Customer Lifetime Value: a framework for application in the insurance industry - Building a Business Process to Generate and Maintain an Automatic Estimation Agent

Research Project submited as partial fulfilment for the Master Degree in Statistics and Information Management

Multi-GPU support on the marrow algorithmic skeleton framework

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Framework para a construção de “portais de negócio” para gestão de solicitações de consumidores IaaS na HP Cloud

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Gas adsorption in the MIL-53(AI) metal organic framework. Experiments and molecular simulation

Dissertação para obtenção do Grau de Doutor em Engenharia Química

A framework for developing motion-based games

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Expanding the magic circle in pervasive casual play

Dissertação para obtenção do Grau de Doutor em 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

A knowledge-based framework to facilitate E-training implementation

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

Extensão do SDK do Kinect: criação de uma biblioteca de gestos

As interfaces naturais têm ganho atenção crescente por parte da comunidade científica. Esta interação, nomeadamente baseada em gestos e voz, tem sido progressivamente mais usada para estabelecer a comunicação entre o homem e a máquina de forma natural. Em paralelo, têm surgido no marcado alguns novos dispositivos com o objetivo de suportar estas formas naturais de interface, entre eles, sensores de movimento. Esta dissertação tem como objetivo a proposta de algoritmos projetados para auxiliar o programador no reconhecimento de gestos, especificamente em dispositivos conhecidos como sensores de movimentos. Atualmente o programador tem o trabalho de desenvolver todo o código para adicionar reconhecimento de gestos à sua aplicação. A solução apresentada neste documento propõe um novo conjunto de métodos que visam a criação de uma biblioteca de gestos e a consequente capacidade de reconhecimento de gestos anteriormente armazenados. A validação deste trabalho consistiu na extensão do Software Development Kit (SDK) do dispositivo Kinect, de forma a adicionar ferramentas complementares, que permitam simplificar a definição e reconhecimento de gestos. A primeira parte consiste na captação e armazenamento de gestos, através do mapeamento de pontos, modelando os gestos e armazenando tal modelo. Esta primeira fase permite no desenvolvimento de um sistema a criação de uma biblioteca de gestos pré-definidos, como por exemplo os gestos da Língua Gestual Portuguesa. Numa segunda fase, a extensão do SDK auxilia também as tarefas de reconhecimento de gestos em tempo real, isto é, deteção do gesto que o utilizador de uma aplicação esteja a fazer e procura desse gesto na biblioteca.

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.

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.

Kinect-sign

A nova era da informação que se está a assistir tem possibilitado a criação de novas e vastas coleções de intelecto virtual, como por exemplo o Wikipedia, Corsera, entre outros. Estas ferramentas vieram possibilitar a procura por cultura, resoluções de problemas do quotidiano, novos métodos de aprendizagem, por parte da sociedade em geral. Porém, como é habitual, tem-se vindo a verificar uma certa dificuldade inerente por parte de certas minorias sociais, que não possuem as mesmas capacidades de um indivíduo “normal“. Esta dissertação tem como objetivo a criação de uma ferramenta, em formato de jogo sério, para apoiar o ensino de Língua Gestual Portuguesa a um público ouvinte o -“Kinect Sign”. Com este estudo pretende-se explorar as mais recentes ferramentas de desenvolvimento de jogos, mais conhecidas como Authoring Tools e a sua integração com Natural User interfaces, concretamente o sensor Kinect. A solução apresentada neste documento propõe a utilização desta ferramenta a todos os indivíduos iniciantes que necessitem de uma introdução a esta forma de comunicação, para tornar um pouco menos agressiva a entrada no complexo mundo da linguagem gestual. A validação deste trabalho consistiu no desenvolvimento de um jogo protótipo que incentive os jogadores a aprenderem enquanto jogam. Analisaram-se problemas e tecnologias atuais para se chegar a uma estruturação semelhante a um jogo comum disponível em qualquer superfície comercial e websites dedicados ao género. Posterior apresentação a uma população selecionada a fim de analisar a sua opinião e utilidade do modelo desenvolvido, seguindo-se a resposta a um pequeno questionário.