72 resultados para Modular reasoning
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This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.
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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.
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This thesis justifies the need for and develops a new integrated model of practical reasoning and argumentation. After framing the work in terms of what is reasonable rather than what is rational (chapter 1), I apply the model for practical argumentation analysis and evaluation provided by Fairclough and Fairclough (2012) to a paradigm case of unreasonable individual practical argumentation provided by mass murderer Anders Behring Breivik (chapter 2). The application shows that by following the model, Breivik is relatively easily able to conclude that his reasoning to mass murder is reasonable – which is understood to be an unacceptable result. Causes for the model to allow such a conclusion are identified as conceptual confusions ingrained in the model, a tension in how values function within the model, and a lack of creativity from Breivik. Distinguishing between dialectical and dialogical, reasoning and argumentation, for individual and multiple participants, chapter 3 addresses these conceptual confusions and helps lay the foundation for the design of a new integrated model for practical reasoning and argumentation (chapter 4). After laying out the theoretical aspects of the new model, it is then used to re-test Breivik’s reasoning in light of a developed discussion regarding the motivation for the new place and role of moral considerations (chapter 5). The application of the new model shows ways that Breivik could have been able to conclude that his practical argumentation was unreasonable and is thus argued to have improved upon the Fairclough and Fairclough model. It is acknowledged, however, that since the model cannot guarantee a reasonable conclusion, improving the critical creative capacity of the individual using it is also of paramount importance (chapter 6). The thesis concludes by discussing the contemporary importance of improving practical reasoning and by pointing to areas for further research (chapter 7).
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O recurso à monitorização do comportamento dos programas durante a execução é necessário em diversos contextos de aplicação. Por exemplo, para verificar a utilização dos recursos computacionais durante a execução, para calcular métricas que permitam melhor definir o perfil da aplicação ou para melhor identificar em que pontos da execução estão as causas de desvios do comportamento desejado de um programa e, noutros casos, para controlar a configuração da aplicação ou do sistema que suporta a sua execução. Esta técnica tem sido aplicada, quer no caso de programas sequenciais, quer se trate de programas distribuídos. Em particular, no caso de computações paralelas, dada a complexidade devida ao seu não determinismo, estas técnicas têm sido a melhor fonte de informação para compreender a execução da aplicação, quer em termos da sua correcção, quer na avaliação do seu desempenho e utilização dos recursos computacionais. As principais dificuldades no desenvolvimento e na adopção de ferramentas de monitorização, prendem-se com a complexidade dos sistemas de computação paralela e distribuída e com a necessidade de desenvolver soluções específicas para cada plataforma, para cada arquitectura e para cada objectivo. No entanto existem funcionalidades genéricas que, se presentes em todos os casos, podem ajudar ao desenvolvimento de novas ferramentas e à sua adaptação a diferentes ambientes computacionais. Esta dissertação propõe um modelo para suportar a observação e o controlo de aplicações paralelas e distribuídas (DAMS - Distributed ApplicationsMonitoring System). O modelo define uma arquitectura abstracta de monitorização baseada num núcleo mínimo sobre o qual assentam conjuntos de serviços que realizam as funcionalidades pretendidas em cada cenário de utilização. A sua organização em camadas de abstracção e a capacidade de extensão modular, permitem suportar o desenvolvimento de conjuntos de funcionalidades que podem ser partilhadas por distintas ferramentas. Por outro lado, o modelo proposto facilita o desenvolvimento de ferramentas de observação e controlo, sobre diferentes plataformas de suporte à execução. Nesta dissertação, são apresentados exemplos da utilização do modelo e da infraestrutura que o suporta, em diversos cenários de observação e controlo. Descreve-se também a experimentação realizada, com base em protótipos desenvolvidos sobre duas plataformas computacionais distintas.
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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores
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This article is a short introduction on how to use Modellus (a computer package that is freely available on the Internet and used in the IOP Advancing Physics course) to build physics games using Newton’s laws, expressed as differential equations. Solving systems of differential equations is beyond most secondary-school or first-year college students. However, with Modellus, the solution is simply the output of the usual physical reasoning: define the force law, compute its magnitude and components, use it to obtain the acceleration components, then the velocity components and, finally, use the velocity components to find the coordinates.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática.
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Dissertação de Mestrado em Engenharia Informática
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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Educação Médica 1991; 2 (2): 29-40
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Journal of Bacteriology (Apr 2006) 3024-3036
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores