Geotecnologias aplicadas à caracterização e mapeamento das alterações da cobertura vegetal intra-urbana e da expansão urbana da cidade de Rio Claro (SP)

Pós-graduação em Geografia - IGCE

Avaliação da adaptação marginal de restaurações cerâmicas inlay após a cimentação

Pós-graduação em Odontologia Restauradora - ICT

Método para extração e caracterização de lesões de pele usando difusão anisotrópica, crescimento de regiões, watersheds e contornos ativos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geotecnologias digitais no ensino médio: avaliação prática de seu potencial

Pós-graduação em Geografia - IGCE

Estudo das características morfométricas de diferentes regiões do intestino delgado e índices zootécnicos em quatro linhagens de frangos de corte

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

Educação matemática através de interfaces computacionais: o papel de componentes interativos na postura exploratória e na aprendizagem

Neste trabalho, investigamos o papel de componentes interativos, frequentemente utilizados na construção de interfaces computacionais educativas, na postura exploratória do estudante e na aprendizagem de conceitos matemáticos. Selecionamos para esta pesquisa os seguintes componentes: caixa de combinações (combo box) e campo de texto (text field). Do ponto de vista educacional, estes componentes têm papéis distintos: o primeiro orienta as escolhas do estudante durante um processo exploratório, enquanto que o segundo não oferece qualquer orientação. Para comparar o papel desses componentes, desenvolvemos duas interfaces computacionais interativas através das quais o estudante pode explorar o comportamento gráfico de uma função do primeiro grau. Ambas as interfaces são idênticas entre si, a menos do componente interativo empregado: em uma delas foi utilizado a caixa de combinações e em outra o campo de texto. Tanto a postura exploratória quanto o desempenho em testes de conhecimento foram avaliados a partir de medidas diretas registradas pelas próprias interfaces. A postura exploratória foi avaliada através do número e do tipo de interações do estudante com o componente interativo, sendo este registro uma das características singulares desta pesquisa, pois permite a observação de alguns comportamentos do estudante durante o processo de interação com a interface, e não somente antes e após a interação. Dentro da limitação da ferramenta de coleta de dados da presente pesquisa, a aprendizagem foi medida através da comparação do desempenho em testes de conhecimento aplicados antes e depois do uso dos componentes interativos pelos estudantes. Neste contexto, diferenças significativas no papel de cada componente na postura exploratória e na aprendizagem foram então observadas.

Development of a CAD system for automatic classification of microcalcifications based on FPGA

This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

Optimum-Path Forest Applied for Breast Masses Classification

In Computer-Aided Diagnosis-based schemes in mammography analysis each module is interconnected, which directly affects the system operation as a whole. The identification of mammograms with and without masses is highly needed to reduce the false positive rates regarding the automatic selection of regions of interest for further image segmentation. This study aims to evaluate the performance of three techniques in classifying regions of interest as containing masses or without masses (without clinical findings), as well as the main contribution of this work is to introduce the Optimum-Path Forest (OPF) classifier in this context, which has never been done so far. Thus, we have compared OPF against with two sorts of neural networks in a private dataset composed by 120 images: Radial Basis Function and Multilayer Perceptron (MLP). Texture features have been used for such purpose, and the experiments have demonstrated that MLP networks have been slightly better than OPF, but the former is much faster, which can be a suitable tool for real-time recognition systems.

Modelagem computacional das túnicas cardíacas para processamento e controle de qualidade

This paper considers a study of the anatomical features of the cardiac system and a three-dimensional model of the different tunics that comprise the heart wall, for processing and quality control of radiological images. The structures are built by the layer overlapping method, where a layer can be understood as a slice of the three-dimensional object. The pericardium, myocardium and endocardium were represented with three-dimensional cylinders and hexagons. The spatial arrangement of the cardiac system is determined by an background image of a real model, which values are defined according to the shape of the region and on the anatomical patients characteristics. The results are significant, considering the anatomical structures details, as well as the representation of the thicknesses of the regions of the heart wall. The validation of the anatomical model was accomplished through comparisons with dimensions obtained from a real model and allows verifying that the model is appropriate. The degree of representation will allow the verification of the influence of radiological parameters, morphometric peculiarities and stage of the diseases on the quality of the images, as well as on the performance of the Computer-Aided Diagnosis (CAD).

Bamboo as sustainable material used in design and civil construction: species, management, characterization and applications

The use of bamboo as construction and raw material for producing products can be considered a feasible alternative to the abusive use of steel, concrete and oil byproducts. Its use can also reduce the pressure on the use of wood from native and planted forests. Although there are thousands of bamboo species spread about the world and Brazil itself has hundreds of native species, the use and basic knowledge of its characteristics and applications are still little known and little disseminated. This paper's main objective is to introduce the species, the management phases, the physical and mechanical characteristics and the experiences in using bamboo in design and civil construction as per the Bamboo Project implemented at UNESP, Bauru campus since 1994. The results are divided into: a) Field activities - description of the technological species of interest, production chain flows, types of preservative treatments and clump management practices for the development, adaptation and production of different species of culms; b) Lab experiments - physical and mechanical characterization of culms processed as laminated strips and as composite material (glue laminated bamboo – glubam); c) Uses in projects - experiences with natural bamboo and glubam in design, architecture and civil construction projects. In the final remarks, the study aims to demonstrate, through practical and laboratory results, the material's multi-functionality and the feasibility in using bamboo as a sustainable material.

A survey of evolutionary algorithms for decision-tree induction

This paper presents a survey of evolutionary algorithms that are designed for decision-tree induction. In this context, most of the paper focuses on approaches that evolve decision trees as an alternate heuristics to the traditional top-down divide-and-conquer approach. Additionally, we present some alternative methods that make use of evolutionary algorithms to improve particular components of decision-tree classifiers. The paper's original contributions are the following. First, it provides an up-to-date overview that is fully focused on evolutionary algorithms and decision trees and does not concentrate on any specific evolutionary approach. Second, it provides a taxonomy, which addresses works that evolve decision trees and works that design decision-tree components by the use of evolutionary algorithms. Finally, a number of references are provided that describe applications of evolutionary algorithms for decision-tree induction in different domains. At the end of this paper, we address some important issues and open questions that can be the subject of future research.

The effect of implant design on insertion torque and immediate micromotion

Objectives: To evaluate the effect of insertion torque on micromotion to a lateral force in three different implant designs. Material and methods: Thirty-six implants with identical thread design, but different cutting groove design were divided in three groups: (1) non-fluted (no cutting groove, solid screw-form); (2) fluted (901 cut at the apex, tap design); and (3) Blossomt (Patent pending) (non-fluted with engineered trimmed thread design). The implants were screwed into polyurethane foam blocks and the insertion torque was recorded after each turn of 901 by a digital torque gauge. Controlled lateral loads of 10N followed by increments of 5 up to 100N were sequentially applied by a digital force gauge on a titanium abutment. Statistical comparison was performed with two-way mixed model ANOVA that evaluated implant design group, linear effects of turns and displacement loads, and their interaction. Results: While insertion torque increased as a function of number of turns for each design, the slope and final values increased (Po0.001) progressively from the Blossomt to the fluted to the non-fluted design (M +/- standard deviation [SD] = 64.1 +/- 26.8, 139.4 +/- 17.2, and 205.23 +/- 24.3 Ncm, respectively). While a linear relationship between horizontal displacement and lateral force was observed for each design, the slope and maximal displacement increased (Po0.001) progressively from the Blossomt to the fluted to the non-fluted design (M +/- SD 530 +/- 57.7, 585.9 +/- 82.4, and 782.33 +/- 269.4 mm, respectively). There was negligible to moderate levels of association between insertion torque and lateral displacement in the Blossomt, fluted and non-fluted design groups, respectively. Conclusion: Insertion torque was reduced in implant macrodesigns that incorporated cutting edges, and lesser insertion torque was generally associated with decreased micromovement. However, insertion torque and micromotion were unrelated within implant designs, particularly for those designs showing the least insertion torque.

Three-Dimensional Ultrasonographic Assessment of Fetal Total Lung Volume as a Prognostic Factor in Primary Pleural Effusion

Objectives-The purpose of this study was to predict perinatal outcomes using fetal total lung volumes assessed by 3-dimensional ultrasonography (3DUS) in primary pleural effusion. Methods-Between July 2005 and July 2010, total lung volumes were prospectively estimated in fetuses with primary pleural effusion by 3DUS using virtual organ computer-aided analysis software. The first and last US examinations were considered in the analysis. The observed/expected total lung volumes were calculated. Main outcomes were perinatal death (up to 28 days of life) and respiratory morbidity (orotracheal intubation with mechanical respiratory support >48 hours). Results-Twelve of 19 fetuses (63.2%) survived. Among the survivors, 7 (58.3%) had severe respiratory morbidity. The observed/expected total lung volume at the last US examination before birth was significantly associated with perinatal death (P < .01) and respiratory morbidity (P < .01) as well as fetal hydrops (P < .01) and bilateral effusion (P = .01). Conclusions-Fetal total lung volumes may be useful for the prediction of perinatal outcomes in primary pleural effusion.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Software for subjective visual vertical assessment: an observational cross-sectional study

Spatial orientation in relation to the gravitational axis is significantly important for the maintenance of the posture, gait and for most of the human's motor activities. The subjective visual vertical exam evaluates the individual's perception of vertical orientation. Objectives: The aims of this study were (1) to develop a virtual system to evaluate the subjective visual vertical exam, (2) to provide a simple tool to clinical practice and (3) to assess the subjective visual vertical values of h ealthy subjects using the new software. Study Design: observational cross-sectional study. Methods: Thirty healthy volunteers performed the subjective visual vertical exam in both static and dynamic conditions. The exam consisted in adjusting a virtual line in the vertical position using the computer mouse. For the static condition, the virtual line was projected in a white background. For the dynamic condition, black circles rotated in clockwise or counterclockwise directions. Six measurements were taken and the mean deviations in relation to the real vertical calculated. Results: The mean values of subjective visual vertical measurements were: static -0.372 degrees; +/- 1.21; dynamic clockwise 1.53 degrees +/- 1.80 and dynamic counterclockwise -1.11 degrees +/- 2.46. Conclusion: This software showed to be practical and accurate to be used in clinical routines.