Electrical and Computer Engineering Commons^™

Time-Domain Line Protection In Presence Of Renewables, Prabin Adhikari

All Dissertations

Inverter based resources (IBRs) are crucial in integrating renewable energy sources into the power grid. However, their unique fault characteristics, significantly different from synchronous generators (SGs), present several challenges for existing line protection schemes at both transmission and distribution levels. These schemes, reliant on distance and directional relays designed in phasor domain, are not well-suited for IBRs. Most published literature addressing this problem concentrates on altering the control design of inverters. However, this approach faces practical limitations. Inverter controls, often proprietary, are not readily accessible to utilities, rendering the control-based solutions impractical for widespread implementation.

To address this challenge, this …

Computer Vision Algorithms For Assessment Of Surgical Suturing Skill Using Hand And Needle Motion, Jianxin Gao

All Dissertations

Surgical suturing skill assessment is a crucial part of surgical education. Vascular surgery educators have developed a simulation-based examination called Fundamentals of Vascular Surgery, which includes a clock-face model for assessing open surgical suturing skills. The clock-face model, however, requires the valuable time of expert surgeons to determine examinees' skills. Moreover, expert surgeons have different judgments for appropriate sutures, which leads to inconsistent grading. These limitations motivate us to use sensors to measure examinees' needle motions and hand motions during the clock-face suturing exercises, and then use the measurements for objective suturing skill assessment.

To assess suturing skills based on …

Impacts Of High-Frequency Operation On Magnetics And Performance On Isolated Power Electronic Converter Design, David Arturo Porras Fernandez

Graduate Theses and Dissertations

The pursuit of high-power density and high switching frequency is a central theme in the advancement of power electronic converters. While these parameters offer significant benefits in terms of compactness and performance, they also introduce challenges related to efficiency and thermal management. This doctoral dissertation aims to provides a design framework to analyze the implications of high-frequency operation (> 100 kHz) on magnetics design and performance in power electronic converters, particularly when integrating silicon carbide (SiC) power modules. It examines the advantages and disadvantages of high-frequency operation and delves into its effects on the performance of the converter, focusing on …

Evaluation, Modeling And Application Of Gallium Nitride Field Effect Transistor, Geno Guillaume

Graduate Theses and Dissertations

Gallium Nitride (GaN) has emerged as one of the leading materials for power devices due to its wide band gap and high electron mobility. The band gap is the minimum energy required to excite an electron up to a state in the conduction band where it can participate in conduction. Because of this, wide band gap (WBG) materials are favorable for various electrical applications. The market for GaN high-electron-mobility transistor (HEMT) is projected to exceed $1.25 billion by 2027. With the increase of market interest, modern technologies emerge that aim to push the boundaries of efficiency for GaN power devices. …

Modeling, Optimization, And Characterization For Choke Horn Antennas, Ibrahim Nasser I Alquaydheb

Graduate Theses and Dissertations

This dissertation presents a comprehensive study focusing on the modeling, optimization, and characterization of choke horn antennas (CHAs). An analytical model designed to capture the parameters of CHA and derive the total radiated fields from the choke and waveguide elements is primarily focused on in this work. Compared to the use of simulation software, such as ANSYS HFSS (High Frequency Structure Simulator) or CST Studio, which employs numerical methods to simulate and calculate antenna performance, numerous advantages are offered by the analytical model. Analytical models provide deeper insight into electromagnetic interactions and the principles governing antenna behavior, leading to a …

Thermal Management Of Roadway-Embedded Power Electronics For Electric Vehicle Dynamic Wireless Charging Systems, Conner R. Sabin

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles (EVs) are gaining popularity worldwide. However, concerns raised by the public about purchasing EVs include the limited availability of charging infrastructure, high costs, and the inconvenience of current charging methods. Dynamic wireless charging systems enable electric vehicles to charge while driving, thereby extending the range of EVs and reducing the necessity for large, expensive batteries. Moreover, these systems can initiate charging automatically without user interaction, enhancing charging convenience.

The ground assembly of existing dynamic wireless charging systems consists of an electromagnetic assembly, power electronics for the transmitter pad, and power electronics for grid connection. Installation of these systems …

Periodic Information Leakage Fault Detection On A Risc-V Microprocessor, Idris Somoye

Electrical and Computer Engineering ETDs

The execution behavior of a Microprocessor (μP) in the presence of a fault is difficult to predict because of the complex interactions across pipeline stages and between functional units within the architecture. Fault effects are known to not introduce any type of anomaly in the input-output behavior for 10s of thousands to millions of clock cycles. These characteristics increase the difficulty of evaluating μP architectures for resilience to information leakage events, i.e., scenarios where a fault causes sensitive data such as an encryption key to be inadvertently diverted to a primary output channel. This dissertation explores two promising strategies for …

Secondary Electron Yield Of Metals, Alloys, And Metal Oxides From First Principles Based Monte Carlo Simulations, Raul E. Gutierrez

Electrical and Computer Engineering ETDs

Density Functional Theory (DFT) based Monte Carlo (MC) simulations of the Sec-
ondary Electron Yield (SEY) of metals, alloys, and metal oxides are performed to
find material properties that could help reduce or influence the multipactor effect.
In order to accurately model the SEY of materials, knowledge of the frequency- and
momentum-dependent Energy Loss Function (qDepELF) is required. The qDepELF
is difficult to determine from experiment; however, it can be calculated from first
principles. The DFT-MC approach for simulating the secondary electron genera-
tion, propagation, and emission processes is described herein. Material properties,
which are calculated using DFT and used …

Fabrication And Characterization Of A Monolithic Photonic Integrated Circuit With High-Aspect Ratio Photonic Device Structures, Sami A. Nazib

Optical Science and Engineering ETDs

The focus of this work was to create a process to fabricate an InP-based Photonic Integrated Circuit (PIC). The design of the PIC required the photonic components of this device to be created by deep etching of an epitaxially-grown multilayer structure. Therefore, a novel dry etching process was developed to produce very high aspect- ratio (HAR) features. This process not only involved the development of dry etch chemistry but also the engineering of a metal mask structure. The next step of the challenge was to use a polymer-based material that would have two functions: cladding for the etched photonic components …

Data-Driven Viewpoint For Developing Next-Generation Mg-Ion Solid-State Electrolytes, Fang-Ling Yang, Ryuhei Sato, Eric Jian-Feng Cheng, Kazuaki Kisu, Qian Wang, Xue Jia, Shin-Ichi Orimo, Hao Li

Journal of Electrochemistry

Magnesium (Mg) is a promising alternative to lithium (Li) in solid-state batteries due to its abundance and high theoretical volumetric capacity. However, the sluggish Mg-ion conduction in the lattice of solid-state electrolytes (SSEs) is one of the key challenges that hamper the development of Mg-ion solid-state batteries. Though various Mg-ion SSEs have been reported in recent years, key insights are hard to be derived from a single literature report. Besides, the structure-performance relationships of Mg-ion SSEs need to be further unraveled to provide a more precise design guideline for SSEs. In this Viewpoints article, we analyze the structural characteristics of …

Professor Yong Yang, The Editorial Board Member Of Journal Of Electrochemistry, Is Elected As A Fellow Of The Electrochemical Society, Editorial Office Of J.Electrochem.

Journal of Electrochemistry

No abstract provided.

Kai Wu, The Editorial Board Member Of Journal Of Electrochemistry And Chief Scientist Of Catl, Receives The National Science And Technology Progress Award, Editorial Office Of J.Electrochem.

Journal of Electrochemistry

No abstract provided.

Sorbitol-Electrolyte-Additive Based Reversible Zinc Electrochemistry, Qiong Sun, Hai-Hui Du, Tian-Jiang Sun, Dian-Tao Li, Min Cheng, Jing Liang, Hai-Xia Li, Zhan-Liang Tao

Journal of Electrochemistry

The unstable zinc (Zn)/electrolyte interfaces formed by undesired dendrites and parasitic side reactions greatly hinder the development of aqueous zinc ion batteries. Herein, the hydroxy-rich sorbitol was used as an additive to reshape the solvation structure and modulate the interface chemistry. The strong interactions among sorbitol and both water molecules and Zn electrode can reduce the free water activity, optimize the solvation shell of water and Zn²⁺ ions, and regulate the formation of local water (H₂O)-poor environment on the surface of Zn electrode, which effectively inhibit the decomposition of water molecules, and thus, achieve the thermodynamically stable …

Series Reports From Professor Wei’S Group Of Chongqing University: Advancements In Electrochemical Energy Conversions (1/4): Report 1: High-Performance Oxygen Reduction Catalysts For Fuel Cells, Fa-Dong Chen, Zhuo-Yang Xie, Meng-Ting Li, Si-Guo Chen, Wei Ding, Li Li, Jing Li, Zi-Dong Wei

Journal of Electrochemistry

Two major challenges, high cost and short lifespan, have been hindering the commercialization process of low-temperature fuel cells. Professor Wei’s group has been focusing on decreasing cathode Pt loadings without losses of activity and durability, and their research advances in this area over the past three decades are briefly reviewed herein. Regarding the Pt-based catalysts and the low Pt usage, they have firstly tried to clarify the degradation mechanism of Pt/C catalysts, and then demonstrated that the activity and stability could be improved by three strategies: regulating the nanostructures of the active sites, enhancing the effects of support materials, and …

First Announcement Of 76th Annual Meeting Of The International Society Of Electrochemistry, International Society Of Electrochemistry (Ise)

Journal of Electrochemistry

No abstract provided.

Integrated Multi-Omics Analysis Of Cerebrospinal Fluid In Postoperative Delirium, Bridget A. Tripp, Simon T. Dillon, Min Yuan, John M. Asara, Sarinnapha M. Vasunilashorn, Tamara G. Fong, Sharon K. Inouye, Long H. Ngo, Edward R. Marcantonio, Zhongcong Xie, Towia A. Libermann, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

Preoperative risk biomarkers for delirium may aid in identifying high-risk patients and developing intervention therapies, which would minimize the health and economic burden of postoperative delirium. Previous studies have typically used single omics approaches to identify such biomarkers. Preoperative cerebrospinal fluid (CSF) from the Healthier Postoperative Recovery study of adults ≥ 63 years old undergoing elective major orthopedic surgery was used in a matched pair delirium case–no delirium control design. We performed metabolomics and lipidomics, which were combined with our previously reported proteomics results on the same samples. Differential expression, clustering, classification, and systems biology analyses were applied to individual …

Efficient Deep Neural Network Compression For Environmental Sound Classification On Microcontroller Units, Shan Chen, Na Meng, Haoyuan Li, Weiwei Fang

Turkish Journal of Electrical Engineering and Computer Sciences

Environmental sound classification (ESC) is one of the important research topics within the non-speech audio classification field. While deep neural networks (DNNs) have achieved significant advances in ESC recently, their high computational and memory demands render them highly unsuitable for direct deployment on resource-constrained Internet of Things (IoT) devices based on microcontroller units (MCUs). To address this challenge, we propose a novel DNN compression framework specifically designed for such devices. On the one hand, we leverage pruning techniques to significantly compress the large number of model parameters in DNNs. To reduce the accuracy loss that follows pruning, we propose a …

A New Approach: Ordinal Predictive Maintenance With Ensemble Binary Decomposition (Opmeb), Ozlem Ece Yurek, Derya Birant

Turkish Journal of Electrical Engineering and Computer Sciences

Predictive maintenance (PdM), a fundamental element of modern industrial systems, employs machine learning to monitor equipment conditions, estimate failure probabilities, and optimize maintenance schedules. Its core objective is to enhance equipment reliability, extend lifespan, and minimize costs through data-driven insights by enabling efficient maintenance scheduling, reducing downtime, and optimizing resource allocation. In this paper, we propose a novel ordinal predictive maintenance with ensemble binary decomposition (OPMEB) method for the PdM domain, considering the hierarchical nature of class labels reflecting the machine's health status, including categories like healthy, low risk, moderate risk, and high risk. The proposed OPMEB method was validated …

A Real-Time Embedded System Designed For Nilm Studies With A Novel Competitive Decision Process Algorithm, Sai̇d Mahmut Çinar, Rasi̇m Doğan, Emre Akarslan

Turkish Journal of Electrical Engineering and Computer Sciences

This paper explores the determination of any load or load combination in a power system at any moment. This process requires measurements at the main electric utility service entry of a house, known as nonintrusive measurement. To accurately identify loads, total harmonic distortion, RMS, third harmonic currents, and power consumption are considered their fingerprints. Based on these fingerprints, an algorithm called the competitive decision process is developed and integrated into an embedded system. This algorithm has a two-level decision mechanism. In the first stage, the winner loads with the highest similarity scores from each feature are determined, and the loads …

Ensemble Learning For Accurate Prediction Of Heart Sounds Using Gammatonegram Images, Sinam Ashinikumar Singh, Sinam Ajitkumar Singh, Aheibam Dinamani Singh

Turkish Journal of Electrical Engineering and Computer Sciences

The analysis of heart sound signals constitutes a pivotal domain in healthcare, with the prediction of imbalanced heart sounds offering critical diagnostic insights. However, the inherent diversity in cardiac sound patterns presents a substantial challenge in predicting imbalanced signals. Many scientific disciplines have focused a great deal of emphasis on the problem of class inequality. We introduce an ensemble learning approach employing a convolutional neural network model-based deep learning algorithm to effectively tackle the challenges associated with predicting imbalanced heart sound signals. We use a Gammatone filter bank to extract relevant features from the heard sound signal. Our approach leverages …

Multi-Label Voice Disorder Classification Using Raw Waveforms, Gökay Di̇şken

Turkish Journal of Electrical Engineering and Computer Sciences

Automated voice disorder systems that distinguish pathological voices from healthy ones have been developed with the aid of machine learning methods. Both clinicians and patients can benefit from these systems as they provide many advantages, compared to the invasive techniques. These systems can produce binary (healthy/pathological) or multi-class (healthy/selected pathologies) decisions. However, multiple disorders might exist in an individual’s voice. Multi-label classification should be considered in such cases. By this time, only a single report is available on this topic, where hand-crafted features were used, and a data augmentation technique was utilized to overcome class imbalances. In this study, a …

Detection And Classification Of Unauthorized Use Of Irrigation Motors In Agricultural Irrigation, Önder Ci̇velek, Sedat Görmüş, Hali̇l İbrahi̇m Okumuş, Orhan Gazi̇ Kederoglu

Turkish Journal of Electrical Engineering and Computer Sciences

The decarbonisation of electricity generation requires the real-time monitoring and control of grid components in order to efficiently and timely dispatch demand. This highly automated system, known as the Smart Grid, relies on smart or sensor-equipped distribution network components to optimise energy flow and minimise losses. However, energy theft, a major obstacle to efficient resource utilisation, poses a significant challenge to achieving this goal. This study proposes and evaluates a real-time telemetry and control system designed to mitigate energy theft in agricultural irrigation applications. The system increases energy efficiency by tracking the energy use in agricultural irrigation. The key challenge …

Enrichment Of Turkish Question Answering Systems Using Knowledge Graphs, Okan Çi̇ftçi̇, Fati̇h Soygazi̇, Selma Teki̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Recent capabilities of large language models (LLMs) have transformed many tasks in Natural Language Processing (NLP), including question answering. The state-of-the-art systems do an excellent job of responding in a relevant, persuasive way but cannot guarantee factuality. Knowledge graphs, representing facts as triplets, can be valuable for avoiding errors and inconsistencies with real-world facts. This work introduces a knowledge graph-based approach to Turkish question answering. The proposed approach aims to develop a methodology capable of drawing inferences from a knowledge graph to answer complex multihop questions. We construct the Beyazperde Movie Knowledge Graph (BPMovieKG) and the Turkish Movie Question Answering …

A New Dynamic Classifier Selection Method For Text Classification, İsmai̇l Terzi̇, Alper Kürşat Uysal

Turkish Journal of Electrical Engineering and Computer Sciences

The primary objective of employing multiple classifier systems (MCS) in pattern recognition is to enhance classification accuracy. Dynamic classifier selection (DCS) and dynamic ensemble selection (DES) are two purposeful forms of multiple classifier systems. While DES involves the selection of a classifier set followed by decision combination, DCS opts for the choice of a single competent classifier, eliminating the necessity for classifier combination. As a consequence, DCS methods exhibit superior efficiency in terms of processing time and memory usage compared to DES methods. Moreover, a substantial performance gap exists between the performance of Oracle and both DES and DCS methods. …

Network Intrusion Detection Based On Machine Learning Strategies: Performance Comparisons On Imbalanced Wired, Wireless, And Software-Defined Networking (Sdn) Network Traffics, Hi̇lal Hacilar, Zafer Aydin, Vehbi̇ Çağri Güngör

Turkish Journal of Electrical Engineering and Computer Sciences

The rapid growth of computer networks emphasizes the urgency of addressing security issues. Organizations rely on network intrusion detection systems (NIDSs) to protect sensitive data from unauthorized access and theft. These systems analyze network traffic to detect suspicious activities, such as attempted breaches or cyberattacks. However, existing studies lack a thorough assessment of class imbalances and classification performance for different types of network intrusions: wired, wireless, and software-defined networking (SDN). This research aims to fill this gap by examining these networks’ imbalances, feature selection, and binary classification to enhance intrusion detection system efficiency. Various techniques such as SMOTE, ROS, ADASYN, …

Distributed Energy Trading Models Utilizing Reinforcement Learning And Game-Theoretic Based Approaches In Smart Grids, Nicholas Kemp

Electrical and Computer Engineering ETDs

Community-driven energy initiatives have become crucial for effective energy management, particularly in trading and management. The rise of Distributed Energy Resources in smart grids demands a redesign of traditional Demand Response Management (DRM) models to account for prosumers' dynamic behavior in energy markets. Decentralization, including peer-to-peer (P2P) energy trading, is vital for resilience and sustainability. This thesis introduces two coalitional DRM models: one based on hedonic community formation games, and the other combining matching theory with coalition games. These models empower prosumers to autonomously select energy trading communities using partially available data. To optimize energy consumption, two additional models are …

Data Lakes: A Survey Of Concepts And Architectures, Sarah Azzabi, Zakiya Alfughi, Abdelkader Ouda

Electrical and Computer Engineering Publications

This paper presents a comprehensive literature review on the evolution of data-lake technology, with a particular focus on data-lake architectures. By systematically examining the existing body of research, we identify and classify the major types of data-lake architectures that have been proposed and implemented over time. The review highlights key trends in the development of data-lake architectures, identifies the primary challenges faced in their implementation, and discusses future directions for research and practice in this rapidly evolving field. We have developed diagrammatic representations to highlight the evolution of various architectures. These diagrams use consistent notations across all architectures to further …

Insights On Strategy And Approach For China To Construct A Modern Integrated Circuits Industrial System, Ximing Yin, Beibei Zhang, Tailun Chen, Jiang Yu, Jin Chen

Bulletin of Chinese Academy of Sciences (Chinese Version)

The integrated circuit (IC) industry is highly complex and systematic, and its key core technology breakthroughs are highly dependent on the support of systematic capabilities. The West especially the United States has accelerated the promotion of the “small-yard, high-fence” strategy, the “New Washington Consensus”, the “de-risking”, and other systematic policies to curb China’s rise. China’s IC industry chain is facing extreme risks such as rupture or blockage. Meanwhile, facing the new mission and requirements of Chinese modernization and new-quality productivity, China needs to accelerate the modernization of the IC industry with new development paradigms, new strategies, and new approaches. Based …

Deep Integration Of Technological Innovation And Industrial Innovation In Modern Industrial System: Inspiration From Global New Generation Lithography Systems, Jiang Yu, Feng Chen, Yue Guo

Bulletin of Chinese Academy of Sciences (Chinese Version)

Utilizing technological innovation to lead the construction of a modern industrial system is a strategic choice for seizing the opportunities of the new round of technological revolution and industrial transformation. It is also a necessary step for winning the strategic initiative towards high-level self-reliance and self-improvement. Technological innovation is the intrinsic driving force behind industrial innovation, and industrial innovation is the value embodiment of technological innovation. The deep integration of technological innovation and industrial innovation is the key to constructing and improving a modern industrial system. Taking the global extreme ultra-violet (EUV) lithography system as an example, based on the …

Optoelectronic And Morphological Surface Resistance Evaluation Of Laser-Induced Graphene Counter Electrodes For Potential Applications In Cesium Lead Halide Perovskite Solar Cells, Ziad Khalifa, Sameh Osama Abdellatif, Rami Ghannam

Chemical Engineering

This study investigates the physicochemical, optical, and electrical characterization of laser-induced graphene (LIG) samples for integration as counter electrodes in cesium lead halide perovskite solar cells. The impact of laser processing parameters on electrode performance is explored, including laser power, laser speed, and beam defocus. Density functional theory (DFT) computational modeling is employed for atomistic investigation and work function estimation, demonstrating the density of states (DOS), quantum capacitance of the graphene sheets, and energy work function. NiO is utilized as a hole transport layer, and the energy work function of LIG is tuned accordingly. SEM measurements estimate thin film porosity, …