Operations Research, Systems Engineering and Industrial Engineering Commons^™

Development Of Software Tools For Efficient And Sustainable Process Development And Improvement, Jake P. Stengel

Theses and Dissertations

Infrastructure is a key component in the well-being of our society that leads to its growth, development, and productive operations. A well-built infrastructure allows the community to be more competitive and promotes economic advancement. In 2021, the ASCE (American Society of Civil Engineers) ranked the American infrastructure as substandard, with an overall grade of C-. The overall ranking suffers when key infrastructure categories are not maintained according to the needs of the population. Therefore, there is a need to consider alternative methods to improve our infrastructure and make it more sustainable to enhance the overall grade. One of the challenges …

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 …

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 …

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.

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 …

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

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

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.

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. …

Energy Planning Model Design For Forecasting The Final Energy Consumption Using Artificial Neural Networks, Haidy Eissa

Theses and Dissertations

“Energy Trilemma” has recently received an increasing concern among policy makers. The trilemma conceptual framework is based on three main dimensions: environmental sustainability, energy equity, and energy security. Energy security reflects a nation’s capability to meet current and future energy demand. Rational energy planning is thus a fundamental aspect to articulate energy policies. The energy system is huge and complex, accordingly in order to guarantee the availability of energy supply, it is necessary to implement strategies on the consumption side. Energy modeling is a tool that helps policy makers and researchers understand the fluctuations in the energy system. Over the …

Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He

Theses and Dissertations

Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …

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 …

Design Of A Novel Manual And Automated Penetration Testing Framework For Connected Industrial Control Systems (Ics), Rafat Elsharef

Theses and Dissertations

This research presents the design of new framework—a manually executed and an automated penetration testing process for Connected Industrial Control Systems (ICS). Both frameworks were built using open-source security software and ICS equipment currently used in critical infrastructure, manufacturing companies, and other institutions in the United States and around the world. Existing penetration testing frameworks have largely been focused on manual testing and are specific to Information Technology (IT). In addition, a new severity scoring system framework, called Common Vulnerability Scoring System for Industrial Control Systems (CVSS-ICS), was recommended for calculating the severity score in Industrial Control Systems (ICS).The broader …

Reevaluating Order Fulfillment Decisions For E-Tailers Under True Simulated Operating Conditions, Amir H. Kalantari

Theses and Dissertations

This dissertation makes both a methodological and an applied contribution. From a methodological standpoint, this is among the very first works in the literature to explore the concepts of true simulated operating conditions and fully embedded decision-making algorithms. We illustrate the effectiveness of these concepts by applying them to an online retailer (i.e. e-tailer) order fulfillment decision making process.

Online shopping has completely transformed retail markets in recent years. For customers, it provides convenience, visibility and choice, and for retailers it provides market expansion opportunities, operational cost reduction, and many other advantages. There are fundamental differences between the supply chain …

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

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

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 …

A Microscopic Simulation Laboratory For Evaluation Of Off-Street Parking Systems, Yun Yuan

Theses and Dissertations

The parking industry produces an enormous amount of data every day that, properly analyzed, will change the way the industry operates. The collected data form patterns that, in most cases, would allow parking operators and property owners to better understand how to maximize revenue and decrease operating expenses and support the decisions such as how to set specific parking policies (e.g. electrical charging only parking space) to achieve the sustainable and eco-friendly parking.

However, there lacks an intelligent tool to assess the layout design and operational performance of parking lots to reduce the externalities and increase the revenue. To address …

Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie

Theses and Dissertations

Preventing cyberterrorism is becoming a necessity for individuals, organizations, and governments. However, current policies focus on technical and managerial aspects without asking for experts and non-experts values and preferences for preventing cyberterrorism. This study employs value focused thinking and public value forum to bare strategic measures and alternatives for complex policy decisions for preventing cyberterrorism. The strategic measures and alternatives are per socio-technical process.

Data Analysis And Processing Techniques For Remaining Useful Life Estimations, John Scott Bucknam

Theses and Dissertations

In the field of engineering, it is important to understand different engineering systems and components, not only in how they currently perform, but also how their performance degrades over time. This extends to the field of prognostics, which attempts to predict the future of a system or component based on its past and present states. A common problem in this field is the estimation of remaining useful life, or how long a system or component functionality will last. The well-known datasets for this problem are the PHM and C-MAPSS datasets. These datasets contain simulated sensor data for different turbofan engines …

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

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

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

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

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

Theses and Dissertations

No abstract provided.

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

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

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

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, …