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Operations Research, Systems Engineering and Industrial Engineering Commons™
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Articles 1 - 30 of 63
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid
Simulation And Analysis Of Dynamic Threat Avoidance Routing In An Anti-Access Area Denial (A2ad) Environment, Dante C. Reid
Theses and Dissertations
This research modeled and analyzed the effectiveness of different routing algorithms for penetration assets in an A2AD environment. AFSIM was used with different configurations of SAMs locations and numbers to compare the performance of AFSIM’s internal zone and shrink algorithm routers with a Dijkstra algorithm router. Route performance was analyzed through computational and operational metrics, including computational complexity, run-time, mission survivability, and simulation duration. This research also analyzed the impact of the penetration asset’s ingress altitude on those factors. Additionally, an excursion was conducted to analyze the Dijkstra algorithm router’s grid density holding altitude constant to understand its impact on …
Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian
Bayesian Recurrent Neural Networks For Real Time Object Detection, Stephen Z. Kimatian
Theses and Dissertations
Neural networks have become increasingly popular in real time object detection algorithms. A major concern with these algorithms is their ability to quantify their own uncertainty, leading to many high profile failures. This research proposes three novel real time detection algorithms. The first of leveraging Bayesian convolutional neural layers producing a predictive distribution, the second leveraging predictions from previous frames, and the third model combining these two techniques together. These augmentations seek to mitigate the calibration problem of modern detection algorithms. These three models are compared to the state of the art YOLO architecture; with the strongest contending model achieving …
Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston
Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston
Theses and Dissertations
Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …
Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick
Classification And Analysis Of Twitter Bot And Troll Accounts, Callan P. Mccormick
Theses and Dissertations
This research trains, tests, and analyzes bot and troll classification models using publicly available, open source datasets. Specifically, it applies decision tree, random forest, feed forward neural networks, and long-short term memory neural networks with hyperparameters tuned via designed experiment to five labeled bot datasets created between 2011 and 2020 and one dataset labeling state-sponsored disinformation accounts or trolls. The first three models utilize account profile features, while the last model applies natural language processing techniques, specifically GloVe embedding, to analyze a user’s Tweet history. Results indicate that the random forest model outperforms the other three models with an average …
Analysis And Optimization Of Contract Data Schema, Franklin Sun
Analysis And Optimization Of Contract Data Schema, Franklin Sun
Theses and Dissertations
agement, development, and growth of U.S Air Force assets demand extensive organizational communication and structuring. These interactions yield substantial amounts of contracting and administrative information. Over 4 million such contracts as a means towards obtaining valuable insights on Department of Defense resource usage. This set of contracting data is largely not optimized for backend service in an analytics environment. To this end, the following research evaluates the efficiency and performance of various data structuring methods. Evaluated designs include a baseline unstructured schema, a Data Mart schema, and a snowflake schema. Overall design success metrics include ease of use by end …
Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill
Hierarchical Federated Learning On Healthcare Data: An Application To Parkinson's Disease, Brandon J. Harvill
Theses and Dissertations
Federated learning (FL) is a budding machine learning (ML) technique that seeks to keep sensitive data private, while overcoming the difficulties of Big Data. Specifically, FL trains machine learning models over a distributed network of devices, while keeping the data local to each device. We apply FL to a Parkinson’s Disease (PD) telemonitoring dataset where physiological data is gathered from various modalities to determine the PD severity level in patients. We seek to optimally combine the information across multiple modalities to assess the accuracy of our FL approach, and compare to traditional ”centralized” statistical and deep learning models.
Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald
Air Force Cadet To Career Field Matching Problem, Ian P. Macdonald
Theses and Dissertations
This research examines the Cadet to Air Force Specialty Code (AFSC) Matching Problem (CAMP). Currently, the matching problem occurs annually at the Air Force Personnel Center (AFPC) using an integer program and value focused thinking approach. This paper presents a novel method to match cadets with AFSCs using a generalized structure of the Hospitals Residents problem with special emphasis on lower quotas. This paper also examines the United States Army Matching problem and compares it to the techniques and constraints applied to solve the CAMP. The research culminates in the presentation of three algorithms created to solve the CAMP and …
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Theses and Dissertations
The United States Air Force is investing in artificial intelligence (AI) to speed analysis in efforts to modernize the use of autonomous unmanned combat aerial vehicles (AUCAVs) in strike coordination and reconnaissance (SCAR) missions. This research examines an AUCAVs ability to execute target strikes and provide reconnaissance in a SCAR mission. An orienteering problem is formulated as anMarkov decision process (MDP) model wherein a single AUCAV must optimize its target route to aid in eliminating time-sensitive targets and collect imagery of requested named areas of interest while evading surface-to-air missile (SAM) battery threats imposed as obstacles. The AUCAV adjusts its …
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Theses and Dissertations
Using convolutional neural networks (CNNs) for image classification for each frame in a video is a very common technique. Unfortunately, CNNs are very brittle and have a tendency to be over confident in their predictions. This can lead to what we will refer to as “flickering,” which is when the predictions between frames jump back and forth between classes. In this paper, new methods are proposed to combat these shortcomings. This paper utilizes a Bayesian CNN which allows for a distribution of outputs on each data point instead of just a point estimate. These distributions are then smoothed over multiple …
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Theses and Dissertations
We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …
Identifying Characteristics For Success Of Robotic Process Automations, Charles M. Unkrich
Identifying Characteristics For Success Of Robotic Process Automations, Charles M. Unkrich
Theses and Dissertations
In the pursuit of digital transformation, the Air Force creates digital airmen. Digital airmen are robotic process automations designed to eliminate the repetitive high-volume low-cognitive tasks that absorb so much of our Airmen's time. The automation product results in more time to focus on tasks that machines cannot sufficiently perform data analytics and improving the Air Force's informed decision-making. This research investigates the assessment of potential automation cases to ensure that we choose viable tasks for automation and applies multivariate analysis to determine which factors indicate successful projects. The data is insufficient to provide significant insights.
A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia
A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia
Theses and Dissertations
The purpose of this research is to explore the utility and current state of touchless technologies. Five categories of technologies are identified as a result of collecting and reviewing literature: facial/biometric recognition, gesture recognition, touchless sensing, personal devices, and voice recognition. A thematic analysis was conducted to evaluate the advantages and disadvantages of the five categories. A reference analysis was also conducted to determine the similarities between articles in each category. Touchless sensing showed to have the most advantages and least similar references. Gesture recognition was the opposite. Comparing analyses shows more reliable technology types are more beneficial and diverse.
Analysis Of Generalized Artificial Intelligence Potential Through Reinforcement And Deep Reinforcement Learning Approaches, Jonathan Turner
Analysis Of Generalized Artificial Intelligence Potential Through Reinforcement And Deep Reinforcement Learning Approaches, Jonathan Turner
Theses and Dissertations
Artificial Intelligence is the next competitive domain; the first nation to develop human level artificial intelligence will have an impact similar to the development of the atomic bomb. To maintain the security of the United States and her people, the Department of Defense has funded research into the development of artificial intelligence and its applications. This research uses reinforcement learning and deep reinforcement learning methods as proxies for current and future artificial intelligence agents and to assess potential issues in development. Agent performance were compared across two games and one excursion: Cargo Loading, Tower of Hanoi, and Knapsack Problem, respectively. …
The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold
The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold
Theses and Dissertations
Traditional control mechanisms restrict human input on the displays in 5th generation aircraft. This research explored methods for enhancing pilot interaction with large, information dense cockpit displays; specifically, the effects of visual feedback and control button configuration when augmenting cursor control with head tracking technology. Previous studies demonstrated that head tracking can be combined with traditional cursor control to decrease selection times but can increase pilot mental and physical workload. A human subject experiment was performed to evaluate two control button configurations and three visual feedback conditions. A Fitts Law analysis was performed to create predictive models of selection time …
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Theses and Dissertations
Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …
Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood
Enterprise Resource Allocation For Intruder Detection And Interception, Adam B. Haywood
Theses and Dissertations
This research considers the problem of an intruder attempting to traverse a defender's territory in which the defender locates and employs disparate sets of resources to lower the probability of a successful intrusion. The research is conducted in the form of three related research components. The first component examines the problem in which the defender subdivides their territory into spatial stages and knows the plan of intrusion. Alternative resource-probability modeling techniques as well as variable bounding techniques are examined to improve the convergence of global solvers for this nonlinear, nonconvex optimization problem. The second component studies a similar problem but …
Algorithm Selection Framework: A Holistic Approach To The Algorithm Selection Problem, Marc W. Chalé
Algorithm Selection Framework: A Holistic Approach To The Algorithm Selection Problem, Marc W. Chalé
Theses and Dissertations
A holistic approach to the algorithm selection problem is presented. The “algorithm selection framework" uses a combination of user input and meta-data to streamline the algorithm selection for any data analysis task. The framework removes the conjecture of the common trial and error strategy and generates a preference ranked list of recommended analysis techniques. The framework is performed on nine analysis problems. Each of the recommended analysis techniques are implemented on the corresponding data sets. Algorithm performance is assessed using the primary metric of recall and the secondary metric of run time. In six of the problems, the recall of …
Meta Learning Recommendation System For Classification, Clarence O. Williams Iii
Meta Learning Recommendation System For Classification, Clarence O. Williams Iii
Theses and Dissertations
A data driven approach is an emerging paradigm for the handling of analytic problems. In this paradigm the mantra is to let the data speak freely. However, when using machine learning algorithms, the data does not naturally reveal the best or even a good approach for algorithm choice. One method to let the algorithm reveal itself is through the use of Meta Learning, which uses the features of a dataset to determine a useful model to represent the entire dataset. This research proposes an improvement on the meta-model recommendation system by adding classification problems to the candidate problem space with …
Evaluating The Resiliency Of Industrial Internet Of Things Process Control Using Protocol Agnostic Attacks, Hector L. Roldan
Evaluating The Resiliency Of Industrial Internet Of Things Process Control Using Protocol Agnostic Attacks, Hector L. Roldan
Theses and Dissertations
Improving and defending our nation's critical infrastructure has been a challenge for quite some time. A malfunctioning or stoppage of any one of these systems could result in hazardous conditions on its supporting populace leading to widespread damage, injury, and even death. The protection of such systems has been mandated by the Office of the President of the United States of America in Presidential Policy Directive Order 21. Current research now focuses on securing and improving the management and efficiency of Industrial Control Systems (ICS). IIoT promises a solution in enhancement of efficiency in ICS. However, the presence of IIoT …
Multi-Plc Exercise Environments For Training Ics First Responders, Joseph K. Daoud
Multi-Plc Exercise Environments For Training Ics First Responders, Joseph K. Daoud
Theses and Dissertations
When systems are targeted by cyber attacks, cyber first responders must be able to react effectively, especially when dealing with critical infrastructure. Training for cyber first responders is lacking and most existing exercise platforms are expensive, inaccessible or ineffective. This paper presents a mobile training platform which incorporates a variety of programmable logic controllers into a single system which facilitates the development of the unique skills required of cyber first responders operating in the realm of industrial control systems. The platform is modeled after a jail in the northeastern United States and was developed to maximize realism. Example training scenarios …
A Method To Develop Neck Injury Criteria To Aid Design And Test Of Escape Systems Incorporating Helmet Mounted Displays, Jeffrey C. Parr
A Method To Develop Neck Injury Criteria To Aid Design And Test Of Escape Systems Incorporating Helmet Mounted Displays, Jeffrey C. Parr
Theses and Dissertations
HMDs are becoming common human-machine interface equipment in manned military flight, but introducing this equipment into the overall aircraft escape system poses new and significant system design, development, and test concerns. Although HMDs add capabilities, which improve operator performance, the increased capability is often accompanied by increased head supported mass. The increased mass can amplify the risk of pilot neck injury during ejection when compared to lighter legacy helmets. Currently no adequate USAF neck injury criteria exist to effectively guide the requirements, design, and test of escape systems for pilots with HMDs. This research effort presents a novel method to …
Toward Automating Web Protocol Configuration For A Programmable Logic Controller Emulator, Deanna R. Fink
Toward Automating Web Protocol Configuration For A Programmable Logic Controller Emulator, Deanna R. Fink
Theses and Dissertations
Industrial Control Systems (ICS) remain vulnerable through attack vectors that exist within programmable logic controllers (PLC). PLC emulators used as honeypots can provide insight into these vulnerabilities. Honeypots can sometimes deter attackers from real devices and log activity. A variety of PLC emulators exist, but require manual figuration to change their PLC pro le. This limits their flexibility for deployment. An automated process for configuring PLC emulators can open the door for emulation of many types of PLCs. This study investigates the feasibility of creating such a process. The research creates an automated process for figuring the web protocols of …
Analysis Of The Impact Of Data Normalization On Cyber Event Correlation Query Performance, Smile T. Ludovice
Analysis Of The Impact Of Data Normalization On Cyber Event Correlation Query Performance, Smile T. Ludovice
Theses and Dissertations
A critical capability required in the operation of cyberspace is the ability to maintain situational awareness of the status of the infrastructure elements that constitute cyberspace. Event logs from cyber devices can yield significant information, and when properly utilized they can provide timely situational awareness about the state of the cyber infrastructure. In addition, proper Information Assurance requires the validation and verification of the integrity of results generated by a commercial log analysis tool. Event log analysis can be performed using relational databases. To enhance database query performance, previous literatures affirm denormalization of databases. Yet database normalization can also increase …
Measuring The Utility Of A Cyber Incident Mission Impact Assessment (Cimia) Process For Mission Assurance, Christy L. Peterson
Measuring The Utility Of A Cyber Incident Mission Impact Assessment (Cimia) Process For Mission Assurance, Christy L. Peterson
Theses and Dissertations
Information is a critical asset on which virtually all modern organizations depend upon to meet their operational mission objectives. Military organizations, in particular, have embedded Information and Communications Technologies (ICT) into their core mission processes as a means to increase their operational efficiency, exploit automation, improve decision quality, and shorten the kill chain. However, the extreme dependence upon ICT results in an environment where a cyber incident can result in severe mission degradation, or possibly failure, with catastrophic consequences to life, limb, and property. These consequences can be minimized by maintaining real-time situational awareness of mission critical resources so appropriate …
Host-Based Multivariate Statistical Computer Operating Process Anomaly Intrusion Detection System (Paids), Glen R. Shilland
Host-Based Multivariate Statistical Computer Operating Process Anomaly Intrusion Detection System (Paids), Glen R. Shilland
Theses and Dissertations
No abstract provided.
A Hybrid Templated-Based Composite Classification System, Michael A. Turnbaugh
A Hybrid Templated-Based Composite Classification System, Michael A. Turnbaugh
Theses and Dissertations
An automatic target classification system contains a classifier which reads a feature as an input and outputs a class label. Typically, the feature is a vector of real numbers. Other features can be non-numeric, such as a string of symbols or alphabets. One method of improving the performance of an automatic classification system is through combining two or more independent classifiers that are complementary in nature. Complementary classifiers are observed by finding an optimal method for partitioning the problem space. For example, the individual classifiers may operate to identify specific objects. Another method may be to use classifiers that operate …
Internet Protocol Geolocation: Development Of A Delay-Based Hybrid Methodology For Locating The Geographic Location Of A Network Node, John M. Roehl
Internet Protocol Geolocation: Development Of A Delay-Based Hybrid Methodology For Locating The Geographic Location Of A Network Node, John M. Roehl
Theses and Dissertations
Internet Protocol Geolocation (IP Geolocation), the process of determining the approximate geographic location of an IP addressable node, has proven useful in a wide variety of commercial applications. Commercial applications of IP Geolocation include market research, redirection for performance enhancement, restricting content, and combating fraud. The potential for military applications include securing remote access via geographic authentication, intelligence collection, and cyber attack attribution. IP Geolocation methods can be divided into three basic categories based upon what information is used to determine the geographic location of the given IP address: 1) Information contained in databases, 2) information that is leaked during …
Beyond Passswords: Usage And Policy Transformation, Alan S. Alsop
Beyond Passswords: Usage And Policy Transformation, Alan S. Alsop
Theses and Dissertations
The purpose of this research is to determine whether the transition to a two-factor authentication system is more secure than a system that relied only on what users “know” for authentication. While we found that factors that made passwords inherently vulnerable did not transfer to the PIN portion of a two-factor authentication system, we did find significant problems relating to usability, worker productivity, and the loss and theft of smart cards. The new authentication method has disrupted our ability to stay connected to ongoing mission issues, forced some installations to cut off remote access for their users and in one …
Recommendations For A Standardized Program Management Office (Pmo) Time Compliance Network Order (Tcno) Patching Process, Michael Czumak Iii
Recommendations For A Standardized Program Management Office (Pmo) Time Compliance Network Order (Tcno) Patching Process, Michael Czumak Iii
Theses and Dissertations
Network security is a paramount concern for organizations utilizing computer technology, and the Air Force is no exception. Network software vulnerability patching is a critical determinant of network security. The Air Force deploys these patches as Time Compliance Network Orders (TCNOs), which together with associated processes and enforced timelines ensure network compliance. While the majority of the network assets affected by this process are Air Force owned and operated, a large number are maintained by external entities known as Program Management Offices (PMOs). Although these externally controlled systems provide a service to the Air Force and reside on its network, …
Towards The Development Of A Defensive Cyber Damage And Mission Impact Methodology, Larry W. Fortson Jr.
Towards The Development Of A Defensive Cyber Damage And Mission Impact Methodology, Larry W. Fortson Jr.
Theses and Dissertations
The purpose of this research is to establish a conceptual methodological framework that will facilitate effective cyber damage and mission impact assessment and reporting following a cyber-based information incidents. Joint and service guidance requires mission impact reporting, but current efforts to implement such reporting have proven ineffective. This research seeks to understand the impediments existing in the current implementation and to propose an improved methodology. The research employed a hybrid historical analysis and case study methodology for data collection through extensive literature review, examination of existing case study research and interviews with Air Force members and civilian personnel employed as …