Doctor of Philosophy / Department of Electrical and Computer Engineering / Sanjoy Das and Anil Pahwa / Because a majority of day-to-day activities rely on electricity, it plays an important role in daily life. In this digital world, most of the people’s life depends on electricity. Without electricity, the flip of a switch would no longer produce instant light, television or refrigerators would be nonexistent, and hundreds of conveniences often taken for granted would be impossible. Electricity has become a basic necessity, and so any interruption in service due to disturbances in power lines causes a great inconvenience to customers. Customers and utility commissions expect a high level of reliability. Power distribution systems are geographically dispersed and exposure to environment makes them highly vulnerable part of power systems with respect to failures and interruption of service to customers. Following the restructuring and increased competition in the electric utility industry, distribution system reliability has acquired larger significance. Better understanding of causes and consequences of distribution interruptions is helpful in maintaining distribution systems, designing reliable systems, installing protection devices, and environmental issues. Various events, such as equipment failure, animal activity, tree fall, wind, and lightning, can negatively affect power distribution systems. Weather is one of the primary causes affecting distribution system reliability. Unfortunately, as weather-related outages are highly random, predicting their occurrence is an arduous task. To study the impact of weather on overhead distribution system several models, such as linear and exponential regression models, neural network model, and ensemble methods are presented in this dissertation. The models were extended to study the impact of animal activity on outages in overhead distribution system. Outage, lightning, and weather data for four different cities in Kansas of various sizes from 2005 to 2011 were provided by Westar Energy, Topeka, and state climate office at Kansas State University weather services. Models developed are applied to estimate daily outages. Performance tests shows that regression and neural network models are able to estimate outages well but failed to estimate well in lower and upper range of observed values. The introduction of committee machines inspired by the ‘divide & conquer” principle overcomes this problem. Simulation results shows that mixture of experts model is more effective followed by AdaBoost model in estimating daily outages. Similar results on performance of these models were found for animal-caused outages.

In reservoir engineering, history matching is the technique that reviews the uncertain parameters of a reservoir simulation model in order to obtain a response according to the observed production data. Reservoir properties have uncertainties due to their indirect acquisition methods, that results in discrepancies between observed data and reservoir simulator response. A history matching method is the Ensemble Smoother with Multiple Data assimilation (ES-MDA), where an ensemble of models is used to quantify the parameters uncertainties. In ES-MDA, the number of iterations must be defined previously the application by the user, being a determinant parameter for a good quality matching. One way to handle this, is by implementing adaptive methodologies when the algorithm keeps iterating until it reaches good matchings. Also, in large-scale reservoir models it is necessary to apply the localization technique, in order to mitigate spurious correlations and high uncertainty reduction of posterior models. The main objective of this dissertation is to evaluate two main parameters of history matching when using an adaptive ES-MDA: localization and ensemble size, verifying the impact of these parameters in the adaptive scheme. The adaptive ES-MDA used in this work defines the number of iterations and the inflation factors automatically and distance-based Kalman gain localization was used to evaluate the localization influence. The parameters influence was analyzed by applying the methodology in the benchmark UNISIM-I-H: a synthetic large-scale reservoir model based on an offshore Brazilian field. The experiments presented considerable reduction of the objective function for all cases, showing the ability of the adaptive methodology of keep iterating until a desirable overcome is obtained. About the parameters evaluated, a relationship between the localization and the required number of iterations to complete the adaptive algorithm was verified, and this influence has not been observed as function of the ensemble size. / Em engenharia de reservatórios, ajuste de histórico é a técnica que revisa os parâmetros incertos de um modelo de simulação de reservatório para obter uma resposta condizente com os dados de produção observados. As propriedades do reservatório possuem incertezas, devido aos métodos indiretos em que foram adquiridas, resultando em discrepâncias entre os dados observados e a resposta do simulador de reservatório. Um método de ajuste de histórico é o Conjunto Suavizado com Múltiplas Aquisições de Dados (sigla em inglês ES-MDA), onde um conjunto de modelos é utilizado para quantificar as incertezas dos parâmetros. No ES-MDA o número de iterações necessita ser definido previamente pelo usuário antes de sua aplicação, sendo um parâmetro determinante para um ajuste de boa qualidade. Uma forma de contornar esta limitação é implementar metodologias adaptativas onde o algoritmo continue as iterações até que alcance bons ajustes. Por outro lado, em modelos de reservatórios de larga-escala é necessário aplicar alguma técnica de localização para evitar correlações espúrias e uma alta redução de incertezas dos modelos a posteriori. O principal objetivo desta dissertação é avaliar dois principais parâmetros do ajuste de histórico quando aplicado um ES-MDA adaptativo: localização e tamanho do conjunto, verificando o impacto destes parâmetros no método adaptativo. O ES-MDA adaptativo utilizado define o número de iterações e os fatores de inflação automaticamente e a localização no ganho de Kalman baseada na distância foi utilizada para avaliar a influência da localização. Assim, a influência dos parâmetros foi analisada aplicando a metodologia no benchmark UNISIM-I-H: um modelo de reservatório sintético de larga escala baseado em um campo offshore brasileiro. Os experimentos apresentaram considerável redução da função objetivo para todos os casos, mostrando a capacidade da metodologia adaptativa de continuar iterando até que resultados aceitáveis fossem obtidos. Sobre os parâmetros avaliados, foi verificado uma relação entre a localização e o número de iterações necessárias, influência esta que não foi observada em função do tamanho do conjunto.

[pt] Em 1999, a empresa estatal Petrobras e o CEASM (Centro de Estudos e Ações Solidárias da Maré) instituição comunitária localizada na Maré, o maior conjunto de favelas do país, estabeleceram uma parceria que visava auxiliar algumas escolas públicas locais a desempenhar melhor o seu papel. Dessa parceria nasceu o Programa Criança Petrobras na Maré que, junto com a idéia de ajudar a melhorar as escolas tinha, também, entre seus objetivos a melhoria do desempenho escolar dos estudantes. Isso deveria ocorrer por meio do oferecimento de oficinas pedagógicas e culturais complementares à grade curricular regular. Com essa ação, esperava-se que os alunos atendidos pudessem ampliar seu capital cultural e seu capital escolar e, conseqüentemente, melhorar seu desempenho. Atualmente, o Projeto atende a metade das escolas públicas municipais de Ensino Fundamental existentes na Maré, o que significa o atendimento a oito escolas. Diante disso, a interrogação principal que guia este estudo refere-se a possíveis relações entre o Programa Criança Petrobras na Maré e o desempenho escolar dos estudantes das oito escolas em que o mesmo se faz presente. Para tentar responder a esta questão, analisamos um conjunto de indicadores escolares, incluindo os resultados dos estudantes dessas escolas na Prova Brasil de 2005 e estabelecemos comparações com as oito escolas públicas não atendidas pelo Programa. Entre os principais achados da pesquisa, está a melhoria das notas obtidas pelos alunos de turmas atendidas pelo Programa em avaliações pedagógicas dos professores. / [fr] En 1999, l`entreprise Petrobras et le Centre d`Études Solidaires de la Maré (CEASM), instituition localisé dans la Maré, ont etabli une alliance que visais aider les écoles bubliques de la localilé, à accomplir mielleur leur objectve. On peut dire, que de cette alliance est né, le Programme Entfant Petrbrasavec, l`ideé de potencialiser la perfomance scolaire des élèves et, entre autres objectives, améliorer les écoles. Afin de bien concrétizer ce projet, la médiation devrait se donner par le développement des -officines- pédagogique et culturelles, complémentaires au curriculum régulière. Dans cette perspective, on espérait, rendre possible l`ampliation du capital culturel et scolaire des élèves, et en conséquence elever leurs performances. Actuellement, la moitié des écoles publique, municipal, d´enseignement fondamental existant à la Maré sont bneficié par le projet. Ça signfie huit écoles. Devant le cadre designé, l`interogation principal, de ce travail, pose en question les possibles relations entre le programme, déjà mentionner, et la performance scolaire des élèves. Pour essayer de repondre cette question, nous avons analiser un ensemble de données, des indicateurs scolaires, le resultat de la performance de ces élèves à la Preuve Brésil de 2005 et, ensuite, nous avons établi une comparaisons avec les autres, huit, écoles non bénéficié par le programme. Entre, les principaux constatations de la recherche, on peut détacher l`élévation de performance des élèves aux examens pedagogiques faites par les instituteurs.

Drone usage is increasing, both in recreational use and in the industry. With it comes a number of problems to tackle. Primarily, there are certain areas in which flying drones pose a security threat, e.g., around airports or other no-fly zones. Other problems can appear when there are drones in mobile networks which can cause interference. Such interference comes from the fact that radio transmissions emitted from drones can travel more freely than those from regular UEs (User Equipment) on the ground since there are few obstructions in the air. Additionally, the data traffic sent from drones is often high volume in the form of video streams. The goal of this thesis is to identify so-called "rogue drones" connected to an LTE network. Rogue drones are flying drones that appear to be regular UEs in the network. Drone identification is a binary classification problem where UEs in a network are classified as either a drone or a regular UE and this thesis proposes machine learning methods that can be used to solve it. Classifications are based on radio measurements and statistics reported by UEs in the network. The data for the work in this thesis is gathered through simulations of a heterogenous LTE network in an urban scenario. The primary idea of this thesis is to use a type of cascading classifier, meaning that classifications are made in a series of stages with increasingly complex models where only a subset of examples are passed forward to subsequent stages. The motivation for such a structure is to minimize the computational requirements at the entity making the classifications while still being complex enough to achieve high accuracy. The models explored in this thesis are two-stage cascading classifiers using decision trees and ensemble learning techniques. It is found that close to 60% of the UEs in the dataset can be classified without errors in the first of the two stages. The rest is forwarded to a more complex model which requires more data from the UEs and can achieve up to 98% accuracy.

In many real classification problems, the data set used for model induction is significantly imbalanced. This occurs when the number of examples of some classes is much lower than the other classes. Imbalanced datasets can compromise the performance of most classical classification algorithms. The classification models induced by such datasets usually present a strong bias towards the majority classes, tending to classify new instances as belonging to these classes. A commonly adopted strategy for dealing with this problem is to train the classifier on a balanced sample from the original dataset. However, this procedure can discard examples that could be important for a better class discrimination, reducing classifier efficiency. On the other hand, in recent years several studies have shown that in different scenarios the strategy of combining several classifiers into structures known as ensembles has proved to be quite effective. This strategy has led to a stable predictive accuracy and, in particular, to a greater generalization ability than the classifiers that make up the ensemble. This generalization power of classifier ensembles has been the focus of research in the imbalanced learning field in order to reduce the bias toward the majority classes, despite the complexity involved in generating efficient ensembles. Optimization meta-heuristics, such as evolutionary algorithms, have many applications for ensemble learning, although they are little used for this purpose. For example, evolutionary algorithms maintain a set of possible solutions and diversify these solutions, which helps to escape out of the local optimal. In this context, this thesis investigates and develops approaches to deal with imbalanced datasets, using ensemble of classifiers induced by samples taken from the original dataset. More specifically, this theses propose three solutions based on evolutionary ensemble learning and a fourth proposal that uses a pruning mechanism based on dominance ranking, a common concept in multiobjective evolutionary algorithms. Experiments showed the potential of the developed solutions. / Em muitos problemas reais de classificação, o conjunto de dados usado para a indução do modelo é significativamente desbalanceado. Isso ocorre quando a quantidade de exemplos de algumas classes é muito inferior às das outras classes. Conjuntos de dados desbalanceados podem comprometer o desempenho da maioria dos algoritmos clássicos de classificação. Os modelos de classificação induzidos por tais conjuntos de dados geralmente apresentam um forte viés para as classes majoritárias, tendendo classificar novas instâncias como pertencentes a essas classes. Uma estratégia comumente adotada para lidar com esse problema, é treinar o classificador sobre uma amostra balanceada do conjunto de dados original. Entretanto, esse procedimento pode descartar exemplos que poderiam ser importantes para uma melhor discriminação das classes, diminuindo a eficiência do classificador. Por outro lado, nos últimos anos, vários estudos têm mostrado que em diferentes cenários a estratégia de combinar vários classificadores em estruturas conhecidas como comitês tem se mostrado bastante eficaz. Tal estratégia tem levado a uma acurácia preditiva estável e principalmente a apresentar maior habilidade de generalização que os classificadores que compõe o comitê. Esse poder de generalização dos comitês de classificadores tem sido foco de pesquisas no campo de aprendizado desbalanceado, com o objetivo de diminuir o viés em direção as classes majoritárias, apesar da complexidade que envolve gerar comitês de classificadores eficientes. Meta-heurísticas de otimização, como os algoritmos evolutivos, têm muitas aplicações para o aprendizado de comitês, apesar de serem pouco usadas para este fim. Por exemplo, algoritmos evolutivos mantêm um conjunto de soluções possíveis e diversificam essas soluções, o que auxilia na fuga dos ótimos locais. Nesse contexto, esta tese investiga e desenvolve abordagens para lidar com conjuntos de dados desbalanceados, utilizando comitês de classificadores induzidos a partir de amostras do conjunto de dados original por meio de metaheurísticas. Mais especificamente, são propostas três soluções baseadas em aprendizado evolucionário de comitês e uma quarta proposta que utiliza um mecanismo de poda baseado em ranking de dominância, conceito comum em algoritmos evolutivos multiobjetivos. Experimentos realizados mostraram o potencial das soluções desenvolvidas.

Under de senaste två åren har jag genomfört min masterutbildning i komposition vid Kungliga Musikhögskolan i Stockholm. I det här arbetet gör jag en undersökning och ett formulerande av de tankar som kommit ur – och styrt – mitt komponerande, mitt lyssnande och mitt lärande under dessa två år. Begreppet anslag blir här en ledsagare för tanken och arbetet inleds med skapandet begreppet. Därefter presenteras och analyseras sex av de musikverk jag komponerat under masterutbildningen. Ingången till de sex verk som presenteras sker från vitt skilda håll, i hopp om att bredda förståelsen kring uppkomsten av begreppet anslag och att fördjupa dess dubbelverkande utbyte med musiken. Genom begreppet anslag bli skapandet av musik ett instrument med vilket undersökningar av världen och existensen tycks mer möjliga att påbörja.

In many real classification problems, the data set used for model induction is significantly imbalanced. This occurs when the number of examples of some classes is much lower than the other classes. Imbalanced datasets can compromise the performance of most classical classification algorithms. The classification models induced by such datasets usually present a strong bias towards the majority classes, tending to classify new instances as belonging to these classes. A commonly adopted strategy for dealing with this problem is to train the classifier on a balanced sample from the original dataset. However, this procedure can discard examples that could be important for a better class discrimination, reducing classifier efficiency. On the other hand, in recent years several studies have shown that in different scenarios the strategy of combining several classifiers into structures known as ensembles has proved to be quite effective. This strategy has led to a stable predictive accuracy and, in particular, to a greater generalization ability than the classifiers that make up the ensemble. This generalization power of classifier ensembles has been the focus of research in the imbalanced learning field in order to reduce the bias toward the majority classes, despite the complexity involved in generating efficient ensembles. Optimization meta-heuristics, such as evolutionary algorithms, have many applications for ensemble learning, although they are little used for this purpose. For example, evolutionary algorithms maintain a set of possible solutions and diversify these solutions, which helps to escape out of the local optimal. In this context, this thesis investigates and develops approaches to deal with imbalanced datasets, using ensemble of classifiers induced by samples taken from the original dataset. More specifically, this theses propose three solutions based on evolutionary ensemble learning and a fourth proposal that uses a pruning mechanism based on dominance ranking, a common concept in multiobjective evolutionary algorithms. Experiments showed the potential of the developed solutions. / Em muitos problemas reais de classificação, o conjunto de dados usado para a indução do modelo é significativamente desbalanceado. Isso ocorre quando a quantidade de exemplos de algumas classes é muito inferior às das outras classes. Conjuntos de dados desbalanceados podem comprometer o desempenho da maioria dos algoritmos clássicos de classificação. Os modelos de classificação induzidos por tais conjuntos de dados geralmente apresentam um forte viés para as classes majoritárias, tendendo classificar novas instâncias como pertencentes a essas classes. Uma estratégia comumente adotada para lidar com esse problema, é treinar o classificador sobre uma amostra balanceada do conjunto de dados original. Entretanto, esse procedimento pode descartar exemplos que poderiam ser importantes para uma melhor discriminação das classes, diminuindo a eficiência do classificador. Por outro lado, nos últimos anos, vários estudos têm mostrado que em diferentes cenários a estratégia de combinar vários classificadores em estruturas conhecidas como comitês tem se mostrado bastante eficaz. Tal estratégia tem levado a uma acurácia preditiva estável e principalmente a apresentar maior habilidade de generalização que os classificadores que compõe o comitê. Esse poder de generalização dos comitês de classificadores tem sido foco de pesquisas no campo de aprendizado desbalanceado, com o objetivo de diminuir o viés em direção as classes majoritárias, apesar da complexidade que envolve gerar comitês de classificadores eficientes. Meta-heurísticas de otimização, como os algoritmos evolutivos, têm muitas aplicações para o aprendizado de comitês, apesar de serem pouco usadas para este fim. Por exemplo, algoritmos evolutivos mantêm um conjunto de soluções possíveis e diversificam essas soluções, o que auxilia na fuga dos ótimos locais. Nesse contexto, esta tese investiga e desenvolve abordagens para lidar com conjuntos de dados desbalanceados, utilizando comitês de classificadores induzidos a partir de amostras do conjunto de dados original por meio de metaheurísticas. Mais especificamente, são propostas três soluções baseadas em aprendizado evolucionário de comitês e uma quarta proposta que utiliza um mecanismo de poda baseado em ranking de dominância, conceito comum em algoritmos evolutivos multiobjetivos. Experimentos realizados mostraram o potencial das soluções desenvolvidas.

Estuda as ações de transformação e preservação do conjunto histórico de Paranaguá no século XX e início do XXI, partindo do primeiro ato de preservação em caráter nacional, o tombamento Colégio dos Jesuítas em 1938 pelo antigo Serviço do Patrimônio Histórico e Artístico Nacional, até o reconhecimento do conjunto histórico em 2009 pelo Instituto do Patrimônio Histórico e Artístico Nacional. A partir de três edifícios representativos na cidade, Colégio dos Jesuítas e igrejas de São Benedito e da Ordem Terceira de São Francisco das Chagas, analisa as atividades do Serviço do Patrimônio, como também os fatos que influenciaram na decisão sobre a delimitação e o tombamento do conjunto histórico. Analisa, ainda, a importância dessa área preservada no contexto urbano de Paranaguá com forte apoio da revisão bibliográfica a partir de autores como Márcia Chuva, Maria Cecília Londres, José Reginaldo Gonçalves, Lia Mayumi, Márcia Sant\'Ana e Cristiane Gonçalves e de fontes documentais primárias como cartas, pareceres, relatórios, peças gráficas, croquis e fotografias. Além disso, também realiza entrevistas, buscando as ações realizadas pelos órgãos oficiais neste patrimônio. Dessa forma, a pesquisa se insere no quadro de discussões relativas à preservação de conjuntos históricos no Brasil, contribuindo particularmente para avaliar o papel da população nas decisões de proteção do patrimônio cultural. / Studies the transformation and conservation of the city of Paranagua historical ensemble during the 20th and beginning of the 21st centuries starting from the first national act of preservation, the listing of the Colégio dos Jesuítas (Jesuit college) in 1938 by the former National Historical and Artistic Heritage Service until the recognition of the historical ensemble in 2009 by the Institute of National Historical and Artistic Heritage. Considering three representative buildings in the city - the Jesuit College and the churches São Benedito and thesis Ordem Terceira de São Francisco das Chagas the thesis analyses the activities of the Heritage Service as well as the facts that influenced in the decision regarding the delimitation and listing of the historical ensemble. The thesis also analyses the importance of this preserved area in the urban context of Paranagua and is strongly supported by the bibliographical revision of texts by authors such as Márcia Chuva, Maria Cecília Londres, José Reginaldo Gonçalves, Lia Mayumi, Márcia Sant\'Ana and Cristiane Gonçalves as well as primary sources of documents such as letters, reviews, reports, graphic pieces, sketches and photos. It also analyses interviews that highlight activities conducted by official bodies on this heritage. This way, the research is considered part of the debate on preservation of historical areas in Brazil and provides a special contribution to the evaluation of the role played by public participation in decisions regarding the protection of cultural heritage.

A oferta de produtos,informação e serviços a partir de perfis de usuários tem tornado os sistemas de recomendação cada vez mais presentes na Web, aumentando a facilidade de escolha e de permanência dos usuários nestes sistemas. Entretanto, existem otimizações a serem feitas principalmente com relação à modelagem do perfil do usuário. Geralmente, suas preferências são modeladas de modo superficial, devido à escassez das informações coletadas,como notas ou comentários, ou devido a informações indutivas que estão suscetíveis a erros. Esta dissertação propõe uma ferramenta de recomendação baseado em interações multimodais, capaz de combinar informações de usuários processadas individualmente por algoritmos de recomendação tradicionais. Nesta ferramenta desenvolveram-se quatro técnicas de combinação afim fornecer aos sistemas de recomendação, subsídios para melhoria na qualidade das predições em diversos domínios. / Providing products, information and services from user profiles has made the recommendation systems to be increasingly present, increasing the ease of selection and retention of users in Webservices. However, there are optimizations to be made in these systems mainly with respect to modeling the user profile. Generally, the preferences are modeled superficially, due to the scarcity of information collected, as notes or comments, or because of inductive information that is susceptible to errors. This work proposes are commendation tool based on multimodal interactions that combines users\' interactions, wich are processed individually by traditional recommendation algorithms. In this tool developed four combination of techniques in order to provide recommendation systems subsidies to improve the quality of predictions.

"Movements -- homage to Joseph Haydn" is commissioned by Dr. Helmut Sohmen, to commemorate the 200th anniversary of the death of Joseph Haydn. It is premiered by the Anton von Webern Orchestra of the Universitat fur Musik und darstellende Kunst Wien in Vienna on 28 November 2009. The Asian premiere is performed on I February 2010, by the orchestra of the Academy of Performance Arts of Hong Kong. / During the past two centuries, music has developed from classical to romantic, and to contemporary; orchestra size from thirty musicians to a double or even a triple; from simple harmonic structures to complicated; from tonal to atonal; from sound to silence; from resonance to dissonance and noise (or some people say it in the other way round); and lastly, from Haydn to contemporary composers (including Tang!!). In "Movements -- homage to Joseph Haydn", inspired by Haydn's simplicity, several excerpts are taken from Haydn's works, small as just a tiny fragment or large as an original quotation. It aims to strive for a balance between the shifting of Haydn's style and Tang's, giving a mix of classical and modern flavor. It shows changes from the modern to the classical Haydn, then back to the modern, like a scene of time line. Movements is presented in one continuous movement, with four distinct sections: I. Before "Sunrise"; II. Franz Joseph Haydn; III. After "The Lark"; and IV. Adagio e cantabile. / I. Before "Sunrise" begins in a rather slow but ongoing tempo, creating a blurred atmosphere; not really a descriptive scene before a real sunrise. It aims for a feeling of leading-to, moving towards the string quartet "Sunrise" by Haydn. Although nothing from Sunrise has been used, the musical ideas are taken from the works before it. The piccolo leads the start with a series of acute repeated notes, which create the vague sounds of the minor 7th and the major 9th intervals with the repeated pattern in the trumpets and the piano. The figures are then followed by the other main element: the long sustained chords, which are recurred frequently throughout the whole section. The long chords echo in the orchestra, and sustain with inner-movement shifting among different groups of instruments, in varying registers. When the repetitions and the long sustained chords get merging together, the repeated figures gradually become transparent, and transform into a dominant one. Without any pauses, the repetitions naturally turn into the second section and fill into its harmony. / II. Franz Joseph Haydn has a quoted passage from Haydn's String Quartet No. 61 "Fifth" in D minor op. 76 no.2, also presented in the solo strings, with accompaniment of the tutti strings and harmonic support from the winds. The second section differs from the misty first; the quotation itself is clear and with varying developments afterwards. / III. After "The Lark", a fast section, has a quoted passage from the last movement of Haydn's String Quartet No. 53 in D major "The Lark" op.64 no.5. Short scale figures are used in a simple phrase structure. The changing texture is important so as to maintain the direction and progression of the section. Starting in the woodwind section, each phrase is designed to keep a common factor of spinning up and down, and spiraling among the entire ensemble. Layers with different fragmented materials are added onto the top like a multilayer cake. Together with numerous contrapuntal shifting, where two or three different textural ideas move at the same time, new but related ideas (scale figures) are kept being created. It is like putting hundreds of images of one single object together onto one single screen, with images taken in different angles, different time and different perspectives. Within the screen, uncountable colorful details are kept, with chemical effects. / The first theme of the second movement of Haydn's Piano Sonata no.59 in E flat major is collaged with the last section, IV. Adagio e cantabile. Sustained chords are built to proceed alongside the theme, in a way of fading in and out alternatively. The finale aims for a conclusion of the whole piece, bringing Haydn to modernity. Both subjects are like representing two different times from two different spaces, recurring in the same moment and on the same platform. / The instrumentation of Movements consists of pair winds (with the exception of an extra bass clarinet and four horns), percussions, piano and strings. In order to pay tribute to Haydn's string quartets, the first and third sections are entitled after two famous quartets: String Quartet No. 63 "Sunrise" in Bb major op.76 no.4 and String Quartet No. 53 in D major "The Lark" op.64 no.5. The strings are sometimes divided into a solo group of quartet versus the tutti strings, implying a string quartet solo with orchestra accompaniment. Adagio e cantabile, the title of the last section, is a tempo marking taken from a slow movement of a Haydn's Piano Sonata no.59 Hob. XVI: 49 in Eb major, where the sonata was also partially used in a 1994 movie "Interview of the Vampire: The Vampire Chronicles" . In general, the tempo structure is simply set in a form of slow-fast-slow, as III. After "The Lark" is a comparatively faster section than the other three. Gestures from Haydn's string quartets are used as reference. For example, simply chords, scale pattern, repeated notes and simple phrase structure, are constructed as the foundation of Movements . These gestures are designed to be presented in varying ways such as variations, augmentation, amplification, and compression. / 1. Movements: homage to Joseph Haydn, for orchestra -- 2. Falling up, for string quartet and suona -- 3. Distorted indulgence, for clarinet, electric-guitar, cello, contrabass, piano and percussion (all amplified) -- 4. It is what it is! for sheng and chamber orchestra (1 clarinet in Bb, 1 bass clarinet in Bb, 1 soprano saxophone in Bb, 1 alto saxophone in Eb, 1 horn in F, 1 tuba, 1 violin, 1 viola, 1 cello, 1 piano, 1 percussion) -- 5. Chao, for suona and Chinese orchestra -- 6. Dragon-lantern, for 9 suonas and Chinese orchestra -- 7. Clarin and Tim, for Bb clarinet, tenor timpani and concert timpani. / Tang, Lok Yin. / "(December 2009)"--Abstract. / Adviser: Wai Kwong Victor Chan. / Source: Dissertation Abstracts International, Volume: 73-03, Section: A, page: . / Thesis (D.Mus.)--Chinese University of Hong Kong, 2010. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.