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.

A system’s approach to cache hierarchy-aware decomposition of data-parallel computations

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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.

The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

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.

O dever de obediência a ordens ilegais na Guarda Nacional Republicana

The Republican National Guard (GNR) is a military structure and hierarchical force where discipline and obedience is a serious matter, but at the same time, the scope of its activity relates to the protection of the rights, freedoms and guarantees of citizens and the primacy of public interest. While security force, GNR ensures democratic law, guarantee the internal security and the rights of citizens. The controversial issue that lies at the heart of this work its related with the balance between the hierarchy and the written law. The hierarchy, also established by law, with given powers, exist to apply the law. However, the rule of law has exceptions. Which institute to prioritize, hierarchy or the law. And within the law, its rules or the exceptions. Who decides? The GNR's officers have to obey the laws and regulations and comply with the accuracy and timeliness determinations, orders and instructions issued by a superior, given in terms of service, as long as does not involve the practice of crime. The GNR´s officer with command tasks exercises power of authority inherent in these functions, and the corresponding disciplinary authority, being responsible for acts by himself or by his order are practiced. Identify situations of exception to law enforcement, the situations in which one must obey illegal orders, is difficult and thankless, it requires conferred authority and raises the weight of responsibility for decisions and orders issued.

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].