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Defending Federated Recommender Systems Against Untargeted Attacks: A Contribution-Aware Robust Aggregation Scheme, Ruicheng Liang, Yuanchun Jiang, Feida Zhu, Ling Cheng, Huiwen Liu Jan 2025

Defending Federated Recommender Systems Against Untargeted Attacks: A Contribution-Aware Robust Aggregation Scheme, Ruicheng Liang, Yuanchun Jiang, Feida Zhu, Ling Cheng, Huiwen Liu

Research Collection School Of Computing and Information Systems

Federated recommender systems (FedRSs) effectively tackle the tradeoff between recommendation accuracy and privacy preservation. However, recent studies have revealed severe vulnerabilities in FedRSs, particularly against untargeted attacks seeking to undermine their overall performance. Defense methods employed in traditional recommender systems are not applicable to FedRSs, and existing robust aggregation schemes for other federated learning-based applications have proven ineffective in FedRSs. Building on the observation that malicious clients contribute negatively to the training process, we design a novel contribution-aware robust aggregation scheme to defend FedRSs against untargeted attacks, named contribution-aware Bayesian knowledge distillation aggregation (ConDA), comprising two key components for the …

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Effects Of Multitasking During Interpersonal Video Chats, Clementina Edema, Matthew W. Merkling, Gabriela Gomes, Alina Niftulaeva, Caleb T. Carr, Aimee E. Miller-Ott Jan 2025

Effects Of Multitasking During Interpersonal Video Chats, Clementina Edema, Matthew W. Merkling, Gabriela Gomes, Alina Niftulaeva, Caleb T. Carr, Aimee E. Miller-Ott

Faculty Publications - Communications

Even when engaged in synchronous dyadic video chats, individuals can be distracted from their communication partner. Drawing on the concept of crosstalk in face-to-face interactions, two studies explored the impact of a video chat partner’s distraction on perceptions of that partner’s social attractiveness, electronic propinquity, conversational immediacy, and social presence. The first study (N = 40) used a survey to have respondents recall and describe three specific prior social dyadic video chats (i.e. dyadic, dual front mediated crosstalk, collective mediated crosstalk), and then provide metrics of study variables for each episode and partner. The second study (N = …

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The Effect Of Participation In A Place-Based Engineering Learning Experience On Engineering Career Aspiration Of Nebraska’S Rural Students: A Mixed Method Study, Samereh Soleimani Babadi Jan 2025

The Effect Of Participation In A Place-Based Engineering Learning Experience On Engineering Career Aspiration Of Nebraska’S Rural Students: A Mixed Method Study, Samereh Soleimani Babadi

Department of Agricultural and Biological Systems Engineering: Masters Project Reports

This study investigates the influence of a place-based, hands-on engineering learning experience on rural middle school students' engineering career aspirations, using Social Cognitive Career Theory (SCCT) as a framework. Employing a mixed-methods approach, we explored how these localized learning experiences shape students' career goals through socio-cognitive factors such as self-efficacy, outcome expectations, goals, and interest. Quantitative analysis of pre- and post-activity surveys revealed significant increases in career aspiration scores, particularly among students from farming backgrounds and female students with initially lower expectations. Path analyses indicated that self-efficacy and interest were the strongest mediators between Place-based learning and engineering career aspirations. …

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Cultivating Quality Of Life: Assessing Diet, Physical Activity, And Mental Health Among Arab-American Breast Cancer Survivors - Uncovering Barriers And Facilitators For Holistic Well-Being, Nouf Ali Alhomaidhi Jan 2025

Cultivating Quality Of Life: Assessing Diet, Physical Activity, And Mental Health Among Arab-American Breast Cancer Survivors - Uncovering Barriers And Facilitators For Holistic Well-Being, Nouf Ali Alhomaidhi

CGU Theses & Dissertations

This dissertation examines the quality of life among Arab-American breast cancer survivors, with a particular emphasis on dietary practices, physical activity, and mental health. Despite increasing survivorship rates in this population, there remains a significant gap in the literature addressing their unique post-treatment experiences and needs. Employing a convergent parallel mixed-methods design, this study integrates quantitative survey data and qualitative narrative interviews to assess adherence to health behavior guidelines and to identify culturally specific barriers and facilitators to well-being. Quantitative findings indicated suboptimal adherence to recommended dietary and physical activity guidelines and highlighted prevalent psychological distress among participants. Thematic analysis …

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Marked By Valor: The “Lost” History Of The 6th United States Colored Troops, Heavy Artillery, Daniel William O’Sullivan Jan 2025

Marked By Valor: The “Lost” History Of The 6th United States Colored Troops, Heavy Artillery, Daniel William O’Sullivan

CGU Theses & Dissertations

“Marked by Valor: The ‘Lost’ History of the 6 th U.S.C.T., Heavy Artillery,” argues that the camaraderie of having been a Black Union soldier solidified a sub-culture of Black veterans and their families in Natchez, Mississippi, that cohered throughout the Reconstruction period using the tools and the affiliations first gained in slavery and strengthened during the soldiers’ time in the army. Underlying this narrative is an interpretation of Southern history that maintains that we cannot understand the events of the postwar period—not only for Black veterans, but to some extent all freed people—if we do not understand all that came …

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The Role Of Social Media In Students’ Learning: Perceptions From The Us And China, Jia Pang Jan 2025

The Role Of Social Media In Students’ Learning: Perceptions From The Us And China, Jia Pang

CGU Theses & Dissertations

In an era where digital technologies permeate nearly every aspect of daily life, social media emerged as a powerful yet contentious tool in education. This study aims to addresses the broader challenge of understanding how social media reshapes student learning experiences, both positively and negatively, in an increasingly interconnected and information-driven world. The theoretical framework of this qualitative study is built on the principles of connectivism and Phillips’s Model. The data sources for this study include interview data from 30 participants in the United States and China, as well as university policy documents related to social media usage from universities …

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An Evolving Standard Of Decency: Examining The American Juvenile Justice System And The Constitutionality Of Youth Incarceration, Mark S. Smith Jan 2025

An Evolving Standard Of Decency: Examining The American Juvenile Justice System And The Constitutionality Of Youth Incarceration, Mark S. Smith

CGU Theses & Dissertations

The United States incarcerates more children and adolescents than any other developed nation in the world. Studies have shown that juvenile detention is generally ineffective at rehabilitating delinquent youth, which places the practice at odds with the stated intent of modern juvenile justice. Similar to the adult criminal justice system, there is a significant and widespread disparity in the incarceration rate between that of minority youth and their white counterparts in the juvenile system. Finally, a substantial and growing body of medical and behavioral research concludes that trauma associated with juvenile detention can cause long-term or even lifetime negative neurological …

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Geometric Dimensionality Reduction, Daniel Livschitz Jan 2025

Geometric Dimensionality Reduction, Daniel Livschitz

CGU Theses & Dissertations

The emergence of AI models developed through computationally intensive training has resulted in a surge of research into dimensionality reduction techniques that spans across numerous mathematical disciplines. In this thesis we establish Geometric Dimensionality Reduction, a non-linear data compression technique that utilizes low dimensional manifolds embedded in dimensional spaces to form composite contraction-and-projection maps. Geometric Dimensionality Reduction is predominantly demonstrated through a novel algorithm entitled LGE (Livschitz-Gu-Eyunni) that utilizes Multicomplex rotation groups and polyspherical coordinates to define a single tuneable logarithmic map from ℝ 2푛 to ℝ 푛+1 with deterministic time complexity, geometric tunability, and semi-reversibility. Significant breakthroughs in the …

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Reproductive Refugees: The Legacy Of The One Child Policy On Chinese Refugees In The United States, Brianna Michelle Chan-George Jan 2025

Reproductive Refugees: The Legacy Of The One Child Policy On Chinese Refugees In The United States, Brianna Michelle Chan-George

CGU Theses & Dissertations

This paper analyzes the cases of Chinese refugees who were running from the People of Republic of China’s (PRC) one child policy to the United States from 1993-1995. I argue that the process of the one child policy’s enforcement to the asylum cases in the United States was a messy and confusing process. The legal definitions, understandings and practices of both the United States and the PRC were inconsistent and contradictory.

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Innovating Government The Open Way: Modeling The Open Data Ecosystem, Jeanne Holm Jan 2025

Innovating Government The Open Way: Modeling The Open Data Ecosystem, Jeanne Holm

CGU Theses & Dissertations

Governments around the world are releasing open data with the aim of stimulating innovation, driving economic development, and advancing social good. Despite significant investment in data infrastructure and technology, many open data initiatives struggle to effectively engage stakeholders or deliver on their intended outcomes. Thus, this dissertation targets the research question: How can a human-centered open government data ecosystem be modeled to ensure that stakeholders are engaged and find data? It also explores which stakeholders should be engaged and what methods are most effective in engaging them. To address the research questions, this dissertation adopts a design science methodology and …

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Creating & Validating A Teacher Resilience Scale In The U.S. Context, Joy Mccreary Jan 2025

Creating & Validating A Teacher Resilience Scale In The U.S. Context, Joy Mccreary

CGU Theses & Dissertations

The teaching force faces significant challenges, including high attrition rates and an aging workforce, exacerbated by the COVID-19 pandemic. Prior research highlights teacher resilience as a critical factor in addressing these challenges, emphasizing its multi-dimensional and contextual nature. While several international scales have been developed to measure teacher resilience, none exist tailored to the unique educational landscape of the United States. This study developed and validated a U.S.-specific Teacher Resilience Scale (USMTRS), confirming its strong reliability and multidimensional structure. Findings showed that teacher resilience is widespread and most strongly tied to job satisfaction, while only weakly related to burnout. Results …

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Unseen Journeying: Latinx Mothers’ Experiences And Navigation Of Pre-Referral Home-School Collaboration, Yoné Rodríguez Jan 2025

Unseen Journeying: Latinx Mothers’ Experiences And Navigation Of Pre-Referral Home-School Collaboration, Yoné Rodríguez

CGU Theses & Dissertations

Research has documented various home-school collaboration obstacles faced by Latinx mothers whose children receive special education services. However, minimal attention has focused on Latinx mothers of students in the pre-referral stage—the time when students facing significant academic difficulties may be struggling in the classroom but have not yet been referred to special education evaluation. Responding to this gap in the literature, this qualitative study investigated how Latinx mothers experienced and navigated pre-referral home-school collaboration, which was conceptualized as the dynamic process occurring between family members and school personnel working towards common goals related to student growth. In alignment with Chicana …

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A Conspiratorial Republic: The Societal And Political Impact Of Conspiratorial Knowledge In The Early Nineteenth-Century United States, Kylee Nikole Robinson Jan 2025

A Conspiratorial Republic: The Societal And Political Impact Of Conspiratorial Knowledge In The Early Nineteenth-Century United States, Kylee Nikole Robinson

CGU Theses & Dissertations

This thesis argues that the American conspiratorial worldview identified by Bernard Bailyn during the American Revolution persisted well into the early American republic period, having a significant impact on early republic society. Drawing on Michael Butter’s study of conspiracy theories, this study examines how early Americans continued to view republican government as inherently fragile and continuously under threat from corrupting forces. This conspiratorial belief established the common American worldviews that the right to personal representation and personal liberties were constantly at risk. Ultimately, this mindset influenced major political developments in the early republic period including the decision to declare war …

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Declarative Design For Spatial Analysis Models, Yassine Elouri Jan 2025

Declarative Design For Spatial Analysis Models, Yassine Elouri

CGU Theses & Dissertations

Geographic Information Systems (GIS) have become indispensable tools in addressing complex spatial challenges across diverse domains, including urban planning, environmental conservation, and climate change. However, the technical expertise required to use GIS effectively, particularly proficiency in general-purpose programming languages (GPLs), remains a significant barrier to broader adoption. Domain-Specific Languages (DSLs) have proven to lower this barrier by offering tailored abstractions that simplify problem-solving in specific domains. Despite their potential, the GIS domain lacks a formal DSL framework that bridges the gap between the design of spatial analysis models and their practical implementation. This research addresses this gap by proposing Gaia, …

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Feedback Loops: Challenge & Recovery, Patrick Barry Jan 2025

Feedback Loops: Challenge & Recovery, Patrick Barry

Articles

About halfway through the course on feedback I teach to law students, I tell them to take out their calendar and look over their recent schedule. How many days in the previous few weeks, I ask them, felt like "challenge days"? I explain that challenge days are days when you have to perform at a high level, whether because a major task requires a lot of your energy and mental bandwidth-studying for a big test, preparing for a tough negotiation, dealing with an unexpected family crisis-or because the time available to handle a lot of minor tasks seems cruelly inadequate. …

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“Being Natural Is Simply A Pose”: The Concept Of Foucault’S Panopticon In The Picture Of Dorian Gray And Orlando, Mya Corcoran Jan 2025

“Being Natural Is Simply A Pose”: The Concept Of Foucault’S Panopticon In The Picture Of Dorian Gray And Orlando, Mya Corcoran

The Oswald Review: An International Journal of Undergraduate Research and Criticism in the Discipline of English

No abstract provided.

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Comparing The Representations Of Order And Behavior In James Joyce’S “The Dead” And Samuel Beckett’S Endgame, Araav Thakker Jan 2025

Comparing The Representations Of Order And Behavior In James Joyce’S “The Dead” And Samuel Beckett’S Endgame, Araav Thakker

The Oswald Review: An International Journal of Undergraduate Research and Criticism in the Discipline of English

No abstract provided.

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Inoffensively Alice: Gender Politics In The Alice Series, Eirian Gail Wells Jan 2025

Inoffensively Alice: Gender Politics In The Alice Series, Eirian Gail Wells

The Oswald Review: An International Journal of Undergraduate Research and Criticism in the Discipline of English

No abstract provided.

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The Oswald Review Of Undergraduate Research And Criticism In The Discipline Of English: Volume 27, 2025 Jan 2025

The Oswald Review Of Undergraduate Research And Criticism In The Discipline Of English: Volume 27, 2025

The Oswald Review: An International Journal of Undergraduate Research and Criticism in the Discipline of English

No abstract provided.

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America's Forgotten History Of Constitutional Crisis, Marcus A. Gadson Jan 2025

America's Forgotten History Of Constitutional Crisis, Marcus A. Gadson

Faculty Publications

Scholars have insisted that constitutional crisis is rare in American history. They are wrong. Constitutional crisis has been one of the most important constants in American history. The events of January 6, 2021, the assassination attempt on President Trump, and the debate about whether to invoke the Twenty-Fifth Amendment to force President Biden out of office are child’s play compared to the constitutional crises this country has endured. Those observations are only surprising because so few scholars have studied constitutional crises at the state level. They are focused on national and international constitutional crises. This Article has three goals. First, …

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Predicting Superconducting Critical Temperature From Composition-Derived Features: A Transparent Linear And Regularized Regression Study, Md Ahiduzzaman Jan 2025

Predicting Superconducting Critical Temperature From Composition-Derived Features: A Transparent Linear And Regularized Regression Study, Md Ahiduzzaman

Data Science and Data Mining

We study prediction of superconducting critical temperature (Tc) from 81 composition-derived descriptors across 21,263 materials. To keep the analysis transparent and repro- ducible, we focus on linear models: Ordinary Least Squares (OLS), Ridge, Lasso, and Elastic Net (ENet). All models share a single evaluation protocol (5-fold cross-validation with standardized inputs) and are compared on RMSE, MAE, and R2. On this feature set, OLS attains the best cross-validated performance (RMSE = 17.6 K, MAE = 13.3 K , R2 = 0.735), with Lasso/ENet essentially tied next (RMSE ≈ 17.7 K , R2 ≈ 0.734); Ridge underperforms (RMSE = 18.9 K , …

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Comparative Analysis Of Lasso, Ridge, And Elastic Net For Variable Selection In High-Dimensional Maize Data, Md Ahiduzzaman Jan 2025

Comparative Analysis Of Lasso, Ridge, And Elastic Net For Variable Selection In High-Dimensional Maize Data, Md Ahiduzzaman

Data Science and Data Mining

In high-dimensional genomic data analysis, traditional linear regression techniques often struggle due to the presence of a large number of predictor variables relative to observations. Penalized regression methods such as LASSO, Ridge, and Elastic Net have emerged as effective solutions by imposing regularization, which helps in managing multicollinearity and enhancing prediction accuracy. This study applies these techniques to the Maize dataset to model the time to male flowering, selecting relevant genetic markers as predictors. Our findings suggest that Elastic Net is particularly effective for high-dimensional data with correlated variables, achieving a balance between prediction accuracy and variable selection. The results …

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Handwritten Digit Recognition Using Machine Learning Classifiers, Md Ahiduzzaman Jan 2025

Handwritten Digit Recognition Using Machine Learning Classifiers, Md Ahiduzzaman

Data Science and Data Mining

This project explores and compares the performance of various machine learning classifiers for handwritten digit recognition using the MNIST dataset. The classifiers include Logistic Regression, k-Nearest Neighbors, and Convolutional Neural Networks. Each classifier is evaluated based on accuracy, precision, recall, F1-score, and confusion matrix analysis.

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Multimodal Feature Fusion And Machine Learning For Adhd Detection Using Neuroimaging Data, Isabel Pham Jan 2025

Multimodal Feature Fusion And Machine Learning For Adhd Detection Using Neuroimaging Data, Isabel Pham

Master's Projects

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopment disorder that can significantly affect a person’s attention, impulse control, and executive function. Currently, the traditional diagnosis method often relies on clinical assessments and observations. However, these methods can be subjective and lead to inconsistencies in diagnosis between individuals. To address this challenge, neuroimaging and machine learning (ML) are promising tools for providing a more objective diagnosis of ADHD. The goal of this project is to apply a multimodal approach in which structural and functional features of specific regions of the brain are used to develop a more accurate and objective …

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Simple Vs. Complex Human Activity Classification Via Hybrid Machine Learning Models, Anusha Kukreja Jan 2025

Simple Vs. Complex Human Activity Classification Via Hybrid Machine Learning Models, Anusha Kukreja

Master's Projects

In-depth understanding of the complexity of daily human activities is crucial for building responsive health monitoring and assistive technologies. However, limited research has focused on distinguishing activities based on their involvement level, as most existing work classifies only the type of activity performed. In this thesis, we address this gap by proposing a method to classify human activities as either simple or complex using sensor data from the Opportunity dataset. We define complex activities as those involving object interactions or multiple coordinated movements (e.g., drinking from a cup, cleaning a table), and simple activities as static or low-effort postures (e.g., …

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On The Adversarial Robustness Of Quantized Neural Networks Against Common Adversaries In Time-Series Forecasting, Maanak Arora Jan 2025

On The Adversarial Robustness Of Quantized Neural Networks Against Common Adversaries In Time-Series Forecasting, Maanak Arora

Master's Projects

Real-world edge applications now use modern machine learning models which require both resource efficiency and robustness against adversarial threats. Deep neural networks which include time series forecasting models still face risks from adversarial perturbations while quantization techniques used for memory and compute efficiency create unpredictable robustness challenges. This project investigates the adversarial resistance of Long Short-Term Memory (LSTM) models after applying post-training quantization at three different precision levels: 16-bit floating point (FP16), 8-bit integer (INT8) and custom 4-bit quantization. The Jena Climate dataset serves as our main benchmark for training a fullprecision LSTM model followed by multiple quantization strategies which …

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Physiotrack: A Gamified Physiotherapy System, Pranavi Chaturvedula Jan 2025

Physiotrack: A Gamified Physiotherapy System, Pranavi Chaturvedula

Master's Projects

Traditional physiotherapy methods tend to be non-interactive and provide little to no personalized instruction, even though physiotherapy is critical to stroke recovery. This thesis explores a fully adaptive, sensor-based, feedback architecture intended for stroke patients which remotely supervises movement and personalizes exercises enabled by multimodal sensors. The system uses filtering and windowed segmentation of accelerometer and skeletal data to compute features like jerk, speed, and joint movement angular range. A game engine applies accelerometer and skeletal features together with optimized, lightweight ML models to drive adaptive feedback, scoring, and difficulty adjustment. The architecture supports responsive continuous sensor streaming within the …

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Performance Comparison Of Machine Learning Across Metal, Cuda, And Neuromorphic Frameworks, Ryan Saini Jan 2025

Performance Comparison Of Machine Learning Across Metal, Cuda, And Neuromorphic Frameworks, Ryan Saini

Master's Projects

Machine learning’s computational demands necessitate optimal performance and utilization. This research compares Apple Silicon M3 Pro with MPS, NVIDIA RTX 3070 GPU with CUDA, and neuromorphic computing for machine learning methods. We provide a cross-platform and cross-architecture performance analysis of machine learning methods to identify optimal configurations for training and inference scenarios. On traditional neural networks, Apple Silicon with MPS delivers superior energy efficiency at the cost of longer processing times for training and inference. NVIDIA with CUDA offers faster computation in training and inference at higher energy costs. Convolutional spiking neural networks perform competitively on event-based data, particularly on …

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Why We Need To Fill In Our Mixed-Use Communities’ Business Vacancies And How We Can Do That, Victor Huynh Jan 2025

Why We Need To Fill In Our Mixed-Use Communities’ Business Vacancies And How We Can Do That, Victor Huynh

Master's Projects

This planning report provides an in-depth exploration as to why so many mixed use communities, including transit-oriented developments, in metropolitan regions across the country are facing challenges with filling in their retail business vacancies at the ground floor. It also provides a current snapshot of best practices to remedy this widespread barrier to cities functioning more effectively and sustainably. This report provides a combination of findings from a literature review which identifies the most common reasons and remedies for business vacancies, and a research design which identifies which urban planning or urban design characteristics correlate most frequently with case sites …

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Uninterruptable Non-Isolated Integrated Power Electronics Converter (Unipec) For Commercial Truck Auxiliary Power Unit, Pouya Zolfi, Ahmad Alzahrani, Ayman M. El-Refaie Jan 2025

Uninterruptable Non-Isolated Integrated Power Electronics Converter (Unipec) For Commercial Truck Auxiliary Power Unit, Pouya Zolfi, Ahmad Alzahrani, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

A low component count high efficiency and high-power density three-port DC-DC converter named UNIPEC is introduced for commercial trucks auxiliary power unit (APU) application. The proposed UNIPEC is a single magnetic core topology which is achieved by integration and modification of switched capacitor technology and bidirectional multi-level DC-DC converter. With peak simulation efficiency of 97.3% and power density of 12.6 kW/L, proposed unit is an attractive candidate for conventional and refrigerated freight transportation applications. Comparison study and low power experimental validation results are presented. Reliability analysis of UNIPEC is also conducted and mean time to failure (MTTF) reported. A 1 …

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