Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

A complex networks approach for data clustering

This work proposes a method for data clustering based on complex networks theory. A data set is represented as a network by considering different metrics to establish the connection between each pair of objects. The clusters are obtained by taking into account five community detection algorithms. The network-based clustering approach is applied in two real-world databases and two sets of artificially generated data. The obtained results suggest that the exponential of the Minkowski distance is the most suitable metric to quantify the similarities between pairs of objects. In addition, the community identification method based on the greedy optimization provides the best cluster solution. We compare the network-based clustering approach with some traditional clustering algorithms and verify that it provides the lowest classification error rate. (C) 2012 Elsevier B.V. All rights reserved.

Heuristics for minimizing the maximum within-clusters distance

The clustering problem consists in finding patterns in a data set in order to divide it into clusters with high within-cluster similarity. This paper presents the study of a problem, here called MMD problem, which aims at finding a clustering with a predefined number of clusters that minimizes the largest within-cluster distance (diameter) among all clusters. There are two main objectives in this paper: to propose heuristics for the MMD and to evaluate the suitability of the best proposed heuristic results according to the real classification of some data sets. Regarding the first objective, the results obtained in the experiments indicate a good performance of the best proposed heuristic that outperformed the Complete Linkage algorithm (the most used method from the literature for this problem). Nevertheless, regarding the suitability of the results according to the real classification of the data sets, the proposed heuristic achieved better quality results than C-Means algorithm, but worse than Complete Linkage.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.

Role of Two Clusters of Male Alcoholics in Treatment Retention

Aims: This study aimed to classify alcohol-dependent outpatients on the basis of clinical factors and to verify if the resulting types show different treatment retention. Methods: The sample comprised 332 alcoholics that were enrolled in three different pharmacological trials carried out at Sao Paulo University, Brazil. Based on four clinical factors problem drinking onset age, familial alcoholism, alcohol dependence severity, and depression - K-means cluster analysis was performed by using the average silhouette width to determine the number of clusters. A direct logistic regression was performed to analyze the influence of clusters, medication groups, and Alcoholics Anonymous ( AA) attendance in treatment retention. Results: Two clusters were delineated. The cluster characterized by earlier onset age, more familial alcoholism, higher alcoholism severity, and less depression symptoms showed a higher chance of discontinuing the treatment, independently of medications used and AA attendance. Participation in AA was significantly related to treatment retention. Discussion: Health services should broaden the scope of services offered to meet heterogeneous needs of clients, and identify treatment practices and therapists which improve retention. Information about patients' characteristics linked to dropout should be used to make treatment programs more responsive and attractive, combining pharmacological agents with more intensive and diversified psychosocial interventions. Copyright (C) 2012 S. Karger AG, Basel

Micropolítica do trabalho dos profissionais de saúde na UBS: visão sobre necessidades de saúde das famílias

Este estudo teve como objetivo compreender as potencialidades e limitações do processo de trabalho da enfermagem de uma Unidade Básica de Saúde para o reconhecimento das necessidades de saúde da população. A vertente metodológica utilizada foi a pesquisa social, na perspectiva qualitativa, tendo como base de análise dos discursos a hermêutica-dialética, e como alicerce a Teoria da Interpretação Práxica da Enfermagem em Saúde Coletiva. Os dados foram coletados por meio da entrevista semiestruturada e os processos de trabalho das equipes foram analisados através do Fluxograma Analisador do Modelo de Atenção de um Serviço de Saúde. Concluiu-se que há limitações no cotidiano do processo de trabalho da equipe de enfermagem à medida em que o reconhecimento e enfrentamento das necessidades de saúde perpassavam pela identificação de agravos instalados, deixando em segundo plano os determinantes sociais das más condições de vida associadas ao processo saúde-doença.

Porcelain monolayers and porcelain/alumina bilayers reinforced by Al2O3/GdAlO3 fibers

Aim. This work tested the effect of the addition of Al2O3/GdAlO3 longitudinal fibers in different contents to veneering porcelain of two dental all ceramic systems. Methods: Fibers (0.5 mm diameter) obtained by the Laser Heated Pedestal Growth (LHPG) method were added to bar-shaped specimens made by veneer porcelain (monolayers) or both the veneer and the core ceramic (bilayers) of two all-ceramic systems: In-Ceram Alumina - glass infiltrated alumina composite (GIA) and In-Ceram 2000 AL Cubes - alumina polycrystal (AP) (VITA Zahnfabrik). The longitudinal fibers were added to veneering porcelain (VM7) in two different proportions: 10 or 17 vol%. The bars were divided into nine experimental conditions (n = 10) according to material used: VM7 porcelain monolayers, VM7/GIA, VM7/AP; and according to the amount of fibers within the porcelain layer: no fibers, 10 vol% or 17 vol%. After grinding and polishing the specimens were submitted to a three point bending test (crosshead speed = 0.5 mm/min) with porcelain positioned at tensile side. Data were analyzed by means of one-way ANOVA and a Tukey's test (alpha = 5%). Scanning electronic microscopy (SEM) was conducted for fractographic analysis. Results. Regarding the groups without fiber addition, VM7/AP showed the highest flexural strength (MPa), followed by VM7/GIA and VM7 monolayers. The addition of fibers led to a numerical increase in flexural strength for all groups. For VM7/GIA bilayers the addition of 17 vol% of fibers resulted in a significant 48% increase in the flexural strength compared to the control group. Fractographic analysis revealed that the crack initiation site was in porcelain at the tensile surface. Cracks also propagated between fibers before heading for the alumina core. Conclusions. The addition of 17 vol% of Al2O3/GdAlO3 longitudinal fibers to porcelain/glass infiltrated alumina bilayers significantly improved its flexural strength. 10 vol% or 17 vol% of fibers inclusion increased the flexural strength for all groups. (C) 2011 Elsevier Ltd. All rights reserved.

Description of atmospheric conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargue and averaged monthly models, the utility of the GDAS data is shown. (C) 2012 Elsevier B.V. All rights reserved.

Multivariate analysis in the maximum strength performance

This study performed an exploratory analysis of the anthropometrical and morphological muscle variables related to the one-repetition maximum (1RM) performance. In addition, the capacity of these variables to predict the force production was analyzed. 50 active males were submitted to the experimental procedures: vastus lateralis muscle biopsy, quadriceps magnetic resonance imaging, body mass assessment and 1RM test in the leg-press exercise. K-means cluster analysis was performed after obtaining the body mass, sum of the left and right quadriceps muscle cross-sectional area (Sigma CSA), percentage of the type II fibers and the 1RM performance. The number of clusters was defined a priori and then were labeled as high strength performance (HSP1RM) group and low strength performance (LSP1RM) group. Stepwise multiple regressions were performed by means of body mass, Sigma CSA, percentage of the type II fibers and clusters as predictors' variables and 1RM performance as response variable. The clusters mean +/- SD were: 292.8 +/- 52.1 kg, 84.7 +/- 17.9 kg, 19249.7 +/- 1645.5 mm(2) and 50.8 +/- 7.2% for the HSP1RM and 254.0 +/- 51.1 kg, 69.2 +/- 8.1 kg, 15483.1 +/- 1 104.8 mm(2) and 51.7 +/- 6.2 %, for the LSP1RM in the 1RM, body mass, Sigma CSA and muscle fiber type II percentage, respectively. The most important variable in the clusters division was the Sigma CSA. In addition, the Sigma CSA and muscle fiber type II percentage explained the variance in the 1RM performance (Adj R-2 = 0.35, p = 0.0001) for all participants and for the LSP1RM (Adj R-2 = 0.25, p = 0.002). For the HSP1RM, only the Sigma CSA was entered in the model and showed the highest capacity to explain the variance in the 1RM performance (Adj R-2 = 0.38, p = 0.01). As a conclusion, the muscle CSA was the most relevant variable to predict force production in individuals with no strength training background.

Stochastic competitive learning in complex networks

Competitive learning is an important machine learning approach which is widely employed in artificial neural networks. In this paper, we present a rigorous definition of a new type of competitive learning scheme realized on large-scale networks. The model consists of several particles walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder particles. The particle's walking rule is composed of a stochastic combination of random and preferential movements. The model has been applied to solve community detection and data clustering problems. Computer simulations reveal that the proposed technique presents high precision of community and cluster detections, as well as low computational complexity. Moreover, we have developed an efficient method for estimating the most likely number of clusters by using an evaluator index that monitors the information generated by the competition process itself. We hope this paper will provide an alternative way to the study of competitive learning.

Prevalence of depression and anxiety disorders in hospitalized patients at the dermatology clinical ward of a university hospital

BACKGROUND: The objective of this study was to estimate the prevalence of depression and anxiety disorders in hospitalized patients at the dermatology ward at a university hospital in Sao Paulo, Brazil. OBJECTIVE: To assess the prevalence of mood and anxiety disorders in hospitalized patients at the dermatology ward at a university hospital in Sao Paulo. METHOD: A total of 75 patients, men and women, aged between 18 and 76 years, took part in the research. The study employed a descriptive, cross sectional and correlational method. The data was collected by means of a social demographic questionnaire and the PRIME-MD. RESULTS: It was found that 45.3 percent of the subjects presented with depressive symptoms, and 52 percent presented with symptoms of anxiety and that this survey showed moderate and high significant correlations (p<0,01; r= 0,616) for depression and anxiety. CONCLUSION: These facts could evidence the relationship between physical and psyche, just as the literature presents.

Home range, movements and diurnal roosts of the endangered thin-spined porcupine, Chaetomys subspinosus (Rodentia: Erethizontidae), in the Brazilian Atlantic Forest

Chaetomys subspinosus is the sole species within the Chaetomyinae subfamily of Caviomorph rodents. This poorly studied porcupine is restricted to the Atlantic Forest in eastern Brazil, where deforestation and habitat fragmentation threaten its survival. Data on the ranging and roosting behavior of C. subspinosus is fairly scarce as it is difficult to observe these behaviors in nature and, consequently, it is very rarely detected during field surveys. We monitored the home ranges of three radio-tagged females over the course of 1 year (2005-2006) and collected data on several aspects of their natural history including movement patterns and the use of diurnal roosts and latrines. The animals were monitored at Parque Estadual Paulo Cesar Vinha, a nature reserve dominated by restinga forests, a subtype of Atlantic Forest occurring on sandy soil. The estimated home range varied little between individuals and was relatively small (mean = 2.14 ha/individual and 1.09 ha/individual using minimum convex polygon and kernel methods, respectively). The animals travelled an average of 147 m/night (range: 21-324 m/night) between two consecutive day roosts. The day roosts were mostly located on vine and liana tangles in the canopy which also aid in connecting the canopy to adjacent trees or the forest floor. Latrines were mostly located near the ground in places heavily protected by spiny bromeliads or by other tangled vegetation. Our data suggests that C. subspinosus has the smallest range among all Neotropical Erethizontids which is likely due to its small size and strictly folivorous diet. Our data also helps explain why C. subspinosus is so difficult to observe in nature: researchers should focus on arboreal masses of tangled vegetation where individuals will normally rest during the day. (C) 2011 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.

Avaliação dos exercícios proprioceptivos no tratamento dos distúrbios do manguito rotador em profissionais de enfermagem: um estudo clínico controlado e randomizado

CONTEXTUALIZAÇÃO: A dor no ombro em profissionais de enfermagem pode acarretar limitação das atividades diárias e ocupacionais e interferir na qualidade de vida. OBJETIVO: Comparar o efeito da aplicação de dois programas fisioterapêuticos diferenciados pelos exercícios de propriocepção em trabalhadores de enfermagem com desordem do manguito rotador, segundo indicadores de qualidade de vida, satisfação no trabalho e intensidade da dor. MÉTODO: Trata-se de um estudo experimental, randomizado, prospectivo, comparativo, com análise quantitativa dos dados. A coleta de dados foi realizada no período de junho de 2010 a julho de 2011, por meio de um questionário sociodemográfico e profissional, questionário Western Ontario Rotador Cuff Index (WORC), Escala de Satisfação no Trabalho (Occupational Stress Indicator) e Escala Visual Numérica (EVN) para intensidade da dor. Após randomização, os sujeitos foram alocados em dois grupos. No Grupo 1 (controle), foram aplicados exercícios de alongamento, fortalecimento e crioterapia. No Grupo 2 (experimental), foram realizados os mesmos exercícios que no Grupo 1 acrescidos de exercícios proprioceptivos. Os dados foram analisados por meio do Statistical Package for the Social Science, versão 16.0 para Windows. RESULTADOS: Após os tratamentos fisioterapêuticos, houve melhora significativa da dor nos sujeitos dos dois grupos e da qualidade de vida nos trabalhadores do Grupo 2. Não houve alteração dos indicadores de satisfação no trabalho nos dois grupos. CONCLUSÕES: Os exercícios proprioceptivos foram importantes no tratamento dos distúrbios osteomusculares. No entanto, os resultados não permitiram inferir a melhor efetividade deles em relação ao outro tratamento, pois não houve diferença significativa entre os grupos. Ensaio clínico registrado no ClinicalTrials.gov NCT01465932.

Cost Management Practices and Strategic Perspectives: a study in the construction industry of the State of Parana

The purpose of this paper is to investigate the cost management practices of building industry companies of Parana that follow the typology of Porter's strategies. The sample comprises member companies of the Association of Construction Industries of the State of Parana (PR-SINDUSCON) operating in the segment of residential buildings. The data were collected by means of questionnaires sent to 317 SINDUSCON members. 69 were returned and 54 used for our research. Exploratory Factorial Analysis of the data allowed us to identify two groups of cost management practices. Analyses suggest equality between the adopted cost management practices and the Cost Control Planning (CCP) practices among the companies of the Group 1, regardless of the generic strategy adopted. The companies of the Group 2 that adopted the differentiation strategy seem to use mainly the ACR cost management practice. Our findings differ from those obtained by Chenhall insofar as companies that adopt low cost strategies tend to use managerial controls focused on cost control and rigid budgetary controls.