School of Systems Science and Industrial Engineering, Binghamton University, Binghamton, NY, USA
Marquette University
University of Nevada, Las Vegas
New Jersey Institute of Technology
Louisiana State University at Baton Rouge
University of Arkansas, Fayetteville
CUNY City College
TÜBİTAK
Dataset For Integrity Attacks On Time Synchronized Synchrophasor Data,
2026
Edith Cowan University
Dataset For Integrity Attacks On Time Synchronized Synchrophasor Data, Taylah Griffiths, Mohiuddin Ahmed, Chadni Islam
Research outputs 2022 to 2026
Phasor measurement units, also known as synchrophasors, are a vital component within smart grids to determine the stability of the grid. These devices send synchrophasor data to phasor data concentrators that collate and analyse the data. Recently, synchrophasor communication data has become beneficial for the research community. However, datasets covering cyberattacks on synchrophasor data are not public. Having access to this data would aid in investigating mitigations against cyberattacks. This paper describes a public specialized dataset, known as ECU-PMU-FDI/TSA. The dataset contains synchrophasor communication data for cybersecurity mitigation testing. Three hours of communication data was captured, from a simulated testbed. …
Evolving Ai Integration In Complex Medical Decision-Making And Multidisciplinary Transplant Care: A Systematic Review Of Human-Ai Collaboration,
2026
Missouri University of Science and Technology
Evolving Ai Integration In Complex Medical Decision-Making And Multidisciplinary Transplant Care: A Systematic Review Of Human-Ai Collaboration, Rachel L. Dzieran, Cihan H. Dagli, Robert J. Marley
Engineering Management and Systems Engineering Faculty Research & Creative Works
Purpose of Review: Artificial intelligence (AI) in healthcare has evolved dramatically from early expert systems, which were initially considered replacements for clinical judgment, to today's collaborative frameworks that aim to augment physician decision-making. This evolution is particularly crucial in domains such as transplant surgery, where decisions carry irreversible consequences and require the integration of complex, often ambiguous data. Drawing on peer-reviewed literature from 2019 to 2025, we conducted a systematic review that analyzed key elements distinguishing successful human-AI partnerships from those that fail. Recent Findings: The ideal balance incorporates human expertise into AI systems through weighted integration approaches, rather than …
Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms,
2026
Florida Institute of Technology
Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton
Theses and Dissertations
Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …
Efficient Charging Scheduling Through Coordination Of Electric Vehicle Platoons And Charging Stations,
2026
Edith Cowan University
Efficient Charging Scheduling Through Coordination Of Electric Vehicle Platoons And Charging Stations, Liwan Qi, Bochun Wu, Shoubo Li, Yi Gong, Wei Ni
Research outputs 2022 to 2026
This paper focuses on charging allocation in a vehicle-to-infrastructure (V2I) communications-enabled electric vehicle (EV) network with heterogeneous traffic flows, where manned EVs and EV platoons coexist, and each EV platoon may have a different size and travel speed. In such a network, hybrid traffic flows pose significant challenges since platoons with multiple EVs can easily cause severe station overloading and increase the total time cost for charging service, particularly when large platoons occur. To tackle this issue, a centralized approach is proposed to plan charging allocation and optimize the velocities of manned EVs and EV platoons with the assistance of …
Ncf Sensor Coated With Cofe1.96la0.04o4/Lafeo3 Heterostructures For Room-Temperature Detection Of Liquefied Petroleum Gas Concentration,
2026
Missouri University of Science and Technology
Ncf Sensor Coated With Cofe1.96la0.04o4/Lafeo3 Heterostructures For Room-Temperature Detection Of Liquefied Petroleum Gas Concentration, Ziqiang Liu, Fujian Tang, Yufang He, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Liquefied petroleum gas (LPG) is a highly flammable fuel widely used for cooking, heating and transportation, making real-time leak detection essential for preventing fire, explosion, and suffocation hazards. In this study, a room-temperature no-core fiber (NCF) sensor coated with CoFe1.96La0.04O4/LaFeO3 heterostructures was developed for LPG detection. The heterostructures were characterized using XRD, Raman spectroscopy, SEM, TEM, XPS, PL spectroscopy, and UV–vis spectroscopy. Experimental results showed that La incorporation and heterostructure formation refined the particles size, improved surface accessibility, and modulated the electronic structure and band gap, thereby enhancing LPG adsorption, carrier redistribution, and …
Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes,
2026
Guangdong University of Technology
Lrq-Solver: A Transformer-Based Neural Operator For Fast And Accurate Solving Of Large-Scale 3d Pdes, Peijian Zeng, Guan Wang, Haohao Gu, Xiaoguang Hu, Tiezhu Gao, Zhuowei Wang, Aimin Yang, Xiaoyu Song
Electrical and Computer Engineering Faculty Publications and Presentations
Solving large-scale PDEs on complex three-dimensional geometries remains a central challenge in scientific and engineering computing, often due to expensive pre-processing stages and high computational overhead. We present Low-Rank Query-based PDE Solver (LRQ-Solver), a physics-integrated deep learning framework for efficient CAE simulations of complex three-dimensional geometries in CAD-driven design analysis. Built upon the Parameter-Conditioned Lagrangian Modeling (PCLM) that embeds physical consistency into the learning process and the Low-Rank Query Attention (LR-QA) module that reduces attention complexity from O(N2) to O(NC2+C3) via covariance decomposition, LRQ-Solver supports multi-configuration analysis within iterative design workflows. On two benchmark datasets, it achieves a 28.6% error …
Adaptive Improved Particle Swarm Optimization-Based Maximum Power Point Tracking And Energy Smoothing For Photovoltaic Hybrid Battery–Supercapacitor Storage Systems,
2026
Edith Cowan University
Adaptive Improved Particle Swarm Optimization-Based Maximum Power Point Tracking And Energy Smoothing For Photovoltaic Hybrid Battery–Supercapacitor Storage Systems, Mohammad Aminul Islam, Guo Shaokai, Jakaria Mahdi Imam, Mohammad Khairul Basher, Nowshad Amin, Tarek Abedin, Mohammad Nur-E-Alam
Research outputs 2022 to 2026
The rapid development of photovoltaic (PV) systems has made them an important component of the global clean energy strategy. However, the intermittency and non-linear characteristics of photovoltaic (PV) output remain major challenges for stable renewable energy utilization. This study proposes an adaptive improved particle swarm optimization (IPSO)-based maximum power point tracking (MPPT) strategy integrated with hybrid energy storage coordination for photovoltaic systems. The IPSO introduces adaptive inertia adjustment, velocity clamping, and stagnation reinitialization, which improve the convergence robustness under dynamic irradiance and temperature conditions. The algorithm was benchmarked against Perturb & Observe (P&O), Incremental Conductance (INC), and standard PSO using …
Graphene Oxide–Driven In Situ Bismuth Reduction Enables Highly Efficient Electroreduction Of Co2 To Formic Acid,
2026
Missouri University of Science and Technology
Graphene Oxide–Driven In Situ Bismuth Reduction Enables Highly Efficient Electroreduction Of Co2 To Formic Acid, Hao Feng, Bohong Zhang, Jie Huang, Xinhua Liang
Electrical and Computer Engineering Faculty Research & Creative Works
To enable large scale efficient electrochemical CO2 reduction reaction (CO2RR) to formic acid (HCOOH), it is important to develop catalysts that can be operated in a wide potential window with good stability. Herein, we successfully synthesized Bi2O3 catalyst supported on graphene oxide (GO) and graphene (G) and found that Bi2O3/GO catalyst had a better overall performance than Bi2O3/G. The Bi2O3/GO catalyst demonstrated an outstanding CO2RR performance with a greater than 90% faradaic efficiency (FE) across a wide applied potential window …
Thermo-Mechanical Behaviour Of Metal-Coated Optical Fibers For Distributed High-Temperature Sensing: From Laboratory Characterization To Industrial Case Validation,
2026
Missouri University of Science and Technology
Thermo-Mechanical Behaviour Of Metal-Coated Optical Fibers For Distributed High-Temperature Sensing: From Laboratory Characterization To Industrial Case Validation, Koustav Dey, Rony Kumer Saha, Bohong Zhang, Laura Bartlett, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
Reliable distributed temperature sensing in high-temperature environments remains a significant challenge due to the thermal and mechanical limitations of conventional optical fibers. In particular, polymer-coated fibers degrade above ∼300 °C due to coating failure, mechanical fragility and hydrogen ingress. Metal-coated optical fibers offer a robust alternative for harsh environments such as Electric Arc Furnaces (EAFs), aerospace engines, nuclear systems, and oil and gas wells, owing to their superior mechanical strength and hermetic sealing. In this work, a first comprehensive experimental investigation of the thermo-mechanical behavior of metal-coated optical fibers for distributed high temperature sensing is presented over a wide temperature …
Ai-Driven Biomarker Discovery & Progression Modeling For Precision Diagnosis Of Glaucoma,
2026
Southern Methodist University
Ai-Driven Biomarker Discovery & Progression Modeling For Precision Diagnosis Of Glaucoma, Cheng Huang
Computer Science and Engineering Theses and Dissertations
This dissertation presents a comprehensive study on the integration of artificial intelligence (AI) for glaucoma diagnosis and retinal image analysis. Leveraging multimodal imaging data including fundus photography, Optical Coherence Tomography Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), the research develops a suite of deep learning frameworks designed to detect early glaucomatous changes with high precision, robustness, and interpretability. A series of novel architectures are introduced, spanning vessel segmentation networks, biomarker discovery pipelines, and multimodal fusion models, all designed to enhance diagnostic accuracy and generalizability across diverse populations. To facilitate reproducible and scalable ophthalmic AI research, this work …
Ph-Compensated Hydrogen Peroxide Quantification Using A Dual-Modal Fiber-Optic Probe,
2026
Missouri University of Science and Technology
Ph-Compensated Hydrogen Peroxide Quantification Using A Dual-Modal Fiber-Optic Probe, Homayoon Soleimani Dinani, Bohong Zhang, Maryam Karimi, Rex E. Gerald, Shelley D. Minteer, Jie Huang
Electrical and Computer Engineering Faculty Research & Creative Works
We report a dual-modal fiber-optic probe that integrates electrochemical quantification of hydrogen peroxide (H₂O₂) with co-localized fluorescent pH sensing for pH-indexed interpretation of the H₂O₂ response. H₂O₂ is a reactive oxygen species involved in oxidative stress, inflammation, and cellular signaling, and local pH modulates both its production and electrochemical response. Many electrochemical H₂O₂ sensors exhibit pH-dependent sensitivity, creating ambiguity unless pH is measured and used for compensation, which is difficult in small, heterogeneous, or rapidly changing microenvironments. A three-electrode configuration—working (WE), counter (CE), and Ag/AgCl pseudo-reference (pRE) electrodes—is fabricated directly on the cylindrical surface of a 710-µm-diameter optical fiber using …
Dense Platinum Nanoparticles Confined In Mn-N-C Nanocages For Robust Heavy-Duty Pemfcs,
2026
School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, P.R. China; School of Materials and Environmental Engineering, Chengdu Technological University, Chengdu 611730, P.R. China
Dense Platinum Nanoparticles Confined In Mn-N-C Nanocages For Robust Heavy-Duty Pemfcs, Lei Zhao, Zhen-Min Cao, Jia-Yu Zuo, Ming-Liang Yang, Hong-Yan Qiao, Jun-Song Chen, Rui Wu
Journal of Electrochemistry
High-loading Pt cathodes are essential for heavy-duty proton exchange membrane fuel cells but suffer from a critical tradeoff between ionomer sulfonate poisoning and nanoparticle instability. Herein, we report a spatial confinement strategy to encapsulate dense Pt nanoparticles (~51.8 wt%) within Mn/N-co-doped mesoporous carbon nanocages (denoted as Pt-MnNC). This architecture excludes bulky ionomers to create an ionomer-shielded environment against sulfonate poisoning, while Mn-Nx-mediated strong metal-support interactions anchor the Pt nanoparticles to prevent agglomeration and further boost durability. In the 5 × 5 cm2 membrane electrode assembly tests, the Pt-MnNC catalyst delivers an exceptional power density of 1.26 W·cm …
Efficient Acidic H2O2 Electrosynthesis Over Co Atoms Anchored On Nitrogen-Doped Hierarchical Porous Carbon,
2026
State Key Laboratory of Green and Efficient Development of Phosphorus Resources, School of Chemistry and Environmental Engineering, Wuhan Institute of Technology, Wuhan 430205, China; Hubei Key Laboratory of Processing and Application of Catalytic Materials, College of Chemistry and Chemical Engineering, Huanggang Normal University, Huanggang 438000, China
Efficient Acidic H2O2 Electrosynthesis Over Co Atoms Anchored On Nitrogen-Doped Hierarchical Porous Carbon, Xiao Huang, Zi-Hao Zhan, Hao-Xu Niu, Guan-Yu Luo, Jin-Tao Huang, Bo-Xuan Jin, De-Li Wang
Journal of Electrochemistry
The two-electron oxygen reduction reaction (2e− ORR) presents a promising route for the on-site production of hydrogen peroxide (H2O2), offering a green alternative to energy-consuming anthraquinone process. However, the high selectivity toward the competing 4e− ORR over the desired 2e− pathway leads to low Faradaic efficiency for H2O2, posing a critical challenge in catalyst design. In this work, a nitrogen-doped hollow hierarchical porous carbon with anchored Co atoms (CoN/HPC) was constructed for high-performance H2O2 production. The as-prepared Co-N/HPC catalyst showed excellent 2e− ORR performance, achieving …
Engineering Small-Sized Cations With Strong Solvation For High-Voltage Supercapacitors,
2026
College of Materials Science and Engineering, Tianjin Key Laboratory of Advanced Fibers and Energy Storage, Tiangong University, Tianjin 300387, China
Engineering Small-Sized Cations With Strong Solvation For High-Voltage Supercapacitors, Tong Huo, Pan Liu, Hao Chen, Peng Zhang, Zhen-Lei Chen, Guo-Fu Sun, Zhi-Qiang Shi, Jing Wang
Journal of Electrochemistry
Supercapacitors (SCs) have attracted much attention in the field of energy storage due to their high power density and long cycle life. However, their relatively low energy density limits their application in a wider range of fields. Methods to increase energy density include enhancing specific capacitance and extending operating voltage window. Herein, we report a novel electrolyte salt, tetramethylammonium bis(fluorosulfonyl)imide (TMA-FSI), the resulting electrolyte formed with propylene carbonate (PC), designated as TMF, exhibited a wide electrochemical stability window (ESW) of 5.09 V. On the one hand, we found that the small size of TMA+ enables it to enter the …
Superiorgat: Graph Attention Networks For Sparse Lidar Point Cloud Reconstruction In Autonomous Systems,
2026
SUNY Morrisville College
Superiorgat: Graph Attention Networks For Sparse Lidar Point Cloud Reconstruction In Autonomous Systems, Khalfalla Awedat, Mohamed Abidalrekab, Gurcan Comert, Mustafa Ayad, Negash Begashaw
Electrical and Computer Engineering Faculty Publications and Presentations
LiDAR-based perception in autonomous systems is fundamentally limited by sparse vertical sampling and further degraded by structured beam dropout caused by occlusions, sensor faults, or reduced-cost LiDAR hardware. These degradations disrupt vertical geometric continuity and negatively affect downstream perception tasks such as object detection, localization, and scene understanding. Existing reconstruction approaches often struggle to balance reconstruction accuracy with the computational efficiency required for real-time autonomous operation. This paper presents SuperiorGAT, a graph attention–based framework for reconstructing missing elevation information in sparse LiDAR point clouds under structured beam loss. The proposed method models LiDAR scans as beam-aware graphs and enhances standard …
Scheduling The Charging Of Battery-Electric Vehicles Under Heterogeneous Scheduling Constraints,
2026
Utah State University
Scheduling The Charging Of Battery-Electric Vehicles Under Heterogeneous Scheduling Constraints, Justin Whitaker, Greg Droge, Mario Harper
Electrical and Computer Engineering Student Research
Adopting battery electric vehicles (EVs) for vehicle fleets requires scheduling charging alongside day-to-day operations. This problem is complicated by complex utility cost structures, limited battery capacity, and competition for shared charging resources. Existing methods that simultaneously schedule routes and charging neither address the full cost structure nor employ high-fidelity charging models, and no prior work analyzes fleets containing vehicles with heterogeneous routing constraints. This work addresses these gaps by combining a state-of-the-art flexible-schedule formulation with time-of-use (TOU) demand costs and a non-linear, variable-rate charging model as drawn from additional state-of-the-art works. The proposed method is validated against two state-of-the-art methods, …
Multi-Solution Ternary Grover’S Algorithm For Logic-Based Quantum Machine Learning With Pseudo-Kronecker Reed–Muller Form Minimization,
2026
Portland State University
Multi-Solution Ternary Grover’S Algorithm For Logic-Based Quantum Machine Learning With Pseudo-Kronecker Reed–Muller Form Minimization, Sophia Lee, Ali Al-Bayaty, Marek Perkowski
Electrical and Computer Engineering Faculty Publications and Presentations
Optimization problems in machine-learning (ML) applications can be computationally challenging for classical methods, particularly when they involve large, unstructured search spaces. Quantum computing offers a promising approach to combinatorial optimization by utilizing quantum superposition and amplitude amplification. This paper presents a new methodology using logic-based quantum machine learning (QML) as a complete framework for employing a multi-solution ternary Grover’s algorithm to minimize incomplete binary functions represented by Pseudo-Kronecker Reed–Muller (PKRO) expansions, consistent with Occam’s razor principle. Unlike previous quantum approaches based on Kronecker Reed–Muller (KRO) or fixed-polarity Reed–Muller (FPRM) representations, our work introduces the first Grover-based optimization framework for PKRO …
Breaking The Build: Detecting Software Supply Chain Vulnerabilities In Ci/Cd Pipelines,
2026
SUNY Albany
Breaking The Build: Detecting Software Supply Chain Vulnerabilities In Ci/Cd Pipelines, Mercedes R. Wahl, Dr. Benjamin Yankson
Military Cyber Affairs
This study examines whether integrating structured DevSec- Ops security controls into CI/CD pipelines can reduce software supply chain risk by preventing vulnerable components from progressing through the software development lifecycle. Software supply chain attacks frequently originate from weaknesses or compromises within dependencies, build environments, and trusted development stages, making early detection essential. A controlled sandbox experiment compared two pipeline configurations: a baseline CI/CD pipeline with no automated security enforcement and a secure DevSecOps pipeline integrating automated vulnerability scanning, SBOM generation, and artifact integrity verification. A known vulnerable dependency, the Python requests package (version 2.19.0) associated with CVE-2018-18074, was intentionally introduced …
Challenges, Trends, And The Role Of Lstm In Ai-Based Predictive Maintenance Of Electrolyzers For Solar Hydrogen Systems: A Review,
2026
Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang Al- Sultan Abdullah, 26600 Pekan, Pahang, Malaysia
Challenges, Trends, And The Role Of Lstm In Ai-Based Predictive Maintenance Of Electrolyzers For Solar Hydrogen Systems: A Review, Yani Koerniawan Kuatno, Muhamad Zahim Sujod
Turkish Journal of Electrical Engineering and Computer Sciences
The transition toward low-carbon energy systems has increased interest in hydrogen as a clean energy carrier, with solar-driven water electrolysis emerging as a promising technology due to its high efficiency and compatibility with renewable energy sources. However, dynamic operating conditions and intermittent renewable input accelerate electrolyzer degradation, reducing reliability and system lifespan. Predictive maintenance (PdM), supported by artificial intelligence (AI), offers a data-driven approach to anticipate failures and improve operational durability. This review systematically investigates AI-based PdM approaches for electrolyzers, with an emphasis on long short-term memory (LSTM) networks and Internet of things (IoT) integration. Following PRISMA 2020 guidelines, 35 …
Dynamic Focal Loss Adjustment For Railway Defect Detection,
2026
Eskisehir Technical University
Dynamic Focal Loss Adjustment For Railway Defect Detection, Mehmet Koç, Ridvan Özdemi̇r, Ömer Gerek
Turkish Journal of Electrical Engineering and Computer Sciences
Railway infrastructure is critical to the safe and efficient operation of transportation systems, and the early detection of defects is essential for preventing catastrophic failures. Automated defect detection methods are therefore crucial for maintaining continuous safety while reducing maintenance costs. Although Focal Loss is widely used in object detection under class-imbalanced conditions, its fixed α parameter may limit its effectiveness in detecting rare defects. In this study, we propose an adaptive α-tuned Focal Loss approach that dynamically adjusts class weights based on average precision (AP) values. By iteratively optimizing α without relying on gradient-based optimization, the proposed method improves the …
