Análise de desempenho baseada em simulação de redes WirelessHART

This dissertation describes the implementation of a WirelessHART networks simulation module for the Network Simulator 3, aiming for the acceptance of both on the present context of networks research and industry. For validating the module were imeplemented tests for attenuation, packet error rate, information transfer success rate and battery duration per station

Aplicação de técnicas de aprendizado de máquina no reconhecimento de classes estruturais de proteínas

Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

Um monitor de metadados de QoS e QoC para plataformas de middleware

Context-aware applications are typically dynamic and use services provided by several sources, with different quality levels. Context information qualities are expressed in terms of Quality of Context (QoC) metadata, such as precision, correctness, refreshment, and resolution. On the other hand, service qualities are expressed via Quality of Services (QoS) metadata such as response time, availability and error rate. In order to assure that an application is using services and context information that meet its requirements, it is essential to continuously monitor the metadata. For this purpose, it is needed a QoS and QoC monitoring mechanism that meet the following requirements: (i) to support measurement and monitoring of QoS and QoC metadata; (ii) to support synchronous and asynchronous operation, thus enabling the application to periodically gather the monitored metadata and also to be asynchronously notified whenever a given metadata becomes available; (iii) to use ontologies to represent information in order to avoid ambiguous interpretation. This work presents QoMonitor, a module for QoS and QoC metadata monitoring that meets the abovementioned requirement. The architecture and implementation of QoMonitor are discussed. To support asynchronous communication QoMonitor uses two protocols: JMS and Light-PubSubHubbub. In order to illustrate QoMonitor in the development of ubiquitous application it was integrated to OpenCOPI (Open COntext Platform Integration), a Middleware platform that integrates several context provision middleware. To validate QoMonitor we used two applications as proofof- concept: an oil and gas monitoring application and a healthcare application. This work also presents a validation of QoMonitor in terms of performance both in synchronous and asynchronous requests

Autopsy: quality assurance in the ICU

Objective: To examine the correlation between the clinical diagnosis and autopsy findings in adult patients who died in an intensive care unit (ICU). To determine the rate of agreement of the basic and terminal causes of death and the types of errors in order to improve quality control of future care,Design, Retrospective study.Setting: Adult ICU in a university hospital.Patients: 30 adult patients who died in the ICU. with the exclusion of medicolegal cases.Methods and main results: Anatomo-clinical meetings were held to analyze the pre- and postmortem correlations in 30 consecutive autopsies at the ICU of the University Hospital, School of Medicine of Botucatu/ UNESP, from January 1994 to January 1997. The rate of correct clinical diagnoses of the basic cause was 66.7 %; in 23.3 % of cases, if the correct diagnosis was made, management would have been different, as would have been the evolution of the patient's course (Class I error): in 10 % of the cases the error would not have led to a change in management (Class II error). The rate of correct clinical diagnoses of terminal cause was 80 %.Conclusions: the rate of recognition of the basic cause was 66.7 %, which is consistent with the literature, but the Class I error rate was higher than that reported in the literature.

A function to predict the risk for death in the neonatal sepsis

This was a prospective study of 43 septic neonates at the NICU of the School of Medicine of Botucatu, São Paulo State University. Clinical and laboratory data of sepsis were analyzed based on outcome divided into two groups, survival and death. We calculated the discriminatory power of the relevant variables for the diagnosis of sepsis in each group, and using software for Discriminant Analysis, a function was proposed. There were 43 septic cases with 31 survivals and 12 deaths. The variables that had the highest discriminatory power were: n(o) of compromised systems, the SNAP, FiO2, and (A-a)O2. The study of these and others variables, such as birth weight, n(o) of risk factors, and pH using a Linear Discriminant Function(LDF) allowed us to identify the high-risk neonates for death with a low error rate (8.33%). The LDF was: F = 0.00043 (birth weight) + 0.30367 (n(o) of risk factors) - 0.1171 (n(o) of compromised systems) + 0.33223 (SNAP) + 2.27972 (pH) - 14.96511 (FiO2) + 0.01814 ((A-a)O2). If F > 22.77 there was high risk of death. This study suggests that the LDF at the onset of sepsis is useful for the early identification of the high-risk neonates that need special clinical and laboratory surveillance.

Associations between LEP, DGAT1 and FABP4 gene polymorphisms and carcass and meat traits in Nelore and crossbred beef cattle

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

Identification of Landslide Scars in the Region of the Serra do Mar, São Paulo State, Brazil, Using Digital Image Processing and Spatial Analysis Tools

The objective of the present study, developed in a mountainous region in Brazil where many landslides occur, is to present a method for detecting landslide scars that couples image processing techniques with spatial analysis tools. An IKONOS image was initially segmented, and then classified through a Batthacharrya classifier, with an acceptance limit of 99%, resulting in 216 polygons identified with a spectral response similar to landslide scars. After making use of some spatial analysis tools that took into account a susceptibility map, a map of local drainage channels and highways, and the maximum expected size of scars in the study area, some features misinterpreted as scars were excluded. The 43 resulting features were then compared with visually interpreted landslide scars and field observations. The proposed method can be reproduced and enhanced by adding filtering criteria and was able to find new scars on the image, with a final error rate of 2.3%.

Método simplificado para manutenção da concentração sangüínea de propofol em nível aproximadamente constante, associado ao óxido nitroso no paciente pediátrico

JUSTIFICATIVA E OBJETIVOS: A manutenção de concentração sangüínea alvo-controlada em níveis aproximadamente constantes do propofol é uma técnica que pode ser empregada de modo simplificado na sala de cirurgia. A finalidade desta pesquisa é comparar clínica e laboratorialmente a infusão de propofol em crianças usando os atributos farmacocinéticos de Short e de Marsh. MÉTODO: Foram estudados 41 pacientes com a idade de 4 a 12 anos, de ambos os sexos, estado físico ASA I ou II, distribuídos em dois grupos S (20 pacientes) e M (21 pacientes). No Grupo S utilizaram-se os atributos farmacocinéticos de Short, e no Grupo M, os atributos farmacocinéticos de Marsh. A indução anestésica foi feita com bolus de alfentanil 30 µg.kg-1, propofol 3 mg.kg-1 e pancurônio, 0,08 mg.kg-1 por via venosa. Procedeu-se a intubação traqueal e a manutenção com N2O/O2 (60%) em ventilação controlada mecânica. No grupo S a infusão de propofol foi de 254 (30 min) seguido de 216 µg.kg-1.min-1 por mais 30 min. No grupo M a infusão de propofol foi de 208 (30 min) seguido de 170 µg.kg-1.min-1 por mais 30 min. Através do atributo farmacocinético específico a cada grupo a meta foi a obtenção da concentração-alvo de 4 µg.kg-1 de propofol. Foram colhidas três amostras sangüíneas (aos 20, 40 e 60 minutos) para a dosagem do propofol pelo método da Cromatografia Líquida de Alta Performance. RESULTADOS: Os Grupos S e M foram considerados similares quanto à idade, altura, peso e sexo (p > 0,05). Não houve diferença estatística significativa entre os dois grupos estudados para os parâmetros: PAS, PAD, FC, FiN2O, SpO2 da hemoglobina e P ET CO2 no final da expiração. A comparação entre grupos no número de bolus repetidos de alfentanil não foi estatisticamente significativa. O índice bispectral (BIS) não apresentou diferença estatisticamente significativa entre M0 (vigília) e os demais momentos em ambos os grupos. Os valores Medianos da Performance do Erro (MPE) e os valores Medianos Absolutos da Performance do Erro (MAPE) mostraram diferenças estatísticas significativas entre os grupos no momento 60. Valores medianos da concentração sangüínea de propofol (µg.kg-1) mostraram diferenças estatísticas significativas entre M e S no momento 60 e entre os momentos 40 e 60 no grupo S. CONCLUSÕES: A anestesia com propofol usando os atributos farmacocinéticos de Marsh (Grupo M) apresentou menor erro no cálculo da concentração-alvo de propofol de 4 µg.kg-1. Além disso, utiliza menor quantidade de propofol para obter resultados clínicos semelhantes. Por todas essas qualidades deve ser a preferida para uso em crianças ASA I e com idades entre 4 e 12 anos.

Parentage testing in alpacas (Vicugna pacos) using semi-automated fluorescent multiplex PCRs with 10 microsatellite markers

The aim of this study was to assess and apply a microsatellite multiplex system for parentage determination in alpacas. An approach for parentage testing based on 10 microsatellites was evaluated in a population of 329 unrelated alpacas from different geographical zones in Peru. All microsatellite markers, which amplified in two multiplex reactions, were highly polymorphic with a mean of 14.5 alleles per locus (six to 28 alleles per locus) and an average expected heterozygosity (H-E) of 0.8185 (range of 0.698-0.946). The total parentage exclusion probability was 0.999456 for excluding a candidate parent from parentage of an arbitrary offspring, given only the genotype of the offspring, and 0.999991 for excluding a candidate parent from parentage of an arbitrary offspring, given the genotype of the offspring and the other parent. In a case test of parentage assignment, the microsatellite panel assigned 38 (from 45 cases) offspring parentage to 10 sires with LOD scores ranging from 2.19 x 10(+13) to 1.34 x 10(+15) and Delta values ranging from 2.80 x 10(+12) to 1.34 x 10(+15) with an estimated pedigree error rate of 15.5%. The performance of this multiplex panel of markers suggests that it will be useful in parentage testing of alpacas.

Escherichia coli phylogenetic group determination and its application in the identification of the major animal source of fecal contamination

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

Adenocarcinoma in females detected in serous effusions: Cytomorphologic aspects and immunocytochemical reactivity to cytokeratins 7 and 20

OBJECTIVE: To investigate the usefulness of assessing the immunoreactivity of cytokeratins 7 (CK7) and 20 (CK20) as well as several cytomorphologic parameters in effusions with metastatic adenocarcinomas in the search for the primary site of the tumor. STUDY DESIGN: From the files of the Pathology Department, A. C. Camargo Hospital, we studied cytologic smears from 73 metastatic adenocarcinomas originally from the breast, 63 from the ovary, 40 from the lung and 32 from the stomach, looking for morphologic parameters that could have discriminant potential in suggesting the primary site in a routine situation, including intranuclear inclusions, prominent nucleoli, mitosis, signet-ring cells, psammoma bodies, nuclear crease, binucleation and multinucleation, papillary features, acinar profile (including ball cells) and single cells. Immunoreactions were performed with monoclonal antibodies to CK7 (OV-TL 12/30 and CK20 (Ks 20.8) and included morphologic analysis. Both analyses were studied in a blind fashion regarding the primary site of the tumors. RESULTS: Positivity ratios for breast, ovary, stomach and lung cases were 67.6%, 63.5%, 29.7% and 45.5%, respectively, for CK7 and 17.2%, 15.8%, 13.5% and 32.2%, respectively, for CK20. Discriminant analysis of morphologic and immunocytochemical parameters had an error rate of 42.9% in recognizing the primary site and a Wilk's lambda of .7290. CONCLUSION: The more efficient parameter with discriminant function was the papillary appearance showed by CK7, which should be used in further studies with a similar scope. The set of parameters used in this study were insufficient to discriminate the primary site of female adenocarcinomas in effusions with significant accuracy.

Avaliação estatística de métodos de poda aplicados em neurônios intermediários da rede neural MLP

There are several papers on pruning methods in the artificial neural networks area. However, with rare exceptions, none of them presents an appropriate statistical evaluation of such methods. In this article, we proved statistically the ability of some methods to reduce the number of neurons of the hidden layer of a multilayer perceptron neural network (MLP), and to maintain the same landing of classification error of the initial net. They are evaluated seven pruning methods. The experimental investigation was accomplished on five groups of generated data and in two groups of real data. Three variables were accompanied in the study: apparent classification error rate in the test group (REA); number of hidden neurons, obtained after the application of the pruning method; and number of training/retraining epochs, to evaluate the computational effort. The non-parametric Friedman's test was used to do the statistical analysis.

Fusion of fingerprint recognition methods for robust human identification

Biometrics is one of the biggest tendencies in human identification. The fingerprint is the most widely used biometric. However considering the automatic fingerprint recognition a completely solved problem is a common mistake. The most popular and extensively used methods, the minutiae-based, do not perform well on poor-quality images and when just a small area of overlap between the template and the query images exists. The use of multibiometrics is considered one of the keys to overcome the weakness and improve the accuracy of biometrics systems. This paper presents the fusion of a minutiae-based and a ridge-based fingerprint recognition method at rank, decision and score level. The fusion techniques implemented leaded to a reduction of the Equal Error Rate by 31.78% (from 4.09% to 2.79%) and a decreasing of 6 positions in the rank to reach a Correct Retrieval (from rank 8 to 2) when assessed in the FVC2002-DB1A database. © 2008 IEEE.

Estimativa da vulnerabilidade natural do aquífero livre no município de Rio Claro/SP

Pós-graduação em Geociências e Meio Ambiente - IGCE

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)