Real-time labview assessment on adsorption systems

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Structural time series models and the Kalman filter: A concise review

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

Positive self-image over time

This paper incorporates egocentric comparisons into a human capital accumulation model and studies the evolution of positive self image over time. The paper shows that the process of human capital accumulation together with egocentric comparisons imply that positive self image of a cohort is first increasing and then decreasing over time. Additionally, the paper finds that positive self image: (1) peaks earlier in activities where skill depreciation is higher, (2) is smaller in activities where the distribution of income is more dispersed, (3) is not a stable characteristic of an individual, and (4) is higher for more patient individuals.

Machine learning Gaussian short rate

Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco

A clustering approach for vehicle routing problems with hard time windows

Dissertação para obtenção do Grau de Mestre em Logica Computicional

Design of a Continuous-Time (CT) Sigma-Delta modulator for class D audio power amplifiers

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Human activity recognition with accelerometry: novel time and frequency features

Human Activity Recognition systems require objective and reliable methods that can be used in the daily routine and must offer consistent results according with the performed activities. These systems are under development and offer objective and personalized support for several applications such as the healthcare area. This thesis aims to create a framework for human activities recognition based on accelerometry signals. Some new features and techniques inspired in the audio recognition methodology are introduced in this work, namely Log Scale Power Bandwidth and the Markov Models application. The Forward Feature Selection was adopted as the feature selection algorithm in order to improve the clustering performances and limit the computational demands. This method selects the most suitable set of features for activities recognition in accelerometry from a 423th dimensional feature vector. Several Machine Learning algorithms were applied to the used accelerometry databases – FCHA and PAMAP databases - and these showed promising results in activities recognition. The developed algorithm set constitutes a mighty contribution for the development of reliable evaluation methods of movement disorders for diagnosis and treatment applications.

State detection in a financial portfolio: a self-organizing maps approach for financial time series

This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.

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.

A matter of time: Phases of customer co-creation community participation and their impact on customer behavior

Despite the growing relevance of co-creating customer communities only little scientific evidence is available on their impact on transactional behavior of participants. Previous research has mostly used self-reported data or distinguished only between during and pre-community phases obtaining mixed results. However, the author proposes that co-creating community activity takes place in five distinguishable phases and changes in transactional behavior are limited to certain phases. Using 33 months of transactional data of a Dutch online auction provider a study was conducted covering all five phases of the community co-creation process from community planning over community set-up, co-development and co-testing to post-launch. The overall results indicate mixed effects of community participation on the different transactional variables during the co-creation process. Community participation had positive effects on auctions listing behavior at the community set-up, co-development and post-launch phases, whereby the number of auctions listed peaked during the community set-up phase. These results suggest that the impact on transactional behavior differs between co-creation phases and different psychological mechanism limited to certain phases might trigger the respective changes.

Being ahead of its time the consumer resistance phenomenon: A comparative case study research

Double Degree.

Post-merger innovative performance in the renewable energy sector

Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.

Clinical practice guidelines in Portugal : quantitative and qualitative evaluation

RESUMO: Introdução As normas de orientação clínica são ferramentas úteis na translação de conhecimentos desde a investigação para a prática clínica diária. Estratégias ativas de implementação de normas de orientação clínica requerem elevado esforço organizacional e financeiro. Quando os recursos são escassos, as estratégias passivas podem ser a única opção de disseminação. Desde 2011 a Direção Geral da Saúde publicou cento e cinquenta e nove normas de orientação clínica. Nesta Tese é feita uma avaliação do impacto que estratégias de disseminação de normas de orientação clínica têm no padrão de prescrição dos médicos e uma avaliação qualitativa do processo das normas de orientação clínica em Portugal. Métodos: O primeiro artigo é um estudo quasi experimental usando uma série de análises temporais interrompida para comparar os níveis observados e esperados de prescrição de inibidores da ciclooxigenasa-2, antes e depois da publicação da norma de orientação clínica sobre a utilização de anti-inflamatórios não esteroides. O segundo estudo é um artigo de opinião e debate no qual numa primeira parte contextualiza o processo das normas da Direcção Geral da Saúde, na segunda parte aponta virtudes e defeitos no processo e a terceira parte constitui uma contribuição com vista à melhoria do processo. Discussão A produção de normas de orientação clínica requer metodologia rigorosa e complexa. A literatura médica revela que a translação de conhecimento é uma tarefa árdua. Estratégias de implementação ativas requerem recursos financeiros e organizacionais sólidos. Estratégias de implementação passivas podem representar uma solução aceitável se os recursos financeiros e organizacionais escasseiam. Pouco é conhecido sobre a eficácia destas estratégias fora do contexto de investigação. Com esta Tese pretendo contribuir para a clarificação desta resposta, outros países e instituições podem ver utilidade nesta informação, bem como pretendo contribuir para a discussão e melhoria do processo das normas de orientação clínica em Portugal. ------------------ ABSTRACT: Introduction Clinical practice guidelines can help address the failure to translate research findings into clinical practice. Active clinical practice guidelines implementation strategies require active efforts from organizations and are resource and financially demanding. Passive implementation strategies may represent the only option if resources are scarce. Out of research environment, real world efficacy of passive implementation strategies is still undetermined. Since 2011 the Portuguese General Health Directorate published one hundred and fifty nine guidelines. In this Thesis I evaluate the impact of passive dissemination of clinical practice guideline in clinician’s prescription behavior and review, from a qualitative point of view, the Portuguese clinical practice guideline process. Methods The first study is a quasi-experimental study using a retrospective interrupted time-series analysis design to compare the observed and expected prescription of cyclooxygenase-2 before and after the non steroidal antiinflammatory guideline publication. The second study is an opinion and debate article in which I firstly review the General Health Directorate guideline process. The second part states positive and negative aspects in the process and the third part is a contribution aimed at improving the process in the future. Discussion Clinical practice guidelines production demands a rigorous and complex methodology. medical iterature reveals that knowledge translation is a difficult task. Active implementation strategies demand solid financial and organizational resources. Passive implementation strategies may represent an acceptable solution if financial and organizational resources are scarce. Little is known about the efficacy of these strategies out of the research context. With this Thesis I intend to contribute to clarify this question, other countries and institutions with similar conditions may find this information useful, and also to contribute for the discussion and general improvement of national clinical practice guidelines process.

Who uses NHS saúde 24 hotline? Has the user changed over time?

There has been an increase in the use of telephone-based services and internet throughout the years and, therefore, the Saúde 24 Hotline has become an important service in Portugal. This service aims to screen, counsel and refer the patient in order to avoid unnecessary visits to health institutions and also to indicate the most appropriate resource according to the illness. This work has two different questions: the first one examines the determinants of satisfaction that have more influence on the overall satisfaction of the Saúde 24 Hotline users. The second one aims to analyze if the confidence level of the users is increasing over time, measured by following the recommendation. The first study was conducted on a random sample collected from June to October 2014, which was taken from the User Satisfaction Survey. The second approach includes data from January 2008 to December 2014 from the Clinical Data Base of all users who have called the Hotline. Findings suggest that the majority of users are very satisfied with the service and the variables with more impact on the overall satisfaction are commitment and availability from the nurse, adequacy of call duration and quick identification of the problem. The survey indicates that 94% of respondents follow the recommendation and on average people have called the hotline 3 times in the previous year. The results from the Clinical Database show that people who were recommended to go to the emergency room are more likely to follow the advice than the people who were recommended to book routine appointments

Electrohysterogram signal component cataloging with spectral and time-frequency methods

The Electrohysterogram (EHG) is a new instrument for pregnancy monitoring. It measures the uterine muscle electrical signal, which is closely related with uterine contractions. The EHG is described as a viable alternative and a more precise instrument than the currently most widely used method for the description of uterine contractions: the external tocogram. The EHG has also been indicated as a promising tool in the assessment of preterm delivery risk. This work intends to contribute towards the EHG characterization through the inventory of its components which are: • Contractions; • Labor contractions; • Alvarez waves; • Fetal movements; • Long Duration Low Frequency Waves; The instruments used for cataloging were: Spectral Analysis, parametric and non-parametric, energy estimators, time-frequency methods and the tocogram annotated by expert physicians. The EHG and respective tocograms were obtained from the Icelandic 16-electrode Electrohysterogram Database. 288 components were classified. There is not a component database of this type available for consultation. The spectral analysis module and power estimation was added to Uterine Explorer, an EHG analysis software developed in FCT-UNL. The importance of this component database is related to the need to improve the understanding of the EHG which is a relatively complex signal, as well as contributing towards the detection of preterm birth. Preterm birth accounts for 10% of all births and is one of the most relevant obstetric conditions. Despite the technological and scientific advances in perinatal medicine, in developed countries, prematurity is the major cause of neonatal death. Although various risk factors such as previous preterm births, infection, uterine malformations, multiple gestation and short uterine cervix in second trimester, have been associated with this condition, its etiology remains unknown [1][2][3].