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 30 for “"Data-driven modelling"”.
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Data-driven modelling of perceptual properties of 3D shapes
… perceptual properties of 3D shapes and build data-driven models. We rely on crowdsourcing platforms to collect large number of human judgements on style matching and aesthetics of 3D shapes. The judgement data collected directly from humans is used to learn metrics of style matching and …
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Combining mechanistic modelling with data-driven modelling in mathematical oncology
Mathematical modelling in cancer research has been developing and has contributed valuable insights. By helping to understand the mechanisms of biological processes and predict clinical outcomes, mathematical models can complement empirical cancer research. In chapter 2, we studied the dynamics by …
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Accuracy Improvement in Robotic Milling Through Data-Driven Modelling and Control
… 6-dof industrial robot over its workspace using data-driven methods. First, a data-driven modeling approach utilizing Gaussian Process Regression (GPR) of data acquired from modal impact hammer experiments to predict the modal parameters of a 6-dof industrial robot as a function of its arm …
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Advancing Rockfall Hazard Assessment through Data-Driven Modelling Based on Laboratory-Scale Experiments
… 30°) onto a horizontal concrete surface. Motion data captured from dual camera angles were analyzed to evaluate key parameters, including the coefficient of restitution (COR), translational and angular velocity, runout distance, and trajectory dispersion. The results highlighted significant …
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On data-driven modelling and terminal sliding mode control of dynamic systems with applications
This thesis addresses critical issues in system modelling and control with some applications to robotics and automation. The main content is divided into three parts, namely data-driven identification, fast terminal sliding mode control alongside underactuated crane control, and robotic pointing …
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Data-driven modelling and optimised reverse engineering of complex dynamical systems in cancer research
Biological systems typically generate complex data that encapsulate the dynamics of interactions among measurables over time. To support the formation of insights into time series data from a biological system, there is a requirement to develop new methods that can analyse and translate such …
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Object Modelling by Example
Modelling by example has arisen as a powerful paradigm for reducing the artistic skill required for computer graphics. Instead of relying on the user's own modelling skills, a system that models by example allows users to reuse the work of others. To date, modelling by example, also known as …
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Theory and applications of multifunctional reservoir computers
… application areas are explored which include, data-driven modelling of multistability, generating chaotic itinerancy, and reconstructing dynamical transitions present in the epileptic brain.
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Epidemiology and modelling to support the routine infant immunisation programme in England.
… the use of epidemiological and mathematical modelling to inform vaccination policy, focusing on two critical aspects: the impact of changes to the meningococcal vaccination schedule and the potential introduction of a universal varicella vaccine. Two dynamic transmission models were developed …
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Isolation of Cellulose Nanocrystals: Data-Driven Identification of Key Factors Affecting Yield and Morphology
… but also their surface charge and morphology. A database was compiled from literature data and revealed to contain a bias in reported yields due to the frequent absence of a phase separation method in optimisation studies. Despite this, the dataset enabled the training of a neural network model …
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Modelling and predictive control techniques for building heating systems
… been developed for deriving building models from data in which large, unmeasured disturbances are present. A spatio-temporal filtering process was introduced to determine estimates of the disturbances from measured data, which were then incorporated with metaheuristic search techniques to derive …
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Karst hazard analysis towards the development of predictive karst models for southern Ontario
… currently feasible is a lack of sufficient karst data, though this is not entirely due to the lack of karst features. Geophysical data was collected at Lake on the Mountain, Ontario as part of this karst investigation. This data was collected in order to validate the long-standing hypothesis that …
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Pct1 regulates phosphatidylcholine synthesis in response to changes in surface curvature elastic stress sensed on the inner nuclear membrane
… By aligning imaging with lipidomic analysis and data-driven modelling, Pct1 membrane association is demonstrated to correlate with membrane stored curvature elastic stress estimates. Furthermore, this process occurs inside the nucleus, although nuclear localization signal mutants can compensate …
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A Physically Informed Data-Driven Approach to Analyze Human Induced Vibration in Civil Structures
… for VBOI research based on physically informed data-driven models of structural dynamical systems. The first part of this dissertation presents a method for extracting temporal gait parameters via underfloor accelerometers. The time between an occupant's consecutive steps can be measured with …
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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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Distributional and relational inductive biases for graph representation learning in biomedicine
… motivates the mass collection of biomolecular data and data-driven modelling to gain insights into physiological phenomena. Recent predictive modelling efforts have focused on deep representation learning methods which offer a flexible modelling paradigm to handling high dimensional data at …
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Multi-scale computational modeling of coronary blood flow: application to fractional flow reserve.
… combined with computational coronary flow modelling may reduce the patient’s burden of undergoing invasive testing. Research statement. The ability to obtain information of the hemodynamic significance of detected lesions would streamline decision making in escalation to invasive …
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An evaluation of a data-driven approach to regional scale surface runoff modelling
Modelling surface runoff can be beneficial to operations within many fields, such as agriculture planning, flood and drought risk assessment, and water resource management. In this study, we built a data-driven model that can reproduce monthly surface runoff at a 4-km grid network covering 13 …
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Understanding ozone, climate and their interactions with causal machine learning
… This thesis develops and applies data-driven approaches to model ozone and temperature, aiming to alleviate some of the limitations of numerical models and leverage growing volumes of data characterising the Earth system. Chapters 1 and 2 introduce the main themes of the thesis, …
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