Spill-over effects in multi-partner loyalty programs

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

Study of multi-component systems in polybenzimidazole membrane formation and their impact on membrane performance

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Data-centric concurrency control on the java programming language

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Dispositivo de interligação multi-rádio de longo alcance para redes de sensores com alimentação solar

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

Business model analysis of Mobitto: How to solve the chicken and egg problem of a multi-sided platform?

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

STRUCTURE-FUNCTION ANALYSIS OF MULTI-COPPER OXIDASES

Dissertation presented to obtain the Ph.D degree in Biochemistry, Structural Biochemistry

Experimental high-throughput adsorption unit for multi-evaluation of adsorbents for gas capture, storage and separation applications

Dissertação para obtenção do grau de Mestre em Engenharia Química e Bioquímica

Optimização energética de sistemas multi-componente da zona fria do Steam Cracker

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores

Aterragem de robôs aéreos multi-rotor em plataformas móveis: uma solução baseada em comportamentos e em saliência visual

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.

Synchronization properties of multi-oscillator circadian systems

Dissertation presented to obtain the Ph.D degree in Computational Biology

The implementation of an Enterprise Geographical Information System to support Cadastre and Expropriation activities.

The processes of mobilization of land for infrastructures of public and private domain are developed according to proper legal frameworks and systematically confronted with the impoverished national situation as regards the cadastral identification and regularization, which leads to big inefficiencies, sometimes with very negative impact to the overall effectiveness. This project report describes Ferbritas Cadastre Information System (FBSIC) project and tools, which in conjunction with other applications, allow managing the entire life-cycle of Land Acquisition and Cadastre, including support to field activities with the integration of information collected in the field, the development of multi-criteria analysis information, monitoring all information in the exploration stage, and the automated generation of outputs. The benefits are evident at the level of operational efficiency, including tools that enable process integration and standardization of procedures, facilitate analysis and quality control and maximize performance in the acquisition, maintenance and management of registration information and expropriation (expropriation projects). Therefore, the implemented system achieves levels of robustness, comprehensiveness, openness, scalability and reliability suitable for a structural platform. The resultant solution, FBSIC, is a fit-for-purpose cadastre information system rooted in the field of railway infrastructures. FBSIC integrating nature of allows: to accomplish present needs and scale to meet future services; to collect, maintain, manage and share all information in one common platform, and transform it into knowledge; to relate with other platforms; to increase accuracy and productivity of business processes related with land property management.

Past/present and future worries: na fMRI study

For the past decade, numerous imaging techniques gave rise to remarka-ble progresses in the understanding of brain’s structure and function. Amongst the wide variety of studies onto the field of neuroscience, neuropsychiatric re-searches with resource to neuroimaging have attracted increasing attention. The present study will focus on the identification of brain areas recruited while normative subjects read sentences related to past/present or future wor-ries. Our main aim was to accurately characterize these brain areas while providing them with a time-stamp that would hopefully help us understand the implications of past/present memories and future envisioning in worrying episodes. With that purpose, functional magnetic resonance imaging data was collected from ten healthy individuals. The obtained data was processed and statistically treated using the General Linear Model and both Fixed and Ran-dom Effects Analysis for group-level results. Thereafter, a Multi-Voxel Pattern Analysis with Searchlight Mapping was performed in order to find patterns of activation that allow differentiation between conditions. The obtained results indicate higher brain activation while reading sen-tences related to past/present worries when compared to future worry or neu-tral sentences. The main areas include frontal cortex, posterior parietal, occipital and temporal areas. Worrying, per se, was characterized by activation of the medial posterior parietal cortex, left posterior occipital lobe and left central temporal lobe. With the searchlight mapping approach we were able to further identify patterns of distinction between conditions, which were located in the parietal, limbic and frontal lobes.