Operations Research, Systems Engineering and Industrial Engineering Commons^™

Co-Designing Ai Tools To Reduce Kidney Discard, Casey Hines

Undergraduate Research Conference at Missouri S&T

Currently, there are about 94,000 people on the kidney transplant waiting list. Less than one-third will receive a new kidney this year. Unfortunately, some kidneys that could have been transplanted into a new recipient, end up being discarded. The largest group of discarded kidneys are ones that are high-risk. At present, an organ procurement organization will send out offers for an available kidney to transplant centers. These offers go out in chronological order following the kidney transplant waiting list. A single high-risk kidney could potentially go through hundreds of offers before being accepted by a transplant center. The longer the …

Behavioral Science Can Increase Zipper Merge Usage, Maria Galbraith

Undergraduate Research Conference at Missouri S&T

Research demonstrates that zipper merges (or late merges), under heavy traffic conditions, are safer and faster than a traditional early merge. In implementation, zipper merges can be less efficient due to a lack of compliance on the part of drivers, often more accustomed to early merging. Behavioral science has been applied to a many transportation-related challenges, such as increasing seat belt usage and decreasing drinking and driving but has not yet been applied to the zipper merge. We have identified six relevant behavioral science strategies including (1) social norms, (2) appeals to reason, (3) emotional appeals, (4) humor, (5) memory …

The Implementation Of Energy Sharing Using A System Of Systems Approach, Julia Morgan

Doctoral Dissertations

"There is an increasing demand for renewable energy and consumers need more procurement options to meet their needs. Energy sharing provides a peer-to-peer (P2P) marketplace where prosumer electricity is redistributed to fellow energy-sharing community participants. This redistribution of prosumer electricity provides consumers with additional electricity suppliers, while also decreasing the load on the utility company. Though significant progress has been made regarding research and implementation of energy sharing, there is still room for growth when evaluating energy-sharing communities and defining appropriate community coordination based on end-user needs. The first contribution in this work identified nine characteristics of energy-sharing communities as …

The Role Of Psychological Reactance In Smart Home Energy Management Systems, Matthew Thomas Heatherly

Masters Theses

“With an ever-growing demand for energy, our increasing consumption is producing more greenhouse gases and other pollutants, impacting climate change. One approach to reducing residential energy consumption is through the use of smart energy management systems. However, automation from smart technology inherently removes a certain amount of control from the user. If loss of control is perceived as a loss of freedom, this may lead users to experience psychological reactance when using these products. A set of experiments was conducted to assess how three features of a message notification from smart home energy management systems may induce reactance in users. …

The Effects Of Rigid Polyurethane Foam As A Confinement Material On Breaching Charge Detonations, Nathan Franz Paerschke-O'Brien

Masters Theses

"The effects of a rigid polyurethane foam used as a confinement material on four types of breaching explosives were tested, focusing on the changes in shockwave peak pressures, detonation load compression forces, and brisance cratering abilities. The Plate Dent testing procedure was modified to incorporate a load cell force sensor, and two air overpressure sensors were included adjacent to the blast to quantify each test result. The testing variables focused on the polyurethane foam cure times and thickness volumes around the breaching explosives to determine the breaching charges' optimal energy output capabilities when confined by the foam material. The rigid …

A Fuzzy Clustering Methodology To Analyze Interfaces And Assess Integration Risks In Large-Scale Systems, Josh Henry Goldschmid

Doctoral Dissertations

“Interface analysis and integration risk assessment for a large-scale, complex system is a difficult systems engineering task, but critical to the success of engineering systems with extraordinary capabilities. When dealing with large-scale systems there is little time for data gathering and often the analysis can be overwhelmed by unknowns and sometimes important factors are not measurable because of the complexities of the interconnections within the system. This research examines the significance of interface analysis and management, identifies weaknesses in literature on risk assessment for a complex system, and exploits the benefits of soft computing approaches in the interface analysis in …

Sensor Data Based Adaptive Models For Assembly Worker Training In Cyber Manufacturing, Md. Al-Amin

Doctoral Dissertations

“Production innovations are occurring faster than ever leading conventional production systems towards cyber manufacturing. Manufacturing workers thus need to frequently learn new methods and skills. In fast-changing, largely uncertain production systems, manufacturers with the ability to comprehend workers’ behavior and assess their operational performance in near real-time will achieve better performance than peers. Recognizing worker actions in near real-time while performing the assembly can serve this purpose. However, reliably recognizing the assembly actions performed by the workers is challenging, because the actions for assembly are complex and workers are not only heterogeneous but sensitive to the variation of the work …

Infrastructure Systems Modeling Using Data Visualization And Trend Extraction, Jacob Marshal Hale

Doctoral Dissertations

“Current infrastructure systems modeling literature lacks frameworks that integrate data visualization and trend extraction needed for complex systems decision making and planning. Critical infrastructures such as transportation and energy systems contain interdependencies that cannot be properly characterized without considering data visualization and trend extraction.

This dissertation presents two case analyses to showcase the effectiveness and improvements that can be made using these techniques. Case one examines flood management and mitigation of disruption impacts using geospatial characteristics as part of data visualization. Case two incorporates trend analysis and sustainability assessment into energy portfolio transitions.

Four distinct contributions are made in this …

Establishing Links Between Safety Culture, Climate, Behaviors, And Outcomes Of Long-Haul Truck Drivers, Carlton Washburn

Doctoral Dissertations

“This research examines the safety relationships between safety culture, safety influences, safety climate, and safety outcomes for long-haul truck drivers. The relationships focus on the intersection of the electronic logging device (ELD) technology, regulations, and truck drivers that fall into the lone-worker category. Truck drivers were interviewed to understand their beliefs, attitudes, practices, values, and behavior patterns aligned with the phase in of the ELD system. Large truck crashes during the same time period were analyzed to understand associations. Outcomes included both a safety culture and climate were established for long-haul truck drivers. Both positive and negative safety behaviors were …

Agent-Based Model Of Broadband Adoption In Unserved And Underserved Areas, Ankit Agarwal

Masters Theses

"In the last two decades, demand for broadband internet has far outpaced its availability. The Federal Communications Commission’s (FCC) 2020 Broadband Deployment report suggests that at least 22 million Americans living in rural areas lack access to broadband internet. With the COVID-19 pandemic affecting normal life, there is an overwhelming need to enable unserved and underserved communities to adapt to the “new normal”. To address this challenge, federal and state agencies are funding internet service providers (ISPs) to deploy infrastructure in rural communities. However, policymakers and ISPs need open-source tools to predict take-rates of broadband service and formulate effective strategies …

A Time Series Sustainability Assessment Of A Partial Energy Portfolio Transition, Jacob Hale, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

Energy portfolios are overwhelmingly dependent on fossil fuel resources that perpetuate the consequences associated with climate change. Therefore, it is imperative to transition to more renewable alternatives to limit further harm to the environment. This study presents a univariate time series prediction model that evaluates sustainability outcomes of partial energy transitions. Future electricity generation at the state-level is predicted using exponential smoothing and autoregressive integrated moving average (ARIMA). The best prediction results are then used as an input for a sustainability assessment of a proposed transition by calculating carbon, water, land, and cost footprints. Missouri, USA was selected as a …

Rural Access To Industry 4.0: Barriers From The Infrastructure Planning Front Lines, Javier Valentin-Sivico, Casey I. Canfield, Ona Egbue

Engineering Management and Systems Engineering Faculty Research & Creative Works

Many rural communities lack adequate broadband infrastructure, which limits the economic development potential in these regions. They are not able to attract new businesses, and established businesses are unable to use tools and services that require high-speed internet. Broadband access is a requirement for the Internet of Things, robotics, and big data, which are part of Industry 4.0 and the future economy. Such technological advances are not only transforming the manufacturing environments and the service industry, but also finding applications in the food supply chain, such as precision agriculture. In this study, we conducted 17 semi-structured interviews (11 reported here) …

A Markov Chain Approach For Forecasting Progression Of Opioid Addiction, Abhijit Gosavi, Susan L. Murray, N. Karagiannis

Engineering Management and Systems Engineering Faculty Research & Creative Works

The U.S. is currently facing an opioid crisis. Naltrexone is a common treatment for drug addiction; it reduces the desire to take opiates. However, addicts often stop treatment or continue to use opioids while in treatment. This results in increased fatalities and associated costs. A Markov-chain model is presented to analyze the progression of opioid addiction to assist the medical community in developing appropriate treatments. The model includes patients who continue opiate use while on naltrexone (blocked patients) and those who use opiates after missing naltrexone doses (unblocked patients). The other types of patients are abstinent (the best-case scenario) and …

Communicating Uncertain Information From Deep Learning Models In Human Machine Teams, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank, Luke Andrews, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The role of human-machine teams in society is increasing, as big data and computing power explode. One popular approach to AI is deep learning, which is useful for classification, feature identification, and predictive modeling. However, deep learning models often suffer from inadequate transparency and poor explainability. One aspect of human systems integration is the design of interfaces that support human decision-making. AI models have multiple types of uncertainty embedded, which may be difficult for users to understand. Humans that use these tools need to understand how much they should trust the AI. This study evaluates one simple approach for communicating …

The Application Of Fuzzy Analytic Hierarchy Process In Sustainable Project Selection, Rakan Alyamani, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

The project selection process is a crucial step in sustainable development. Effective sustainable development depends on the ability to select the appropriate sustainable project to implement to ensure that the desired goals are met. Some of the most common characteristics or criteria used in evaluating sustainable projects include novelty, uncertainty, skill and experience, technology information transfer, and project cost. Prioritizing these criteria based on relative importance helps project managers and decision makers identify elements that require additional attention, better allocate resources, as well as improve the selection process when evaluating different sustainable project alternatives. The aim of this research is …

Transceivers As A Resource: Scheduling Time And Bandwidth In Software-Defined Radio, Nathan D. Price, Maciej Jan Zawodniok, Ivan G. Guardiola

Electrical and Computer Engineering Faculty Research & Creative Works

In the future, software-defined radio may enable a mobile device to support multiple wireless protocols implemented as software applications. These applications, often referred to as waveform applications, could be added, updated, or removed from a software-radio device to meet changing demands. Current software-defined radio solutions grant an active waveform exclusive ownership of a specific transceiver or analog front-end. Since a wireless device has a limited number of front-ends, this approach puts a hard constraint on the number of concurrent waveform applications a device can support. A growing trend in software-defined radio research is to virtualize front-ends to allow sharing and …

A Model To Estimate The Lifetime Of Bess For The Prosumer Community Of Manufacturers With Ogs, Md Monirul Islam, Cihan H. Dagli, Zeyi Sun

Engineering Management and Systems Engineering Faculty Research & Creative Works

Onsite generation system (OGS) with renewable sources for modern manufacturing plant is considered as a critical alternative energy source for the manufacturers. Prosumer community can be formed by aggregating such manufacturers to achieve a mutual goal of sustainable and resilient power system. As the sustainability of the network depends on the reliable operations of each component in the network, it is required to monitor the performance and lifetime of the components existed in the network. One of the critical as well as costly components used to enhance the reliability and performance of the network is the battery energy storage system …

A System-Of-Systems Model To Simulate The Complex Emergent Behavior Of Vehicle Traffic On An Urban Transportation Infrastructure Network, Rayan Assaad, Cihan H. Dagli, Islam H. El-Adaway

Engineering Management and Systems Engineering Faculty Research & Creative Works

Transportation agencies face escalating challenges in forecasting the traffic demand. Traditional prediction methods focused on individual transportation sectors and failed to study the inter-dependencies between the different transportation systems. Hence, there is a need for more advanced and holistic modeling techniques. To this end, this paper models and analyses an urban transportation system-of-systems incorporating seven various systems: population and GDP, CO₂ emission, gasoline price and total vehicle trips, traffic demand, public and private transportation, transportation investment, and traffic congestion. Accordingly, this research simulates transportation networks as a collection of task-oriented systems that combine their resources to form a complex …

Agent Based Modeling For Flood Inundation Mapping And Rerouting, Vinayaka Gude, Steven Corns, Cihan H. Dagli, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

Natural disasters like earthquakes and floods can have a serious impact on road networks, which are critical to supply chain infrastructure and to provide connectivity. These extreme events can result in isolating people in the affected area from hospitals and emergency response. This paper presents an agent-based model for understanding flood propagation and developing inundation mapping. The results from the mapping are used to identify the roads prone to floods based on elevation data and flood simulation. A simulation environment was set up in SUMO, and the costs associated with the traffic disruption are evaluated. This paper discusses the integration …

An Agent-Based Approach To Artificial Stock Market Modeling, Samuel Vanfossan, Cihan H. Dagli, Benjamin J. Kwasa

Engineering Management and Systems Engineering Faculty Research & Creative Works

Consumer stock markets have long been a target of modeling efforts for the economic gains anticipatorily enabled by well-performing models. Aimed at identifying strategies capable of achieving desired returns, many modeling approaches have attempted to capture the innumerable and intricate complexities present within these adaptive socio-technical systems. Decreasingly constrained by available computation power, contemporary models have grown in sophistication to include several of the features present in de facto market systems. However, these models require extensive effort to dictate the variety of states, behaviors, and adaptations that entities of the system may exhibit. Mandating the development of complex formulas and …

An Agent-Based Model To Study Competitive Construction Bidding And The Winner's Curse, Amr Elsayegh, Cihan H. Dagli, Islam H. El-Adaway

Engineering Management and Systems Engineering Faculty Research & Creative Works

Reverse auction theory is the basis for competitive construction bidding process. The lowest bid method is utilized for selecting contractors in public projects. The winning contractor having the lowest bid value could be cursed when the submitted bid value results in negative profits. This is caused by many factors such as the contractor's estimation accuracy and markup. This is addressed in this paper by providing a model simulating the construction competitive bidding and the occurrence of the winner's curse. To this end, the authors show the extent to which the winner's curse affects the status of contracting companies. The objectives …

Efficient Architecture Search For Deep Neural Networks, Ram Deepak Gottapu, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper addresses the scalability challenge of automatic deep neural architecture search by implementing a parameter sharing approach with regularized genetic algorithm (RGE). The key idea is to use a regularized genetic algorithm (RGE) on a pre-determined template and discover a high-performance architecture by searching for the optimal chromosome. During evolution, each model corresponding to a discovered chromosome is trained for a fixed number of epochs to minimize a canonical cross-entropy loss on a given training dataset. Meanwhile, the performance of the trained model on validation dataset is used as a fitness value to perform the evolutions. Because of parameter …

Modeling And Simulation Of A Robotic Bridge Inspection System, Md Monirul Karim, Cihan H. Dagli, Ruwen Qin

Engineering Management and Systems Engineering Faculty Research & Creative Works

Inspection and preservation of the aging bridges to extend their service life has been recognized as one of the important tasks of the State Departments of Transportation. Yet manual inspection procedure is not efficient to determine the safety status of the bridges in order to facilitate the implementation of appropriate maintenance. In this paper, a complex model involving a remotely controlled robotic platform is proposed to inspect the safety status of the bridges which will eliminate labor-intensive inspection. Mobile cameras from unmanned airborne vehicles (UAV) are used to collect bridge inspection data in order to record the periodic changes of …

Preface To The Special Issue: "Complex Adaptive Systems," Malvern, Pennsylvania, November 13-15, 2019, Nil Kilicay-Ergin, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

No abstract provided.

A System Dynamics Approach For Study Of Population Growth And The Residential Housing Market In The Us, Gasser Galal Ali, Islam H. El-Adaway, Cihan H. Dagli

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The US Consensus bureau estimated the total construction spending at 1,320,305 Million Dollars, in February 2020, with an increase of 1.1% since last February. The construction market is large, and risky. Prediction of the market behavior, for several years ahead, is needed in order to take strategic investment decision for long and expensive projects. The goal of this research is to study the relationship between population growth and the housing market. To that end, a system dynamics model is developed. System dynamics is a top-down approach that starts with the high-level behavior of a complex system to simulate the behavior …

A System Dynamics Model For Construction Safety Behavior, Mohamad Abdul Nabi, Islam H. El-Adaway, Cihan H. Dagli

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Construction Industry has always been reputed by its high incident rates and poor safety performance. Construction accidents are, in most cases, resulted from the unsafe behaviors of construction workers on site. The study of workers' behavior is crucial in order to understand the causation of unsafe behaviors. Therefore, the objective of this paper is to simulate construction safety behavior in order to predict the number of safety incidents and better understand their causation factors. The simulation model illustrates how construction system influences construction labors on site in terms of unsafe behavior. The standard leading indicators of safety performance are first …

Exploring The Relationship Between Sustainable Projects And Institutional Isomorphisms: A Project Typology, Rakan Alyamani, Suzanna Long, Mohammad Nurunnabi

Engineering Management and Systems Engineering Faculty Research & Creative Works

With the increase in awareness about the wide range of issues and adverse effects associated with the use of conventional energy sources came an increase in project management research related to sustainability and sustainable development. Part of that research is devoted to the development of sustainable project typologies that classify projects based on a variety of external factors that can significantly impact these projects. This research focuses on developing a sustainable project typology that classifies sustainable projects based on the external institutional influences. The typology explores the influence of the coercive, normative, and mimetic institutional isomorphisms on the expected level …

Flood Prediction And Uncertainty Estimation Using Deep Learning, Vinayaka Gude, Steven Corns, Suzanna Long

Engineering Management and Systems Engineering Faculty Research & Creative Works

Floods are a complex phenomenon that are difficult to predict because of their non-linear and dynamic nature. Therefore, flood prediction has been a key research topic in the field of hydrology. Various researchers have approached this problem using different techniques ranging from physical models to image processing, but the accuracy and time steps are not sufficient for all applications. This study explores deep learning techniques for predicting gauge height and evaluating the associated uncertainty. Gauge height data for the Meramec River in Valley Park, Missouri was used to develop and validate the model. It was found that the deep learning …

Predicting Complex System Behavior Using Hybrid Modeling And Computational Intelligence, Vinayaka Gude

Doctoral Dissertations

“Modeling and prediction of complex systems is a challenging problem due to the sub-system interactions and dependencies. This research examines combining various computational intelligence algorithms and modeling techniques to provide insights into these complex processes and allow for better decision making. This hybrid methodology provided additional capabilities to analyze and predict the overall system behavior where a single model cannot be used to understand the complex problem. The systems analyzed here are flooding events and fetal health care. The impact of floods on road infrastructure is investigated using graph theory, agent-based traffic simulation, and Long Short-Term Memory deep learning to …

Real-Time Assembly Operation Recognition With Fog Computing And Transfer Learning For Human-Centered Intelligent Manufacturing, Wenjin Tao, Md Al-Amin, Haodong Chen, Ming-Chuan Leu, Zhaozheng Yin, Ruwen Qin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In a human-centered intelligent manufacturing system, every element is to assist the operator in achieving the optimal operational performance. The primary task of developing such a human-centered system is to accurately understand human behavior. In this paper, we propose a fog computing framework for assembly operation recognition, which brings computing power close to the data source in order to achieve real-time recognition. For data collection, the operator's activity is captured using visual cameras from different perspectives. For operation recognition, instead of directly building and training a deep learning model from scratch, which needs a huge amount of data, transfer learning …