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Turkish Journal of Electrical Engineering and Computer Sciences

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Energetics Analysis Of Solitary Waves Using A Multi-Layer Model, Hunter Boswell, Frank D. Han, Guirong Yan, Wouter Mostert

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study investigates the performance of a vertically-Lagrangian multi-layer model on numerically simulating shoaling and breaking two-dimensional solitary waves during both the breaking and post-breaking processes. The energy dissipation of the breaking event for the multi-layer waves is analyzed and compared to prior direct numerical simulation work with the same bathymetric and wave cases. It shows very similar data collapse to shallow-water inertial theory. For post-breaking behavior, bore characteristics are compared to an experimental study of bores formed from breaking solitary waves and similar results are found. While the multi-layer method was not found to behave sufficiently well for direct …

Distributed Model Predictive Control-Based Power Management Scheme For Grid-Integrated Microgrids, Sergio Escareno, Sijo Augustine, Liang Sun, Sathishkumar J. Ranade, Olga Lavrava, Enrico Pontelli, John Hedengren

Faculty Publications

Transitioning from traditional electrical grids to smart grids is currently an ongoing process that many nations are striving for due to their access to renewable resources. Energy management is one of the key parameters that decides the performance of such complex systems. Distributed Model Predictive Control (DMPC) is a promising technique that can be used to improve the energy management of grid-connected systems. This paper analyzes a grid-connected inverter system with DMPC that exchanges key operating parameters with the grid to optimize coordinated power sharing between its respective loads. The state-space model for the inverter is derived and verified to …

A Longitudinal Study Of Performance And Workload In Military Flight Training, Kristen Fitzgerald Biondich

Doctoral Dissertations and Projects

The purpose of this quantitative longitudinal research study of aircrew undergoing transition training was to examine the relationships between progressive syllabus events and aircrew performance, and progressive syllabus events and workload. In military aviation, the transition from one platform to another can present significant challenges to aircrew, especially regarding task saturation and performance. Previous research has suggested methods for improving the practice of flight training but has not investigated the emerging OA-1K mission and platform. The OA-1K is a modified Air Tractor AT-802U, a rugged, single-engine turboprop aircraft that is intended for use flying light attack and reconnaissance missions. This …

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi

Harrisburg University Other Works

This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …

Reproducible Semantic Data Management Workflow For Materials Data Science: Generating Knowledge Graphs With Robust Fairifcation Pipelines, Kyle R. Henrikson, Van D. Tran, Meredith Francis, Isabella Giammattei, Quynh D. Tran, Laura S. Bruckman, Erika I. Barcelos, Roger H. French

Student Scholarship

Combining data from multiple sources is crucial for efficient knowledge aggregation in materials data science. FAIR data from ontology and Linked Data principles enable this. Semantic data management streamlines data exchange and aggregation, ensuring information is available and extractable. FAIRLinked and GraphDB provide solutions for consolidating, hosting, and extracting meaningful insight from multimodal data.

Influence Of Co2 Curing On Carbonation Depth, Phase Composition, And Micro-Mechanical Properties Of Fbc Ash-Blended Cementitious Materials, Heejung Jun, Seongho Han, Sanghwon Wi, Jinyoung Yoon

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study investigates the physicochemical and mechanical performance of cementitious composites incorporating fluidized bed combustion (FBC) ash under accelerated carbon dioxide (CO₂) curing. FBC ash, due to its high contents of free calcium oxide (CaO) and sulfate (SO₃), has been reported to cause challenges, such as volume instability and lower early-age strength. To address these limitations, CO2 curing was applied to promote accelerated carbonation and stabilize the hydration products. Cement paste and mortar samples, made with up to 40 % by cement weight replacement with FBC ash (labelled CF), were subjected to either CO₂ curing …

Tuning Oxygen Reduction Kinetics In Lasrcoo4 With Strained Epitaxial Thin Films And Wrinkled Freestanding Membranes, Habib Rostaghi Chalaki, Ebenezer Sessi, Mohammad El Loubani, Dongkyu Lee

Faculty Publications

Sluggish oxygen reduction reaction (ORR) remains a critical barrier to advancing intermediate-temperature electrochemical energy devices. Here, we demonstrate that strain engineering in two platforms, epitaxial thin films and freestanding membranes, systematically tunes ORR kinetics in Ruddlesden-Popper LaSrCoO4. In epitaxial films, film thickness is varied to control in-plane tensile strain, whereas in freestanding membranes strain relaxation during the release step using water-soluble sacrificial layers produces flat or wrinkled architectures. Electrochemical impedance spectroscopy analysis reveals more than an order of magnitude increase in the oxygen surface exchange coefficient for tensile-strained films relative to relaxed films, together with a larger oxygen vacancy concentration. …

Accuracy Of Glenohumeral Joint Center Of Rotation Estimates Using Traditional Motion Capture Versus Bi-Plane Fluoroscopy, Julia A. Dunn, Ola Alsaadi, Kevin Shelburne, Michelle B. Sabick

Mechanical and Materials Engineering: Faculty Scholarship

Accurate estimation of the glenohumeral joint center of rotation is critical for biomechanical modeling of shoulder motion. This study evaluated the accuracy of three predictive methods for estimating glenohumeral joint center of rotation using optical motion capture, compared against a benchmark derived from synchronous bi-plane fluoroscopy. Five healthy adults performed shoulder abduction, flexion, and external rotation in 90° abducted and adducted positions. Root mean square error and axial errors were calculated across the full range of motion. Results showed that none of the predictive methods met clinically acceptable thresholds, with absolute error exceeding 10 mm and axial errors surpassing ±5 …

Molecular Survival Strategies Against Kidney Filtration: Implications For Therapeutic Protein Engineering, William Heaps, Anna Elise Packard, Kristina M. Mccammon, Tyler P. Green, Joseph P. Talley, Bradley C. Bundy, Dennis Della Corte

Faculty Publications

The glomerular filtration barrier poses a significant challenge for circulating proteins, with molecules below ~60–70 kDa facing rapid renal clearance. Endogenous proteins have evolved sophisticated evasion mechanisms including oligomerization, carrier binding, electrostatic repulsion, and FcRn-mediated recycling. Understanding these natural strategies provides blueprints for engineering therapeutic proteins with improved pharmacokinetics. This review examines how endogenous proteins resist filtration, evaluates their application in protein engineering, and discusses clinical translation including established technologies (PEGylation, Fc-fusion) and emerging strategies (albumin-binding domains, glycoengineering). We address critical challenges of balancing half-life extension with tissue penetration, biological activity, and immunogenicity—essential considerations for the rational design of next-generation …

A Review Of Routing Attacks In Routing Protocol Over Low-Power And Lossy-Based Iot Networks, Lanka Chris Sejaphala Mr., Vusimuzi Malele Prof, Francis Lugayizi Prof.

Journal of Cybersecurity Education, Research and Practice

Low-power and Lossy IoT Networks (LLNs) comprise physical sensors, processing capability, power, and other technologies to exchange information between systems and devices over the internet. However, these networks are susceptible to routing attacks affecting resources, traffic flow, and topology formation. In the related work, it has been discovered that many previous studies do not consider algorithms and implementation approaches for routing attacks. This research study provides a comprehensive in-depth synthesis insight into the description, effects, and algorithms & implementation of four routing attacks in LLNs i.e., rank, sinkhole, DIS-flooding, and worst parent attacks. The findings of this research study highlight …

Insight Into The Decalcification Mechanism Of Calcium Silicate Hydrate Under A Water–Heat–Salt Environment, Wei Zhang, Boya Zhang, Jia Sun, Juntao Dang, Xiangke Guo, Keliang Li, Bo Tao Huang, Biqin Dong, Hongyan Ma, Dongshuai Hou

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Understanding the decalcification mechanism of calcium silicate hydrate (C–S–H) under marine environments is crucial for concrete durability. In this study, the decalcification behavior of C–S–H under a water–heat–salt environment was systematically investigated through immersion experiments and reactive molecular dynamics simulations. Experimental results showed that elevated temperature and NaCl solution significantly accelerated Ca leaching and reduced the Ca/Si ratio of C–S–H. Simulation results further revealed that both high temperature and NaCl reduce the dissolution free energy of Ca, making its release more thermodynamically and kinetically favorable. Local structure analysis indicated that Cl^– disrupts Ca–Os (O atoms in silicate tetrahedra) connection …

Robust And High-Efficiency Demodulation Of Ultra-Weak Fbg Arrays In Ofdr-Based Distributed Sensing, Zhaopeng Zhang, Yuxuan Cao, Xu Liu, Dingcheng Wang, Bo Liu, Chen Zhu

Electrical and Computer Engineering Faculty Research & Creative Works

A robust and high-efficiency demodulation scheme for optical frequency domain reflectometry (OFDR) based ultra-weak fiber Bragg grating (UWFBG) array detection system, originating from the Buneman frequency estimation (BFE) algorithm, is proposed and experimentally demonstrated. Due to the current limitations and imperfections of FBG inscription technology, the quasi-continuous inscription approach, along with its less-than-ideal outcomes, gives rise to problems of grating spectrum splitting and spectral distortion during the grating demodulation process. This renders the traditional approach of directly applying the BFE algorithm for grating demodulation ineffective, despite its significant enhancement of demodulation efficiency. To address this issue, we propose utilizing the …

Reformulation Of The Protein Databank For Real-Time Search Of Geometrical Attributes Of Protein Structures, Musa Azeem, Christopher Lee, Aaron Hein, Christopher Ott, Homayoun Valafar

Faculty Publications

Introduction:

In this study, we introduce the design and implementation of PDBMine, a large-scale, queryable platform for mining sequence-structure statistics from the Protein Data Bank (PDB). PDBMine enables rapid analysis of local conformational trends across proteins by extracting dihedral angles and sequence patterns at scale. In addition to the design and implementation of PDBMine, we also present results validating its ability to return structurally meaningful information.

Methods:

We first assess the accuracy of its dihedral angle distributions by comparing them to established Ramachandran space and verifying expected behaviors of residues such as glycine and proline. We then use PDBMine to …

Jiving With Llms: Assessing First Year Students’ Computer Programming Self Efficacy After Reading Code With Llms, Michelle Jarvie-Eggart, Joseph Roy Teahen, Daniel T. Masker, Jose Padilla, Leo C. Ureel Ii, Laura E. Brown, Scott Pomerville, Jon Sticken

Michigan Tech Publications

This study investigated the impact of leveraging generative artificial intelligence (GenAI) to assist 1st-year engineering and computer science (CS) students in reading code in a new (to them) language. Students were asked to comment code in FORTRAN. They were then asked to run the code through ChatGPT-4.0 for its comments and reflect on what they learned from the experience. Participants completed survey items from Ramalingam and Wiedenbeck’s Computer Programming Self-Efficacy Scale (CPSES) prior to and after the intervention. Additional open-ended reflective (qualitative) questions were added to the quantitative questions in the postintervention questionnaire. This study documents increases in self-efficacy for …

Temperature Dependent High Frequency Performance Of A 62% Algan Channel Hemt, Jiahao Chen, Abdullah Al Mamun Mazumder, Parthasarathy Seshadri, Dheekshinn Nandakumar, Ruixin Bai, Rafael Andrew Choudhury, M. Asif Khan, Chirag Gupta

Faculty Publications

This article reports on the temperature dependent performance of a HEMT with an Al_0.62Ga_0.38N channel layer and an Al_0.84Ga_0.16N barrier layer grown by metal–organic chemical vapor deposition. The device in this report was measured at room temperature and elevated temperatures of 100–150 °C. The sheet resistance increased from 3.5 kΩ/sq (25 °C) to 5.4 kΩ/sq (150 °C), while the contact resistance remained nominally similar. For a device with 160 nm gate length and 2 µm source-to-drain length, excellent electrical characteristics have been achieved when the device was operated at 150 °C with …

A Contextual Attention-Based Transformer Model For Enhanced Hate Speech Detection On Twitter, Mira Mansour, Nancy Akoum, Seifedine Kadry

Iraqi Journal for Computer Science and Mathematics

Hate speech on social media poses significant societal challenges, necessitating accurate and context-sensitive automated detection. Traditional machine learning (ML) models typically rely on lexical or superficial features, limiting their ability to capture nuanced or contextually ambiguous expressions of hate speech. Recent transformer-based methods (e.g., RoBERTa) provide improved contextual understanding but often lack explicit mechanisms guiding the model’s attention to critical semantic tokens, thereby reducing interpretability and sensitivity to nuanced linguistic contexts. This paper introduces a novel contextual attention-guided transformer model that explicitly incorporates lexicon-guided attention supervision into RoBERTa fine-tuning, significantly enhancing semantic precision in hate speech detection on Twitter. Evaluations …

Numerical Solution Of A Coupled Nonlinear Dynamic Problem Of Thermoviscoelasticity, Abdali Abdukarimov, Ibodat Turabekovna Khaldybaeva, Askarova Shamshetdinovna Ayjamal

Technical science and innovation

This paper presents a numerical solution of a coupled nonlinear dynamic problem of thermoviscoelasticity. A Duffing-type oscillator with temperature-dependent properties is used to model nonlinear hereditary deformable systems. After specifying the temperature dependences of the elastic modulus 𝐸 and viscosity parameter 𝜂 and introducing dimensionless variables, the problem is reduced to a system of nonlinear integro-differential equations. A numerical procedure for solving this system is developed, and representative examples are computed. The results are presented in graphical form for various values of the governing parameters.

Precision Acoustofluidics For High-Throughput Mechanobiology In Suspension Cells, Kaichun Yang, Ruoyu Zhong, Ke Li, John Mai, Pengzhan Liu, Ye He, Joseph Rich, Ying Chen, Janna Wang, Zhiteng Ma, Zhiteng Ma, Xianchen Xu, Qian Wu, Tony Jun Huang

Faculty Publications

Mechanomodulation, the process of altering cellular behavior through applied mechanical forces, plays a critical role in physiological processes and has substantial implications for cancer therapy, immunology, and drug development. However, precise and efficient stimulation of nonadherent cells remains a major challenge, limiting the investigation of mechanotransduction pathways and the development of targeted therapeutics. Here, we developed an acoustofluidic platform named Suspension-cell Targeted Response to Excitation via Acoustofluidic Mechanomodulation (STREAM) to enable precise, high-throughput stimulation of suspension cells. STREAM accomplishes this using 101.14-megahertz high-frequency surface acoustic waves to deliver controlled mechanical stimulation at a throughput of 500,000 cells per minute. STREAM …

Pengujian High Fidelity Prototipe Media Pembelajaran Interaktif Bahasa Inggris Dengan Gamifikasi Menggunakan User Experience Questionare, Adhitya Prastyadi, Meizano Muhammad Ardhi, Daniel Rinaldi, Margaretha Karolina Sagala

Jurnal Sosial Humaniora Terapan

Abstract

Testing a Hi-Fi Prototype of Interactive English Learning Media with Gamification Using UEQ

This study aims to test and evaluate the User Experience (UX) quality of a High-Fidelity prototype for interactive English learning media integrating gamification elements. The research is motivated by the low English proficiency and motivation among Indonesian students, and the potential of digital media and gamification to enhance learning engagement. Inspired by the success of the Duolingo application, this prototype was designed to create an enjoyable and effective learning experience. A quantitative research methodology was employed, involving high school students as participants selected via purposive sampling. …

Integrated Optimization Of Underground Mine Ventilation Using Hardy Cross, Monte Carlo Simulations, And Machine Learning Techniques: A Step Toward Sustainable Mining, Hussein A. Saleem

Journal of Sustainable Mining

Underground mine ventilation is crucial for ensuring worker safety, air quality, and operational efficiency. Effective optimization of ventilation systems reduces energy consumption, enhances airflow distribution, and minimizes risks associated with harmful gases and fire hazards. This study proposed an integrated framework combining the Hardy Cross (HC) method, Monte Carlo (MC) simulations, and machine learning (ML) techniques to optimize the ventilation system at the Jabal Sayid mine in Saudi Arabia. The HC method was employed to provide deterministic baseline airflow calculations, while the MC simulations accounted for uncertainties in resistance values and environmental conditions, generating probabilistic distributions of key parameters. Among …

Universal Sound Separation: Distance-Aware Mixture Simulation, Co-Occurrence Conditioning, And Chain-Of-Inference, Wonjun Park

Computer Science and Engineering Theses - Archive

Universal Sound Separation (USS) -- the task of disentangling arbitrary sound sources from a single-channel acoustic mixture -- remains an open challenge due to the ill-posed nature of the problem and the distributional gap between synthetic training data and real-world recordings. This thesis addresses three distinct bottlenecks in the USS pipeline: training data realism, inference strategy, and conditioning richness. We first present two knowledge-guided approaches to sound source separation. The first is a distance-aware mixing strategy that leverages Large Language Models (LLMs) to assign plausible loudness relationships between audio sources during training data synthesis. By querying an LLM about the …

Data-Driven Prediction Of Concrete Bridge Deck Corrosion Using Ground Penetrating Radar (Gpr), Nafisa Shafiullah

Civil Engineering Theses

Corrosion detection remains a crucial factor in the proper maintenance of Reinforced Concrete (RC) structures. While several studies have used Ground Penetrating Radar (GPR) for corrosion detection, quantitative models for prediction are still limited. This study presents an approach for the quantitative prediction of rebar corrosion in concrete using GPR data obtained from a prior experimental program involving accelerated corrosion. A total of 36 RC samples were cast, varying in cover depth, rebar diameter, and concrete porosity. The samples were subjected to an impressed current of 0.65 A in a 5% NaCl solution over three phases: 10, 20, and 30 …

A. Vs. I In Ai: Is There A Threshold To "Engineered" Intelligence?, Joshit Mohanty

Engineering Management & Systems Engineering Faculty Publications

Despite artificial intelligence reshaping the world, its development generates uncertainties regarding future capabilities. AI simultaneously exists as an artifact of engineering design and as autonomous intelligence, creating an observer-participant feedback loop. This paper proposes that embodied AI faces a bandwidth-limited intelligence threshold T_h that it arises from B = min(C_sens,C_Act). However, Shannon capacity measures bits while intelligence operates on concepts, necessitating a dual-channel model separating physical bandwidth B_io from representational capacity B_rep. Intelligence emerges as multi-dimensional rather than scalar, with components exhibiting different bandwidth dependencies. Surpassing T_h requires either new sensing methods expanding B, enhanced representational frameworks, or reconceptualization within …

A Literature Review And Conceptual Framework For Sustainability In Open-Pit Mine Planning, Raymond Kudzawu-D'Pherdd, Kwame Awuah-Offei, Esteban Koberg De La Cruz, Marcos Goycoolea, Andrea Brickey, Alexandra M. Newman

Mining Engineering Faculty Research & Creative Works

This paper presents a comprehensive literature review and a conceptual framework for integrating environmental sustainability into strategic mine planning, focusing on open pits. Despite growing interest, easily discernible sustainability metrics remain elusive in early mine-planning stages, and are included as a post-processing step, if at all, rather than integrated a priori into a mine plan via, e.g., optimization. Through a literature review, we identify efforts regarding how environmental dimensions, such as emissions, water use, and land rehabilitation, are addressed across mine planning phases. We propose the Environmental Stewardship and Sustainability Framework for Mine Planning, which: (i) embeds sustainability into decision …

Set-Theoretic Reachability-Informed Model Predictive Control For Mechanical And Aerospace Systems, Jinaykumar Nitinkumar Patel

Mechanical and Aerospace Engineering Dissertations

Modern mechanical and aerospace systems increasingly operate autonomously in environments characterized by nonlinear dynamics, uncertainty, and safety constraints. In these settings, estimation and control methods based on nominal models and single-point trajectory predictions are usually insufficient to ensure safe and reliable operation. This dissertation uses a set-theoretic perspective, in which the system state, uncertainty, and admissible behavior are described by sets instead of point estimates. The key question is not only what the state is, but what set of states remains consistent with the dynamics, disturbances, control limits, and available measurements. This provides bounded descriptions of uncertainty and supports control …

A Coupled Thermo-Hydraulic Transfer Model For Soil Freezing, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Frost heave is a common challenge in cold regions, threatening infrastructure stability. Despite decades of research, numerical simulation remains difficult due to the complex nature of coupled processes. This study presents a coupled thermo-hydraulic model for soil freezing, developed within the framework of unsaturated soil mechanics. The model uses suction and temperature as primary variables and incorporates a method to estimate ice content. It employs a soil freezing characteristic surface (SFCS), previously developed in related work, to calculate unfrozen water content as a function of both suction and temperature in partially frozen soils. The model is implemented in COMSOL for …

Ai Data Center Dynamic Load Effects On Current Transformer Saturation, Sergio A. Hernandez

Electrical Engineering Theses

AI data centers can produce rapid changes in electrical demand that may influence current transformer performance during faults. This study evaluates the effect of an AI data center transient on CT saturation during single line-to-ground faults using a 400 V, 60 Hz grid connected inverter model in MATLAB/Simulink. The normal condition transient produced a maximum RMS current rate of approximately 211 A/ms, which was used along with the maximum power condition to define fault inception cases. A MATLAB time-domain CT model then swept the fault current DC offset coefficient to determine the minimum offset required for CT saturation. The calculated …

Experimental Thermal Characterization And Comparison Of Direct Liquid Cooling And Air Cooling For A High-Density Gpu Server Thermal Test Vehicle, Oluwagbolahan Esan

Mechanical and Aerospace Engineering Theses

As the power density of artificial intelligence (AI) and high-performance computing (HPC) servers escalates, air cooling is approaching fundamental scaling limits set by air's low convective heat transfer coefficient and rising parasitic fan power. This thesis presents an experimental comparison of direct-to-chip liquid cooling and air cooling for a high-density GPU server, using a Thermal Test Vehicle (TTV) that emulates the device layout and power-density regime of an 8-GPU SXM5-class baseboard (eight emulated GPU blocks and four NVLink Switch modules). The liquid configuration was tested at 8.8 kW (8.0 kW GPU, 800 W switch) across three Coolant Distribution Unit (CDU) …

End-To-End Development And Experimental Validation Of A 1/10-Scale Autonomous Vehicle, Rikkin Pankaj Panchal

Electrical Engineering Theses

Autonomous vehicle development demands vast resources, making scaled down platforms a critical alternative for solving core algorithmic challenges. The primary contribution of this thesis is the end to end development and validation of a complete real time autonomous driving pipeline deployed on a one tenth scale vehicle. To streamline platform development, an AI assisted annotation framework automates dataset generation, significantly reducing manual labor while improving training data quality. The system perception stack features a reinforcement learning guided online multi camera calibration framework that enables adaptive surround view stitching without the need for offline recalibration. This is paired with robust lane …