Elaboração e aplicação de um Programa de Treino aos alunos do 2º ano de Dança, da Academia de Dança do Vale do Sousa, com vista à realização do exame de Grau 5 da Royal Academy of Dance

Relatório Final de Estágio apresentado à Escola Superior de Dança, com vista à obtenção do grau de Mestre em Ensino de Dança.

Estudo exploratório : as estratégias motivacionais no ensino da técnica da dança clássica, para alunos do 3º ano, no Ginasiano Escola de Dança

Relatório Final de Estágio apresentado à Escola Superior de Dança, com vista à obtenção do grau de Mestre em Ensino de Dança.

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.

A comprehensive simulation study of slotted CSMA/CA for IEEE 802.15.4 wireless sensor networks

In this paper, we analyze the performance limits of the slotted CSMA/CA mechanism of IEEE 802.15.4 in the beacon-enabled mode for broadcast transmissions in WSNs. The motivation for evaluating the beacon-enabled mode is due to its flexibility for WSN applications as compared to the non-beacon enabled mode. Our analysis is based on an accurate simulation model of the slotted CSMA/CA mechanism on top of a realistic physical layer, with respect to the IEEE 802.15.4 standard specification. The performance of the slotted CSMA/CA is evaluated and analyzed for different network settings to understand the impact of the protocol attributes (superframe order, beacon order and backoff exponent) on the network performance, namely in terms of throughput (S), average delay (D) and probability of success (Ps). We introduce the concept of utility (U) as a combination of two or more metrics, to determine the best offered load range for an optimal behavior of the network. We show that the optimal network performance using slotted CSMA/CA occurs in the range of 35% to 60% with respect to an utility function proportional to the network throughput (S) divided by the average delay (D).

On the performance limits of slotted CSMA/CA in IEEE 802.15.4 for broadcast transmissions in wireless sensor networks

The IEEE 802.15.4 has been adopted as a communication protocol standard for Low-Rate Wireless Private Area Networks (LRWPANs). While it appears as a promising candidate solution for Wireless Sensor Networks (WSNs), its adequacy must be carefully evaluated. In this paper, we analyze the performance limits of the slotted CSMA/CA medium access control (MAC) mechanism in the beacon-enabled mode for broadcast transmissions in WSNs. The motivation for evaluating the beacon-enabled mode is due to its flexibility and potential for WSN applications as compared to the non-beacon enabled mode. Our analysis is based on an accurate simulation model of the slotted CSMA/CA mechanism on top of a realistic physical layer, with respect to the IEEE 802.15.4 standard specification. The performance of the slotted CSMA/CA is evaluated and analyzed for different network settings to understand the impact of the protocol attributes (superframe order, beacon order and backoff exponent), the number of nodes and the data frame size on the network performance, namely in terms of throughput (S), average delay (D) and probability of success (Ps). We also analytically evaluate the impact of the slotted CSMA/CA overheads on the saturation throughput. We introduce the concept of utility (U) as a combination of two or more metrics, to determine the best offered load range for an optimal behavior of the network. We show that the optimal network performance using slotted CSMA/CA occurs in the range of 35% to 60% with respect to an utility function proportional to the network throughput (S) divided by the average delay (D).

Chronic use of benzodiazepines among older adults

OBJECTIVE To analyze the perception of and motivation for the chronic use of benzodiazepine among older adults. METHODS A qualitative study was conducted on 22 older adults living in Bambuí, MG, Southeastern Brazil, who were taking benzodiazepines and had the clinical and cognitive ability to respond to interview questions. The collected data were analyzed on the basis of the “signs, meanings, and actions” model. RESULTS The main reasons pointed out for the use of benzodiazepines were “nervousness”, “sleep problems”, and “worry” due to family and financial problems, everyday problems, and existential difficulties. None of the interviewees said that they used benzodiazepines in a dose higher than that recommended or had been warned by health professionals about any risks of their continuous use. Different strategies were used to obtain the prescription for the medication, and any physician would prescribe it, indicating that a bond was established with the drug and not with the health professional or healthcare service. Obtaining and consuming the medication turned into a crucial issue because benzodiazepine assumes the status of an essential food, which leads users to not think but sleep. It causes a feeling of relief from their problems such as awareness of human finitude and fragility, existential difficulties, and family problems. CONCLUSIONS Benzodiazepine assumes the characteristics of polyvalence among older adults, which extrapolate specific clinical indications, and of essentiality to deal with life’s problems in old age. Although it relieves the “nerves”, the chronic use of benzodiazepines buffers suffering and prevents older adults from going through the suffering. This shows important difficulties in the organization and planning of strategies that are necessary for minimizing the chronic use in this population.

Digital serious games and simulation games - comparison of two approaches to lean training

In an increasingly competitive and globalized world, companies need effective training methodologies and tools for their employees. However, selecting the most suitable ones is not an easy task. It depends on the requirements of the target group (namely time restrictions), on the specificities of the contents, etc. This is typically the case for training in Lean, the waste elimination manufacturing philosophy. This paper presents and compares two different approaches to lean training methodologies and tools: a simulation game based on a single realistic manufacturing platform, involving production and assembly operations that allows learning by playing; and a digital game that helps understand lean tools. This paper shows that both tools have advantages in terms of trainee motivation and knowledge acquisition. Furthermore, they can be used in a complementary way, reinforcing the acquired knowledge.

Estudo de um método de avaliação de desempenho aplicado aos técnicos de radiologia do Hospital Curry Cabral

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde

Políticas e modelos de gestão em unidades de fisioterapia: estratégias para a mudança

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde

Factors associated with dietary supplement use by people who exercise at gyms

OBJECTIVE To assess the factors associated with the use of dietary supplements by people who exercise at gyms.METHODS A cross-sectional study with a sample defined by convenience, considering the number of gyms registered in the Conselho Regional de Educação Física (Regional Council of Physical Education) of Sao Luis, MA, Northeastern Brazil, from July 2011 to July 2012. The final sample comprised 723 individuals who exercise at gyms. The dependent variable was supplement use, and the explanatory variables were length of time and motivation of the physical exercises, duration, goal and self-perception of training, weekly frequency of gym attendance, sex, age, educational attainment, self-perception of body weight, smoking and self-perception of diet. The association between variables was analysed by hierarchical Poisson regression based on a theoretical model.RESULTS Supplement use was reported by 64.7% of the participants. Most of the sample was male (52.6%). The most frequent age group was 20 to 39 years (74.4%). Most participants (46.1%) had been exercising for over a year. The following variables were associated with supplement use: self-perceiving body weight as below ideal (p < 0.001), smoking (p < 0.001), exercising for 7 to 12 months (p = 0.028) or more than one year (p < 0.001), spending more than two hours at the gym (p = 0.051), and perceiving training as moderate (p = 0.024) or intense (p = 0.001).CONCLUSIONS The use of supplements lacks proper professional guidance, being motivated by individuals unsatisfied with their low body weight and who perceive their workout as intense, which raises the need for monitoring this population.

Using the TRAILER tool for managing informal learning in academic and professional contexts: the learner perspective

Informal Learning plays an important role in everyone's life and yet we often are unaware of it. The need to keep track of the knowledge acquired through informal learning is increasing as its sources become increasingly diverse. This paper presents a study on a tool developed to help keeping track of learners' informal learning, both within academic and professional contexts, This tool, developed within the European Commission funded TRAILER project, will further integrate the improvements suggested by users during the piloting phase. The two studied contexts were similar regarding the importance and perception of Informal Learning, but differed concerning tool usage. The overall idea of managing one's informal learning was well accepted and welcomed, which validated the emerging need for a tool with this purpose.

Managing Informal Learning in professional contexts: the learner’s perspective

Informal Learning is present in everyone's life but its awareness only recently has been reported. The need to keep track of the knowledge acquired this way is increasing as its sources diversity also increases. This work presents the pilots trials on the use of a tool developed to help keeping track of the learners’ informal learning, within a number of companies spread out in three countries. This tool developed through the European Commission funded project TRAILER, is still under development, which will allow integrating the set of improving suggestions obtained from users during the piloting phase. The overall idea of managing one’s informal learning was well accepted and welcomed, which validated the emerging need for a tool with this purpose.

Derivation methods for hybrid knowledge bases with rules and ontologies

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Learning with tangible interfaces

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Aplicação de metodologias Lean ao fabrico de elevadores

Num mercado cada vez mais competitivo, torna-se fundamental para as empresas produzirem mais com menos recursos, aumentando a eficiência interna, através da otimização dos seus processos. Neste contexto aparece o Lean Manufacturing, metodologia que tem como objetivo criar valor para os stakeholders, através da eliminação de desperdício na cadeia de valor. Este projeto descreve a análise e a formulação de soluções do processo de produção de um Módulo de Serviço, produto que faz parte do sistema elétrico de um elevador. Para análise do problema utilizamos técnicas e ferramentas lean, tais como, o value stream mapping (VSM), o diagrama de processo e o diagrama de spaghetti. Para formulação do problema usamos o value stream design (VSD), a metodologia 5S, o sistema Kanban e a criação de fluxo contínuo, através do conceito takt time, do sistema Pull, da definição do processo pacemaker, da programação nivelada (Heijunka), do conceito pitch time e da caixa de nivelamento (Heijunka Box). Com este projeto pretendemos demonstrar que a implementação de um fluxo unitário de peças através da filosofia Lean Manufacturing, acrescenta qualidade ao produto, cria flexibilidade, aumenta a produtividade, liberta áreas de produção, aumenta a segurança, reduz o custo com o stock e aumenta a motivação organizacional.