Digital Commons Network^™

Designing Explainable Ai To Improve Human-Ai Team Performance: A Medical Stakeholder-Driven Scoping Review, Harishankar V. Subramanian, Casey I. Canfield, Daniel Burton Shank

Engineering Management and Systems Engineering Faculty Research & Creative Works

The rise of complex AI systems in healthcare and other sectors has led to a growing area of research called Explainable AI (XAI) designed to increase transparency. In this area, quantitative and qualitative studies focus on improving user trust and task performance by providing system- and prediction-level XAI features. We analyze stakeholder engagement events (interviews and workshops) on the use of AI for kidney transplantation. From this we identify themes which we use to frame a scoping literature review on current XAI features. The stakeholder engagement process lasted over nine months covering three stakeholder group's workflows, determining where AI 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 …

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 …

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. …

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 …

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 …

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 …

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 Novel Bayesian Framework Infers Driver Activation States And Reveals Pathway-Oriented Molecular Subtypes In Head And Neck Cancer, Zhengping Liu, Chunhui Cai, Xiaojun Ma, Jinling Liu, Lujia Chen, Vivian Wai Yan Lui, Gregory F. Cooper, Xinghua Lu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Head and neck squamous cell cancer (HNSCC) is an aggressive cancer resulting from heterogeneous causes. To reveal the underlying drivers and signaling mechanisms of different HNSCC tumors, we developed a novel Bayesian framework to identify drivers of individual tumors and infer the states of driver proteins in cellular signaling system in HNSCC tumors. First, we systematically identify causal relationships between somatic genome alterations (SGAs) and differentially expressed genes (DEGs) for each TCGA HNSCC tumor using the tumor-specific causal inference (TCI) model. Then, we generalize the most statistically significant driver SGAs and their regulated DEGs in TCGA HNSCC cohort. Finally, we …

Push Them Forward: Challenges In Intergovernmental Organizations' Influence On Rural Broadband Infrastructure Expansion, Javier Valentín-Sívico, Casey I. Canfield, Ona Egbue

Engineering Management and Systems Engineering Faculty Research & Creative Works

Many rural US communities lack access to adequate broadband services. This paper draws on semi-structured interviews conducted in 2019 with 16 Regional Planning Commissions to uncover dynamics of how these intergovernmental organizations contribute to the deployment of broadband infrastructure in rural Missouri. The proposed framework integrates the decomposed Theory of Planned Behavior (TPB), the Theory of Reasoned Goal Pursuit, and Stakeholder Theory. Many participants reported a low level of involvement in broadband infrastructure initiatives even though supporting infrastructure development to promote economic growth is one of the Regional Planning Commissions' primary goals. Regional Planning Commissions are highly influenced by four …

Robust And Accurate Estimation Of Cellular Fraction From Tissue Omics Data Via Ensemble Deconvolution, Manqi Cai, Molin Yue, Tianmeng Chen, Jinling Liu, Erick Forno, Xinghua Lu, Timothy Billiar, Juan Celedón, Chris Mckennan, Wei Chen, Jiebiao Wang

Engineering Management and Systems Engineering Faculty Research & Creative Works

Motivation: Tissue-level omics data such as transcriptomics and epigenomics are an average across diverse cell types. To extract cell-type-specific (CTS) signals, dozens of cellular deconvolution methods have been proposed to infer cell-type fractions from tissue-level data. However, these methods produce vastly different results under various real data settings. Simulation-based benchmarking studies showed no universally best deconvolution approaches. There have been attempts of ensemble methods, but they only aggregate multiple single-cell references or reference-free deconvolution methods. Results: To achieve a robust estimation of cellular fractions, we proposed EnsDeconv (Ensemble Deconvolution), which adopts CTS robust regression to synthesize the results from 11 …

Techno-Economic Feasibility Analysis Of A Fully Mobile Radiation Oncology System Using Monte Carlo Simulation, Alex T. Price, Casey I. Canfield, Geoffrey D. Hugo, James A. Kavanaugh, Lauren E. Henke, Eric Laugeman, Pamela Samson, Clair Reynolds-Kueny, Elizabeth A. Cudney

Engineering Management and Systems Engineering Faculty Research & Creative Works

PURPOSEDisparities in radiation oncology (RO) can be attributed to geographic location, socioeconomic status, race, sex, and other societal factors. One potential solution is to implement a fully mobile (FM) RO system to bring radiotherapy to rural areas and reduce barriers to access. We use Monte Carlo simulation to quantify techno-economic feasibility with uncertainty, using two rural Missouri scenarios.METHODSRecently, a semimobile RO system has been developed by building an o-ring linear accelerator (linac) into a mobile coach that is used for temporary care, months at a time. Transitioning to a more FM-RO system, which changes location within a given day, presents …

Techno-Economic Feasibility Analysis Of A Fully Mobile Radiation Oncology System Using Monte Carlo Simulation, Alex T. Price, Casey I. Canfield, Geoffrey D. Hugo, James A. Kavanaugh, Lauren E. Henke, Eric Laugeman, Pamela Samson, Clair Reynolds-Kueny, Elizabeth A. Cudney

Engineering Management and Systems Engineering Faculty Research & Creative Works

PURPOSE Disparities in radiation oncology (RO) can be attributed to geographic location, socioeconomic status, race, sex, and other societal factors. One potential solution is to implement a fully mobile (FM) RO system to bring radiotherapy to rural areas and reduce barriers to access. We use Monte Carlo simulation to quantify techno-economic feasibility with uncertainty, using two rural Missouri scenarios. METHODS Recently, a semimobile RO system has been developed by building an o-ring linear accelerator (linac) into a mobile coach that is used for temporary care, months at a time. Transitioning to a more FM-RO system, which changes location within a …

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 …

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 …

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 …

Maintenance Optimization In A Digital Twin For Industry 4.0, Abhijit Gosavi, Vy Khoi Le

Engineering Management and Systems Engineering Faculty Research & Creative Works

The advent of Internet of Things and artificial intelligence in the era of Industry 4.0 has transformed decision-making within production systems. In particular, many decisions that previously required significant human activity are now made automatically with minimal human intervention via so-called digital twins (DTs). In the context of maintenance and reliability modeling, this naturally calls for new paradigms that can be seamlessly integrated within DTs for decision-making. The input data for time to failure needed in reliability computations are directly collected from the work center in a digital setting and often do not satisfy a known distribution. A neural network …

Monte Carlo Particle Simulation Of Avalanche Breakdown In A Reverse Biased Diode With Full Band Structure, Zeyi Sun, Manish Kizhakkeveettil Mathew, Ryan From, Donghyun Kim

Engineering Management and Systems Engineering Faculty Research & Creative Works

To model the avalanche breakdown of a voltage regulator diode under reverse bias, a computationally rigorous device physics model using the Monte Carlo method to solve charge carrier Boltzmann transport equations (BTEs) is proposed. The transport of energetic charge carriers is calculated by using the full energy band instead of the non-parabolic band structure. The position-dependent doping profile found in real diodes is modeled accurately and time-efficiently. A two-step method is introduced to accelerate the simulation of avalanche breakdown. With the proposed model, the expected IV characteristics of a voltage regulator diode under reverse bias are simulated. The transport of …

Complex System Methodology For Meta Architecture Optimization Of The Kidney Transplant System Of Systems, Richard Threlkeld, Lirim Ashiku, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The demand for kidney transplants is growing and far outweighs the supply of kidneys. With approximately 20 percent of kidneys discarded each year, there is an opportunity to develop a methodology to analyze the key performance attributes of the complex kidney transplant system. This paper designs and analyzes a meta-architecture for the organ procurement system with a use case in the kidney transplant system. The complex systems and interfaces create emergent behavior that will affect the key performance attributes of Performance, Discard Rate, Observed over Expected Kidney Transplants, Affordability, and Acceptability. These key performance attributes, interfaces, and rules are developed …

Extraction Of Stripline Surface Roughness Using Cross-Section Information And S-Parameter Measurements, Zeyi Sun, Jian Liu, Xiaoyan Xiong, Victor Khilkevich, Donghyun Kim, Darvl Beetner

Engineering Management and Systems Engineering Faculty Research & Creative Works

To characterize additional conductor loss introduced by conductor surface roughness, various models have been proposed to describe the relationship between foil roughness levels and surface roughness correction factor. However, all these empirical or physical models require a PCB sample to be manufactured and analyzed in advance. The procedure requires dissecting the PCB and is time- and labor-consuming. To avoid such a process, a new surface roughness extraction process is proposed here. Only the measured S-parameter and nominal cross-sectional information of the board are needed to extract the roughness level of conductor foils. Besides, this method can also deal with boards …

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 …

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 …

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 …

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 …

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 …