A relação dos pais com o ensino pré-escolar: representações e envolvimento no jardim-de-infância dos seus filhos

Dissertação de Mestrado, Psicologia da Educação (Contextos Educativos), 12 de Novembro de 2010, Universidade dos Açores.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

Automatic email organization

Introdução Actualmente, as mensagens electrónicas são consideradas um importante meio de comunicação. As mensagens electrónicas – vulgarmente conhecidas como emails – são utilizadas fácil e frequentemente para enviar e receber o mais variado tipo de informação. O seu uso tem diversos fins gerando diariamente um grande número de mensagens e, consequentemente um enorme volume de informação. Este grande volume de informação requer uma constante manipulação das mensagens de forma a manter o conjunto organizado. Tipicamente esta manipulação consiste em organizar as mensagens numa taxonomia. A taxonomia adoptada reflecte os interesses e as preferências particulares do utilizador. Motivação A organização manual de emails é uma actividade morosa e que consome tempo. A optimização deste processo através da implementação de um método automático, tende a melhorar a satisfação do utilizador. Cada vez mais existe a necessidade de encontrar novas soluções para a manipulação de conteúdo digital poupando esforços e custos ao utilizador; esta necessidade, concretamente no âmbito da manipulação de emails, motivou a realização deste trabalho. Hipótese O objectivo principal deste projecto consiste em permitir a organização ad-hoc de emails com um esforço reduzido por parte do utilizador. A metodologia proposta visa organizar os emails num conjunto de categorias, disjuntas, que reflectem as preferências do utilizador. A principal finalidade deste processo é produzir uma organização onde as mensagens sejam classificadas em classes apropriadas requerendo o mínimo número esforço possível por parte do utilizador. Para alcançar os objectivos estipulados, este projecto recorre a técnicas de mineração de texto, em especial categorização automática de texto, e aprendizagem activa. Para reduzir a necessidade de inquirir o utilizador – para etiquetar exemplos de acordo com as categorias desejadas – foi utilizado o algoritmo d-confidence. Processo de organização automática de emails O processo de organizar automaticamente emails é desenvolvido em três fases distintas: indexação, classificação e avaliação. Na primeira fase, fase de indexação, os emails passam por um processo transformativo de limpeza que visa essencialmente gerar uma representação dos emails adequada ao processamento automático. A segunda fase é a fase de classificação. Esta fase recorre ao conjunto de dados resultantes da fase anterior para produzir um modelo de classificação, aplicando-o posteriormente a novos emails. Partindo de uma matriz onde são representados emails, termos e os seus respectivos pesos, e um conjunto de exemplos classificados manualmente, um classificador é gerado a partir de um processo de aprendizagem. O classificador obtido é então aplicado ao conjunto de emails e a classificação de todos os emails é alcançada. O processo de classificação é feito com base num classificador de máquinas de vectores de suporte recorrendo ao algoritmo de aprendizagem activa d-confidence. O algoritmo d-confidence tem como objectivo propor ao utilizador os exemplos mais significativos para etiquetagem. Ao identificar os emails com informação mais relevante para o processo de aprendizagem, diminui-se o número de iterações e consequentemente o esforço exigido por parte dos utilizadores. A terceira e última fase é a fase de avaliação. Nesta fase a performance do processo de classificação e a eficiência do algoritmo d-confidence são avaliadas. O método de avaliação adoptado é o método de validação cruzada denominado 10-fold cross validation. Conclusões O processo de organização automática de emails foi desenvolvido com sucesso, a performance do classificador gerado e do algoritmo d-confidence foi relativamente boa. Em média as categorias apresentam taxas de erro relativamente baixas, a não ser as classes mais genéricas. O esforço exigido pelo utilizador foi reduzido, já que com a utilização do algoritmo d-confidence obteve-se uma taxa de erro próxima do valor final, mesmo com um número de casos etiquetados abaixo daquele que é requerido por um método supervisionado. É importante salientar, que além do processo automático de organização de emails, este projecto foi uma excelente oportunidade para adquirir conhecimento consistente sobre mineração de texto e sobre os processos de classificação automática e recuperação de informação. O estudo de áreas tão interessantes despertou novos interesses que consistem em verdadeiros desafios futuros.

Reliability of a questionnaire on substance use among adolescent students, Brazil

OBJECTIVE: To analyze reliability of a self-applied questionnaire on substance use and misuse among adolescent students. METHODS: Two cross-sectional studies were carried out for the instrument test-retest. The sample comprised male and female students aged 1119 years from public and private schools (elementary, middle, and high school students) in the city of Salvador, Northeastern Brazil, in 2006. A total of 591 questionnaires were applied in the test and 467 in the retest. Descriptive statistics, the Kappa index, Cronbach's alpha and intraclass correlation were estimated. RESULTS: The prevalence of substance use/misuse was similar in both test and retest. Sociodemographic variables showed a "moderate" to "almost perfect" agreement for the Kappa index, and a "satisfactory" (>0.75) consistency for Cronbach's alpha and intraclass correlation. The age which psychoactive substances (tobacco, alcohol, and cannabis) were first used and chronological age were similar in both studies. Test-retest reliability was found to be a good indicator of students' age of initiation and their patterns of substance use. CONCLUSIONS: The questionnaire reliability was found to be satisfactory in the population studied.

Automatic synthesis of VHDL Hardware Components from IOPT Petri Net models

Conferência: 39th Annual Conference of the IEEE Industrial-Electronics-Society (IECON), Vienna, Austria, Nov 10-14, 2013

Yellow fever in Brazil: thoughts and hypotheses on the emergence in previously free areas

This article describes and discusses factors associated to the reemergence of yellow fever and its transmission dynamics in the states of São Paulo (Southeastern Brazil) and Rio Grande do Sul (Southern) during 2008 and 2009. The following factors have played a pivotal role for the reemergence of yellow fever in these areas: large susceptible human population; high prevalence of vectors and primary hosts (non-human primates); favorable climate conditions, especially increased rainfall; emergence of a new genetic lineage; and circulation of people and/or monkeys infected by virus. There is a need for an effective surveillance program to prevent the reemergence of yellow fever in other Brazilian states.

Automatic diagnosis of liver steatosis by ultrasound using autoregressive tissue characterization

Liver steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles. Today, the assessment is subjectively performed by visual inspection. Here a classifier based on features extracted from ultrasound (US) images is described for the automatic diagnostic of this phatology. The proposed algorithm estimates the original ultrasound radio-frequency (RF) envelope signal from which the noiseless anatomic information and the textural information encoded in the speckle noise is extracted. The features characterizing the textural information are the coefficients of the first order autoregressive model that describes the speckle field. A binary Bayesian classifier was implemented and the Bayes factor was calculated. The classification has revealed an overall accuracy of 100%. The Bayes factor could be helpful in the graphical display of the quantitative results for diagnosis purposes.

Orchestration of e-learning services for automatic evaluation of programming exercises

Managing programming exercises require several heterogeneous systems such as evaluation engines, learning objects repositories and exercise resolution environments. The coordination of networks of such disparate systems is rather complex. These tools would be too specific to incorporate in an e-Learning platform. Even if they could be provided as pluggable components, the burden of maintaining them would be prohibitive to institutions with few courses in those domains. This work presents a standard based approach for the coordination of a network of e-Learning systems participating on the automatic evaluation of programming exercises. The proposed approach uses a pivot component to orchestrate the interaction among all the systems using communication standards. This approach was validated through its effective use on classroom and we present some preliminary results.

Teste de Morisky-Green e Brief Medication Questionnaire para avaliar adesão a medicamentos

OBJETIVO: Analisar a confiabilidade e o desempenho da versão em português de instrumentos de avaliação da adesão ao tratamento anti-hipertensivo. MÉTODOS: Pacientes hipertensos atendidos de janeiro a setembro de 2010 em uma unidade de atenção primária em Porto Alegre, RS, foram selecionados aleatoriamente (n = 206). Na avaliação da adesão foram utilizadas versões em português do Teste de Morisky-Green (TMG) e do Brief Medication Questionnaire (BMQ). Foram analisados consistência interna, estabilidade temporal e desempenho com relação a três padrões-ouro: controle inadequado da pressão arterial (> 140/90 mmHg); taxa insuficiente de retirada de medicação na farmácia da Unidade Básica de Saúde (< 80%); e a combinação de ambos. RESULTADOS: Dos pacientes avaliados, 97 utilizavam medicamentos dispensados somente pela farmácia da Unidade Básica de Saúde. Os testes apresentaram boa consistência interna: BMQ α de Cronbach de 0,66 (IC95% 0,60;0,73) e o TMG 0,73 (IC95% 0,67;0,79). O desempenho do BMQ no domínio regime apresentou sensibilidade de 77%, especificidade de 58% e área sob a curva ROC de 0,70 (IC95% 0,55;0,86), e o TMG sensibilidade de 61%, especificidade de 36% e área sob a curva ROC de 0,46 (IC95% 0,30;0,62). A correlação entre o BMQ e o TMG foi de r = 0,28, p > 0,001. A baixa adesão ao BMQ está associada a maiores níveis tensionais quando comparada com pacientes aderentes (148,4 [dp 20,1] vs 128,8 [dp 17,8], p < 0,001), mas não para o TMG. CONCLUSÕES: O BMQ apresentou melhor desempenho que o TMG, com maiores sensibilidade e especificidade. A avaliação da adesão pode auxiliar o clinico na discriminação entre uso inadequado da medicação e esquema terapêutico insuficiente.

On the development of an automatic voice pleasantness classification and intensity estimation system

In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

Integration of an automatic storage and retrieval system (ASRS) in a discrete-part automation system

This technical report describes the work carried out in a project within the ERASMUS programme. The objective of this project was the Integration of an Automatic Warehouse in a Discrete-Part Automation System. The discrete-part automation system located at the LASCRI (Critical Systems) laboratory at ISEP was extended with automatic storage and retrieval of the manufacturing parts, through the integration of an automatic warehouse and an automatic guided vehicle (AGV).

Adaptação cultural da versão brasileira do Godin-Shephard Leisure-Time Physical Activity Questionnaire

OBJETIVO: Realizar adaptação cultural para versão brasileira do questionário de atividade física no tempo de lazer e avaliar a validade de conteúdo, praticabilidade, aceitabilidade e confiabilidade.MÉTODOS: Foram realizadas as etapas de tradução, síntese, retrotradução, avaliação por comitê de especialistas e pré-teste, seguidos pela avaliação da praticabilidade, aceitabilidade e confiabilidade (teste-reteste). Os juízes avaliaram as equivalências semântico-idiomática, conceitual, cultural e metabólica. A versão adaptada foi submetida ao pré-teste (n = 20) e teste-reteste (n = 80) em indivíduos saudáveis e pacientes com doenças cardiovasculares, em Limeira, SP, entre 2010 e 2011. A proporção de concordância do comitê de juízes foi quantificada por meio do Índice de Validade de Conteúdo. A confiabilidade foi avaliada segundo critério de estabilidade, com intervalo de 15 dias entre as aplicações, a praticabilidade pelo tempo gasto na entrevista e a aceitabilidade pelo percentual de itens não respondidos e proporção de pacientes que responderam a todos os itens.RESULTADOS: A versão traduzida do questionário apresentou equivalências semântico-idiomática, conceitual, cultural e metabólica adequadas, com substituição de algumas atividades físicas mais adequadas para a população brasileira. A análise da praticabilidade evidenciou curto tempo de aplicação do instrumento (média de 3,0 min). Quanto à aceitabilidade, todos os pacientes responderam a 100% dos itens. A análise do teste-reteste sugeriu estabilidade temporal do instrumento (Índice de Correlação Intraclasse = 0,84).CONCLUSÕES: A versão brasileira do questionário apresentou propriedades de medida satisfatórias. Recomenda-se sua aplicação a populações diversas em estudos futuros, a fim de disponibilizar propriedades de medida robustas.

Demo: automatic personal identification system for security in critical services: a case study

The demonstration proposal moves from the capabilities of a wireless biometric badge [4], which integrates a localization and tracking service along with an automatic personal identification mechanism, to show how a full system architecture is devised to enable the control of physical accesses to restricted areas. The system leverages on the availability of a novel IEEE 802.15.4/Zigbee Cluster Tree network model, on enhanced security levels and on the respect of all the users' privacy issues.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Automatic tunning of Okumura-Hata model on railway communications

This paper presents the Genetic Algorithms (GA) as an efficient solution for the Okumura-Hata prediction model tuning on railways communications. A method for modelling the propagation model tuning parameters was presented. The algorithm tuning and validation were based on real networks measurements carried out on four different propagation scenarios and several performance indicators were used. It was shown that the proposed GA is able to produce significant improvements over the original model. The algorithm developed is currently been used on real GSM-R network planning process for an enhanced resources usage.