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 102 for “"High-resolution data"”.
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Improving traffic signal performance using high-resolution data
… arterials due to lack of traffic monitoring and data collection system. This research aims to improve the traffic signal performance based on the collected high-resolution traffic signal data and the derived performance measures by the SMART-Signal system developed at the University of Minnesota. …
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Utilizing High Resolution Data to Identify Minimum Vehicle Emissions Cases Considering Platoons and EVP
… flowchart was developed to analyze the traffic data and to identify platoons. The platoon end time was obtained from the simulation and used to calculate the offset of the downstream intersection. The simulation calculates vehicle emissions with the aid of the VT-Micro microscopic emission …
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Advances in Traffic Signal Operations Management: Machine Learning Measurement and Transition Improvements Through High-Resolution Data
… the integration of advanced technologies and data-driven approaches. First, the study compares traditional traffic delay measurement methods, specifically the Highway Capacity Manual (HCM) methodology, with a Machine Learning Vision System (MLVS). This comparison acknowledges the HCM's …
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A Collaborative Web Application Framework for Least Cost Caloric Paths with Constraints on High Resolution Data
… and implementation for a web application spatial data visualization tool, built in conjunction with expert input from an anthropologist, that strives to serve as an interactive tool for analyzing human travel across terrain. In addition to using least cost caloric paths across high resolution …
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A high speed data acquisition system
… world around us. The interface between analogue data sources and these digital systems is the realm of analogue to digital converters (ADCs) that acquire digital snap-shots of data for further processing. Some applications require high sampling rates or high resolution data (or both). In addition …
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Prediction of peak energy demand and timestamping in commercial supermarkets using deep learning
… proposed with three phases. In the first phase, data preprocessing cleans the raw data into the intended input for the deep learning model, and timestamp labelling creates the expected output for training and evaluation of the model. The second phase focuses on energy consumption prediction using …
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Spatial modeling for periodic surfaces in manufacturing
High-resolution spatial data is essential for characterizing and monitoring surface quality in manufacturing. However, the measurement of high-resolution spatial data is generally expensive and time-consuming. Interpolation based on spatial models is a typical approach to cost-effectively acquire …
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Forecasting groundwater contaminant plume development using statistical and machine learning methods
… equation. With the large groundwater quality datasets that have been collected for decades at legacy contaminated sites, there is an emerging potential to use data- driven machine learning algorithms to model contaminant plume development and improve site management. However, spatial and …
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Depositional Architecture of Confined Meander Belt Deposits, Lower Cretaceous Grand Rapids Formation, east-central Alberta
… stratigraphic levels. Facies mapping and a high-resolution allostratigraphic framework are used to map the 3D distribution of marginal marine units and fluvial bodies. A confined fluvial meander belt in the Colony Allomember is studied in detail using a high-resolution data set of densely …
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Adaptive synthetic Schlieren imaging
… index gradients including the relatively high cost of parabolic mirrors and the fact that the technique does not easily yield quantitative data. Both these issues are resolved by using synthetic Schileren photography, but this technique produces images with a lower resolution than …
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Neural Operator Models as Applied to Fluid Flow Systems and Real Ocean Dynamics
Data-driven, deep-learning modeling frameworks have been recently developed for forecasting time series data. Such machine learning models may be useful in multiple domains including the atmospheric and oceanic ones, and in general, the larger fluids community. The present work investigates the …
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Analysis of microtopography, vegetation, and active-layer thickness using terrestrial LIDAR and kite photography, Barrow, AK
… In 2010, terrestrial LIDAR was used to collect high-resolution elevation data for four 10 m × 10 m plots where maximum active-layer thickness (ALT) and elevation have been monitored on an annual basis since the mid-1990s and had been monitored in the 1960s as well. The raw LIDAR point cloud was …
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Analysis of microtopography, vegetation, and active-layer thickness using terrestrial LIDAR and kite photography, Barrow, AK
… In 2010, terrestrial LIDAR was used to collect high-resolution elevation data for four 10 m × 10 m plots where maximum active-layer thickness (ALT) and elevation have been monitored on an annual basis since the mid-1990s and had been monitored in the 1960s as well. The raw LIDAR point cloud was …
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Deep Multi-Resolution Operator Networks (DMON): Exploring Novel Data-Driven Strategies for Chaotic Inverse Problems
… at the cost of working with large descriptive datasets, a requirement that many applications cannot afford. This thesis proposes and explores the novel Deep Multi-resolution Operator Network (DMON), inspired by the recently developed DeepONet architecture. The DMON model is designed to solve …
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Real-time non-intrusive reed valve measurement and analysis
… This sensor has allowed the acquisition of high resolution position data, recorded during unstable operating conditions, in a format that is convenient for further analysis. This in turn has provided the opportunity to improve the modelling of reed valves through the development of the …
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Automatic land-cover-classification derived from high-resolution Ikonos satellite image in the urban atlantic forest in Rio de Janeiro, Brasil by means of an objects-oriented approach
… with visual interpretation using SPOT data. This work produced a compatible thematic map in the scale 1:50,000. The scale of these maps permit to have a global vision of the land change cover but unfortunately do not correspond with the geographic information system of the city, which …
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Optimization of thermoplastic composite manufacturing with digital process intelligence
… built to close this knowledge gap with high-resolution manufacturing data collection. This inexpensive system, comprised of a series of Programmable Logic Controller (PLC)s, Raspberry Pi-based telemetry units, and SQL database, captures high resolution data across hundreds of shop-floor …
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Deep Learning Approach for Cell Nuclear Pore Detection and Quantification over High Resolution 3D Data
… segmenting and quantifying cell nuclear pores in high-resolution 3D microscopy data is critical for cellular biology and disease research. This thesis introduces a deep learning pipeline crafted to automate the segmentation and quantification of nuclear pores from high-resolution 3D cell organelle …
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Diagnostics of indoor environmental quality exposures and climate-infrastructure vulnerability in South African schools
… amplified by a lack of long-term solutions with high-resolution data to quantify the environmental inequity between permanent (brick) and temporary (containerbased and prefabricated) classrooms, as well as a methodological gap in translating such data into actionable, low-cost interventions. …
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Reflection seismic data acquisition and processing for enhanced interpretation of high resolution objectives
Reflection seismic data were acquired (by CONOCO, Inc.) which targeted known channel interruption of an upper Pennsylvanian coal seam (Herrin #6) in the Illinois basin. The data were reprocessed and interpreted by the Regional Geophysics Laboratory, Virginia Tech. Conventional geophysical …
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