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63.
An efficient approach to machine learning based text classification through distributed computing
by Immaneni, Raghu Nandan, M.S.  California State University, Long Beach. 2015: 86 pages; 1603338.
64.
Using Code Inspection, Code Modification, and Machine Learning to prevent SQL Injection
by Trumble, Brandon, M.S.  Kutztown University of Pennsylvania. 2015: 50 pages; 1590429.
66.
Classification of Placental Chorionic Surface Vasculature Network Features Using Machine Learning Techniques
by Hambarsoomian, Hike, M.S.  California State University, Long Beach. 2017: 50 pages; 10603969.
67.
Machine Learning Methods for Predicting Evolution, Mutation Effects, and Optimal Experimental Design
by Wang, Xiaokang, Ph.D.  University of California, Davis. 2020: 138 pages; 27999669.
68.
Computational methods for support vector machine classification and large-scale Kalman filtering
by Howard, Marylesa Marie, Ph.D.  University of Montana. 2013: 124 pages; 3568109.
69.
Enhanced Machine Learning Engine Engineering Using Innovative Blending, Tuning, and Feature Optimization
by Uddin, Muhammad Fahim, Ph.D.  University of Bridgeport. 2018: 192 pages; 13427950.
70.
System identification and robust control of a high-precision computer numerical controlled machine
by Sanders, Robert W., M.S.  California State University, Long Beach. 2015: 60 pages; 1603105.
71.
Machine Learning and Cellular Automata: Applications in Modeling Dynamic Change in Urban Environments
by Curtis, Brian J., D.Engr.  The George Washington University. 2018: 84 pages; 10785215.
72.
A Comparison of Variance and Renyi's Entropy with Application to Machine Learning
by Peccarelli, Adric M., M.S.  Northern Illinois University. 2017: 38 pages; 10603911.
73.
An investigation of data privacy and utility using machine learning as a gauge
by Mivule, Kato, D.Sc.  Bowie State University. 2014: 262 pages; 3619387.
74.
Optimal Subset Selection for Causal Inference Using Machine Learning and Particle Swarm Optimization
by Sharma, Dhruv, D.Engr.  The George Washington University. 2018: 132 pages; 10928545.
75.
Machine Learning and Network-Based Systems Toxicology Modeling of Chemotherapy-Induced Peripheral Neuropathy
by Bloomingdale, Peter, Ph.D.  State University of New York at Buffalo. 2018: 353 pages; 13427432.
76.
Practical Inference-Time Attacks against Machine-Learning Systems and a Defense against Them
by Sharif, Mahmood, Ph.D.  Carnegie Mellon University. 2019: 137 pages; 27662625.
78.
Lean Six Sigma Methodology Used to Improve Machine Availability in a Manufacturing Process
by Huval, Ory P., M.S.  University of Louisiana at Lafayette. 2016: 61 pages; 10247041.
79.
A Machine Learning Approach to Quantifying Likely Locations of Gas and Gas Hydrate Accumulation
by Runyan, Taylor E., M.S.  University of Louisiana at Lafayette. 2017: 55 pages; 10268964.
80.
Atomistic Monte Carlo Simulation and Machine Learning Data Analysis of Eutectic Alkali Metal Alloys
by Reitz, Doug, Ph.D.  George Mason University. 2018: 118 pages; 10982615.
81.
Date-Driven Topology Identification in Power Distribution Systems with Machine Learning
by Li, Yifu, M.S.  The George Washington University. 2020: 129 pages; 28087793.
84.
A manual for developing and implementing an AS9100 certified quality management system for small machine shops
by Smith, Concetta, M.S.  California State University, Dominguez Hills. 2014: 145 pages; 1526312.
88.
A study of the contribution of human factors to human-machine system failures in dynamic mission operations
by Davis, TImothy A., Ph.D.  The George Washington University. 2010: 189 pages; 3379259.
89.
Predicting “Essential” Genes in Microbial Genomes: A Machine Learning Approach to Knowledge Discovery in Microbial Genomic Data
by Palaniappan, Krishnaveni, Ph.D.  Nova Southeastern University. 2010: 252 pages; 3428281.
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