Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 112 for “"Clustering Analysis"”.
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Clustering analysis using Swarm Intelligence
… application of the swarm intelligence methods in clustering analysis of datasets. The main objectives of the thesis are ∙ Take the advantage of a novel evolutionary algorithm, called artificial bee colony, to improve the capability of K-means in finding global optimum clusters in nonlinear …
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Clustering Analysis of Zernike Coefficients Through Quantile Regression
<p>In this thesis, we use the model-based clustering procedure to cluster fifteen Zernike coefficients into groups. Quantile regressions are considered to describe the relationship between Zernike coefficients and pupil size. We employ Gibbs sampler and adaptive rejection Metropolis sampling to …
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Clustering Analysis of Zernike Coefficients From High Order Aberration Patients
<p>This thesis focuses on clustering fifteen Zernike coefficients using the method of clustering of linear regression models (CLM). EM algorithm is used to infer the maximum likelihood estimate of parameters for each cluster. Bayesian information criterion (BIC) combined with Bootstrapped maximum …
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Construction of efficient indexes from Fuzzy Clusters: preliminary study
… database needs to be analyzed. In fields of data analysis as well as machine learning, there is a method of so-called clustering analysis. This method identifies a partition (i.e. a collection of classes or clusters) over data corresponding to their density. The thesis generally hypothesizes that …
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Three Novel Algorithms for Triangle Mesh Processing: Progressive Delaunay Refinement Mesh Generation, Mls-Based Scattered Data Interpolation and Constrained Centroid Voronoi-Based Quadrangulation
… in this thesis uses quantization theory and clustering analysis to generate multiresolution quadrilateral mesh.
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MALDI-TOF MS Data Processing Using Wavelets, Splines and Clustering Techniques.
… multivariable statistics techniques such as clustering analysis, and signal processing techniques to evaluate the complicated biological signals. A MatLab implementation shows the processing steps consecutively including step-interval unification, adaptive wavelet denoising, baseline …
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Designing two-stage recycling operations for increased usage of undervalued raw materials
… existing data from the recycling industry. A clustering analysis provides criteria for grouping raw materials by recognizing the pattern of varied compositions. This grouping (binning) strategy using the clustering analysis increases the homogeneity and distinctiveness of uncertain raw …
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Proteome-Wide Prediction of Acetylation Substrates
… describe my basic computational methods, using a clustering analysis of protein sequences to predict lysine acetylation based on the sequence characteristics of acetylated lysines within histones. I define a local amino acid sequence composition that represents potential acetylation sites by …
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Clustering Methods for Network Adjacency Data
Clustering analysis aims to detect the topological community-structure of networks (connected graphs with n vertices and m edges), and studies inherent relations behind partitions. In this thesis, we consider far-reaching model-free clustering algorithms including Girvan and Newman’s edge …
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C6 and C9 volatile compounds in 223 cucumbers (cucumis sativus L.) In Genome-Wide Association Studies (GWAS)
Volatile profile analysis has been conducted on limited cucumber varieties. This research aimed to quantify C6 and C9 compounds in 223 GWAS cucumber varieties. A comprehensive analysis of volatiles was performed using solid-phase microextraction gas chromatography-mass spectrometry (SPME-GC-MS). …
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APPLY DATA CLUSTERING TO GENE EXPRESSION DATA
<p>Data clustering plays an important role in effective analysis of gene expression. Although DNA microarray technology facilitates expression monitoring, several challenges arise when dealing with gene expression datasets. Some of these challenges are the enormous number of genes, the …
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A Colorimetric Sensor Array for Aqueous Analyses
… analyses, including principal component analysis (PCA) and hierarchical clustering analysis (HCA) were used to analyze the digital databases. This technique has also been successfully applied to the analyses of complex mixtures; various commercial beverages, including sodas, beers and …
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Požiūrio į senėjimą ir pagyvenusius žmones sąsajos su asmenybiniais ir psichosocialiniais veiksniais /
… of the averages, also a regressive and clustering analysis. It is only the openness and the agreeableness from the Big Five, which are linked to ageism and anxiety about ageing. As men are more open-minded and less conscientious, they have a poorer opinion of the elderly, but more …
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The SUN Action database : collecting and analyzing typical actions for visual scene types
… overall diversity of responses. A hierarchical clustering analysis reveals a heterogeneous clustering structure, with some categories readily grouping together, and other categories remaining apart even at coarse clustering levels. Finally, two simple classifiers are introduced for predicting …
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Cartilage mechanobiology and transcriptional effects of combined mechanical compression and IGF-1 stimulation on bovine cartilage explants
… compression in cartilage explants. Discussion: Clustering analysis revealed five distinct groups. TIMP-3 and ADAMTS-5, MMP-l and IGF-2, and IGF-1 and Collagen II, were all robustly co-expressed under all conditions tested. In comparing gene expression levels to previously measured aggrecan …
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Measuring Incrementally Developed Model Transformations Using Change Metrics
… changes is demonstrated using exploratory clustering analysis on a transformation task. We show how, for this transformation task using both languages, metrics derived from the difference model result in clusters that reflect characteristics of individual changes, in contrast to clusters …
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An Exploration of Neuroanatomical Signatures of Pediatric Bipolar Disorder Using Structural Neuroimaging
… models to assess BD risk and 2) data-driven clustering of patients based on specific neuroanatomical profiles, i.e. biotypes. While the normative development model was unable to quantify BD risk at an individual level, it nevertheless emphasized the heterogeneous nature of both healthy and BD …
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Source Parameters and Tectonic Setting of the 2017 St. Elias Earthquake Sequence near the Southern Terminus of the Eastern Denali Fault, Northwestern Canada
… relocation method, coupled with clustering analysis, was applied to the aftershock distribution, confirming that seismicity was localized along two previously unmapped fault structures. Stress inversion indicates that the maximum principal stress axis is oriented almost …
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Genomic Profiling of Alternative splicing in liver cancer
… on progression of liver cancer. By performing clustering analysis of alternative splicing isoforms, two different subtypes with distinct clinical prognosis were found from the of liver cancer patients. The genes observed in subtypes were related to regulation of apoptosis, regulation of cell …
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