Mobile and web tools for participative learning

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, para a obtenção do grau de Mestre em Engenharia Informática

Anthropocentric-based robotic and autonomous systems: assessment for new organisational options

Text based on the paper presented at the Conference "Autonomous systems: inter-relations of technical and societal issues" held at Monte de Caparica (Portugal), Universidade Nova de Lisboa, November, 5th and 6th 2009 and organized by IET-Research Centre on Enterprise and Work Innovation

O financiamento por capitação ajustada pelo risco em contexto de integração vertical de cuidados de saúde : a utilização dos consumos com medicamentos como proxy da carga de doença em ambulatório

RESUMO - Introdução - Com o presente projecto de investigação pretendeu-se estudar o financiamento por capitação ajustado pelo risco em contexto de integração vertical de cuidados de saúde, recorrendo particularmente a informação sobre o consumo de medicamentos em ambulatório como proxy da carga de doença. No nosso país, factores como a expansão de estruturas de oferta verticalmente integradas, inadequação histórica da sua forma de pagamento e a recente possibilidade de dispor de informação sobre o consumo de medicamentos de ambulatório em bases de dados informatizadas são três fortes motivos para o desenvolvimento de conhecimento associado a esta temática. Metodologia - Este trabalho compreende duas fases principais: i) a adaptação e aplicação de um modelo de consumo de medicamentos que permite estimar a carga de doença em ambulatório (designado de PRx). Nesta fase foi necessário realizar um trabalho de selecção, estruturação e classificação do modelo. A sua aplicação envolveu a utilização de bases de dados informatizadas de consumos com medicamentos nos anos de 2007 e 2008 para a região de Saúde do Alentejo; ii) na segunda fase foram simulados três modelos de financiamento alternativos que foram propostos para financiar as ULS em Portugal. Particularmente foram analisadas as dimensões e variáveis de ajustamento pelo risco (índices de mortalidade, morbilidade e custos per capita), sua ponderação relativa e consequente impacto financeiro. Resultados - Com o desenvolvimento do modelo PRx estima-se que 36% dos residentes na região Alentejo têm pelo menos uma doença crónica, sendo a capacidade de estimação do modelo no que respeita aos consumos de medicamentos na ordem dos 0,45 (R2). Este modelo revelou constituir uma alternativa a fontes de informação tradicionais como são os casos de outros estudos internacionais ou o Inquérito Nacional de Saúde. A consideração dos valores do PRx para efeitos de financiamento per capita introduz alterações face a outros modelos propostos neste âmbito. Após a análise dos montantes de financiamento entre os cenários alternativos, obtendo os modelos 1 e 2 níveis de concordância por percentil mais próximos entre si comparativamente ao modelo 3, seleccionou-se o modelo 1 como o mais adequado para a nossa realidade. Conclusão - A aplicação do modelo PRx numa região de saúde permitiu concluir em função dos resultados alcançados, que já existe a possibilidade de estruturação e operacionalização de um modelo que permite estimar a carga de doença em ambulatório a partir de informação relativa ao seu perfil de consumo de medicamentos dos utentes. A utilização desta informação para efeitos de financiamento de organizações de saúde verticalmente integradas provoca uma variação no seu actual nível de financiamento. Entendendo este estudo como um ponto de partida onde apenas uma parte da presente temática ficará definida, outras questões estruturantes do actual sistema de financiamento não deverão também ser olvidadas neste contexto. ------- ABSTRACT - Introduction - The main goal of this study was the development of a risk adjustment model for financing integrated delivery systems (IDS) in Portugal. The recent improvement of patient records, mainly at primary care level, the historical inadequacy of payment models and the increasing number of IDS were three important factors that drove us to develop new approaches for risk adjustment in our country. Methods - The work was divided in two steps: the development of a pharmacy-based model in Portugal and the proposal of a risk adjustment model for financing IDS. In the first step an expert panel was specially formed to classify more than 33.000 codes included in Portuguese pharmacy national codes into 33 chronic conditions. The study included population of Alentejo Region in Portugal (N=441.550 patients) during 2007 and 2008. Using pharmacy data extracted from three databases: prescription, private pharmacies and hospital ambulatory pharmacies we estimated a regression model including Potential Years of Life Lost, Complexity, Severity and PRx information as dependent variables to assess total cost as the independent variable. This healthcare financing model was compared with other two models proposed for IDS. Results - The more prevalent chronic conditions are cardiovascular (34%), psychiatric disorders (10%) and diabetes (10%). These results are also consistent with the National Health Survey. Apparently the model presents some limitations in identifying patients with rheumatic conditions, since it underestimates prevalence and future drug expenditure. We obtained a R2 value of 0,45, which constitutes a good value comparing with the state of the art. After testing three scenarios we propose a model for financing IDS in Portugal. Conclusion - Drug information is a good alternative to diagnosis in determining morbidity level in a population basis through ambulatory care data. This model offers potential benefits to estimate chronic conditions and future drug costs in the Portuguese healthcare system. This information could be important to resource allocation decision process, especially concerning risk adjustment and healthcare financing.

Adapter module for self-learning production systems

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica, Sistemas e Computadores

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.

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.

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

Learning to manage in knowledge-based organizations: the role of learning logs or portfolios

Paper presented at the 8th European Conference on Knowledge Management, Barcelona, 6-7 Sep. 2008 URL: http://www.academic-conferences.org/eckm/eckm2007/eckm07-home.htm

The role of lifelong learning (LLL) in the creation of a european knowledge- based society

This chapter appears in Encyclopaedia of Human Resources Information Systems: Challenges in e-HRM edited by Torres-Coronas, T. and Arias-Oliva, M. Copyright 2009, IGI Global, www.igi-global.com. Posted by permission of the publisher. URL:http://www.igi-pub.com/reference/details.asp?id=7737

Models and tools for value systems analysis in collaborative environments

Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative Networks

Recommending media content based on machine learning methods

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Cluster Turismo Sustentável em Áreas Protegidas: o caso do Alente

Local Tourist Systems (LTS) can be analyzed according to an investigation structure that derives from industrial economics on industrial districts, local productive systems or learning regions. LTS concept is a useful analytical tool that can seize the resorts diversity and organization. Resorts can be conceived both as clusters or industrial districts, either with a perfect agreement between productive sphere and local community or a mere industrial juxtaposition without any economic or social connection. On the other hand tourist clusters analysis has cross referred almost exclusively to socio-economic criteria. Environmental issues were almost disregarded. Approaches swing from the “greening” of products and practices to initiatives focused on an integrated approach, linking environment and tourist development. This paper tries to discuss how to favor – inside a tourist destination - the creation of clusters grounded on sustainable tourism. The case studies (the 5 Alentejo Natural Reserves: Estuário do Sado; Lagoas de Santo André e da Sancha; Vale do Guadiana; Sudoeste Alentejano e Costa Vicentina; Serra de S. Mamede) are analyzed under the light of how microstructures groups can allow a territorial sustainable tourist development. The issues of “resources and competences” and “governance” ar

Municipal solid waste management system: decision support through systems analysis

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Engineering

Learning networks and moodle use in online courses: a social network analysis study

Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação

Internationalization process: GuestCentric Systems Embracing People‟s Republic of China

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics