Operations Research, Systems Engineering and Industrial Engineering Commons^™

Predictive And Prescriptive Analytics For Minimizing The Cost Of Recidivism, Adreana Julander

Operations Research and Engineering Management Theses and Dissertations

A problem faced by the United States is the ever increasing prison population. There are inmates serving long sentences, new inmates being sentenced for the first time, and those who have previously served prison sentences that reoffend. The third group and the reduction of recidivism are the focus this dissertation. It is estimated that over 80% of inmates released from prison will reoffend within the next ten years. Is there an optimal sentence length that reduces that chance of an ex-convict reoffending? Are there programs or opportunities that some inmates have while incarcerated that reduce the probability they will return …

Modeling Advancement In Spacefaring Through Deep Learning, Peng-Hung Tsai

Theses and Dissertations

Predicting advancement in space exploration technology allows space agencies and companies to strategically allocate resources, prioritize missions, and explore collaborations on complex projects. This foresight acts as a roadmap for future exploration, making the best use of valuable resources. The present study employs spacecraft lifetimes as an exemplar of technological progress and proposes a novel forecasting model based on Long Short-Term Memory (LSTM) networks. Existing research often suggests an increasing exponential relationship between technology performance and time (the generalized Moore's Law). However, applying this model directly to spacecraft lifetimes has a limitation. Spacecraft lifespans are unknown at launch, and recent …

Safety And Risk Management Strategies For Achieving Regulatory Compliance In Construction Projects, Danny Rodriguez

Harrisburg University Dissertations and Theses

The architectural and construction business places great importance on safety and regulatory compliance because of its inherent high-risk nature and strict legal obligations. The prevalence of accidents and infractions at construction sites underscores the imperative for enhanced safety management systems and compliance with rules, notwithstanding substantial endeavors. The main objective of this study is to examine the many elements that impact the effectiveness of safety management, adherence to regulations, and the development of a safety culture, with the ultimate purpose of improving safety outcomes on construction sites.

The issue statement pertains to the difficulties associated with safety management and compliance …

Quantifying Lock Criticality For Inland Waterway Navigation Using An Agent-Based Simulation, Ashwin Narayan

Industrial Engineering Undergraduate Honors Theses

Inland waterway travel has tremendous potential to improve multimodal transportation in the United States due to its environment-friendly and safe nature. Waterway travel has proven to be much cheaper per ton-mile and more fuel efficient than trucks. Millions of dollars have recently been invested in inland waterway networks to facilitate travel. The waterway infrastructure must be resilient to enable efficient waterway travel and prevent unnecessary delays. Locks, an important component of waterway infrastructure, enable vessels to travel between waterways of varying depths and must be maintained consistently to avoid unexpected failures. However, with limited resources, it is difficult to preserve …

Application Of Agent-Based Simulation And Game Theory In Evaluating Implementation Of Whole Genome Sequencing In Treating Lung Cancer, Fateme Ghalenoei

Master's Theses

Cancer, particularly lung cancer, presents significant diagnostic and economic challenges globally. Timely diagnosis and cost management play pivotal roles in treatment success. A biomarker is any measurable molecule in blood, bodily fluids, or tissues, indicating the potential presence of an abnormal bodily process, condition, or disease. Biomarker testing is a laboratory test in oncology that is used in the selection of targeted cancer treatments and to help avoid ineffective treatments. Whole Genome Sequencing (WGS), is a biomarker test which while more comprehensive, comes at a higher cost. This study proposes an agent-based simulation model within a game-theoretic framework to examine …

Five Pivotal Practices For Leaders To Cultivate Empathy Within Virtual Scrum Teams, Dahm Mongkol Hongchai, Charles M. Weber

Engineering and Technology Management Faculty Publications and Presentations

In the digital and global economy, business leaders need more than just business and technology competencies; they also require empathy. However, there is a notable scarcity of research on empathy in Scrum for product development. This study aims to uncover critical insights into how leaders can foster empathy within virtual Scrum teams. Accordingly, this paper proposes five pivotal themes leaders can employ: Scrum fundamentals, meditation, self- and other-analysis, healthy interactions, and informal connections. These vital strategies offer actionable methods for leaders seeking to enhance empathy within their virtual Scrum teams.

Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny

All Theses

High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …

Exploring Telehealth Utilization Through Data Analytics, Statistical Analyses, And Machine Learning Techniques, Aysenur Betul Cengil

Graduate Theses and Dissertations

This dissertation investigates the utilization of telehealth services, initially focusing on the Arkansas healthcare system and then extending the analysis nationwide. It aims to understand the factors influencing telehealth adoption and its impact on healthcare delivery. After examining telehealth utilization in Arkansas from 2018 to 2022, the research utilizes a comprehensive dataset from Epic Cosmos, which includes a wide range of patient and visit data from multiple healthcare facilities across the United States from 2018 to 2023. This timeframe allows for a detailed analysis of telehealth trends before, during, and after the COVID-19 pandemic. In Chapter 2, we analyze key …

Home Care Work Of Caregivers For Mexican American Adults With Dementia: A Culturally Informed Model Integrating Work System Analyses And Health Disparities Research Framework, Laura Cristina Tovar Felix

Open Access Theses & Dissertations

Dementia is an umbrella term for different diseases such as Alzheimer's, vascular dementia, Lewy body, frontotemporal, and mixed dementias. Dementia is caused by a variety of diseases that cause damage to brain cells interfering with the ability of brain cells to communicate between each other. Dementia is associated with different types of brain cell damage in a specific region of the brain (What Is Dementia?, 2024).Dementia affects 55 million people worldwide, where the most affected population is the low-income and the middle-income countries. (Greenblat, 2023). Every 20 years the number almost double, and by 2039 is estimated to reach 78 …

Development Of Electric Vehicle Charging Station Microgrid With Simulation Modelling, Tenzin Lhaden

Open Access Theses & Dissertations

The rapid adoption of electric vehicles (EVs) necessitates innovative solutions to overcome challenges in energy management, sustainability, and grid reliance. This research develops a hybrid simulation model for EV charging stations, integrating renewable energy sources, such as solar photovoltaic (PV) systems, with energy storage systems (ESS). Leveraging discrete-event simulation (DES) and agent-based modeling (ABM) in AnyLogic, the model offers a comprehensive analysis of charging station operations, incorporating stochastic EV arrivals, dynamic energy allocation, and user-defined customization.Key contributions include the development of hybrid simulation model integrating solar PV, energy storage, and energy management systems (EMS) that dynamically optimizes energy distribution from …

Organizational Reliability And Resilience As A Dynamic System: Knowledge Modeling With Fuzzy Cognitive Maps, Antonie J. Jetter, Ahmed A. Alibage, Nan Peter Liang

Engineering and Technology Management Faculty Publications and Presentations

Safety research in complex environments recommends that high-hazard industries improve reliability and increase their capacity for resilience by enacting principles for high-reliability organizing (HRO). This view has been highly influential in many industries, ranging from aviation to hospitals, and is at the core of many safety culture programs. However, even though HRO principles originated in business practice and were observed in diverse organizations, practitioners frequently struggle to enact them in the contexts of their work. This is likely caused by two limitations of current research: principles are insufficiently specified and the interdependencies between them, such as mutually reinforcing vs. tradeoff …

Power Resilience Planning Under The Threat Of Artificial Intelligence, Chip Corbett, Cuong Nguyen, Dahm M. Hongchai, Prajakta Thorat, Pavithra Prasad, Sarah Von Schimmelmann, Charles M. Weber, Timothy R. Anderson

Engineering and Technology Management Faculty Publications and Presentations

The earth is an unstable planet. Change is constant and frequently chaotic. It is very important to plan carefully to manage changes that can be anticipated now, and to cover potential issues that might not yet have been discovered. The dawn of artificial intelligence (AI) presents a host of new concerns and opportunities. The criteria for evaluation are diverse and complex. Cybersecurity is absolutely essential, yet advances in technology have created an internet of things (IoT) where threat vectors might gain access to critical command and control elements through trillions of connected IoT devices. Whereas elegant zero trust cybersecurity models …

Quantifying Relationships In Fuzzy Cognitive Maps Based On Content Analysis Of Unstructured Research Texts, Ahmed Alibage, Antonie J. Jetter, Elpiniki Papageorgiou

Engineering and Technology Management Faculty Publications and Presentations

FCM projects often rely on knowledge-based approaches, such as expert interviews, which can be challenging to conduct because they require extensive expert participation. We propose a novel alternative to create FCM models based on expert knowledge that is already codified in research texts and other publications. In this approach, thematic network analysis identifies FCM concepts and signed causal connections, while computation of t-coefficient is used to determine the weights of the identified edges. We introduce and evaluate the approach in the context of a real-world system modeling project that is based on 47 carefully selected, peer reviewed research publications on …

Identification And Validation Of A Measurement Of Emergency Physician Workload During End Of Shift Patient Handoffs, Steven Foster

All Dissertations

Recent increases in emergency physician (EP) workload have been identified as contributors to increased EP burnout, increased staff attrition, decreased patient safety, and increased patient admission rates. Patient handoffs have been extensively researched as critical points in patient care, with existing research primarily focusing on communication errors and interventions designed to standardize handoff communication protocols.

While end of shift handoffs in hospital emergency departments (EDs) intuitively represent a transfer of patient caseload from an outgoing EP to an incoming EP, there is a fundamental lack of literature examining how such handoffs contribute to EP workload, and a similar lack of …

Advancing Prediction And Decision Analytics Techniques To Improve Treatment Of Tuberculosis, Maryam Kheirandish Borujeni

Graduate Theses and Dissertations

Tuberculosis (TB) remains a global health challenge, significantly impacting morbidity and mortality rates worldwide. Despite advancements in diagnosis and treatment, TB continues to pose substantial challenges, particularly in low-resource settings. This dissertation aims to develop a robust treatment monitoring framework for TB patients to ensure personalized and effective treatment using demographic and clinical information. The current standard TB treatment framework, recommended by the World Health Organization (WHO), involves monitoring patients through laboratory tests such as smear and culture sputum tests at specific time points during treatment. These tests, however, are not fast and accurate enough to determine the severity of …

Using Causal Inference To Understand Public Perception Towards Electric Vehicle Adoption, Jesus Alejandro Gutierrez Araiza

Open Access Theses & Dissertations

Why despite all efforts to promote Electric Vehicles (EVs) as an alternative transportation method through strategies such as tax credits on unit purchasing or long-term environmental benefits communication, its market penetration has not reached the expected goals in the United States? Even though there have been important advancements in the EV technical perspective and financial EV purchasing incentives, the final EV customers still face barriers on their scenarios that do not allow them to purchase this type of contemporary transportation means. Not understanding their local barriers could be a mistake that could reduce EVA expectations in the country and keep, …

Integrating Machine Learning And Simulation For Resource Planning Of Hospital Systems Based On Predicted Length Of Stay, S M Atikur Rahman

Open Access Theses & Dissertations

Recently Hospital Systems faced a high invasion of patients generated by several events such as health crisis related epidemic (COVID, FLU) or seasonal flows. Hence, managing hospital bed availability and efficiency with proper care is obligatory for addressing the challenges associated with the overburden of patients. However, the Length of stay (LOS) is often increased due to the high patient influx and overcrowding problem occurs within the Hospital. It resolves these issues, it is essential for hospital authority to predict the Patients LOS which is the crucial indicator for the use of medical resources (allocation, utilization of providers and resource) …

Optimization Of Customer Service And Driver Dispatch Areas For On-Demand Food Delivery, Jingfeng Yang, Hoong Chuin Lau, Hai Wang

Research Collection School Of Computing and Information Systems

With the rapid development and popularization of mobile and wireless communication technologies, on-demand food delivery (OFD) platforms have been able to connect restaurants, customers, and drivers in real time, drastically changing dining and food delivery services. Motivated by the critical need for supply and demand management in the on-demand food delivery market, we focus on the optimization of customer service area and driver dispatch area for on-demand food delivery services. Specifically, for each restaurant, the platform needs to decide the (1) customer service area (CSA), i.e., the surrounding area within which customers can see the restaurant’s information and order food …

Understanding The Challenges To Robotic-Assisted Surgery Adoption From The Perspectives Of The Human-Robot Interaction, Built Environment, And Training, Patrick A. Fuller

All Theses

Introduction: Robotic-assisted surgery (RAS) is a form of minimally invasive surgery that is increasing in both its adoption and development due to many perceived advantages such as tremor reduction and motion scaling. However, RAS is still relatively new and there are a variety of novel barriers and challenges to the adoption of these platforms. Objectives: This study aims to understand how the integration of RAS platforms impacts the interactions and outcomes of interactions between surgical team members to explore the barriers from three aspects critical to facilitating Robotic-assisted-surgery (RAS) adoption: the human-robotic interaction, built environment, and RAS training. Future …

Path-Choice-Constrained Bus Bridging Design Under Urban Rail Transit Disruptions, Yiyang Zhu, Jian Gang Jin, Hai Wang

Research Collection School Of Computing and Information Systems

Although urban rail transit systems play a crucial role in urban mobility, they frequently suffer from unexpected disruptions due to power loss, severe weather, equipment failure, and other factors that cause significant disruptions in passenger travel and, in turn, socioeconomic losses. To alleviate the inconvenience of affected passengers, bus bridging services are often provided when rail service has been suspended. Prior research has yielded various methodologies for effective bus bridging services; however, they are mainly based on the strong assumption that passengers must follow predetermined bus bridging routes. Less attention is paid to passengers’ path choice behaviors, which could affect …

Virtual Engagement: Can Law Enforcement Benefit From Utilizing Extended Reality In Their Training Systems?, Jacob Maxwell Read

Electronic Theses and Dissertations

Introduction: Extended reality (XR) technologies offer innovative training solutions for various industries, including healthcare, manufacturing, aviation, sports, military, and law enforcement. XR can provide a solution for training where job tasks are difficult or near impossible to train in real-life. A human factors research and design approach could provide an effective, low-risk, and cost and time-efficient option for integrating the use of XR technology into training for many industries. To advance this goal, this research answered two main research questions: (1) What training needs/challenges are best suited for an XR training system designed for law enforcement officers (LEOs)? (2) …

Dynamic Model Of An Overhead Crane, Leonard Ruesga

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis a novel spatial model of an overhead crane was developed. The model includes: bridge, trolley, driving and follower wheels for the bridge and trolley, drum, cable, and the payload. The model accounts for the winding/unwinding of the cable around the drum as the payload is raised/lowered. The cable and the payload were considered as rigid bodies with uniformly distributed mass. First, the kinematic equations of the model were developed by using constraint equations. Second, the dynamic equations were derived through use of Newton’s Laws. Developing the rotational dynamic equations required the determination of the angular momentum vectors …

Opioid Overdose Epidemic Modeling, Chelsea Spence

All Dissertations

The opioid overdose crisis in the United States has led to thousands of lost lives and thousands more people struggling with opioid dependence. Disease modeling allows researchers to examine the course that the disease may take and to investigate policies to determine the effects they may have. Disease models can be used to model non-communicable diseases and have been used to study opioid use disorder. Many types of disease models exist with their own inherent benefits and drawbacks.

In this dissertation, we provide a scoping review of the disease models that have been used to study the opioid overdose epidemic. …

An Emergency Response System To Assist The Movement Of Vehicles During Emergency Operations In Urban Transportation Networks, Jamal Nahofti Kohneh

All Dissertations

Emergency responders need to arrive at the emergency scene as soon as possible, but operating vehicles under emergency conditions can pose a risk to both the responders and other road users, potentially resulting in crashes or delays in emergency operations. In this research, an emergency response system is proposed to assist emergency and non-emergency response vehicles (ERVs and non-ERVs) during emergency operations in a connected vehicle environment. This system collects the information from connected ERVs and non-ERVs, utilizes this information as inputs in the proposed models, and sends instruction messages back to vehicles. The proposed models provide the fastest ERV …

Feasibility Assessment And Container Traffic Forecasting Of Inland Waterway Container On Barge Transportation, Fan Bu

Graduate Theses and Dissertations

Container on Barge (COB) transportation is an intermodal freight transport mode that moves shipping containers via barges on navigable inland and intracoastal waterways. During the past twenty years, COB has been a growing mode of container shipping globally due to its low-cost, eco-friendly, and congestion-reducing characteristics. Europe and China are currently leading global COB transportation, and the United States (U.S.) may have the potential to achieve economic benefits through the implementation of COB within its intermodal transportation system. To explore this potential, this dissertation investigates the implementation feasibility of COB transportation within the U.S. intermodal freight transportation system. Three contributions …

Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao

Research Collection School Of Computing and Information Systems

This paper studies the problem in transportation networks and introduces a novel reinforcement learning-based algorithm, namely. Different from almost all canonical sota solutions, which are usually computationally expensive and lack generalizability to unforeseen destination nodes, segac offers the following appealing characteristics. segac updates the ego vehicle’s navigation policy in a sample efficient manner, reduces the variance of both value network and policy network during training, and is automatically adaptive to new destinations. Furthermore, the pre-trained segac policy network enables its real-time decision-making ability within seconds, outperforming state-of-the-art sota algorithms in simulations across various transportation networks. We also successfully deploy segac …

Smart Grid Cybersecurity In The Age Of Artificial Intelligence, Chip Corbett, Charles M. Weber, Timothy R. Anderson

Engineering and Technology Management Faculty Publications and Presentations

The security of the power grid is essential for the proper function of a democratic society, yet it is constantly under threat. The internet of things (loT) will make a bad situation much worse. Misinformation, disinformation, and malinformation (MDM) have been identified as serious threats to our democratic institutions, and that same acronym applies to mobile device management (MDM), and these devices have become ubiquitous. People are notoriously bad at doing basic cybersecurity. With trillions of devices and remote access everywhere, what could possibly go wrong? Now add in the engaging opportunity of distributed energy resources (DERs) and life gets …

Leveraging Machine Learning And Stochastic Programming To Address Vaccine Hesitancy In Public Health Resource Allocation, Hieu Trung Bui

Graduate Theses and Dissertations

Infectious disease outbreaks highlight the urgent need for effective strategies to distribute vaccines and allocate critical healthcare resources to contain the disease and reduce its negative impacts on the population. Managing these allocations is a significant challenge, especially in marginalized communities facing uncertainty in healthcare demand and logistical constraints. This dissertation addresses these challenges by investigating factors that influence dynamic changes in vaccine hesitancy (VH) and its implications for disease spread and healthcare resource demand. It develops optimization models for vaccine distribution and resource allocation under uncertainty, validated with data from the COVID-19 pandemic in the U.S. The first study …

Enabling Sustainable Freight Forwarding Network Via Collaborative Games, Pang Jin Tan, Shih-Fen Cheng, Richard Chen

Research Collection School Of Computing and Information Systems

Freight forwarding plays a crucial role in facilitating global trade and logistics. However, as the freight forwarding market is extremely fragmented, freight forwarders often face the issue of not being able to fill the available shipping capacity. This recurrent issue motivates the creation of various freight forwarding networks that aim at exchanging capacities and demands so that the resource utilization of individual freight forwarders can be maximized. In this paper, we focus on how to design such a collaborative network based on collaborative game theory, with the Shapley value representing a fair scheme for profit sharing. Noting that the exact …

Fuel-Saving Route Planning With Data-Driven And Learning-Based Approaches: A Systematic Solution For Harbor Tugs, Shengming Wang, Xiaocai Zhang, Jing Li, Xiaoyang Wei, Hoong Chuin Lau, Bing Tian Dai, Binbin Huang Huang, Zhe Xiao, Xiuju Fu, Zheng Qin

Research Collection School Of Computing and Information Systems

In recent years, there are trends toward cleaner port environments through enforcement by imposed legislation. Transit optimisation of fuel-based port service boats like harbour tugs has emerged as a critical task to reduce fuel consumption and carbon emission. In this paper, an innovative learning-based method, comprising a Reinforcement Learning (RL) model together with a fuel consumption prediction model, was proposed to formulate fuel-saving transit routes. Firstly, an ensemble model is established by combining a Long Short-Term Memory (LSTM) model with a Multilayer Perceptron (MLP) model, predicting fuel use based on tugboat movement and environment factors. Subsequently, an innovative RL based …