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

Clearing the cloudy crystal balls: Hybrid modelling for energy and climate change mitigation scenarios – A case study for Portugal

Dissertação para obtenção do Grau de Doutor em Ambiente

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.

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.

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.

Efficient paraconsistent reasoning with rules and ontologies for the semantic web

Ontologies formalized by means of Description Logics (DLs) and rules in the form of Logic Programs (LPs) are two prominent formalisms in the field of Knowledge Representation and Reasoning. While DLs adhere to the OpenWorld Assumption and are suited for taxonomic reasoning, LPs implement reasoning under the Closed World Assumption, so that default knowledge can be expressed. However, for many applications it is useful to have a means that allows reasoning over an open domain and expressing rules with exceptions at the same time. Hybrid MKNF knowledge bases make such a means available by formalizing DLs and LPs in a common logic, the Logic of Minimal Knowledge and Negation as Failure (MKNF). Since rules and ontologies are used in open environments such as the Semantic Web, inconsistencies cannot always be avoided. This poses a problem due to the Principle of Explosion, which holds in classical logics. Paraconsistent Logics offer a solution to this issue by assigning meaningful models even to contradictory sets of formulas. Consequently, paraconsistent semantics for DLs and LPs have been investigated intensively. Our goal is to apply the paraconsistent approach to the combination of DLs and LPs in hybrid MKNF knowledge bases. In this thesis, a new six-valued semantics for hybrid MKNF knowledge bases is introduced, extending the three-valued approach by Knorr et al., which is based on the wellfounded semantics for logic programs. Additionally, a procedural way of computing paraconsistent well-founded models for hybrid MKNF knowledge bases by means of an alternating fixpoint construction is presented and it is proven that the algorithm is sound and complete w.r.t. the model-theoretic characterization of the semantics. Moreover, it is shown that the new semantics is faithful w.r.t. well-studied paraconsistent semantics for DLs and LPs, respectively, and maintains the efficiency of the approach it extends.

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.

Hybrid capture II and PapilloCheck® tests for detection of anal high-risk human papillomavirus

Introduction This study evaluated the level of concordance between hybrid capture II (HCII) and PapilloCheck® for the detection of high-risk human papillomavirus (HPV) in anal samples. Methods Anal cell samples collected from 42 human immunodeficiency virus (HIV)+ patients were analyzed. Results Considering only the 13 high-risk HPV types that are detectable by both tests, HCII was positive for 52.3% of the samples, and PapilloCheck® was positive for 52.3%. The level of concordance was 80.9% (Kappa = 0.61). Conclusions Good concordance was observed between the tests for the detection of high-risk HPV.

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.

From "Humanities and Computing" to "Digital Humanities": Digital Humanities in Portugal with a focus on Historical Research

In the following text I will develop three major aspects. The first is to draw attention to those who seem to have been the disciplinary fields where, despite everything, the Digital Humanities (in the broad perspective as will be regarded here) have asserted themselves in a more comprehensive manner. I think it is here that I run into greater risks, not only for what I have mentioned above, but certainly because a significant part, perhaps, of the achievements and of the researchers might have escaped the look that I sought to cast upon the past few decades, always influenced by my own experience and the work carried out in the field of History. But this can be considered as a work in progress and it is open to criticism and suggestions. A second point to note is that emphasis will be given to the main lines of development in the relationship between historical research and digital methodologies, resources and tools. Finally, I will try to make a brief analysis of what has been the Digital Humanities discourse appropriation in recent years, with very debatable data and methods for sure, because studies are still scarce and little systematic information is available that would allow to go beyond an introductory reflection.

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.

Experimental and numerical approaches for structural assessment in new footbridge designs (SFRSCC–GFPR hybrid structure)

Within the civil engineering field, the use of the Finite Element Method has acquired a significant importance, since numerical simulations have been employed in a broad field, which encloses the design, analysis and prediction of the structural behaviour of constructions and infrastructures. Nevertheless, these mathematical simulations can only be useful if all the mechanical properties of the materials, boundary conditions and damages are properly modelled. Therefore, it is required not only experimental data (static and/or dynamic tests) to provide references parameters, but also robust calibration methods able to model damage or other special structural conditions. The present paper addresses the model calibration of a footbridge bridge tested with static loads and ambient vibrations. Damage assessment was also carried out based on a hybrid numerical procedure, which combines discrete damage functions with sets of piecewise linear damage functions. Results from the model calibration shows that the model reproduces with good accuracy the experimental behaviour of the bridge.

Development of innovative hybrid sandwich panel slabs: Experimental results

The authors appreciate the collaboration of the following labs: Civitest for developing DHCC materials, PIEP for conducting VARTM process (Eng. Luis Oliveira) and Department of Civil Engineering of Minho University to perform the tests (Mr. Antonio Matos and Eng. Marco Jorge).