Electrical and Computer Engineering Commons^™

Corrigendum To “Advanced Techniques In Quartz Wafer Precision Processing: Stealth Dicing Based On Filament-Induced Laser Machining” [Opt. Laser Technol. 171 (2024) 110474] (Optics And Laser Technology (2024) 171, (S0030399223013671), (10.1016/J.Optlastec.2023.110474)), Yun Wang, Yutang Dai, Farhan Mumtaz, Kaiyan Luo

Electrical and Computer Engineering Faculty Research & Creative Works

The authors regret, that the affiliation for author Yun Wang was incomplete. To accurately reflect both the author's academic affiliation and the research platform where the work was conducted. The correct affiliation for Yun Wang is updated as above. The authors would like to apologize for any inconvenience caused.

A Low-Noise And High-Gain Integrated Photoplethysmography Sensor For Continuous Vital Signs Monitoring, Neethu Mohan

Dissertations

Photoplethysmography (PPG) sensing is an important technology used for measuring health parameters like, heart rate, respiratory rate, blood oxygen saturation, and blood pressure (BP). The PPG sensing is used for individuals who have to periodically monitor their health due to chronic health conditions. The basic requirements of a wearable PPG sensor include non-invasiveness, prolonged battery life, and being userfriendly. These type of sensors have great demand in the healthcare applications and there is a significant rise in the demand of these sensors. The basic objective of these PPG sensors is to make the continuous vital health monitoring easier without the …

A Software-Defined Radio Testbed For Mimo-Ofdm Communications, Chaz G. Maschman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we implement a testbed for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems via GNU Radio. Specifically, we implement a configurable framework for the construction of MIMO-OFDM software-defined radio (SDR) systems as a GNU Radio module. The GNU Radio MIMO-OFDM module consists of multiple algorithmic blocks necessary for implementation of a MIMO-OFDM system. This includes a library for the generation of orthogonal or pseudo-random pilot sequences, amendments to the Schmidl-Cox protocol for MIMO synchronization, and the creation of click-and-drag GNU Radio blocks implementing the conversion of arbitrary data sent via external programs to MIMO-OFDM frames, the initial …

How Do Social Network Models Compare To All-To-All Models For Forecasting Tuberculosis Epidemics? A Mathematical Modeling Study, Masabho Peter Milali, Hae-Young Kim, George Corliss, Anna Bershteyn

Electrical and Computer Engineering Faculty Research and Publications

Background. Mathematical models guide tuberculosis (TB) target-setting, yet most assume homogeneous “all-to-all” mixing. We compared projected intervention impacts between an all-to-all compartmental model and a Barabási–Albert (BA) scale‑free social network model under otherwise identical disease assumptions.

Methods. We calibrated transmission parameters so both models produced similar baseline trends, then introduced vaccination (coverage 30–70%; efficacy 80–95%) and treatment (20–50% increases in recovery) after a 400‑day burn‑in. Outcomes were assessed 300 days post‑intervention.

Results. Under 60% coverage, increasing vaccine efficacy from 80% to 95% yielded smaller projected reductions in active TB with the network model than with all‑to‑all mixing. Treatment improvements showed …

Assessment Of Thickness-Dependent Recombination Mechanisms And Realistic Performance Limits In Csbi₃I₁₀ Lead-Free Perovskite Solar Cells, Samiul Sadek, Ayan Saha, Jegadesan Subbiah, Mohammad Tariqul Islam, Mohammad Junaebur Rashid, Mohammad Aminul Islam, Gufran Umar Alam Shaikh, Wan Zulhafizhazuan Bin Wan Jusoh, Mohammad Nur-E-Alam, Puvaneswaran Chelvanathan, Mohd Adib Ibrahim

Research outputs 2022 to 2026

Lead-free perovskite solar cells (PSCs) offer a promising, environmentally sustainable alternative to their lead-based counterparts, yet their performance is often constrained by charge transport and recombination limitations. This study presents a comprehensive numerical investigation into the thickness-dependent performance of lead-free bismuth-based PSCs employing CsBi₃I₁₀ as the absorber layer. Through systematic variation of the absorber, electron transport layer (ETL), and hole transport layer (HTL) thicknesses within a planar FTO/TiO₂/CsBi₃I₁₀/Spiro-OMeTAD/Ag architecture modeled using SCAPS-1D, an optimal absorber thickness range of 0.5–1.0 µm is identified. Under idealized conditions, a peak power conversion efficiency (PCE) of 21.62% is predicted, primarily to illustrate thickness-dependent trends. …

Condition Monitoring Of Induction Motor Using Motor Current Signature Analysis, Francis Ikechukwu Obianke, Joseph Okhaifoh, Benjamin Akinloye

Al-Bahir

Induction machines serve as the cornerstone and driving force of modern manufacturing and production systems. This research aims to monitor and analyse the operating performance of induction motors using motor current signature analysis (MCSA). MCSA is employed to process the current signal of a motor into a frequency spectrum, known as the current signature by applying the Fast Fourier Transform (FFT) algorithm. The underlying principle is that vibration generated in a motor is closely related to the changes of the magnetic field density, and the induced voltage varies with the stator current.

A simulation model replicating the behaviour of an …

AiXGa1−XN (0.7 < X < 1) Schottky Diodes Using Distributed Polarization Doped Layer With A Current Density Of 14 Ka/Cm2, Tariq Jamil, Abdullah Al Mamun Mazumder, Mafruda Rahman, Muhammad Ali, Grigory Simin, M. Asif Khan

Faculty Publications

High Al-content Al_xGa_1-xN (0.7 < x < 1) quasi-vertical Schottky barrier diodes (SBDs) with distributed polarization doping were grown on the bulk AlN substrate. They exhibit excellent rectification behavior with a large forward current density (~14 kA/cm² ) and a high breakdown field of ~8.3 MV/cm. The SBDs also exhibited low ideality factors of (n~1.2) with a high Schottky barrier height (Φ _b~ 1.7 eV). Thus, this study demonstrates the feasibility of the distributed polarization doping approach for high current–high voltage devices.

An Interpretable Hybrid Deep And Reinforcement Learning Paradigm For Glioma Prognosis, Renuga Devi M Ms

Theses and Dissertations

Brain tumors are highly aggressive and lethal types of cancer, particularly gliomas. These cancerous growths show complicated pathophysiological behaviours and with poor prognosis despite therapeutic advances. Due to their biological differences and infiltrating growth, as well as overlapping radiological characteristics, they pose great difficulty in diagnosis, grading, and survival prediction. Artificial intelligence technology, which includes machine learning , deep learning, and reinforcement learning has developed into a new paradigm for the automation of brain tumor diagnostics and personalized treatment. The main goal of this study is to create an integrated AI-based framework that can perform brain tumor segmentation, grading and …

Intrusion Detection Latency: The Neglected Metric, Sandhyarani Dash, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

Accuracy remains the dominant evaluation metric in Intrusion Detection System (IDS) research, yet an IDS that detects attacks too late is functionally equivalent to one that fails—particularly in Internet of Things (IoT) environments. In operational settings, the timing of detection shapes both the scope of adversarial activity and the feasibility of effective response. To the best of our knowledge, latency (the speed at which intrusions are identified) has received no systematic attention. Our analysis of published IDS papers reveals that latency is defined inconsistently—often referring to inference, communication, computation time, or combinations of these-leading to incomparable performance claims. To close …

Axial Sulfur-Coordination Engineering Boosting Fe–N–C Catalysts For High-Performance Proton Exchange Membrane Fuel Cells, Lin Lin, Xiu-Xuan Hou, Zhe-Chen Fan, Yi-Xuan Yin, Wei-Yi Zhao, Kai Wei, Yu-Die Zhou, Li-Na Hou, Ying Wang, Hao Wan, Jun-Jie Ge

Journal of Electrochemistry

Fe-N-C catalysts have long suffered from kinetically sluggish oxygen reduction reaction (ORR) due to excessive adsorption strength toward oxygen intermediates and low site utilization. Heteroatom doping effectively accelerates ORR reaction kinetics through electronic structure modulation of metal sites for optimal intermediate adsorption, while chemical vapor deposition (CVD) enhances the turnover frequency (TOF) of active sites. Herein, we developed an FeSNC catalyst featuring abundant FeS₁N₄ sites via a dual-precursor CVD strategy. Experimental and theoretical analyses revealed that S incorporation disrupts the symmetric coordination of active sites, which optimizes OH* adsorption energies from 0.212 eV to 1.194 eV. Moreover, …

Deciphering The Role Of Binder Reaction Exothermicity In Thermal Runaway Of Lithium-Ion Cells, Wen Wen, Jing-Hong Zhou, Hao-Tian Lu, Xing-Gui Zhou

Journal of Electrochemistry

Thermal safety associated with lithium-ion cells as power sources remains a critical industry concern. A comprehensive understanding of how internal exothermic side reactions contribute to temperature rise is fundamental for accurately analyzing thermal runaway processes and predicting the thermal safety of lithium-ion cells. While various side-reactions, such as decomposition of solid electrolyte interphase layer, reaction between anode materials and electrolyte, reaction between cathode materials and electrolyte, and electrolyte decomposition, have been identified as heat generation sources in previous studies, the quantification of these reactions remains insufficiently standardized. Particularly, the impact of heat generation from binder decomposition (most commonly polyvinylidene difluoride) …

Reconstruction Of Information System Acceptance Model In The Era Of Integrated Artificial Intelligence: A Systematic Literature Review, Ilham, Merlin Apriliyanti

Library Philosophy and Practice (e-journal)

This study aims to explain the rapid development of Artificial Intelligence (AI) which has driven significant transformations in the development and use of information systems. However, most classical information system acceptance models, such as the Technology Acceptance Model (TAM) and  (UTAUT), have not been able to fully explain the unique characteristics of AI-based systems that are autonomous, adaptive, and complex. This study aims to reconstruct the information system acceptance model in the era of integrated AI through a Systematic Literature Review (SLR) approach. This study was conducted using the PRISMA protocol on 130 leading scientific articles indexed by Scopus and …

A Pretraining-Based Framework For On-Device Training Of Imu-Based Locomotion Mode Detection For Wearable Active Exoskeletons, Muhammad Tahir Khan

LSU Master's Theses

Active exoskeletons are being developed to support human movement in physically demanding industries such as construction. For these systems to work effectively, they must be able to correctly identify the user’s current activity. This process is known as locomotion mode detection and plays an important role in selecting the appropriate control parameters for exoskeletons. Many existing approaches use inertial measurement units (IMUs) to recognize these activities and have shown strong performance. However, most of these methods depend on large amounts of labeled data collected under specific conditions. As a result, they often do not perform well when applied to new …

Deep Learning Based Control System For Multi-Zone Hvac Residential Buildings, Mohammad H. Z. Alghalayeeni

Mechanical Engineering Theses

Heating, ventilation, and air conditioning (HVAC) systems are major contributors to residential energy consumption. However, most homes continue to rely on single zone thermostat control, which regulates temperature based on a single sensor and cannot account for thermal variations across multiple rooms. This often leads to uneven thermal conditions and inefficient energy use in multi-zone residential buildings. This thesis presents a deep reinforcement learning based approach for improving HVAC zoning control through dynamic airflow distribution. A physics based multi zone thermal model of a residential house was developed to simulate heat transfer processes including conduction, convection, solar and internal heat …

Exploiting Chaotic Antenna Arrays For Rf Fingerprint Authentication And Physical Layer Security In Wireless Communications, Joshua K. Thomas Ranstrom

USF Tampa Graduate Theses and Dissertations

Modern wireless networks support a wide range of applications including consumer devices, healthcare monitoring, industrial automation, smart grids, and military platforms, in which transmitted information is often highly sensitive and subject to stringent confidentiality and integrity requirements. As wireless communication operates over an open broadcast medium it exposes systems to physical layer (PHY) threats such as eavesdropping, in which an adversary passively intercepts transmitted information, and spoofing, in which a forged transmission misleads the receiver about device identity. Cryptographic defenses address both threats but require computational assumptions and key management infrastructure that may not scale to dense or resource-constrained deployments. …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

Learning To Refine Gesture-Derived Voxel-To-Loop For Generative 3d Modeling In Vr, Kallen Lonbom, Trudi Di Qi

Engineering Faculty Articles and Research

We present a generative modeling pipeline for refining and denoising coarse 3D shapes created through freehand interaction in virtual reality (VR). While recent loop-based generative models focus on shape synthesis from clean inputs, our work addresses the challenge of reconstructing coherent geometry from noisy, coarse volumetric data. To this end, we introduce a hybrid voxel-to-loop representation that captures the topology of rough voxel shapes and converts them into sequential cross-sectional loops for generative refinement. We develop two transformer architectures and evaluate their efficacy primarily on synthetically perturbed datasets with additional examples from VR. Our results demonstrate that this representation is …

Secure Machine Learning In Networking Systems, Wenwei Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid integration of Machine Learning (ML) into networking systems, ensuring the security and trustworthiness of these intelligent frameworks has become a paramount concern. While ML offers unprecedented capabilities in spectrum management and collaborative learning, it also introduces novel vulnerabilities that can be exploited by sophisticated adversaries. This dissertation investigates and addresses critical security challenges across three key dimensions of ML-driven networking: adversarial spectrum sensing, the security of privacy-preserving unlearning processes, and efficient post-attack model recovery.

First, we address the threat of adversarial spectrum attacks in cognitive radio networks, where malicious nodes manipulate sensing reports to disrupt spectrum access. …

Multi-Modal Tensor Fusion For Alzheimer’S Disease Recognition, Mason Li, Tiffany Le, Jiajing Huang, Yuxin Wen

Engineering Faculty Articles and Research

Accurate and early diagnosis of Alzheimer’s disease (AD) is critical for effective intervention, disease monitoring, and patient care. Traditional diagnostic approaches rely on a single modality, such as clinical assessments, neuroimaging, or genetic markers, which may fail to capture the complex, multifaceted nature of AD. Multimodal learning has therefore been explored to integrate complementary information across data sources. However, conventional fusion strategies, including early feature concatenation and late decision-level fusion, often model modalities independently and fail to capture high-order cross-modal interactions. To address these limitations, we propose a multimodal tensor fusion network (MTFN) that integrates heterogeneous data sources, including visual …

Arid: Agglomerative Regionalization Via Information Divergence, A Novel Clustering Algorithm For Geo-Spatial Data, Joshua David Sills

Dissertations and Theses

Regionalization is a clustering problem that seeks to partition geospatial data into geographically contiguous regions while remaining internally homogeneous in their attributes. It has been successfully applied towards the development of urban planning, natural resource discovery, and ecological analysis. Existing popular approaches optimize homogeneity using Euclidean or variance-based criteria, which ignore distributional differences such as variance shifts, multimodality, and higher-order dependence. This thesis introduces ARID (Agglomerative Regionalization via Information Divergence), a spatially constrained agglomerative clustering framework that replaces distance-based merging with an information-theoretic, Ward-like criterion that utilizes the Kullback-Leibler (KL) divergence. ARID constructs a neighborhood graph from coordinate space and …