No description available.

No description available.

No description available.

The aim of this study was to compare the incidence of root canal dentinal micro-cracks after canal instrumentation using reciprocating files (WaveOne Gold® and Twisted Adaptive®) and continuous rotation files (Edge Evolve® and EndoSequence®) in an ex-vivo benchtop study. This project used a novel methodology of finding dentinal defects using the “K-cube”, which allows evaluators to visualize sectioned root surfaces before instrumentation and after instrumentation. Mesial roots from 40 human mandibular first molars were divided into 4 groups of 10 for each file type. Root section pictures were taken with a Zeiss Discovery V20 stereomicroscope before and after canal instrumentation. Each of the pre-instrumentation and post-instrumentation images were evaluated for dentinal defects by four calibrated endodontists utilizing REDCap survey. Using a chi-square analysis, there was no statistically significant difference between dentinal defects created by continuous and reciprocating rotation (p=0.1924) and no difference between the four file types (p=0.2317).

The Large Hadron Collider (LHC) located at CERN, Geneva has finally been put in production, generating unprecedented amount of data. These data are distributed across many computing centers all over the world that form the Worldwide LHC Computing Grid (WLCG). One of the main issues since the beginning of the WLCG project is an effective file access on the site level in order to fully exploit huge computing farms. The aim of this thesis is to explore existing data distribution work flows, standards, methods and protocols. An integral part of the work is the analysis of jobs of physicists to understand input/output workloads and to discover possible inefficiencies. Then, new upcoming solutions are evaluated in terms of performance, sustainability and integration into existing frameworks. It is expected that these solutions will be based on distributed file systems such as NFS 4.1, Lustre and HDFS.

M.A. (Information Science) / Please refer to full text to view abstract

O termo \"Psicossomática\" utilizado para designar a inter-relação entre sintomas físicos e fatores emocionais nas diversas patologias variou durante anos provocando confusões. Os diversos tratamentos médicos podem elevar gastos nos serviços de saúde. O presente estudo busca caracterizar a demanda de pacientes do Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo (HCFMRP-USP) no período de 1996 a 2004 cujo diagnóstico é Doença Psicossomática. A coleta de dados foi realizada em prontuários médicos, no Serviço de Arquivo Médico (SAME), com a categoria diagnóstica F 45 que, de acordo com o CID-10, significa Transtorno de Somatização; essa categoria foi utilizada como palavra chave no banco de dados. Na busca pelos prontuários foram encontrados 397, porém apenas 136 registravam o diagnóstico F 45, amostra do presente estudo. A coleta foi dificultada devido às letras ilegíveis e à falta de dados nos prontuários relacionados aos itens do instrumento de coleta. A população constitui-se pela maioria nascida no Estado de São Paulo com 43% da amostra, desses 14% nasceram em Ribeirão Preto-SP e 29% nasceram em outras cidades do Estado; são moradores do Estado de São Paulo 48%, desses 26% moram em Ribeirão Preto e 22% moram em outras cidades do Estado; 74,2% dos indivíduos são do sexo feminino; 87% têm cor de pele branca; 57% têm 1º grau incompleto; 70% professam a religião católica. Quanto ao estado civil, tem-se que 57% dos indivíduos são casados/amasiados; 52,96% possuem filhos; 32% dos indivíduos vivem com uma pessoa na mesma casa; 43,4% exercem a ocupação do lar e 14% dos indivíduos possuem como fator estressor problemas de saúde. Os indivíduos atendidos na Unidade de Emergência, em sua maior parte, comparecem numa freqüência de até cinco vezes (35%); os atendidos nos ambulatórios do HC, em sua maioria, comparecem numa freqüência de 20 vezes (49%). Os internados possuem a freqüência de zero a cinco vezes com 57% dos indivíduos. O local com o maior número de atendidos é a Unidade de Emergência com 43% dos indivíduos da amostra. Os dados encontrados caracterizam a população de indivíduos portadores de Transtorno de Somatização como: mulheres, casadas ou amasiadas, de baixa renda, sem filhos, do lar, com faixa etária entre 43 e 53 anos, de cor branca, com 1º grau de escolaridade incompleta, católicas, que moram com uma pessoa na mesma casa, nascidas em outras cidades do Estado de São Paulo, residentes em Ribeirão Preto e que freqüentam a Unidade de Emergência sem seguir um tratamento médico. Dessa forma, esses pacientes com Transtorno Psicossomático, isto é, pacientes com Transtorno de Somatização, contribuem para elevar os custos e a demanda dos Serviços de Saúde. Se esses indivíduos fossem atendidos de acordo com suas necessidades individuais, as filas de espera poderiam diminuir e suas condições de saúde poderiam ser melhores. / The term \"Psychosomatics\", used to designate the interrelation between physical symptoms and emotional factors in different diseases has varied over time, provoking confusion in medical treatments, and has increased health service expenses. This study aims to characterize the demand of patients who attended the Hospital das Clínicas of the University of São Paulo at Ribeirão Preto Medical School (HCFMRP-USP) between 1996 and 2004, and were diagnosed as Psychosomatic Disease. Data were collected in medical files at the Medical Filing Service (SAME), which contained the diagnosis category F 45. According to the ICD-10, this means Somatization Disorder. This category was used as a key word in the file search. We found 397 files, only 136 of which contained registries of the F45 diagnosis and constituted the study sample. Data collection was impaired by unreadable handwriting and lack of data about items for data to be surveyed. The population consists of a majority born in the State of São Paulo (42%), 29% born in other cities in the same state and 14% in Ribeirão Preto; most participants (26%) live in Ribeirão Preto, while 22% live in other cities in the same state; 74.2% of individuals are women; 87% of the sample are white; 57% have not finished primary education and 70% proclaim themselves Catholic. As to civil status, 57% of participants are married or have a fixed partner; 52,96% have children; 32% of individuals live with one person in the same house, 43.4% are housewives, and 14% of individuals possess health problems as a stressor. Most of the participants (35%) attended at the Emergency Unit make up to five visits; individuals attended at the HC outpatient clinics mostly (49%) make 20 visits. Hospitalized patients make between zero and five visits, with 57% of the sample. The Emergency Unit attends the largest number of patients (43%). These data characterize the patient population with Somatization Disorder as: women, married or with a fixed partner, low income, without children, housewives, age range between 43 and 53 years, white, unfinished primary education, Catholic, live with one person in the same house, born in other cities of the State of São Paulo and living in Ribeirão Preto, and visit the Emergency Unit without receiving further medical follow-up treatment. Thus, patients with psychosomatic disorder, that is, patients with somatization disorder, contributing to high health system costs and also generate high care demands. If this population s needs were adequately attended to, waiting lines could decrease and these individuals could improve their health conditions.

Peng, Xiang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 98-115). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Statement --- p.3 / Chapter 1.2 --- Major Contributions --- p.6 / Chapter 1.3 --- Thesis Outline --- p.7 / Chapter 2 --- Background Study --- p.9 / Chapter 2.1 --- Content-based Image Retrieval --- p.9 / Chapter 2.1.1 --- Image Representation --- p.11 / Chapter 2.1.2 --- High Dimensional Indexing --- p.15 / Chapter 2.1.3 --- Image Retrieval Systems Design --- p.16 / Chapter 2.2 --- Relevance Feedback --- p.19 / Chapter 2.2.1 --- Self-Organizing Map in Relevance Feedback --- p.20 / Chapter 2.2.2 --- Decision Tree in Relevance Feedback --- p.22 / Chapter 2.2.3 --- Bayesian Classifier in Relevance Feedback --- p.24 / Chapter 2.2.4 --- Nearest Neighbor Search in Relevance Feedback --- p.25 / Chapter 2.2.5 --- Support Vector Machines in Relevance Feedback --- p.26 / Chapter 2.3 --- Imbalanced Classification --- p.29 / Chapter 2.4 --- Active Learning --- p.31 / Chapter 2.4.1 --- Uncertainly-based Sampling --- p.33 / Chapter 2.4.2 --- Error Reduction --- p.34 / Chapter 2.4.3 --- Batch Selection --- p.35 / Chapter 2.5 --- Convex Optimization --- p.35 / Chapter 2.5.1 --- Overview of Convex Optimization --- p.35 / Chapter 2.5.2 --- Linear Program --- p.37 / Chapter 2.5.3 --- Quadratic Program --- p.37 / Chapter 2.5.4 --- Quadratically Constrained Quadratic Program --- p.37 / Chapter 2.5.5 --- Cone Program --- p.38 / Chapter 2.5.6 --- Semi-definite Program --- p.39 / Chapter 3 --- Imbalanced Learning with BMPM for CBIR --- p.40 / Chapter 3.1 --- Research Motivation --- p.41 / Chapter 3.2 --- Background Review --- p.42 / Chapter 3.2.1 --- Relevance Feedback for CBIR --- p.42 / Chapter 3.2.2 --- Minimax Probability Machine --- p.42 / Chapter 3.2.3 --- Extensions of Minimax Probability Machine --- p.44 / Chapter 3.3 --- Relevance Feedback using BMPM --- p.45 / Chapter 3.3.1 --- Model Definition --- p.45 / Chapter 3.3.2 --- Advantages of BMPM in Relevance Feedback --- p.46 / Chapter 3.3.3 --- Relevance Feedback Framework by BMPM --- p.47 / Chapter 3.4 --- Experimental Results --- p.47 / Chapter 3.4.1 --- Experiment Datasets --- p.48 / Chapter 3.4.2 --- Performance Evaluation --- p.50 / Chapter 3.4.3 --- Discussions --- p.53 / Chapter 3.5 --- Summary --- p.53 / Chapter 4 --- BMPM Active Learning for CBIR --- p.55 / Chapter 4.1 --- Problem Statement and Motivation --- p.55 / Chapter 4.2 --- Background Review --- p.57 / Chapter 4.3 --- Relevance Feedback by BMPM Active Learning . --- p.58 / Chapter 4.3.1 --- Active Learning Concept --- p.58 / Chapter 4.3.2 --- General Approaches for Active Learning . --- p.59 / Chapter 4.3.3 --- Biased Minimax Probability Machine --- p.60 / Chapter 4.3.4 --- Proposed Framework --- p.61 / Chapter 4.4 --- Experimental Results --- p.63 / Chapter 4.4.1 --- Experiment Setup --- p.64 / Chapter 4.4.2 --- Performance Evaluation --- p.66 / Chapter 4.5 --- Summary --- p.68 / Chapter 5 --- Large Scale Learning with BMPM --- p.70 / Chapter 5.1 --- Introduction --- p.71 / Chapter 5.1.1 --- Motivation --- p.71 / Chapter 5.1.2 --- Contribution --- p.72 / Chapter 5.2 --- Background Review --- p.72 / Chapter 5.2.1 --- Second Order Cone Program --- p.72 / Chapter 5.2.2 --- General Methods for Large Scale Problems --- p.73 / Chapter 5.2.3 --- Biased Minimax Probability Machine --- p.75 / Chapter 5.3 --- Efficient BMPM Training --- p.78 / Chapter 5.3.1 --- Proposed Strategy --- p.78 / Chapter 5.3.2 --- Kernelized BMPM and Its Solution --- p.81 / Chapter 5.4 --- Experimental Results --- p.82 / Chapter 5.4.1 --- Experimental Testbeds --- p.83 / Chapter 5.4.2 --- Experimental Settings --- p.85 / Chapter 5.4.3 --- Performance Evaluation --- p.87 / Chapter 5.5 --- Summary --- p.92 / Chapter 6 --- Conclusion and Future Work --- p.93 / Chapter 6.1 --- Conclusion --- p.93 / Chapter 6.2 --- Future Work --- p.94 / Chapter A --- List of Symbols and Notations --- p.96 / Chapter B --- List of Publications --- p.98 / Bibliography --- p.100

Wong, Yuk Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 95-100). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Contribution --- p.3 / Chapter 1.3 --- Organization of This Work --- p.5 / Chapter 2 --- Literature Review --- p.6 / Chapter 2.1 --- Content-based Image Retrieval --- p.6 / Chapter 2.1.1 --- Query Technique --- p.6 / Chapter 2.1.2 --- Relevance Feedback --- p.7 / Chapter 2.1.3 --- Previously Proposed CBIR systems --- p.7 / Chapter 2.2 --- Invariant Local Feature --- p.8 / Chapter 2.3 --- Invariant Local Feature Detector --- p.9 / Chapter 2.3.1 --- Harris Corner Detector --- p.9 / Chapter 2.3.2 --- DOG Extrema Detector --- p.10 / Chapter 2.3.3 --- Harris-Laplacian Corner Detector --- p.13 / Chapter 2.3.4 --- Harris-Affine Covariant Detector --- p.14 / Chapter 2.4 --- Invariant Local Feature Descriptor --- p.15 / Chapter 2.4.1 --- Scale Invariant Feature Transform (SIFT) --- p.15 / Chapter 2.4.2 --- Shape Context --- p.17 / Chapter 2.4.3 --- PCA-SIFT --- p.18 / Chapter 2.4.4 --- Gradient Location and Orientation Histogram (GLOH) --- p.19 / Chapter 2.4.5 --- Geodesic-Intensity Histogram (GIH) --- p.19 / Chapter 2.4.6 --- Experiment --- p.21 / Chapter 2.5 --- Feature Matching --- p.27 / Chapter 2.5.1 --- Matching Criteria --- p.27 / Chapter 2.5.2 --- Distance Measures --- p.28 / Chapter 2.5.3 --- Searching Techniques --- p.29 / Chapter 3 --- A Distributed Scheme for Large-Scale CBIR --- p.31 / Chapter 3.1 --- Overview --- p.31 / Chapter 3.2 --- Related Work --- p.33 / Chapter 3.3 --- Scalable Content-Based Image Retrieval Scheme --- p.34 / Chapter 3.3.1 --- Overview of Our Solution --- p.34 / Chapter 3.3.2 --- Locality-Sensitive Hashing --- p.34 / Chapter 3.3.3 --- Scalable Indexing Solutions --- p.35 / Chapter 3.3.4 --- Disk-Based Multi-Partition Indexing --- p.36 / Chapter 3.3.5 --- Parallel Multi-Partition Indexing --- p.37 / Chapter 3.4 --- Feature Representation --- p.43 / Chapter 3.5 --- Empirical Evaluation --- p.44 / Chapter 3.5.1 --- Experimental Testbed --- p.44 / Chapter 3.5.2 --- Performance Evaluation Metrics --- p.44 / Chapter 3.5.3 --- Experimental Setup --- p.45 / Chapter 3.5.4 --- Experiment I: Disk-Based Multi-Partition Indexing Approach --- p.45 / Chapter 3.5.5 --- Experiment II: Parallel-Based Multi-Partition Indexing Approach --- p.48 / Chapter 3.6 --- Application to WWW Image Retrieval --- p.55 / Chapter 3.7 --- Summary --- p.55 / Chapter 4 --- Image Retrieval System for IND Detection --- p.60 / Chapter 4.1 --- Overview --- p.60 / Chapter 4.1.1 --- Motivation --- p.60 / Chapter 4.1.2 --- Related Work --- p.61 / Chapter 4.1.3 --- Objective --- p.62 / Chapter 4.1.4 --- Contribution --- p.63 / Chapter 4.2 --- Database Construction --- p.63 / Chapter 4.2.1 --- Image Representations --- p.63 / Chapter 4.2.2 --- Index Construction --- p.64 / Chapter 4.2.3 --- Keypoint and Image Lookup Tables --- p.67 / Chapter 4.3 --- Database Query --- p.67 / Chapter 4.3.1 --- Matching Strategies --- p.68 / Chapter 4.3.2 --- Verification Processes --- p.71 / Chapter 4.3.3 --- Image Voting --- p.75 / Chapter 4.4 --- Performance Evaluation --- p.76 / Chapter 4.4.1 --- Evaluation Metrics --- p.76 / Chapter 4.4.2 --- Results --- p.77 / Chapter 4.4.3 --- Summary --- p.81 / Chapter 5 --- Shape-SIFT Feature Descriptor --- p.82 / Chapter 5.1 --- Overview --- p.82 / Chapter 5.2 --- Related Work --- p.83 / Chapter 5.3 --- SHAPE-SIFT Descriptors --- p.84 / Chapter 5.3.1 --- Orientation assignment --- p.84 / Chapter 5.3.2 --- Canonical orientation determination --- p.84 / Chapter 5.3.3 --- Keypoint descriptor --- p.87 / Chapter 5.4 --- Performance Evaluation --- p.88 / Chapter 5.5 --- Summary --- p.90 / Chapter 6 --- Conclusions and Future Work --- p.92 / Chapter 6.1 --- Conclusions --- p.92 / Chapter 6.2 --- Future Work --- p.93 / Chapter A --- Publication --- p.94 / Bibliography --- p.95

Ye, Chong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 61-63). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Classification of P2P systems --- p.1 / Chapter 1.2 --- Replication in P2P systems --- p.3 / Chapter 1.3 --- Related work --- p.7 / Chapter 1.4 --- Organization --- p.10 / Chapter 1.5 --- Publications derived from this work --- p.11 / Chapter 2 --- P2P Replication System --- p.12 / Chapter 2.1 --- Peers --- p.13 / Chapter 2.2 --- Erasure code replication --- p.13 / Chapter 2.3 --- Estimation of file availability --- p.14 / Chapter 2.4 --- Problem formulation --- p.15 / Chapter 2.5 --- Performance metrics --- p.17 / Chapter 3 --- Decentralized Decisions --- p.19 / Chapter 3.1 --- Writable peer set --- p.20 / Chapter 3.2 --- Stretch factor estimation --- p.21 / Chapter 3.3 --- Locking phase --- p.22 / Chapter 4 --- Equal Weight Replication --- p.23 / Chapter 4.1 --- The decentralized replication algorithms --- p.23 / Chapter 4.1.1 --- Random algorithm --- p.23 / Chapter 4.1.2 --- Group partition algorithm --- p.25 / Chapter 4.1.3 --- High Available First (HAF) algorithm --- p.27 / Chapter 4.2 --- Evaluation of algorithms --- p.29 / Chapter 4.2.1 --- Simulation setup --- p.29 / Chapter 4.2.2 --- Simulation results --- p.31 / Chapter 4.3 --- Summary --- p.40 / Chapter 4.4 --- Clarification of individual contributions --- p.41 / Chapter 5 --- Replication with Preferences --- p.43 / Chapter 5.1 --- Problem re-defined --- p.44 / Chapter 5.2 --- The Bi-weight model --- p.46 / Chapter 5.3 --- The statistical rounding policy --- p.48 / Chapter 5.4 --- The distributed replication algorithm --- p.49 / Chapter 5.5 --- Evaluation of the algorithm --- p.51 / Chapter 5.5.1 --- Simulation setup --- p.51 / Chapter 5.5.2 --- Simulation results --- p.52 / Chapter 5.6 --- Discussion --- p.56 / Chapter 5.7 --- Summary --- p.57 / Chapter 6 --- Future work --- p.58 / Chapter 7 --- Conclusion --- p.59 / Bibliography --- p.61