Thesis (Ph.D.)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / The problem of the dissertation is to examine and describe the rib-pattern and the concept of judgment in the Book of Psalms because of the emphasis which recent interpreters have placed on the Psalter as the hymn book of the cultic community. The primary concern of the dissertation is to show that in the Psalms, the concept of judgment is uniquely related to the temple and to the priesthood, and to point out the various ways in which Yahweh's judgment as seen in the Psalter affected the lives of the people of Israel. [TRUNCATED] / 2031-01-01

The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Labs. This new learning algorithm can be seen as an alternative training technique for Polynomial, Radial Basis Function and Multi-Layer Perceptron classifiers. An interesting property of this approach is that it is an approximate implementation of the Structural Risk Minimization (SRM) induction principle. The derivation of Support Vector Machines, its relationship with SRM, and its geometrical insight, are discussed in this paper. Training a SVM is equivalent to solve a quadratic programming problem with linear and box constraints in a number of variables equal to the number of data points. When the number of data points exceeds few thousands the problem is very challenging, because the quadratic form is completely dense, so the memory needed to store the problem grows with the square of the number of data points. Therefore, training problems arising in some real applications with large data sets are impossible to load into memory, and cannot be solved using standard non-linear constrained optimization algorithms. We present a decomposition algorithm that can be used to train SVM's over large data sets. The main idea behind the decomposition is the iterative solution of sub-problems and the evaluation of, and also establish the stopping criteria for the algorithm. We present previous approaches, as well as results and important details of our implementation of the algorithm using a second-order variant of the Reduced Gradient Method as the solver of the sub-problems. As an application of SVM's, we present preliminary results we obtained applying SVM to the problem of detecting frontal human faces in real images.

Cette thèse traite de la restructuration des documents déstructurés de type PDF contenant des éléments graphiques tels que les schémas, les plans et les dessins, dans l’objectif de les restructurer. En nous appuyant sur la méthode KDD (Knowledge Discovery in Database) pour la restructuration des données, nous introduisons la méthode (A)KDD (Antropocentric Knowledge Discovery in Database) que nous avons développé et qui est dérivée de la méthode KDD en ajoutant l’aspect incrémental et l’aspect centré sur l’utilisateur. Nous présentons, en particulier, une technique fondée sur le principe du tri par paquet pour extraire efficacement les symboles graphiques contenus dans un document PDF. Elle est comparée aux résultats de Puglissi sur les chaînes de caractères. Puis, nous formulons l’hypothèse selon laquelle la prise en compte de l’ordre chronologique présent dans les fichiers PDF dans le processus incrémental améliore la restructuration des documents. Nous montrons la validité de cette hypothèse sur un certain nombre d’exemples. Enfin, nous montrons l’efficacité du processus pour identifier les symboles en même temps que les équipotentielles. Le mémoire se conclut en montrant les avancées et les limites de la solution de la méthode (A)KDD et nous proposons des perspectives. / This thesis deals with the restructuring of unstructured PDF documents containing graphical elements such as schematics, plans and drawings, with the aim of restructuring them. Using the KDD (Knowledge Discovery in Database) method for data restructuring, we introduce the (A) KDD (Antropocentric Knowledge Discovery in Database) method that we developed which is derived from the KDD method by adding an incremental aspect and an user-centered approach. We present, in particular, a technique based on on the bucket sort algorithm pattern in order to extract with efficiency graphic symbols contained in a PDF file. It is compared to the results obtained by Puglissi on strings. Then, we formulate the hypothesis:”taking into account the chronological order present in the PDF files in the incremental process improves the restructuring of the documents”. We illustrate the validity of this hypothesis on several examples. Finally, we show the efficiency of the process in the identification of the symbols at the same time as the equipotentials. The thesis concludes by showing the advances and the limits of the solution of the (A) KDD method and we propose some perspectives.

Design patterns are widely used in game design, especially in action games. Design patterns can be seen as a group of concluded gameplay. A stealth game is a video game genre that rewards the player for using stealth (conceal avatar of player in order to avoid enemies) to overcome antagonists. In some cases there is a conflict between difficulty and game experience in stealth game. In order to solve this problem, we researched design patterns in stealth games. We observed a set of stealth game design patterns from three different stealth games. The collection used a different template of game design pattern.Then we created a questionnaire to collect opinions from designers that have experience in stealth game area. Based on such data, we designed and created a prototype of application. Unlike other websites or books, the application shown game design pattern for a single type of game(stealth game). From the application designers can check stealth game design patterns based on design document. The application can introduce stealth game design patterns to designers, and show how to use them in stealth game design.

INTRODUÇÃO: O transtorno de déficit de atenção com hiperatividade (TDAH) persistente em adultos apresenta prevalência significativa na população geral. Nota-se também uma alta taxa de comorbidade com outros quadros psiquiátricos, especialmente o transtorno bipolar (TB). Entretanto, ainda hoje discutem-se as próprias definições do TDAH e os limites da comorbidade TDAH+TB, que poderia ser uma extensão dos sintomas do espectro bipolar, uma sobreposição dos dois transtornos ou uma entidade separada com substrato neurobiológico distinto. Impõe-se, assim, a pesquisa de biomarcadores válidos com potencial aplicação na prática clínica. O surgimento recente de técnicas de classificação de padrões morfológicos cerebrais complexos possibilita uma investigação mais direcionada de biomarcadores, buscando em cada indivíduo um conjunto de características que seja capaz de classificá-lo como pertencente a um determinado grupo. OBJETIVOS: Aplicar, de maneira inédita, a técnica de reconhecimento automatizado de padrão aos dados de neuroimagem de pacientes adultos sem tratamento prévio com diagnóstico de TDAH com início na infância, TB, TDAH+TB e controles saudáveis (CS), em busca de assinaturas neuroanatômicas associadas a estes transtornos. MÉTODOS: Três grupos de adultos nunca tratados compostos de 67 sujeitos com TDAH, 30 sujeitos com TB e 16 sujeitos preenchendo critérios diagnósticos para ambos os transtornos; e uma amostra de CS (n=66), foram submetidos ao exame de ressonância magnética (RM) estrutural e de imagem por tensor de difusão (diffusion tensor imaging; DTI). Através de um método automatizado, regiões de interesse foram posicionadas ao longo de todo o cérebro e através destas foram obtidas medidas cerebrais a partir das imagens multimodais. Tais medidas foram usadas como dados de entrada para um classificador não-linear baseado em support vector machine (SVM). Comparações entre todos os pacientes e CS foram feitas através de subgrupos pareados individualmente para gênero e idade e pareados entre os grupos para nível socioeconômico e escolaridade. As medidas de desempenho diagnóstico foram analisadas com o auxílio de curvas receiver operating characteristic (ROC). RESULTADOS: As análises de classificação entre todos os subgrupos apresentaram resultados expressivamente acima do acaso, com exceção da comparação entre os pacientes com TB e os CS (p=0,09). A comparação entre os subgrupos com TDAH e CS apresentou medidas de área sob a curva (AUC) e acurácia diagnóstica de até 0,71 e 66,2% (p=0,003). A comparação entre os subgrupos com TDAH e TB obteve AUC e acurácia diagnóstica de até 0,78 e 70,2% (p=0,01). As análises de classificação entre os pacientes TDAH+TB e todos os outros subgrupos resultaram em valores de até 0,89 e 80,5% (p=0,0009) de AUC e acurácia diagnóstica respectivamente. CONCLUSÃO: Os resultados fornecem endosso neurobiológico para a validade do diagnóstico clinico de TDAH em adultos. As características cerebrais mostraram-se suficientemente fortes para o diagnóstico diferencial entre o TDAH e o TB e também reforçam a hipótese de que a associação TDAH+TB deve ser compreendida como uma entidade neurobiológica distinta. Restam ainda relevantes dificuldades na busca de biomarcadores para a caracterização do TB. As assinaturas neuroanatômicas identificadas neste estudo podem fornecer informações objetivas adicionais e valiosas, servindo como base para estudos futuros que avaliem sua possível influência em decisões terapêuticas dos pacientes apresentando sintomas do espectro TDAH e da comorbidade TDAH+TB / INTRODUCTION: Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent condition in the general adult population. Also important is its high rate of comorbidity with other psychiatric disorders, particularly bipolar disorder (BD). However, not only the definition of ADHD is still a matter of discussion but also the limits of the ADHD+BD comorbidity; such comorbidity may be interpreted as a continuum spectrum of BD, an overlap of symptoms, or a separate diagnostic entity with a distinct neurobiological substrate. Therefore, further search for valid biomarkers with potential application in clinical practice is still required. The recent development of high-dimensional pattern recognition techniques has allowed targeted investigations of biomarkers, searching for sets of characteristics that could be used to classify each patient in a particular group. OBECTIVES: To apply, for the first time in the literature, machine learning-based pattern recognition methods to neuroimaging data obtained in never-treated adults with childhood-onset ADHD, BD, ADHD+BD and healthy controls (HC), searching for different neuroanatomical signatures associated with each disorder. METHODS: Three groups of never treated adults as following: 67 ADHD patients, 30 BD patients, 16 patients fulfilling diagnostic criteria for both disorders; and a sample of HC (n=66) underwent structural magnetic resonance imaging (MRI) and diffusion magnetic resonance imaging (DTI) acquisitions. A support vector machine (SVM) classifier with non-linear kernel was applied on multi-modal image features extracted on regions-of-interest placed across the whole brain. Comparisons among all patients and controls were carried out through subgroups individually matched for gender and age, and group-matched for years of education and socio-economic status. Diagnostic performance measures were evaluated by computing receiver operating characteristic (ROC) curves. RESULTS: All results on classification analyses were clearly significant above chance level, except in the comparison analysis between BD patients and HC (p=0.09). The comparison between ADHD and HC subgroups afforded area under the curve (AUC) measures and diagnostic accuracy of up to 0.71 and 66.2% (p=0.003). Comparison between ADHD and BD subgroups achieved AUC and diagnostic accuracy of up to 0.78 and 70.2% (p=0.01). Classification analysis between ADHD+BD patients and the other subgroups yielded AUC and diagnostic accuracy values of up to 0.89 and 80.5% (p=0.0009). CONCLUSION: The present study provides neurobiological endorsement to the validity of the clinically-based diagnosis of ADHD in adults. Brain features were strong enough to the differential diagnosis between ADHD and BD, as well as to reinforce the hypothesis that ADHD+BD may represent a distinct neurobiological entity. However, relevant challenges persist regarding the search for biomarkers for BD. The neuroanatomical signatures identified herein may provide additional, objective information, paving the way for future studies assessing its influence in treatment decisions in adults with ADHD and ADHD+BD spectrum symptoms

Complex patterns arise in many extended nonlinear nonequilibrium systems in physics, chemistry and biology. Information extraction from these complex patterns is a challenge and has been a main subject of research for many years. We study patterns in Rayleigh-Benard convection (RBC) acquired from our laboratory experiments to develop new characterization techniques for complex spatio-temporal patterns. Computational homology, a new topological characterization technique, is applied to the experimental data to investigate dynamics by quantifying convective patterns in a unique way. The homology analysis is used to detect symmetry breakings between hot and cold flows as a function of thermal driving in experiments, where other conventional techniques, e.g., curvature and wave-number distribution, failed to reveal this asymmetry. Furthermore, quantitative information is acquired from the outputs of homology to identify different spatio-temporal states. We use this information to obtain a reduced dynamical description of spatio-temporal chaos to investigate extensivity and physical boundary effects in RBC. The results from homological analysis are also compared to other dimensionality reduction techniques such as Karhunen-Loeve decomposition and Fourier analysis.

INTRODUÇÃO: O transtorno de déficit de atenção com hiperatividade (TDAH) persistente em adultos apresenta prevalência significativa na população geral. Nota-se também uma alta taxa de comorbidade com outros quadros psiquiátricos, especialmente o transtorno bipolar (TB). Entretanto, ainda hoje discutem-se as próprias definições do TDAH e os limites da comorbidade TDAH+TB, que poderia ser uma extensão dos sintomas do espectro bipolar, uma sobreposição dos dois transtornos ou uma entidade separada com substrato neurobiológico distinto. Impõe-se, assim, a pesquisa de biomarcadores válidos com potencial aplicação na prática clínica. O surgimento recente de técnicas de classificação de padrões morfológicos cerebrais complexos possibilita uma investigação mais direcionada de biomarcadores, buscando em cada indivíduo um conjunto de características que seja capaz de classificá-lo como pertencente a um determinado grupo. OBJETIVOS: Aplicar, de maneira inédita, a técnica de reconhecimento automatizado de padrão aos dados de neuroimagem de pacientes adultos sem tratamento prévio com diagnóstico de TDAH com início na infância, TB, TDAH+TB e controles saudáveis (CS), em busca de assinaturas neuroanatômicas associadas a estes transtornos. MÉTODOS: Três grupos de adultos nunca tratados compostos de 67 sujeitos com TDAH, 30 sujeitos com TB e 16 sujeitos preenchendo critérios diagnósticos para ambos os transtornos; e uma amostra de CS (n=66), foram submetidos ao exame de ressonância magnética (RM) estrutural e de imagem por tensor de difusão (diffusion tensor imaging; DTI). Através de um método automatizado, regiões de interesse foram posicionadas ao longo de todo o cérebro e através destas foram obtidas medidas cerebrais a partir das imagens multimodais. Tais medidas foram usadas como dados de entrada para um classificador não-linear baseado em support vector machine (SVM). Comparações entre todos os pacientes e CS foram feitas através de subgrupos pareados individualmente para gênero e idade e pareados entre os grupos para nível socioeconômico e escolaridade. As medidas de desempenho diagnóstico foram analisadas com o auxílio de curvas receiver operating characteristic (ROC). RESULTADOS: As análises de classificação entre todos os subgrupos apresentaram resultados expressivamente acima do acaso, com exceção da comparação entre os pacientes com TB e os CS (p=0,09). A comparação entre os subgrupos com TDAH e CS apresentou medidas de área sob a curva (AUC) e acurácia diagnóstica de até 0,71 e 66,2% (p=0,003). A comparação entre os subgrupos com TDAH e TB obteve AUC e acurácia diagnóstica de até 0,78 e 70,2% (p=0,01). As análises de classificação entre os pacientes TDAH+TB e todos os outros subgrupos resultaram em valores de até 0,89 e 80,5% (p=0,0009) de AUC e acurácia diagnóstica respectivamente. CONCLUSÃO: Os resultados fornecem endosso neurobiológico para a validade do diagnóstico clinico de TDAH em adultos. As características cerebrais mostraram-se suficientemente fortes para o diagnóstico diferencial entre o TDAH e o TB e também reforçam a hipótese de que a associação TDAH+TB deve ser compreendida como uma entidade neurobiológica distinta. Restam ainda relevantes dificuldades na busca de biomarcadores para a caracterização do TB. As assinaturas neuroanatômicas identificadas neste estudo podem fornecer informações objetivas adicionais e valiosas, servindo como base para estudos futuros que avaliem sua possível influência em decisões terapêuticas dos pacientes apresentando sintomas do espectro TDAH e da comorbidade TDAH+TB / INTRODUCTION: Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent condition in the general adult population. Also important is its high rate of comorbidity with other psychiatric disorders, particularly bipolar disorder (BD). However, not only the definition of ADHD is still a matter of discussion but also the limits of the ADHD+BD comorbidity; such comorbidity may be interpreted as a continuum spectrum of BD, an overlap of symptoms, or a separate diagnostic entity with a distinct neurobiological substrate. Therefore, further search for valid biomarkers with potential application in clinical practice is still required. The recent development of high-dimensional pattern recognition techniques has allowed targeted investigations of biomarkers, searching for sets of characteristics that could be used to classify each patient in a particular group. OBECTIVES: To apply, for the first time in the literature, machine learning-based pattern recognition methods to neuroimaging data obtained in never-treated adults with childhood-onset ADHD, BD, ADHD+BD and healthy controls (HC), searching for different neuroanatomical signatures associated with each disorder. METHODS: Three groups of never treated adults as following: 67 ADHD patients, 30 BD patients, 16 patients fulfilling diagnostic criteria for both disorders; and a sample of HC (n=66) underwent structural magnetic resonance imaging (MRI) and diffusion magnetic resonance imaging (DTI) acquisitions. A support vector machine (SVM) classifier with non-linear kernel was applied on multi-modal image features extracted on regions-of-interest placed across the whole brain. Comparisons among all patients and controls were carried out through subgroups individually matched for gender and age, and group-matched for years of education and socio-economic status. Diagnostic performance measures were evaluated by computing receiver operating characteristic (ROC) curves. RESULTS: All results on classification analyses were clearly significant above chance level, except in the comparison analysis between BD patients and HC (p=0.09). The comparison between ADHD and HC subgroups afforded area under the curve (AUC) measures and diagnostic accuracy of up to 0.71 and 66.2% (p=0.003). Comparison between ADHD and BD subgroups achieved AUC and diagnostic accuracy of up to 0.78 and 70.2% (p=0.01). Classification analysis between ADHD+BD patients and the other subgroups yielded AUC and diagnostic accuracy values of up to 0.89 and 80.5% (p=0.0009). CONCLUSION: The present study provides neurobiological endorsement to the validity of the clinically-based diagnosis of ADHD in adults. Brain features were strong enough to the differential diagnosis between ADHD and BD, as well as to reinforce the hypothesis that ADHD+BD may represent a distinct neurobiological entity. However, relevant challenges persist regarding the search for biomarkers for BD. The neuroanatomical signatures identified herein may provide additional, objective information, paving the way for future studies assessing its influence in treatment decisions in adults with ADHD and ADHD+BD spectrum symptoms

Les échangeurs de chaleur constitués de microcanaux parallèles sont considérés une bonne solution technologique pour dissiper de grands flux de chaleur dans les composants et les systèmes miniaturisés. D’une manière générale cette réduction de taille permet une diminution des coûts des matériaux et l'utilisation de plus faible quantité de fluides frigorigènes pour les systèmes de refroidissement. Cette étude est divisée en deux parties complémentaires A et B. Elles visent à étudier le comportement thermo-hydraulique dans les échangeurs de chaleur constitués de microcanaux pour une meilleure compréhension des transferts de chaleur et des écoulements diphasiques dans les évaporateurs miniatures. Dans la partie A, nous étudions l'ébullition convective du réfrigérant R134a dans un mini échangeur composé de neuf microcanaux parallèles de section transversale circulaire, placés horizontalement, avec un diamètre interne de 0,77 mm et longueur et 150 mm. Les résultats expérimentaux montrent que la configuration d'écoulement a une forte influence sur le coefficient de transfert de chaleur, et que différents mécanismes de transfert de chaleur ont lieu dans chacune de ces configurations d'écoulement. En revanche la perte de pression est une fonction directe de la vitesse massique, du titre de vapeur et de la pression du système. La partie B, porte sur l’analyse de la distribution de l'écoulement diphasique en l’absence de transferts de chaleur et de changement de phase liquide-vapeur. A partir de ces résultats nous montrons que les effets du titre de gaz sur la répartition du liquide change considérablement selon la position de l'ensemble (tube d'alimentation, distributeur-canaux). / Heat exchangers consisting of parallel micro-channels are considered a good technological solution in response to the increasing demand for compact systems, which require high heat flux dissipation, ensuring a decrease in the material costs and the use of a lower quantity of refrigerants. The aim of this study was to investigate the thermo-hydraulic behavior inside these components provided by microchannels. This study is divided into two experimental studies (A and B) which are complementary. In part A, the convective boiling of the refrigerant R134a is analyzed within nine parallel microchannels of circular cross section, positioned horizontally, with internal diameter and length of 0.77 mm and 150 mm, respectively. The experimental results show that the flow pattern has a strong influence on the heat transfer coefficient, and that different heat transfer mechanisms are associated with each of the flow patterns observed, whereas the frictional pressure drop is a direct function of the mass velocity, vapor quality and pressure of the system. In part B, the two-phase flow distribution, using as the working fluid a mixture of air and water, is analyzed inside a circular header coupled to nine branched parallel microchannels of circular cross-section with internal diameter and length of 0.8 mm and 150 mm, respectively. The results show that the effect of the gas quality on the liquid distribution changes considerably depending on the configuration (feeder tube-header-channels).