Enabling Global Experiments With Interactive Reconfiguration And Steering By Multiple Users

In global scientific experiments with collaborative scenarios involving multinational teams there are big challenges related to data access, namely data movements are precluded to other regions or Clouds due to the constraints on latency costs, data privacy and data ownership. Furthermore, each site is processing local data sets using specialized algorithms and producing intermediate results that are helpful as inputs to applications running on remote sites. This paper shows how to model such collaborative scenarios as a scientific workflow implemented with AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic), a decentralized framework offering a feasible solution to run the workflow activities on distributed data centers in different regions without the need of large data movements. The AWARD workflow activities are independently monitored and dynamically reconfigured and steering by different users, namely by hot-swapping the algorithms to enhance the computation results or by changing the workflow structure to support feedback dependencies where an activity receives feedback output from a successor activity. A real implementation of one practical scenario and its execution on multiple data centers of the Amazon Cloud is presented including experimental results with steering by multiple users.

Culturtainment - a new interactive entertainment genre: assessment of Cultural Heritage digital content in leisure software games

European Master in Multimedia and Audiovisual Administration

Collaborative geographic visualization

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas Ambientais

Visualization of clusters in geo-referenced data using three-dimensional self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Interactive whiteboards in Portuguese primary schools: the teachers' view

Focusing on the use of Interactive Whiteboards (IWBs) in primary schools in Oeiras municipality, this article presents primary teachers’ views, from their experience, on the implementation of this innovation as a resource for the teaching and learning processes. IWBs have been recently launched in the framework of a major program aiming the technological modernization of Portuguese schools, in order to promote the use of ICT in teaching and learning, as well as in school management. Findings show that teachers are enthusiastic about Interactive White Boards because they really believe their pupils learn better and in a more joyful way. However, they draw attention to the need of training in order to fully exploit the potential of this resourc

Diagnosis of Helicobacter pylori: comparison of an urease test, histological visualization of curved bacteria and culture

Helicobacter pylori was investigated in 189 patients for culture, microscopic visualization of campylobacter-like organisms (CLO) and a ten minute urease test. In 136 (72%) the bacteria was isolated, and in 98 of them CLO were histologically detected. Specificity, sensitivity, positive and negative predictive values of microscopic visualization of CLO were: 0.77, 0.73, 0.97 and 0.51, respectively; 98 culture-positive patients were urease test positive. Specificity, sensitivity, positive and negative predictive values of the urease test were: 0.83, 0.72, 0.92 and 0.54, respectively. Comparing the urease test with culture of H. pylori combined with microscopic visualization of CLO, its specificity, sensitivity, positive and negative predictive values were: 0.95, 0.71, 0.98 and 0.48, respectively. Probably, these values are not real, since bacteria different from H. pylori could be misclassified as CLO.

Multidimensional scaling visualization of earthquake phenomena

Earthquakes are associated with negative events, such as large number of casualties, destruction of buildings and infrastructures, or emergence of tsunamis. In this paper, we apply the Multidimensional Scaling (MDS) analysis to earthquake data. MDS is a set of techniques that produce spatial or geometric representations of complex objects, such that, objects perceived to be similar/distinct in some sense are placed nearby/distant on the MDS maps. The interpretation of the charts is based on the resulting clusters since MDS produces a different locus for each similarity measure. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analyzed. The events, characterized by their magnitude and spatiotemporal distributions, are divided into groups, either according to the Flinn–Engdahl seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Space-time and Space-frequency correlation indices are proposed to quantify the similarities among events. MDS has the advantage of avoiding sensitivity to the non-uniform spatial distribution of seismic data, resulting from poorly instrumented areas, and is well suited for accessing dynamics of complex systems. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools, for understanding the global behavior of earthquakes.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamic Analysis and Pattern Visualization of Forest Fires

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamical Analysis and Visualization of Tornadoes Time Series

In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.

Multidimensional Scaling Visualization using Parametric Similarity Indices

In this paper, we apply multidimensional scaling (MDS) and parametric similarity indices (PSI) in the analysis of complex systems (CS). Each CS is viewed as a dynamical system, exhibiting an output time-series to be interpreted as a manifestation of its behavior. We start by adopting a sliding window to sample the original data into several consecutive time periods. Second, we define a given PSI for tracking pieces of data. We then compare the windows for different values of the parameter, and we generate the corresponding MDS maps of ‘points’. Third, we use Procrustes analysis to linearly transform the MDS charts for maximum superposition and to build a global MDS map of “shapes”. This final plot captures the time evolution of the phenomena and is sensitive to the PSI adopted. The generalized correlation, the Minkowski distance and four entropy-based indices are tested. The proposed approach is applied to the Dow Jones Industrial Average stock market index and the Europe Brent Spot Price FOB time-series.

Attachment, Physiological and Familial Vulnerability in Childhood Obesity: an Interactive Multisystem Approach

The aims of the present study were to test the association between insecure attachment and basal cortisol and catecholamines levels in a sample of obese children. The role of familial vulnerability and gender was also investigated. Methods: Cortisol and catecholamines levels of 8- to 13-year olds obese children were measured. Self-report questionnaires were used to assess attachment pattern and current anxiety and depression, and parent-report questionnaires were used to assess attachment, current anxiety and depression and familial vulnerability. Linear regression analyses were performed for individuals that scored low versus high on parental internalizing problems, and for boys and girls, separately. Results: In the group with high parental internalizing problems, insecure attachment was significantly associated with reduced basal levels of cortisol, in boys (p=0.007, b= -0.861, R2= 73.0%). In the group with low parental internalizing problems, the association between insecure attachment and cortisol was not significant in either boys or girls, and it was negative in boys (p=0.075, b= -0.606, R2= 36.7%) and positive in girls (p=0.677, b= 0.176, R2= 3.1%) . Conclusions: Apparently, physiological risk factors for psicopathology in obesity are more evident in individuals with a high familial vulnerability. In addition, patterns of physiological risk for psicopathology in obesity are different in boys and girls. Therefore, it is important to take into account familial vulnerability and gender when investigating physiological risk factors for psycopathology in obesity. Insecure attachment in childhood may be a risk factor for obesity. Interventions to increase children's attachment security should examine the effects on children's weight.

Geometry based visualization with OpenCL

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Long-term biosignals visualization and processing

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

Post-MAPS: An interactive acquisition platform for gastroenterology

Post-MAPS is a web platform that collects gastroenterological exam data from several european hospital centers, to be used in future clinical studies and was developed in partnership with experts from the gastroenterological area and information technology (IT) technicians. However, although functional, this platform has some issues that are crucial for its functioning, and can render user interaction unpleasant and exhaustive. Accordingly, we proposed the development of a new web platform, in which we aimed for an improvement in terms of usability, data uni cation and interoperability. Therefore, it was necessary to identify and study different ways of acquiring clinical data and review some of the existing clinical databases in order to understand how they work and what type of data they store, as well as their impact and contribution to clinical knowledge. Closely linked to the data model is the ability to share data with other systems, so, we also studied the concept of interoperability and analyzed some of the most widely used international standards, such as DICOM, HL7 and openEHR. As one of the primary objectives of this project was to achieve a better level of usability, practices related to Human Computer-Interaction, such as requirement analysis, creation of conceptual models, prototyping, and evaluation were also studied. Before we began the development, we conducted an analysis of the previous platform, from a functional point of view, which allowed us to gather not only a list of architectural and interface issues, but also a list of improvement opportunities. It was also performed a small preliminary study in order to evaluate the platform's usability, where we were able to realize that perceived usability is different between users, and that, in some aspects, varies according to their location, age and years of experience. Based on the information gathered during the platform's analysis and in the conclusions of the preliminary study, a new platform was developed, prepared for all potential users, from the inexperienced to the most comfortable with technology. It presents major improvements in terms of usability, also providing several new features that simplify the users' work, improving their interaction with the system, making their experience more enjoyable.