Operations Research, Systems Engineering and Industrial Engineering Commons^™

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 …

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 …

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 …

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 …

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 …

Quantifying Time-Frequency Co-Movement Impact Of Covid-19 On U.S. And China Stock Market Toward Investor Sentiment Index, Rui Nian, Yijin Xu, Qiang Yuan, Chen Feng, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Worldwide Spread of Covid-19 Dramatically Influences the World Economic Landscape. in This Paper, We Have Quantitatively Investigated the Time-Frequency Co-Movement Impact of Covid-19 on U.S. and China Stock Market Since Early 2020 in Terms of Daily Observation from National Association of Securities Dealers Automated Quotations Index (Ndx), Dow Jones Industrial Average (Djia), Standard & Poor's 500 Index (Spx), Shanghai Securities Composite Index (Ssec), Shenzhen Securities Component Index (Szi), in Favor of Spatiotemporal Interactions over Investor Sentiment Index, and Propose to Explore the Divisibility and the Predictability to the Volatility of Stock Market during the Development of Covid-19. We Integrate …

Evaluating Decision Making In Sustainable Project Selection Between Literature And Practice, Rakan Alyamani, Suzanna Long, Mohammad Nurunnabi

Engineering Management and Systems Engineering Faculty Research & Creative Works

A robust project selection process is critical for the selection of sustainable projects that meet the needs of an organization or community. There are multiple factors or criteria that can be considered in the selection of the appropriate sustainable project, but it can be challenging to find sufficient depth of expert opinion to perform a strong evaluation of these criteria. Several researchers have turned to the sustainable project literature as a source of expert opinion to evaluate the criteria used in sustainable project selection and rank them based on importance using different multi-criteria decision-making (MCDM) methodologies. However, using the literature …

Comparing Behavioral Theories To Predict Consumer Interest To Participate In Energy Sharing, Julia Morgan, Casey I. Canfield

Engineering Management and Systems Engineering Faculty Research & Creative Works

Consumer investment in distributed energy resources (DERs) is increasing the penetration of renewable energy in the grid. In some cases, DERs produce more electricity than needed by the owner and this excess electricity is sold to the utility (e.g., net metering). In contrast, energy sharing allows a facilitator, which may or may not be the utility, to redistribute excess renewable electricity to fellow community members directly. However, little is known about consumer interest in participating in this type of arrangement. This preregistered study uses structural equation modeling to compare two behavioral theories, Value-Belief-Norm and Diffusion of Innovation, to predict consumer …

Handwriting Features Based Detection Of Fake Signatures, Anton Akusok, Leonardo Espinosa Leal, Kaj Mikael Bjxc3xb6rk, Amaury Lendasse, Renjie Hu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Detection of Fake Signatures is a Hard Task. in This Paper, We Present a Novel Method for Detecting Trained Forgeries using Features Extracted from Sliding Windows with Different overlaps on a Publicly Available Dataset of Static Images of Signatures. using a Linear Machine Learning Model Named Extreme Learning Machine (Elm), Our Methodology Achieves, in Average, an Equal Error Rates (Eer) of 2.31% for an overlap of 90%. in Line with the State-Of-The-Art Results Available in the Scientific Literature.

Network Intrusion Detection System Using Deep Learning, Lirim Ashiku, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The widespread use of interconnectivity and interoperability of computing systems have become an indispensable necessity to enhance our daily activities. Simultaneously, it opens a path to exploitable vulnerabilities that go well beyond human control capability. The vulnerabilities deem cyber-security mechanisms essential to assume communication exchange. Secure communication requires security measures to combat the threats and needs advancements to security measures that counter evolving security threats. This paper proposes the use of deep learning architectures to develop an adaptive and resilient network intrusion detection system (IDS) to detect and classify network attacks. The emphasis is how deep learning or deep neural …

Single-Image Super Resolution Using Convolutional Neural Network, William Symolon, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

Increasing threats to U.S. national security satellite constellations have resulted in an increased interest in constellation resilience and satellite redundancy. CubeSats have contributed to commercial, scientific and government applications in remote sensing, communications, navigation and research and have the potential to enhance satellite constellation resilience. However, the inherent size, weight and power limitations of CubeSats enforce constraints on imaging hardware; the small lenses and short focal lengths result in imagery with low spatial resolution. Low resolution limits the utility of CubeSat images for military planning purposes and national intelligence applications. This paper implements a super-resolution deep learning architecture and proposes …

Sos Explorer Application With Fuzzy-Genetic Algorithms To Assess An Enterprise Architecture -- A Healthcare Case Study, Josh Goldschmid, Vinayaka Gude, Steven Corns

Engineering Management and Systems Engineering Faculty Research & Creative Works

Kevin Dooley (1997), defined Complex Adaptive System (CAS) as a group of semi-autonomous agents who interact in interdependent ways to produce system-wide patterns, such that those patterns then influence behavior of the agents. A healthcare system is considered as a Complex Adaptive System of system (SoS) with agents composed of strategies, people, process, and technology. Healthcare systems are fragmented with independent systems and information. The enterprise architecture (EA) aims to address these fragmentations by creating boundaries around the business strategy and key performance attributes that drive integration across multiple systems of processes, people, and technology. This paper uses a SoS …

The Identification And Prediction In Abundance Variation Of Atlantic Cod Via Long Short-Term Memory With Periodicity, Time–Frequency Co-Movement, And Lead-Lag Effect Across Sea Surface Temperature, Sea Surface Salinity, Catches, And Prey Biomass From 1919 To 2016, Rui Nian, Qiang Yuan, Hui He, Xue Geng, Chi Wei Su, Bo He, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

The Population of Atlantic Cod Significantly Contributes to the Prosperity of Fishery Production in the World. in This Paper, We Quantitatively Investigate the Global Abundance Variation in Atlantic Cod from 1919 to 2016, in Favor of Spatiotemporal Interactions over Manifold Impact Factors at Local Observation Sites and Propose to Explore the Predictive Mechanism with the Help of its Periodicity, Time–frequency Co-Movement, and Lead-Lag Effects, Via Long Short-Term Memory (Lstm). We First Integrate Evidence Yielded from Wavelet Coefficients, to Suggest that the Abundance Variation Potentially Follows a 36-Year Major Cycle and 24-Year Secondary Cycle at the Time Scales of 55 Years …

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 …

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 …

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 …

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 …

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. …

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 …

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 …

Nnbmss: A Novel And Fast Method For Model Structure Selection, Amaury Lendasse, Kallin Khan, Edward Ratner

Engineering Management and Systems Engineering Faculty Research & Creative Works

In This Paper, We Present a New Method to Perform Model Structure Selection. This Proposed Method Can Be Used to Select the Complexity of Any Continuous Regression Method. We Also Present an Asymptotic Mathematical Proof of the Proposed Method and the New Method is Illustrated on a Benchmark. Compared to the Well-Known 10-Fold Cross-Validation, the Computational Time Associated to Our New Method is Approximately Divided by a Factor 8 as Illustrated on the Benchmark.

Machine Learning For Measuring And Analyzing Online Social Communications, Chris Bronk, Amaury Lendasse, Peggy Lindner, Dan S. Wallach, Barbara Hammer

Engineering Management and Systems Engineering Faculty Research & Creative Works

In This Paper, We Propose a Framework for Application of a Novel Machine Learning-Based System for Analyzing Online Social Communications. as an Example, We Are Targeting Anti-Semitic Graphical Memes Posted to Social Media. We Presented Very Promising Preliminary Results on a Facebook Dataset that Consists of a Total of 10000 Labeled Memes. We Can Conclude that Machine Learning Will Soon Be Able to Successfully Analyze and Monitor Complex Social Communications.

A Multi-Elm Model For Incomplete Data, Baichuan Chi, Amaury Lendasse, Edward Ratner, Renjie Hu

Engineering Management and Systems Engineering Faculty Research & Creative Works

This Paper Presents a Novel Model of Extreme Learning Machines (Elms) for Incomplete Data. Elms Are Fast Accurate Randomized Neural Networks. Nevertheless, Elm Can Only Be Applied on the Complete Dataset. Therefore, a Novel Multi-Elm Model for Incomplete Data is Proposed, Consisting of Multiple Secondary Elms and One Primary Elm. the Secondary Elms Are Approximating the Primary Elm's Hidden Neurons' Outputs for the Data with Missing Values. as Summarized in the Experimental Section, This Model Can Be Applied on Data with Any Missing Patterns, without using Imputations and Can Outperform the Traditional Imputation Methods within a Reasonable Fraction of Missing …

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 …

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 …