Other Operations Research, Systems Engineering and Industrial Engineering Commons^™

Ambient Air Emission Profiles Of Polycyclic Aromatic Hydrocarbons Around A Typical University Power House In Nigeria, Oyetunji Okedere

Tanzania Journal of Engineering and Technology (TJET)

The level of electricity generation in Nigeria is presently grossly inadequate. Consequently, the productive sectors of the economy do not presently enjoy an uninterrupted supply of electrical energy from the country’s national grid and the downtime is in most cases too much. Using diesel-fueled electric power generators has become an attractive alternative to meet the shortfall in the energy supply gap. In this study, the levels of polycyclic aromatic hydrocarbons in the vicinity of the diesel-fueled electric power generators operated by Osun State University, Osogbo, Nigeria were investigated with a view to ascertain the priority levels and carcinogenic PAHs. Since …

A Behavioral Epidemic Model: A Simulation And Empirical Analysis, Ann Osi, Navid Ghaffarzadegan

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Software Maintenance: Planning A Server Upgrade - A Library Perspective, Wilhelmina Randtke, Melissa Jackson

University Libraries: Faculty Presentations

Like many libraries, the Georgia Southern University Libraries (GS Libraries) rely on tools to support library services which are run on in-house servers. The servers are run by main campus Information Technology Services (ITS), and ITS is not familiar with how each piece of software is used and how it is supposed to work. ITS monitors the basic high level server architecture but does not work with the actual applications installed on these servers.

Tools like EZProxy and ILLiad are mission critical and are run in-house. Over the past year, the GS Libraries have formalized an upgrade process for the …

Advances In Quaternion-Valued Neural Networks, Jeremiah P. Bill

Theses and Dissertations

This dissertation investigates the construction, optimization, and application of quaternion neural networks (QNNs) to Department of Defense (DoD) related problem sets. QNNs are a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. This work provides a critical evaluation of the myriad different quaternion backpropagation derivations that exist in the literature, testing the performance of each on a range of regression problem sets. The optimization dynamics of QNNs are explored, presenting visualizations of QNN loss surfaces and a novel method for assessing the “smoothness” of these loss surfaces. Finally, this dissertation presents …

Assessing And Predicting The Students’ Systems Thinking Preference: Multi-Criteria Decision Making And Machine Learning, Siham Tazzit

Theses and Dissertations

The 21st century is marked by a technological revolution that features digital implementation and high interconnectivity between systems across different domains, such as transportation, agriculture, education, and health. Although these technological changes resulted in modern systems capable of easing individuals’ lives, these systems are increasingly complex, and that increased complexity is only expected to continue. The increased system complexity is due to the rapid exchange of information between subsystems, which creates high interconnectivity and interdependence between the subsystems and their elements. Workforce skill sets, as a result, must be modified appropriately to ensure the systems’ success. Systems Thinking is an …

Ai Methods For Identifying Process Defects In Advanced Manufacturing With Rare Labeled Data, Ayantha Umesh Senanayaka Mudiyanselage

Theses and Dissertations

This dissertation aims to provide efficient process defect identification methods for advanced manufacturing environments using AI tools/algorithms with limited labeled data availability. Asset and equipment quality become highly sensitive in sustaining virtuous performance and safety in various manufacturing domains. Internally generated process imperfections degrade finished products' optimum performance and mechanical attributes. The evolution of big data and intelligent sensing systems leverage data-driven defect identification in advanced manufacturing environments. Widely adopted data-driven process anomaly detection methods assume that the training (source) and testing (target) data follow the same distribution and that labeled data are available in both source and target domains. …

Variability In Anesthesia And Its Implications For Improving Patient Safety, Joshua Michael Biro

All Dissertations

Improving patient safety in anesthesia has proven to be an arduous and challenging task. Despite the many strategies and interventions to improve patient safety that have been employed, patient harm in anesthesia remains a problem. The struggle to reduce patient harm in anesthesia is both attributable to and representative of the complexity of the anesthesia system. In navigating this complex system, anesthesia providers have different approaches to how they accomplish their work, which results in variability in anesthesia practice. This variability provides an immense challenge to designing and implementing efforts to improve patient safety, as rigid interventions are often met …

The Characteristics Of Successful Military It Projects: A Cross-Country Empirical Study, Helene Berg, Jonathan D. Ritschel

Faculty Publications

In the armed forces, successful digitalization is crucial to ensure effective operations. Much of the existing literature on project factors during the planning and execution phases of public IT projects do not focus specifically on military sector projects. Therefore, the paper aims to provide empirical insights into the characteristics of successful military IT projects. Data from such projects in NATO countries and agencies were collected through interviews and project documents. The findings relating to the main variable of interest, “delivery of client benefit,” supported previous findings on IT project performance. Medium-sized projects performed better than small and large projects, and …

Cost Estimation Trends For Major Defense Acquisition Programs, Sammantha Jones, Edward D. White, Jonathan D. Ritschel, Shawn M. Valentine

Faculty Publications

The authors use both descriptive and inferential techniques to investigate average and standard deviation trends in cost estimates for major defense acquisition programs (MDAPs) grouped into decades from the 1970s to 2010s. For total program-cost-growth factors (CGFs), the 2010s exhibited lower CGFs compared to the 1990s. For the program-acquisition-unit cost (PAUC) CGFs, the 2010s appear lower than the 1990s and borderline lower than the 1970s. A statistically significant decreasing trend in the standard deviations of total program CGFs throughout the decades was identified. This lowering variability trend also appeared for PAUC CGFs from the 1980s onward. This finding appears to …

Resources Based Planning Framework For Infrastructure Maintenance And Rehabilitation Projects, Heba Gad

Theses and Dissertations

Infrastructure maintenance and rehabilitation projects involve activities scattered over a large geographical area (e.g., scattered road segments maintenance, telecom towers maintenance program, etc.). Planning such projects require a resource-based approach that accounts for the implications of resource mobility between activities’ locations in terms of time & cost. Existing scheduling techniques fall short of addressing the unique challenges of the scattered nature of these projects in combination with organization's limited resources availability. To address this need, this research presents a resources-based planning framework for infrastructure maintenance and rehabilitation scattered projects with the objective of enhancing resources utilization achieving time and cost …

Design And Analysis Of Asymmetric “String-Of-Pearls” Common Repeating-Ground-Track Satellite Constellations For Missions Requiring Regional Coverage, Nathaniel Choo

Theses and Dissertations

Satellite constellation design must balance many factors that emerge from multiple sources, including environmental hazards and competing mission objectives. The dynamic nature of space systems makes the problem of ‘optimal’ satellite constellation design even more challenging. Restricting satellite constellation designs to predefined geometric frameworks can alleviate many challenges associated with the design problem; however, it raises an important question: which geometric framework performs best for each mission set? This research leverages simulations, metaheuristics, and mathematical programming techniques to address this question for missions focusing on Earth-observation of one or more regions.

First, this research captures the current state of satellite …

Portfolio Optimization Using Value Focused Thinking, Tyler Martin

Theses and Dissertations

This thesis explores the application of Value Focused Thinking (VFT) and multi-objective portfolio optimization to create a well-aligned portfolio for an organization faced with over 50 alternatives and limited funding. A novel technique is proposed to develop an optimized portfolio based on VFT scores, utilizing heuristic approaches like evolutionary algorithms. The research outcomes include an optimized portfolio, the total value evaluation of alternatives, and a sensitivity analysis. The new approach outperforms the organization’s previous method, resulting in a portfolio that better addresses the organization’s core values and objectives, scoring 21.21% higher.

Developing Systems Engineering And Machine Learning Frameworks For The Improvement Of Aviation Maintenance, Fatine Elakramine

Theses and Dissertations

This dissertation develops systems engineering and machine learning models for aviation maintenance support. With the constant increase in demand for air travel, aviation organizations compete to maintain airworthy aircraft to ensure the safety of passengers. Given the importance of aircraft safety, the aviation sector constantly needs technologies to enhance the maintenance experience, ensure system safety, and limit aircraft downtime. Based on the current literature, the aviation maintenance sector still relies on outdated technologies to maintain aircraft maintenance documentation, including paper-based technical orders. Aviation maintenance documentation contains a mixture of structured and unstructured technical text, mainly inputted by operators, making them …

Human Factors Engineering, Robert S. Keyser

KSU Distinguished Course Repository

Human Factors Engineering is a comprehensive survey of human factors theory, research, and applications which are of particular relevance to Quality and Engineering Management. Emphasis will be placed on operator constraints in the design of work processes, workplaces, and instrumentation.

Development Of A Smart Waste Management System For City Application, Lawrence D. Fraction

Morehead State Theses and Dissertations

A thesis presented to the faculty of the Elmer R. Smith College of Business and Technology Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Lawrence D. Fraction on April 14, 2023.

Rate Effects In Aircraft Learning Curves, Caleb J. Ahern

Theses and Dissertations

Across the Department of Defense (DoD), a wide variety of analytical tools are employed by cost analysts to estimate weapon system costs. One of the techniques widely employed by practitioners is the learning curve (LC). Although learning curves have been widely studied, using rate-adjustments or production rate effects (PRE), their usage have only intermittently been evaluated in place of using the traditional learning curve. Previous studies analyzing production rate found mixed results. This research aims to examine aircraft production data to determine if production rate model is preferrable in United States Air Force programs. Additionally, this PRE research seeks to …

Team And Skill Matching For Disaster Recovery Operations, Emily B. Frahm

Theses and Dissertations

United States Air Force (USAF) bases are key power projection platforms that ensure mission readiness and help bring humanitarian aid to locations in need. Recovering airfields after attack or natural disaster is a key mission of USAF civil engineers, and accomplishing this repair as swiftly as possible is key to maintaining our position in the global order. Accomplishing a disaster recovery project is a set of teams, each assigned to a specific task, and made up of a series of personnel. The question answered within this paper is: how do we match the right person with the appropriate skills to …

Pattern Of Life Modeling On Maritime Vessels With Bayesian Inferencing, Miles A. Kelly

Theses and Dissertations

Despite decades of research, maritime traffic models’ limited predictive power continues to constrain their operational utility. We build on previous pattern of life modeling algorithms and contribute a Bayesian inferencing model for anomaly detection. Our probabilistic approach provides decision makers the capability to tailor the belief threshold for identifying anomalies and to enact a measured response based on the degree of abnormality. We perform a case study to evaluate the results, verifying that our Bayesian inferencing method accurately refines its probability when given the location and time of a ship of interest, and serving as a proof of concept for …

Uncertainty Quantification In Federated Learning For Persistent Post-Traumatic Headache, Byungmoo Brian Kim

Theses and Dissertations

A post-traumatic headache (PTH), resulting from a mild traumatic brain injury (mTBI), potentially develops into persistent post-traumatic headache (PPTH). Although no known cure for PPTH exists, research has shown that receiving treatment at earlier stages of PTH lowers the risk of patients developing PPTH. Previous studies have shown machine learning (ML) models capable of predicting a patient’s PTH progression, but none have considered the issue of protecting patient privacy. Due to patient privacy, ML models only have access to data within the institution. Federated learning (FL) harnesses data from separate institutions without sacrificing patient privacy as institutions can run ML …

Long-Term Asset Prioritization To Support District Planning, Melissa R. Sallberg

Theses and Dissertations

The United States Air Force (USAF) relies on its installations to project military power across the globe. However, due to the deferred infrastructure maintenance and recapitalization backlog of $33 billion as of 2019 (Wilson & Goldfein, 2019), it is more critical than ever for base-level community planners to focus their attention to the projects that will achieve each installation’s long-term goals. The recent incorporation of asset management principles into the USAF District Planning Process allows a unique opportunity to improve the existing scoring model for a holistic look at what matters to enterprise leaders and community planners making the plans …