One of the most relevant issues in the field of biology is the unveiling of the evolutionary history of different species and organisms. The evolutionary relationships of these species and organisms are explained by constructing phylogenetic trees whose leaves represent species and whose internal nodes represent hypothesized ancestors. The tree reconstruction process is known as Phylogenetic Inference. Phylogenies can be used not only for explaining the evolutionary history of organisms but also for many other purposes such as the design of new drugs by tracking the evolution of diseases. In the last few years, the amount of genetic data collected from organisms and species has increased greatly. Based on this, biologists have sought methods that are capable of computing phylogenies of small, medium, and even large datasets in a reasonable time and with accuracy. The neighbor-joining method is one used most for phylogenetic inference because of its computation efficiency. Since the increase of datasets, novel neighbor-joining- based approaches have been developed with the goal of computing efficiency and accurate phylogenies of thousands of sequences. Therefore, this study compared the canonical neighbor-joining method represented by MEGA software with two novel neighbor-joining-based approaches--the NINJA method and the FastTree method--to identify the most efficient and effective method for the computational performance, topological accuracy, and topological similarity through the scalability of the sequences size. The study was accomplished by executing experiments using small, medium, and large protein and nucleotide sequences. The FastTree method was the most successful at balancing the trade-off among the Computational Performance, Topological Accuracy, and Topological Similarity when scaling up the number of sequences in this study.

O setor de serviços tem fundamental importância para a economia global, porém o layout de organizações deste setor tipicamente não é abordado com a mesma intensidade com que se discute arranjo físico em ambientes industriais. O objetivo desta dissertação reside na aplicação de sistemáticas de concepção de layout com vistas ao planejamento e aprimoramento do arranjo físico e agrupamento de recursos de uma biblioteca. Como objetivos específicos, traz a aplicação do planejamento sistemático de layout (SLP) para o posicionamento de recursos e organização dos fluxos de uma biblioteca, e a adaptação do algoritmo Close Neighbor para agrupamento de materiais bibliográficos (livros) em prateleiras de acordo com sua área de abrangência. Para tanto, inicialmente apresentam-se as características da Biblioteca da Faculdade de Farmácia da UFRGS (local de aplicação do estudo), a análise da movimentação de pessoas e de materiais, a abordagem proposta e as diretrizes para organização do arranjo físico da biblioteca e do acervo de livros. Dentre outros procedimentos operacionais, fez-se necessária a realização de reuniões com a equipe da biblioteca e com a direção da Faculdade de Farmácia, visando a estabelecer prioridades e definir características desejadas para o arranjo físico do espaço em estudo. Na sequência, implantou-se a proposta de layout selecionada, seguida de uma discussão acerca do desempenho da biblioteca antes e depois da implantação do novo layout; tal discussão foi baseada tanto em resultados numéricos (análise quantitativa) como na percepção da equipe envolvida (análise qualitativa). / The service sector is of fundamental importance to the global economy, but the layout of organizations in this sector is typically not approached with the same intensity with which physical arrangement is discussed in industrial environments. The objective of this dissertation is to apply layout design systematics with a view to planning and improving the physical arrangement and grouping of library resources. As a specific goal, the application of systematic layout planning (SLP) for the positioning of resources and organization of a library's flows, and the adaptation of the Close Neighbor algorithm for grouping bibliographic materials (books) into shelves according to their area of comprehensiveness. In order to do so, the characteristics of the Library of the Faculty of Pharmacy of UFRGS (place of application of the study), the analysis of the movement of people and materials, the proposed approach and the guidelines for the organization of the physical arrangement of the library and of the collection of books. Among other operational procedures, it was necessary to hold meetings with the library staff and the Faculty of Pharmacy, in order to establish priorities and define desired characteristics for the physical arrangement of the space under study. Next, the selected layout proposal was implanted, followed by a discussion about the library's performance before and after the implementation of the new layout; such a discussion was based on both numerical results (quantitative analysis) and the perception of the team involved (qualitative analysis).

Submitted by Automação e Estatística (sst@bczm.ufrn.br) on 2018-05-02T22:45:42Z No. of bitstreams: 1 WinnieDeLimaTorres_DISSERT.pdf: 1538022 bytes, checksum: ad6fc16589291a27b8b718b755afdf44 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2018-05-07T21:40:35Z (GMT) No. of bitstreams: 1 WinnieDeLimaTorres_DISSERT.pdf: 1538022 bytes, checksum: ad6fc16589291a27b8b718b755afdf44 (MD5) / Made available in DSpace on 2018-05-07T21:40:35Z (GMT). No. of bitstreams: 1 WinnieDeLimaTorres_DISSERT.pdf: 1538022 bytes, checksum: ad6fc16589291a27b8b718b755afdf44 (MD5) Previous issue date: 2018-01-30 / Alguns campos da ciência propõem-se a estudar distúrbios no trato vocal a partir de análises sobre padrões de vibração da voz. Em geral, a importância dessas pesquisas está na identificação, em uma fase mais específica, de doenças de maior ou menor gravidade, a serem sanadas com terapia vocal ou que requerem maior atenção, gerando inclusive a necessidade de procedimentos cirúrgicos para o seu controle. Embora, já exista na literatura indicações de que o processamento digital de sinais permite diagnosticar, de um modo não invasivo, patologias laríngeas, como doenças vocais que ocasionem edema, nódulo e paralisia, não existe definição do método mais indicado e das características, ou parâmetros, mais adequados para detectar a presença de desvios vocais. Sendo assim, neste trabalho é proposto um algoritmo para detecção de desvios vocais por meio da análise de sinais de voz. Para a realização deste trabalho, utilizou-se dados constantes no banco de dados Disordered Voice Database, desenvolvido pelo Massachusetts Eye and Ear Infirmary (MEEI), devido sua utilização em pesquisas na área acústica de voz. Foram utilizados 166 sinais contidos nessa base de dados, com sinais de vozes saudáveis e de vozes patológicas afetadas por edema, por nódulo e por paralisia nas pregas vocais. A partir dos sinais de voz, foram gerados modelos Auto Regressivos (AR e ARMA) para representação desses sinais e, utilizando os parâmetros dos modelos obtidos, foi utilizado o algoritmo K-Nearest Neighbors (KNN) para a classificação dos sinais analisados. Com o intuito de analisar a eficiência do algoritmo proposto neste estudo, os resultados obtidos desse algoritmo foram comparados com um método de detecção considerando apenas distância euclidiana entre os sinais. Os resultados encontrados apontam que o método proposto neste trabalho apresenta um bom resultado, gerando uma taxa de acerto na classificação acima de 71% (maior que os 31% a partir do uso da distância euclidiana). Além disso, o método utilizado é de fácil implementação, podendo ser utilizado em hardwares mais simples. Logo, essa pesquisa tem potencial para gerar um classificador barato e acessível para a utilização em larga escala por profissionais de saúde, como uma alternativa de pré análise não invasiva para detecção de patologias otorrinolaringológicas que afetem a voz. / Some fields in Science propose to study vocal tract disorders from an analysis about voice vibration patterns. Generally, the weight of those researches is given by the identification – in a more specific level – of diseases in different stages of severity, which would be redressed through voice therapy or means that require more attention, hence generating the need of surgical procedures for its control. Although there are evidences in literature that the Digital Signal Processing allows a non-invasive diagnosis of laryngeal pathologies, such as vocal cord disorders, which provoke swelling, nodules, and paralyses, there is no definition of any most indicated method, and characteristics or appropriated parameters to detect voice deviations. Thus, the present paper proposes an algorithm to detect vocal deviances through the Voice Signal Analysis. In order to complete this study, it had been used data from the Disordered Voice Database, developed by the Massachusetts Eye and Ear Infirmary (MEEI) due to their wide use in researches regarding the voice and speech. A total of 166 signals from this database were used, including healthy voices and pathologic voices affected by swelling, nodule, and vocal fold paralysis. From the voice signals, autoregressive processes of order (AR and ARMA) were generated for a representation of those signals, and – by using the models’ parameters obtained – it had been used the KNN algorithm for a classification of the signals analyzed. Seeking an analysis of the efficiency of the algorithm proposed in this study, the results obtained from this algorithm were compared to a detection method, which only considers the Euclidian distance between the signals. The results found point that the propositioned method in this work presents a satisfactory result, generating a hit rate on the classification above 71% (more than the 31% from the use of the Euclidian distance). Moreover, the method used is easy to implement, so that it can be used along with simpler hardware. Consequently, this research has the potential to generate a cheap and accessible sorter for wide-scale use by health care professionals as a non-invasive pre-analysis to detect otorhinolaryngological pathologies that affect the voice.

O setor de serviços tem fundamental importância para a economia global, porém o layout de organizações deste setor tipicamente não é abordado com a mesma intensidade com que se discute arranjo físico em ambientes industriais. O objetivo desta dissertação reside na aplicação de sistemáticas de concepção de layout com vistas ao planejamento e aprimoramento do arranjo físico e agrupamento de recursos de uma biblioteca. Como objetivos específicos, traz a aplicação do planejamento sistemático de layout (SLP) para o posicionamento de recursos e organização dos fluxos de uma biblioteca, e a adaptação do algoritmo Close Neighbor para agrupamento de materiais bibliográficos (livros) em prateleiras de acordo com sua área de abrangência. Para tanto, inicialmente apresentam-se as características da Biblioteca da Faculdade de Farmácia da UFRGS (local de aplicação do estudo), a análise da movimentação de pessoas e de materiais, a abordagem proposta e as diretrizes para organização do arranjo físico da biblioteca e do acervo de livros. Dentre outros procedimentos operacionais, fez-se necessária a realização de reuniões com a equipe da biblioteca e com a direção da Faculdade de Farmácia, visando a estabelecer prioridades e definir características desejadas para o arranjo físico do espaço em estudo. Na sequência, implantou-se a proposta de layout selecionada, seguida de uma discussão acerca do desempenho da biblioteca antes e depois da implantação do novo layout; tal discussão foi baseada tanto em resultados numéricos (análise quantitativa) como na percepção da equipe envolvida (análise qualitativa). / The service sector is of fundamental importance to the global economy, but the layout of organizations in this sector is typically not approached with the same intensity with which physical arrangement is discussed in industrial environments. The objective of this dissertation is to apply layout design systematics with a view to planning and improving the physical arrangement and grouping of library resources. As a specific goal, the application of systematic layout planning (SLP) for the positioning of resources and organization of a library's flows, and the adaptation of the Close Neighbor algorithm for grouping bibliographic materials (books) into shelves according to their area of comprehensiveness. In order to do so, the characteristics of the Library of the Faculty of Pharmacy of UFRGS (place of application of the study), the analysis of the movement of people and materials, the proposed approach and the guidelines for the organization of the physical arrangement of the library and of the collection of books. Among other operational procedures, it was necessary to hold meetings with the library staff and the Faculty of Pharmacy, in order to establish priorities and define desired characteristics for the physical arrangement of the space under study. Next, the selected layout proposal was implanted, followed by a discussion about the library's performance before and after the implementation of the new layout; such a discussion was based on both numerical results (quantitative analysis) and the perception of the team involved (qualitative analysis).

Made available in DSpace on 2014-06-12T15:57:17Z (GMT). No. of bitstreams: 2 arquivo3157_1.pdf: 3737373 bytes, checksum: 7ca491f9a72f2e9cf51764a7acac3e3c (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2010 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / Esta dissertação introduz uma estrutura de dados baseada em gride implementada em GPU. Ela foi desenvolvida para pesquisa dos vizinhos mais próximos em nuvens de pontos dinâmicas, de uma forma massivamente paralela. A implementação possui desempenho em tempo real e é executada em GPU, ambas construção do gride e pesquisas dos vizinhos mais próximos (exatos e aproximados). Dessa forma, a transferência de memória entre sistema e dispositivo é minimizada, aumentando o desempenho de uma forma geral. O algoritmo proposto pode ser usado em diferentes aplicações com cenários estáticos ou dinâmicos. Além disso, a estrutura de dados suporta nuvens de pontos tridimensionais e dada sua natureza dinâmica, o usuário pode mudar seus parâmetros em tempo de execução. O mesmo se aplica ao número de vizinhos pesquisados. Uma referência em CPU foi implementada e comparações de desempenho justificam o uso de GPUs como processadores massivamente paralelos. Em adição, o desempenho da estrutura de dados proposta é comparada com implementações em CPU e GPU de trabalhos anteriores. Finalmente, uma aplicação de renderização baseada em pontos foi desenvolvida de forma a verificar o potencial da estrutura de dados

The work described in this thesis contributes to the development of a system to evaluate sailing performance. This work was motivated by the lack of tools available to evaluate sailing performance. The goal of the work presented is to detect and classify the turns of a sailing yacht. Data was collected using a BlackBerry PlayBook affixed to a J/24 sailing yacht. This data was manually annotated with three types of turn: tack, gybe, and mark rounding. This manually annotated data was used to train classification methods. Classification methods tested were multi-layer perceptrons (MLPs) of two sizes in various committees and nearest- neighbour search. Pre-processing algorithms tested were Kalman filtering, categorization using quantiles, and residual normalization. The best solution was found to be an averaged answer committee of small MLPs, with Kalman filtering and residual normalization performed on the input as pre-processing.

Word embeddings are useful in many tasks in Natural Language Processing and Information Retrieval, such as text mining and classification, sentiment analysis, sentence completion, or dictionary construction. Word2vec and its predecessor fastText, both well-known models to produce word embeddings, are powerful techniques to study the syntactic and semantic relations between words by representing them in a low-dimensional vector. By applying algebraic operations on these vectors semantic relationships such as word analogies, gender-inflections, or geographical relationships can be easily recovered. The aim of this work is to investigate how word embeddings could be utilized to augment and enrich queries in DBMSs, e.g. to compare text values according to their semantic relation or to group rows according to the similarity of their text values. For this purpose, we use pre-trained word embedding models of large text corpora such as Wikipedia. By exploiting this external knowledge during query processing we are able to apply inductive reasoning on text values. Thereby, we reduce the demand for explicit knowledge in database systems. In the context of the IMDB database schema, this allows for example to query movies that are semantically close to genres such as historical fiction or road movie without maintaining this information. Another example query is sketched in Listing 1, that returns the top-3 nearest neighbors (NN) of each movie in IMDB. Given the movie “Godfather” as input this results in “Scarface”, “Goodfellas” and “Untouchables”.

The aim of this dissertation is to study two problems of distributed nearest neighbor classification (DiNN) systematically. The first one compares two DiNN classifiers based on different schemes: majority voting and weighted voting. The second one is an extension of the DiNN method to the crowdsourcing application, which allows each worker data has a different size and noisy labels due to low worker quality. Both statistical guarantees and numerical comparisons are studied in depth.<br><div><br></div><div><div>The first part of the dissertation focuses on the distributed nearest neighbor classification in big data. The sheer volume and spatial/temporal disparity of big data may prohibit centrally processing and storing the data. This has imposed a considerable hurdle for nearest neighbor predictions since the entire training data must be memorized. One effective way to overcome this issue is the distributed learning framework. Through majority voting, the distributed nearest neighbor classifier achieves the same rate of convergence as its oracle version in terms of the regret, up to a multiplicative constant that depends solely on the data dimension. The multiplicative difference can be eliminated by replacing majority voting with the weighted voting scheme. In addition, we provide sharp theoretical upper bounds of the number of subsamples in order for the distributed nearest neighbor classifier to reach the optimal convergence rate. It is interesting to note that the weighted voting scheme allows a larger number of subsamples than the majority voting one.</div></div><div><br></div><div>The second part of the dissertation extends the DiNN methods to the application in crowdsourcing. The noisy labels in crowdsourcing data and different sizes of worker data will deteriorate the performance of DiNN methods. We propose an enhanced nearest neighbor classifier (ENN) to overcome this issue. Our proposed method achieves the same regret as its oracle version on the expert data with the same size. We also propose two algorithms to estimate the worker quality if it is unknown in practice. One method constructs the estimators for worker quality based on the denoised worker labels through applying kNN classifier on expert data. Unlike previous worker quality estimation methods, which have no statistical guarantee, it achieves the same regret as the ENN with observed worker quality. The other method estimates the worker quality iteratively based on ENN, and it works well without expert data required by most previous methods.<br></div>

The analysis of spatial point patterns is commonly focused on the distances to the nearest neighbor. The distance of organisms to the edge of the enclosure is also of interest in some biological studies performed in the laboratory. We define the B (border) function and derive its shape assuming complete spatial randomness (CSR) for square, rectangular, circular, and some three-dimensional arenas. The idea is then extended outside the laboratory setting to work with maps and points located in geographical regions. Commands in R ( R Core Team, 2012) to calculate and plot the empirical B̂ function are included. The B function, based on distances to the nearest edge, in addition to the G function, based on distances to the nearest neighbor, contributes to the understanding of the spatial distribution of the points.

The analysis of spatial point patterns is commonly focused on the distances to the nearest neighbor. The distance of organisms to the edge of the enclosure is also of interest in some biological studies performed in the laboratory. We define the B (border) function and derive its shape assuming complete spatial randomness (CSR) for square, rectangular, circular, and some three-dimensional arenas. The idea is then extended outside the laboratory setting to work with maps and points located in geographical regions. Commands in R ( R Core Team, 2012) to calculate and plot the empirical B̂ function are included. The B function, based on distances to the nearest edge, in addition to the G function, based on distances to the nearest neighbor, contributes to the understanding of the spatial distribution of the points.