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 165 for “"Data-Driven Approaches"”.
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New Data-Driven Approaches to Text Simplification
… text simplification (ATS) and proposing new data-driven approaches to solving them. We propose methods for learning sentence splitting and deletion decisions, built upon parallel corpora of original and manually simplified Spanish texts, which outperform the existing similar systems. Our …
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Metabolic Pathway Optimization with Data Driven Approaches
… property. The models are trained on synthetic datasets generated using fully reversible Michaelis-Menten kinetics. All parameters are randomly sampled from a maximum entropy distribution assuming no prior knowledge on the system. For a pathway up to 15 nodes, the results show over 90% accuracy …
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Data-Driven Approaches for Enhancing Power Grid Reliability
… thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops …
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Integrative data-driven approaches to tornado wind field reconstruction
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-08-01
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Data-driven Approaches to Stellar Variability Detection and Characterisation
… as a part of the Centre for Doctoral Training in Data-Intensive Sciences. Much of this work has been conducted as a part of the NGTS consortium. I implemented and tested a novel generalisation of the autocorrelation function (the G-ACF), which applies to irregularly sampled data, such as …
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Non-line-of-sight imaging using data-driven approaches
… This thesis proposes the application of data-driven techniques to NLOS imaging to leverage the convolutional neural network's ability to learn invariants to scene variations. We demonstrate the classification of an object hidden behind a scattering media along with the localization and …
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Data Driven Approaches to Model Building: Applications to Energy Industries
… a combination of first principles and available data. The focus of this work is on the application of data-driven modelling approaches in two specific instances of problems in upstream (oil & gas extraction) and downstream (refining & chemicals) industries, namely (a) cementing of wells drilled …
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Data-Driven Approaches to Narrative Personalisation through Psychologically Motivated Models
AI-driven personalisation offers a clear opportunity for creative industries to engage audiences more effectively. This project seeks to understand how such personalisation can be effectively and ethically exploited in story experiences to generate greater audience engagement. More specifically, …
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Data-Driven Approaches in Water Pipe Condition Assessment and Failure Prediction
… common issue of class imbalance in pipe failure datasets. A semi-supervised clustering approach was introduced, integrating expert knowledge with data-driven techniques to enhance the representation of rare failure events. This was supported by a hybrid sampling strategy and class weighting …
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Data driven approaches to improve operational efficiency of emergency medical services
We study data-driven approaches to maximize the service level of Emergency Medical Services (EMS) in emerging economies. These systems usually operate under heavy resource constraints and face significant operational challenges, making them structurally and operationally different from systems in …
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Advancing computational materials design and model development using data-driven approaches
… MD simulations, uncertainty quantification, and data-driven methodologies to accelerate the computational design of innovative materials and models across the following interconnected chapters. Beginning with the development of force fields for atomic-level systems and coarse-grained models for …
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Data-driven approaches from ab initio methods in condensed matter to climate science
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
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Quantifying grain boundary structure – property relationships with atomistic simulations and data driven approaches
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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Data-driven approaches for residential water end-use classification and sustainable urban water management
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms
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Resource Allocation for Green Cloud Networks under Uncertainty: Stochastic, Robust and Big Data-driven Approaches
… decade. To meet the growing demand in massive data processing, a large number of geographically-distributed data centers begin to surge in the era of data deluge and information explosion. Along with their remarkable expansion, contemporary cloud networks are being challenged by the growing …
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Online boiler convective heat exchanger monitoring: a comparison of soft sensing and data-driven approaches
… by respectively using a soft sensor and a data-driven method. The soft sensor approach is based on a one-dimensional thermofluid process model which takes measurements as inputs and calculates unmeasured variables as outputs. The model is calibrated based on design information. The …
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Integration of Physically-based and Data-driven Approaches for Thermal Field Prediction in Additive Manufacturing
… of the underlying science, physically-based approaches alone are insufficient for component-scale thermal field prediction. Here, I present a new framework that integrates physically-based and data-driven approaches with quasi in situ thermal imaging to address this problem. The framework …
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