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 59 for “"Data-Driven Method"”.
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Modeling Damage Evolution and Damage Healing using Data Driven Method
… deep neural networks to analyze a multisource dataset developed by Pragathi comprising grayscale images and strain contours during composite materials processing. We also utilized a Zero-Bias Deep Neural Network model to effectively detect defects in composite materials, thus enabling their …
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Data-Driven Method to Improve High Resolution Flood Risk Assessments
… practices by leveraging machine learning (ML) methodologies. Specifically, three major studies were conducted to advance our understanding and modeling capabilities. In the first Chapter, we have developed a block-level Socio-Economic-Infrastructure Vulnerability (SEIV) Index that helps …
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A data-driven method for improving a black-box controller
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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Data-driven extraction of the substructure of quark and gluon jets in proton-proton and heavy-ion collisions
… between theoretical models. Therefore a fully data-driven technique is crucial for an unbiased extraction of the quark and gluon jet spectra and substructure. We demonstrate a fully data-driven method for separating quark and gluon contributions to jet observables using a statistical technique …
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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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Design of database for automatic example-driven design and assembly of man-made objects
In this project, we have built a database of models that have been designed such that they can be directly fabricated by a casual user. Each of the models in this database has design specifications up to the screw level, and each component has a direct reference to a commercial part from online …
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Designing the Enterprise Architecture of an Innovative Plant Engineering Company
… decisions, this study developed a unique data-driven method, the Decision-Making Support Model (DMSM). Applying this model to a plant engineering company as a case study confirmed its capability to support data-driven decision-making.
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Search for supersymmetric particles in opposite sign dilepton events with the CMS detector
… a search for supersymmetric particles in the data collected by CMS at center of mass energy of 7 TeV is presented. The search is focused on the selection of events characterized by pairs of opposite sign electrons or muons. This particular exclusive signature (which we refer to as opposite …
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Detecting episodes of star formation using Bayesian model selection.
Bayesian model comparison is a data-driven method to establish model complexity. In this dissertation we investigate its use in detecting multiple episodes of star formation from the analysis of the Spectral Energy Distribution (SED) of galaxies. This method is validated by simulating galaxy …
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Multi-Agent Deep Reinforcement Learning and GAN-Based Market Simulation for Derivatives Pricing and Dynamic Hedging
… to learn directly from large amounts of data. Deep reinforcement learning is a particularly powerful method that uses agents to learn by interacting with an environment of data. Although many traders and investment managers rely on traditional statistical and stochastic methods to price …
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Learning and Reconstructing Conflicts in O-RAN
… (KPIs). In this paper, we introduce the first data-driven method for reconstructing and labeling conflict graphs in Open Radio Access Network (O-RAN). Specifically, we leverage GraphSAGE, an inductive learning framework, to dynamically learn the hidden relationships between xApps, control …
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A Methodology for Agricultural Robotics development
… in unstructured, harsh environments. A general methodology for the design and development of agricultural robots is proposed using the thesis’ central work, the Vegebot lettuce-picking robot, as an example. An embodied approach to design is recommended, with development based on rapid iterations …
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Smoothness- transferred random field
… between neighboring local regions, while data energy for the evidence from local regions. Usually, the smoothness energy is constructed in terms of a fixed set of filters or basis which can be learned from training examples and steered to local structures in test examples. ST-RF, on the …
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Realtime state estimation for contact manipulation
… are hard to resolve directly. We propose a data-driven method to assess the contact formation, which is then used in real time by the state estimator. We apply our framework to two iconic tasks in robotic manipulation: planar pushing and object insertion. We evaluate the algorithm in a setup …
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Approximation of Large Stiff Acausal Models
… simulate. In this thesis, we introduce a general data-driven method to generate surrogates, called the Continuous-Time Echo State Networks (CTESN), that can capture multiple widely separated time-scales which is easy to automate. We comment on its implementa- tion and then propose an active …
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Data-Driven sequential decision making with learning under ambiguity
… these parameters are estimated from historical data, and treated as known quantities in the decision-making process. This approach ignores parameter uncertainty introduced by data inadequacy (e.g., limited availability of data, data contained with noise), making the robustness of decisions …
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POLYMETALLIC NODULE ABUNDANCE ESTIMATION USING SIDESCAN SONAR: A QUANTITATIVE APPROACH USING ARTIFICIAL NEURAL NETWORK
… planning of exploitation strategies. Traditional methods for PMN quantification are labour and time intensive as they rely on freefall box corer measurements and/or image processing of seabed photographs. This research thesis explores PMN abundance estimation using a data-driven method based on …
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Design, Fabrication, and Data-Driven Locomotion Control of Modular Reconfigurable Soft Robots
… modeling thegeometry and actuation necessitate a data-driven method to achieve tractable locomotioncontrol. A learning-based gait synthesis strategy is presented and experimentally shownto improve gait speed and uncoupling of rotation and translation behavior. Finally, thesedesign and control …
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A data-driven approach to bucket-filling control for autonomous excavators
We develop a data-driven, statistical control method for autonomous excavators. Interactions between soil and an excavator bucket are highly complex and nonlinear, making traditional physical modeling difficult to use for real-time control. Here, we propose a data-driven method, exploiting data …
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Robust design evolution and impact of In-Cylinder Pressure Sensors to combustion control and optimization : a systems and strategy perspective
… mover industries. In addition, Chapter 2 gives a data driven method for identifying the Skills needed for suppliers to realize the above recommendations. This method is based on collective intelligence of 690 experienced professionals with 20 years of work experience on average from 40 targeted …
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