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Articles 1381 - 1410 of 75018

Full-Text Articles in Engineering

A Review On Underwater Beamforming: Techniques, Challenges, And Future Directions, Ruba Zaheer, Quoc Viet Phung, Iftekhar Ahmad, Asma Aziz, Daryoush Habibi, Yue Rong, Walid K. Hasan Jan 2026

A Review On Underwater Beamforming: Techniques, Challenges, And Future Directions, Ruba Zaheer, Quoc Viet Phung, Iftekhar Ahmad, Asma Aziz, Daryoush Habibi, Yue Rong, Walid K. Hasan

Research outputs 2022 to 2026

This paper comprehensively reviews recent advancements in Underwater Beamforming (UWB) systems, highlighting its pivotal role in underwater communication, sensing, and environmental monitoring. It explores the various beamforming applications, ranging from maritime surveillance to marine life monitoring, and indicates its significance in enhancing signal clarity, spatial resolution, and noise suppression in underwater acoustic environments. The unique challenges posed by the underwater environment that introduce complexities into the beamforming process such as non-stationary noise interference, severe signal attenuation, multipath propagation, and dynamic environmental variability are thoroughly discussed. The review systematically discusses and examines conventional, adaptive, and learning-based beamforming techniques, analyzing their strengths, …

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Tribological Properties Of Woven Carbon Fiber/Peek Composites From Ambient To 200 °C: Ultra-Low Wear And Performance Evolution, Zheng Bo Xu, Shu Qing Kou, Feng Qiu, Liang Yu Chen, Hong Yu Yang, Jun Nan Dai, Shi Li Shu, Ruifen Guo, Qi Chuan Jiang, Lai Chang Zhang Jan 2026

Tribological Properties Of Woven Carbon Fiber/Peek Composites From Ambient To 200 °C: Ultra-Low Wear And Performance Evolution, Zheng Bo Xu, Shu Qing Kou, Feng Qiu, Liang Yu Chen, Hong Yu Yang, Jun Nan Dai, Shi Li Shu, Ruifen Guo, Qi Chuan Jiang, Lai Chang Zhang

Research outputs 2022 to 2026

The limited mechanical and tribological stability of carbon fiber reinforced PEEK matrix composites at elevated temperatures remains a major obstacle to their widespread application in extreme service environments. In this work, stain-woven carbon fiber (60 wt%) reinforced PEEK composite (CP60) was fabricated via compression molding, and its temperature-dependent mechanical and wear performance was systematically evaluated. Friction and wear behavior were systematically investigated using pin-on-disc tests under dry sliding conditions. Experiments were conducted at two distinct temperatures (room temperature (RT) and 200 °C) with diverse loads (200–400 N) and sliding velocities (0.47 and 0.94 m/s). The composite exhibited lower average friction …

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Covert Transmission For Active Ris-Aided Full-Duplex Uav Integrated Sensing, Communication, And Computation Systems, Qi Zhang, Wei Gao, Chuan Liu, Yu Yao, Shihao Yan, Feng Shu, Shi Jin Jan 2026

Covert Transmission For Active Ris-Aided Full-Duplex Uav Integrated Sensing, Communication, And Computation Systems, Qi Zhang, Wei Gao, Chuan Liu, Yu Yao, Shihao Yan, Feng Shu, Shi Jin

Research outputs 2022 to 2026

Next-generation wireless network should accomplish integrated sensing, communication, and computation (ISCC) capabilities. This paper proposes a novel covert transmission scheme based on active reconfigurable intelligent surface (RIS)-enabled full-duplex (FD) unmanned aerial vehicle (UAV)-ISCC framework, where the multi-functional UAV realizes simultaneous target sensing and uplink (UL) covert communication, as well as performing edge computing (EC) for users. To maximize the minimum covert transmission rate (CTR) among all UL users, UAV transmit beamforming and trajectory, RIS weights, power allocation and signal processing in a FD UL transmission system are jointly devised. To tackle the intractable non-convex problem, we leverage second order cone …

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Design Of Artificial Interference Signal Waveforms For Covert Communication Aided By Multiple Friendly Nodes, Xuyang Zhao, Wei Guo, Yongchao Wang, Shihao Yan Jan 2026

Design Of Artificial Interference Signal Waveforms For Covert Communication Aided By Multiple Friendly Nodes, Xuyang Zhao, Wei Guo, Yongchao Wang, Shihao Yan

Research outputs 2022 to 2026

In this work, we consider a covert communication scenario with multiple friendly interference nodes. The goal is to hide a legitimate communication link from a transmitter to a receiver under a warden’s surveillance. Firstly, we propose a novel strategy for generating artificial noise (AN) signals and formulate a corresponding design problem, aiming to minimize the adverse effects of AN on the legitimate receiver while enhancing communication covertness. Specifically, we optimize the basis matrix for AN signal space using statistical information of the involved channel coefficients, when precise channel state information are unavailable. Secondly, we analyze the geometric structure of the …

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Harnessing Mono-2-(Methacryloyloxy) Ethyl Succinate Grafting For Robust Micro/Nanoplastic-Resistant Ultrafiltration Membranes, Mohadeseh Najafi, Javad Farahbakhsh, Mitra Golgoli, Michael Johns, Masoumeh Zargar Jan 2026

Harnessing Mono-2-(Methacryloyloxy) Ethyl Succinate Grafting For Robust Micro/Nanoplastic-Resistant Ultrafiltration Membranes, Mohadeseh Najafi, Javad Farahbakhsh, Mitra Golgoli, Michael Johns, Masoumeh Zargar

Research outputs 2022 to 2026

The growing presence of microplastics (MPs) and nanoplastics (NPs) in water systems poses a serious threat to conventional treatment processes, particularly membrane filtration. This study focuses on a surface modification strategy for commercial ultrafiltration (UF) membranes via plasma-induced grafting of mono-2-(methacryloyloxy) ethyl succinate (MMES) to enhance resistance against MP/NPs fouling. The membranes were characterised using advanced analytical techniques, including high-resolution scanning electron microscopy (HRSEM), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM), confirming successful grafting, increased hydrophilicity, and a more negative surface charge. At optimal conditions of grafting (2 min pretreatment, 0.5 M monomer concentration, and 3 h grafting …

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Sensing-Then-Beamforming: Robust Transmission Design For Ris-Empowered Integrated Sensing And Covert Communication, Xingyu Zhao, Min Li, Ming Min Zhao, Shihao Yan, Min Jian Zhao Jan 2026

Sensing-Then-Beamforming: Robust Transmission Design For Ris-Empowered Integrated Sensing And Covert Communication, Xingyu Zhao, Min Li, Ming Min Zhao, Shihao Yan, Min Jian Zhao

Research outputs 2022 to 2026

Traditional covert communication often relies on the knowledge of the warden's channel state information, which is inherently challenging to obtain due to the non-cooperative nature and potential mobility of the warden. The integration of sensing and communication technology provides a promising solution by enabling the legitimate transmitter to sense and track the warden, thereby enhancing transmission covertness. In this paper, we develop a framework for sensing-then-beamforming in reconfigurable intelligent surface (RIS)-empowered integrated sensing and covert communication (ISACC) systems, where the transmitter (Alice) estimates and tracks the mobile aerial warden's channel using sensing echo signals while simultaneously sending covert information to …

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A Universal Hybrid Model-Free Deep Quantum–Transfer Learning Controller Enhanced By Grey Wolf Optimization For Dc–Dc Boost Converters With Hardware-In-Loop Validation, Seyyed Morteza Ghamari, Asma Aziz Jan 2026

A Universal Hybrid Model-Free Deep Quantum–Transfer Learning Controller Enhanced By Grey Wolf Optimization For Dc–Dc Boost Converters With Hardware-In-Loop Validation, Seyyed Morteza Ghamari, Asma Aziz

Research outputs 2022 to 2026

This paper proposes a universal hybrid model-free quantum–transfer learning controller with enhanced online grey wolf optimization algorithm (GWO–QTL) for DC–DC boost converter. This system has the characteristics of non-minimum phase behavior, parasitic effects, and fractional-order dynamics because of high frequency operation. These characteristics make analytical modeling complicated and make it difficult to have a single traditional controller that will operate reliably over different converter types. This motivates the creation of a unified model-free control framework that is able to learn directly from the behavior of the converter without relying on the topology specific models. Reinforcement learning, where an agent interacts …

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Additive Manufacturing And Heat Treatment Of Zero Poisson’S Ratio Self-Expanding Nitinol Stents, Farhana Yasmin, Vafadar, Majid Tolouei-Rad Jan 2026

Additive Manufacturing And Heat Treatment Of Zero Poisson’S Ratio Self-Expanding Nitinol Stents, Farhana Yasmin, Vafadar, Majid Tolouei-Rad

Research outputs 2022 to 2026

Additive manufacturing (AM) has recently gained attention as an effective approach for printing patient-specific, self-expanding Nitinol (NiTi alloy) stents with complex structural designs for the treatment of peripheral arterial disease (PAD). However, achieving the desired phase transformation temperature and superelastic performance remains challenging due to compositional variations, phase imbalance and microstructural inhomogeneities introduced during the printing process. In this study, self-expanding Nitinol stents with a zero Poisson’s ratio (ZPR) structural design were fabricated via laser powder bed fusion (PBF-LB). The printed stents showed no evidence of cracks or structural defects, confirming PBF-LB’s capability to produce mechanically sound stent geometries. However, …

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C2p-M: Critical Connection Protection In Multiplex Graphs, Conggai Li, Wei Ni, Ming Ding, Youyang Qu, Jianjun Chen, Wenjie Zhang, Thierry Rakotoarivelo Jan 2026

C2p-M: Critical Connection Protection In Multiplex Graphs, Conggai Li, Wei Ni, Ming Ding, Youyang Qu, Jianjun Chen, Wenjie Zhang, Thierry Rakotoarivelo

Research outputs 2022 to 2026

Multiplex graphs represent diverse real-world interactions among entities, where multiple relationship types coexist within the same set of entities. These graphs introduce privacy risks, as data collectors can exploit cross-layer dependencies to infer hidden and sensitive connections. In this work, we propose a C2P-M framework that identifies and protects critical connections while preserving the structural information in multiplex graphs. Unlike conventional methods for single-layer graphs that perturb all edges uniformly, C2P-M selectively protects critical connections, maintaining the analytical usability of the graph. To achieve this, we introduce the multiplex p-cohesion model, which incorporates new score functions that account for both …

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Numerical Investigation Of The Influence Of Fiber Content On The Shear Performance Of Uhpc Deep Beams Reinforced With Hybrid Steel And Synthetic Fibers, Hossein Mirzaaghabeik, Sanjay Kumar Shukla, Nuha S. Mashaan Jan 2026

Numerical Investigation Of The Influence Of Fiber Content On The Shear Performance Of Uhpc Deep Beams Reinforced With Hybrid Steel And Synthetic Fibers, Hossein Mirzaaghabeik, Sanjay Kumar Shukla, Nuha S. Mashaan

Research outputs 2022 to 2026

This study investigates the shear performance of ultra-high-performance concrete deep beams (UHPC-DBs) reinforced with hybrid fibers comprising 5D steel fibers and Forta-Ferro (FF) synthetic fibers. UHPC-DBs are widely used in bridges, piles, and transfer girders because of their high load-bearing capacity. Although fiber content strongly influences shear behavior, the contribution of synthetic fibers in hybrid systems remains insufficiently understood. To address this gap, finite element analysis based on the concrete damage plasticity (CDP) model was developed in ABAQUS and validated using experimental results from five previously tested UHPC-DBs with different fiber contents. Load–deflection response, crack patterns, shear capacity, mid-span deflection, …

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Setting Standards For Engineering Writing. Supplementary Information [Data], Hidden For Review Jan 2026

Setting Standards For Engineering Writing. Supplementary Information [Data], Hidden For Review

Higher education research

We present an approach to defining minimum standards of written communication for engineering graduates based on the evaluation of writing samples by industry personnel. Communication skills are widely recognised as core graduate capabilities; however, universities often lack explicit, evidence-based standards aligned with industry expectations. This study applies the borderline group method of empirical standard setting to elicit judgement from industry professionals who supervise graduate engineers. Participants evaluated samples of student writing in two common engineering genres, technical report executive summaries and emails, using dichotomous acceptability judgements supported by evaluations of structure, content and expression. We present a validated framework, supported …

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Improving Efficiency In Noma Schemes Having Inter-User Interference Using Mechanism Design, Zory Marantz Jan 2026

Improving Efficiency In Noma Schemes Having Inter-User Interference Using Mechanism Design, Zory Marantz

Publications and Research

Modern wireless systems utilize non-orthogonal multiple access to increase their rate capacities; however, the efficiency of the individual utility defined in bits per Joule has yet to be considered. Multiple variations of non-orthogonal multiple access have the interference of the signal-to-interference-plus-noise ratio as a function of the received power from multiple other users due to code implementations that are non-orthogonal or non-ideal cancellation in successive-interference-cancellation methods. Game theoretic concepts are used to improve user bits-per-Joule performance. Previous solutions increment transmit power and are not based on closed form systematic methods. The mechanism design presented here led to a non-cooperative Nash …

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Convergence Of High Throughput Experimentation And Machine Learning To Rapidly Advance Application-Specific Polymer Development, Mashrafee Aryan, Daniel Struble, Felix Campbell, Saroj Upreti, S. M.Ashik Abedin, Aahil Khambawla, Jeetain Mittal, Michael S. Dimitriyev, Emily B. Pentzer, Svetlana A. Sukhishvili, Xiaodan Gu, Boran Ma Jan 2026

Convergence Of High Throughput Experimentation And Machine Learning To Rapidly Advance Application-Specific Polymer Development, Mashrafee Aryan, Daniel Struble, Felix Campbell, Saroj Upreti, S. M.Ashik Abedin, Aahil Khambawla, Jeetain Mittal, Michael S. Dimitriyev, Emily B. Pentzer, Svetlana A. Sukhishvili, Xiaodan Gu, Boran Ma

Faculty Publications

Machine learning (ML) has heavily influenced the way scientific study is done with demonstrated successes in nearly every field. However, furthering performance and explainability of ML models in increasingly complex systems and with increasingly demanding outcomes requires a significant influx of high-quality data. To that end, this Review covers some of the techniques, instrumentation, and methodologies that have shown promise for significantly accelerating the discovery of polymer materials, optimization of their properties, and elucidation of property–application relationships through high throughput (HT) experimentation, characterization, and analysis. Attention is given to not only ML, but also to hardware advancements and their synergy …

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Skin Type Diversity In Image Datasets, Neda Alipour Jan 2026

Skin Type Diversity In Image Datasets, Neda Alipour

Doctoral

Image-based AI systems that analyse human skin are increasingly used in healthcare and computer vision applications. However, many human skin-based image datasets do not provide reliable information about skin type, making it difficult to assess whether these systems perform consistently across the full spectrum of skin colour. The objective of this thesis is to examine how skin type diversity is represented and measured in image datasets, and to evaluate the reliability of image-based skin type measurement methods under different imaging conditions. Using publicly available skin lesion image datasets as a well-defined and widely used sub-class of skin image datasets, this …

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Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Environments, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram Jan 2026

Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Environments, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram

Data Science Faculty Publications

An important challenge with Machine Learning (ML) is its transferability; that is, whether an ML model trained on one set of data can be applied to a second set of data without requiring full retraining of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether an ML model trained for …

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Privacy-Preserving Federated Learning With Optimized Ensemble Weighting And Knowledge Distillation For Covid-19 Detection From Non-Iid Medical Imaging Data, Richard Annan, Hong Qin, Robert Newman, Madhuri Siddula, Letu Qingge Jan 2026

Privacy-Preserving Federated Learning With Optimized Ensemble Weighting And Knowledge Distillation For Covid-19 Detection From Non-Iid Medical Imaging Data, Richard Annan, Hong Qin, Robert Newman, Madhuri Siddula, Letu Qingge

Computer Science Faculty Publications

Medical imaging enables rapid and accurate diagnosis of COVID-19, with CT scans proving especially effective. However, data privacy concerns limit collaborative model development across hospitals. To address this issue, we introduce a novel federated learning framework. It is referred to as Independent Knowledge Distillation with post-Ensemble Federated Learning (IKDEFL). Differential Privacy (DP) is integrated into the framework to improve privacy guarantees. Three DP mechanisms are evaluated. These include Fixed Gaussian, Gaussian Adaptive, and Tree Adaptive. The evaluation has been conducted on heterogeneous and Non-Independent and Identically Distributed (Non-IID) datasets. These datasets reflect real-world hospital scenarios. Results show that IKDEFL significantly …

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A Comparative Analysis Of Explainable Ai (Xai) Techniques For Transparent And Reliable Image Classification, Sovon Chakraborty, Shakib Mahmud Dipto, Kevin R. Pilkiewicz, Michael L. Mayo, Pratip Rana Jan 2026

A Comparative Analysis Of Explainable Ai (Xai) Techniques For Transparent And Reliable Image Classification, Sovon Chakraborty, Shakib Mahmud Dipto, Kevin R. Pilkiewicz, Michael L. Mayo, Pratip Rana

Computer Science Faculty Publications

Evaluating the trustworthiness of black-box machine learning models remains a significant methodological challenge. Their lack of transparency and interpretability limits applicability, because stakeholders often seek transparency before trusting the results of black-box machine learning models. Explainable AI (XAI) methods provide for human-understandable justifications and informed decision-making of these black-box architectures. Therefore, it is imperative to select the proper XAI model tailored to specific tasks. In this research, we focus on examining four XAI techniques: PEEK, LRP, GRAD-CAM, and LIME to understand how they perform against each other for image classification tasks. We evaluate the performance, robustness, generalizability, noise stability, and …

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Biosecure-Llm Framework: Protecting Llms From Cyberbiosecurity Threats And The Case For Independent Ai Safety Governance, Xavier-Lewis Palmer, Lucas Potter, Srdjan Lesaja, Sotirios Karathanasis, Mohammad Ghasemigol Jan 2026

Biosecure-Llm Framework: Protecting Llms From Cyberbiosecurity Threats And The Case For Independent Ai Safety Governance, Xavier-Lewis Palmer, Lucas Potter, Srdjan Lesaja, Sotirios Karathanasis, Mohammad Ghasemigol

Computer Science Faculty Publications

Large Language Models (LLMs) are becoming critical infrastructure in scientific, healthcare, and governmental contexts. As frontier AI laboratories increasingly partner with government agencies, a fundamental question arises: Who should control the safety and policy-enforcement layers that constrain model behavior? Current safety mechanisms (LLM guardrails) are typically designed for generic "harmlessness" and operate by detecting semantic patterns and refusing requests. However, they are inadequate governance instruments because they cannot implement auditable, domain-specific controls tied to external regulatory policy objects (e.g., control lists or rules governing personally identifying information). Even a perfectly aligned model is not able to express institution-specific policy without …

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Untrained Position-Encoded Multilayer Perceptron Network For Structured Illumination Microscopy Reconstruction, Sahil Sharma, Leonidas Zimianitis, Krishnendu Samanta, Balpreet Singh Ahluwalia, Joby Joseph, Dushan N. Wadduwage Jan 2026

Untrained Position-Encoded Multilayer Perceptron Network For Structured Illumination Microscopy Reconstruction, Sahil Sharma, Leonidas Zimianitis, Krishnendu Samanta, Balpreet Singh Ahluwalia, Joby Joseph, Dushan N. Wadduwage

Computer Science Faculty Publications

Structured Illumination Microscopy (SIM) enables super-resolution imaging by encoding high-frequency spatial information through patterned light. While traditional Fourier-based reconstruction methods are prone to artifacts under suboptimal conditions, recent deep learning approaches often require large training datasets and lack adaptability across different imaging setups. In this work, we present Position Encoded Multi-Layer Perceptron (PEM) network that leverages implicit neural representations (INRs) and SIM forward-model-driven modeling to reconstruct super-resolved images without any training data. PEM-SIM represents each spatial coordinate as a combination of sinusoidal functions across multiple frequencies, enabling rich encoding of fine spatial detail. A forward model grounded in SIM image …

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Influence Of Surface Features On Heat Transfer During Dropwise Condensation Over Superhydrophobic Surfaces In Shear Flow, Shaur Humayun, R. Daniel Maynes, Julie Crocket, Brian D. Iverson Jan 2026

Influence Of Surface Features On Heat Transfer During Dropwise Condensation Over Superhydrophobic Surfaces In Shear Flow, Shaur Humayun, R. Daniel Maynes, Julie Crocket, Brian D. Iverson

Faculty Publications

This study investigates heat transfer during dropwise condensation (DWC) on superhydrophobic (SH) surfaces in humid air shear flow, emphasizing the effect of increased drop mobility and the influence of surface micro/nanostructure on heat transfer rates. Experiments were conducted on smooth hydrophobic, microstructured SH, nanostructured carbon-infiltrated carbon nanotube (CICNT) surfaces, and two-tiered SH surfaces with both micro and nanostructures. Heat transfer rates were measured under humid air flow rates in the range of 2–4 CFM. Experimental results demonstrate that surfaces with nanostructure (including two-tiered structures) exhibit increased drop mobility and coalescence-induced drop jumping, enhancing drop removal rates and overall heat transfer …

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The Composition Of Gases From A Diffusion Flame Above Longleaf Pine Needle Fuel Beds, David R. Weise, Thomas H. Fletcher, Timothy J. Johnson, Weimin Hao, Russell G. Tonkyn, Catherine A. Banach, Javier Palarea-Albaladejo, Mahsa Alizadeh, Stephen Baker Jan 2026

The Composition Of Gases From A Diffusion Flame Above Longleaf Pine Needle Fuel Beds, David R. Weise, Thomas H. Fletcher, Timothy J. Johnson, Weimin Hao, Russell G. Tonkyn, Catherine A. Banach, Javier Palarea-Albaladejo, Mahsa Alizadeh, Stephen Baker

Faculty Publications

The gas and tar composition of a wildland fire diffusion flame from longleaf pine needles is currently relatively unmeasured and more data are needed to fill in the gap between pyrolysis data and smoke plume data, thus improving physical and chemical modeling of wildland smoke formation. A pilot experiment to measure light gas and tar composition of such a flame is described for three flame zones: persistent flame (flame base), intermittent flame, and smoke plume. Flame gases from 24 experimental fires were collected in canisters and analyzed for CO2, CO, H2, CH4, and C2 to C7 hydrocarbon gases. Other light …

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Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty Jan 2026

Cybersecurity Center For Offshore Wind Energy (Final Project Round), Sachin Shetty

Center for Secure and Intelligent Critical Systems (CSICS) Publications

This project establishes a Cybersecurity Center for Offshore Wind Energy with the objective of designing and operating a cyber-physical testbed for wind energy farms (WEFs) that enables comprehensive cybersecurity research. The testbed incorporates a Supervisory Control and Data Acquisition (SCADA) system connected to turbine models via industrial-grade programmable logic controllers (PLCs) and remote terminal units (RTUs). It supports side-channel data acquisition, implementation and analysis of various cyberattack scenarios, and development of attack detection, mitigation, and best-practice guidance tailored to wind energy systems. During the project, the team expanded the number and fidelity of mathematical turbine models (MTMs), integrated these models …

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Sustainable Paper Production From Date Palm And Reed Leaves Through The Valorization Of Agricultural Waste Products, Imane Belyamani, Alreem Alameri, Jacqueline Soghman Jan 2026

Sustainable Paper Production From Date Palm And Reed Leaves Through The Valorization Of Agricultural Waste Products, Imane Belyamani, Alreem Alameri, Jacqueline Soghman

All Works

The environmental consequences of wood-based paper production, including greenhouse gas emissions, have accelerated the search for sustainable alternatives. This study investigates the use of reed and date palm fibers as eco-friendly raw materials for paper production, focusing on starch's influence on their thermal, structural, and mechanical properties. Reed fibers exhibited a higher pulp yield (58.2 %) and lower lignin content (7.8 %) compared to date palm fibers (55.9 % yield, 14.1 % lignin), contributing to papers with smoother textures and greater flexibility. The incorporation of starch into both fiber types resulted in notable performance improvements, though the effects were more …

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Low-Energy Co2 Sequestration Via Palm Waste Biochar Activated With Carbide Lime For Mineral Carbonation Of Industrial Wastes, Maisa El Gamal, Ameera F. Mohammad, Basim Abu-Jdayil, Imen Ben Salem, Suhaib Hameedi Jan 2026

Low-Energy Co2 Sequestration Via Palm Waste Biochar Activated With Carbide Lime For Mineral Carbonation Of Industrial Wastes, Maisa El Gamal, Ameera F. Mohammad, Basim Abu-Jdayil, Imen Ben Salem, Suhaib Hameedi

All Works

A sustainable method for enhancing CO₂ capture and sequestration was developed by accelerating the carbonation of alkaline industrial wastes using carbide lime-activated biochar (BC(CLW)), an alkaline by-product of acetylene production. The biochar was produced from palm tree waste through slow pyrolysis at 400 °C, followed by activation with carbide lime slurry to enhance its alkalinity, surface basic sites, and reactivity toward CO₂. Three industrial residues, namely ladle furnace slag (LF), baghouse dust (BH), and cyclone silo dust (CD), were blended with 0, 5, 7, and 10 wt. % BC(CLW) and carbonated under ambient conditions. Characterization by thermogravimetric analysis (TGA), Fourier-transform …

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Chronofy: A Temporal-Logical Decay Architecture For Information Validity In Time-Aware Retrieval-Augmented Generation, Muntaser Syed, Marius Silaghi, Sheikh Abujar, Sharun Akter Jan 2026

Chronofy: A Temporal-Logical Decay Architecture For Information Validity In Time-Aware Retrieval-Augmented Generation, Muntaser Syed, Marius Silaghi, Sheikh Abujar, Sharun Akter

Electrical Engineering and Computer Science Student Publications

Retrieval-Augmented Generation (RAG) systems retrieve and integrate external knowledge to ground large language model (LLM) outputs. However, current RAG architectures treat all retrieved facts as equally valid regardless of temporal provenance, leading to temporal hallucination, where plausible but obsolete facts corrupt the output. A clinical lab reading from yesterday is actionable; the same reading from six months ago is noise. We present Chronofy, a three-layer neuro-symbolic framework implementing the Temporal-Logical Decay Architecture (TLDA) that embeds temporal validity directly into the representation, retrieval, and reasoning layers of RAG systems. Layer 1 reserves a dedicated temporal subspace within Matryoshka embeddings to make …

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Epistemic Edge: Subjective Logic Guardrails For Llm-Driven Iot Actuation, Muntaser Syed, Marius Silaghi Jan 2026

Epistemic Edge: Subjective Logic Guardrails For Llm-Driven Iot Actuation, Muntaser Syed, Marius Silaghi

Electrical Engineering and Computer Science Student Publications

Deploying large language models (LLMs) as decision-making agents in safety-critical Internet of Things (IoT) systems introduces risks that purely behavioral guardrails, such as action whitelists, cannot fully address. This paper presents Epistemic Edge, a four-tier neuro-symbolic pipeline that augments LLM-driven actuation with subjective logic (SL) uncertainty quantification, temporal decay, and dual guardrails combining epistemic threshold checks with behavioral whitelists. We evaluate seven locally-deployed models: three PrismML Bonsai 1-bit models (1.7B, 4B, 8B), three 4-bit quantized models (Qwen3-8B, Llama 3.2-3B, Phi-3.5-mini), and the DeepSeek-R18B reasoning model, across eight ablation conditions and five IoT actuation scenarios (2,800 controlled trials). We further validate …

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Real-Time Neck Posture Classification Using A Lightweight Wearable Imu Pendant, Muntaser Syed, Alfred Sjöqvist, Noah Sedlik, Tsing Liu Jan 2026

Real-Time Neck Posture Classification Using A Lightweight Wearable Imu Pendant, Muntaser Syed, Alfred Sjöqvist, Noah Sedlik, Tsing Liu

Electrical Engineering and Computer Science Student Publications

Poor neck posture during prolonged device use contributes to musculoskeletal disorders affecting millions worldwide. Existing posture monitoring solutions rely on camera-based systems or complex multi-sensor arrays, limiting their practicality for continuous daily use. We present a lightweight, chest-worn pendant using a single 6-axis IMU (accelerometer and gyroscope) for real-time classification of seven neck posture states: neutral, mild flexion, moderate flexion, severe flexion, extension, lateral tilt, and lying. Our approach employs an ensemble architecture combining bidirectional LSTM, Transformer encoder, and 1D-CNN models with learnable fusion weights. To address limited training data, we apply aggressive data augmentation (30x multiplication) including noise injection, …

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Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti Jan 2026

Workshop Outcomes Report: 2nd International Workshop On Seismic Resilience Of Arctic Infrastructure And Social Systems, Majid Ghayoomi, Daniela Morganti

Faculty Publications

The report provides an overview of the second international workshop on Seismic Resilience of Arctic Infrastructure and Social Systems. The report discusses agenda, workshop activities, interdisciplinary working groups, and results. It ends with several strategic questions and investigation plans that were developed as part of the workshop activities.

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Forcing A Molecule To Switch: Quantifying Mechanical Control At The Atomic Scale, A. M. Shashika D. Wijerathna, Markus Zirnheld, Michael L. Hildebrand, Myles Perry, Marjorie Cenese, Yuan Zhang Jan 2026

Forcing A Molecule To Switch: Quantifying Mechanical Control At The Atomic Scale, A. M. Shashika D. Wijerathna, Markus Zirnheld, Michael L. Hildebrand, Myles Perry, Marjorie Cenese, Yuan Zhang

Physics Faculty Publications

Mechanically induced conformational switching at the single-molecule level represents a fundamental mechanism for molecular functionality, yet quantitative characterization of the underlying force and energy landscape remains limited. Here, we study individual TBrPP-Co(II) molecules on Au(111) using qPlus atomic force microscopy. By reconstructing interaction potentials from 3D Δf(x,y,z) data, we determine a threshold force of ∼96 ± 8 pN and a tip-induced switching interaction energy of ∼38 ± 4 meV associate with the conformational transition. The isolated tip-molecule force follows a power law (exponent ∼6), indicating dominance of long-range van der Waals interactions. …

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Optimizing Ev Battery Charging Using Fuzzy Logic In The Presence Of Uncertainties And Unknown Parameters, Minhaz Uddin Ahmed, Md Ohirul Qays, Stefan Lachowicz, Parvez Mahmud Jan 2026

Optimizing Ev Battery Charging Using Fuzzy Logic In The Presence Of Uncertainties And Unknown Parameters, Minhaz Uddin Ahmed, Md Ohirul Qays, Stefan Lachowicz, Parvez Mahmud

Research outputs 2022 to 2026

The growing use of electric vehicles (EVs) creates challenges in designing charging systems that are smart, dependable, and efficient, especially when environmental conditions change. This research proposes a fuzzy-logic-based PID control strategy integrated into a photovoltaic (PV) powered EV charging system to address uncertainties such as fluctuating solar irradiance, grid instability, and dynamic load demands. A MATLAB-R2023a/Simulink-R2023a model was developed to simulate the charging process using real-time adaptive control. The fuzzy logic controller (FLC) automatically updates the PID gains by evaluating the error and how quickly the error is changing. This adaptive approach enables efficient voltage regulation and improved system …

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