A volumetric hybrid representation for obstacle detection in all-terrain robots

This dissertation presents an approach aimed at three-dimensional perception’s obstacle detection on all-terrain robots. Given the huge amount of acquired information, the adversities such environments present to an autonomous system and the swiftness, thus required, from each of its navigation decisions, it becomes imperative that the 3-D perceptional system to be able to map obstacles and passageways in the most swift and detailed manner. In this document, a hybrid approach is presented bringing the best of several methods together, combining the lightness of lesser meticulous analyses with the detail brought by more thorough ones. Realizing the former, a terrain’s slope mapping system upon a low resolute volumetric representation of the surrounding occupancy. For the latter’s detailed evaluation, two novel metrics were conceived to discriminate the little depth discrepancies found in between range scanner’s beam distance measurements. The hybrid solution resulting from the conjunction of these two representations provides a reliable answer to traversability mapping and a robust discrimination of penetrable vegetation from that constituting real obstructions. Two distinct robotic platforms offered the possibility to test the hybrid approach on very different applications: a boat, under an European project, the ECHORD Riverwatch, and a terrestrial four-wheeled robot for a national project, the Introsys Robot.

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

Reactive hybrid knowledge bases

Hybrid knowledge bases are knowledge bases that combine ontologies with non-monotonic rules, allowing to join the best of both open world ontologies and close world rules. Ontologies shape a good mechanism to share knowledge on theWeb that can be understood by both humans and machines, on the other hand rules can be used, e.g., to encode legal laws or to do a mapping between sources of information. Taking into account the dynamics present today on the Web, it is important for these hybrid knowledge bases to capture all these dynamics and thus adapt themselves. To achieve that, it is necessary to create mechanisms capable of monitoring the information flow present on theWeb. Up to today, there are no such mechanisms that allow for monitoring events and performing modifications of hybrid knowledge bases autonomously. The goal of this thesis is then to create a system that combine these hybrid knowledge bases with reactive rules, aiming to monitor events and perform actions over a knowledge base. To achieve this goal, a reactive system for the SemanticWeb is be developed in a logic-programming based approach accompanied with a language for heterogeneous rule base evolution having as its basis RIF Production Rule Dialect, which is a standard for exchanging rules over theWeb.

Avaliação da sustentabilidade corporativa: estudo das relações híbridas pelo modelo do Hybrid Bottom Line

A presente tese reflete sobre os temas do desenvolvimento sustentável, da sustentabilidade corporativa, da responsabilidade social corporativa e das dimensões do Triple Bottom Line. O principal objetivo do nosso trabalho é contribuir para o conhecimento das relações que se estabelecem nas interseções entre a dimensão económica, social e ambiental da sustentabilidade corporativa, aqui designadas de relações híbridas. Neste sentido, desenvolveu-se um enquadramento teórico que fundamenta o modelo proposto, designado por Hybrid Bottom Line. De acordo com este enquadramento procurou-se conceber uma metodologia que permitisse analisar como é que estas relações de interseção entre economia-ambiente e economia-social se verificam e de que forma os seus resultados podem beneficiar a compreensão, avaliação e melhorias no entendimento da sustentabilidade corporativa, bem como possibilitar uma análise dirigida a fatores recombinantes específicos. Em complemento, foi desenvolvida uma proposta que permite posicionar o esforço desenvolvido pela empresa no âmbito da sustentabilidade e desta forma tipificar as suas ações. Nesta tese a abordagem empírica recaiu na análise dos relatórios de sustentabilidade publicados pelas empresas e baseados nas diretivas de relato propostas pelo Global Reporting Initiative. A amostra para o estudo abrangeu um total de 85 empresas de diferentes dimensões de 36 sectores económicos e representando 36 países de 5 continentes. A análise dos resultados foi feita utilizando diversos métodos de análise de dados (de frequência e de conteúdo) e análises estatísticas (análise de contingência, variância e de correspondências múltiplas) que permitiram observar as relações entre as dimensões do Triple Bottom Line, dando lugar à construção de uma matriz de relações híbridas. Seguidamente foi realizada uma análise longitudinal de uma das empresas da amostra tendo como referência a matriz híbrida obtida, assim como a tipificação da empresa no âmbito da sustentabilidade. Os resultados alcançados nas diferentes fases indicam que o enquadramento teórico que foi utilizado é útil para a análise das interseções entre as dimensões e permite uma avaliação dirigida a fatos ocorridos entre pares dimensionais, bem como projetar análises e posicionamentos futuros. Os resultados obtidos sugerem que a proposta apresentada é útil e deverá ser utilizada e desenvolvida noutros contextos. Esta tese contribui para a ideia de que a responsabilidade corporativa não deve ser só vista e operacionalizada como uma realidade de dimensões segmentadas mas também deve ser observada como um conjunto possível de interações que se manifestam nas interseções das suas diferentes dimensões.

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

Hybrid investment strategy active portfolio management – US stock market

This thesis aims to develop an alternative active managed portfolio strategy based on companies‟ Fundamental and Technical Analysis and analyze its finals results. There is a big distinction between the two approaches and the main objective is to understand if it is possible to take advantage of both. With this in mind a Hybrid investment strategy for the US stock market, due to its dimension and liquidity, which was able to outperform the S&P 500 index, the benchmark, during both Bear and Bull Markets between 2000 and 2015.

Does companionate love express itself unequally in different organizational forms (private companies, hybrid and non-governmental organizations)?

Although, the word “Love” in organizations is seen as a rare concept, but it has gained importance in management theoretical foundation. This study seeks to explore the companionate love in distinct of organizational forms (Private companies; Social organizations; NGO and IPSS) through interviews. The results propose that it is a tensional concept with a complex dynamic: tension of personal behavior, tension of professional behavior; tension of individual impact and tension of community impact. The love dynamic has common points to all organizations, but its expression depends on the specific form of the organization.