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.
Results
Showing 1 to 20 of 107 for “"computational challenges."”.
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Tackling Computational Challenges in High-Throughput RNA Interference Screening
… Huge data sets are being generated, but computational challenges remain in data analysis and hit identification, which have become hurdles in HTS. These must be tackled before we can more accurately and precisely interpret the HTS results, since they are often blurred by spatial noise and …
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Addressing the Analytical and Computational Challenges Using Machine Learning in Biomedical Research
… leverages ML's capabilities to address the computational challenges spanning diverse areas, including adaptive clinical trial designs, survival analysis, and high-dimensional genetic data analysis. Specifically, Chapter 2 focused on the application of ML in response-adaptive randomization …
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Estimating the parameters of a Thévenin equivalent system based on output voltage and current measurements: computational challenges and simulated studies
This thesis presents a study of the computational challenges when estimating the Thévenin equivalent parameters at a large-scale power system network based on local measurements. The estimation will use a common mathematical method for an overdetermined system. The motivation is taken from phasor …
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Risk-sensitive security-constrained economic dispatch via critical region exploration
… flow models, corrective SCED poses significant computational challenges owing to an increase in the dimensionality arising from additional recourse decisions and the number of contingencies to guard against. This thesis analyzes the benefits of allowing recourse actions for simple networks and …
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Fluid-Structure Interaction Modeling of Parachutes with Disreefing and Modified Geometric Porosity and Separation Aerodynamics of a Cover Jettisoned to the Spacecraft Wake
… of spacecraft parachutes involves a number of computational challenges. The canopy complexity created by the hundreds of gaps and slits and design-related modification of that geometric porosity by removal of some of the sails and panels are among the formidable challenges. Disreefing from one …
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Microarray gene expression data analysis using machine learning and neural networks
… gene activities of the whole genome. However, computational challenges have to be faced as a result of the large volume of generated data. In this dissertation, two important applications of microarray data, i.e., genetic regulatory networks inference and cancer classification, are addressed …
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Toward Faster Methods in Bayesian Unsupervised Learning
… of Bayesian unsupervised learning faces three computational challenges. Firstly, existing works aim to speed up Bayesian inference via parallelism, but these methods struggle in Bayesian unsupervised learning due to the so-called “label-switching problem”. Secondly, in Bayesian nonparametrics …
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Inferring Signal Transduction Pathways from Gene Expression Data using Prior Knowledge
… gene expression in response to stimulus . For computational purposes, a signal transduction pathway is represented as a network where nodes are biological molecules. The interaction of two nodes is a directed edge. A plethora of research has been conducted to understand signal transduction …
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A computational approach to understanding spatial and temporal granularities in agent-based modeling
… dissertation examines and overcomes a set of computational challenges to investigate a fundamental problem in spatially explicit epidemic agent-based modeling. This research demonstrates that coarsening spatial and temporal granularities influence both computational tractability and epidemic …
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Efficiency and abstraction in task and motion planning
… dynamics induced by contact creates severe computational challenges, and most known practical approaches rely on hand-designed discrete representations to mitigate computational issues. However, the relationship between the discrete representation and the physical robot is poorly understood …
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Machine Learning Methods for Single Cell RNA-Sequencing Data to Improve Clinical Oncology
… nature of scRNA-seq data, current computational tools face limitations, particularly when confronted with data from clinical oncology. This thesis presents the development and application of ML techniques for scRNA-seq data to address key computational challenges, with a focus on …
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Computational Simulation of Detonation Waves and Model Reduction for Reacting Flows
… interpolation method (DEIM) that addresses the computational challenges involved in the numerical simulations of reacting flows is also proposed and demonstrated.
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On the use of locality aware distributed hash tables for homology searches over voluminous biological sequence data
… This increase in data volumes has introduced computational challenges for frequently performed sequence analytics routines such as DNA and protein homology searches; these must also preferably be done in real-time. This thesis proposes a scalable and similarity-aware distributed storage …
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High-speed high-fidelity computational modeling approaches for cardiac applications
… presents a high-speed, high-fidelity computational modeling approach for cardiac simulations, with a focus on replacement heart valves and left ventricular function. High-fidelity, structurally-based computational models were developed to simulate replacement heart valves. Through a …
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Formatting and searching a massive, multi-parameter clinical information database
… clinical information database poses significant computational challenges. The challenges encountered in converting high-resolution waveform and trend signals in the MIMIC II (Multi-parameter Intelligent Monitoring for Intensive Care II) database from an error-prone proprietary format to a stable …
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Reduced Order Methods for Large Scale Riccati Equations
… differential equations (PDEs) leads to many computational challenges. The primary challenge comes from the fact that discretization methods for PDEs typically lead to very large systems of differential or differential algebraic equations. These systems are used to form algebraic Riccati …
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Explainable AI: A Unified Approach Based on Cooperative Game Theory
… effects and feature interactions. To address computational challenges of SIs, we introduce SHAP-IQ, an efficient model-agnostic approximation method for any-order SIs, and extend KernelSHAP to higher-order interactions. Additionally, TreeSHAP-IQ and GraphSHAP-IQ improve model-specific …
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Empower dynamic scene understanding through scene flow estimation and object segmentation
… these tasks offers a holistic view but faces computational challenges due to scene flow’s high dimensionality. This work proposes a lightweight deep learning architecture combining an enhanced Point Transformer for efficient fea- ture extraction and a point-voxel correlation module for sta- …
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Experimental design and analysis for high-parameter spatial omics
… omics data present unique statistical and computational challenges, and substantial work is required to ensure that findings of spatial omics experiments are actionable in the laboratory and clinic. Here, I examine the underlying statistical properties of spatial biology to propose a …
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