Naval Postgraduate School
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Military Operations Research Society (MORS) Oral History Project Interview of Dr. Kleber S. Masterson, Jr.
Get PDFInterviewers: Dr. Bob Sheldon and Michael W. GarramboneDr. Kleber “Skid” Masterson, Jr. was President of MORS from 1988 to 1989. Dr. Masterson retired from the Navy as a Rear Admiral in 1982, serving his final duty assignment as Chief of the Studies, Analysis and Gaming Agency (SAGA) in the Joint Chiefs of Staff (JCS). The interview was conducted on 18 November 2010, 9 December 2010 and 20 December 2010 in Alexandria, Virginia
THE COST OF BALANCING DUTY AND FAMILY: AN EXAMINATION OF THE MILITARY CHILD CARE MODEL’S IMPACT ON U.S. AIR FORCE READINESS AND QUALITY OF LIFE SERVICES
No full textThe Department of the Air Force (DAF) Child Development Centers (CDCs) are essential to military readiness by providing quality, accessible, and affordable childcare for service members and their families. Currently categorized as a Morale, Welfare, and Recreation (MWR) activity, funding for CDCs is a combination of Appropriated Funds (APFs) and Non-Appropriated Funds (NAFs), with parent fees responsible for covering NAF operating expenses. However, the constraints of the current funding model, with fixed parent fees and rising NAF labor expenses, have led to financial instability. This study utilized fiscal data from the Air Force Services Center (AFSVC) to assess whether CDCs can financially break even under the current structure. The findings reveal that, at most DAF CDCs, parent fees alone are unable to cover NAF personnel costs without additional subsidies. This funding gap strains other MWR programs and forces installations to make operational decisions that impact childcare availability. To address these challenges, this thesis recommends reclassifying CDCs from a morale activity to a mission-essential program and restructuring the funding model to fully cover NAF personnel costs, ensuring long-term financial sustainability and support for military readiness.Distribution Statement A. Approved for public release: Distribution is unlimited.Major, United States Air Forc
DELIVERY SERVICE COMPARISON FOR SECURE GROUP PROTOCOLS
Get PDFSecure group communication is a critical component of modern distributed systems, especially as privacy-centric messaging frameworks become increasingly fundamental for protecting sensitive data. Messaging Layer Security (MLS) offers robust end-to-end encryption tailored for large-scale, dynamic groups. Nonetheless, achieving efficient and reliable message delivery, particularly under varying network conditions and group dynamics, remains a substantial challenge that requires further exploration.This research aims to determine the most suitable delivery protocol for integration with MLS by comparing four protocols: Totem, NanoMQ, Paxos, and Raft. These protocols represent different paradigms for group communication, ranging from reliable multicast to lightweight publish-subscribe and consensus-based replication mechanisms.The protocols will be assessed based on scalability, fault tolerance, latency, and compatibility with MLS security requirements. The evaluation highlights the strengths, limitations, and trade-offs of each protocol. Totem excels in ordered message delivery, NanoMQ is well-suited for low-latency dissemination, while Paxos and Raft offer strong consistency through consensus.The results of this comparison provide practical insights for selecting or optimizing delivery services that complement MLS, ultimately enabling reliable, scalable, and secure group communication.Distribution Statement A. Approved for public release: Distribution is unlimited.Captain, Hellenic Arm
USMC SCHOOL AND COURSE CHOICES AND SUCCESS WITH TUITION ASSISTANCE: AN ANALYSIS OF PARTICIPATION AND OUTCOMES 2014–2021
Get PDFThis study examines the relationship between tuition assistance usage, academic success, and Marine Corps retention from 2014 to 2021. Using descriptive statistics, logistic regression models, Kaplan-Meier survival curves, and Cox proportional hazard models, the analysis assesses the effects of tuition assistance on Marines of ranks E1 to E5. Public institutions accounted for 50% of courses taken by Junior Marines, while for-profit and non-profit schools made up 20–25% each. Non-Commissioned Officers saw a decline in for-profit enrollment from 46% to 32%, while public school enrollment increased from 37% to 42%. Private non-profit schools had the highest success rates at 87% for Junior Marines and 92% for Non-Commissioned Officers. Trades and applied professions and military courses had the highest success rates, while STEM and social sciences and humanities had the highest failure rates. Retention rates between three cohorts of Marines showed that those who used tuition assistance were significantly more likely to remain in service. Marines who did not use tuition assistance had a 69% separation rate between years four and six, compared to 44% for successful tuition assistance users and 25% for those who failed at least one course.Distribution Statement A. Approved for public release: Distribution is unlimited.Captain, United States Marine Corp
COMPUTER VISION AND MACHINE LEARNING FOR HANDWRITTEN DIAGRAM RECOGNITION
Get PDFBecause humans are much better at processing and organizing information visually than narratively, early system schematics or processes will start as handwritten diagrams on either a whiteboard or paper medium. These handwritten diagrams allow for much faster prototyping but still require translation into a digital medium for formal modeling and presentation. Offline graph recognition techniques include deep learning object detectors capable of recognizing diagram symbols. This thesis employs two object classifiers, Faster R-CNN and YOLOv5 to identify and classify objects within handwritten diagrams with an emphasis on detecting and distinguishing between arrow types. We introduce new classes of arrows into an existing data set and fine tune the models to increase classification accuracy. The results indicate that YOLOv5 is superior to Faster R-CNN in the detection of arrows with a precision difference of 0.226 percent. This suggests that YOLOv5 should be the architecture of choice for handwritten diagram recognition programs such as Monterey Phoenix.Distribution Statement A. Approved for public release: Distribution is unlimited.Captain, United States Marine CorpsNational Security Agency, Fort Meade, MD 2075
PLAN PROPERLY NOW OR PAY THE PRICE LATER: ELIMINATING THE DISCONNECT BETWEEN HAZARD MITIGATION PLANNING AND URBAN PLANNING
Get PDFThere currently is a disconnect between the urban planning processes that guide how cities develop and the hazard mitigation planning processes designed to protect cities from natural hazards. Given the ever-increasing frequency and severity of natural disasters impacting the United States, the root causes of this disconnect needed to be identified. Case studies examined how natural disasters impacted major cities within the United States, along with the effect that urban and hazard mitigation planning efforts had in mitigating the effects of natural disasters. These case studies identified that the disconnect between planning disciplines was arbitrary, caused by organizational structures, versus any actual disconnect between planning processes. Two key contributors to this disconnect were caused by the length of time between when a plan is developed and when it becomes reality, and how the failure of infrastructure can render even the most thorough of plans valueless. Reconceptualizing hazard mitigation as an integral element of urban planning is a solution to resolve this disconnect between planning disciplines to allow cities to grow safely in the face of ever more severe natural disasters.Distribution Statement A. Approved for public release: Distribution is unlimited.Civilian, Department of Homeland Securit
KNOWLEDGE GRAPH CONSTRUCTION AND MACHINE LEARNING FOR IMPROVED THREAT IDENTIFICATION
Get PDFKnowledge reasoning and representation in artificial intelligence (AI) are pivotal for advancing predictive research in threat identification. The rapid increase in large-scale data has spurred the deployment of automated solutions, yet current machine learning interfaces still struggle to reliably predict anomalous behaviors—limiting their suitability for critical decision-making. To address this challenge, recent advances in graph neural network theory and modern Koopman theory for dynamical systems have enabled the development of deep graph representation learning techniques combined with knowledge graph construction. This approach enhances threat classification accuracy by learning graph embeddings that capture outlier threat scores. Iterative comparisons using graph similarity measures between the predicted generative graph and the ground truth further refine the predictions. Dimensionality reduction is achieved using Koopman on violent incident information from news articles. The proposed Semi-supervised Predictive Autoencoder Representation using Koopman Learning Evolution (SPARKLE) method offers a scalable, adaptive framework for evolving intelligence, ultimately providing real-time situational awareness in future threat monitoring systems. Future suggested research integrates this innovative approach with multiple authoritative data sources to further advance AI-driven modern threat analysis.Distribution Statement A. Approved for public release: Distribution is unlimited.Civilian, Department of the Nav
PREDICTORS OF SUCCESS IN MARINE CORPS SPECIAL DUTY ASSIGNMENTS: A MACHINE LEARNING ANALYSIS OF GRADUATION AND TOUR COMPLETION
Get PDFThe Marine Corps relies on special duty assignments as critical billets for recruiting, training, and safeguarding national assets. High attrition rates at special duty assignment schools and during tours create significant staffing challenges, yet no comprehensive study has analyzed factors contributing to success in these assignments.Using machine learning techniques and multivariate logistic regression models on data from 15,033 Marines across four special duty assignment types (fiscal years 2017–2024), this research develops predictive models to identify characteristics influencing graduation and tour completion success. The analysis evaluates test scores, personal attributes, performance metrics, service history, and demographics.Results indicate that physical fitness scores, personal awards, relative value at processing, volunteer status, and higher grades positively predict graduation success. For tour completion, martial arts qualifications, combat fitness scores, and being married emerge as significant positive predictors. The Basic Recruiter Course demonstrates consistently higher graduation rates compared to other assignments. This research recommends maintaining volunteer incentive programs while developing enhanced screening methods focused on recent performance metrics. The findings provide empirical evidence to improve the Special Duty Assignment Campaign, though model limitations suggest the need for expanded longitudinal data collection.Distribution Statement A. Approved for public release: Distribution is unlimited.Staff Sergeant, United States Marine Corp
INFERRING THE TEMPERATURE OF A LASER-COOLED RUBIDIUM ATOM CLOUD: MODEL AND EXPERIMENT
No full textAtom-based sensors have the potential to enhance inertial navigation in Global Positioning System (GPS)-denied environments, providing an alternative to traditional accelerometers, gyroscopes, and sensors. Accurate temperature characterization is critical for atom interferometry, which relies on precise control of atomic motion to achieve high sensitivity. This research develops a model to infer the temperature of laser-cooled rubidium vapor by analyzing its ballistic expansion. The release and recapture method is employed to track atomic cloud dynamics after trap release, refining temperature inference through comparison with theoretical models. A magneto-optical trap is used to cool and confine the atoms, followed by sub-Doppler cooling to achieve lower temperatures. By characterizing expansion dynamics, this study improves temperature measurement techniques for cold atomic samples, addressing sources of systematic uncertainty that affect precision in quantum sensors. These findings contribute to advancements in laser cooling methodologies and atomic interferometry at the Naval Postgraduate School, with direct defense applications in inertial navigation, precision measurement, and sensing.Distribution Statement A. Approved for public release: Distribution is unlimited.Major, United States Arm
WHAT EXPLAINS RECENT DEMOCRATIC BACKSLIDING ACROSS LATIN AMERICA?
Get PDFThis thesis explores the causal mechanisms of democratic backsliding in Latin America. The hypothesis presented is that democracy itself will experience natural erosion when its institutions are weakened by individual actors, which will cause the withering of its checks and balance systems. Once democratic checks and balances systems are weakened, populist leaders may arise and seek to consolidate power. The research method used in this thesis will consist of a review of current literature exploring theories of democratic erosion. Comparative case studies focused on Venezuela and Brazil will then be presented to examine how populist leaders such as Hugo Chavez and Jair Bolsonaro undermined democratic institutions in their respective countries and how their institutions responded to either safeguard or further erode democracy. Venezuela’s democratic collapse will be juxtaposed against Brazil’s democratic resilience. Discussion of the findings will range from the use of economic revenue distribution to manipulating the electoral playing field, the professionalism of an apolitical military force being crucial to democracy’s livelihood, as well as how institutions play a key role in the maintenance of checks and balance systems. These findings are significant as they not only explain democratic backsliding in Latin America but also democratic backsliding in contemporary political systems.Distribution Statement A. Approved for public release: Distribution is unlimited.Major, United States Air Forc