69 resultados para Complex combinatorial problem
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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
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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics
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Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Complex problems of globalized society challenge its adaptive capacity. However, it is precisely the nature of these human induced problems that provide enough evidence to show that adaptability may not be on a resilient path. This thesis explores the ambiguity of the idea of adaptation (and its practice) and illustrates the ways in which adaptability contributes to resilience of social ecological systems. The thesis combines a case study and grounded theory approach and develops an analytical framework to study adaptability in resource users’ organizations: from what it depends on and what the key challenges are for resource management and system resilience. It does so for the specific case of fish producers’ organizations (POs) in Portugal. The findings suggest that while ecological and market context, including the type of crisis, may influence the character of fishers’ adaptation within POs (i.e. anticipatory, maladaptive and reactively adaptive), it does not determine it. Instead, it makes agency even more crucial (i.e. leadership, trust and agent’s perceptions in terms of their impact on fishers’ motivation to learn from each other). In sum, it was found that internal adaptation can improve POs’ contribution to fishery management and resilience, but it is not a panacea and may, in some cases, increase system vulnerability to change. Continuous maladaptation of some Portuguese POs points at a basic institutional problem (fish market regime), which clearly reduces fisheries resilience as it promotes overfishing. However, structural change may not be sufficient to address other barriers to Portuguese fishers’ (PO members) adaptability, such as history (collective memory) and associated problematic self-perceptions. The agency (people involved in structures and practices) also needs to change. What and how institutional change and agency change build on one another (e.g. comparison of fisheries governance in Portugal and other EU countries) is a topic to be explored in further research.
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Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.
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Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.
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Saccharomyces cerevisiae as well as other microorganisms are frequently used in industry with the purpose of obtain different kind of products that can be applied in several areas (research investigation, pharmaceutical compounds, etc.). In order to obtain high yields for the desired product, it is necessary to make an adequate medium supplementation during the growth of the microorganisms. The higher yields are typically reached by using complex media, however the exact formulation of these media is not known. Moreover, it is difficult to control the exact composition of complex media, leading to batch-to-batch variations. So, to overcome this problem, some industries choose to use defined media, with a defined and known chemical composition. However these kind of media, many times, do not reach the same high yields that are obtained by using complex media. In order to obtain similar yield with defined media the addition of many different compounds has to be tested experimentally. Therefore, the industries use a set of empirical methods with which it is tried to formulate defined media that can reach the same high yields as complex media. In this thesis, a defined medium for Saccharomyces cerevisiae was developed using a rational design approach. In this approach a given metabolic network of Saccharomyces cerevisiae is divided into a several unique and not further decomposable sub networks of metabolic reactions that work coherently in steady state, so called elementary flux modes. The EFMtool algorithm was used in order to calculate the EFM’s for two Saccharomyces cerevisiae metabolic networks (amino acids supplemented metabolic network; amino acids non-supplemented metabolic network). For the supplemented metabolic network 1352172 EFM’s were calculated and then divided into: 1306854 EFM’s producing biomass, and 18582 EFM’s exclusively producing CO2 (cellular respiration). For the non-supplemented network 635 EFM’s were calculated and then divided into: 215 EFM’s producing biomass; 420 EFM’s producing exclusively CO2. The EFM’s of each group were normalized by the respective glucose consumption value. After that, the EFMs’ of the supplemented network were grouped again into: 30 clusters for the 1306854 EFMs producing biomass and, 20 clusters for the 18582 EFM’s producing CO2. For the non-supplemented metabolic network the respective EFM’s of each metabolic function were grouped into 10 clusters. After the clustering step, the concentrations of the other medium compounds were calculated by considering a reasonable glucose amount and by accounting for the proportionality between the compounds concentrations and the glucose ratios. The approach adopted/developed in this thesis may allow a faster and more economical way for media development.
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Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.
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Most of today’s systems, especially when related to the Web or to multi-agent systems, are not standalone or independent, but are part of a greater ecosystem, where they need to interact with other entities, react to complex changes in the environment, and act both over its own knowledge base and on the external environment itself. Moreover, these systems are clearly not static, but are constantly evolving due to the execution of self updates or external actions. Whenever actions and updates are possible, the need to ensure properties regarding the outcome of performing such actions emerges. Originally purposed in the context of databases, transactions solve this problem by guaranteeing atomicity, consistency, isolation and durability of a special set of actions. However, current transaction solutions fail to guarantee such properties in dynamic environments, since they cannot combine transaction execution with reactive features, or with the execution of actions over domains that the system does not completely control (thus making rolling back a non-viable proposition). In this thesis, we investigate what and how transaction properties can be ensured over these dynamic environments. To achieve this goal, we provide logic-based solutions, based on Transaction Logic, to precisely model and execute transactions in such environments, and where knowledge bases can be defined by arbitrary logic theories.
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RESUMO - A (não) adesão à terapêutica é um problema mundial que, para além de afetar diretamente a saúde dos indivíduos, afeta também os recursos económicos e sociais. Apesar da importância em aderir à terapêutica, largamente fundamentada na evidência científica, facto é que, em muitos casos, os doentes não o fazem. Assim, estudar as questões relacionadas com a adesão tem vindo a ganhar cada vez mais relevância e atualmente constitui um desafio para os sistemas de saúde, pois os mecanismos envolvidos no comportamento de adesão dos indivíduos são complexos. Deste modo, com este estudo pretendeu-se caracterizar uma amostra de indivíduos com diabetes mellitus tipo 2 e relacionar o seu nível de adesão à terapêutica medicamentosa com os fatores de não adesão. Este estudo foi desenvolvido no Agrupamento de Centros de Saúde (ACES) Almada e Seixal e nele participaram 151 diabéticos tipo 2. Para a recolha de dados utilizou-se o Questionário de Identificação de Fatores de Não Adesão adaptado de Cabral e Silva (2010) e a Medida de Adesão aos Tratamentos de Delgado e Lima (2001). Os resultados mostraram um perfil de participantes maioritariamente idosos, reformados, do género feminino, casados, com o ensino primário completo, rendimento mensal entre 301-1000 euros e tendencialmente aderentes à terapêutica medicamentosa. O (i) esquecimento, o (ii) preço da medicação, o (iii) número elevado de medicamentos para tomar de uma vez só, não perceber bem o que deve tomar e como e (v) adormecer antes da toma foram os fatores de não adesão relatados com mais frequência. Foram encontradas relações significativas entre o nível de adesão e o esquecimento, o preço da medicação o número elevado de medicamentos para tomar de uma vez só e adormecer antes da toma. Não encontrámos relações significativas entre o nível de adesão e os dados sociodemográficos, os fatores terapêuticos e o fator de não adesão “não perceber bem o que deve tomar e como”. No presente estudo são discutidos os resultados obtidos, consideradas algumas limitações e efetuadas propostas de investigações futuras.
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Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.
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Ao longo dos últimos anos a reforma dos sistemas prisionais e a eficácia da reinserção social têm vindo a integrar as agendas políticas dos governos dos países europeus. Esta reforma deriva de vários problemas e carências com que se debatem os diversos sistemas prisionais, nomeadamente a sobrelotação, o ambiente propício à violência, o consumo de drogas, a inactividade do recluso e o elevado índice de reincidência criminal. Porém, qualquer reforma que se venha a delinear compreende matérias muito complexas que vão desde os direitos humanos aos recursos humanos e financeiros, imperativos legais, bem como a conciliação entre a punição e a ressocialização. Estas matérias não dependem apenas da vontade política, mas igualmente da sociedade, a qual ainda ergue barreiras à reinserção, tratando o ex-recluso como um excluído da sociedade. Neste sentido, os estudos universitários constituem um elemento chave na procura de soluções para esta problemática, na medida em que se servem das várias áreas do saber para de alguma forma contribuir com possíveis soluções, tendo em vista a melhoria de todo o sistema prisional e a eficácia da reinserção social. Esta dissertação tem assim como objectivo apresentar os principais modelos de sistemas prisionais adoptados em países europeus e efectuar uma comparação entre estes. Pretende-se retirar os aspectos mais relevantes de cada sistema e que têm contribuído para a melhoria das condições dos reclusos e do aumento da reinserção destes na sociedade, bem como na diminuição da taxa de reincidência criminal.
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Currently the world swiftly adapts to visual communication. Online services like YouTube and Vine show that video is no longer the domain of broadcast television only. Video is used for different purposes like entertainment, information, education or communication. The rapid growth of today’s video archives with sparsely available editorial data creates a big problem of its retrieval. The humans see a video like a complex interplay of cognitive concepts. As a result there is a need to build a bridge between numeric values and semantic concepts. This establishes a connection that will facilitate videos’ retrieval by humans. The critical aspect of this bridge is video annotation. The process could be done manually or automatically. Manual annotation is very tedious, subjective and expensive. Therefore automatic annotation is being actively studied. In this thesis we focus on the multimedia content automatic annotation. Namely the use of analysis techniques for information retrieval allowing to automatically extract metadata from video in a videomail system. Furthermore the identification of text, people, actions, spaces, objects, including animals and plants. Hence it will be possible to align multimedia content with the text presented in the email message and the creation of applications for semantic video database indexing and retrieving.
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Economics is a social science which, therefore, focuses on people and on the decisions they make, be it in an individual context, or in group situations. It studies human choices, in face of needs to be fulfilled, and a limited amount of resources to fulfill them. For a long time, there was a convergence between the normative and positive views of human behavior, in that the ideal and predicted decisions of agents in economic models were entangled in one single concept. That is, it was assumed that the best that could be done in each situation was exactly the choice that would prevail. Or, at least, that the facts that economics needed to explain could be understood in the light of models in which individual agents act as if they are able to make ideal decisions. However, in the last decades, the complexity of the environment in which economic decisions are made and the limits on the ability of agents to deal with it have been recognized, and incorporated into models of decision making in what came to be known as the bounded rationality paradigm. This was triggered by the incapacity of the unboundedly rationality paradigm to explain observed phenomena and behavior. This thesis contributes to the literature in three different ways. Chapter 1 is a survey on bounded rationality, which gathers and organizes the contributions to the field since Simon (1955) first recognized the necessity to account for the limits on human rationality. The focus of the survey is on theoretical work rather than the experimental literature which presents evidence of actual behavior that differs from what classic rationality predicts. The general framework is as follows. Given a set of exogenous variables, the economic agent needs to choose an element from the choice set that is avail- able to him, in order to optimize the expected value of an objective function (assuming his preferences are representable by such a function). If this problem is too complex for the agent to deal with, one or more of its elements is simplified. Each bounded rationality theory is categorized according to the most relevant element it simplifes. Chapter 2 proposes a novel theory of bounded rationality. Much in the same fashion as Conlisk (1980) and Gabaix (2014), we assume that thinking is costly in the sense that agents have to pay a cost for performing mental operations. In our model, if they choose not to think, such cost is avoided, but they are left with a single alternative, labeled the default choice. We exemplify the idea with a very simple model of consumer choice and identify the concept of isofin curves, i.e., sets of default choices which generate the same utility net of thinking cost. Then, we apply the idea to a linear symmetric Cournot duopoly, in which the default choice can be interpreted as the most natural quantity to be produced in the market. We find that, as the thinking cost increases, the number of firms thinking in equilibrium decreases. More interestingly, for intermediate levels of thinking cost, an equilibrium in which one of the firms chooses the default quantity and the other best responds to it exists, generating asymmetric choices in a symmetric model. Our model is able to explain well-known regularities identified in the Cournot experimental literature, such as the adoption of different strategies by players (Huck et al. , 1999), the inter temporal rigidity of choices (Bosch-Dom enech & Vriend, 2003) and the dispersion of quantities in the context of di cult decision making (Bosch-Dom enech & Vriend, 2003). Chapter 3 applies a model of bounded rationality in a game-theoretic set- ting to the well-known turnout paradox in large elections, pivotal probabilities vanish very quickly and no one should vote, in sharp contrast with the ob- served high levels of turnout. Inspired by the concept of rhizomatic thinking, introduced by Bravo-Furtado & Côrte-Real (2009a), we assume that each per- son is self-delusional in the sense that, when making a decision, she believes that a fraction of the people who support the same party decides alike, even if no communication is established between them. This kind of belief simplifies the decision of the agent, as it reduces the number of players he believes to be playing against { it is thus a bounded rationality approach. Studying a two-party first-past-the-post election with a continuum of self-delusional agents, we show that the turnout rate is positive in all the possible equilibria, and that it can be as high as 100%. The game displays multiple equilibria, at least one of which entails a victory of the bigger party. The smaller one may also win, provided its relative size is not too small; more self-delusional voters in the minority party decreases this threshold size. Our model is able to explain some empirical facts, such as the possibility that a close election leads to low turnout (Geys, 2006), a lower margin of victory when turnout is higher (Geys, 2006) and high turnout rates favoring the minority (Bernhagen & Marsh, 1997).