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 26 for “"clustering coefficient"”.
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Generating Random Graphs with Tunable Clustering Coefficient
Most real-world networks exhibit a high clustering coefficient— the probability that two neighbors of a node are also neighbors of each other. We propose four algorithms CONF-1, CONF-2, THROW-1, and THROW-2 which are based on the configuration model and that take triangle degree sequence …
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Jungčių prognozavimas, paremtas orientuoto tinklo klasterizacijos koeficientu /
… prediction methods based on a concept of digraph clustering coefficient proposed by M. Bloznelis and L. Leskelä. The goal of this research is to define new link prediction indices derived from the clustering coefficient mentioned above. We also aim to empirically evaluate the performance of the …
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THE PHONOGRAPHIC NETWORK OF LANGUAGE: USING NETWORK SCIENCE TO INVESTIGATE THE PHONOLOGICAL AND ORTHOGRAPHIC SIMILARITY STRUCTURE OF LANGUAGE
… network—phonographic degree and phonographic clustering coefficient—on spoken and visual word recognition. Results indicated a facilitatory effect of phonographic degree on visual word recognition, and a facilitatory effect of phonographic clustering coefficient on spoken word recognition. The …
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Early neighborhood disadvantage and risk for internalizing problems: underlying neurobiological mechanisms
… 2.5 (PM2.5) exposure. Global efficiency and clustering in the central executive (CEN), default mode (DMN), and salience networks (SN) were computed. Hair cortisol concentration (HCC) and perceived stress were measured for the full sample. For a subsample (N = 40), resting heart rate …
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Models for the Generation of Heterogeneous Complex Networks
… as: (i) thesmall world effect,(ii) high average clustering coefficient, (iii) scale-free power law degree distribution, and (iv) emergence of community structure. These four statistical properties are further described later in this dissertation. Mostmodels used to generate complex networks …
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The Effects of Chronic Sleep Deprivation on Sustained Attention: A Study of Brain Dynamic Functional Connectivity
… functional networks, using network measures of clustering coefficient and characteristics path length. In the chronic sleep deprivation condition, a compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed. Specifically, …
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Variational approximation for importance sampling and statistical inference on social influence
… with small-world properties, namely with a high clustering coefficient and a low average path length. We generalize the regular Erd\H{o}s-R\'enyi dyadic random graph by considering higher-order motif, which is triadic graph. We show some properties of our proposed model, analyze the probability …
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Quantifying Resting-State Functional Connectivity in Critically Brain-Injured Patients: A Graph-Theoretical Approach with fNIRS
… for three graph metrics, including degree, clustering coefficient, and local efficiency. Further investigation using machine learning algorithms revealed that these metrics can be used to distinguish between patients and healthy controls with 76% accuracy, and between good and poor patient …
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Kin and social network structure in two populations of Octodon degus
… network parameters (association, strength, and clustering coefficient) in order to determine if these aspects of sociality were driven by kinship. I analyzed social network parameters relative to ecological conditions at burrow systems used by individuals to determine if ecological …
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Nested (2,r)-regular graphs and their network properties.
… properties such as the average path length, clustering coefficient, and the spectrum of these nested graphs.</p>
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A New Look at Clustering Coefficients with Generalization to Weighted and Multi-Faction Networks
… a new method for studying local and global clustering in networks employing random walk pairs. The method is intuitive and directly generalizes standard local and global clustering coefficients to weighted networks and networks containing nodes of multiple types. In the case of two-mode …
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The structure and evolution of the African air transport network
… evolution. A gradual decrease in the average clustering coefficient and degree assortativity coefficient but an increase in the Gini coefficient and largest degree suggest that the network aligns to a growing airline hub-and-spoke structure. During this period, the COVID-19 pandemic occurs and …
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Connectome-Constrained Artificial Neural Networks
… to chaotic behaviour. We also observe that the clustering coefficient of the fly network, and its particular non-zero weight positions, are important for reducing model variance. These findings suggest that BNNs have distinct advantages over arbitrarily-weighted ANNs; notably, from their …
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Análise de grafos de textos literários: investigação de traços psicóticos
… attributes (average total degree, density, clustering coefficient). The results revealed a clear pattern: While lexical diversity and connectivity increased asymptotically over time, recurrence decreased. These findings are compatible with the notion that psychosis is an early trait of our …
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Complex network analysis of extreme precipitations in North America
… geographical distance, betweenness centrality, clustering coefficient, and long-ranged directedness. We found hubs—locations important in propagating EPEs and teleconnections—in areas such as Montana, Wyoming, Alberta, and Saskatchewan in the summer and the West Coast and eastern North America …
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Essays on Information Technologies, Social Networks and Individual Economic Outcomes
… well as a globally negative relationship between clustering coefficient and labor market mobility, suggesting that even individually, strong ties are not always more useful than weak ties.
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Contributions to Data Reduction and Statistical Model of Data with Complex Structures
… data by leveraging the au- toregression and clustering. Existing time series forecasting method treat each series data independently and ignore their inherent correlation. To fill this gap, I proposed a clustering based on autoregression and control the sparsity of the transition matrix …
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Analyzing The Community Structure Of Web-like Networks: Models And Algorithms
… the community. In each step, the algorithm uses clustering coefficient--a parameter that measures the fraction of the neighbors of a node that are neighbors themselves--to decide which nodes from the neighborhood should be pulled in the community. This algorithm has time complexity of order , …
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Effective Methods of Semantic Analysis in Spatial Contexts
… regions of high entity density based on a clustering coefficient; (5) a ranking strategy based on connectivity strength which differentiates important relationships from less relevant ones; (6) a distance measure between entity sequences that quantifies the most related streams of …
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Foundations for a Network Model of Destination Value Creation
… out-degree centralization, and network global clustering coefficient are found to have negative and statistically significant effects on destination value creation, while network in-degree centralization, network betweenness centralization, and network subcommunity count are found to have …
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