Um dos principais interesses na descoberta do conhecimento e mineração de dados é a indução de regras de associação. Regras de associação caracterizam as relações entre os dados a partir de um conjunto de dados estruturado com transações, onde cada transação contém um subconjunto de itens. Seja X e Y dois conjuntos de itens disjuntos, então a regra X → Y define um relacionamento, isto é, a dependência ou a co-ocorrência entre os conjuntos X e Y. Um dos algoritmos mais conhecidos para geração de regras de associação é o algoritmo Apriori. Ele explora regras de associação que respeitam o limiar suporte mínimo, ou seja, as regras devem aparecer em uma quantidade mínima de transações. Esse limiar tem a capacidade de controlar a quantidade de regras extraídas durante a mineração. Entretanto, a frequência ou suporte não consegue medir o nível de interesse de uma regra. Para medir a importância ou interesse de uma regra em relação a outras foram desenvolvidas medidas de interesse. Tais medidas são calculadas a partir das frequências dos conjuntos de itens X, Y e do par XY. Apesar das medidas de interesse realizarem uma filtragem das regras desinteressantes, elas não acarretam na diminuição no tempo de execução da mineração. Para vencer essa dificuldade, técnicas que exploram diretamente regras de associação ótimas foram desenvolvidas. Um conjunto de regras de associação ótimas é um conjunto de regras que otimiza uma determinada medida de interesse. Na literatura existem muitos trabalhos que buscam esse tipo de conjunto de regras de forma direta e eficiente. O trabalho corrente segue esta mesma direção e visou a melhoria dessa tarefa por descobrir uma quantidade arbitrária de regras de associação ótimas. As abordagens anteriores apresentam um entrave em especial, que é a utilização do algoritmo Apriori. Tal técnica realiza uma busca em largura sobre os conjuntos de itens. No entanto, as técnicas mais promissoras que descobrem regras ótimas realizam busca em profundidade sobre o espaço de busca de regras. Em virtude dessa característica, neste trabalho foi adotada a técnica FP-growth, que realiza uma busca em profundidade sobre os conjuntos de itens explorados. Além da adoção da técnica FP-growth, foram desenvolvidas novas estratégias de poda e uma nova estratégia de busca na travessia do espaço de regras. Todas essas inovações foram adicionadas aos algoritmos desenvolvidos no corrente trabalho e proporcionaram melhor eficiência (tempo de execução) em relação ao algoritmo baseline em todos os testes. Tais testes foram realizados sobre conjuntos de dados reais e artificiais. / The induction of association rules is one of the main interests in knowledge discovery and data mining. Association rules describe the relationships between data from a transactional dataset, so that each transaction contains a subset of items. Let X and Y be two disjoint itemsets, then any rule X → Y defines a relationship that represents the dependence or co-occurrence between itemsets X and Y. Apriori is the best-known algorithm to generate association rules. It generates association rules that satisfy a user defined minimum support threshold. This means the rules should occur at least in an arbitrary number of transactions from a dataset. This threshold limits the number of association rules generated by Apriori. Yet, it is not possible to measure the interest of a rule through support. For that, interestingness measures were developed to assess the importance or interest of a rule. The values of these interestingness measures are obtained through frequencies of X, Y and XY. However, it is still an expensive task mining all the association rules and then filter them according to an interestingness measure. To overcome this difficulty, techniques to induce optimal association rules have been developed. Optimal association rules are a ruleset that optimize an arbitrary interestingness measure. In the literature, there are many papers which aim at searching for optimal association rules directly and efficiently. The current MSc thesis follows this direction, aiming at improving this objective. Previous approaches share one obstacle in particular: the use of Apriori. This algorithm performs a breadth-first search on the itemsets space. However, the most promising techniques to find optimal rules perform a depth-first search on the space of rules. Hence, in this research we adopted the FP-growth algorithm, which performs a depth-first search on the itemsets space. Besides using this algorithm, new rule pruning techniques and a new search space traversing on the space rules were developed. The algorithms developed in the current research contain all these innovations. In all tests, the proposed algorithms surpassed the baseline algorithms in terms of efficiency. These tests were conducted on real and articial datasets.

Thesis advisor: Lisa Goodman / As domestic violence (DV) shelters have proliferated across the country over the last three decades, there has been a corresponding increase in the number of rules to which shelter residents must adhere. This qualitative content analysis study represents the first research to explore IPV survivors' experiences living with emergency DV shelter rules. Eight clusters emerged from interviews with 11 survivors: 1) Entering the shelter in a vulnerable state; 2) Perceiving staff-resident relationships as empowering or disempowering; 3) Making sense of the rules in the context of these relationships; 4) Experiencing staff enforcement as collaborative or hierarchical; 5) Experiencing the rules' impact on daily life; 6) Coping with rules; 7) Coping in the shelter generally; and 8) Making recommendations. Results suggest that less boundaried staff-resident relationships, less restrictive rules, and flexible, consistent, and collaborative enforcement lead to more positive experiences for residents. Recommendations are made for shelter practice and future research. / Thesis (PhD) — Boston College, 2010. / Submitted to: Boston College. Lynch School of Education. / Discipline: Counseling, Developmental, and Educational Psychology.

Thesis advisor: Richard Cobb-Stevens / Thesis advisor: Jean-Luc Solere / This dissertation attempts to locate the origins of Descartes' concept of mind in his early, unfinished treatise on scientific method, the <italic>Regulae ad directionem ingenii</italic>. It claims that one can see, in this early work, Descartes' commitment to substance dualism for methodological reasons. In order to begin an analysis of the <italic>Regulae</italic>, one must first attempt to resolve textual disputes concerning its integrity and one must understand the text as a historical work, dialectically situated in the tradition of late sixteenth and early seventeenth century thought. The dissertation provides this historical backdrop and textual sensitivity throughout, but it focuses on three main themes. First, the concept of <italic>mathesis universalis</italic> is taken to be the organizing principle of the work. This methodological principle defines a workable technique for solving mathematical problems, a means for applying mathematics to natural philosophical explanations, and a claim concerning the nature of mathematical truth. In each case, the <italic>mathesis universalis</italic> is designed to fit the innate capacities of the mind and the objects studied by <italic>mathesis</italic> are set apart from the mind as purely mechanical and geometrically representable objects. Second, Descartes' account of perceptual cognition, the principles of which are found in the <italic>Regulae</italic>, is examined. In this account, Descartes describes perception as a mechanical process up to the moment of conscious awareness. This point of awareness and the corresponding actions of the mind are, he claims, independent from mechanical principles; they are incorporeal and cannot be explained reductively. Finally, when Descartes outlines the explanatory bases of his natural science, he identifies certain "simple natures." These are the undetermined categories according to which actual things can be known. Descartes makes an explicit distinction between material simples and intellectual simples. It is argued that this distinction suggests a difference in kind between the sciences of the material world and the science or pure knowledge of the intellectual world. Though the <italic>Regulae</italic> is focused on physical or material explanations, there is a clear commitment to distinguishing this type of explanation from the explanation of mental content and mental acts. Hence, the <italic>Regulae</italic> demonstrates Descartes' early, methodological commitment to substance dualism. / Thesis (PhD) — Boston College, 2010. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Philosophy.

Neste trabalho usamos as regras de soma da QCD para calcular as massas e constantes de acoplamento ou decaimento dos estados exóticos theta+(1540) e cascata--(1862) (pentaquarks), dos mesons escalares charmosos DsJ+(2317), D0(2308) e D0(2405) e do meson axial X(3872). Os mesons foram também tratados como estados exóticos de quatro quarks (tetraquarks). Dois métodos de regra de soma foram aplicados e uma atenção especial foi dada aos limites de validade e incertezas da regra de soma. Em todos os casos encontramos resultados compatíveis com os dados experimentais existentes, mas no caso dos pentaquarks e dos mesons escalares as regras de soma têm algumas de suas condições violadas, levantando a questão sobre a existência das ressonâncias na forma em que foram propostas. Fizemos também uma previsão para um méson axial Xb, que é uma expansão para o setor botônico do modelo assumido para o X(3872). / In this work the QCD Sum Rules have been used to obtain masses and coupling or decay constants of the theta+(1540) and cascade--(1862) pentaquarks, the DsJ+(2317), D0(2308) and D0(2405) charmed scalar mesons and the X(3872) axial meson. The mesons have been treated as 4-quark exotic states (tetraquarks). Two sum rules methods have been used with special attention given to the limits and uncertainties of the sum rules. Results consistent with experimental data have been found in all cases, but some of the sum rules constraints have been violated in the calculation of the pentaquarks and scalar mesons, leaving questions about the existence of the states as they have been built here. A prediction was also made for the mass of a state expanding the model used for X(3872) to the botton sector, named Xb.

L'étude consiste à étudier les normes ou règles d'exception en droit constitutionnel. Il s'agit de s'interroger sur le point de savoir quelle réalité juridique recouvrent les lois qualifiées d'exception (textes exceptionnels) et à quelle finalité servent-elles dans l'ordre constitutionnel français? L'analyse conjointe ( textes constitutionnels, législatifs, des jurisprudences constitutionnelle, administrative ainsi que des discours de la doctrine permet de circonscrire le contenu matériel la notion d'exception. Celle-ci désigne la nonne de limitation. Plus précisément, l'exception est une limitation que le législateur fait tantôt à l'étendue de la validité d'une norme juridique de portée trop générale, tantôt à l'application stricte du droit lorsqu'une telle application détourne la règle de droit de ses propres finalités ou s'avère inefficace, inadéquate à résoudre une situation particulière. Définie comme une norme de limitation, la notion d'exception est d'un apport certain en droit constitutionnel. En effet, en contribuant à la résolution des normes antinomiques par la conciliation et non par l'abrogation, cette notion comble les lacunes et enrichit le droit constitutionnel. Étant un instrument particulièrement efficace du réformisme juridique, la notion d'exception est donc un outil d'adaptation du droit aux circonstances sociales en « douceur ». Harmonisant les normes ayant des contenus contradictoires, cette notion contribue plus généralement à la réflexion sur l'équilibre de l'ordre juridique. / The subject of the study is norms or rules of exception in constitutional law. We have to examine what is legal reality of laws qualified as "rules of exception" (special text) and what purpose they serve in the French constitutional order. The joint analysis of constitutional and legislative texts, constitutional and administrative jurisprudence, as weIl as doctrinal speech allows to define the material content of the notion of exception. This concept refers to the norm of limitation. SpecificaIly, the exception is a limitation that is applied by the legislator either to the scope of the validity of a legal norm too broad or to implementation of the law when this implementation diverts the rule of law of its purposes or is ineffective, inadequate to solve a particular situation. Defmed as a limitation norm, the notion of exception is a real contribution to constitutional law. lndeed, by contributing to the resolution of antinomy norms by conciliation and not by repealing, this concept f1l1s gaps and entiches constitutionallaw. Being a particularly effective instrument of legal reformism, the notion of exception is a tool to adapt the law to the social circumstances by "softness". Harmonizing standards with conflicting contents, this concept more generally contributes to the discussion on the balance of the legalorder.

Transfer models provide a viable means of determining which skills a student needs in order to solve a given problem. However, constructing a good fitting transfer model requires a lot of trial and error. The main goal of this thesis was to develop a procedure for developing better fit transfer models for intelligent tutoring systems. The procedure implements a search method using association rules as a means of guiding the search. The association rules are mined from the instances in the dataset that the transfer model predicts incorrectly. The association rules found in the mining process determines what operation to perform on the current transfer model. Our search algorithm using association rules was compared to a blind search method that finds all possible transfer models for a given set of factors. Our search process was able to find statistically similar models to the ones the blind search method finds in a considerably shorter amount of time. The difference in times between our search process and the blind search method is days to minutes. Being able to find good transfer models quicker will help intelligent tutor system builders as well as cognitive science researchers better assess what makes certain problems hard and other problems easy for students.

The systematic interaction of software developers with the business domain experts that are usually no software developers is crucial to software system maintenance and creation and has surfaced as the big challenge of modern software engineering. Existing frameworks promoting the typical programming languages with artificial syntax are suitable to be processed by computers but do not cater to domain experts, who are used to documents written in natural language as a means of interaction. Other frameworks that claim to be fully automated, such as those using natural language processing, are too imprecise to handle the typical requirements documents written in heterogeneous natural language flavours. In this thesis, a framework is proposed that can support the specification of business rules that is, on the one hand, understandable for nonprogrammers and on the other hand semantically founded, which enables computer processability. This is achieved by the novel language Adaptive Business Process and Rule Integration Language (APRIL). Specifications in APRIL can be written in a style close to natural language and are thus suitable for humans, which was empirically evaluated with a representative group of test persons. A useful and uncommon feature of APRIL is the ability to define reusable abstract mixfix operators as sentence patterns, that can mimic natural language. The semantic underpinning of the mixfix operators is achieved by customizable atomic formulas, allowing to tailor APRIL to specific domains. Atomic formulas are underpinned by a denotational semantics, which is based on Tempura (executable subset of Interval Temporal Logic (ITL)) to describe behaviour and the Object Constraint Language (OCL) to describe invariants and pre- and postconditions. APRIL statements can be used as the basis for automatically generating test code for software systems. An additional aspect of enhancing the quality of specification documents comes with a novel formal method technique (ISEPI) applicable to behavioural business rules semantically based on Propositional Interval Temporal Logic (PITL) and complying with the newly discovered 2-to-1 property. This work discovers how the ISE subset of ISEPI can be used to express complex behavioural business rules in a more concise and understandable way. The evaluation of ISE is done by an example specification taken from the car industry describing system behaviour, using the tools MONA and PITL2MONA. Finally, a methodology is presented that helps to guide a continuous transformation starting from purely natural language business rule specification to the APRIL specification which can then be transformed to test code. The methodologies, language concepts, algorithms, tools and techniques devised in this work are part of the APRIL-framework.

Atualmente, os avanços tecnológicos, principalmente nas áreas de controle e automação, facilitam a inclusão de alarmes em sistemas de supervisão de plantas industriais. É possível incluir um número quase que ilimitado de alarmes com variação de tipos para cada ponto de medição de um processo. Consequentemente, o volume de informações cresce significativamente e isso pode ser prejudicial, uma vez que limita a habilidade do operador no gerenciamento de anomalias e pode exceder sua capacidade de realizar ações eficazes durante o funcionamento do processo. Este trabalho apresenta um estudo sobre modelagem semântica de contexto e utiliza uma base histórica de informações de eventos para análise de padrões. Dessa forma, o intuito é, por meio dos dados de contexto, obter conhecimento útil para inferência e determinação da situação. Uma aplicação real onde são investigados eventos ocorridos em uma planta de uma usina térmica de geração de energia elétrica é usado como estudo de caso para aplicar as ideias desenvolvidas bem como para validar a proposta. Decorrente desse estudo, é proposta uma ontologia de domínio específico implementada a partir de um modelo semântico de contexto. Por fim, é apresentada uma implementação de regras semânticas. / Nowadays, technological advance, especially in the areas of control and automation, make it easy alarm inclusion in supervision of industrial plant systems. You can include a number almost unlimited of alarms with different types for each measurement point of a process. Consequently, the volume of information grows significantly and this can be harmful since it limits the ability of the operator in managing anomalies and may exceed its ability to carry out effective actions during operation of the process. This work presents a study of semantic modeling of context and uses historical bases event information to identify patterns. Thus, the intention is use this context data to obtain useful knowledge for inference and define the situation. A real application where events of a thermal power plant for electricity generation are investigated is used as a case study to apply the ideas developed and to validate the proposal. As a Result of this study, it is proposed a specific domain ontology implemented from a semantic model of context. Finally, it is presented an implementation of semantic rules.

This paper empirically assesses determinants of countries' fiscal rules suggested by the political science, sociology, and economics literature. We find several of these variables to be related to the stringency of fiscal rules, providing indirect evidence for the relevance of governments' deficit bias. These determinants may also serve as instruments in models with (endogenous) fiscal rules as explanatory variable.

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