Engineering Commons^™

The Role Of Ai In Enhancing Teamwork, Resilience And Decision-Making: Review Of Recent Developments, Satyadhar Joshi

Harrisburg University Other Works

This paper explores the transformative impact of artificial intelligence (AI) on organizational teamwork, decision-making, and resilience. This paper furthur reviews recent literature on the integration of Artificial Intelligence (AI) in various organizational functions, focusing on its impact on innovation management, leadership paradigms, and organizational resilience. We provide groundwork required to enhance frameworks that can integrate cognitive scaffolding with antifragile team dynamics, employing behavioral economics and neurocognitive principles. We introduce methodologies for enhancing team resilience through adaptive AI systems, cross-training interventions, and pre-mortem simulation techniques. The framework addresses key challenges in confirmation bias mitigation, cultural dimension alignment, and vigilance decrement prevention. …

Assessment Of Energy Efficiency Measures Recommended For Industrial Facilities: Environmental, Economic, And Life Cycle Perspectives, Dariush Jafari

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

This study assesses the economic, environmental, and life cycle impacts of more than 800 industrial Energy Efficiency Measures (EEMs) identified in manufacturing facilities across Nebraska. These EEMs are notable for their rapid implementation and minimal disruption to the facility’s building structure or core processes.

The research evaluates the financial viability of EEMs by analyzing utility savings, implementation costs, and payback periods. It also examines their cost-effectiveness in reducing greenhouse gas (GHG) emissions, including calculations of net cost and cost of mitigated CO₂-eq.

Key findings indicate that adding insulation to hot pipes and buildings, replacing personal fans with High-Volume, Low-Speed (HVLS) …

Mash Crashworthiness Of Work Zone Devices And Breakaway Luminaire Poles, Mohammadreza Rajaee

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

This thesis presents a study on the crashworthiness of two commonly-used roadside safety devices: Type II barricades and luminaire poles supported by TB1-17 transformer bases. The first part focuses on designing and evaluating a non-proprietary, Type II barricade that meets MASH criteria. A validated LS-DYNA model, based on a previously-tested Type III barricade, was used to guide the design. The proposed Type II system was evaluated through simulation and confirmed with full-scale crash testing. The second part of the study investigates luminaire poles supported by the TB1-17 transformer base. A previously-developed LS-DYNA model was updated and validated using test No. …

A Framework For Quantifying The Benefits Of Electric Vehicle Infrastructure Development, Donya Negahbani

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Under the Biden Administration’s Justice40 Initiative, a significant portion of benefits derived from federal clean transportation investments is required to be directed to disadvantaged communities. Meeting this mandate necessitates a transparent and reproducible approach that quantifies various dimensions of value and allocates them equitably. This dissertation presents a flexible framework specifically tailored for the deployment of electric vehicle charging infrastructure in Nebraska, effectively translating equity goals into rigorous spatial and economic analyses. The framework first identifies multiple distinct categories of benefit that reflect the societal value of charging access: energy savings, economic opportunities, environmental quality enhancements, and public health improvements. …

Development Of Timber Bridge Railing And Approach Guardrail Transition, Aaron Lechtenberger

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Timber bridges with transverse and longitudinal bridge decks are increasingly utilized across the United States. However, limited research exists to develop bridge railing systems for high-service-level roadways that meet current vehicular impact safety standards. In response to this gap, the United States Department of Agriculture - Forest Service -Forest Products Laboratory (USDA-FS-FPL), in collaboration with the Midwest Roadside Safety Facility (MwRSF), initiated a research program to develop, crash test, and evaluate higher-service-level bridge railings and approach guardrail transitions (AGTs) compliant with the American Association of State Highway and Transportation Officials (AASHTO) Manual for Assessing Safety Hardware (MASH).

This study continued …

Towards Advancing Streamflow And Peak Flow Prediction With Machine Learning: Identifying Infrastructure At Risk, Sudan Pokharel

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Due to climate change and its impact, the need for adaptive strategies for natural disaster mitigation and resource management has never been more urgent. Central to this is water resource management, which is essential for sustainable human activities, ecological balance, and the mitigation of natural hazards like floods. Streamflow is a crucial element of water resource management and plays a vital role in planning and building water infrastructure, implementing emergency response plans, supporting flood mitigation initiatives, and regulating agricultural and industrial use. However, accurate prediction of streamflow still remains a challenge due to the complex non-linear and non-stationary interaction between …

Robot-Integrated 4d Building Information Modeling (4d Bim): Framework For Planning Safe Autonomous Construction Operations In Dynamic Environments, Hafiz Oyedimeji Oyediran

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

In the construction industry, the use of autonomous robots is considered a solution to overcome the heavy reliance on human workers to perform repetitive, strenuous, and hazardous tasks. While these robots offer the advantage of autonomous operation, ensuring their safe and efficient integration within construction sites requires precise planning. Such planning must account for the varying project complexities such as scope, site layout, tasks, timelines, existence of human workers, and other spatiotemporal conditions of the construction site. Currently, there are no methods to safely plan autonomous robot operations considering these factors within the overarching construction planning process. Thus, autonomous robots …

Advanced Porosity Control Of Cp780 Galvanized Steel During Gas Metal Arc Welding With Pulsed Arc, Carlos Adrián García Ochoa, Jorge Alejandro Verduzco Martínez, Francisco Fernando Curiel-López, Víctor Hugo López-Morelos, Jaime Taha-Tijerina, Ariosto Medina Flores, Maleni García Gómez

Informatics and Engineering Systems Faculty Publications

This study investigated the control of porosity during gas metal arc welding with pulsed arc (GMAW-P) of complex-phase 780 (CP780) galvanized steel. Due to the Zn coating on this type of steel, porosity forms during welding as a result of Zn vaporization. The objective was to optimize the welding parameters to minimize porosity with a design of experiments using an L9 orthogonal array to analyze the effects of peak current (Ip), pulse time (tp), and pulse frequency (f) in high-speed welding conditions. The results showed that porosity was significantly reduced with a peak current of 313 A, a frequency of …

Empowering Optimal Operations With Renewable Energy Solutions For Grid Connected Merredin Wa Mining Sector, Md Ohirul Qays, Ravi Kumar, Minhaz Ahmed, Stefan Lachowicz, Uzma Amin

Research outputs 2022 to 2026

Mining sectors require a continuous and reliable power supply; however, reliance on traditional grid utilities results in high costs and disruptions and increases extreme carbon emission. The Merredin WA sector seeks to resolve critical energy challenges affecting mining operations in Western Australia. Thus, this research proposes an optimal solar PV system with battery storage and backup generation for the mining sector to ensure a stable and cost-effective power supply that reduces harmful environmental effect. A hybrid data-driven long short-term memory (LSTM)-classical optimization framework is designed here, thereby optimizing PV-battery storage operational cost savings and energy usage. The optimization results indicate …

Advanced Day-Ahead Scheduling Of Hvac Demand Response Control Using Novel Strategy Of Q-Learning, Model Predictive Control, And Input Convex Neural Networks, Rahman Heidarykiany, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we present a Q-Learning optimization algorithm for smart home HVAC systems. The proposed algorithm combines new convex deep neural network models with model predictive control (MPC) techniques. More specifically, new input convex long short-term memory (ICLSTM) models are employed to predict dynamic states in an MPC optimal control technique integrated within a Q-Learning reinforcement learning (RL) algorithm to further improve the learned temporal behaviors of nonlinear HVAC systems. As a novel RL approach, the proposed algorithm generates day-ahead HVAC demand response (DR) signals in smart homes that optimally reduce and/or shift peak energy usage, reduce electricity costs, …

Integrating Blockchain Technology Into Telemedicine: A Framework For Enhancing Data Privacy And Security, Harsha Sammangi, Aditya Jagatha, Jun Liu

Research & Publications

This paper presents a blockchain-based framework designed to enhance data privacy, integrity, and security in telemedicine systems. The proposed architecture employs distributed ledger technology to ensure transparency, traceability, and immutability of patient data exchanges among healthcare providers. Smart contracts automate access permissions and auditing processes, reducing the risks of unauthorized data sharing. The study evaluates the framework’s performance in secure data handling, highlighting blockchain’s role in fostering patient trust and resilience against cyberattacks in remote healthcare environments.

Decentralized Multi-Hop Federated Reinforcement Learning For Energy-Efficient And Secure Routing In Lorawan-Based Smart City Infrastructure, Harsha Sammangi, Aditya Jagatha, Jun Liu

Research & Publications

This paper proposes a decentralized hybrid framework that integrates Federated Learning (FL) and Reinforcement Learning (RL) to enable energy-efficient and secure multi-hop routing in LoRaWAN-based smart city networks. The method allows local model training at gateways and relay nodes, combining real-time routing decisions with privacy-preserving federated aggregation. Key metrics such as residual energy, link quality, and node trust levels are embedded into the reward function, and lightweight encryption plus differential privacy safeguard routing metadata. Simulation results demonstrate substantial gains in packet-delivery ratio, latency, network lifetime and resilience to adversarial attacks when compared to traditional routing protocols.

Optimization-Based Distributed Controller For Multi-Agents System In Microgrid Secondary Control, Fahad S. Alshammari, Ayman El-Refaie, Saleh Alyahya, Sheroz Khan

Electrical and Computer Engineering Faculty Research and Publications

Micro-grids function to connect to power system power produced by the renewable energy resources. In islanded micro-grids, grid-forming units collaborate to maintain the micro-grids voltage and frequency by utilizing droop control technique that includes primary, secondary and tertiary levels. Secondary control intervenes to improve power sharing and restore voltage and frequency to their nominal levels. However, the conventional droop control applied to a grid with mismatched line parameters experiences a trade-off between reactive power sharing and voltage regulations. This paper applies real-time trajectory tracking convex optimization to ensure by communicating power sharing between units in a consensus topology. The optimization …

Computationally Guided Liquid Crystal-Based Competitive Binding Sensing Platform For Optical Detection Of Spike Protein, Homa Ghaiedi, Shubham Pandey, Sophia Ezendu, Tibor Szilvasi, Karthik Nayani

Chemical Engineering Faculty Publications and Presentations

A liquid crystal (LC)-based sensing platform for the rapid optical detection of SARS-CoV-2 ' s spike protein's receptor binding domain (RBD) domain is introduced. This platform utilizes a thermotropic LC, hosted on metal-cation decorated substrates, onto which the spike protein can competitively bind. Density functional theory (DFT) calculations guide the experiments that reveal a homeotropic-to-planar transition in the LCs upon exposure to SARS-CoV-2 spike-decorated yeast, providing a basis for sensitive virus detection. The sensor's reversibility/specificity is confirmed through antibody-induced orientation recovery of the LCs initial orientation. Strikingly, the sensor can detect approximate to 2000 copies of the spike protein per …

Influence Of Boundary Conditions And Blood Rheology On Indices Of Wall Shear Stress From Ivus-Based Patient-Specific Stented Coronary Artery Simulations, R. Patrick Mccarthy, Peter J. Mason, David S. Marks, John F. Ladisa Jr.

Biomedical Engineering Faculty Research and Publications

The long-term clinical efficacy of coronary stents is limited by restenosis. Coronary stenting results in altered arterial geometry, local blood flow patterns, and wall shear stress (WSS), all of which can influence restenosis. Computational fluid dynamics (CFD) simulations employ assumptions about blood properties and boundary conditions, which also influence WSS alterations from stenting. Our objective was to evaluate three common assumptions applied with stented coronary artery CFD simulations (inlet velocity profile, outlet boundary conditions, and viscosity) to provide insight for future studies. A patient-specific right coronary artery was reconstructed from intravascular ultrasound and computed tomography imaging. Time-averaged WSS (TAWSS) and …

Locked Dimerized Cxcl12 Exerts Radiosensitizing Effects In Head And Neck Cancer, Oscar Villarreal Espinosa, Musaddiq Awan, Abdullah A. Memon, Anne Frei, Jamie Foeckler, Rachel Kuehn, Jennifer Bruening, Becky Massey, Stuart J. Wong, Monica Shukla, Julia Kasprzak, Amit Joshi, Michael B. Dwinell, Heather A. Himburg, Joseph Zenga

Biomedical Engineering Faculty Research and Publications

Background

Head and neck squamous cell carcinoma (HNSCC) presents significant treatment challenges, particularly in cases unrelated to human papillomavirus (HPV). The chemokine receptor CXCR4, interacting with its ligand CXCL12, plays a crucial role in tumor proliferation, metastasis, and treatment resistance. This study explores the therapeutic potential of engineered monomeric and dimerized CXCL12 variants (CXCL121 and CXCL122, respectively) in HNSCC and evaluates potential additive effects when combined with radiation therapy.

Methods

Clinical HNSCC biopsies were evaluated for CXCR4 expression in both previously untreated and radiorecurrent disease. HNSCC cell lines were then treated with combinations of CXCL12 variants and radiotherapy and interrogated …

Involvement Of Long Non-Coding Rna (Lncrna) Malat1 In Shear Stress Regulated Adipocyte Differentiation, Justin Caron, Marjan Ghanbariabdolmaleki, Madison Marino, Chong Qiu, Bo Wang, Michael Mak, Shue Wang

Biomedical Engineering Faculty Research and Publications

Adipocyte differentiation plays an important role in bone remodeling due to secretory factors that can directly modulate osteoblast and osteoclast, thus affecting overall bone mass and skeletal integrity. Excessive adipocyte differentiation within the bone marrow microenvironment can lead to decreased bone mass, eventually causing osteoporosis. The mechanical microenvironment of bone marrow, including fluid shear, maintains the balance of adipocyte and osteoblast differentiation during bone remodeling. However, how mechanical cues interact with long noncoding RNA (lncRNA) and regulate adipocyte differentiation remains unexplored. In this study, we investigated the mechanosensitive role of lncRNA MALAT1 during mesenchymal stem cells (MSCs) adipocyte differentiation. By …

Preclinical Development Of Genome Editing To Treat Duchenne Muscular Dystrophy By Exon Skipping, Made Harumi Padmaswari, Shilpi Agrawal, Christopher E. Nelson

Biomedical Engineering Faculty Publications and Presentations

Duchenne muscular dystrophy (DMD) is caused by loss-of-function mutations to the gene encoding dystrophin. Restoring the reading frame of dystrophin by removing internal out-of-frame exons may address symptoms of DMD. Therefore, the principle of exon skipping has been at the center stage in drug development for Duchenne muscular dystrophy (DMD) over the past two decades. Antisense oligonucleotides (AONs) have proven effective in modulating splicing sites for exon skipping, resulting in the FDA approval of several drugs using this technique in recent years. However, due to the temporary nature of AON, researchers are actively exploring genome editing as a potential long-term, …

Sensors And Sensibilities: Exploring Interactions For Habitat Comfort With An Environmental-Physiological Sensing Eyewear In The Wild, Sailin Zhong, Patrick Chwalek, Nathan Perry, David Ramsay, Clayton Miller, Denis Lalanne, S. Hamed Alavi, A. Joseph Paradiso

Research Collection College of Integrative Studies

Buildings increasingly incorporate sensing and actuation techniques to automate the regulation of temperature, lighting, ventilation, and more. This trend seeks to minimize human intervention, justified by the promise of enhancing energy optimization. However, it has been widely acknowledged that loss of control over environmental conditions can lead to a diminished perception of comfort and compromised long-term user awareness and satisfaction. How can we envision building systems that can interact with building inhabitants and engage them at the “right” time and place? In this work, we address this challenge through three key contributions: 1) AirSpecs, a novel smart glasses-based system that …

The Histological And Mechanical Behavior Of Skin During Puncture For Different Impactor Sizes And Loading Rates, Joseph Lesueur, Jared Michael Koser, William Dzwierzynski, Brian D. Stemper, Carolyn E. Hampton, Michael Kleinberger, Frank A. Pintar

Biomedical Engineering Faculty Research and Publications

Purpose

The hierarchical structure of skin dictates its protective function against mechanical loading, which has been extensively studied through numerous experiments. Viscoelasticity and anisotropy have been defined for skin in tensile loading, but most puncture studies utilized skin simulants, which lacked natural tension and varying skin thicknesses. The purpose of this study was to define the mechanical behavior and failure thresholds of skin during puncture with various blunt impactor sizes and loading rates.

Methods

After determining natural tension of porcine skin, 232 isolated skin samples were loaded in puncture. Pre-conditioning, sub-failure, and failure trials were conducted with an electrohydraulic piston …

Towards Human Modeling For Human-Robot Collaboration And Digital Twins In Industrial Environments: Research Status, Prospects, And Challenges, Guoyi Xia, Zied Gharairi, Thorsten Wuest, Karl Hribernik, Aaron Heuermann, Furui Liu, Hui Liu, Klaus-Dieter Thoben

Faculty Publications

Human-Robot Collaboration (HRC) and Digital Twins (DT) have significantly advanced industrial development and digital transformation. Human representations and models are essential in Industry 5.0, where human-centric is one of the key features. Despite the growing interest in human models for HRC and DT, a comprehensive overview of these models and enabling technologies currently needs to be provided. This paper aims to present the research status, prospects, applications, and challenges of human modeling for HRC and DT in industrial environments. This paper adopts a Systematic Literature Review (SLR) approach. Moreover, a framework is proposed to systematize human modeling aspects, the technologies …

An Empirical Evaluation Of Communication Technologies And Quality Of Delivery Measurement In Networked Microgrids, Ruairí De Fréin, Yasin Emir Kutlu

Articles

Networked microgrids (NMG) are gaining popularity as an example of smartgrids (SG), where power networks are integrated with communication technologies. Communication technologies enable NMGs to be monitored and controlled via communication networks. However, ensuring that communication networks in NMGs satisfy quality of delivery (QoD) metrics such as the round trip time (RTT) of NMG control data is necessary. This paper addresses the communication network types and communication technologies used in NMGs. We present various NMG deployments to demonstrate real-life applicability in different contexts. We develop a real-time NMG testbed using real hardware such as Cisco 4331 Integrated Services Routers (ISR). …

Trends In Annual Reported Laser Strikes Per Aircraft Operations In The United States From 2010-2024​, Charles J. Prenaveau, Aidan B. Chen, Brooke Wheeler

Aeronautics Student Publications

Laser strikes targeting aircraft have increased in the United States from 2010 to 2024, even when adjusted for the number of aircraft operations. This trend poses a growing threat to aviation safety.

Drought Effects On Part 121 Operations In California, Brian Robert Barlotta, Steve Na, Vivek Sharma, Brooke E. Wheeler

Aeronautics Student Publications

This study examined whether Part 121 flight disruptions (delays, cancellations, diversions) differed between drought and non-drought periods at the five busiest airports in California from 2004 to 2024. There were no significant differences in disruptions between drought seasons for any of the variables.

Annual Bird Strike Reports Per Airport Operation By Different Runway Configurations In The 11 Contiguous Western States Of The United States, Hyunyoung Jang, Jiin Jang, Constantine Anthony Pagent, Vivek Sharma, Brooke E. Wheeler

Aeronautics Student Publications

This study examined differences in annual bird strike reports per operation by runway configuration: parallel runway and intersecting runway. Results supported that parallel runways experience higher annual bird strike reports per operation compared to intersecting runways, indicating a configuration-based risk pattern.

Drone In Sight: Studying The Rates Of Uas Sightings Near Airports By Month, November 2019 To December 2024, Ethan Akers, James Hart Arnold, Travis Coleman, Vivek Sharma, Brooke Wheeler

Aeronautics Student Publications

A weak, decreasing trend was found in monthly UAS (also

known as Unmanned Aerial Vehicle or Drone) sightings near

airports (FAA, 2025), but it was not statistically significant.

There was a significant difference in UAS sightings by month of

the year between November 2019 and December 2024, with a

more sightings in summer months.

The Effects Of Aviation Environmental Knowledge And Ticket Price Increase On Willingness To Pay, Dylan Dahl, Joonyeong Bae, Angelina Velez, Brooke Wheeler

Aeronautics Student Publications

There was no significant effect of aviation environmental knowledge on willingness to pay (WTP; p = .20); however, there was a significant effect on WTP by ticket price increases (p = .02) between 0 and 15%. This suggests that price is a stronger driver than awareness of environmental impact when paying for sustainable aviation fuel (SAF).

Machine Learning In Baseball Analytics: Sabermetrics And Beyond, Wenbing Zhao, Vyaghri Seetharamayya Akella, Shunkun Yang, Xiong Luo

Electrical and Computer Engineering Faculty Publications

In this article, we provide a comprehensive review of machine learning-based sports analytics in baseball. This review is primarily guided by the following three research questions: (1) What baseball analytics problems have been studied using machine learning? (2) What data repositories have been used? (3) What and how machine learning techniques have been employed for these studies? The findings of these research questions lead to several research contributions. First, we provide a taxonomy for baseball analytics problems. According to the proposed taxonomy, machine learning has been employed to (1) predict individual game plays; (2) determine player performance; (3) estimate player …

Enhanced And Interpretable Prediction Of Multiple Cancer Types Using A Stacking Ensemble Approach With Shap Analysis, Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Zhongming Zhao

Faculty, Staff and Student Publications

Background: Cancer is a leading cause of death worldwide, and its early detection is crucial for improving patient outcomes. This study aimed to develop and evaluate ensemble learning models, specifically stacking, for the accurate prediction of lung, breast, and cervical cancers using lifestyle and clinical data.

Methods: 12 base learners were trained on datasets for lung, breast, and cervical cancer. Stacking ensemble models were then developed using these base learners. The models were evaluated for accuracy, precision, recall, F1-score, AUC-ROC, MCC, and kappa. An explainable AI technique, SHAP, was used to interpret model predictions.

Results: The stacking …

Simultaneous Observations Of Irregular Sporadic E Structures Using The Lwa And A Dps4d, Kenneth S. Obenberger, C. A. Taylor, Jonah J. Colman, Eugene Dao, J. Dowell, J. D. Eccles, Daniel J. Emmons, C. T. Fallen, J. M. Holmes, G. B. Taylor

Faculty Publications

Multi-instrument studies have recently shed new light on the morphology of sporadic E, especially intense sporadic E. Here we present simultaneous observations of dense sporadic E (E_s) structures using the Long Wavelength Array (LWA) radio telescopes and a Digisonde Portable Sounder 4D (DPS4D). Our coordinated observations show that the LWA radio telescopes in central New Mexico can reliably locate regions of dense Es structures as they pass over a Digisonde located over 500 km away in Texas. The LWA appears to be most sensitive to the densest E_s structures, which also appear to contain irregularities with vertical …