Digital Commons Network^™

Dual-Band High Gain Circular Microstrip Array Antenna For Wireless Applications, Hassan Ali Ragheb, Mariam Hossam

Electrical Engineering

This paper presents the design of a compact, high-gain, dual-band microstrip antenna array composed of four circular patch elements. Traditional antenna arrays employ linear or planar configurations, where the feed network plays a key role in shaping the beamwidth and sidelobe level. In contrast, this design achieves compactness by nesting a small-scaled two-element linear array within a larger two-element linear array. Each radiating element is a circular microstrip patch designed for operation at 3.1 GHz and 6.9 GHz, aligning with IEEE 802.11b/g wireless communication standards. The full array configuration operates over dual bands, covering (3.05–3.18) GHz and (6.9–7.0) GHz, and …

Design Of Directive Wideband Microstrip Antenna, Hassan Ali Ragheb

Electrical Engineering

The study under consideration demonstrates design, simulation, and optimization of a compact Ultra-Wideband (UWB) antenna employing a coplanar waveguide (CPW) feeding structure and a circular patch geometry. The design is targeting a 7 GHz operating frequency, offering a balance between compact size, wide bandwidth, and directional radiation characteristics. An initial antenna configuration was developed and analyzed using HFSS, showing satisfactory performance in terms of impedance matching and radiation efficiency. However, asymmetries in the radiation pattern prompted further enhancement. An improved design employees strategically director elements placed above the circular patch to improve forward gain and radiation beam directivity. The optimized …

Network Intelligence For Next-Generation Wireless Networks: Advancing Distribution And Coordination, Yonatan Melese Worku

Electrical and Computer Engineering ETDs

Next-generation wireless networks, encompassing 6G and beyond, face rigorous demands for ultra-low latency, ubiquitous connectivity, exceptionally high data rates, and robust security, necessitating innovative approaches to resource optimization and network protection. This dissertation proposes a pioneering framework that synergizes advanced methodologies—deep reinforcement learning, deep learning, blockchain, and multi-agent systems—to address these challenges. Distributed architectures, underpinned by AI-driven multi-agent systems, form the backbone of this framework, enabling seamless integration and intelligent orchestration across diverse domains. The research advances IoT-based systems leveraging machine learning for resource efficiency in healthcare applications, develops reinforcement learning-driven frameworks to optimize energy and coverage for Unmanned Aerial …

Optimization And Model Averaging Of Histogram-Based Place Cell Firing Rate Maps Using The Point Process Framework, Murat Okatan

Turkish Journal of Electrical Engineering and Computer Sciences

The firing rate of hippocampal place cells depends on the spatial position of the organism in an environment. This position dependence is often quantified by constructing spike-in-location and time-in-location histograms, the ratio of which yields a firing rate map. The purpose of this study is to present a new method for optimizing the spatial resolution of histogram-based firing rate maps. It is pointed out that histogram-based firing rate maps are conditional intensity functions of inhomogeneous Poisson process models of neural spike trains, and, as such, they can be optimized through model selection within the point process framework. The point process …

Isar Imaging Of Drone Swarms At 77 Ghz, Remzi̇ye Büşra Çoruk, Ali̇ Kara, Eli̇f Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

The proliferation of easily available, internet-purchased drones, coupled with the emergence of coordinated drone swarms, poses a significant security threat for airspace. Detecting these swarms is crucial to prevent potential accidents, criminal misuse, and airspace disruptions. This paper proposes a novel inverse synthetic aperture radar (ISAR) imaging technique for high-resolution reconstruction of drone swarms at 77 GHz millimeter wave (mmWave) frequency, offering a valuable tool for military and defense anti-drone systems. The key parameters affecting down-range and cross-range resolution (0.05 m), ultimately enabling the generation of detailed ISAR images are discussed. Here, we create diverse scenarios encompassing various swarm formations, …

Rescon: Residual Consistency For Real-World Super-Resolution, Erdi̇ Saritaş, Hazim Kemal Ekenel

Turkish Journal of Electrical Engineering and Computer Sciences

Real-world super-resolution is a highly challenging problem in the field of computer vision. Besides enhancing image resolution and improving visual details, information loss due to complex real-world degradations is desired to be restored. One of the primary hardness of this problem is finding sufficiently large paired datasets for training. Researchers have developed techniques that generate synthetic low-resolution pairs using high-resolution images with a generative adversarial network-based degradation generator to address this issue. In these approaches, the degradation generator is trained by utilizing real-world low-resolution images as the target domain, generating a degraded low-resolution counterpart of the high-resolution input. However, in …

Regulating The Amount Of Graphene Oxide For Enhanced Capacitive Energy Storage Of Mof Derived Materials, Yong-Ji Qin, Jing-Quan Yang, Hao Wang, Mei-Ling Lian, Pei-Pei Jia, Jun Luo, Xi-Jun Liu, Jun-Feng Liu

Journal of Electrochemistry

In pursuit of more efficient and stable electrochemical energy storage materials, composite materials consisting of metal oxides and graphene oxide have garnered significant attention due to their unique structures and exceptional properties. Graphene oxide (GO), a two-dimensional material with an extremely high specific surface area and excellent conductivity, offers new possibilities for enhancing the electrochemical performance of metal oxides. In this work, we synthesized metal- organic framework (MOF) and GO composites by regulating the amount of GO, and successfully prepared composites of metal oxides supported by nitrogen-doped carbon frameworks and GO through a simple one-step calcination process. Based on the …

Magnetic Macro Pendulum Design And Real-Time Control Application: Simulation And Experiment, Hüseyi̇n Yildiz, Serdar Yilmaz, Yasemi̇n Poyraz Koçak, Erol Uzal

Turkish Journal of Electrical Engineering and Computer Sciences

Over the last decade, the number of studies in the field of magnetic micro robots has significantly increased due to expectations of performing microsurgery, drug delivery, and similar medical procedures. Magnetic micro robots have advantages over other types of micro robots in terms of having independent designs for rotor and stator structures. Magnetic micro robots can be controlled by magnetic fields and can be programmed to move in certain directions and to perform various functions. This paper implements the computer-aided real-time control of a single-arm micro-pendulum structure to (eventually) perform cell manipulation tasks. The mechanical structure, mathematical model, control circuit …

A Deep-Learning-Based Dehazing Framework For Non-Homogenous Scenes, Shimaa Mohammed Abd Elghany, Doaa A. Altantawy, Hossam El-Din Moustafa Moustafa

Mansoura Engineering Journal

The advancement of single-image dehazing techniques has been rapid in recent years. Several existing algorithms that are based on deep learning have shown remarkable efficiency for dealing with homogeneous hazing-free issues, but convolutional neural networks (CNNS) frequently fail on non-homogeneous dehazing datasets. Meanwhile, dehaze results from dense haze regions are often blurry because the information of these regions is typically unknown and difficult to estimate. To address these issues, an efficient image enhancement dehazing algorithm that utilizes deep learning techniques, and a non-uniform atmospheric scattering model had been proposed. Unlike the majority of existing dehazing methods, the medium transmission function …

Algorithmic Optimization Of Filter Bank: Harnessing Rapid Convergence And Its Applications, Keerthana B Ms

Theses and Dissertations

A novel optimization framework is proposed for the design of both uniform and non-uniform filter banks, aimed at improving the accuracy and computational efficiency of biomedical signal classification tasks, with a particular emphasis on the detection of sleep disorders and Alzheimer’s disease.The proposed algorithm is grounded in multirate signal processing theory and aims to achieve Near Perfect Reconstruction (NPR) with minimal computational overhead. The process begins with the optimization of a uniform cosine-modulated filter bank (CMFB), achieved through iterative frequency-domain analysis and parameter tuning. This is followed by the derivation of a non-uniform filter bank via selective merging of bandpass …

Algorithmic Optimization Of Filter Bank: Harnessing Rapid Convergence And Its Applications, Keerthana B

Theses and Dissertations

A novel optimization framework is proposed for the design of both uniform and non-uniform filter banks, aimed at improving the accuracy and computational efficiency of biomedical signal classification tasks, with a particular emphasis on the detection of sleep disorders and Alzheimer’s disease. The proposed algorithm is grounded in multirate signal processing theory and aims to achieve Near Perfect Reconstruction (NPR) with minimal computational overhead. The process begins with the optimization of a uniform cosine-modulated filter bank (CMFB), achieved through iterative frequency-domain analysis and parameter tuning.

This is followed by the derivation of a non-uniform filter bank via selective merging of …

Communication Assistance Using A Large Language Model, Justin Y. Li

Electrical and Computer Engineering Senior Theses

The number of people diagnosed with Autism Spectrum Disorder is growing annually at a rapid pace. Autistic people are known to have multiple problems with communication, requiring assistance and coaching which is already limited in availability due to the amount of training required. At the same time, there has been a recent exponential rise in usage of LLMs like ChatGPT which is widely available. This project aims to prototype a solution using ChatGPT to provide communication assistance to those diagnosed with autism. The project would record voice input through a microphone and transcribe it into text. The text would be …

Mode Engineering And Functional Enhancement In Piezoelectric-On-Silicon Mems Resonators With Magnetic Field Sensing Applications, Ugur Guneroglu

USF Tampa Graduate Theses and Dissertations

This dissertation significantly advances the field of micro-electro-mechanical systems (MEMS) resonators by exploring novel post-fabrication tuning techniques, electrode configuration effects, and innovative sensor applications for thin-film piezoelectric-on-silicon (TPoS) resonator devices. Driven by the increasing demand for tunable, high-precision and robust MEMS resonators in radio frequency (RF) applications such as sensing, timing, and filtering, this research aim to provide foundational knowledge and practical solutions for overcoming existing technological limitations. The dissertation is organized into three main research thrusts, each addressing critical challenges and opportunities in the design, fabrication, and application of TPoS MEMS resonators.

The first research thrust investigates an innovative …

Isolation Enhancement Based On Tm010 And Te30 Mode Characteristics In A Patch Antennas Using Genetic Algorithm Optimization For Ku-Band Applications, Muddineni Raveendra, U. Saravanakumar, P. Padmaloshani, P. Saam Prasanth Dheeraj, Anand Anbalagan, R. Sreelakshmy

Electrical and Computer Engineering Faculty Publications and Presentations

This paper proposes a novel technique to enhance isolation in rectangular patch antennas by leveraging the mode characteristics of TM010 and TE30 to achieve better than −40 dB between the transmitter and receiver with dual‐polarization features. The primary innovation of this work lies in achieving significant isolation enhancement solely by combining two resonant modes with orthogonal polarizations, without incorporating any additional design elements such as parasitic components or decoupling structures. To validate the isolation enhancement based on these mode characteristics, a pair of rectangular transmitter and receiver patch antennas was designed to operate in the frequency range from 14 to …

Flysurf: A Flying Robotic Surface With Shape Morphing And Motion Control, Kevin Aubert De Luchi Lomellini

Electrical and Computer Engineering ETDs

This thesis introduces FlySurf, a novel flying robotic surface capable of simultaneous shape morphing and motion control. FlySurf is modeled as a mesh-based dynamic structure actuated by multiple unmanned aerial vehicles, enabling complex deformations during flight. The proposed control architecture comprises three main components. First, a state estimator to infer the robotic surface state from limited observations. Second, a shape trajectory planner that incorporates an affine deformation term to preserve surface integrity during shape transitions. Third, a surface controller to minimize the error between the desired and actual surface configurations.

The methodology is validated through realistic simulations and hardware experiments, …

The Rise Of Foss In India: Empirical Evidence And Insights From Cross-Sectoral Case Studies, Arul George Scaria, Suryaprakash Mishra, Shubham Shinde, Rashi Singhal

Research Reports

The report analyses the adoption of FOSS in India, primarily through case studies across four sectors (healthcare, education, finance, and software and IT services) and different types of organisations (start-ups, non-profits, medium, large, and public sector organisations). The study highlights both the benefits and challenges experienced by organisations using FOSS. The study illustrates that while organisations benefit from increased innovations, cost/ time savings, flexibility, and enhanced security, they also face challenges such as lack of enough skilled personnel and limited community support. Organisations are also seen taking a cautious approach to licensing, favouring permissive licenses over restrictive ones. Based on …

Participation Of Battery Energy Storage Systems In Load Frequency Control Of Power Systems, Zakaria Afsharbakeshloo

LSU Doctoral Dissertations

In this research, functionalities and roles of Battery Energy Storage Systems (BESSs) in power systems are extended beyond primary frequency control (PFC). The BESSs, while participating in PFC, are controlled through charge controllers to first maintain their state-of-charge (SOC) within an acceptable range through a primary charge controller, and to recharge the BESS to its maximum SOC through a secondary charge controller. This forms a hierarchical frequency and SOC control of power grids with BESSs. In this regard, multiple BESS case is considered as well, and by employing the SOC balancing principle, it is shown that desired power sharing among …

Non-Invasive Near-Field Microwave Sensors For Industrial Internet Of Things Applications, Abirami K

Theses and Dissertations

The industrial sector has been revolutionized by Industrial Revolution 4.0 with the advent of the Internet of Things (IoT) which integrates the physical environment using smart sensors and Artificial Intelligence (AI) mechanisms. This demands the design of smart sensors and actuators to improve the quality of services in Industrial IoT (IIoT). The sensor design using the microwave resonating principle has attracted the research and industrial community for portable, non-invasive, non-destructive and hygienic means to evaluate the quality of substances in the food and farming industry. The microwave planar sensor has advantages in terms of low footprint, low cost, and ease …

Training Stages And Algorithms Of Multilayer Neural Networks For The Control System, Abdishukurov Maqsudovich Shavkat, Xuecheng Li

Technical science and innovation

The application of neural network technologies in control systems consists of several stages. In technological object control systems, each layer of the multilayer perceptron neural networks is represented using separate transfer functions. The result of synthesizing neural network technology into control systems allows for the rapid solution of many problems. Using neural network technology, it is possible to perform many calculations. Chain rules of neural networks are added this paper. Lots of training algorithms are compared to choose better to train network. Backpropagation neural networks is seen deeply in the last page. Problems of interpolation and extrapolation are solved. Algorithms …

Unveiling Degradation Patterns In Dye-Sensitized Solar Cells: A Machine Learning Perspective, Ahmed Alali, Mahmoud Ashraf, Ahmad Muhammad, Sameh O. Abdellatif

Electrical Engineering

This study examines the time-dependent degradation of dye-sensitized solar cells (DSSCs) by systematically investigating several critical parameters, including TiO2 thickness, porosity, dye concentration, and iodine-based electrolyte concentration. We developed a novel figure of merit (FOM) to quantify the degradation rates, utilizing a finite element model (FEM) in COMSOL to simulate performance over time. 400 DSSC samples were fabricated, resulting in a comprehensive dataset comprising over 228,000 data points derived from experimental results and simulations. The findings reveal that PCE declines significantly over time, with an average initial efficiency of 4.0% for the DSSCs, dropping to approximately 0.5% after 360 h. …

Investigating Vacuum Insulator Flashover Resistance Of Rexolite And Acrylic Before And After Applying Novel Insulator Cleaning Techniques, Ritin Joseph

Electrical and Computer Engineering ETDs

Pulsed power involves accumulating large amounts of electrical energy and releasing it instantaneously. Large pulsed power accelerators use a vacuum insulator stack to facilitate power transfer from the liquid to vacuum section. Limiting the probability of surface flashover in this setting to acceptable levels improves machine longevity and prevents energy loss. Post-shot debris deposition requires a refurbishment process to prevent deterioration of dielectric performance, though the current technique of hand-sanding is long, labor-intensive, and pose serious health hazards. I have collected flashover data on frustrum-shaped Acrylic and C-Lec Rexolite® (cross-linked polystyrene) samples using a 500-kV, 20-ns risetime pulsed power test …

الأمن السيبراني والذكاء الاصطناعي: حلول لإدارة أزمات البنية التحتية الرقمية, عبدالله سعد الغامدي

Journal of the Association of Arab Universities for Research in Higher Education مجلة اتحاد الجامعات العربية للبحوث في التعليم العالي

في ظل التحول الرقمي المتسارع، أصبحت إدارة الأزمات التقنية تحديًا استراتيجيًا يستوجب تبني حلول مبتكرة للحفاظ على استمرارية الأعمال وحماية البنية التحتية الرقمية. ناقشت هذه الورقة دور الأمن السيبراني والذكاء الاصطناعي في تعزيز قدرات المنظمات والجهات على التنبؤ بالأزمات والاستجابة لها بفعالية ، وتعتمد على منهجية تحليلية تجمع بين دراسة الحالات الواقعية وتحليل البيانات باستخدام تقنيات التعلم العميق Deep Learning ونظم الأمن السيبراني المتقدمة مثل SIEM وSOAR ومدى الاستفادة من دمج هذه التقنيات لتحسين زمن الاستجابة وتقليل معدل الهجمات الناجحة، مع التدليل على أمثلة من المملكة العربية السعودية والتي سجلت أكثر من 38 مليون محاولة هجوم سيبراني في عام 2024. …

Sidesense: Robust Physiological Motion Detection Via Mmwave Joint Communication And Sensing Systems With Multiple Beams, Mohammed Shadman Ishrak, Jannatun Noor Sameera, Alvin Yang, Yanjun Pan, Yao Zheng, Olga Boric-Lubecke, Victor M. Lubecke

Electrical Engineering and Computer Science Faculty Publications and Presentations

A 28-GHz multibeam joint communication and sensing system called SideSense is presented, in which a line-of-sight (LoS) beam is used to maintain reliable communication, while other sensing beams are used to enhance physiological motion detection. SideSense decodes the motion frequency and shape from the channel state information (CSI) by first tuning the gain ratio and phase differences between the LoS communication beam and non-LoS (NLoS) beam to maximize the sensing signal-to-noise ratio (SSNR) without significantly degrading the communication channel capacity (CCC). Analytical results based on a bistatic model are presented to show a gain ratio of around 1 and a …

Statistical Monitoring Of Hard Faults In Digital Systems, Dany Akshay Deep Isukapalli

Electrical Engineering Theses and Dissertations

Achieving a high test coverage is crucial for helping to ensure that integrated circuits are working correctly and are non-defective. Although scan-based structural tests are used throughout the industry, high-level functional tests may be needed to detect some defects— especially those that are environmentally sensitive. Unfortunately, the character of functional test makes it difficult to obtain high coverage, and it is even hard to estimate coverage because fault simulation times of large circuits are long. As a result, some method is required for predicting the ability of a functional test that has not been fault simulated to detect defects. In …

Distributed Monitoring Of Moving Thermal Targets Using Unmanned Aerial Vehicles And Gaussian Mixture Models, Gustavo Vejarano, Yuanji Huang, Pavithra Sripathanallur Murali

Electrical and Computer Engineering Faculty Works

This paper contributes a two-step approach to monitor clusters of thermal targets on the ground using unmanned aerial vehicles (UAVs) and Gaussian mixture models (GMMs) in a distributed manner. The approach is tailored to networks of UAVs that establish a flying ad hoc network (FANET) and operate without central command. The first step is a monitoring algorithm that determines if the GMM corresponds to the current spatial distribution of clusters of thermal targets on the ground. UAVs make this determination using local data and a sequence of data exchanges with UAVs that are one-hop neighbors in the FANET. The second …

Seconds From Impact: Anticipatory Vehicular Crash Prediction Using Video Vision Transormers, Ryan P. Geisen

Master's Theses

Vehicular collisions represent a significant public health concern, necessitating re search into advanced emergency notification systems. While deep learning has shown promise in accident detection, a research gap persists in applying state-of-the-art transformer architectures to the task of anticipatory, real-time crash prediction from video. This thesis addresses this gap by developing and evaluating a Video Vision Transformer (ViViT) for the binary classification of imminent vehicular collisions. Utilizing a curated dataset of 1,493 unique collision sequences, this study systemati cally investigates the impact of temporal context by comparing the ViViT against a single-frame Vision Transformer (ViT) baseline and conducting comprehensive exper …

Effect Of Growth Conditions On The Performance Of Vertically Conducting Beta-Ga2o3 Diodes On 4h-Sic Substrate By Mocvd, Nifat Jahan Nipa

Theses and Dissertations

This thesis highlights the critical influence of doping strategies, specifically co-delta doping with silicon (Si) and indium (In), on improving the structural quality and device performance of β-Ga₂O₃-based Schottky barrier diodes (SBDs). To achieve better thermal management, β-Ga₂O₃ thin film was grown on bulk 4H-SiC substrates using the Metal-Organic Chemical Vapor Deposition (MOCVD) technique, renowned for its precise control over composition, thickness and doping profile. The ultra-wide bandgap (UWBG), high critical breakdown field and low turn-on resistance of β-Ga₂O₃ make it a strong candidate for next-generation power electronics and short-wavelength detection in extreme environments. However, the presence of structural defects …

Distributed Tracking Control Of Multiple High-Order Uncertain Nonlinear Systems With Guaranteed Performance, Eduardo Alvarez, Wenjie Dong

Electrical and Computer Engineering Faculty Publications

This paper addresses the distributed tracking control of multiple uncertain high-order nonlinear systems with prescribed performance requirements. By introducing a performance function and a nonlinear transformation, the prescribed fixed-time performance tracking control problem is reformulated as a distributed tracking control problem for multiple special nonlinear systems. With the aid of the universal approximation theorem for continuous functions and algebraic graph theory, distributed robust adaptive controllers are designed using the backstepping technique. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms.

Decentralised Consensus Control Of Hybrid Synchronous Condenser And Grid-Forming Inverter Systems In Renewable-Dominated Low-Inertia Grids, Hamid Soleimani, Asma Aziz, S. M.Muslem Uddin, Mehrdad Ghahramani, Daryoush Habibi

Research outputs 2022 to 2026

The increasing penetration of renewable energy sources (RESs) has significantly altered the operational characteristics of modern power systems, resulting in reduced system inertia and fault current capacity. These developments introduce new challenges for maintaining frequency and voltage stability, particularly in low-inertia grids that are dominated by inverter-based resources (IBRs). This paper presents a hierarchical control framework that integrates synchronous condensers (SCs) and grid-forming (GFM) inverters through a leader–follower consensus control architecture to address these issues. In this approach, selected GFMs act as leaders to restore nominal voltage and frequency, while follower GFMs and SCs collaboratively share active and reactive power. …

Forensic Audit: Enhancing Certified Public Accountant Using Artificial Intelligence Techniques, Hasan Mazloum, Nawaf Mazloum, Ahmad Mohamad Saleh

BAU Journal - Science and Technology

Forensic accounting was developed after the widespread corruption in the world of business today. It is now considered a fundamental branch of accounting since it revolves around disputes and issues in the law that require accounting and legal knowledge and practices to be resolved. This study examines the impact of two forensic accounting domains – the expert witness and litigation support – on financial corruption in Lebanon by using AI The objective of this study is to investigate the potential of artificial intelligence (AI) techniques in enhancing forensic audit . The study adopts the analytical descriptive approach utilizing an empirical …