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Browsing Theses and Dissertations by Subject "machine learning"
Now showing items 1-20 of 36
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A New Data Processing System for Generating Sea Ice Surface Roughness and Cloud Mask Data Products from the Multi-Angle Imaging SpectroRadiometer (MISR)
(2023)This study describes two novel data products derived from Multi-angle Imaging SpectroRadiometer (MISR) imagery: Arctic-wide maps of sea ice roughness and a binary cloud detection algorithm. The sea ice roughness maps were ... -
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Advances in Nonlinear Computational Substructuring for Real-Time Hybrid Simulation
(2020)Hybrid Simulation (HS) is an advanced experimental method to investigate the overall structural behavior as well as individual element responses under realistic loading such as earthquake excitation. A typical HS configuration ... -
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Analysis of Failed SSH Attempts for Intrusion Detection
(2024)SSH brute force attacks remain among the most common attack types in computer systems. Recent threat analysis reports consistently highlight their prevalence as a top web security vulnerability. Various passive and active ... -
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Anomalous Motion Detection of Vehicles on Highway using Deep Learning
(2019)Research in visual anomaly detection draws much interest due to applications in surveillance. Common data sets for evaluation are constructed using a stationary camera overlooking an area of interest. Despite the challenges ... -
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Clinical Dataset Analysis and Patient Outcome Prediction via Machine Learning
(2018)We analyze and evaluate relevant machine learning methods for use in extract-ing and understanding clinical data sets in the context of optimization ofclinical processes. Three data sets were considered to demonstrate the ... -
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Compositional Investigation ofStratigraphic & Morphologic Unitsin the South Polar Ice Deposits of Mars
(2021)Variable mixtures of CO2 ice, H2O ice, and dust in volatile exposures at the south pole of Mars influence interactions with the atmosphere that drive their formation, evolution, and eventual preservation as long-term climate ... -
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Deep Convolutional Neural Networks for MultilabelPrediction Using RGBD Data
(2014)Robotics relies heavily on the system's ability to perceive the world around the robot accurately and quickly. In a narrow setting as in manufacturing this goal is relatively simple. To make robotics feasible in more ... -
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Identifying Spatiotemporal Effects of Climate on Civil Conflict
(2020)How do changes in climatic conditions and disaster patterns affect the persistence of civil unrest across countries over time? Existing studies postulate that changing climate conditions will exacerbate various social ... -
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Machine Learning Applied to the Design of Drilled Shafts: Prediction of the Nominal Axial Resistance in Cohesive-Dominant Soils using Artificial Neural Networks
(2023)The use of drilled shafts as deep foundation systems in supporting large civil engineering structures such as highways, bridges, retaining structures and high-rise buildings is rapidly increasing. These foundations are ... -
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Machine Learning based Mountainous Skyline Detection and Visual Geo-Localization
(2017)With the ubiquitous availability of geo-tagged imagery and increased computational power, geo-localization has captured a lot of attention from researchers in computer vision and image retrieval communities. Significant ... -
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Models of Intention for Human-Robot Interaction
(2013)As demand for robots grows in non-industrial settings, there is a corresponding need to develop systems that engage with humans on a social level. A key component of this social interaction is the process of inferring ... -
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Network Traffic Fingerprinting using Machine Learning and Evolutionary Computing
(2019)The Internet has become essential to our daily life, especially with a multitude of IoT devices. However, the end hosts connected to the Internet are prone to be compromised. An essential measure for protecting attacks on ... -
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Novel Techniques for Single-cell RNA Sequencing Data Imputation and Clustering
(2023)Advances in single-cell technologies have shifted genomics research from the analysis of bulk tissues toward a comprehensive characterization of individual cells. These cutting-edge approaches enable the in-depth analysis ... -
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PATIENT CLASSIFICATION USING DEEP LEARNING
(2019)With diseases like Alzheimer's and Influenza still claiming lives, there have been a lot of methods developed in order to combat these diseases. There is a possibility that the key to finding susceptibility towards a disease ... -
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Predicting Agent Behavior by Estimating Motion Planners
(2020)To navigate the world safely, autonomous agents must predict the future actions of the other agents in the world. We propose a method to estimate the future positions of other agents by using a sample-based planner that ... -
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Solutions for Improving Model Simulation in the Virtual Watershed Platform
(2017)This thesis is a collage of the works implemented to enhance the modeling capabilities of the NSF EPSCoR-supported Western Consortium for Water Analysis, Visualization and Exploration (WC-WAVE) Virtual Watershed Project. ... -
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Study of retrofitted system for Intelligent Compaction Analyzer, a machine learning approach for Quality Control of Asphalt Pavement during Construction
(2023)Asphalt pavements play a vital role in transportation infrastructure, but their performance can suffer due to subpar quality resulting from improper construction practices. To tackle this issue, we introduce the Retrofit ... -
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Three Empirical Essays in Public Economics
(2024)This dissertation uses applied microeconometric methods to investigate research questionsin public economics (first two chapters) and to explore the use of deep learning to construct data useful in public economics and ... -
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Three Empirical Essays in Public Economics
(2024)This dissertation uses applied microeconometric methods to investigate research questionsin public economics (first two chapters) and to explore the use of deep learning to construct data useful in public economics and ... -
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Three Empirical Essays in Public Economics
(2024)This dissertation uses applied microeconometric methods to investigate research questionsin public economics (first two chapters) and to explore the use of deep learning to construct data useful in public economics and ...