Engineering Commons^™

A Digital Calibration Source For 21 Cm Cosmology Telescopes, Kalyani Balkrishna Bhopi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Precise calibration of radio telescope beams and gains is a central requirement for 21 cm intensity mapping experiments, which aim to measure large scale cosmological structure through the redshifted emission line of neutral hydrogen. Bright astrophysical foregrounds dominate the sky at these frequencies, and separating them from the cosmological signal demands precise control over instrumental systematics, particularly the telescope beam and its frequency-dependent response. Existing aerial calibration sources are incoherent broadband emitters, detectable only as total power. They provide no direct phase information and suffer from poor sensitivity in low signal-to-noise regimes.

We present the Precision Emitter for 21cm Array …

Hyperglycemia Detection From Sigle - Lead Ecg Using A Hybrid Cnn & Transformer Model, Adam Ayomikun Ogunjembola

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract
Hyperglycemia Detection from Single-Lead ECG using a Hybrid CNN & Transformer Model
Adam Ogunjembola

Diabetes Mellitus is known as high blood glucose. This high blood glucose level happens when the body has a problem with producing or using insulin. Insulin is a very important hormone that the pancreas makes to control how much glucose gets into the bloodstream and cells. Diabetes Mellitus has an effect on the body if it is not treated, such as damaging the blood vessels and nerves which can lead to stroke, kidney failure, heart attack and permanent loss of vision. Since people with diabetes …

Bi-Level Optimization Of Peer-To-Peer Trading In A Decentralized Energy Market, Marshal Miezah

Graduate Theses, Dissertations, and Problem Reports (ETD)

Distributed power generation based on rooftop photovoltaic (PV) systems integrated with battery storage emerges as a promising pathway for reducing greenhouse gas emissions and im- proving flexibility in modern power systems. This study develops a bi-level optimization model to examine how prosumers maximize profit through peer-to-peer (P2P) energy trading with consumers and the grid, and how consumers minimize cost by leveraging P2P trading. The bi-level problem is reformulated as a single-level mixed-integer programming (MIP) model using Karush- Kuhn-Tucker (KKT) conditions to improve tractability and preserve market-clearing behavior. For the model validation and case study development, prosumer and consumer data are …

Development Of Periodic Plasmonic Nano-Structures For Enhanced Labeled Bio-Sensing Systems, Kyle Zackary Smith

Graduate Theses, Dissertations, and Problem Reports (ETD)

The biomedical industry has seen sustained growth over the past half century, with a continually increasing demand for flexible, easy-to-use, and cost-effective tools. One large area of commercial interest has been point-of-use or point-of-care diagnostics, using optical based Lab-On-Chip (LOC) style systems. Label and label-free fluorescence detection systems are common benchtop modalities that have seen recent integration into these portable, cost-effective LOC applications. However, despite their maturity, there are still opportunities to improve device characteristics, specifically in reference to throughput, limit-of-detection (LOD), and hybrid integration (along with associated costs).

Optical research avenues at WVU have focused on improving these systems …

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, …

Drone Endurance In Hydrogen Fuel Cell Hybrid Technologies: Power Architectures And Design Strategies, Yaw Chong Tak, Tarek Abedin, Johnny Koh Siaw Paw, Jagadeesh Pasupuleti, Tan Jian Ding, Tiong Sieh Kiong, K. Kadirgama, F. Benedict, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

This study delivers an exhaustive exploration of novel and hybrid power systems for Unmanned Aerial Vehicles (UAVs) aimed at improving endurance, efficiency, and mission performance. In the wake of increasing requirements for long-endurance and high-performance UAVs, traditional battery systems are limited by their energy density and lifetime. To overcome this, the research compares four primary power sources: hydrogen fuel cells, lithium-based batteries, photovoltaic cells, and supercapacitors, with a focus on their hybrid architecture integration. The originality of this research is in the relative comparison of these power sources in multi-mode UAV operations, with an emphasis on their performance, energy management …

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 …

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 …

Integrating Environmental Awareness In Underwater Acoustic Networks: A Comprehensive Review, Sadaf Vahabli, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi, Walid K. Hasan, Ruba Zaheer

Research outputs 2022 to 2026

Underwater Acoustic Networks (UANs) are critical for enabling long-range underwater communication, supporting a wide range of applications, such as environmental monitoring, resource exploration, disaster prevention and marine security. Unfortunately, UANs operate within a limited acoustic spectrum, where these spectrums often overlap with those used by marine animals for communication, navigation and foraging. Additionally, anthropogenic noise from industrial activities contributes to acoustic pollution, intensifying this problem. This frequency overlap poses significant risks to marine life. Therefore, this review highlights the urgent need to develop environmentally aware UANs that minimize harmful acoustic interference with marine mammals, fish and invertebrates. Further, it focuses …

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 …

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 …

A Novel Hybrid Robust Transfer Learning-Based Adaptive Fractional-Order Super-Twisting Sliding Mode Controller Enhanced For Speed Regulation Of Brushless Dc Motor, Seyyed Morteza Ghamari, Asma Aziz, Daryoush Habibi

Research outputs 2022 to 2026

Brushless DC (BLDC) motors are widely used in applications that are highly-efficient, reliable, and compact, such as electric vehicles, robotics, and medical devices. However, the inherent nonlinearities and load sensitivity of BLDC motors require a robust and adaptive control strategy to ensure satisfactory performance under various operating conditions. Sliding mode control (SMC) has been widely used for the BLDC drives. However, because of its simplicity and robustness, the control effectiveness of the control is limited by the sensitivity to the disturbances and the chattering phenomenon. To remedy this, super-twisting (ST) technique has been proposed to achieve smoother response and better …

Renewable And Affordable Energy For Apartments. Inquiry Into Renewable And Affordable Energy For Apartments, Nishadi Ruwandima Weerasinghe Mudiyanselage, Asma Aziz

Research outputs 2022 to 2026

Recent literature identifies a persistent disparity between detached housing and apartments in accessing renewable and affordable electricity. While rooftop solar PV deployment in Australia  has expanded rapidly since 2017, access to these technologies in multi-unit dwellings (MUDs) remains limited, resulting in higher electricity costs for apartment residents compared with standalone houses. This inequity is increasingly significant given rising electricity prices and the growing share of Australians living in apartments.

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 …

Design, Modeling, And Experimental Development Of Nanoscale Confinement Structures On Planar Silicon-Based Microelectrode Arrays For Single-Entity Electrochemical Sensing, Parinaz Eskandari

Dissertations, Master's Theses and Master's Reports

Electrochemical sensing is widely used for chemical and biological detection due to its high sensitivity, label-free operation, and compatibility with miniaturized electronic systems. However, conventional microelectrode platforms operate in an ensemble-averaged regime in which the measured current represents the collective response of many molecules interacting with the electrode surface. This ensemble averaging masks localized nanoscale electrochemical events and limits the ability to detect rare interactions, such as single molecules or nanoparticles. Achieving single-entity electrochemical detection therefore requires strategies that confine electrochemical reactions to nanoscale regions while maintaining compatibility with scalable planar microfabrication.

This dissertation investigates nanoscale electrochemical confinement on planar …

Experimental Rate Feedback Control Of A Model-Scale Hourglass-Shaped Heaving Point Absorber, James R. Halverson

Dissertations, Master's Theses and Master's Reports

Buoy geometry greatly affects a point absorber wave energy converter's dynamic response to waves. Finding the optimal buoy shape and control method remains an open research area focused on maximizing the conversion of wave kinetic energy into electricity. This work presents an experimental comparison of closed-loop energy extraction between a cylindrical and a truncated cone buoy, both with the same submerged volume, across various wave frequencies and amplitudes. To ensure a fair comparison, the optimal rate feedback gain is calculated for each buoy at each wave condition. Multiple metrics, including power output, capture width, and actuator force, are used to …

Experimental Characterization Of Photonic Crystal Based Invisibility Cloak Under Tm-Polarized Microwaves, Muhammad Danyal

Dissertations, Master's Theses and Master's Reports

Electromagnetic invisibility cloaks guide waves around an object so that the transmitted wavefront remains undisturbed. Most experimental microwave cloaking studies have focused on transverse electric (TE) polarization due to established measurement techniques. In this thesis, the experimental realization and characterization of a dielectric photonic crystal cloak operating under transverse magnetic (TM) polarization are presented. A measurement system operating in the X-band was developed to map the electric field distribution of the transmitted waves. Cloaking performance was first evaluated qualitatively by comparing numerical and experimental field distributions, where restoration of a flat wavefront indicated effective cloaking. Quantitative evaluation was performed by …

Open Source Tools For Ecological Research, Alex P. Riebe

Dissertations, Master's Theses and Master's Reports

This thesis presents the development of an open source wireless sensor network for hibernacula manipulation with an emphasis on accessibility and reproducibility. It addresses the design of the electrical hardware, guidance on antennas and RF implementation, and design of an application-specific communication protocol, all with the explicit goal of enabling ecologists and other conservationists to be able to manufacture, deploy, operate, and maintain the system for their research. The resulting sensor network designed in this thesis is to control the temperature inside bat hibernacula during the winter to study the relationship between temperature and bat mortality rate due to White …

Design And Validation Of A Low-Cost Wearable Electromyography (Emg) System For Monitoring Exercise-Induced Changes In Muscle Activity, Ingrid E. Halverson

Dissertations, Master's Theses and Master's Reports

Wearable technologies have expanded opportunities for monitoring athletic performance, but many existing systems remain costly and confined to laboratory or medical settings. This thesis presents the design, development, and evaluation of a low-cost, wearable EMG platform for monitoring neuromuscular activity during exercise. A wireless device incorporating a surface EMG sensor, an ESP32 microcontroller, and Wi-Fi transmission was developed to acquire muscle activation data. Signal processing techniques, including filtering, root-mean-square (RMS), mean frequency (MNF), and median frequency (MDF) analyses, were used to evaluate changes in muscle activation. Experimental testing demonstrated reliable wireless data acquisition and successful capture of physiological changes before …

High-Performance Circuit Manufacturing And Testing Exercises, Benjamin S. Keppers

Dissertations, Master's Theses and Master's Reports

An advanced demonstrator Printed Circuit Board (PCB) has been designed and implemented providing a framework for advancing students’ knowledge in hands-on PCB design and manufacturing process through industry recognized test coupons, stack ups, and transmission lines. Students are guided through several key aspects of design and simulation relating to manufacturing and qualifications. Manufacturing allows students to refine process development and analyze performance data with respect to qualification tests specified by Global Electronics Association standards. Results are then used to build a stackup model, and complete a design activity for calculating expected test results for a series of controlled impedance electrical …

Antenna-Based Sensors For Dielectric Characterization Of Materials, Hilary Scott Nkimbeng Cho

Dissertations, Master's Theses and Master's Reports

This research introduces antenna-based sensors for dielectric characterization aimed at overcoming the limitations of conventional microwave sensors. Although traditional microwave sensors are widely used for their noncontact operation, high sensitivity, and ability to penetrate various materials, they often face challenges such as large size and high-power consumption. To address these issues, antenna-based sensors are explored for their compactness, ease of fabrication, and flexible design adaptability across diverse sensing applications. An in-depth analysis of multiple antenna sensor configurations is conducted, followed by the design and development of high-performance sensing structures. A saw-tooth slot antenna sensor is developed for highly sensitive liquid …

A Novel Deep Transfer Learning-Based Adaptive Cascade Pi Controller Enhanced By Reinforcement Learning Algorithm And Snake Optimization For Robust Speed Regulation Of Brushless Dc Motors, Seyyed Morteza Ghamari, Asma Aziz

Research outputs 2022 to 2026

Brushless DC (BLDC) are common in electric cars, industrial automation, and robotics because of their high efficiency, high torque control, and compact size. Nevertheless, strong speed and current regulation is not easily attained because of system variation, load variations and the shortcomings of traditional fixed-gain proportional-integral (PI) controllers. In this paper, a new snake optimization-assisted deep transfer learning-based reinforcement learning (SOA-DTL-RL)-based adaptive cascade PI controller is proposed that combines transfer learning with fast adaptation, Reinforcement learning with real-time optimization, and snake optimization with optimal initial gain selection to guarantee the robust speed and current regulation in BLDC motors. The proposed …

Super-Resolution Learning Inspired Spectral-Spatial Correlation Network For Hyperspectral Target Detection, Jiaping Zhong, Yunsong Li, Jianxin Li, Yanzi Shi, Weiying Xie, Paolo Gamba

Research outputs 2022 to 2026

Hyperspectral target detection (HTD) aims at extracting targets from complex backgrounds while overcoming noise interference. Existing deep learning models for HTD usually suffer from low spatial resolution and unitary representation, especially in space-borne platforms. Super-resolution, as a critical technology to enhance the spatial details, could effectively address the aforementioned issue. To make super-resolution absolutely pose positive effects on target detection, this paper proposes an end-to-end novel super-resolution learning inspired spectral-spatial correlation network for hyperspectral target detection (SR-HTD) from the perspective of spatial and spectral regularization to achieve high-precision detection. Specifically, we designed a Spatial Correlation Aggregation (SCA) module inspired by …

Early-Time/High-Frequency Electromagnetic Induction Sensing For Minimal-Metal And None-Metallic Subsurface Targets, Michele Louise Maxson

Dartmouth College Ph.D Dissertations

Conventional electromagnetic induction (EMI) systems operate within the quasi-static regime, where measurements are dominated by conduction currents and are primarily sensitive to highly conductive targets and bulk soil properties. As a result, these systems exhibit limited sensitivity to low-conductivity and layered media, such as permafrost, composite materials, and minimum-metal landmines, where diagnostically relevant information resides in early-time/high-frequency electromagnetic responses, generally above 100 kHz. This limitation reflects a mismatch between conventional EMI system design and the underlying target physics, restricting the ability of standard EMI approaches to resolve fine-scale non-metallic subsurface structure.

In this thesis, I investigate early-time/high-frequency sensitivity as a …

Covert Performance Of Star-Ris Aided Thz Communication System With Rsma And Phase Errors, Xiangbin Yu, Yue Zhou, Shihao Yan, Yun Rui, Xiaoyu Dang, Chau Yuen, Mohsen Guizani

Research outputs 2022 to 2026

In this paper, the covert performance of the simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided Terahertz (THz) communication systems with rate-splitting multiple access (RSMA) over the generalized α-μ fading channel is studied, where the discrete phase error and noise power uncertainty are considered. By means of the Gaussian approximation and Gamma distribution, the closed-form outage probability (OP) of the legitimate users is firstly derived. Then, the covert performance of the system is analyzed, and average detection error probability (ADEP) is deduced for the warden, and resultant closed-form ADEP is obtained. By minimizing the ADEP, the optimal detection threshold …

Optimizing The Size And Siting Of Distributed Generation In Unbalanced Distribution Systems With Multi-Objective Reptile Search Algorithm, Pema Dorji, Chimi Pelden Dorji, Stefan Lachowicz, Octavian Bass

Research outputs 2022 to 2026

This paper presents the Multi-Objective Reptile Search algorithm for identifying ideal rating and location of distributed generation in unbalanced grids, focusing on minimizing power losses, total costs, and carbon emissions. The proposed methodology integrates DIgSILENT PowerFactory and Python platforms to evaluate unbalanced IEEE distribution feeders under varying power factor conditions. The results demonstrate that optimal DG configurations involve strategically positioning multiple units to enable both active and reactive power injection, significantly improving overall system performance across multiple objectives and voltage deviation index. The analysis identifies an optimal PF range between 0.75 and 0.89, with unity power factor operations yielding suboptimal …

Optimal Sizing Of Pv Water Pumping System For Off-Grid Rural Communities, Basma Abulkheir, Eid Gouda, A. A. Hegazi, Amir Abdel Menaem

Mansoura Engineering Journal

A large population worldwide lives in remote rural communities without access to electricity due to the limited reach of national transmission networks. This creates significant challenges in accessing water, hindering improvements in living conditions for off-grid communities. Photovoltaic water pumping systems (PVWPSs) offer a viable solution to this issue, but their sustainability must be examined due to the unpredictable nature of solar radiation. This paper presents a practical techno-economic approach to optimally size a PVWPS. A Particle Swarm Optimization (PSO) algorithm is employed, considering technical and economic indicators like life cycle cost, loss of load probability and PV curtailment rate. …

Real-Time Deep Learning Detection Of Toraja Carving Motifs Using Yolo11m For Cultural Heritage Preservation, Herman Herman, Farid Wajdi Mufti, Abdul Rachman Manga, Haidawati Nasir

Knowledge Engineering and Data Science

Toraja carvings are an important part of Indonesia’s cultural heritage, rich in symbolic, aesthetic, and philosophical meaning. However, the identification and preservation of carving motifs still rely on subjective, time-consuming manual processes, limiting scalability and inconsistent knowledge transmission. From a Knowledge Engineering and Cognitive Data Science perspective, this challenge highlights the need for mechanisms that can transform visual cultural artifacts into structured, machine-interpretable knowledge. This study investigates the use of the YOLO11m model as a data-driven approach for modeling cultural knowledge through automated detection of three Toraja carving motifs: pa_tedong, pa_kapu_baka, and pa_manu_londongan using original images collected directly from traditional …

Dual-Interface Wifi Packet Sniffer System Using Esp32-Cam With Real-Time Pcap Generation For Iot Network Analysis, Boy Setiawan Boy, Maghfiroh Maulani, Zico Pratama Putra, Muhammad Senoyodha Brennaf

Makara Journal of Technology

This study focuses on designing and implementing a cost-effective and energy-efficient WiFi packet sniffer system using the ESP32. The ESP32-CAM module, which combines WiFi, Bluetooth, and microSD support, is used to capture IEEE 802.11 frames in real-time via promiscuous mode. Packets are stored in packet capture format, which is compatible with tools such as Wireshark and Scapy. Developed using the official ESP-IDF, it offers low-level control and high performance. Two user interfaces were implemented: a UART-based text menu and a web-based HTTPS menu hosted on the ESP32 itself. Functional and performance evaluations were conducted with a focus on capturing broadcast …

Detection And Correction Of Object Orientation On Production Lines Using Photodetector-Based Systems, Utkirjon Ubaydullayev, Elmira Raxmanova

Technical science and innovation

This article addresses the issue of errors occurring in high-speed production lines, particularly those caused by misalignment or incorrect positioning of manufactured objects. Although production lines have significantly enhanced industrial efficiency worldwide, they are not immune to mistakes, especially under rapid operation conditions. To mitigate these errors without human intervention, the proposed solution integrates photodetector sensor matrices with robotic manipulators. The system uses high-resolution photodetector arrays, such as the Hamamatsu S13774 CMOS Linear Image Sensor, to capture shadows of objects on the production line, converting these into numerical data. This data is then processed using Principal Component Analysis (PCA) and …