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Author:

Powers, Russell

Title:

Investigation of Noise Reduction Methods on Supersonic Jets Exhausting from Scale Models of Military Style Nozzles

Graduate Program:

Aerospace Engineering

Keywords:

Acoustics
Jet Noise
Noise Reduction
Corrugations
Corrugation
Bevel
Beveled
Experiment
Supersonic
Model
Military
Nozzle

File:

Download RWP_MSThesis_2012_vFINAL.pdf

Committee Members:

Dennis K Mc Laughlin, Thesis Advisor/Co-Advisor

Author:

Whichard, Corey Logan

Title:

Military Service and Specialization in Criminal Violence

Graduate Program:

Crime, Law and Justice

Keywords:

Military
Violence
Specialization

File:

Download 1-Whichard_-_Thesis_-_Formatted_for_Graduate_School.pdf

Committee Members:

Richard B Felson, Thesis Advisor/Co-Advisor

Author:

Smith, William Thomas

Title:

Scheduling Analysis of Stored Combat Load Retrieval Using Monte Carlo Sampling

Graduate Program:

Industrial Engineering

Keywords:

Scheduling
Monte Carlo
Ammunition
Stored Combat Load
Parallel Machine Scheduling
Army
Military

File:

Download Smith_William__IndEng_PhDV2_August2018.pdf

Committee Members:

Guodong Pang, Dissertation Advisor/Co-Advisor
Guodong Pang, Committee Chair/Co-Chair
Soundar Kumara, Committee Member
Vittaldas V Prabhu, Committee Member
Minghui Zhu, Outside Member
Michael Andrew Yukish, Special Member

Author:

Tirrell, Bruce

Title:

Challenging Veteran Stereotypes: An Investigation Around Veteran Status and Its Influence on Aggression, Ostracism, Stress, and Counterproductive Work Behaviors

Graduate Program:

Human Resources and Employment Relations

Keywords:

Veterans
Military
Veteran Stereotypes
Aggression
Stress
Counterproductive Work Behaviors
Organizational Citizenship Behaviors
Ostracism
Emotional Stability
Military Identity
Military Culture

File:

Download Bruce_K_Tirrell_HRER_MS_Thesis_2022.pdf

Committee Members:

Paul Clark, Program Head/Chair
Kameron Carter, Thesis Advisor/Co-Advisor
Dorothea Roumpi, Committee Member
Susan Mohammed, Committee Member

Author:

Garcia, Miguel

Title:

Insights on the use of Machine Learning to Predict Retention of Career Soldiers in the United States Army

Graduate Program:

Data Analytics

Keywords:

Artificial Intelligence
Machine Learning
AI
Deep Learning
Decision Tree
Logistic Regression
Random Forest
XGBoost
Artificial Neural Network
Deep Neural Network
U.S. Army
Military
Attrition
Retention
Person-Event Data Environment
PDE
Department of Defense
DoD
Army Analytics Group
AAG
Naive Bayes
Active Duty
Enlistment
Commissioned Officers
Soldiers
Area Under the Curve
AUC
Data Analytics
Retirement
MEDPROS
PHA
MEPCOM
DTMS
ATMS
ROC Curve
Variable Importance
Preprocessing
Data Quality

File:

Download Insights_on_the_use_of_AI_to_Predict_Retention_of_Career_Soldiers_in_the_US_Army.pdf

Committee Members:

Colin Neill, Program Head/Chair
Partha Mukherjee, Thesis Advisor/Co-Advisor
Guanghua Qiu, Committee Member
Youakim Badr, Thesis Advisor/Co-Advisor