A framework for developing motion-based games

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Study of nuclear reactions relevant for astrophysics by Micro-AMS

Dissertação para obtenção do Grau de Doutor em Física

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

Corruption and Education: Empirical evidence from cross-country micro-data

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics 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

Barriers to micro-enterprise development

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

Data fusion with computational intelligence techniques: a case study of fuzzy inference for terrain assessment

Dissertação apresentada para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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.

Cellulose micro/nano fibers conformational effects probed by nematic liquid crystal droplets

Probing micro-/nano-sized surface conformations, which are ubiquitous in biological systems, by using liquid crystal droplets, which change their ordering and optical appearance in response to the presence of more than ten times smaller cellulose based micro/nano fibers, might find new uses in a range of biological environments and sensors. Previous studies indicate that electrospun micro/nano cellulosic fibers produced from liquid crystalline solutions could present a twisted form [1]. In this work, we study the structures of nematic liquid crystal droplets threaded by cellulose fibers prepared from liquid crystalline and isotropic solutions as well as droplets pierced by spider-made fibers [2]. Planar anchoring at the fibers and planar and homeotropic at the drop surfaces allowed probing cellulose fibers different helical structures as well as aligned filaments.

Writing/erasing 3D micro and nano wrinkles in flexible elastomers for volatile organic compounds sensor

Micro/nano wrinkled patterns on cross-linked urethane/urea polymeric flexible free standing films with two soft segments, polypropylene oxide and polybutadiene, can be induced by UV-irradiation. The ability to write/erase these 3D structures, in a controlled manner, is the main focus of this work. The imprinting of the wrinkled structures was accomplished by swelling in an appropriate solvent followed by drying the membranes after the cross-linking process and UV irradiation. The surface tailoring of the elastomeric membranes was imaged by optical microscopy, scanning electronic microscopy and by atomic force microscopy. To erase the wrinkled structures the elastomers were swollen. The swelling as well as the sol/gel fraction and the UV radiation were tuned in order to control the wrinkles characteristics. It was found that the wrinkles wavelength, in the order of microns (1±0,25μm), was stamped by the UV radiation intensity and exposure time while the wrinkles' amplitude, in the order of nanometers (150-450 nm), was highly dependent on the swelling and sol/gel fraction. A prototype for volatile organic compounds detection was developed taking advantage of the unique 3D micro/nano wrinkles features.

Novel affinity pairs "tag-receptor" for the purification of fusion proteins

Fundação para a Ciência e Tecnologia - SFRH/BD/48804/2008 and the project PTDC/BI/65383/2006 assigned to Prof. Cecíla Roque and also to Associate Laboratory REQUIMTE (Pest-C/EQB/LA0006/2011)