Model morphisms (MoMo) to enable language independent information models and interoperable business networks

MSc. Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering

Incidência regional e tendências de evolução de incêndios em Portugal (1980-2013)

Em pouco mais de três décadas (1980-2013) registaram-se, em Portugal continental, cerca de 745 mil ignições e uma área ardida que ronda 3,7 milhões de hectares. Todavia, quando se analisa a distribuição espacial dos incêndios verifica-se que há distritos especialmente suscetíveis à sua deflagração e outros mais favoráveis à propagação das chamas. A dicotomia Norte/Centro vs Sul de Portugal, tanto no número de ignições como na área ardida, é igualmente bem conhecida. Com o presente trabalho pretende-se analisar a distribuição espacial e detetar tendências de evolução temporal, no período de 1980-2013, tanto na densidade de ignições, como na percentagem de áreas ardidas a nível regional, e, ainda, definir o grau de similaridade existente entre os distritos que compõem Portugal continental, no que se refere à incidência de incêndios florestais. Os resultados referentes à densidade de ignições são perentórios quanto ao seu acréscimo pois, em todas as unidades territoriais, a correlação – baseada quer no coeficiente de Pearson quer no coeficiente de Spearman, de acordo com a análise - revela-se estatisticamente significativa. No que se refere às percentagens de superfície média incinerada, os resultados são mais díspares. Com tendências positivas (p-value <0,05) sobressaem todos os distritos da região Norte, enquanto os de Beja e Évora manifestam a mesma tendência, apenas se aplicado o coeficiente de Spearman. Com tendência inversa, isto é, de decréscimo, apenas se destaca Coimbra. Nos restantes distritos as tendências observadas não revelam significado estatístico.

Immunohistochemical molecular phenotypes of gastric cancer based on SOX2 and CDX2 predict patient outcome

Background Gastric cancer remains a serious health concern worldwide. Patients would greatly benefit from the discovery of new biomarkers that predict outcome more accurately and allow better treatment and follow-up decisions. Here, we used a retrospective, observational study to assess the expression and prognostic value of the transcription factors SOX2 and CDX2 in gastric cancer. Methods SOX2, CDX2, MUC5AC and MUC2 expression were assessed in 201 gastric tumors by immunohistochemistry. SOX2 and CDX2 expression were crossed with clinicopathological and follow-up data to determine their impact on tumor behavior and outcome. Moreover, SOX2 locus copy number status was assessed by FISH (N = 21) and Copy Number Variation Assay (N = 62). Results SOX2 was expressed in 52% of the gastric tumors and was significantly associated with male gender, T stage and N stage. Moreover, SOX2 expression predicted poorer patient survival, and the combination with CDX2 defined two molecular phenotypes, SOX2+CDX2- versus SOX2-CDX2+, that predict the worst and the best long-term patients’ outcome. These profiles combined with clinicopathological parameters stratify the prognosis of patients with intestinal and expanding tumors and in those without signs of venous invasion. Finally, SOX2 locus copy number gains were found in 93% of the samples reaching the amplification threshold in 14% and significantly associating with protein expression. Conclusions We showed, for the first time, that SOX2 combined with CDX2 expression profile in gastric cancer segregate patients into different prognostic groups, complementing the clinicopathological information. We further demonstrate a molecular mechanism for SOX2 expression in a subset of gastric cancer cases.

A governação local no Algarve no contexto de financiamento e responsabilidades

Dissertação de mestrado em Gestão Pública, apresentada à secção autónoma de Ciências Sociais, Jurídicas e Políticas da Universidade de Aveiro,sob orientação da Prof. Doutora Maria Luís Rocha Pinto.

Regional variation in toxoplasmosis seronegativity in the São Paulo metropolitan region

Toxoplasmosis is a highly prevalent zoonotic human infection caused by the Apicomplexa protozoon Toxoplasma gondii. The acute disease is usually mild or asymptomatic, except for foetal infection transmitted by acutely infected pregnant women, which courses as a devastating disease. In order to determine possible regional variations in risk factors, we studied the frequency of seronegativity in areas of the São Paulo Metropolitan Region, comparing liters and age groups. The prevalence of seronegativity was determined retrospectively in 1286 pregnant women receiving prenatal care at public health services in four selected areas of the São Paulo Metropolitan Region of similar socioeconomic background. The São Paulo City area had the higher frequency of seronegativity (41.1%), followed by the Northwest (31.5%) and Southwest (29.9%) areas, with similar intermediate levels, and by the Northeast (22.5%) area with the lowest frequency (p<0.001). A rough estimate disclosed about 280 infected infants/year in the São Paulo Metropolitan Region. Serological titers analyzed by age group suggested a decline in antibody levels with age, as shown by a lower frequency of higher titers in older groups. Our study emphasizes the importance of determining the regional prevalence of toxoplasmosis for proper planning of public health prenatal care.

Fractional Order Generalized Information

This paper formulates a novel expression for entropy inspired in the properties of Fractional Calculus. The characteristics of the generalized fractional entropy are tested both in standard probability distributions and real world data series. The results reveal that tuning the fractional order allow an high sensitivity to the signal evolution, which is useful in describing the dynamics of complex systems. The concepts are also extended to relative distances and tested with several sets of data, confirming the goodness of the generalization.

Proposal for shared services performance management model applied to portugueses public administration

Comunicação apresentada no 8º Congresso Nacional de Administração Pública - Desafios e Soluções, em Carcavelos de 21 a 22 de Novembro de 2011.

Feature Discretization with Relevance and Mutual Information Criteria

Feature discretization (FD) techniques often yield adequate and compact representations of the data, suitable for machine learning and pattern recognition problems. These representations usually decrease the training time, yielding higher classification accuracy while allowing for humans to better understand and visualize the data, as compared to the use of the original features. This paper proposes two new FD techniques. The first one is based on the well-known Linde-Buzo-Gray quantization algorithm, coupled with a relevance criterion, being able perform unsupervised, supervised, or semi-supervised discretization. The second technique works in supervised mode, being based on the maximization of the mutual information between each discrete feature and the class label. Our experimental results on standard benchmark datasets show that these techniques scale up to high-dimensional data, attaining in many cases better accuracy than existing unsupervised and supervised FD approaches, while using fewer discretization intervals.

Person Localization Using Sensor Information Fusion

Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is difficult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to suppress this limitation and to provide location everywhere (even where a structured environment doesn’t exist) a wearable inertial navigation system is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.

Localization system for pedestrians based on sensor and information fusion

Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.

Finding a school technological partner: a multicriteria method for school information system producer selection

The choice of an information systems is a critical factor of success in an organization's performance, since, by involving multiple decision-makers, with often conflicting objectives, several alternatives with aggressive marketing, makes it particularly complex by the scope of a consensus. The main objective of this work is to make the analysis and selection of a information system to support the school management, pedagogical and administrative components, using a multicriteria decision aid system – MMASSITI – Multicriteria Method- ology to Support the Selection of Information Systems/Information Technologies – integrates a multicriteria model that seeks to provide a systematic approach in the process of choice of Information Systems, able to produce sustained recommendations concerning the decision scope. Its application to a case study has identi- fied the relevant factors in the selection process of school educational and management information system and get a solution that allows the decision maker’ to compare the quality of the various alternatives.

SIGESPROTA: elaboração do sistema de informação geográfica de apoio à gestão e avaliação do PROT Alentejo

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Los riesgos tecnológico-sanitários em Cantabria (España)

Trabalho de projecto apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica

Group decision making for selection of an information system in a business context

The main objective of this work is to report on the development of a multi-criteria methodology to support the assessment and selection of an Information System (IS) framework in a business context. The objective is to select a technological partner that provides the engine to be the basis for the development of a customized application for shrinkage reduction on the supply chains management. Furthermore, the proposed methodology di ers from most of the ones previously proposed in the sense that 1) it provides the decision makers with a set of pre-defined criteria along with their description and suggestions on how to measure them and 2)it uses a continuous scale with two reference levels and thus no normalization of the valuations is required. The methodology here proposed is has been designed to be easy to understand and use, without a specific support of a decision making analyst.

Georeferencing Road Accidents with Google Earth: Transforming Information into Knowledge for Decision Support

Over the last fifty years mobility practices have changed dramatically, improving the way travel takes place, the time it takes but also on matters like road safety and prevention. High mortality caused by high accident levels has reached untenable levels. But the research into road mortality stayed limited to comparative statistical exercises which go no further than defining accident types. In terms of sharing information and mapping accidents, little progress has been mad, aside from the normal publication of figures, either through simplistic tables or web pages. With considerable technological advances on geographical information technologies, research and development stayed rather static with only a few good examples on dynamic mapping. The use of Global Positioning System (GPS) devices as normal equipments on automobile industry resulted in a more dynamic mobility patterns but also with higher degrees of uncertainty on road traffic. This paper describes a road accident georeferencing project for the Lisbon District involving fatalities and serious injuries during 2007. In the initial phase, individual information summaries were compiled giving information on accidents and its majour characteristics, collected by the security forces: the Public Safety Police Force (Polícia de Segurança Pública - PSP) and the National Guard (Guarda Nacional Republicana - GNR). The Google Earth platform was used to georeference the information in order to inform the public and the authorities of the accident locations, the nature of the location, and the causes and consequences of the accidents. This paper also gives future insights about augmented reality technologies, considered crucial to advances to road safety and prevention studies. At the end, this exercise could be considered a success because of numerous consequences, as for stakeholders who decide what to do but also for the public awareness to the problem of road mortality.