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 97 for “"data-driven modeling"”.
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Data Driven Modeling of Proteins
… that take advantage of the large amount of data generated in both experiments and computer simulations in order to better understand how proteins work. The first method (pyODEM) improves the modeling of proteins on the global scale, while a second method (pyFrustration) probes the protein's …
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Data-Driven Modeling of Pedestrian Crowds
… studies on new methods for extracting empirical data of pedestrian movements (mainly based on video analysis, lasers, and infrared cameras), but most of the work is still focused on artificial setups for crowds moving through corridors and crowds passing bottlenecks. Even though these controlled …
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Data-driven modeling and transportation data analytics
Data has become increasingly important in transportation research. Unfortunately, existing traffic models, though developed and practiced for decades, are not data driven and therefore inherently incapable of analyzing modern traffic data from multiple sources with different time resolution and …
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Data-driven Modeling of Lithium Intercalation Materials
… particles to the whole cell, but traditional modeling approaches fail to capture all the available information. With the arrival of high-throughput computation and experimentation, there is an unprecedented opportunity to solve key challenges in energy storage via data-driven methods. In this …
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Data driven modeling and simulation about carp aggregation
Asian carp is notorious as one of the most severe aquatic invasive species (AIS) threats to the waters of the Mississippi River Region. The devastating effect of Asian carp calls for desperate measures to decrease the spread of Asian carp and prevent possible invasion into the Great Lake. This work …
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Investigation of backwards erosion piping by data driven modeling
This thesis investigates backwards erosion piping (BEP) as a failure mechanism; it focuses on the ability to use pore water pressure (PWP) measurements to (1) monitor, (2) investigate progression of, and (3) better predict BEP. This thesis starts with understanding PWP trends as BEP progresses, …
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Parametric Dynamical Systems: Transient Analysis and Data Driven Modeling
… a parameter. The need for high fidelity in the modeling stage leads to large-scale parametric dynamical systems. Since these models need to be simulated for a variety of parameter values, the computational burden they incur becomes increasingly difficult. To address these issues, parametric …
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Data-Driven Modeling of the Lake Chad Basin Hydrologic Systems
… of topographical, geological, and hydrological data makes forecasting hydrologic systems in the basin difficult and hinders advanced research and studies of the basin. This research is intended to identify the main climate variables affecting river discharge, lake level, and groundwater level …
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High-fidelity simulation and data-driven modeling of drop aerobreakup.
… simulation, and to develop physics-based and data-driven point-particle models for Lagrangian spray simulation. The sharp gas-liquid interface is resolved using a mass-momentum consistent VOF method. The open-source Basilisk solver has been used for the present simulations. The computaitonal …
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Data driven modeling of corn yield: a machine learning approach
… has been considerable research in leveraging data in the agricultural domain to improve yields. Tremendous amounts of data are generated on farms, ranging from amount of water used for irrigation to the quantities of fertilizers applied. To our knowledge, this study is the first that uses …
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Benchmarking Pavement Environmental Performance Using Data-Driven Modeling and Policy
… current policy are not sufficient, performing a data-driven analysis with a grading and scorecard system to assess, compare, and summarizing pavement design quality, and proposing an effective policy framework to implement the system.
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Data-Driven Modeling of Tracked Order Vibration in Turbofan Engine
… instrumented parts of an aircraft, and the data from various types of instrumentation across these engines are continuously monitored both offline and online for potential anomalies. Vibration monitoring in aircraft engines is traditionally performed using an order tracking methodology. …
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Organ Viability Assessment in Transplantation based on Data-driven Modeling
… and non-invasive biological in situ data to correlate with organ viability; 3) the organs viability is difficult to model because of heterogeneity among organs; 4) both visual inspection and biopsy can be applied only at present time, and how to forecast the viability of …
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Data driven modeling and MPC Based control for Pathological Tremors
… and it's input force/torque. Accurate predictive modeling of tremor signals can be used to provide alleviation from these tremors via various currently available solutions like adaptive deep brain stimulation, electrical stimulation and rehabilitation orthoses. Existing methods are either too …
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Towards Trustworthy Data-driven Modeling and Control of Unmanned Aerial Vehicles
L'abstract è presente nell'allegato / the abstract is in the attachment
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DATA-DRIVEN MODELING AND CONTROL FOR TIME-VARYING MULTISTAGE MANUFACTURING PROCESSES
This thesis aims to develop a unified data-driven process modeling and control framework for quality improvement of nonlinear and time-varying Multistage Manufacturing Processes (MMPs). We first investigate the impact of modeling accuracy on the residual controls which are acknowledged as the main …
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Trajectory optimization and data-driven modeling for robotic bat flapping flight
… efforts in creating both analytical and data-driven models for many of these types of vehicles including ornithopters and small aerial vehicles mimicking insects. However, very few works have explored modeling for aerial vehicles with a skeletal structure throughout the wings and a single …
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Image processing and synthesis: From hand-crafted to data-driven modeling
… deep neural networks. Given a set of training data, deep generate models can generate high-quality natural images following the same distribution. We search the nearest neighbor in the latent space of the deep generate models using a weighted context loss and prior loss. This code is then …
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