Digital Commons Network^™

A Descriptive Study Of The Perception Of Emerging Adults Aged 18-25 Years Toward Police Efficacy And Image In The United States, Jude Louis

Theses and Dissertations

The purpose of this study was to investigate the perceptions of emerging adults toward police efficacy and image. The study was descriptive, used quantitative methodology, and utilized a non-experimental design. Close-ended questions were used in an online format to survey emerging adults aged 18-25 years in the United States. The data was collected using the SurveyMonkey Audience, which was relatively cost-effective, able to gather information from the target audience within a short period of time, and efficient with any sample size. The study occurred over two months in 2024. Emerging adults in the United States aged 18-25 years irrespective of …

The Value Of Play In An International Baccalaureate Primary Years Program Preschool Classroom, Colin Bryce Howell

All Electronic Theses and Dissertations

This work sought to further understand the benefits and consequences of play in early childhood settings. Benefits included brain development stimulation, improvement in intelligence, a boost in personal creative thinking, bolstered communication skills and social emotional regulation abilities, better social competence, improved physical and mental health, increased problem solving skills, and strengthened relationships. Varying types of play provide valuable data points as to the critical importance of play in the development of young children. Research continues to suggest a strong link between the efficacy of purposeful play and the correlating benefits of children’s growth and development in key areas. These …

Restorative Practices Lead To Turnaround: Presbyterian Churches In Nebraska, Regina Claudette Jeanpierre-Bryant

All Electronic Theses and Dissertations

This thesis project examines the Gospel of Luke for restorative practices Jesus used when ministry was hard. Jesus is projected in this study as a self-differentiated leader who was victorious in His ministry because He relied on the Holy Spirit, Scripture, and Prayer as restorative practices when He was faced challenges. It also includes an evaluation of current literature on declining/failing churches and turnaround churches. Qualitative research was conducted using research instruments comprised of interviews with three Nebraskan Presbyterian pastors and a survey of members of a Nebraskan Presbyterian congregation. This research was designed so that it may encourage churches …

Effective Programming And Instruction For Students With Social And Behavioral Needs, Anna S. Cook

All Electronic Theses and Dissertations

Providing special education services to students with Emotional Behavioral Disorders (EBD) can be especially complex. EBD students often display academic deficits which are compounded by difficult behaviors and result in many students lagging 1-2 grade levels behind their peers. If not addressed adequately, the combined skill and behavioral challenges continue into adulthood and lead to troubling outcomes such as higher rates of unemployment, dysfunctional relationships, and negative encounters with the legal system. Early and consistent effective intervention is critical to benefit EBD students across academic and social-emotional domains to facilitate as much appropriate inclusion as possible. This review examines: the …

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 (

Sub-Band Backdoor Attack In Remote Sensing Imagery, Kazi Aminul Islam, Hongyi Wu, Chunsheng Xin, Rui Ning, Liuwan Zhu, Jiang Li

Electrical & Computer Engineering Faculty Publications

Remote sensing datasets usually have a wide range of spatial and spectral resolutions. They provide unique advantages in surveillance systems, and many government organizations use remote sensing multispectral imagery to monitor security-critical infrastructures or targets. Artificial Intelligence (AI) has advanced rapidly in recent years and has been widely applied to remote image analysis, achieving state-of-the-art (SOTA) performance. However, AI models are vulnerable and can be easily deceived or poisoned. A malicious user may poison an AI model by creating a stealthy backdoor. A backdoored AI model performs well on clean data but behaves abnormally when a planted trigger appears in …

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, …

Adversarial Training Based Domain Adaptation Of Skin Cancer Images, Syed Qasim Gilani, Muhammad Umair, Maryam Naqvi, Oge Marques, Hee-Cheol Kim

Electrical & Computer Engineering Faculty Publications

Skin lesion datasets used in the research are highly imbalanced; Generative Adversarial Networks can generate synthetic skin lesion images to solve the class imbalance problem, but it can result in bias and domain shift. Domain shifts in skin lesion datasets can also occur if different instruments or imaging resolutions are used to capture skin lesion images. The deep learning models may not perform well in the presence of bias and domain shift in skin lesion datasets. This work presents a domain adaptation algorithm-based methodology for mitigating the effects of domain shift and bias in skin lesion datasets. Six experiments were …

Real-Time Spectroscopic Ellipsometry For Flux Calibrations In Multi-Source Co-Evaporation Of Thin Films: Application To Rate Variations In Cuinse₂ Deposition, Dhurba R. Sapkota, Balaji Ramanujam, Puja Pradhan, Mohammed A. Razooqi Alaani, Ambalanath Shan, Michael J. Heben, Sylvain Marsillac, Nikolas J. Podraza, Robert W. Collins

Electrical & Computer Engineering Faculty Publications

Flux calibrations in multi-source thermal co-evaporation of thin films have been developed based on real-time spectroscopic ellipsometry (RTSE) measurements. This methodology has been applied to fabricate CuInSe₂ (CIS) thin film photovoltaic (PV) absorbers, as an illustrative example, and their properties as functions of deposition rate have been studied. In this example, multiple Cu layers are deposited step-wise onto the same Si wafer substrate at different Cu evaporation source temperatures (TCu). Multiple In₂Se₃ layers are deposited similarly at different In source temperatures (TIn). Using RTSE, the Cu and In₂Se₃ deposition rates are determined as …

Accelerating Cavity Fault Prediction Using Deep Learning At Jefferson Laboratory, Md M. Rahman, A. Carpenter, K. Iftekharuddin, C. Tennant

Electrical & Computer Engineering Faculty Publications

Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive …

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 …

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 …

A Review Of Emerging Sensor Technologies For Tank Inspection: A Focus On Lidar And Hyperspectral Imaging And Their Automation And Deployment, Sergio Pallas Enguita, Chung-Hao Chen, Samuel Kovacic

Electrical & Computer Engineering Faculty Publications

This paper reviews various sensor technologies for tank inspection, focusing on Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) as advanced solutions for corrosion detection. These technologies are evaluated alongside traditional methods such as ultrasonic, electromagnetic, and thermographic inspections. This review highlights their potential to enhance inspection accuracy, reduce the limitations of manual inspection, and support integrated data analysis for comprehensive asset management. Additionally, this paper proposes a pathway for automating these techniques to streamline inspection processes and improve implementation in practical applications.

Advancing Chronic Kidney Disease Prediction Through Machine Learning And Deep Learning With Feature Analysis, Shiddarth Dey Tusar, S. M. Ahad Ali Chowdhury, Md. Jalal Uddin Chowdhury, Rana M. Pir, H. M. Nur A. Alam, Muhammad Rezaur Rahman, Md. Nural Absar Siddiky, Muhammad Enayetur Rahman

Electrical & Computer Engineering Faculty Publications

Chronic Kidney Diesease (CKD) is a significant health issue, ranking as the fourth leading cause of mortality worldwide. The traditional diagnosis and treatment process, reliant on medical experts, is time-consuming. Therefore, thereis an urgent need for more efficient diagnostic methods to improve patient outcomes and reduce mortality rates. In this study, we employ Machine Learning (ML) and Deep Learning (DL) techniques to predict CKD based on important features. Feature analysis was performed using a correlation matrix and the LASSO algo-rithm to identify the most relevant features for model training. We evaluated several ML and DL classifiers, including Logistic Regression (LR), …

Integrated Machine Learning And Deep Learning Models For Cardiovascular Disease Risk Prediction: A Comprehensive Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran

Electrical & Computer Engineering Faculty Publications

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the performance of traditional Machine Learning (ML) and Deep Learning (DL) models in predicting CVD risk, utilizing a meticulously curated dataset derived from health records. Rigorous preprocessing, including normalization and outlier removal, enhances model robustness. Diverse ML models (Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Gradient Boosting) are compared with a Long Short-Term Memory (LSTM) neural network for DL. Evaluation metrics include accuracy, ROC AUC, computation time, and memory usage. Results identify the …

Direct Measurement Of Microwave Loss In Nb Films For Superconducting Qubits, B. Abdisatarov, D. Bafia, A. Murthy, G. Eremeev, H. E. Elsayed-Ali, J. Lee, A. Netepenko, C. P. A. Carlos, S. Leith, G. J. Rosaz, A. Romanenko, A. Grassellino

Electrical & Computer Engineering Faculty Publications

Niobium films are a key component in modern two-dimensional superconducting qubits, yet their contribution to the total qubit decay rate is not fully understood. The presence of different layers of materials and interfaces makes it difficult to identify the dominant loss channels in present two-dimensional qubit designs. In this paper, we present the study that directly correlates measurements of RF losses in such films to material parameters by investigating a high-power impulse magnetron sputtered (HiPIMS) film atop a three-dimensional niobium superconducting radio frequency (SRF) resonator. By using a 3D SRF structure, we are able to isolate the niobium film loss …

Distance Estimation Based On Step Frequency Using Accelerometer Data, Rami M. Al-Naimat, Khawlah M. Harahsheh, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

In recent years, smartphone sensors have become one of the most important and easily available sensors to facilitate people's lives, especially in health care and positioning (indoor environments). However, the data coming from smartphone sensors can be distorted during the user’s movement such as irrelevant movements, walk mode, and speed of walking. This distortion (noise) impairs the estimated distance accuracy (accumulative error) which increases with increasing walking distance. In addition, the accuracy of the distance traveled is affected by the user's speed, as the speed affects the step length. This work proposes a novel approach for calculating step length in …

Hubris Or Talent? Estimating The Role Of Overconfidence In Chinese Households’ Investment Decisions, Jing Xu, Maroula Khraiche, Xi Mao, Xuan Wang

School of Economics and Finance Faculty Publications

We document the extent to which overconfidence in one’s financial literacy (FL overconfidence) plays a role in households’ reported financial risk aversion and their actual investment behavior, using data from the China Household Finance Survey. We measure FL overconfidence by estimating the gap between people’s self-reported financial literacy and their objectively measured financial knowledge. Our results indicate that FL overconfidence is negatively associated with self-reported financial risk aversion. Additionally, FL overconfidence is positively associated with the likelihood of having a brokerage account, holding risky financial instruments (other than just stock), and a proportion of assets allocated towards risky assets. We …

The Convoy, Chris Zwolinski

Mighty Pen Project Anthology & Archive

A true story in which our narrator realizes something is amiss in his convoy, and takes drastic action.

Articles, stories, and other compositions in this archive were written by participants in the Mighty Pen Project. The program, developed by author David L. Robbins, and in partnership with Virginia Commonwealth University and the Virginia War Memorial in Richmond, Virginia, offers veterans and their family members a customized twelve-week writing class, free of charge. The program encourages, supports, and assists participants in sharing their stories and experiences of military experience so both writer and audience may benefit.

A Symbolic Interactionism’S Perspective Of The Attack On The U.S. Capitol., Odeli Hernandez

Undergraduate Scholarship

This paper aims to draw the line between Symbolic Interactionism and how it ties into the political world. Symbolic Interactionism states that humans interpret and assign meanings to symbols through social interaction, thus influencing their behaviors and shaping their realities. It is said that symbolic interactionism could only be applied to micro levels of social interactions, and not to something as big and intricate as politics. This paper will focus on a stand-alone event, the insurrection of the U.S. Capitol on January 6, 2021. Numerous symbols were displayed before, during, and after the attack on the U.S. Capitol, each of …

Amplifying Awareness: Narrative Rationality In The Discourse Of Childhood Cancer, Rosalinda L. Frick

Undergraduate Scholarship

This paper looks into the complex psychological and economic effects of pediatric cancer on families. The paper has devastating realism as it draws on personal experience, as illustrated by the author's brother, Dylan, dying of brain cancer. Dylan's shortened life serves as a harsh reminder of the need to address this serious problem. The paper delves into the power of Aristotle's persuasion model, specifically looking at the concepts of ethos, pathos, and logos. This persuasion model ties into narrative rationality in the paper and looks at how a story's coherence and fidelity can make a large impact on persuasion and …

Sign Here: How Parental Waivers Exceed The Bounds Of Parents' Fundamental Rights, Carissa Hansen

Mitchell Hamline Law Review

No abstract provided.

Machine Learning To Identify Structural Motifs In Asphaltenes, Arun K. Sharma, Selsela Arsala, James Brady, Madison Franke, Shelby Franke, Supreet Gandhok, Simon-Olivier Gingras, Ana Gomez, Katelyn Huie, Kayla Katz, Samantha Kozlo, Mateo Longoria, Levi Molnar, Nathaly Peña, Sarina Regis

Biology, Agriculture and Chemistry Faculty Publications and Presentations

Asphaltenes are organic compounds that aggregate in crude oil with two dominant molecular architectures: archipelago and continental. Continental architectures possess a single uniform island structure composed of aromatic rings in contrast to archipelago architectures with aromatic cores interconnected through aliphatic chains. The structural composition of asphaltenes varies globally due to geographical differences, posing challenges in their classification due to a lack of uniformity. This study is the first known exploration of using image-based supervised machine learning, particularly the ResNet-50 neural network, for the binary classification of asphaltenes into continental and archipelago motifs. 255 continental and archipelago models underwent structural augmentations …

Stat1 Employs Myeloid Cell-Extrinsic Mechanisms To Regulate The Neutrophil Response And Provide Protection Against Invasive Klebsiella Pneumoniae Lung Infection, Shekina Gonzalez-Ferrer, Zeyu Xiong, Atish Gheware, Janet S Lee, Et Al.

2020-Current year OA Pubs

Klebsiella pneumoniae (KP) is an extracellular Gram-negative bacterium that causes infections in the lower respiratory and urinary tracts and the bloodstream. STAT1 is a master transcription factor that acts to maintain T cell quiescence under homeostatic conditions. Although STAT1 helps defend against systemic spread of acute KP intrapulmonary infection, whether STAT1 regulation of T cell homeostasis impacts pulmonary host defense during acute bacterial infection and injury is less clear. Using a clinical KP respiratory isolate and a pneumonia mouse model, we found that STAT1 deficiency led to an early neutrophil-dominant transcriptional profile and neutrophil recruitment in the lung preceding widespread …

Cep120 Is Essential For Kidney Stromal Progenitor Cell Growth And Differentiation, Ewa Langner, Tao Cheng, Eirini Kefaloyianni, Charles Gluck, Baolin Wang, Moe R Mahjoub

2020-Current year OA Pubs

Mutations in genes that disrupt centrosome structure or function can cause congenital kidney developmental defects and lead to fibrocystic pathologies. Yet, it is unclear how defective centrosome biogenesis impacts renal progenitor cell physiology. Here, we examined the consequences of impaired centrosome duplication on kidney stromal progenitor cell growth, differentiation, and fate. Conditional deletion of the ciliopathy gene Cep120, which is essential for centrosome duplication, in the stromal mesenchyme resulted in reduced abundance of interstitial lineages including pericytes, fibroblasts and mesangial cells. These phenotypes were caused by a combination of delayed mitosis, activation of the mitotic surveillance pathway leading to apoptosis, …

Non-Invasive Auricular Vagus Nerve Stimulation For Subarachnoid Hemorrhage (Navsah): Protocol For A Prospective, Triple-Blinded, Randomized Controlled Trial, Anna Huguenard, Gansheng Tan, Gabrielle Johnson, Markus Adamek, Andrew Coxon, Terrance Kummer, Joshua Osbun, Ananth Vellimana, David Limbrick, Gregory Zipfel, Peter Brunner, Eric Leuthardt

2020-Current year OA Pubs

BACKGROUND: Inflammation has been implicated in driving the morbidity associated with subarachnoid hemorrhage (SAH). Despite understanding the important role of inflammation in morbidity following SAH, there is no current effective way to modulate this deleterious response. There is a critical need for a novel approach to immunomodulation that can be safely, rapidly, and effectively deployed in SAH patients. Vagus nerve stimulation (VNS) provides a non-pharmacologic approach to immunomodulation, with prior studies demonstrating VNS can reduce systemic inflammatory markers, and VNS has had early success treating inflammatory conditions such as arthritis, sepsis, and inflammatory bowel diseases. The aim of the Non-invasive …

Referral Protocol For Women At High Risk For Breast Cancer, Ashley Johnson

Doctor of Nursing Practice (DNP)

Breast cancer is the predominant type of cancer affecting females in the United States. Individualized population screening is widely recommended to detect cancer as quickly as possible. The use of an objective risk assessment tool is endorsed to achieve a more precise, personalized breast health plan. Women at high risk for breast cancer are eligible for close surveillance with more frequent clinical exams, breast magnetic resonance imaging (MRIs), and genetic counseling and testing. At the clinical site for this DNP project, Vanderbilt Breast Center (VBC), the Breast Cancer Risk Assessment Tool (BCRAT) was completed during each mammogram visit, yet the …

Capture Of Patient-Reported Outcomes Data To Trigger A Clinical Decision Support System Feature In Chronic Obstructive Pulmonary Disease Management, Larica Brady

Doctor of Nursing Practice (DNP)

Documentation of patient symptoms directly related to chronic obstructive pulmonary disease (COPD) is primarily notated as free text within the electronic health record. This project aimed to automate the capture of patient-reported outcomes (PRO) data for improving the care of patients diagnosed with COPD. The COPD Assessment Test (CAT) questionnaire was electronically deployed in beta-testing to trigger a clinical decision support feature identified as a Best Practice Advisory (BPA). This project used a quality improvement design to enhance the clinical management of adult patients diagnosed with COPD in the ambulatory setting. The DNP student used a retrospective review of the …