Personalization platform for multimodal ubiquitous computing applications

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

The building blocks of social entrepreneurship: empirical model and framework

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Watershed-scale runoff routing and solute transport in a spatially aggregated hydrological framework

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

Child programming: an adequate domain specific language for programming specific robots

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Study on the development of an autonomous mobile robot

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

Haptic robot-environment interaction for self-supervised learning in ground mobility

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

A knowledge-based framework to facilitate E-training implementation

Dissertação para obtenção do Grau de Mestre em Engenharia Eletrotécnica e de Computadores

Heterogeneous computing with an algorithmic skeleton framework

The Graphics Processing Unit (GPU) is present in almost every modern day personal computer. Despite its specific purpose design, they have been increasingly used for general computations with very good results. Hence, there is a growing effort from the community to seamlessly integrate this kind of devices in everyday computing. However, to fully exploit the potential of a system comprising GPUs and CPUs, these devices should be presented to the programmer as a single platform. The efficient combination of the power of CPU and GPU devices is highly dependent on each device’s characteristics, resulting in platform specific applications that cannot be ported to different systems. Also, the most efficient work balance among devices is highly dependable on the computations to be performed and respective data sizes. In this work, we propose a solution for heterogeneous environments based on the abstraction level provided by algorithmic skeletons. Our goal is to take full advantage of the power of all CPU and GPU devices present in a system, without the need for different kernel implementations nor explicit work-distribution.To that end, we extended Marrow, an algorithmic skeleton framework for multi-GPUs, to support CPU computations and efficiently balance the work-load between devices. Our approach is based on an offline training execution that identifies the ideal work balance and platform configurations for a given application and input data size. The evaluation of this work shows that the combination of CPU and GPU devices can significantly boost the performance of our benchmarks in the tested environments, when compared to GPU-only executions.

A framework for efficient model transformations

The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.

2D position system for a mobile robot in unstructured environments

Nowadays, several sensors and mechanisms are available to estimate a mobile robot trajectory and location with respect to its surroundings. Usually absolute positioning mechanisms are the most accurate, but they also are the most expensive ones, and require pre installed equipment in the environment. Therefore, a system capable of measuring its motion and location within the environment (relative positioning) has been a research goal since the beginning of autonomous vehicles. With the increasing of the computational performance, computer vision has become faster and, therefore, became possible to incorporate it in a mobile robot. In visual odometry feature based approaches, the model estimation requires absence of feature association outliers for an accurate motion. Outliers rejection is a delicate process considering there is always a trade-off between speed and reliability of the system. This dissertation proposes an indoor 2D position system using Visual Odometry. The mobile robot has a camera pointed to the ceiling, for image analysis. As requirements, the ceiling and the oor (where the robot moves) must be planes. In the literature, RANSAC is a widely used method for outlier rejection. However, it might be slow in critical circumstances. Therefore, it is proposed a new algorithm that accelerates RANSAC, maintaining its reliability. The algorithm, called FMBF, consists on comparing image texture patterns between pictures, preserving the most similar ones. There are several types of comparisons, with different computational cost and reliability. FMBF manages those comparisons in order to optimize the trade-off between speed and reliability.

Plataforma smartphone para biossensores de espectroscopia de infravermelho próximo

O tema “Plataforma smartphone para biossensores de Espectroscopia de Infravermelho Próximo”, surge no âmbito da instrumentação médica, na área das BCI – Brain Computer Interfaces, devido à necessidade de encontrar um dispositivo portátil, de custo acessível e elevada performance que permita obter informação acerca da actividade neuronal do córtex motor no decorrer duma determinada tarefa. O objectivo do trabalho consiste no desenvolvimento duma sonda capaz de detectar as alterações hemodinâmicas que ocorrem no córtex, bem como toda a instrumentação inerente à aquisição do sinal e transmissão dos dados para um computador, a análise dos dados e por fim o desenvolvimento de uma aplicação em Android para visualização dos resultados. Foi desenvolvida uma banda para a cabeça, composta pela sonda NIRS: LEDs (Light-Emiting Diodes) de 940nm e 660nm e os respectivos fototransístores de detecção, bem como toda a electrónica de condicionamento do sinal captado. Num módulo à parte, alimentado por duas baterias de 9V, encontram-se os circuitos electrónicos onde é possível regular ganhos de amplificação e offsets. Os dados foram adquiridos pelo microcontrolador Arduíno Uno, usando uma taxa de amostragem de 50Hz em cada um dos dois canais utilizados. O controlo do Arduíno foi feito utilizando o LabVIEW. Para o processamento dos dados, visualização e cálculo das concentrações de oxi e desoxi-hemoglobina no sangue recorreu-se ao Matlab. O sistema foi calibrado com recurso a um oxímetro de pulso clínico usado em cinco indivíduos saudáveis. Finalmente o sistema foi testado ao colocar-se o sensor NIRS sobre o córtex motor esquerdo de nove indivíduos saudáveis destros, fazendo-se uma aquisição de dados durante dois minutos. Utilizou-se um paradigma de 10s de repouso seguido de 10s a abrir e fechar a mão. O sistema NIRS conseguiu medir as alterações que ocorrem nas concentrações de oxi e desoxi-hemoglobina devido à actividade motora de abrir e fechar a mão. Dado o princípio físico ser o mesmo do dos oxímetros convencionais, conseguiu-se ainda medir com sucesso a frequência cardíaca e a saturação percentual de oxigénio após a calibração do sensor. As medidas podem ser visualizadas numa aplicação desenvolvida para o Android. Os resultados sugerem que com esta abordagem, este tipo de dispositivo pode estar disponível a baixo custo quer para doentes quer para indivíduos saudáveis, por exemplo em aplicações de telemóvel.

Probabilistic constraint reasoning with Monte Carlo integration to robot localization

This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.

Desenvolvimento de uma aplicação Android para pacientes sob tratamento

Nos dias de hoje, as tecnologias deixaram de ser tabus para qualquer faixa etária, tor-nando-se uma necessidade emergente. Os smartphones estão entre os dispositivos mais utilizados pela população em geral no quotidiano. Adicionando aos novos estilos de vida atuais, a medicação diária também tem vindo a crescer nos últimos tempos, sendo esta utilizada em casos de hipertensão, colesterol elevado, diabetes ou outras doenças perpétuas, como também na toma de multivitamínicos, medicação para aumento de produtividade, contracetivos ou antibióticos e anti-inflamatórios em casos de constipa-ções ou gripes. Aliado a um estilo de vida célere, a toma de medicação no momento indicado facilmente é esquecida, tornando os tratamentos ineficientes. A aplicação “Hora do comprimido”, desenvolvida para dispositivos Android, permite auxiliar os utilizadores na toma da sua medicação, contínua ou temporária, facilitando o quotidiano do utilizador, viabilizando assim um tratamento completo, sem falhas nas tomas ou feitas fora de horas.

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.

Towards an algorithmic skeleton framework for programming the Intel R Xeon PhiTM processor

The Intel R Xeon PhiTM is the first processor based on Intel’s MIC (Many Integrated Cores) architecture. It is a co-processor specially tailored for data-parallel computations, whose basic architectural design is similar to the ones of GPUs (Graphics Processing Units), leveraging the use of many integrated low computational cores to perform parallel computations. The main novelty of the MIC architecture, relatively to GPUs, is its compatibility with the Intel x86 architecture. This enables the use of many of the tools commonly available for the parallel programming of x86-based architectures, which may lead to a smaller learning curve. However, programming the Xeon Phi still entails aspects intrinsic to accelerator-based computing, in general, and to the MIC architecture, in particular. In this thesis we advocate the use of algorithmic skeletons for programming the Xeon Phi. Algorithmic skeletons abstract the complexity inherent to parallel programming, hiding details such as resource management, parallel decomposition, inter-execution flow communication, thus removing these concerns from the programmer’s mind. In this context, the goal of the thesis is to lay the foundations for the development of a simple but powerful and efficient skeleton framework for the programming of the Xeon Phi processor. For this purpose we build upon Marrow, an existing framework for the orchestration of OpenCLTM computations in multi-GPU and CPU environments. We extend Marrow to execute both OpenCL and C++ parallel computations on the Xeon Phi. We evaluate the newly developed framework, several well-known benchmarks, like Saxpy and N-Body, will be used to compare, not only its performance to the existing framework when executing on the co-processor, but also to assess the performance on the Xeon Phi versus a multi-GPU environment.