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 191 for “"Hierarchical clustering"”.
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Robust curved road boundary identification using hierarchical clustering.
… possible road boundaries through agglomerative hierarchical clustering of edge segments. Each node in the hierarchical clustering is a potential road boundary. Top ranked road boundaries are paired with each other to identify potential road regions. The road regions are then ranked using …
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Hierarchical Clustering Techniques for Energy-efficient Algorithms in WSNs
… by proposing a novel set of Energy-Adaptive Clustering Protocols (ECP) for energy-efficiency in WSNs. The proposed routing strategy takes on several approaches to improve energy efficiency in WSNs. This functional set of protocols are integrated with each other. The proposed novel solutions …
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Exploring Age-Related Metamemory Differences Using Modified Brier Scores and Hierarchical Clustering
… in a list. Our analytical approach includes hierarchical clustering, and we introduce a new measure of MM—the modified Brier—in order to adjust for di↵erences in scale usage between participants. Our data indicate that OAs and YAs di↵er in the strategies they use to assess their memory and in …
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Analysis of the Repeated Measurement Data using the Hierarchical Clustering and Nonlinear Regression Methods in Asthma Pharmacogenetic Study
… ANOVA in the generalized linear model (GLM). A hierarchical clustering method was applied to get daily change (%) of PEFR to combination inhaler. The asthmatics were divided into two groups (favorable vs. poor responses) according to the changes of PEFR using the hierarchical clustering method. …
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Energy-Efficient Measurement of Coverage in Distributed Sensor Networks
… models such as directed diffusion and hierarchical clustering to provide better performance as compared to a centralized scheme. Results obtained from simulation experiments indicate that hierarchical clustering and directed diffusion can be used effectively for coverage measurement. …
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A Combinatorial Tweet Clustering Methodology Utilizing Inter and Intra Cosine Similarity
… This thesis presents a combinatorial hierarchical clustering methodology that categorizes tweets into meaningful clusters by utilizing inter and intra cluster cosine similarity. Cosine similarity is the degree of relativity between two vectors. This thesis proposes a “Combinatorial …
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Content Based Image Retrieval From Microscope Slides
Finally I developed a variation of hierarchical clustering which I call connected clustering. It groups neighboring images that are similar, allowing the system to treat them as a single unit. I show that this improves the response time of the system and reduces redundancy in the results displayed …
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An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange
… This study examines the application of two clustering techniques to the Johannesburg Stock Exchange. First, the application of Salvador and Chan's (2003) L method stopping rule to a hierarchical clustering of time series return data was analysed as a method for determining the number of …
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Data-driven methods for the extraction, grouping and application of terroir units
… MRS outperformed SDS and both the k-means and hierarchical clustering. MRS produced the most spatially uniform and practical zones. Between the two clustering algorithms, hierarchical clustering produced less fragmented results than k-means, and higher Moran’s Index scores. Data-driven zoning …
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A hierarchical approach to improve the ant colony optimization algorithm
… ACO runtime increases dramatically. As a result, clustering nodes into groups is an effective way to reduce the size of the problem while leveraging the advantages of the ACO algorithm. The method for recombining groups of nodes is explored by treating the graph as a hierarchy of clusters, and …
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Coping With New Challengens for Density-Based Clustering
… patterns and relationships in large databases. Clustering is one of the major data mining tasks and aims at grouping the data objects into meaningful classes (clusters) such that the similarity of objects within clusters is maximized, and the similarity of objects from different clusters is …
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A Species Independent Universal Bio-detection Microarray for Pathogen Forensics
… relationships. Classification methods such as hierarchical clustering, Pearson's correlation matrix, principal component analysis and curve fitting regression methods were tested for pathogen specific use cases. Hierarchical clustering and Pearson's correlation matrix methods can establish …
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INVESTIGATIONS ON COGNITIVE COMPUTATION AND COMPUTATIONAL COGNITION
… we have worked on methodological improvements to clustering-based meta-analysis of neuroimaging data, which is a technique that allows to collectively assess, in a quantitative way, activation peaks from several functional imaging studies, in order to extract the most robust results in the …
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Haplotype-Based Association Studies: Approaches to Current Challenges
… of variants, some researchers have employed hierarchical clustering. This thesis starts by addressing the multiple testing problem that results from applying a hierarchical clustering procedure to haplotypes and then performing a statistical test for association at each of the steps in the …
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Optimal clustering techniques for metagenomic sequencing data
… of bacterial microbiota of the human body. Clustering algorithms have been used to search for core microbiota types in the vagina, but results have been inconsistent, possibly due to methodological differences. We performed an extensive comparison of six commonly-used clustering algorithms …
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Quantification of sugars and organic acids in 210 cucumber (cucurbis sativus) varieties for genome-wide association studies (GWAS)
… cucumber samples. A histogram and Agglomerative Hierarchical Clustering (AHC) were performed for each measured variable. The °Brix ranged from 1% – 4.6%. The content of fructose, glucose, and sucrose ranged from 2.88 - 62.28 mg/mL, 3.99 – 63.99 mg/mL, and 0.05 – 13.73 mg/mL, respectively. The pH …
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Google distance analysis of the MIT curriculum
… were used by an MDS layout algorithm and a Hierarchical Clustering algorithm to suggest two new organizations each for Department 6 (E.E. and C.S.) and for the MIT Departments into Schools. Convex hulls in MDS graphs of Department 6, colored based on classes a student has taken, are also …
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THE EFFECT OF BASELINE CLUSTER STRATIFICATION ON THE POWER OF PRE-POST ANALYSIS
… two time points, where strata are determined by clustering on baseline outcomes of the primary measure, is considered. A modified hierarchical clustering algorithm is developed which guarantees optimality as well as requiring each cluster to have at least one subject per study arm. The power is …
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C6 and C9 volatile compounds in 223 cucumbers (cucumis sativus L.) In Genome-Wide Association Studies (GWAS)
… was observed for 12 of them. Aggregation Hierarchical Clustering (AHC) analysis using dendrograms progressively grouped the C6 and C9 compounds into three clusters using their dissimilarity values. Heat map clustering analysis displayed the similarity of volatile compounds in different …
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Molecular Signatures of gastric cancer: An integrated approach to molecular cytogenetics, whole genome copy number and transcriptome profiles
… lines segregated distinctly in supervised hierarchical clustering of 18q genes. Immunohistochemical staining of 18q proteins, Serpin B8 and CD226 antigen, showed overexpression in breakapart-positive primary gastric cancers. Other molecular signatures from whole genome copy number, mRNA and …
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