Electrical and Computer Engineering Commons^™

Toward A Generalizable Perceptual Hashing Framework For Image Manipulation Detection, Priyanka Samanta

Dissertations, Theses, and Capstone Projects

This thesis contributes to research in adversarial image manipulation detection. The primary motivation is the increasing need to verify digital images, especially for legal evidence, journalistic proof, or social media content—where manipulated or fabricated images can mislead, defame, or distort reality. A key application and contribution of this work is the development of eWitness, a blockchain application that generates and registers image provenance at capture time to enable independent verification of authenticity. The secret sauce behind the system is SmartHash, a novel and efficient perceptual hashing algorithm designed for real-world deployment in systems like eWitness. Unlike existing algorithms, SmartHash targets …

Improved Triboelectric Nanogenerator By As-Prepared Lithium Niobate For Energy Harvesting And Sensing Applications, Jahid Inam Chowdhury, Md. Wasikur Rahman, Md Arafat Hossain, Nicholas Dimakis, Mohammed Jasim Uddin

School of Integrative Biological & Chemical Sciences Faculty Publications

Triboelectric nanogenerators (TENGs) have garnered significant research interest due to their ability to harvest mechanical energy efficiently. In this study, we report a TENG composed of polydimethylsiloxane (PDMS) and polyvinyl alcohol (PVA) as triboelectric layers. To enhance charge generation in the PDMS composite polymer, we incorporated lithium niobate (LiNbO3) nanoparticles, leveraging their piezoelectric and ferroelectric properties. The LiNbO3 nanoparticles were synthesized using a solid-state reaction method, resulting in two distinct phases: triclinic LiNbO3 and monoclinic LiNb3O8. Various weight percentages of LiNbO3 and LiNb3O8 nanoparticles were added to the PDMS matrix to optimize power generation. The maximum open-circuit voltage (VOC) and …

Electrical Characterization Of Germanium Tin Alloys And Devices For Space Reliability, Kevin K. Choe

Theses and Dissertations

GeSn (germanium tin) alloys are potentially well suited for near-mid infrared space optoelectronic applications. Alloys of GeSn have similar properties to group III-V and mercury-cadmium-telluride semiconductors and are compatible with cost-effective complementary metal oxide semiconductor (CMOS) manufacturing technology. Recent progress in non-equilibrium remote plasma-enhanced chemical vapor deposition (RPECVD) has enabled the crystalline growth of GeSn with Sn concentrations of up to 10% without Sn surface segregation. Several experimental studies in previous literature report CVD- or molecular beam epitaxy (MBE)-grown GeSn alloys achieving a direct bandgap with 6%-9% Sn content. This novel growth technique opens opportunities for a cost-effective, next-generation optical …

Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson

Theses and Dissertations

Predicting ionosphere effects on radio wave propagation is critical for communications and over-the-horizon radar systems. The D region is challenging to model for several reasons, one of which is chemical complexity. Ion density changes during sunrise/sunset introduce substantial uncertainty in electron density profiles (EDPs). The Data Driven D Region (D3R) model solves electron densities through an ion chemistry model and assimilates relevant space weather inputs. This study evaluates D3R against the Faraday International Reference Ionosphere (FIRI) and measurements using Very Low Frequency (VLF) propagation paths. Space weather event impacts on D3R EDPs are evaluated during the disturbed period from 8-12 …

Renewable-Based Isolated Power Systems: A Review Of Scalability, Reliability, And Uncertainty Modeling, Mehrdad Ghahramani, Daryoush Habibi, Seyyedmorteza Ghamari, Hamid Soleimani, Asma Aziz

Research outputs 2022 to 2026

Electric power systems are increasingly becoming more decentralized. Many communities depend on isolated power systems that operate independently of the main grid. Remote, islanded, and isolated systems face challenges due to the intermittency and unpredictability of renewable energy sources. This paper reviews the current status of renewable integration and control in stand-alone power systems. It examines techniques to enhance system reliability through energy storage, hybrid systems, and advanced predictive models. Additionally, the issues related to connecting stand-alone systems, focusing on reliability and renewable penetration, are discussed. The scalability of stand-alone power systems is analyzed based on classifications of small-, medium-, …

Optimizing Hip And Knee Assistance For Walking And Sit-To-Stand Transitions: An Intrinsic Muscle Mechanics Based Predictive Approach, Neethan Ratnakumar

Dissertations

As the global population ages, the demand for wearable assistive technologies continues to rise, driven by their potential to enhance mobility and independence in older adults. Effectively designed controllers for lower-limb exoskeletons to assist sit-to-stand (STS) and walking are crucial for delivering efficient, safe, and comfortable assistance during daily activities. Traditionally, controller optimization involves biomechanical modeling and user-specific customization. Musculoskeletal simulations play a central role in this process by providing insights into human-exoskeleton interaction dynamics, thereby informing and refining control strategies.

This work presents a simulation-driven approach for developing exoskeleton controllers for walking and STS using two distinct methods: optimal …

An Audio Data-Driven Roadway Digital Twin And Its Underlying Framework For A Digitized Transportation Construction Environment, Anisha Deria, Pedro J. Chacon Dominguez, Yong-Cheol Lee, Jin W. Choi

Michigan Tech Publications

The increasing need to build and maintain transportation systems has led project managers to manage multiple projects simultaneously. Roadway projects often entail several miles of job site, making it difficult to keep track of progress and maintenance activities. To improve the situation, this study proposes an audio data-driven roadway digital twin framework for real-time and remote monitoring of construction projects. The latent characteristics of a digital twin required for establishing a digitized work environment were investigated. As a primary method of seamlessly linking virtual and physical environments, audio data classified and analyzed by deep neural network (DNN) has been employed …

Predicting The Response Of Tendon-Driven Prosthetic Finger With Hyperelastic Joints, Lucas Gallup, Mohamed Trabia, Brendan O'Toole

Mechanical Engineering Faculty Research

Properly designed prosthetics hands can enhance the quality of life for those suffering from limb loss. Recently, 3D-printed prosthetic hands are becoming common. In these prostheses, fingers flex through the tendons that are activated by motion of the wrist. To provide spring action, thermoplastic polyurethane (TPU) hyperelastic joints are used to connect digits to each other as well as to the wrist. While these designs are common, no model for the relationship between tendon tension and joint flexion is available. This work has developed a quasi-static virtual work-based model to predict the relationship between tendon forces and the flexion of …

Superhydrophilic Porous Coooh Nano-Architecture With Abundant Oxygen Vacancies For Enhanced Urea Electrooxidation At Ampere-Level Current Densities, Wen-Jing Lv, Xiao-Man Tang, Xue-Tong Wang, Wen-Cai Liu, Jian-Wen Zhu, Guo-Jing Wang, Yuan-Zhi Zhu

Journal of Electrochemistry

The conversion of urea-containing wastewater into clean hydrogen energy has gained increasing attention. However, challenges remain, particularly with sluggish catalytic kinetics and limited long-term stability of urea oxidation reaction (UOR). Herein, we report the loosely porous CoOOH nano-architecture (CoOOH LPNAs) with hydrophilic surface and abundant oxygen vacancies (O_v) on carbon fiber paper (CFP) by electrochemical reconstruction of the CoP nanoneedles precursor. The resulting three-dimensional electrode exhibited an impressively low potential of 1.38 V at 1000 mA·cm⁻² and excellent durability for UOR. Furthermore, when tested in an anion exchange membrane (AEM) electrolyzer, it required only 1.53 V at …

Structure Regulation Engineering For Biomass-Derived Carbon Anodes Enabling High-Rate Dual-Ion Batteries, Rui Zhou, Rui Liu, Yun-Nuo Li, Si-Jie Jiang, Tian-Tian Jing, Yan-Song Xu, Fei-Fei Cao

Journal of Electrochemistry

Dual-ion batteries (DIBs) usually use carbon-based materials as electrodes, showing advantages in high operating voltage, potential low cost, and environmental friendliness. Different from conventional “rocking chair” type secondary batteries, DIBs perform a unique working mechanism, which employ both cation and anion taking part in capacity contribution at an anode and a cathode, respectively, during electrochemical reactions. Graphite has been identified as a suitable cathode material for anion intercalation at high voltages (> 4.8 V) with fast reaction kinetics. However, the development of DIBs is being hindered by dynamic mismatch between a cathode and an anode due to sluggish Li^{+ …}

Design And Optimization Of Anode Catalysts For Direct Ethanol Fuel Cells: Advances And Challenges In C-C Bond Activation And Selective Modulation Of The C1 Pathway, Kai-Chi Qin, Meng-Tian Huo, Yu Liang, Si-Yuan Zhu, Zi-Hao Xing, Jin-Fa Chang

Journal of Electrochemistry

Direct ethanol fuel cells (DEFCs) are a promising alternative to conventional energy sources, offering high energy density, environmental sustainability, and operational safety. Compared to methanol fuel cells, DEFCs exhibit lower toxicity and a more mature preparation process. Unlike hydrogen fuel cells, DEFCs provide superior storage and transport feasibility, as well as cost-effectiveness, significantly enhancing their commercial viability. However, the stable C–C bond in ethanol creates a high activation energy barrier, often resulting in incomplete electrooxidation. Current commercial platinum (Pt)- and palladium (Pd)-based catalysts demonstrate low C–C bond cleavage efficiency (

Assessing Solar Radiation Patterns In Sarawak Using Measured Data And The Hargreaves-Samani Model For Photovoltaic Systems Application, Chun Yong Soo, Xian Hwa Chan, Wan Mohamad Husni Wan Mokhtar, Ahmad Rujhan Mohd Rais

Makara Journal of Technology

This study evaluates the Hargreaves-Samani model for estimating solar radiation in five locations in Sarawak: Bintulu, Kapit, Sri Aman, Kuching, and Miri (Subis), using minimum and maximum temperatures as key inputs. Analysis reveals stable minimum temperatures (19.7 °C to 28.8 °C), supporting consistent solar radiation patterns favorable for Photovoltaic (PV) performance. Miri (Subis) recorded the highest daily maximum temperature of 44.8 °C, while Kuching had the lowest at 24.7 °C, highlighting significant regional climatic variability. Analysis also indicates strong solar potential in Bintulu, Kapit, Sri Aman, Kuching, and Miri, with radiation peaking at 7.5 kWh/m², though seasonal variations impact PV …

Direct Control Strategy Using Polynomial Fuzzy-Based Adaptive Fractional Order Pid Controller, Ali Rospawan, Clara Lavita Angelina, Faisal Samsuri, Muhammad Yeza Baihaqi, Edmun Halawa, Muhammad Munajat, Vincent Vincent, Surawan Setiyadi, Irwan Purnama, Joni Welman Simatupang

Makara Journal of Technology

This paper presents a novel direct control strategy using a polynomial fuzzy neural network-based adaptive fractional order proportional integral derivative (PFNN-AFOPID) controller for nonlinear and time-varying systems. The proposed approach integrates the enhanced flexibility of fractional order calculus PID with the superior nonlinear approximation capabilities of polynomial fuzzy models, enabling dynamic adjustment of all control parameters without requiring precise mathematical modeling of system dynamics. By extending traditional PID control with fractional-order operations, the controller achieves improved frequency response and robustness against disturbances. Experimental validation on a DC motor position control system demonstrates significant performance improvements. Compared to traditional PID, the …

Analog To Digital Converters Topologies For Radar System Application: A Comparison, Kulsoom Mateen, Wafa Alharbi, Aziza I. Hussein

Effat Undergraduate Research Journal

Analog-to-digital converters (ADCs) that convert analog signals into digital ones play a significant role in radar systems. The accuracy and resolution of radar readings are significantly influenced by the quality and performance of ADCs. This paper discusses and compares the application of five different types of ADCs in radar systems. It also elaborates on each ADC's working principle, advantages, and limitations. The parameters compared are resolution and dynamic range, signal-to-noise ratio (SNR), latency and sampling rate, power consumption, size, and cost. After thorough research, we concluded that each ADC differs depending on the designer’s desired application. For example, flash ADCs …

Satellite Internet Technology: Connect The Unconnected, Nora Turki Alamoudi Ms., Aziza I.Hussien Proffessor

Effat Undergraduate Research Journal

Satellite Internet is the internet provided through a network of communication satellite constellations in space. This type of internet can cover an area of a wider range than the commonly used cable internet. The development of small-sized satellite technology in the commercial space sector has entered a vigorous phase of development. However, approximately four billion individuals worldwide lack internet access. Most of these citizens live in developing countries. It is in this context that the industry of satellite internet is expanding its social and economic development through connectivity. The implementation of the idea requires examining the advantages provided by satellite …

Sar Analog-To-Digital Converters For Point-Of-Care Biosensors: A Comparison, Eithar Alammari, Joud Alamro, Sara Alashwali, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

The SAR ADC, recognized for its low power consumption, moderate resolution, and satisfactory processing speed, stands as an ideal choice for ultra-low power biomedical applications. Recent efforts have been concentrated on enhancing the power efficiency of the SAR ADC sub-components through intricate refinements and innovative techniques. These efforts aim to minimize energy consumption without compromising the ADC's performance. Therefore, this paper aims to thoroughly examine various implementation approaches for the main components of the SAR ADC, highlighting their individual strengths, weaknesses, and limitations within wireless biomedical applications.

Electrical Energy Consumption Forecasting Based On Conventional And Artificial Intelligence Methods: A Comparison, Haya H. Binsalim, Jana Kamal, Salma Badaam, Danah Milyani, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

Artificial Intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review and compare the classical techniques and the emerging new AI-based techniques used for forecasting electrical energy consumption in buildings. The findings revealed that the Artificial Neural Network (ANN) model achieved the lowest Mean Absolute Percentage Error (MAPE) of 0.928%. AI-based techniques have many advantages over classical techniques, such as their ability to handle a large amount of data and provide accurate and fast results.

Continuous Versus Discrete-Time Sigma-Delta Analog To Digital Converters For Biomedical Applications: A Comparison, Haya H. Binsalim, Batool Alaidroos, Basma Shigdar, Salma Badaam, Aziza I. Hussein

Effat Undergraduate Research Journal

Continuous-time (CT) and discrete-time (DT) sigma-delta (ΔΣ) converters are two commonly used techniques for analog-to-digital conversion. While both methods operate based on the principles of oversampling and noise shaping, they differ in their implementation and performance characteristics. CT ΔΣ converters use analog circuits to sample and process signals continuously, while DT ΔΣ utilizes digital circuits to sample and process signals at discrete intervals. This paper presents a comprehensive comparison between CT and DT ΔΣ converters, highlighting their advantages and limitations. The comparison is made in terms of design complexity, power consumption, signal-to-noise ratio (SNR), and other essential parameters in medical …

Wideband Spectrum Sensing For Cognitive Radio Using Under-Sampled Successive Approximation Adc, Aziza I. Hussein

Effat Undergraduate Research Journal

The radio spectrum, an inherently limited resource, has been increasingly utilized owing to the recent exponential growth of wireless services. This has led to a new approach, termed cognitive radio, predicated upon exploitation of spectrum holes for omnipresent spectrum utilization. This is made possible via cognitive radio networks’ employment of spectrum sensing. Wideband spectrum sensing has been the focal challenge point in cognitive radio technology, since existing techniques are reliant on analog to digital converters (ADC) with sampling at the Nyquist rate. Unfortunately, in order to perform digitization of wideband RF signals at the Nyquist rate, a very high sampling …

Fault Detection In Analog Vlsi Circuits Based On Artificial Intelligence

Effat Undergraduate Research Journal

In thepastdecade,artificialintelligence(AI)hasbeenonthe rise asatooltobeutilizedacrossallthefieldsavailableintheindustry. Specificallyinthemicroelectronicsfield,exploringthecurrentoptionsof VLSI faultdetectionandtheirtypesiscrucialforadvancementandis importantinidentifyingwhetherthereisroomforimprovementorthe optimumisalreadybeingdone.Therefore,thepurposeofthisresearch is tocompareandcontrastbetweenVLSIfaultdetectionindigitaland analog circuitsusingAI.Techniquestoimproveefficiencysuchastrou- bleshootinginsmallsegmentsratherthanthewholesystemandsome resolutions todrawbacksthataren’tdetectibletohumansliketimingare discussed andresolvedinthispaper.Moreover,somenon-idealitiesand risks likemarginalstabilitywereconsidered.Finally,presentelements that areusedintoday’sfaultdetectioncircuitslikeneuralcontrollers and theANNswerediscussedaswell.Currently,theANNsarethemost utilized toolforfaultdiagnosesanddetection;however,forthecontinu- ation ofthistechnology’sgrowth,developersneedtofindmoreefficient methodstomovepastit.

Electrical Energy Consumption Forecasting Analysis Based On Conventional And Artificial Intelligence Methods: A Comparison, Aziza I. Hussein

Effat Undergraduate Research Journal

Artificial intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review the classical techniques and the emerging new techniques based on AI of the building electrical energy consumption forecasting. The advantages of AI-based techniques over the classical are that AI methods can handle a large amount of data yet gives accurate results, the results can be found very quickly, in addition to AI having the ability to solve complex nonlinear patterns of raw data. This paper will discuss several studies using different models of forecasting based on …

Evaluation Of The Performance Of The Traveling Wave Differential Element In Protective Relays, Niranjan Kc

Master's Theses

This thesis evaluates the dependability, security, and limitations of the traveling wave differential protection function (TW87) in modern time-domain-based protective relays, using a combination of simulations and hardware testing in a laboratory environment. Fault transients are first generated using the electromagnetic transients program model of a real, 230 kV, 65.7 km long overhead transmission line, which are then played back on real time-domain-based protective relays. Various fault scenarios are chosen to evaluate the impacts of factors such as fault inception angle, distance to fault from line terminals, fault type, fault impedance, and external faults on the relay functions’ performance. Results …

The Design Of Coplanar Waveguide Traveling-Wave Kinetic-Impedance Parametric Amplifiers, Jordan Scott Savoie

Master's Theses

Astronomical observations and many physics experiments rely on cryogenic amplifiers for readout. Current sensitivity is limited by the noise figure of high-electronmobility transistor (HEMT) amplifiers, which have proven di!cult to decrease further in recent years. Traveling-wave kinetic-impedance parametric amplifiers (TKIPAs) are an emerging class of amplifiers which have the potential to substantially improve the sensitivity of microwave low-noise amplifiers (LNAs) while also accepting relatively high input powers and amplifying over a wide bandwidth. In this thesis, I present the design, modeling, and testing procedures for coplanar waveguide (CPW) TKIPAs developed by our group at the National Radio Astronomy Observatory. Using …

Developing Deep Learning Methods For Cognitive Impairment Detection Based On Non-Invasive Data, Muath Alsuhaibani

Electronic Theses and Dissertations

Cognitive impairment detection is on the rise to help reduce the burden of healthcare costs on institutions and individuals. Mild Cognitive Impairment (MCI) is an early stage of cognitive decline progressing to Alzheimer’s disease (AD) or AD-related Dementia (ADRD). Detecting the early stages of AD/ADRD is crucial for early interventions among older adults to mitigate cognitive decline over time. However, the current diagnostic methods are often costly and/or invasive, such as MRI and PET scans. Thus, the search for non-invasive and cost-effective screening tools for the early detection of cognitive impairment using speech, language, visual, and motor data is growing. …

Assessing Cascaded Op-Amp And Pre-Current Amplifier Configurations In Transimpedance Amplifier Interfacing Circuits For Nano-Scale Current-Based Sensor Applications, Mohamed Mamdouh, Sameh O. Abdellatif

Electrical Engineering

This study provides a comprehensive analysis of two proposed configurations for current-to-voltage converters tailored for nano-scale current-based sensor applications, focusing on key performance metrics such as linearity, dynamic range, DC noise immunity, and power losses. The evaluation employed frequency-dependent analyses, including transient response, step response, input impedance, and frequency-dependent noise spectra, to compare a cascaded double output configuration with a pre-current amplifier design. The results indicate a trade-off between dynamic range and linearity, with the pre-current amplifier demonstrating a higher dynamic range but lower linearity compared to the cascaded configuration. Additionally, the current amplifier configuration exhibited advantages in power consumption …

Investigating Resilience Of Cyberattack Detection Using Lyapunov-Based Economic Model Predictive Control To Data Poisoning, Helen Durand, Akkarakaran Francis Leonard

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks may be performed on process control systems due to their integration of networking and computing with physical systems. Prior work in our group has developed detection strategies for nonlinear systems under sensor, actuator, and combined sensor and actuator attacks which can ensure, under characterizable conditions, that attacks can be detected before they cause safety issues. However, this work did not take into account the potential that an attacker could attempt to provide data to a process that causes an attack to remain undetected but that also is consistent with different process dynamics than those which the process has. This …

Response Of Dynamic Processes With Control Implemented On A Noisy Quantum Computer, Shilpa Narashimhan, Dominic Messina, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

A major challenge to determining the applicability (and potential outperformance over classical computers) of a quantum computer (QC) within chemical manufacturing processes is quantum noise. Computations by a QC are error-prone due to the influence of quantum noise inherent to the hardware. Errors in control inputs may destabilize a chemical process and lead to unsafe conditions for manufacturing personnel and the environment. The response of a process with control implemented on a QC to errors due to noise must be investigated thoroughly. In this work, the impacts of control input errors due to quantum noise on a process are modeled …

Heuristic Strategies For Process Stabilization Using Proportional Control Implemented By A Noisy Quantum Simulator, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Processing and storage demands of industrial processes are causing fields such as optimization, scheduling, and control to assess the effectiveness of quantum devices in their applications. A key objective of control systems is to ensure process safety. This paper focuses on the potential of quantum devices to compute control inputs that maintain system safety despite sources of nondeterminism inherent to currently available quantum devices (quantum noise). In our previous work, we employed a quantum simulator to assess whether a quantum implementation of a proportional (P) control law could stabilize a single-input/single-output system under quantum noise approximated from a real quantum …

Tools To Design Algorithms For Implementing Control Over Quantum Computers, Shilpa Narashimhan, Jihan Abou Halloun, Kip Nieman, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Quantum computers (QCs) may find future applications within control systems that operate manufacturing processes. For application within control engineering, quantum algorithm development must be led by control engineers. However, control engineers may face challenges in designing quantum algorithms for control engineering problems. In this work, we provide several path-finding studies that leverage engineering tools such as optimization, encryption, and computational "short-cuts" toward making algorithm design for QC easier for control engineers.

Improving High Frequency Absorptive Filters For Quantum Computing, Christopher B. Sutton

Graduate Masters Theses

Coaxial transmission lines in superconducting quantum circuits are subject to infrared radiation (IR) leakage as signals travel from room temperature (≈ 300 K) to low temperature (≈ 10 mK). Current experimental configurations typically include an epoxy based filter on all cables connecting classical devices (pulse generators, VNA, etc.) to the quantum circuit. The epoxy is characterized by its dielectric properties per unit length and acts as an absorber, attenuating IR noise. Historically, such IR filters have been fabricated by the experimentalists who require them, more recently they have become commercially available. This work investigates the performance of filters which were …