abstract: Bruegel is a four movement composition inspired by the paintings and engravings of Flemish artist Pieter Bruegel the Elder (1525-1569). It is scored for Bass Clarinet in Bb, Electric Guitar, One Percussionist (Glockenspiel, Woodblock, Snare, Kick Drum, and Brake Drums), Piano and String Quartet. Each movement explores a painting or engraving from Bruegel’s catalog of works and attempts to embody each piece of art through the use of certain compositional techniques. The Cripples (Movement I) explores layered rhythms and disjunct melodic fragments which play on the idea of Bruegel’s painting of crippled men trampling over each other and stumbling. Small moments of balance are found throughout only to be lost. Patience (Movement II) is based on an early engraving of Bruegel, which depicts a lone woman who represents a virtue, in this case patience, surrounded by sin and vices. Juxtaposed textures are presented with patience eventually finding itself victorious to temptation. Children’s Games (Movement III) explores a painting which depicts a large number of children playing a plethora of different games. The movement uses graphic notation and plays with the idea of games to create a compositional “game” for the ensemble. Big Fish Eat Little Fish (Movement IV) depicts a large fish eating several smaller fish. A process is introduced which plays on the idea of increasing density and lasts for the bulk of the movement. / Dissertation/Thesis / Masters Thesis Music 2016

abstract: Performances of three prominent, full-time brass chamber ensembles (the Canadian Brass, Mnozil Brass, and Trompettes de Lyon), are studied for their inclusion of entertainment outside the bounds of traditional music performance. The various additions include acting, choreography, novel changes in instrumentation, props, technical exhibitions, audience interaction, and inherently humorous arrangements. These are identified, categorized, and analyzed for frequency of use. Representative scenes from each ensemble are compared for similarities with the intent of establishing general rules for the usage of each non-traditional element. Differences in overall show structure, compared to that of traditional chamber ensembles, are also discussed. In a separate component of this project, the author wrote an original show based on the above research, and performed it with the Grand Valley State University Faculty Brass Quintet. The process of creation and observations of rehearsal and performance settings are included in this document to guide the efforts of other prospective show-writers. / Dissertation/Thesis / Doctoral Dissertation Music 2017

abstract: Ensemble learning methods like bagging, boosting, adaptive boosting, stacking have traditionally shown promising results in improving the predictive accuracy in classification. These techniques have recently been widely used in various domains and applications owing to the improvements in computational efficiency and distributed computing advances. However, with the advent of wide variety of applications of machine learning techniques to class imbalance problems, further focus is needed to evaluate, improve and optimize other performance measures such as sensitivity (true positive rate) and specificity (true negative rate) in classification. This thesis demonstrates a novel approach to evaluate and optimize the performance measures (specifically sensitivity and specificity) using ensemble learning methods for classification that can be especially useful in class imbalanced datasets. In this thesis, ensemble learning methods (specifically bagging and boosting) are used to optimize the performance measures (sensitivity and specificity) on a UC Irvine (UCI) 130 hospital diabetes dataset to predict if a patient will be readmitted to the hospital based on various feature vectors. From the experiments conducted, it can be empirically concluded that, by using ensemble learning methods, although accuracy does improve to some margin, both sensitivity and specificity are optimized significantly and consistently over different cross validation approaches. The implementation and evaluation has been done on a subset of the large UCI 130 hospital diabetes dataset. The performance measures of ensemble learners are compared to the base machine learning classification algorithms such as Naive Bayes, Logistic Regression, k Nearest Neighbor, Decision Trees and Support Vector Machines. / Dissertation/Thesis / Masters Thesis Computer Science 2017

Missense mutations account for more than 50% of the mutations known to be involved in human inherited diseases. Missense classification is a challenging task that involves sequencing of the genome, identifying the variations, and assessing their deleteriousness. This is a very laborious, time and cost intensive task to be carried out in the laboratory. Advancements in bioinformatics have led to several large-scale next-generation genome sequencing projects, and subsequently the identification of genome variations. Several studies have combined this data with information on established deleterious and neutral variants to develop machine learning based classifiers. There are significant issues with the missense classifiers due to which missense classification is still an open area of research. These issues can be classified under two broad categories: (a) Dataset overlap issue - where the performance estimates reported by the state-of-the-art classifiers are overly optimistic as they have often been evaluated on datasets that have significant overlaps with their training datasets. Also, there is no comparative analysis of these tools using a common benchmark dataset that contains no overlap with the training datasets, therefore making it impossible to identify the best classifier among them. Also, such a common benchmark dataset is not available. (b) Inadequate capture of vital biological information of the protein and mutations - such as conservation of long-range amino acid dependencies, changes in certain physico-chemical properties of the wild-type and mutant amino acids, due to the mutation. It is also not clear how to extract and use this information. Also, some classifiers use structural information that is not available for all proteins. In this study, we compiled a new dataset, containing around 2 - 15% overlap with the popularly used training datasets, with 18,036 mutations in 5,642 proteins. We reviewed and evaluated 15 state-of-the-art missense classifiers - SIFT, PANTHER, PROVEAN, PhD-SNP, Mutation Assessor, FATHMM, SNPs&GO, SNPs&GO3D, nsSNPAnalyzer, PolyPhen-2, SNAP, MutPred, PON-P2, CONDEL and MetaSNP, using the six metrics - accuracy, sensitivity, specificity, precision, NPV and MCC. When evaluated on our dataset, we observe huge performance drops from what has been claimed. Average drop in the performance for these 13 classifiers are around 15% in accuracy, 17% in sensitivity, 14% in specificity, 7% in NPV, 24% in precision and 30% in MCC. With this we show that the performance of these tools is not consistent on different datasets, and thus not reliable for practical use in a clinical setting. As we observed that the performance of the existing classifiers is poor in general, we tried to develop a new classifier that is robust and performs consistently across datasets, and better than the state-of-the-art classifiers. We developed a novel method of capturing long-range amino acid dependency conservation by boosting the conservation frequencies of substrings of amino acids of various lengths around the mutation position using AdaBoost learning algorithm. This score alone performed equivalently to the sequence conservation based tools in classifying missense mutations. Popularly used sequence conservation properties was combined with this boosted long-range dependency conservation scores using AdaBoost algorithm. This reduced the class bias, and improved the overall accuracy of the classifier. We trained a third classifier by incorporating changes in 21 important physico-chemical properties, due to the mutation. In this case, we observed that the overall performance further improved and the class bias further reduced. The performance of our final classifier is comparable with the state-of-the-art classifiers. We did not find any significant improvement, but the class-specific accuracies and precisions are marginally better by around 1-2% than those of the existing classifiers. In order to understand our classifier better, we dissected our benchmark dataset into: (a) seen and unseen proteins, and (b) pure and mixed proteins, and analysed the performance in detail. Finally we concluded that our classifier performs consistently across each of these categories of seen, unseen, pure and mixed protein.

abstract: This dissertation investigates the classification of systemic lupus erythematosus (SLE) in the presence of non-SLE alternatives, while developing novel curve classification methodologies with wide ranging applications. Functional data representations of plasma thermogram measurements and the corresponding derivative curves provide predictors yet to be investigated for SLE identification. Functional nonparametric classifiers form a methodological basis, which is used herein to develop a) the family of ESFuNC segment-wise curve classification algorithms and b) per-pixel ensembles based on logistic regression and fused-LASSO. The proposed methods achieve test set accuracy rates as high as 94.3%, while returning information about regions of the temperature domain that are critical for population discrimination. The undertaken analyses suggest that derivate-based information contributes significantly in improved classification performance relative to recently published studies on SLE plasma thermograms. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2018

Le projet de recherche présente un travail monographique sur l'architecte français Maurice Novarina, originaire de Haute-Savoie, qui a réalisé, tout au long du XXe siècle, d'importantes commandes publiques ; des églises – pour lesquelles il est le plus connu – et plus de 30 000 logements conçus lors des grandes opérations d'urbanisme des Trente Glorieuses. Son œuvre, répartie sur le territoire français et localisée majoritairement en Rhône-Alpes, en région parisienne et en Normandie, illustre l'évolution des commandes, des conceptions et des mises en œuvre architecturales et urbaines. Maurice Novarina fait partie des architectes qui ont marqué le XXe siècle par une production importante en quantité, et remarquée, hier comme aujourd'hui en qualité. En effet, nombreuses de ses réalisations sont considérées comme patrimoine puisqu'elles concernent certains monuments historiques, des bâtiments « Label XXe », ou intégrés dans des chartes patrimoniales et paysagères. Ce travail cherche donc à repositionner l'architecte dans l'histoire de l'architecture et de l'urbanisme du XXe siècle, à préciser le contexte politique, économique et social dans lequel sont nés les projets, et à questionner son œuvre en lumière des théories de la modernité. L'œuvre de Maurice Novarina reprend les caractéristiques architecturales et urbaines de la doctrine moderne : l'influence du compagnon de la modernité qu'est Auguste Perret est sensible dans les projets de reconstruction d'après-guerre, alors que celle de Le Corbusier et de la Charte d'Athènes irradie l'ensemble des projets d'urbanisme, plus particulièrement les ZUP. Ces modèles forts, les architectes les interprètent, les réduisent ou les améliorent. La production de Maurice Novarina, comme celle de nombreux de ses contemporains, concerne alors une architecture ordinaire, qui s'impose dans les réalisations du XXe siècle et se révèle omniprésente dans la presse architecturale de l'époque, alors qu'elle est finalement peu évoquée par l'Histoire. Ces architectures perdurent comme héritage du XXe siècle et résultent, non pas de la banalité, mais d'une forme d'application de la modernité corbuséenne, qui au-delà des grandes théories, a marqué les esprits et formaté notre regard contemporain. Partant de l'hypothèse que les principes architecturaux et urbains de la modernité peuvent prendre des formes de l'ordinaire, nous verrons comment, chez Maurice Novarina, l'architecture relie les deux entités contraires (modernité / ordinaire) et que le processus complexe d'élaboration des projets, reposant sur des associations d'acteurs, des commanditaires récurrents et des équipes pluridisciplinaires, participent également à la richesse des œuvres. / L'auteur n'a pas fourni de résumé en anglais.

Text classification for companies is becoming more important in a world where an increasing amount of digital data are made available. The aim is to research whether five different machine learning algorithms can be used to automate the process of classification of invoice data and see which one gets the highest accuracy. Algorithms are in a later stage combined for an attempt to achieve higher results. N-grams are used, and results are compared in form of total accuracy of classification for each algorithm. A library in Python, called scikit-learn, implementing the chosen algorithms, was used. Data is collected and generated to represent data present on a real invoice where data has been extracted. Results from this thesis show that it is possible to use machine learning for this type of problem. The highest scoring algorithm (LinearSVC from scikit-learn) classifies 86% of all samples correctly. This is a margin of 16% above the acceptable level of 70%.

Interest in distributed approaches to machine learning has increased significantly in recent years due to continuously increasing data sizes for training machine learning models. In this thesis we describe three popular machine learning algorithms: decision trees, Naive Bayes and support vector machines (SVM) and present existing ways of distributing them. We also perform experiments with decision trees distributed with bagging, boosting and hard data partitioning and evaluate them in terms of performance measures such as accuracy, F1 score and execution time. Our experiments show that the execution time of bagging and boosting increase linearly with the number of workers, and that boosting performs significantly better than bagging and hard data partitioning in terms of F1 score. The hard data partitioning algorithm works well for large datasets where the execution time decrease as the number of workers increase without any significant loss in accuracy or F1 score, while the algorithm performs poorly on small data with an increase in execution time and loss in accuracy and F1 score when the number of workers increase.

Made available in DSpace on 2014-12-17T14:35:57Z (GMT). No. of bitstreams: 1 AntonioPS.pdf: 1422474 bytes, checksum: 56eb2f26bc9793947acf218454e0cb2d (MD5) Previous issue date: 2008-11-14 / Cette ?tude propose une lecture du sport d endurance, prenant comme perspective th?orique l imaginaire radical et consid?rant les dimensions socio-historiques e subjectives de la pratique de courses de longue distance. D abord, l ?chantillon la recherche a ?t? compos? de huit sujets-atl?tes du groupe de courreurs de rue Sport Vida. Ainsi, em m?me temps que nous faisons une analyse socio-historique de cette pratique sportive, nous consid?rons l ensemble des aspects s?cio-culturels et poursuivons la recherche avec comme objectif de comprendre les sens qui lui sont attribu?s par les sjuets-atl?tes, au-del? de l aspect ?conomique et de la consommation. Nous observons que, m?me si l alt?tismo qui est pratiqu? a des aspects competitifs (economiques), les atl?tes cr?ent d autres sens pour continuer a pratiquer ce sport, comme les amiti?s, ?tre ensemble avec les amis. Ils rompent avec la logique d?terministe du sport d?passer la limite du corps, vaincre ? n importe quel prix, d?passer les coll?gues -, en cherchant des moments de solidarit?, un sport sans violence et affectif. Nous percevons n?anmoins des contradictions dans le discours de quelques atl?tes quand confessent que le plus important est l amour du sport, les amiti?s, mais r?clament du manque de sponsorts et d appui pour pouvoir s entrainer tranquillement. Cette recherche a aussi montr? que dans la pratique de ce sport, les atl?tes construisent une obstination, sachant le sacrifice qu il impose au corps, mais cela se transforme en plaisir, excitation et recherche d ?motions fortes. Valeurs ?thiques sont aussi construites et valoris?es dans l atl?tisme, ce qui est observ? lorsque que les sujets-atl?tes critiquent avec v?emence a propos de l usage de substances chimiques par les sportifs. En choisissant l imaginaire radical comme principale inspiration th?orique pour cette recherche, il devient ?vident que le sport peut ?tre ressignifi?, ? partir du moment que cet imaginaire est potencialis? dans l enseignement de l ?ducation physique, porvocant chez les ?l?ves une r?flexion critique sur la soci?t? et sur le sport, qui passe ? ?tre redimensionn? vers la solidarit?, avec d?mocratie et autonomie. Enfin, l ?tude a r?v?l? que le sport d endurance est capable de cr?er des liens sociaux et structurer des relations ? partir de cette pratique / Este estudo prop?e uma leitura do esporte de rendimento, com o aporte te?rico do imagin?rio radical, considerando as dimens?es s?cio-hist?ricas e subjetivas na pr?tica de corridas de longa dist?ncia. De in?cio, a amostra da pesquisa foi composta por oito sujeitos-atletas do grupo de corredores de rua Sport Vida. Assim, ao fazermos uma an?lise s?cio-hist?rica dessa pr?tica esportiva, consideramos em conjunto os aspectos socioculturais e seguimos com o objetivo de compreender os sentidos a ela atribu?dos pelos sujeitos-atletas, para al?m do aspecto econ?mico e do consumo. Observamos que, mesmo o atletismo envolvendo aspectos relacionados ao rendimento, os atletas criam outros sentidos para continuarem desenvolvendo essa pr?tica, como as amizades, o estar juntos com os amigos. Eles rompem com a l?gica determinista do esporte ultrapassar o limite do corpo, vencer a qualquer pre?o, sobrepujar os colegas , buscando momentos de solidariedade, um esporte sem viol?ncia e afetivo. Percebemos, por?m, contradi??es, no discurso de alguns atletas, quando confessam que o mais importante ? o amor pelo esporte, as amizades, mas reclamam da falta de patroc?nio e de apoio para poderem treinar com mais tranq?ilidade. Esta pesquisa tamb?m revelou que, nessa pr?tica, os atletas constroem uma obstina??o, devido ao sacrif?cio que ela imp?e ao corpo, por?m isso ? transformado em prazer, excita??o e busca de fortes emo??es. Valores ?ticos tamb?m s?o constru?dos e valorizados no atletismo, o que ? observado quando os sujeitos-atletas fazem cr?ticas contundentes ao uso de subst?ncias qu?micas por aqueles(as) que o praticam. Ao tomarmos o imagin?rio radical como principal fonte te?rica para esta pesquisa, fica evidente que o esporte pode ser ressignificado, desde que esse imagin?rio seja potencializado no ensino da educa??o f?sica, provocando nos alunos uma reflex?o cr?tica sobre a sociedade e sobre o esporte, que passa a ser direcionado para a solidariedade, com democracia e autonomia. Enfim, o estudo revelou que o esporte de rendimento ? capaz de criar la?os sociais e estruturar rela??es ? sua volta

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-05-31T20:42:21Z No. of bitstreams: 1 MayteDuarteLealCoutinho_TESE.pdf: 5311317 bytes, checksum: abfa1929995ae7c350372d6daa5498e6 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-06-03T20:03:24Z (GMT) No. of bitstreams: 1 MayteDuarteLealCoutinho_TESE.pdf: 5311317 bytes, checksum: abfa1929995ae7c350372d6daa5498e6 (MD5) / Made available in DSpace on 2016-06-03T20:03:24Z (GMT). No. of bitstreams: 1 MayteDuarteLealCoutinho_TESE.pdf: 5311317 bytes, checksum: abfa1929995ae7c350372d6daa5498e6 (MD5) Previous issue date: 2015-06-18 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / No contexto de mudan?as clim?ticas sobre a Am?rica do Sul (AS) tem-se observado que a combina??o de altas temperaturas mais chuvas e altas temperaturas menos chuvas, provocam diferentes impactos como: eventos extremos de precipita??o, condi??es favor?veis para queimadas e secas. Com isto, estas regi?es enfrentam amea?a crescente de escassez de ?gua, local ou generalizada. Assim, a disponibilidade de ?gua no Brasil depende em grande parte, do clima e de suas varia??es em diversas escalas de tempo. Neste sentido, o objetivo principal desta pesquisa ? estudar o balan?o de umidade por meio de Regional Climate Models (RCM) do Project Regional Climate Change Assessments for La Plata Basin (CLARIS- LPB), assim como, combinar estes RCM por meio de duas t?cnicas estat?sticas, na tentativa de melhorar a previs?o sobre tr?s ?reas da AS: Amaz?nia (AMZ), Nordeste do Brasil (NEB) e Bacia do Prata (LPB) nos climas do passado (1961-1990) e do futuro (2071-2100). O transporte de umidade sobre AS foi investigado por meio do fluxo de umidade integrado verticalmente. Os principais resultados mostraram que os fluxos m?dios de vapor d??gua nas regi?es tropicais (AMZ e NEB) s?o maiores atrav?s das bordas leste e norte, assim indicando que as contribui??es dos ventos al?sios do Atl?ntico Norte e do Sul s?o igualmente importantes para a entrada de umidade durante os meses de JJA e DJF. Esta configura??o foi observada em todos os modelos e climas. Na compara??o dos climas verificou-se que a converg?ncia do fluxo de umidade no clima passado foi menor em rela??o ao futuro em diferentes regi?es e ?pocas. De forma semelhante, constatou-se que a precipita??o foi reduzida no clima futuro nas regi?es tropicais (AMZ e NEB), possivelmente devido os intensos fluxos de umidade que adentraram nas regi?es. Por interm?dio das t?cnicas de Regress?o M?ltipla por Componente Principal (C_RCP) e da combina??o convexa (C_EQM), analisamos e comparamos as combina??es dos modelos (ensemble). Os resultados indicaram que a combina??o por RCP foi melhor em representar a precipita??o observada em ambos os climas. Sendo que, al?m dos valores mostrarem ser pr?ximos aos observados, a t?cnica obteve coeficiente de correla??o de moderada ? forte magnitude, em praticamente todos os meses nos diferentes climas e regi?es. Al?m do mais, na avalia??o das t?cnicas de combina??o, a tend?ncia percentual (PBIAS) mostrou que em geral, a C_RCP obteve valores de baixa magnitude (PBIAS = 0%) indicando ter um desempenho ?muito bom? no clima passado e (PBIAS = -4% a 3%) para o clima futuro, sobre as regi?es de estudo. Enquanto a C_EQM mostrou no clima passado, que a AMZ obteve um desempenho ?bom? e nas regi?es do NEB e LPB obtiveram desempenho de ?bom a satisfat?rio?. Logo, os resultados mostraram que as t?cnicas tem um potencial promissor para aplica??es operacionais em centro de previs?o de tempo e clima. / In the context of climate change over South America (SA) has been observed that the combination of high temperatures and rain more temperatures less rainfall, cause different impacts such as extreme precipitation events, favorable conditions for fires and droughts. As a result, these regions face growing threat of water shortage, local or generalized. Thus, the water availability in Brazil depends largely on the weather and its variations in different time scales. In this sense, the main objective of this research is to study the moisture budget through regional climate models (RCM) from Project Regional Climate Change Assessments for La Plata Basin (CLARIS-LPB) and combine these RCM through two statistical techniques in an attempt to improve prediction on three areas of AS: Amazon (AMZ), Northeast Brazil (NEB) and the Plata Basin (LPB) in past climates (1961-1990) and future (2071-2100). The moisture transport on AS was investigated through the moisture fluxes vertically integrated. The main results showed that the average fluxes of water vapor in the tropics (AMZ and NEB) are higher across the eastern and northern edges, thus indicating that the contributions of the trade winds of the North Atlantic and South are equally important for the entry moisture during the months of JJA and DJF. This configuration was observed in all the models and climates. In comparison climates, it was found that the convergence of the flow of moisture in the past weather was smaller in the future in various regions and seasons. Similarly, the majority of the SPC simulates the future climate, reduced precipitation in tropical regions (AMZ and NEB), and an increase in the LPB region. The second phase of this research was to carry out combination of RCM in more accurately predict precipitation, through the multiple regression techniques for components Main (C.RPC) and convex combination (C.EQM), and then analyze and compare combinations of RCM (ensemble). The results indicated that the combination was better in RPC represent precipitation observed in both climates. Since, in addition to showing values be close to those observed, the technique obtained coefficient of correlation of moderate to strong magnitude in almost every month in different climates and regions, also lower dispersion of data (RMSE). A significant advantage of the combination of methods was the ability to capture extreme events (outliers) for the study regions. In general, it was observed that the wet C.EQM captures more extreme, while C.RPC can capture more extreme dry climates and in the three regions studied.