied too much on this in his own ratings.

Influence of surface texture on the galling characteristics of lean duplex and austenitic stainless steels

Two simulative test methods were used to study galling in sheet forming of two types of stainlesssteel sheet: austenitic (EN 1.4301) and lean duplex LDX 2101 (EN 1.4162) in different surface conditions. Thepin-on-disc test was used to analyse the galling resistance of different combinations of sheet materials and lubricants. The strip reduction test, a severe sheet forming tribology test was used to simulate the conditionsduring ironing. This investigation shows that the risk of galling is highly dependent on the surface texture of theduplex steel. Trials were also performed in an industrial tool used for high volume production of pumpcomponents, to compare forming of LDX 2101 and austenitic stainless steel with equal thickness. The forming forces, the geometry and the strains in the sheet material were compared for the same component.It was found that LDX steels can be formed to high strain levels in tools normally applied for forming ofaustenitic steels, but tool adaptations are needed to comply with the higher strength and springback of thematerial.

Caracterização de núcleos celulares no adenocarcinoma primário de reto por análise de imagem digital

O câncer colorretal é um tumor maligno freqüente no mundo ocidental. É o terceiro em freqüência e o segundo em mortalidade nos países desenvolvidos. No Brasil está entre as seis neoplasias malignas mais encontradas e a quinta em mortalidade. Dos tumores colorretais, aproximadamente 40% estão localizados no reto. A sobrevida, em cinco anos, dos pacientes operados por câncer do reto varia entre 40% e 50%, estando os principais fatores prognósticos, utilizados na prática clínica corrente, baseados em critérios de avaliação clínico-patológicos. A avaliação das alterações morfométricas e densimétricas nas neoplasias malignas tem, recentemente, sido estudadas e avaliadas através da análise de imagem digital e demonstrado possibilidades de utilização diagnóstica e prognóstica. A assinatura digital é um histograma representativo de conjuntos de características de textura da cromatina do núcleo celular obtida através da imagem computadorizada. O objetivo deste estudo foi a caracterização dos núcleos celulares neoplásicos no adenocarcinoma primário de reto pelo método da assinatura digital e verificar o valor prognóstico das alterações nucleares da textura da cromatina nuclear para esta doença. Foram avaliados, pelo método de análise de imagem digital, 51 casos de pacientes operados no Hospital de Clínicas de Porto Alegre (HCPA) entre 1988 e 1996 e submetidos à ressecção eletiva do adenocarcinoma primário de reto, com seguimento de cinco anos pós-operatório, ou até o óbito antes deste período determinado pela doença, e 22 casos de biópsias normais de reto obtidas de pacientes submetidos a procedimentos endoscópicos, para controle do método da assinatura digital. A partir dos blocos de parafina dos espécimes estocados no Serviço de Patologia do HCPA, foram realizadas lâminas coradas com hematoxilina e eosina das quais foram selecionados 3.635 núcleos dos adenocarcinomas de reto e 2.366 núcleos dos controles da assinatura digital, totalizando 6.001 núcleos estudados por análise de imagem digital. De cada um destes núcleos foram verificadas 93 características, sendo identificadas 11 características cariométricas com maior poder de discriminação entre as células normais e neoplásicas. Desta forma, através da verificação da textura da cromatina nuclear, foram obtidos os histogramas representativos de cada núcleo ou conjunto de núcleos dos grupos ou subgrupos estudados, também no estadiamento modificado de Dukes, dando origem às assinaturas digitais correspondentes. Foram verificadas as assinaturas nucleares, assinaturas de padrão histológico ou de lesões e a distribuição da Densidade Óptica Total. Houve diferença significativa das características entre o grupo normal e o grupo com câncer, com maior significância para três delas, a Área, a Densidade Óptica Total e a Granularidade nuclear. Os valores das assinaturas médias nucleares foram: no grupo normal 0,0009 e nos estadiamentos; 0,9681 no A, 4,6185 no B, 2,3957 no C e 2,1025 no D e diferiram com significância estatística (P=0,001). A maior diferença do normal ocorreu no subgrupo B de Dukes-Turnbull. As assinaturas nucleares e de padrão histológico mostraram-se distintas no grupo normal e adenocarcinoma, assim como a distribuição da Densidade Óptica Total a qual mostra um afastamento progressivo da normalidade no grupo com câncer. Foi possível a caracterização do adenocarcinoma de reto, que apresentou assinaturas digitais específicas. Em relação ao prognóstico, a Densidade Óptica Total representou a variável que obteve o melhor desempenho, além do estadiamento, como preditor do desfecho.

A Common-feature approach for testing present-value restrictions with financial data

It is well known that cointegration between the level of two variables (labeled Yt and yt in this paper) is a necessary condition to assess the empirical validity of a present-value model (PV and PVM, respectively, hereafter) linking them. The work on cointegration has been so prevalent that it is often overlooked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. The basis of this result is the use of rational expectations in forecasting future values of variables in the PVM. If this condition fails, the present-value equation will not be valid, since it will contain an additional term capturing the (non-zero) conditional expected value of future error terms. Our article has a few novel contributions, but two stand out. First, in testing for PVMs, we advise to split the restrictions implied by PV relationships into orthogonality conditions (or reduced rank restrictions) before additional tests on the value of parameters. We show that PV relationships entail a weak-form common feature relationship as in Hecq, Palm, and Urbain (2006) and in Athanasopoulos, Guillén, Issler and Vahid (2011) and also a polynomial serial-correlation common feature relationship as in Cubadda and Hecq (2001), which represent restrictions on dynamic models which allow several tests for the existence of PV relationships to be used. Because these relationships occur mostly with nancial data, we propose tests based on generalized method of moment (GMM) estimates, where it is straightforward to propose robust tests in the presence of heteroskedasticity. We also propose a robust Wald test developed to investigate the presence of reduced rank models. Their performance is evaluated in a Monte-Carlo exercise. Second, in the context of asset pricing, we propose applying a permanent-transitory (PT) decomposition based on Beveridge and Nelson (1981), which focus on extracting the long-run component of asset prices, a key concept in modern nancial theory as discussed in Alvarez and Jermann (2005), Hansen and Scheinkman (2009), and Nieuwerburgh, Lustig, Verdelhan (2010). Here again we can exploit the results developed in the common cycle literature to easily extract permament and transitory components under both long and also short-run restrictions. The techniques discussed herein are applied to long span annual data on long- and short-term interest rates and on price and dividend for the U.S. economy. In both applications we do not reject the existence of a common cyclical feature vector linking these two series. Extracting the long-run component shows the usefulness of our approach and highlights the presence of asset-pricing bubbles.

Soil texture spatial variability of different parent material in pereira barreto, São Paulo state

The variation of soil textural characteristics is a function of the relief and parent materials. The objective of this work was to study soil texture spatial variability from different parent material in Pereira Barreto, SP. An area of 530.67 hectares was mapped through the use of Global Positioning System receivers and obtaining of Digital Elevation Models. A set of 201 soil samples was collected from every seven hectares, at three depths: 0 - 0.25 m; 0.25 - 0.50 m; and 0.80 - 1.00 m. The amounts of sand, silt and clay were obtained by the pipette method and analyzed by both descriptive statistics and geostatistics. Soil textures varied as a function of parent materials and topography.

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries

Potassium Leaching as Affected by Soil Texture and Residual Fertilization in Tropical Soils

Potassium (K) leaching is affected by soil texture and available K, among other factors. In this experiment, effects of soil texture and K availability on K distribution were studied in the presence of roots, with no excess water. Soils from two 6-year field experiments on a sandy clay loam and a clay soil fertilized yearly with 0, 60, 120, and 180 kg ha-1 of K2O were accommodated in pots that received 90 kg ha-1 of K2O. Soybean was grown up to its full bloom (R2). Under field conditions, K leaching below the arable layer increased with K rates, but the effect was less noticeable in the clay soil. Potassium leaching in a sandy clay loam soil was related to soil K contents from prior fertilizations. With no excess water, in the presence of soybean roots, K distribution in the profile was significant in the lighter textured soil but was not apparent on the heavier textured soil.

Correction of soil acidity in the subsurface of an oxisol with sandy loam texture under no-tillage

No Rio Grande do Sul (RS), muitas áreas sob plantio direto apresentam elevada saturação por Al e baixa saturação por bases na camada de 0,10-0,20 m (subsuperfície), e isso pode diminuir a produção de grãos de culturas anuais. O objetivo do presente trabalho foi avaliar se a ocorrência de alta saturação por Al e baixa saturação por bases em subsuperfície (0,10-0,20 m), no plantio direto, pode representar um ambiente restritivo para a produção de culturas, bem como avaliar os modos de incorporação de calcário na correção da acidez do solo em subsuperfície. Para isso, foi realizado um experimento com os cultivos de soja (2005/ 2006), milho (2006/2007), trigo (2007) e soja (2007/2008), em um Latossolo Vermelho distrófico típico (Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), 2006) de textura franco arenosa, há quatro anos sob plantio direto, no município de Tupanciretã (RS). Os seis tratamentos foram: sem revolvimento com ou sem calcário; lavração com ou sem calcário; e escarificação com ou sem calcário. Aos 24 meses após a aplicação dos tratamentos e nas camadas de 0-0,05, 0,05-0,10, 0,10-0,15, 0,15-0,20 e 0,20-0,30 m, foram avaliados os valores de pH-H2O, saturação por Al e por bases. Avaliou-se a produtividade de soja (2005/2006), milho (2006/2007), trigo (2007) e soja (2007/2008). A acidez do solo em subsuperfície não alterou a produtividade das culturas quando as propriedades de acidez na camada de 0-0,10 m estavam em níveis em que não se recomenda a aplicação de calcário, segundo a CQFSRS/SC (2004). A incorporação de calcário com aração foi o modo mais eficiente de corrigir a acidez em profundidade.

Fractal analysis of leaf-texture properties as a tool for taxonomic and identification purposes: a case study with species from Neotropical Melastomataceae (Miconieae tribe)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

CENSUS HISTOGRAMS: A SIMPLE FEATURE EXTRACTION and MATCHING APPROACH FOR FACE RECOGNITION

Most face recognition approaches require a prior training where a given distribution of faces is assumed to further predict the identity of test faces. Such an approach may experience difficulty in identifying faces belonging to distributions different from the one provided during the training. A face recognition technique that performs well regardless of training is, therefore, interesting to consider as a basis of more sophisticated methods. In this work, the Census Transform is applied to describe the faces. Based on a scanning window which extracts local histograms of Census Features, we present a method that directly matches face samples. With this simple technique, 97.2% of the faces in the FERET fa/fb test were correctly recognized. Despite being an easy test set, we have found no other approaches in literature regarding straight comparisons of faces with such a performance. Also, a window for further improvement is presented. Among other techniques, we demonstrate how the use of SVMs over the Census Histogram representation can increase the recognition performance.

New Insights on Nontechnical Losses Characterization Through Evolutionary-Based Feature Selection

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

Fuzzy Logic and Geostatistical Techniques for Spatialization of Soil Texture in Region with Rough Terrains

From the geotechnical standpoint, it is interesting to analyse the soil texture in regions with rough terrain due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this paper is to present a methodology that provides the soil texture spatialization by using Fuzzy logic and Geostatistic. The results were correlated with maps drawn specifically for the study area. The knowledge of the spatialization of soil properties, such as the texture, can be an important tool for land use planning in order to reduce the potential soil losses during rain seasons. (c) 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of Spatial Statistics 2011

Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Feature selection through gravitational search algorithm

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.