Engineering Commons^™

Underlying Substrate Effect On Electrochemical Activity For Hydrogen Evolution Reaction With Low-Platinum-Loaded Catalysts, Baleeswaraiah Muchharla, Peter V. Sushko, Kishor K. Sadasivuni, Wei Cao, Akash Tomar, Hani Elsayed-Ali, Adetayo Adedeji, Abdennaceur Karoui, Joshua M. Spurgeon, Bijandra Kumar

Electrical & Computer Engineering Faculty Publications

Platinum is known as the best catalyst for the hydrogen evolution reaction (HER) but the scarcity and high cost of Pt limit its widespread applicability. Herein, the role of the underlying substrate on the HER activity of dispersed Pt atoms is uncovered. A direct current magnetron sputtering technique is utilized to deposit transition metal (TM) thin films of W, Ti, and Ta as underlying substrates for extremely low loading of Pt (

Identification And Characterization Of Two Novel Kcnh2 Mutations Contributing To Long Qt Syndrome, Anthony Owusu-Mensah, Jacqueline Treat, Joyce Bernardi, Ryan Pfeiffer, Robert Goodrow, Bright Tsevi, Victoria Lam, Michel Audette, Jonathan M. Cordeiro, Makarand Deo

Electrical & Computer Engineering Faculty Publications

We identified two different inherited mutations in KCNH2 gene, or human ether-a-go-go related gene (hERG), which are linked to Long QT Syndrome. The first mutation was in a 1-day-old infant, whereas the second was in a 14-year-old girl. The two KCNH2 mutations were transiently transfected into either human embryonic kidney (HEK) cells or human induced pluripotent stem-cell derived cardiomyocytes. We performed associated multiscale computer simulations to elucidate the arrhythmogenic potentials of the KCNH2 mutations. Genetic screening of the first and second index patients revealed a heterozygous missense mutation in KCNH2, resulting in an amino acid change (P632L) in the …

Domain Adaptive Federated Learning For Multi-Institution Molecular Mutation Prediction And Bias Identification, W. Farzana, M. A. Witherow, I. Longoria, M. S. Sadique, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Deep learning models have shown potential in medical image analysis tasks. However, training a generalized deep learning model requires huge amounts of patient data that is usually gathered from multiple institutions which may raise privacy concerns. Federated learning (FL) provides an alternative to sharing data across institutions. Nonetheless, FL is susceptible to a few challenges including inversion attacks on model weights, heterogenous data distributions, and bias. This study addresses heterogeneity and bias issues for multi-institution patient data by proposing domain adaptive FL modeling using several radiomics (volume, fractal, texture) features for O6-methylguanine-DNA methyltransferase (MGMT) classification across multiple institutions. The proposed …

Using Feature Selection Enhancement To Evaluate Attack Detection In The Internet Of Things Environment, Khawlah Harahsheh, Rami Al-Naimat, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The rapid evolution of technology has given rise to a connected world where billions of devices interact seamlessly, forming what is known as the Internet of Things (IoT). While the IoT offers incredible convenience and efficiency, it presents a significant challenge to cybersecurity and is characterized by various power, capacity, and computational process limitations. Machine learning techniques, particularly those encompassing supervised classification techniques, offer a systematic approach to training models using labeled datasets. These techniques enable intrusion detection systems (IDSs) to discern patterns indicative of potential attacks amidst the vast amounts of IoT data. Our investigation delves into various aspects …

Quest For An Optimal Spin-Polarized Electron Source For The Electron-Ion Collider, J. Biswas, E. Wang, O. Rahman, J. Sharitka, K. Kisslinger, Adam Masters, S. Marsillac, T. Lee

Electrical & Computer Engineering Faculty Publications

Superlattice GaAs photocathodes play a crucial role as the primary source of polarized electrons in various accelerator facilities, including the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson National Laboratory and the Electron-Ion Collider (EIC) at Brookhaven National Laboratory. To increase the quantum efficiency (QE) of GaAs/GaAsP superlattice photocathodes, a Distributed Bragg Reflector (DBR) is grown underneath using metal-organic chemical vapor deposition (MOCVD). There are several challenges associated with DBR photocathodes: the resonance peak may not align with the emission threshold of around 780 nm, non-uniform doping density in the top 5 nm may significantly impact QE and spin polarization, …

Toward Inclusivity: Rethinking Islamophobic Content Classification In The Digital Age, Esraa Aldreabi, Mukul Dev Chhangani, Khawlah M. Harahsheh, Justin M. Lee, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

In this paper, we implement a comprehensive three-class system to categorize social media discussions about Islam and Muslims, enhancing the typical binary approach. These classes are: I) General Discourse About Islam and Muslims, II) Criticism of Islamic Teachings and Figures, and III) Comments Against Muslims. These categories are designed to balance the nuances of free speech while protecting diverse groups like Muslims, ex-Muslims, LGBTQ+ communities, and atheists. By utilizing machine learning and employing transformer-based models, we analyze the distribution and characteristics of these classes in social media content. Our findings reveal distinct patterns of user engagement with topics related to …

Runtime Performance Of Gamess Quantum Chemistry Application Offloaded To Gpus, Masha Sosonkina, Gabriel Mateescu, Peng Xu, Tosaporn Sattasathuchana, Buu Pham, Mark S. Gordon, Sarom S. Leang

Electrical & Computer Engineering Faculty Publications

Computational chemistry is at the forefront of solving urgent societal problems, such as polymer upcycling and carbon capture. The complexity of modeling these processes at appropriate length and time scales is mainly manifested in the number and types of chemical species involved in the reactions and may require models of several thousand atoms and large basis sets to accurately capture the chemical complexity and heterogeneity in the physical and chemical processes. The quantum chemistry package General Atomic and Molecular Electronic Structure System (GAMESS) has a wide array of methods that can efficiently and accurately treat complex chemical systems. In this …

Thermal Diffusivity And Acoustic Properties Of Nb Thin Films Studied By Time-Domain Thermoreflectance, Md. Obidul Islam, Hani Elsayed-Ali

Electrical & Computer Engineering Faculty Publications

The thermal diffusion and acoustic properties of Nb impacts the thermal management of devices incorporating Nb thin films such as superconducting radiofrequency (SRF) cavities and superconducting high-speed electronic devices. The diffusion and acoustic properties of 200-800 nm thick Nb films deposited on Cu substrates were investigated using time-domain thermoreflectance (TDTR). The films were examined by X-ray diffraction, scanning electron microscopy, and atomic force microscopy. The grain size and thermal diffusivity increase with film thickness. The thermal diffusivity increased from 0.100± 0.002 cm²s^-1 to 0.237± 0.002 cm²s^-1 with the increase in film thickness from 200 …

A Fresh Revisit Of The Issues And Improvements In Impulse Invariance Filter Design For Infinite Impulse Response Filters, Chiman Kwan, Hal Ferguson

Electrical & Computer Engineering Faculty Publications

The objective of this paper is to first present some issues with impulse invariance filter (IIF) design during the design of digital infinite impulse response (IIR) filters. Engineers are often confused about some inconsistent observations. For instance, if the impulse response of a digital filter is designed using the impulse invariance procedure, then the analog and digital filters’ frequency and step responses are very different. Two simple remedies are presented in this paper. One is a post-processing approach that scales the frequency and step responses of the digital filter by the sampling interval T. Another one is a pre-processing approach …

Predictions Of Lattice Parameters In Niti High-Entropy Shape-Memory Alloys Using Different Machine Learning Models, Tu-Ngoc Lam, Jiajun Jiang, Min-Cheng Hsu, Shr-Ruei Tsai, Mao-Yuan Luo, Shuo-Ting Hsu, Wen-Jay Lee, Chung-Hao Chen, E-Wen Huang

Electrical & Computer Engineering Faculty Publications

This work applied three machine learning (ML) models—linear regression (LR), random forest (RF), and support vector regression (SVR)—to predict the lattice parameters of the monoclinic B19′ phase in two distinct training datasets: previously published ZrO₂-based shape-memory ceramics (SMCs) and NiTi-based high-entropy shape-memory alloys (HESMAs). Our findings showed that LR provided the most accurate predictions for a_c, a_m, b_m, and c_m in NiTi-based HESMAs, while RF excelled in computing βm for both datasets. SVR disclosed the largest deviation between the predicted and actual values of lattice parameters for both training datasets. A combination approach …

Parametrization Of Fluid Models For Electrical Breakdown Of Nitrogen At Atmospheric Pressure, Shirshak K. Dhali

Electrical & Computer Engineering Faculty Publications

In the transient phase of an atmospheric pressure discharge, the avalanche turns into a streamer discharge with time. Hydrodynamic fluid models are frequently used to describe the formation and propagation of streamers, where charge particle transport is dominated by the creation of space charge. The required electron transport data and rate coefficients for the fluid model are parameterized using the local mean energy approximation (LMEA) and the local field approximation (LFA). In atmospheric pressure applications, the excited species produced in the electrical discharge determine the subsequent conversion chemistry. We performed the fluid model simulation of streamers in nitrogen gas at …

Scene Classification Of Remote Sensing Image Based On Multi-Path Reconfigurable Neural Network, Wenyi Hu, Chunjie Lan, Tian Chen, Shan Liu, Lirong Yin, Lei Wang

Electrical & Computer Engineering Faculty Publications

Land image recognition and classification and land environment detection are important research fields in remote sensing applications. Because of the diversity and complexity of different tasks of land environment recognition and classification, it is difficult for researchers to use a single model to achieve the best performance in scene classification of multiple remote sensing land images. Therefore, to determine which model is the best for the current recognition classification tasks, it is often necessary to select and experiment with many different models. However, finding the optimal model is accompanied by an increase in trial-and-error costs and is a waste of …

Generalized Functions In The Study Of Signals And Systems, Erik I. Verriest, Gunther Dirr, W. Steven Gray

Electrical & Computer Engineering Faculty Publications

We collect three instances where the theory of generalized functions may still make contributions to the study of signals and systems. In the first, a purely algebraic approach is presented for LTI-ODE's, in terms of two operators, D and T, respectively the differentiation operator and the multiplication-by-the-independent-variable operator. This formalism adds simplicity, a duality theory, and nicely generalizes to other classes of operator equations and their solutions. In the second part we extend the classical bilateral Laplace transform to include Bohl functions with support in ℝ by invoking Sato's hyperfunctions. Finally, in the third case we use the Colombeau algebra …

An Enhanced Real-Time Intrusion Detection Framework Using Federated Transfer Learning In Large-Scale Iot Networks, Khawlah Harahsheh, Malek Alzaqebah, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

The exponential growth of Internet of Things (IoT) devices has introduced critical security challenges, particularly in scalability, privacy, and resource constraints. Traditional centralized intrusion detection systems (IDS) struggle to address these issues effectively. To overcome these limitations, this study proposes a novel Federated Transfer Learning (FTL)-based intrusion detection framework tailored for large-scale IoT networks. By integrating Federated Learning (FL) with Transfer Learning (TL), the framework enhances detection capabilities while ensuring data privacy and reducing communication overhead. The hybrid model incorporates convolutional neural networks (CNNs), bidirectional gated recurrent units (BiGRUs), attention mechanisms, and ensemble learning. To address the class imbalance, Synthetic …

Methylene Blue-Mediated Photodynamic Therapy In Combination With Doxorubicin: A Novel Approach In The Treatment Of Ht-29 Colon Cancer Cells, Nima Rastegar-Pouyani, Jaber Zafari, Alireza Nasirpour, Hossein Vazini, Nabbaa Najjar, Seyedeh Zohreh Azarshin, Fatemeh Javani Jouni

Electrical & Computer Engineering Faculty Publications

Introduction: With an alarmingly growing number of patients diagnosed with colorectal cancer, adopting innovative anti-cancer approaches has recently garnered great attention. One interesting concept is the co-administration of cytotoxic agents and safer modalities such as photodynamic therapy (PDT), which can subsequently improve therapeutic efficacy and potentially reduce the risks of severe adverse effects and drug resistance. In the course of PDT, a locally injected photosensitizer (PS) is irradiated with a light source, which subsequently generates reactive oxygen species (ROS) and induces programmed cell death in tumor cells.

Methods: In this study, to evaluate the potential anti-cancer effects of chemotherapy combined …

Characterizing Climatic Socio-Environmental Tipping Points In Coastal Communities: A Conceptual Framework For Research And Practice, Julie Elizabeth Shortridge, Anamaria Bukvic, Molly Mitchell, Jesse Goldstein, Tom Allen

Political Science & Geography Faculty Publications

The concept of climate tipping points in socio-environmental systems is increasingly being used to describe nonlinear climate change impacts and encourage social transformations in response to climate change. However, the processes that lead to these tipping points and their impacts are highly complex and deeply uncertain. This is due to numerous interacting environmental and societal system components, constant system evolution, and uncertainty in the relationships between events and their consequences. In the face of this complexity and uncertainty, this research presents a conceptual framework that describes systemic processes that could lead to tipping points socio-environmental systems, with a focus on …

Self-Optimized Agent For Load Balancing And Energy Efficiency: A Reinforcement Learning Framework With Hybrid Action Space, Bishoy Salama Attia, Aamen Elgharably, Mariam Nabil Aboelwafa, Ghada Alsuhli, Karim Banawan, Karim G. Seddik

Faculty Journal Articles

We consider the problem of jointly enhancing the network throughput, minimizing energy consumption, and improving the network coverage of mobile networks. The problem is cast as a reinforcement learning (RL) problem. The reward function accounts for the joint optimization of throughput, energy consumption, and coverage (through the number of uncovered users); our RL framework allows the network operator to assign weights to each of these cost functions based on the operator's preferences. Moreover, the state is defined by key performance indicators (KPIs) that are readily available on the network operator side. Finally, the action space for the RL agent comprises …

Draft Makerspace Optimization And Procedure For The University Of Northern Iowa And Cedar Falls, Andrew Nii Anang

Graduate Research Papers

The University of Northern Iowa (UNI) Makcrspace is a dynamic, communal setting created to encourage members of the community at large to be creative, innovative and engage in hands-on learning. Access to a variety of hand and power tools as well as state-of-the-art technologies is available at this cutting-edge facility. The Makerspace promotes a culture of experimentation and entrepreneurship while offering assistance for multidisciplinary initiatives. The Makerspace incorporates real-world, project-based learning experience, greatly improving UNI's educational environment. It enhances the university's reputation for encouraging innovation and research by drawing in potential students and community members who are interested in cutting-edge …

A Transverse-Flux Constant Force Mechanism, Gozde Sivka, Bertrand Dechant, Colton Bruce, Jonathan Z. Bird

Electrical and Computer Engineering Faculty Publications and Presentations

A new type of constant force magnet mechanism is presented that relies on the interaction of magnets alone to create a constant force over a prescribed stroke length. It is demonstrated that by using a transverse field path a very uniform radial field along the travel length is created. This can then be used to create a constant force over a long stroke length. The constat force value is shown to be adjustable through the rotation of the stator relative to the translator. The operating principle of the presented transverse-flux constant force mechanism is validated by using 3-D finite element …

Evaluating Friction Characteristics Of High Friction Surface Treatment Application Under Varied Polishing And Slippery Conditions, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The frictional attributes of high friction surface treatment (HFST) play a crucial role in ensuring optimal traffic safety, particularly in wet weather conditions. Friction consists of two important components: adhesion and hysteresis. This research focuses on evaluating these essential factors in HFST using two different aggregates and two distinct sizes by considering various abrasion and polishing methods. To isolate these components for assessment, testing was carried out under various slippery conditions, including dry, wet with water, and wet with water + soap. The inclusion of liquid hand soap in the test procedure effectively minimized or even eliminated the adhesion component's …

Improving Aggregate Abrasion Resistance Prediction Via Micro-Deval Test Using Ensemble Machine Learning Techniques, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Aggregate is the most extracted material from the world's mines and widely used in civil and construction projects. The Micro-Deval abrasion test (MD) is one of the most important tests that provides characteristics of crushed aggregates that show their resistance against mechanical abrasive factors such as repeated impact loading. The impact of various factors on abrasive resistance properties of aggregates has led researchers to seek correlations, often focusing on limited data samples, leading to reduced accuracy. This study employs machine learning (ML) methods to predict MD abrasion values, considering diverse aggregate properties. Various ensemble ML methods were applied, revealing the …

Photogrammetry-Based Method For Measuring Volume Changes Of Soil Specimens During Critical Phases Of Triaxial Testing, Sara Fayek, Xiong Zhang, Pingxin Xia

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Triaxial tests has been routinely used to measure the stress–strain relationship for geomaterials. During triaxial testing, many sources of errors that cannot be completely avoided but are often ignored or approximated using empirical equations. This paper presents a systematic investigation of soil volume change, volume strain nonuniformity, and cross-sectional calculation along the specimen during triaxial testing using a photogrammetry-based method. Consolidated drained triaxial tests were performed in which two parallel measurements were taken: (1) relative volume using the conventional triaxial testing and (2) absolute volume using the photogrammetry-based method. The difference in the observed volume and void ratio measurements between …

Influence Of Nanofiller Surface Treatment On Mechanical Properties Of Pyrolyzed Ceramic Nanocomposites, Laxmi Sai Viswanadha, Chenglin Wu, Jeremy Watts, Mohammad Naraghi

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The brittleness and limited plastic deformation of ceramics restrict their applications. In this work, the effects of pristine (CNTP), functionalized (CNTOH, CNTCOOH) and silanized MWCNTs on the mechanical properties of Silicon Carbide obtained by pyrolyzing polycarbosilane SMP-10 were studied. Functionalization with 3-glycidoxypropyltrimethoxy was analyzed through dispersion stability, zeta potential, and EDS analyses, revealing increased silicon content and colloidal stability in silanized MWCNTs. However, silanized MWCNTs led to reduced mechanical properties in composites, while untreated MWCNTs (CNTP, CNTOH, CNTCOOH), showed a substantial increase in modulus by 74.2 %, 86.9 %, and 30.5 %, respectively. The observed enhancement in mechanical properties exceeded …

A Vehicle-Bridge Interaction Model Considering Contact Patch Size And Vehicle Self-Generated Excitation – A Theoretical Study, Zhenhua Shi, Yahya M. Mohammed, Nasim Uddin, Genda Chen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This paper presents an improved theoretical damped single-axle vehicle-bridge dynamic interaction model to consider the effect of the contact patch size and motor-induced vehicle excitation. The contact patch issue is critical as it determines the minimum time step for simulation and maximum identifiable frequency, while the inclusion of the motor-induced vehicle excitation benefits the design of autonomous self-driven rather than towed vehicles. Estimations of the contact patch size for both the pneumatic tire and solid wheel scenarios are discussed. The contact patch responses, which degenerate into contact point responses when the contact patch size is assumed to be infinitely small, …

Data-Driven Analysis Of Progressive Design Build In Water And Wastewater Infrastructure Projects, Fareed Salih, Radwa Eissa, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The United States has invested heavily in water and wastewater infrastructure projects to address growing demand and aging systems. To ensure the effective delivery of these projects, agencies are shifting toward alternative delivery methods such as progressive design build (PDB), which has demonstrated accelerated schedule and enhanced cost performance across the literature as well as multiple projects compared to traditional DB. This has raised a need for evaluating PDB's state of adoption and performance in the water and wastewater sector. To this end, the authors: (1) conducted descriptive and statistical analyses of the 21 PDB water and wastewater projects available …

The Hydration, Microstructure, And Mechanical Properties Of Vaterite Calcined Clay Cement (Vc³), Yaqiang Li, Yue Li, Hongyan Ma, Jiaqi Li

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Limestone (calcite) calcined clay cement (LC3) is a promising low-CO2 binder, but the low activity of calcite cannot compensate the reduction in clinker factor, resulting in low one-day strength and limiting its broad applications. As recent carbon capture and utilization technologies allow scalable production of vaterite, a more reactive CaCO3 polymorph, we overcome the challenge by introducing vaterite calcined clay cement (VC3), inspired by the vaterite-calcite phase change. In the present study, VC3 exhibits higher compressive strengths and faster hydration than LC3. Compared to hydrated LC3, hydrated VC3 exhibits increased amount of hemi- and mono-carboaluminate formation and decreased amount of …

Performance Of Smart Shear Keys In Concrete Bridges Under Tsunami Loading: An Experimental Study, Haibin Zhang, Xinzhe Yuan, Genda Chen, Pedro Lomonaco

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Bridges have recently been exposed to an increasing number of natural hazards such as earthquakes and tsunamis. These extreme events have resulted in transverse offsets, overturning moments, and even dropping-off of superstructures due to their weak connection to substructures. These outcomes are potentially prevented or mitigated by developing and deploying sliding, modular, adaptive, replaceable, and two-dimensional (SMART) shear keys as fuse elements between superstructures and substructures. The novelty of SMART shear keys is to enable an adaptive control of both the force and displacement of bridges under different types of loads. In this study, the performance of SMART shear keys …

Skilled Worker Shortage Across Key Labor-Intensive Construction Trades In Union Versus Nonunion Environments, Tamima Elbashbishy, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Skilled labor plays a crucial role in ensuring that construction projects are completed on time, within budget, and to the required standards of quality and safety. However, the construction industry has been facing a labor shortage in recent years, which poses a significant challenge to the industry's growth and sustainability. Therefore, it is important to examine the characteristics of the construction skilled labor market to understand the factors that contribute to the shortage of skilled workers and develop strategies to address the issue. This paper fills this knowledge gap. To this end, the authors (1) collected and processed project documentation …

A Holistic Approach To Exploring The Root Factors Of Work Zone Accidents, Bahaa Chammout, Muaz O. Ahmed, Islam H. El-Adaway, William Lieser

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Work zones are crucial for infrastructure maintenance and improvement. However, ongoing projects within work zones sometimes can place workers and drivers in dangerous situations. Despite safety regulations, work zone accidents persist with notable severity and frequency. Previous research has explored work zone accident causation, but it has not provided a comprehensive understanding of the factors that impact work zone safety. This paper addresses this research gap by following a multistep methodology. First, a systematic literature review (SLR) was conducted to identify a comprehensive list of 37 factors impacting work zone safety. Second, social network analysis (SNA) was employed to analyze …

Enhancing Pricing Practices Of Subcontractors: A Comparative Analysis Using Simulation Modeling, Muaz O. Ahmed, Islam H. El-Adaway, Kalyn T. Coatney

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The construction industry often relies on subcontracting, where subcontractors bid for portions of a project before general contractors bid for the entire project in a process referred to as multi-stage bidding (MSG). MSG can be complex, and winning bidders may be burdened with underestimating their bids and encountering the winner's curse. Despite various studies investigating this issue, further research is necessary to examine bidding strategies for subcontractors. This paper addresses this research need by exploring and comparing how bidding strategies based on reinforcement learning and game theory could aid subcontractors in mitigating the winner's curse in MSG. The authors used …