Dynamic adaptation of interaction models for stateful web services

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Microscopy image segmentation by active contour models

In this thesis a semi-automated cell analysis system is described through image processing. To achieve this, an image processing algorithm was studied in order to segment cells in a semi-automatic way. The main goal of this analysis is to increase the performance of cell image segmentation process, without affecting the results in a significant way. Even though, a totally manual system has the ability of producing the best results, it has the disadvantage of taking too long and being repetitive, when a large number of images need to be processed. An active contour algorithm was tested in a sequence of images taken by a microscope. This algorithm, more commonly known as snakes, allowed the user to define an initial region in which the cell was incorporated. Then, the algorithm would run several times, making the initial region contours to converge to the cell boundaries. With the final contour, it was possible to extract region properties and produce statistical data. This data allowed to say that this algorithm produces similar results to a purely manual system but at a faster rate. On the other hand, it is slower than a purely automatic way but it allows the user to adjust the contour, making it more versatile and tolerant to image variations.

Participatory Surveillance and Mathematical Models in Epidemiologic Research: Successes and Challenges

Theoretical epidemiology aims to understand the dynamics of diseases in populations and communities. Biological and behavioral processes are abstracted into mathematical formulations which aim to reproduce epidemiological observations. In this thesis a new system for the self-reporting of syndromic data — Influenzanet — is introduced and assessed. The system is currently being extended to address greater challenges of monitoring the health and well-being of tropical communities.(...)

Learning Activities with Semantic. Hypermedia in Higher Education

The increasing use of information and communication technologies (ICT) in diverse professional and personal contexts calls for new knowledge, and a set of abilities, competences and attitudes, for an active and participative citizenship. In this context it is acknowledged that universities have an important role innovating in the educational use of digital media to promote an inclusive digital literacy. The educational potential of digital technologies and resources has been recognized by both researchers and practitioners. Multiple pedagogical models and research approaches have already contributed to put in evidence the importance of adapting instructional and learning practices and processes to concrete contexts and educational goals. Still, academic and scientific communities believe further investments in ICT research is needed in higher education. This study focuses on educational models that may contribute to support digital technology uses, where these can have cognitive and educational relevance when compared to analogical technologies. A teaching and learning model, centered in the active role of the students in the exploration, production, presentation and discussion of interactive multimedia materials, was developed and applied using the internet and exploring emergent semantic hypermedia formats. The research approach focused on the definition of design principles for developing class activities that were applied in three different iterations in undergraduate courses from two institutions, namely the University of Texas at Austin, USA and the University of Lisbon, Portugal. The analysis of this study made possible to evaluate the potential and efficacy of the model proposed and the authoring tool chosen in the support of metacognitive skills and attitudes related to information structuring and management, storytelling and communication, using computers and the internet.

Amyotrophic Lateral Sclerosis:Mammalian Cell Models,Copper-Zinc Superoxide Dismutaseand Biological Characteristics

"Amyotrophic Lateral Sclerosis (ALS) is the most severe and common adult onset disorder that affects motor neurons in the spinal cord, brainstem and cortex, resulting in progressive weakness and death from respiratory failure within two to five years of symptoms onset(...)

Enterprise reference lexicon building from business models

Nowadays, a significant increase on the demand for interoperable systems for exchanging data in business collaborative environments has been noticed. Consequently, cooperation agreements between each of the involved enterprises have been brought to light. However, due to the fact that even in a same community or domain, there is a big variety of knowledge representation not semantically coincident, which embodies the existence of interoperability problems in the enterprises information systems that need to be addressed. Moreover, in relation to this, most organizations face other problems about their information systems, as: 1) domain knowledge not being easily accessible by all the stakeholders (even intra-enterprise); 2) domain knowledge not being represented in a standard format; 3) and even if it is available in a standard format, it is not supported by semantic annotations or described using a common and understandable lexicon. This dissertation proposes an approach for the establishment of an enterprise reference lexicon from business models. It addresses the automation in the information models mapping for the reference lexicon construction. It aggregates a formal and conceptual representation of the business domain, with a clear definition of the used lexicon to facilitate an overall understanding by all the involved stakeholders, including non-IT personnel.

Learning facial-expression models with crowdsourcing

The computational power is increasing day by day. Despite that, there are some tasks that are still difficult or even impossible for a computer to perform. For example, while identifying a facial expression is easy for a human, for a computer it is an area in development. To tackle this and similar issues, crowdsourcing has grown as a way to use human computation in a large scale. Crowdsourcing is a novel approach to collect labels in a fast and cheap manner, by sourcing the labels from the crowds. However, these labels lack reliability since annotators are not guaranteed to have any expertise in the field. This fact has led to a new research area where we must create or adapt annotation models to handle these weaklylabeled data. Current techniques explore the annotators’ expertise and the task difficulty as variables that influences labels’ correction. Other specific aspects are also considered by noisy-labels analysis techniques. The main contribution of this thesis is the process to collect reliable crowdsourcing labels for a facial expressions dataset. This process consists in two steps: first, we design our crowdsourcing tasks to collect annotators labels; next, we infer the true label from the collected labels by applying state-of-art crowdsourcing algorithms. At the same time, a facial expression dataset is created, containing 40.000 images and respective labels. At the end, we publish the resulting dataset.

Real-time collaborative editing of OutSystems DSL models

Real-time collaborative editing systems are common nowadays, and their advantages are widely recognized. Examples of such systems include Google Docs, ShareLaTeX, among others. This thesis aims to adopt this paradigm in a software development environment. The OutSystems visual language lends itself very appropriate to this kind of collaboration, since the visual code enables a natural flow of knowledge between developers regarding the developed code. Furthermore, communication and coordination are simplified. This proposal explores the field of collaboration on a very structured and rigid model, where collaboration is made through the copy-modify-merge paradigm, in which a developer gets its own private copy from the shared repository, modifies it in isolation and later uploads his changes to be merged with modifications concurrently produced by other developers. To this end, we designed and implemented an extension to the OutSystems Platform, in order to enable real-time collaborative editing. The solution guarantees consistency among the artefacts distributed across several developers working on the same project. We believe that it is possible to achieve a much more intense collaboration over the same models with a low negative impact on the individual productivity of each developer.

eHealth e a adoção da inovação em assisted living technologies : o caso das demências

RESUMO - Assistimos hoje a um contexto marcado (i) pelo progressivo envelhecimento das sociedades ocidentais, (ii) pelo aumento da prevalência das doenças crónicas, de que as demências são um exemplo, (iii) pelo significativo aumento dos custos associados a estas patologias, (iv) por orçamentos públicos fortemente pressionadas pelo controlo da despesa, (v) por uma vida moderna que dificulta o apoio intergeracional, tornando o suporte proporcionado pelos filhos particularmente difícil, (vi) por fortes expectativas relativamente à prestação de cuidados de saúde com qualidade. Teremos assim de ser capazes de conseguir melhorar os serviços de saúde, ao mesmo tempo que recorremos a menos recursos financeiros e humanos, pelo que a inovação parece ser crítica para a sustentabilidade do sistema. Contudo a difusão das Assistive Living Technologies, apesar do seu potencial, tem sido bastante baixa, nomeadamente em Portugal. Porquê? Hamer, Plochg e Moreira (2012), no editorial do International Journal of Healthcare Management, enquadram a Inovação como “podendo ser imprevisível e mesmo dolorosa, pelo que talvez possamos não ficar surpreendidos se surgirem resistências e que, inovações bastante necessárias, capazes de melhorar os indicadores de saúde, tenham sido de adoção lenta ou que tenham mesmo sido insustentáveis”. Em Portugal não há bibliografia que procure caracterizar o modelo de difusão da inovação em eHealth ou das tecnologias de vivência assistida. A bibliografia internacional é igualmente escassa. O presente projeto de investigação, de natureza exploratória, tem como objetivo principal, identificar barreiras e oportunidades para a implementação de tecnologias eHealth, aplicadas ao campo das demências. Como objetivos secundários pretendemse identificar as oportunidades e limitações em Portugal: mapa de competências nacionais, e propor medidas que possa acelerar a inovação em ALT, no contexto nacional. O projeto seguirá o modelo de um estudo qualitativo. Para o efeito foram conduzidas entrevistas em profundidade junto de experts em ALT, procurando obter a visão daqueles que participam do lado da Oferta- a Indústria; do lado da Procura- doentes, cuidadores e profissionais de saúde; bem como dos Reguladores. O instrumento utilizado para a recolha da informação pretendida foi o questionário não estruturado. A análise e interpretação da informação recolhida foram feitas através da técnica de Análise de Conteúdo. Os resultados da Análise de Conteúdo efetuada permitiram expressar a dicotomia barreira/oportunidade, nas seguintes categorias aqui descritas como contextos (i) Contexto Tecnológico, nas subcategorias de Acesso às Infraestruturas; Custo da Tecnologia; Interoperabilidade, (ii) Contexto do Valor Percecionado, nas subcategorias de Utilidade; Eficiência; Divulgação, (iii) Contexto Político, compreendendo a Liderança; Organização; Regulação; Recursos, (iv) Contexto Sociocultural, incluindo nomeadamente Idade; Literacia; Capacidade Económica, (v) Contexto Individual, incluindo como subcategorias, Capacidade de Adaptação a Novas tecnologias; Motivação; Acesso a equipamentos (vi) Contexto Específico da Doença, nomeadamente o Impacto Cognitivo; Tipologia Heterogénea e a Importância do Cuidador. Foi proposto um modelo exploratório, designado de Modelo de Contextos e Forças, que estudos subsequentes poderão validar. Neste modelo o Contexto Tecnológico é um Força Básica ou Fundamental; o Contexto do Valor Percecionado, constitui-se numa Força Crítica para a adoção de inovação, que assenta na sua capacidade para oferecer valor aos diversos stakeholders da cadeia de cuidados. Temos também o Contexto Político, com capacidade de modelar a adoção da inovação e nomeadamente com capacidade para o acelerar, se dele emitir um sinal de urgência para a mudança. O Contexto Sociocultural e Individual expressam uma Força Intrínseca, dado que elas são características internas, próprias e imutáveis no curto-prazo, das sociedade e das pessoas. Por fim há que considerar o Contexto Específico da Doença, nesta caso o das demências. Das conclusões do estudo parece evidente que as condições tecnológicas estão medianamente satisfeitas em Portugal, com evidentes progressos nos últimos anos (exceção para a interoperabilidade aonde há necessidade de maiores progressos), não constituindo portanto barreira à introdução de ALT. Aonde há necessidade de investir é nas áreas do valor percebido. Da análise feita, esta é uma área que constitui uma barreira à introdução e adoção das ALT em Portugal. A falta de perceção do valor que estas tecnologias trazem, por parte dos profissionais de saúde, doentes, cuidadores e decisores políticos, parece ser o principal entrave à sua adoção. São recomendadas estratégias de modelos colaborativos de Investigação e Desenvolvimento e de abordagens de cocriação com a contribuição de todos os intervenientes na cadeia de cuidados. Há também um papel que cabe ao estado no âmbito das prioridades e da mobilização de recursos, sendo-lhe requerida a expressão do sentido de urgência para que esta mudança aconteça. Foram também identificadas oportunidades em diversas áreas, como na prevenção, no diagnóstico, na compliance medicamentosa, na terapêutica, na monitorização, no apoio à vida diária e na integração social. O que é necessário é que as soluções encontradas constituam respostas àquilo que são as verdadeiras necessidades dos intervenientes e não uma imposição tecnológica que só por si nada resolve. Do estudo resultou também a perceção de que há que (i) continuar a trabalhar no sentido de aproximar a comunidade científica, da clínica e do doente, (ii) fomentar a colaboração entre centros, com vista à criação de escala a nível global. Essa colaboração já parece acontecer a nível empresarial, tendo sido identificadas empresas Portuguesas com vocação global. A qualidade individual das instituições de ensino, dos centros de investigação, das empresas, permite criar as condições para que Portugal possa ser país um piloto e um case-study internacional em ALT, desde que para tal pudéssemos contar com um trabalho colaborativo entre instituições e com decisões políticas arrojadas.

Mobile image processing to support educational geometry games

The mobile IT era is here, it is still growing and expanding at a steady rate and, most of all, it is entertaining. Mobile devices are used for entertainment, whether social through the so-called social networks, or private through web browsing, video watching or gaming. Youngsters make heavy use of these devices, and even small children show impressive adaptability and skill. However not much attention is directed towards education, especially in the case of young children. Too much time is usually spent in games which only purpose is to keep children entertained, time that could be put to better use such as developing elementary geometric notions. Taking advantage of this pocket computer scenario, it is proposed an application geared towards small children in the 6 – 9 age group that allows them to consolidate knowledge regarding geometric shapes, forming a stepping stone that leads to some fundamental mathematical knowledge to be exercised later on. To achieve this goal, the application will detect simple geometric shapes like squares, circles and triangles using the device’s camera. The novelty of this application will be a core real-time detection system designed and developed from the ground up for mobile devices, taking into account their characteristic limitations such as reduced processing power, memory and battery. User feedback was be gathered, aggregated and studied to assess the educational factor of the application.

Factores sociodemográficos na saúde oral : influências nos comportamentos de rotinas de saúde oral, frequências de idas a consultas, auto avaliação do estado de saúde oral e presença de dor em jovens de 12 anos

RESUMO - Introdução: A saúde oral é uma componente essencial na saúde geral e no bem-estar dos indivíduos. Sabe-se que os problemas de saúde oral afectam predominantemente os elementos de níveis socioeconómicos mais baixos, evidenciando a influência dos determinantes sociais da saúde na saúde oral das populações. Os objectivos deste estudo são caracterizar os comportamentos de rotinas diárias de higiene oral, frequências de idas a consultas de saúde oral, auto-avaliação do estado de saúde oral e percepção de dor na cavidade oral em crianças de 12 anos em Portugal e analisar a associação entre estes e os factores sociodemográficos. Métodos: Foi realizado um estudo observacional, transversal e analítico, abrangendo 1309 jovens e baseado em informação recolhida no III Estudo Nacional de Prevalência de Doenças Orais (ENPDO). Para além das estatísticas descritivas usuais, as estatísticas inferenciais basearam-se predominantemente em modelos de regressão logística binária. Resultados: Dos participantes, 70.6% (n=924) escova “duas ou mais vezes por dia” com associação com todas as variáveis sociodemográficas. Na análise multivariada, o género masculino (OR=2.088; IC95%: 1.574-2.770, em relação ao género feminino), a área de residência predominantemente rural ou mediamente urbana (OR= 1.800; IC95%: 2.587; OR=1.516; IC95%: 1.093-2.103, em relação a zonas predominantemente urbanas), a escolaridade da mãe ser o ensino básico (OR= 2.112; IC95%: 1.408-3.168, em relação ao ensino superior) e a actividade laboral do pai ser desempregado (OR= 1.938; IC95%: 1.280-2.934, em relação a ser trabalhador) foram as variáveis com mais impacto para a adopção de comportamentos de escovagem potencialmente inadequados (p<0.05). A maioria dos inquiridos (94.2%; n=1247) já tinham ido a uma consulta de saúde oral e 74.5% (n=860) nos últimos 12 meses, 95.5% (n=1250) encontram-se satisfeitos com a saúde oral e 44.5% (n=578) afirma ter tido algum tipo de dor na cavidade oral nos últimos 12 meses. Conclusão: Os resultados obtidos estão de acordo com a literatura em termos de factores de associação. Desta forma, a saúde oral nos jovens de 12 anos em Portugal, nos diversos contextos aqui analisados, pode ser considerada como satisfatória. A única excepção relevante é a componente da dor, com valores alarmantes embora de natureza mais subjectiva. A influência dos factores sociodemográficos sugere que futuras abordagens para a promoção da saúde oral tenham em conta os determinantes de saúde no delineamento de estratégias quer a nível individual quer a nível comunitário.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Simplified wind turbine models for wind energy integration into power systems

This paper analyses the boundaries of simplified wind turbine models used to represent the behavior of wind turbines in order to conduct power system stability studies. Based on experimental measurements, the response of recent simplified (also known as generic) wind turbine models that are currently being developed by the International Standard IEC 61400-27 is compared to complex detailed models elaborated by wind turbine manufacturers. This International Standard, whose Technical Committee was convened in October 2009, is focused on defining generic simulation models for both wind turbines (Part 1) and wind farms (Part 2). The results of this work provide an improved understanding of the usability of generic models for conducting power system simulations.

Development of 3D in vitro models for prediction of hepatic metabolism and toxicity

The development of human cell models that recapitulate hepatic functionality allows the study of metabolic pathways involved in toxicity and disease. The increased biological relevance, cost-effectiveness and high-throughput of cell models can contribute to increase the efficiency of drug development in the pharmaceutical industry. Recapitulation of liver functionality in vitro requires the development of advanced culture strategies to mimic in vivo complexity, such as 3D culture, co-cultures or biomaterials. However, complex 3D models are typically associated with poor robustness, limited scalability and compatibility with screening methods. In this work, several strategies were used to develop highly functional and reproducible spheroid-based in vitro models of human hepatocytes and HepaRG cells using stirred culture systems. In chapter 2, the isolation of human hepatocytes from resected liver tissue was implemented and a liver tissue perfusion method was optimized towards the improvement of hepatocyte isolation and aggregation efficiency, resulting in an isolation protocol compatible with 3D culture. In chapter 3, human hepatocytes were co-cultivated with mesenchymal stem cells (MSC) and the phenotype of both cell types was characterized, showing that MSC acquire a supportive stromal function and hepatocytes retain differentiated hepatic functions, stability of drug metabolism enzymes and higher viability in co-cultures. In chapter 4, a 3D alginate microencapsulation strategy for the differentiation of HepaRG cells was evaluated and compared with the standard 2D DMSO-dependent differentiation, yielding higher differentiation efficiency, comparable levels of drug metabolism activity and significantly improved biosynthetic activity. The work developed in this thesis provides novel strategies for 3D culture of human hepatic cell models, which are reproducible, scalable and compatible with screening platforms. The phenotypic and functional characterization of the in vitro systems performed contributes to the state of the art of human hepatic cell models and can be applied to the improvement of pre-clinical drug development efficiency of the process, model disease and ultimately, development of cell-based therapeutic strategies for liver failure.

Predicting market direction with hidden Markov models

This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.