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Browsing Theses and Dissertations by Subject "Machine Learning"
Now showing items 1-20 of 41
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AI-Enabled Contextual Representations for Image-based Integration in Health and Safety
(2021)Recent advancements in the area of Artificial Intelligence (AI) have made it the field of choice for automatically processing and summarizing information in big-data domains such as high-resolution images. This approach, ... -
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American Sign Language Gesture Recognition using Motion Tracking Gloves in VR
(2022)Gesture recognition has become an topic of great interest as it continues to advance the capabilities of human computer interaction. Research has shown that related technologies have the potential to facilitate highly ... -
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Automated Detection and Localization of Blastholes through UAV Imaging and Machine Learning
(2024)Drilling accuracy is the primary factor influencing the explosive energy distribution of a blasting process. Therefore, knowing the final location of drillholes is crucial to obtain optimal blasting results. This research ... -
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Axially Loaded Drilled Shafts: LRFD Resistance Factor Calibration and Predictive Techniques for Settlement
(2016)In areas where local geology consists of unique or uncommon subsurface materials, uncertainty in deep foundation design may lead to excessive construction costs and inadequate reliability. While the calibration of area-specific ... -
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Big Data Application and System Co-optimization in Cloud and HPC Environment
(2022)The emergence of big data requires powerful computational resources and memory subsystems that can be scaled efficiently to accommodate its demands. Cloud is a new well-established computing paradigm that can offer customized ... -
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Bridging Machine Learning for Smart Grid Applications
(2021)This dissertation proposes to develop, leverage, and apply machine learning algorithms on various smart grid applications including state estimation, false data injection attack detection, and reliability evaluation. The ... -
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Deep Convolutional Neural Networks Based Single Image Super-Resolution And Classification For Crater Detection
(2019)Craters are among the most abundant features on the surface of many planets with great importance for planetary scientists. Craters reveal chronology information about planets and may be used for autonomous spacecraft ... -
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Determination of Progression Speeds for Traffic Signal Coordination
(2020)Signal coordination has been widely implemented throughout the world as an effective approach to mitigating traffic congestion, improving operational efficiency on urban arterials, and reducing fuel consumption and emissions. ... -
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Evolving Effective Micro Behaviors for Real-Time Strategy Games
(2015)Real-Time Strategy games have become a new frontier of artificial intelligence research. Advances in real-time strategy game AI, like with chess and checkers before, will significantly advance the state of the art in AI ... -
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Global Ensemble Streamflow and Flood Modeling with Application of Large Data Analytics, Deep learning and GIS
(2019)ABSTRACTFlooding is one of the most dangerous natural disasters that repeatedly occur globally, and flooding frequently leads to major urban, financial, anthropogenic, and environmental impacts in the subjected area. ... -
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HMM-Based Techniques for Intent Recognition in a Simulated Realistic Naval Environment
(2016)Activity recognition aims to recognize the actions of one or more agents froma series of observations. Intent recognition is an area of research dedicated toautomatically detecting and predicting the intentions of agents ... -
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I/O Throughput Prediction for HPC Applications Using Darshan Logs
(2022)As most High Performance Computing (HPC) applications deal with large volumes of data, I/O performance is of critical importance to optimize application performance. Despite having large-scale, high-performance parallel ... -
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Investigating Ensembles of Single-class Classifiers for Multi-class Classification
(2023)Traditional methods of multi-class classification in machine learning involve the use of a monolithic feature extractor and classifier head trained on data from all of the classes at once. These architectures (especially ... -
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Machine Learning Techniques Applied to the Nevada Geothermal Play Fairway Analysis
(2021)This study introduces machine learning techniques to the Nevada geothermal play fairway analysis (PFA), which provided geothermal potential maps for 96,000 km2 of west-central to eastern Nevada. The motivation for this ... -
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Modeling the Abnormality: Machine Learning-based Anomaly and Intrusion Detection in Software-defined Networks
(2023)Modern software-defined networks (SDN) provide additional control and optimal functionality over large-scale computer networks. Due to the rise in networking applications, cyber attacks have also increased progressively. ... -
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Network Security Monitoring and Analysis based on Big Data Technologies
(2013)Network flow data provide valuable information to understand the network state and to be aware of the network security threats. However, processing the large amount of data collected from the network and providing real ... -
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Predictive Modelling of Gas Concentrations in Tunnels Using Machine Learning.
(2023)This study introduces a machine learning methodology for predicting gas concentrationsat specific location within a tunnel model. The machine learning model is trained using gas concentration data obtained from sensors ... -
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Recursive Hyperspheric Classification
(2018)Data guide decisions and processes. Moreover, while the practice of obtaining data may be mundane, the analysis of data provides vision and understanding. Within data -- ideally -- are hidden patterns and metadata that ... -
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Risk, Need, and Racial Inequality: A Machine Learning Analysis of Rearrest in Juvenile Drug Treatment Courts and Traditional Juvenile Courts
(2022)Juvenile justice system involvement has many impacts on the lives of youth. This often includes negative outcomes for youth who receive highly punitive treatment rather than more rehabilitative approaches. One approach to ... -
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Robust Event Cause Analysis in Power Grids using Machine Learning Algorithms
(2019)Power grids are composed of generation, transmission, distribution and customer level assets along with protection, monitoring, and control equipment that are well-coordinated and operated to deliver sinusoidal voltage and ...