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 18 of 18 for “"graph network"”.
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Structural brain connectivity of HIV-positive children: a graph network analysis study
… in adults and children infected by HIV. Graph theory analyses have been applied to HIV neuropathogenesis previously, these have demonstrated significant disruptions to brain connectivity in older HIV+ adults on treatment. However, no previous studies have investigated the same topological …
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Classification and visualisation of text documents using networks
… of text classification and text visualisation graph/network theoretic methods can be applied effectively. For text classification we assessed the effectiveness of graph/network summary statistics to develop weighting schemes and features to improve test accuracy. For text visualisation we …
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Novel Networks in Collider Searches for New Physics
… space. A map of event similarities forms a graph network, which provides a convenient range of network variables able to quantify local topologies. In networks constructed from nodes of LHC events, we aim to use network variables to increase sensitivity to anomalous topologies local to BSM …
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Investigating the impact of ageing on the tumour microenvironment and its crosstalk with malignant cells in pancreatic cancer
… mouse models. Single- cell transcriptomics, graph network-based machine learning, flow cytometry and histological analyses showed that aged models have a more inflammatory TME relative to young models. Moreover, tumours from aged models showed a higher abundance of senescent cells, suggesting …
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Mathematical and computational approaches to contagion dynamics on networks
… In particular we introduce the basics of graph/network theory, epidemiological models (both well mixed and on networks), and mobility models (the gravity and radiation models). After the introduction of these topics, we propose a general framework for epidemiological network models from …
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Advancing 6DoF Object Pose Estimation: Keypoint Voting, Optimal Keypoint Sampling, and Bridging the Simulation-to-real Gap
… and RGB-D methods. Second, KeyGNet leverages a graph network to optimize the keypoint selection, improving accuracy and efficiency by learning dispersed, evenly distributed keypoints. KeyGNet enhances performance across all metrics, notably increasing ADD(S) on Occlusion LINEMOD by 16.4% and …
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Using small world models to study infection communication and control
… Attention has focused in recent years on graph (network) models and especially on those exhibiting the small-world properties described by Watts and Strogatz in “Nature” in 1998. This thesis examines such graph models, discovering several attributes which may yield improved results. In …
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Multimedia Big Data Analytics and Fusion for Data Science
… optimization strategy. First, a hierarchical graph fusion network is presented to capture the inter-modality correlations among modalities. The network hierarchy models the modality-wise combinations with gradually increased complexity to explore all n-modality interactions. Next, an adaptive …
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Improving the capacity of radio spectrum: exploration of the acyclic orientations of a graph
… frequency assignment within a telecommunications network. The solution space of the frequency assignment problem is best described by the acyclic orientations of the network. An acyclic orientation Ɵ of a graph (network) G is an orientation of the edges of the graph which does not create any …
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Visual Experience in Temporal Situational Context: Method of Matching and Modeling in Design
… context called the Temporal Framed Scene Graph (TFSG), and examined in two projects. The first project investigates the modeling of human behavior in an augmented reality exhibition using a recurrent graph network, with behavior represented in TFSG format. In the second project, …
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Cost-effective Design of Automotive Framing Systems Using Flexibility and Reconfigurability Principles
… into systems, sub-systems, and modular assembly. Graph network (NW), change propagation index (CPI) and hybrid design structure matrix (HDSM) were introduced. Design structures matrix (DSM) and hybrid design structure matrix (HDSM) were used along with axiomatic design (AD) to ensure customer …
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Connectivity biomarkers in neurodegenerative tauopathies
… and how the anatomical and neurochemical networks that underlie clinical features might be altered by disease. I investigate simple clinical biomarkers, showing that a two-minute test of verbal fluency is a potential diagnostic biomarker to distinguish between PD and PSP and that the ACE-R …
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Optimizing and Understanding Network Structure for Diffusion
Given a population contact network and electronic medical records of patients, how to distribute vaccines to individuals to effectively control a flu epidemic? Similarly, given the Twitter following network and tweets, how to choose the best communities/groups to stop rumors from spreading? How to …
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Novel Machine Learning Models Based Uncertainty Estimation and Sequential Predictions for Blockchain Networks
… address to con- duct illicit activities over the network. Consequently, this double-edged sword technology urges the necessity of analysing blockchain data to detect illicit activities. In the existing literature, visual analytics have been widely used to gain useful insights from large-scale …
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Computational and Visual Analyses of Spatial Interactions: A Case Study of the County-to-County Migration In theUs
… contains three different data spaces: (1) the geographic space, such as locations of origins and destinations; (2) the graph/network space, such as flows/links between locations; and (3) the multivariate space, including variables for locations (e.g., unemployment rate, median income) and flows …
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Software and Hardware Co-design for Efficient Neural Networks
Deep Neural Networks (DNNs) offer state-of-the-art performance in many domains but this success comes at the cost of high computational and memory resources. Since DNN inference is now a popular workload on both edge and cloud systems, there is an urgent need to improve its energy efficiency. The …
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Learning aggregates and interpolation for algebraic multigrid
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms
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Investigating the performance of transport infrastructure using real-time data and a scalable multi-modal agent based model
… to quantify temporally and spatially dynamic network performance metrics (eg. journey times on different transport models) and secondly to organise these data sources in a framework which can handle the volume and type of the data and organise the data in a way so that it is useful for the …