What parental cognitive dimensions are important to understand children’s eating habits?

Obesidade é uma preocupação de saúde pública. Objetivos OMS - Redução a zero da taxa de crescimento da obesidade e uma redução em 10% na prevalência de atividade física insuficiente. Em Portugal, os estudos de prevalência apontam para valores entre 24% e os 34% de crianças e jovens pré-obesos e obesos. Extensa confirmação da obesidade infantil como preditor da obesidade na idade adulta. Em alguns países há indicadores de que a taxa de obesidade infantil começa a ter uma ligeira diminuição, provavelmente fruto de intervenções no macrosistema. Necessidade de intervenção direta nos microssistemas familiar e escolar da criança para uma intervenção mais abrangente e eficaz. Existe um ampla confirmação da influência parental nos comportamentos alimentares da criança. Os comportamentais parentais relacionados com a alimentação da criança são influenciados por variáveis cognitivas parentais. A maioria dos pais de crianças com excesso de peso subavalia o peso do seu filho, mas não de outras crianças. Os pais das crianças pré-escolares distorcem mais o peso do que os pais de crianças mais velhas. Os pais com uma perceção correta utilizam mais estratégias de restrição alimentar.

Promoção da auto-eficácia parental para a alimentação saudável infantil: áreas de intervenção

Barreiras parentais à alimentação saudável: 1) intrapessoais (relacionadas com a criança preferências alimentares; o estado de saúde; dificuldades de mudança de hábitos; relacionadas com os pais: baixo controlo; baixa auto-eficácia; stress parental); 2) interpessoais (comportamento da criança às refeições; estrutura da família; influências dos pares e de outros familiares; tempo disponível); 3) ambientais (escola; recursos financeiros; tempo disponível). Objetivos do estudo: identificação das barreiras percecionadas pelos pais a uma alimentação saudável da criança; identificar as estratégias de confronto que os pais utilizam para lidar com estas barreiras; identificar as diferenças das barreiras e estratégias utilizadas ao longo do desenvolvimento da criança; avaliar o grau de eficácia atribuído às estratégias utilizadas.

Sustainable Tourism and Agriculture Multifunctionality by PAR: A Variable Selection Approach

Copyright © 2013 Springer Netherlands.

Data analysis model selection for estimating local population size of the Risso’s dolphin (Grampus griseus) in the Azores

27th Annual Conference of the European Cetacean Society. Setúbal, Portugal, 8-10 April 2013.

Envolvimento parental nas classes populares e papel do diretor de turma

Mestrado em Educação, especialidade de Administração e Organização Escolar.

Bem te Quero : da educação parental à promoção dos direitos da criança

Trabalho apresentado em XIII Congreso Internacional Galego-Portugués de Psicopedagoxía, Área 5 Familia, Escuela y Comunidad. Universidad da Coruña, 2 de Setembro de 2015.

Por uma família participativa: estratégias e propostas de atividade para o envolvimento parental

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

O envolvimento parental: partilhar vivências e experiências

Relatório da Prática Profissional Supervisionada Mestrado em Educação Pré-Escolar

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

QoS-based surrogates selection and service proposal formulation in offloading environments

Resource constraints are becoming a problem as many of the wireless mobile devices have increased generality. Our work tries to address this growing demand on resources and performance, by proposing the dynamic selection of neighbor nodes for cooperative service execution. This selection is in uenced by user's quality of service requirements expressed in his request, tailoring provided service to user's speci c needs. In this paper we improve our proposal's formulation algorithm with the ability to trade o time for the quality of the solution. At any given time, a complete solution for service execution exists, and the quality of that solution is expected to improve overtime.

Formação de adultos e cidadania: repensar as práticas de envolvimento parental na escola

Dissertação de mestrado em Ciências da Educação: área de Educação e Desenvolvimento

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

Supplier's selection model based on an empirical study

The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, there were identified five broad selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. After the identification criteria, a survey was elaborated and companies were contacted in order to understand which factors have more weight in their decisions to choose the partners. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Value Analysis. The goal of the paper it's to supply a selection reference model that can represent an orientation/pattern for a decision making on the suppliers/partners selection process

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.

Analysis of the domain of applicability of an algorithm for a resources system selection problem for Distributed/Agile/Virtual Enterprises integration

The process of resources systems selection takes an important part in Distributed/Agile/Virtual Enterprises (D/A/V Es) integration. However, the resources systems selection is still a difficult matter to solve in a D/A/VE, as it is pointed out in this paper. Globally, we can say that the selection problem has been equated from different aspects, originating different kinds of models/algorithms to solve it. In order to assist the development of a web prototype tool (broker tool), intelligent and flexible, that integrates all the selection model activities and tools, and with the capacity to adequate to each D/A/V E project or instance (this is the major goal of our final project), we intend in this paper to show: a formulation of a kind of resources selection problem and the limitations of the algorithms proposed to solve it. We formulate a particular case of the problem as an integer programming, which is solved using simplex and branch and bound algorithms, and identify their performance limitations (in terms of processing time) based on simulation results. These limitations depend on the number of processing tasks and on the number of pre-selected resources per processing tasks, defining the domain of applicability of the algorithms for the problem studied. The limitations detected open the necessity of the application of other kind of algorithms (approximate solution algorithms) outside the domain of applicability founded for the algorithms simulated. However, for a broker tool it is very important the knowledge of algorithms limitations, in order to, based on problem features, develop and select the most suitable algorithm that guarantees a good performance.