Operations Research, Systems Engineering and Industrial Engineering Commons^™

A Model-Adaptive Random Search Actor Critic: Convergence Analysis And Inventory-Control Case Studies, Yuehan Luo, Jiaqiao Hu, Abhijit Gosavi

Engineering Management and Systems Engineering Faculty Research & Creative Works

Reinforcement learning (RL) is an exciting area within the domain of Markov Decision Processes (MDPs) in which the underlying optimization problem is solved either in a simulator of the real-world system or via direct interaction with the real-world system, when its underlying transition probabilities are difficult to estimate. The latter is commonly true of large-scale, real-world MDPs with complex underlying transition dynamics. RL is currently being widely researched in the world of medicine/neuroscience after some spectacular success stories demonstrating super-human behavior in computer games. In this paper, we propose a new actor-critic-based RL algorithm for approximately solving continuous state/action MDPs …

Contextualizing Renewable Energy Adoption: An Examination Of The Role Of Community Choice Aggregation, Ankit Agarwal

Doctoral Dissertations

"The rapid expansion of renewable energy generation in the U.S., both through distributed and utility-scale facilities, is largely driven by top-down policy measures and the growing engagement of residential consumers on both individual and community levels. Previous studies on motives behind residential renewable energy adoption have examined procurement options in isolation and within a static context, primarily focused on intrinsic attributes like economic incentives, emission reductions, and peer popularity. This research introduces a novel context, assessing renewable procurement options in the presence of Community Choice Aggregation (CCA), a more prevalent and accessible alternative. This dissertation makes four pivotal contributions, offering …

Navigating Innovation Within A Contractor's Business Model: A System Dynamics Approach, Mariam Elazhary, Cihan Dagli, Islam H. El-Adaway

Engineering Management and Systems Engineering Faculty Research & Creative Works

Innovation is essential in the construction industry, but current practices often focus narrowly on specific aspects rather than taking a comprehensive approach. To address this, systematic innovation through business model innovation (BMI) is proposed to enhance overall performance. Despite increasing interest in BMI research, it remains in its early stages, lacking quantitative analysis of its impact on business model components. This paper develops a framework using system dynamics to assess changes to a construction company's BM when faced with a variety of innovations across various projects. This shall be accomplished by (1) establishing factors and their relationships that define a …

Advancing A Systems Perspective On Innovative Behavior, Stephen Demski

Doctoral Dissertations

"Engineering organizations pursue innovation in strategy, structure, processes, and the services and products offered to remain relevant and competitive. Identifying factors supporting or constraining innovative work behavior and recognizing the complexity of their interactions are vital to sustaining an innovative workforce, yet how factors interact has not been comprehensively studied.

Recognizing innovative work behavior as the output of a complex system of factors guided this study’s literature search that identified over one hundred individual, team, and organizational factors influencing innovative behavior, interviews of engineers to learn what factors are essential in their work environment, and Delphi survey to rank factors, …

Enhancing Diversity And Inclusion In Computer Science Undergraduate Programs: The Role Of Admissions, Ouldooz Baghban Karimi, Giulia Toti, Mirela Gutica, Rebecca Robinson, Lisa Zhang, James Paterson, Peggy Lindner, Michael O'Dea

Engineering Management and Systems Engineering Faculty Research & Creative Works

Despite continued efforts to further the participation of women in Computer Science (CS), progress has been limited during the past decades. Recent efforts have been focused on recruitment and retention, with a notable gap in exploring the impact of admissions processes on diversity and inclusion. Through an extensive literature review, contextual analysis of public admissions data from 40 universities across four regions around the world, and qualitative and quantitative analysis on surveys and interviews, we explored the role of admissions in enhancing diversity and inclusion in CS undergraduate programs. Our findings highlight the role of financials, the possible positive effects …

Mindfulness And Workplace Safety: An Integrative Review, Zihan Liu, Kevin Hoff, Erica Baranski, Galen Snyder, Rhona Flin, Peggy Lindner, Christiane Spitzmueller

Engineering Management and Systems Engineering Faculty Research & Creative Works

Mindfulness has recently gained popularity in applied settings to enhance workplace safety, especially in safety-critical occupations such as healthcare and construction. In this review, we synthesize existing research across disciplines to establish a theoretical model of mindfulness and safety. Based on 32 empirical studies, we first summarize and critically analyze how mindfulness and safety are conceptualized and operationalized in the literature. We then consolidate empirical findings and conceptual arguments and draw upon the job demands–resources model to propose a theoretical model linking the basic benefits of mindfulness to safety-related job demands. Specifically, we propose that mindfulness (a) improves detection of …

Machine Learning-Based Seismic Damage Assessment Of Residential Buildings Considering Multiple Earthquake And Structure Uncertainties, Xinzhe Yuan, Liujun Li, Haibin Zhang, Yanping Zhu, Genda Chen, Cihan H. Dagli

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Wood-frame structures are used in almost 90% of residential buildings in the United States. It is thus imperative to rapidly and accurately assess the damage of wood-frame structures in the wake of an earthquake event. This study aims to develop a machine-learning-based seismic classifier for a portfolio of 6,113 wood-frame structures near the New Madrid Seismic Zone (NMSZ) in which synthesized ground motions are adopted to characterize potential earthquakes. This seismic classifier, based on a multilayer perceptron (MLP), is compared with existing fragility curves developed for the same wood-frame buildings near the NMSZ. This comparative study indicates that the MLP …

Don’T Touch That Dial: Psychological Reactance, Transparency, And User Acceptance Of Smart Thermostat Setting Changes, Matthew Heatherly, Denise A. Baker, Casey I. Canfield

Psychological Science Faculty Research & Creative Works

Automation inherently removes a certain amount of user control. If perceived as a loss of freedom, users may experience psychological reactance, which is a motivational state that can lead a person to engage in behaviors to reassert their freedom. In an online experiment, participants set up and communicated with a hypothetical smart thermostat. Participants read notifications about a change in the thermostat's setting. Phrasing of notifications was altered across three dimensions: strength of authoritative language, deviation of temperature change from preferences, and whether or not the reason for the change was transparent. Authoritative language, temperatures outside the user's preferences, and …

Evaluating The Impact Of Broadband Access And Internet Use In A Small Underserved Rural Community, Javier Valentín-Sívico, Casey I. Canfield, Sarah A. Low, Christel Gollnick

Engineering Management and Systems Engineering Faculty Research & Creative Works

Having adequate access to the internet at home enhances quality-of-life for households and facilitates economic and social opportunities. Despite increased investment in response to the COVID-19 pandemic, millions of households in the rural United States still lack adequate access to high-speed internet. In this study, we evaluate a wireless broadband network deployed in Turney, a small, underserved rural community in northwest Missouri. In addition to collecting survey data before and after this internet intervention, we collected pre-treatment and post-treatment survey data from comparison communities to serve as a control group. Due to technical constraints, some of Turney's interested participants could …

Evaluating The Impact Of Broadband Access And Internet Use In A Small Underserved Rural Community, Javier Valentín-Sívico, Casey I. Canfield, Sarah A. Low, Christel Gollnick

Engineering Management and Systems Engineering Faculty Research & Creative Works

Having adequate access to the internet at home enhances quality-of-life for households and facilitates economic and social opportunities. Despite increased investment in response to the COVID-19 pandemic, millions of households in the rural United States still lack adequate access to high-speed internet. In this study, we evaluate a wireless broadband network deployed in Turney, a small, underserved rural community in northwest Missouri. In addition to collecting survey data before and after this internet intervention, we collected pre-treatment and post-treatment survey data from comparison communities to serve as a control group. Due to technical constraints, some of Turney's interested participants could …

Higher Research Productivity = More Pay? Gender Pay-For-Productivity Inequity Across Disciplines, Charissa Samaniego, Peggy Lindner, Maryam A. Kazmi, Bobbie A. Dirr, Dejun Tony Kong, Evonzia Jeff-Eke, Christiane Spitzmueller

Engineering Management and Systems Engineering Faculty Research & Creative Works

Gender pay equity for academics continues to be elusive. Adding to scholarship around structural barriers to gender equity in academic settings, we investigate the link between scholarly performance and compensation. We expect high research productivity to be differentially associated with compensation outcomes for men and women. Building on social role theory, we hypothesize that these relationships are contingent upon whether researchers are inside or outside of Science, Technology, Engineering, and Mathematics (STEM). Using the h-index, compensation, and researcher demographics for 3033 STEM and social and behavioral sciences (SBS) researchers from 17 R1 universities, we applied multilevel modeling techniques and showed …

Improving Social Bot Detection Through Aid And Training, Ryan Kenny, Baruch Fischhoff, Alex Davis, Casey I. Canfield

Engineering Management and Systems Engineering Faculty Research & Creative Works

Objective: We test the effects of three aids on individuals' ability to detect social bots among Twitter personas: a bot indicator score, a training video, and a warning. Background: Detecting social bots can prevent online deception. We use a simulated social media task to evaluate three aids. Method: Lay participants judged whether each of 60 Twitter personas was a human or social bot in a simulated online environment, using agreement between three machine learning algorithms to estimate the probability of each persona being a bot. Experiment 1 compared a control group and two intervention groups, one provided a bot indicator …

Modeling Of A Microstrip Line Referenced To A Meshed Return Plane, Zeyi Sun, Jian Liu, Xiaoyan Xiong, Yuan Liu, Victor Khilkevich, Donghyun Kim, Daryl G. Beetner

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transmission Lines Referenced to Meshed Return Planes Are Widely Used Because of the Physical Flexibility Imparted by the Meshed Plane. Poor Accounting for the Meshed Ground, However, Can Lead to Severe Signal Integrity and Radio Frequency Interference Issues. Full-Wave Simulation Can Characterize the Electrical Performance at an Early Design Stage, But It is Both Time and Computational Resource Consuming. to Make the Simulation More Efficient, a Method is Proposed in This Study to Model Transmission Lines with a Meshed Reference Ground using 2D Analysis. the 2D Analysis is Performed at Several Locations Along the Length of the Trace above the …

A Computational Mapping Of Online News Deserts On African News Websites, Dani Madrid-Morales, Joan Ramon Rodríguez‐Amat, Peggy Lindner

Engineering Management and Systems Engineering Faculty Research & Creative Works

To date, the study of news deserts, geographic spaces lacking local news and information, has largely focused on countries in the Global North, particularly the United States, and has predominantly been interested in the causes and consequences of the disappearance of local media outlets (e.g., newspapers and TV stations) to the social fabric of a community. In this article, we extend the concept of "news deserts" by drawing on literature on the geography of news in Africa, where information voids have long been documented but have not been studied within the conceptual framework of news deserts. Using computational tools, we …

An Effective Transfer Learning Based Landmark Detection Framework For Uav-Based Aerial Imagery Of Urban Landscapes, Bishwas Praveen, Vineetha Menon, Tathagata Mukherjee, Bryan Mesmer, Sampson Gholston, Steven Corns

Engineering Management and Systems Engineering Faculty Research & Creative Works

Aerial imagery captured through airborne sensors mounted on Unmanned Aerial Vehicles (UAVs), aircrafts, satellites, etc. in the form of RGB, LiDAR, multispectral or hyperspectral images provide a unique perspective for a variety of applications. These sensors capture high-resolution images that can be used for applications related to mapping, surveying, and monitoring of crops, infrastructure, and natural resources. Deep learning based algorithms are often the forerunners in facilitating practical solutions for such data-centric applications. Deep learning-based landmark detection is one such application which involves the use of deep learning algorithms to accurately identify and locate landmarks of interest in images captured …

A Genome-Wide Association Study Coupled With Machine Learning Approaches To Identify Influential Demographic And Genomic Factors Underlying Parkinson’S Disease, Md Asad Rahman, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Background: Despite the recent success of genome-wide association studies (GWAS) in identifying 90 independent risk loci for Parkinson's disease (PD), the genomic underpinning of PD is still largely unknown. At the same time, accurate and reliable predictive models utilizing genomic or demographic features are desired in the clinic for predicting the risk of Parkinson's disease. Methods: To identify influential demographic and genomic factors associated with PD and to further develop predictive models, we utilized demographic data, incorporating 200 variables across 33,473 participants, along with genomic data involving 447,089 SNPs across 8,840 samples, both derived from the Fox Insight online study. …

Usdot Tier-1 University Transportation Center For Advancing Cybersecurity Research And Education, Yunpeng Jack Zhang, Kailai Wang, Lingguang Song, Amaury Lendasse, Houbing Herbert Song, Zhu Han, Rakesh Verma, Arlei Silva, Carlos Rubio-Medrano, Zhixia Richard Li, Guohui Zhang

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Transportation Cybersecurity Center for Advanced Research and Education (Cyber-Care) is a Us Department of Transportation (Usdot) Tier-1 University Transportation Center (Utc) Funded in 2023. Cyber-Care Primarily Focuses on the Usdot Statutory Research Priority Area of 'reducing Transportation Cybersecurity Risks.' Cyber-Care Aims to Establish a Fundamental Knowledge Basis and Explore Advanced Theory to Mitigate the Impacts of Large-Scale Cyberattacks on Transportation Infrastructure and Connected and Automated Vehicle (Cav) Systems. the Research Projects at Cyber-Care Will Develop Conceptual Frameworks, Construct Comprehensive Datasets, Explore Novel Analytical Approaches, Support the Implementation of Public Policies and Infrastructure Investments, and Build a High-Quality Industry Workforce …

Deep Reinforcement Learning For Approximate Policy Iteration: Convergence Analysis And A Post-Earthquake Disaster Response Case Study, Abhijit Gosavi, L. (Lesley) H. Sneed, L. A. Spearing

Engineering Management and Systems Engineering Faculty Research & Creative Works

Approximate Policy Iteration (API) is a Class of Reinforcement Learning (RL) Algorithms that Seek to Solve the Long-Run Discounted Reward Markov Decision Process (MDP), Via the Policy Iteration Paradigm, Without Learning the Transition Model in the Underlying Bellman Equation. Unfortunately, These Algorithms Suffer from a Defect Known as Chattering in Which the Solution (Policy) Delivered in Each Iteration of the Algorithm Oscillates between Improved and Worsened Policies, Leading to Sub-Optimal Behavior. Two Causes for This that Have Been Traced to the Crucial Policy Improvement Step Are: (I) the Inaccuracies in the Policy Improvement Function and (Ii) the Exploration/exploitation Tradeoff Integral …

Show-Me Resilience: Assessing And Reconciling Rural Leaders’ Perceptions Of Climate Resilience In Missouri, Zachary J. Miller, Caleb O'Brien, Casey I. Canfield, Lauren Sullivan

Engineering Management and Systems Engineering Faculty Research & Creative Works

Rural areas of the United States play a vital role in coping with, adapting to and mitigating climate change, yet they often lag urban areas in climate planning and action. Rural leaders—e.g., policymakers, state/federal agency professionals, non-profit organization leadership, and scholars – are pivotal for driving the programs and policies that support resilient practices, but our understanding of their perspectives on climate resilience writ large is limited. We conducted semi-structured interviews with 23 rural leaders in Missouri to elucidate their conceptualizations of climate resilience and identify catalysts and constraints for climate adaptation planning and action across rural landscapes. We investigated …

Application Of Modeling Methodologies To Improve An Emergency Departments Workflow, Prachita Humane

Doctoral Dissertations

"The healthcare system in the United States is complex and challenging to understand, and the emergency department (ED) serves as a bridge between outpatient and inpatient care. According to the Centers for Disease Control and Prevention, over 130 million people visited emergency rooms in the United States in 2018. The ED is composed of multiple subunits and components that make it difficult to comprehend fully. In this study, a combination of engineering analysis methods was used to identify and understand the issues in the ED.

The first contribution of this research involved collecting data through job shadowing of human entities …

Sustainable Development: A Data Analysis Investigation For A New Conceptual Model, Case Study Comparison And Validation Techniques, Tiffanie Marie Toles

Doctoral Dissertations

"The three pillars model for sustainability, often represented with three intersecting circles described as economic, environmental, and social factors with sustainability being at the center is a complex and philosophically open model [1]. As society promotes efforts to reduce carbon impacts, there becomes a need to critically review the models employed for understanding. This research presents a validated methodology, an updated conceptual configuration of sustainability for overall use, as well as a sustainable development performance measurement system. Using the 2020 Sustainable Development Goals Index Data, 232 indicators from 193 countries were used to evaluate the efficacy of using more than …

Development Of Flood Prediction Models Using Machine Learning Techniques, Bhanu Kanwar

Doctoral Dissertations

"Flooding and flash flooding events damage infrastructure elements and pose a significant threat to the safety of the people residing in susceptible regions. There are some methods that government authorities rely on to assist in predicting these events in advance to provide warning, but such methodologies have not kept pace with modern machine learning. To leverage these algorithms, new models must be developed to efficiently capture the relationships among the variables that influence these events in a given region. These models can be used by emergency management personnel to develop more robust flood management plans for susceptible areas. The research …

Evaluating Barriers To And Impacts Of Rural Broadband Access, Javier Valentín-Sívico

Doctoral Dissertations

"The lack of adequate broadband infrastructure persists in many rural communities. Beyond funding, additional barriers persist, such as digital literacy and community-level self-efficacy. As a result, the first contribution articulates barriers at the organizational level. This work proposes a framework based on the Theory of Planned Behavior to highlight stakeholder dynamics that have constrained Regional Planning Commissions from advancing broadband infrastructure in rural areas. One approach to address these barriers is to provide stakeholders with analytical tools to evaluate the benefits and costs of various broadband options for their community since there is not a one-size-fits-all solution. To this end, …

Encouraging Voluntary Government Action Via A Solar-Friendly Designation Program To Promote Solar Energy In The United States, Xue Gao, Casey I. Canfield, Tian Tang, Hunter Hill, Morgan Higman, John Cornwell

Engineering Management and Systems Engineering Faculty Research & Creative Works

Sustainable development requires an accelerated transition toward renewable energy. In particular, substantially scaling up solar photovoltaics (PV) adoption is a crucial component of reducing the impacts of climate change and promoting sustainable development. However, it is challenging to convince local governments to take action. This study uses a combination of propensity score matching (PSM) and difference-in-differences (DID) models to assess the effectiveness of a voluntary environmental program (VEP) called SolSmart that targets local governments to engage in solar-friendly practices to promote the local solar PV market in the United States. Via specific designation requirements and technical assistance, SolSmart simplifies the …

A Systems Approach For Solving Inter-Policy Gaps In Dynamic Spectrum Access-Based Wireless Rural Broadband Networks, Pawel Kryszkiewicz, Casey I. Canfield, Shamsnaz Virani Bhada, Alexander M. Wyglinski

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this paper, we articulate the challenge of multiple intersecting policies for the realization of rural broadband networks employing dynamic spectrum access (DSA). Broadband connectivity has been identified as a critical component of economic development, especially during the COVID-19 pandemic, and rural communities have been significantly (and negatively) affected by the lack of this important resource. Although technologies exist that can deliver broadband connectivity, such as 4G LTE and 5G cellular networks, the challenges associated with efficiently deploying this infrastructure within a rural environment are multi-dimensional in terms of the different dependent policy decisions that need to be considered. To …

Resource Availability And Implications For The Development Of Plug‐In Electric Vehicles, Ona Egbue, Suzanna Long, Seong Dae Kim

Engineering Management and Systems Engineering Faculty Research & Creative Works

Plug‐in electric vehicles (PEVs) have immense potential for reducing greenhouse gas emissions and dependence on fossil fuels, and for smart grid applications. Although a great deal of research is focused on technological limitations that affect PEV battery performance targets, a major and arguably equal concern is the constraint imposed by the finite availability of elements or resources used in the manufacture of PEV batteries. Availability of resources, such as lithium, for batteries is critical to the future of PEVs and is, therefore, a topic that needs attention. This study addresses the issues related to lithium availability and sustainability, particularly supply …

A Variable Node Optimization Model For Byzantine Fault Tolerant Systems, Ian Robert Fulton

Masters Theses

“Byzantine Fault Tolerance (BFT) has been a major subject of study over the last two decades with increasing societal dependance on secure, correct, and reliable computer systems and online services. This research presents a model for high-level optimization of emerging systems that rely on these BFT algorithms and use a variable numbers of decision nodes. The model highlights the relationship between the security of a system and its efficiency. Two experiments were performed to determine system performance by varying the number of compromised nodes, decision nodes, and total nodes. They examine the probability that a transaction will be compromised based …

State Level Trends In Renewable Energy Procurement Via Solar Installation Versus Green Electricity, Eric Michael Hanson

Masters Theses

“In the past 5 years, consumer options for procuring renewable energy have increased, ranging from rooftop solar installation to utility green pricing to Community Choice Aggregation. These options vary in terms of costs and benefits to the consumer as well as grid integration implications. However, little is known regarding how the presence of a wide range of options for utility-scale renewable procurement affects demand for distributed residential solar installations. In theory, there are three possible relationships, (1) positive correlation, where utility-scale and distributed resources complement each other to increase overall production, (2) negative correlation, where utility-scale and distributed resources are …

Advances And Applications In High-Dimensional Heuristic Optimization, Samuel Alexander Vanfossan

Doctoral Dissertations

“Applicable to most real-world decision scenarios, multiobjective optimization is an area of multicriteria decision-making that seeks to simultaneously optimize two or more conflicting objectives. In contrast to single-objective scenarios, nontrivial multiobjective optimization problems are characterized by a set of Pareto optimal solutions wherein no solution unanimously optimizes all objectives. Evolutionary algorithms have emerged as a standard approach to determine a set of these Pareto optimal solutions, from which a decision-maker can select a vetted alternative. While easy to implement and having demonstrated great efficacy, these evolutionary approaches have been criticized for their runtime complexity when dealing with many alternatives or …

Reducing Kidney Discard With Artificial Intelligence Decision Support: The Need For A Transdisciplinary Systems Approach, Richard Threlkeld, Lirim Ashiku, Casey I. Canfield, Daniel Burton Shank, Mark A. Schnitzler, Krista L. Lentine, David A. Axelrod, Anil Choudary Reddy Battineni, Henry Randall, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Purpose of Review: A transdisciplinary systems approach to the design of an artificial intelligence (AI) decision support system can more effectively address the limitations of AI systems. By incorporating stakeholder input early in the process, the final product is more likely to improve decision-making and effectively reduce kidney discard.

Recent Findings: Kidney discard is a complex problem that will require increased coordination between transplant stakeholders. An AI decision support system has significant potential, but there are challenges associated with overfitting, poor explainability, and inadequate trust. A transdisciplinary approach provides a holistic perspective that incorporates expertise from engineering, social science, and …