Investigation Of Insertion Loss In Inkjet-Printed Coplanar Waveguide Based On Drying Temperature,
2025
Korea Institute of Industrial Technology
Investigation Of Insertion Loss In Inkjet-Printed Coplanar Waveguide Based On Drying Temperature, Jun Ho Yu, Sung Min Sim, Jin Woo Choi, Sang Ho Lee, Jung Mu Kim
Michigan Tech Publications
In this study, we propose an optimized inkjet printing process to improve the insertion loss of inkjet-printed coplanar waveguide (CPW) transmission lines. The process involves varying the drying temperature and adjusting the number of printing steps to investigate their effects on the electrical characteristics of the printed CPW. The relationships between surface roughness, surface cavities, morphological changes, and insertion loss are studied by conducting atomic force microscopy analysis and by examining the insertion loss up to 3 GHz. The printed CPW that underwent low-temperature drying after the first printing and high-temperature drying after the second printing before sintering showed improved …
Regulating Lithium Metal Nucleation And Growth For Dendrite Suppression: From Liquid-Electrolyte To Solid-State Batteries,
2025
Tianjin Key Laboratory of Advanced Carbon and Electrochemical Energy Storage, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300350, P. R. China
Regulating Lithium Metal Nucleation And Growth For Dendrite Suppression: From Liquid-Electrolyte To Solid-State Batteries, Ao Du, Juan Zhang, Pan Xu, Ya-Jie Li, Kang-Yu Yi, Zhen-Zhen Shen, Hui-Lin Ge, Guang-Wen Zhang, Chao-Hui Zhang, Yu-Hao Wang, Chen-Zi Zhao, Meng-Yang Xu, Yu-Lin Jie, Rui Wen, Shu-Hong Jiao, Si-Qi Shi, Qiang Zhang, Chun-Peng Yang, Yu-Guo Guo
Journal of Electrochemistry
Lithium metal anodes, with a theoretical capacity of up to 3860 mAh·g−1, are regarded as the cornerstone for developing next-generation high-energy-density batteries. However, several key challenges hinder their practical applications, including dendrite formation, unstable solid electrolyte interphase (SEI), side reactions with electrolytes, and associated safety risks. This review systematically explores the mechanisms of lithium nucleation, growth, and stripping in both liquid and solid-state battery systems, analyzing critical theoretical concepts like heterogeneous nucleation thermodynamics, surface diffusion kinetics, space charge effects, and SEI-induced nucleation, which are crucial for understanding the genesis of dendrite growth. Additionally, the review discusses the electrochemical-mechanical …
Evolving Towards Efficient Technologies In Power Systems: The Paradigm Of Energy Internet Survey,
2025
Electrical Power Engineering Department, Faculty of Engineering, Zagazig University, 44519 Zagazig, Egypt
Evolving Towards Efficient Technologies In Power Systems: The Paradigm Of Energy Internet Survey, Dina Emad, Omar Abdel-Rahim, Tanemasa Asano, Sobhy M. Abdelkader
Mansoura Engineering Journal
The Energy Internet represents a significant advancement in the modernization and automation of electricity systems, offering a framework for future smart grids where all electrical devices are interconnected through energy routers. This system integrates advanced power electronics, information technology, and smart control technologies, enabling the accommodation of diverse energy sources and storage devices. With its bidirectional energy flow and sharing capabilities, the Energy Internet holds great promise for the future. However, several challenges must be addressed to fully realize this potential. This review provides an overview of the Energy Internet framework and explores key challenges, particularly those related to energy …
Blockchain In Smart Cities,
2025
United Arab Emirates University
Blockchain In Smart Cities, Shamma Alnuaimi
Thesis/ Dissertation Defenses
This thesis explores the integration of blockchain technology with smart cities to enhance efficiency, transparency, and reliability. The basic principles of blockchain, its layered architecture, consensus protocols, and decentralized security are first reviewed. The thesis then highlights how blockchain features can be integrated with urban and energy systems. The research focuses on how token economy can be used with smart cities to promote individuals to engage in desired behaviors by employing blockchain-based incentive mechanisms that can encourage responsible energy consumption.
The FairChain test system was developed and tested using blockchain technology and the Internet of Things (IoT) to demonstrate the …
A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data,
2025
SK Unviersity of Agricultural Sciences and Technology of Kashmir
A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data, Yasir Altaf, Abdul Wahid, Mudasir Manzoor Kirmani
Turkish Journal of Electrical Engineering and Computer Sciences
Midair hand gesture recognition plays a crucial role in applications such as sign language recognition and human-computer interaction, particularly for supporting individuals with partial or complete hearing loss. However, recognizing gestures in midair remains challenging due to the rapid and complex nature of hand movements. To address this, noninvasive techniques like surface electromyography (sEMG)—which captures muscle activity through sensors placed on the skin—have gained attention. sEMG provides rich time-series data that reflect both spatial and temporal muscle dynamics. In this study, we propose a deep learning architecture that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to classify …
Integrated Log Spectrogram Convolutional Neural Network (Ils-Cnn) For Robust Spoken Digit Recognition,
2025
TÜBİTAK
Integrated Log Spectrogram Convolutional Neural Network (Ils-Cnn) For Robust Spoken Digit Recognition, Awais Ahmed
Turkish Journal of Electrical Engineering and Computer Sciences
Spoken digit recognition (SDR), a type of supervised automatic speech recognition, is essential for various human-machine interaction applications, including banking operations, dialing systems, price extraction, and airline reservation systems. However, designing an effective SDR system presents several challenges, such as developing labeled audio data, selecting appropriate feature extraction methods, and creating high-performance models. To overcome these challenges, a novel approach for robust spoken digit recognition using an integrated log spectrogram convolutional neural network (ILS-CNN) has been proposed. The proposed work presents an efficient SDR method by taking advantage of a log spectrogram layer directly within the neural network to enhance …
Railway Track Condition Monitoring Based On Sensor Data And Artificial Neural Networks,
2025
TÜBİTAK
Railway Track Condition Monitoring Based On Sensor Data And Artificial Neural Networks, Ivan Kots, Alina Isaeva, Mark Denisenko, Alexander Sinyukin, Andrey Kovalev
Turkish Journal of Electrical Engineering and Computer Sciences
Monitoring the condition of engineering objects is one of the urgent tasks of industry, construction, and transport infrastructure. This article describes a system for condition monitoring and diagnostics of rail tracks in real time. Compared with other similar studies, the proposed system has the advantages of compactness, usability, scalability and versatility of application. The proposed monitoring system is based on an Nvidia Jetson Nano embedded computing board and also includes inertial sensor modules, a microphone, a geolocation module, communication modules, an SSD storage device, and a battery. The prototype of the diagnostic module is a portable device that can be …
Modeling And Simulation Of Dynamic Energy Management Systems For Smart Buildings,
2025
TÜBİTAK
Modeling And Simulation Of Dynamic Energy Management Systems For Smart Buildings, Onur Özel, Ali̇ Rifat Boynueğri̇, Hayri̇ Yi̇ği̇t, Burak Tekgün
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents a dynamic energy management system tailored for smart residential buildings, integrating thermal and electrical models to achieve both natural gas and electricity bill cost reduction. By harnessing wind and solar energy sources, the system aims to meet the diverse energy needs of modern homes. Through load shifting and thermal storage strategies, known as power-to-heat (P2H) approaches, the system ensures efficient renewable energy utilization while maintaining resident comfort. Validation of the proposed system was conducted using real-world data from the Yıldız Technical University Smart Home Laboratory, demonstrating its practical applicability and effectiveness. Results indicate significant reductions in both …
Grey Wolf Optimization Of Pi Controller For Power Management In Wind Farms: A Novel Approach,
2025
TÜBİTAK
Grey Wolf Optimization Of Pi Controller For Power Management In Wind Farms: A Novel Approach, Anis Feddaoui, Lotfi Farah, Abdelouahab Benretem, Mohammed Abdeldjalil Djehaf
Turkish Journal of Electrical Engineering and Computer Sciences
This study proposes a novel power management strategy for wind farms using a grey wolf optimization (GWO)-based PI controller. The method aims to enhance active and reactive power control in systems employing dou bly fed induction generators. Three control strategies are evaluated—namely, a classical frequency-domain PI controller, an Artificial Neural Network (ANN)-based controller, and the proposed GWO-based PI controller—the last of which represents the main contribution. The classical PI and ANN controllers are included strictly for comparative bench marking. MATLAB simulations demonstrate that the GWO-beased PI controller offers superior dynamic performance, particularly in settling time and overshoot reduction. A power …
Performance Analysis Of Ris-Empowered Ofdm-Im Communications Under Weibull Fading And Joint Tx/Rx I/Q Imbalance,
2025
TÜBİTAK
Performance Analysis Of Ris-Empowered Ofdm-Im Communications Under Weibull Fading And Joint Tx/Rx I/Q Imbalance, Büşra Ceni̇kli̇oğlu, İbrahi̇m Develi̇, Ayşe Eli̇f Canbi̇len
Turkish Journal of Electrical Engineering and Computer Sciences
A modernist technique, reconfigurable intelligent surface (RIS) provides outstanding signal reflection and amplification, making it highly valuable for upcoming communication systems. Besides, a major contributor is index modulation (IM), attaining superior spectral and energy efficiency, and achieving hardware sufficiency. The primary and novel contribution of this work is the derivation of a highly accurate, closed-form approximate expression for the average bit error rate (ABER) of an orthogonal frequency division multiplexing (OFDM)-IM system operating in the complex and challenging environment characterized by joint transmitter/receiver (Tx/Rx) in-phase and quadrature phase imbalance (IQI) and Weibull fading. This essential analytical achievement is facilitated by …
Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking,
2025
University of mouloud Mammeri of Tizi-Ouzou
Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah
Turkish Journal of Electrical Engineering and Computer Sciences
This study presents the implementation of a fuzzy logic–based control system on a field-programmable gate array (FPGA) for a quadrotor autonomous aerial vehicle (UAV). The objective is to design and integrate six Takagi–Sugeno fuzzy controllers to regulate roll, pitch, and yaw angles, along with longitudinal, latitudinal, and altitude movements, thereby stabilizing the UAV and enabling it to follow a desired trajectory. Due to the computational complexity of the six controllers, achieving the desired performance requires considerable processing time, which can adversely affect the quadrotor’s mission. Owing to their high processing power and operating frequency, FPGAs enable the control algorithm to …
Ai-Driven Optimization Of Wind Energy Distribution In Texas Using Multi-Agent Reinforcement Learning,
2025
Southern Methodist University
Ai-Driven Optimization Of Wind Energy Distribution In Texas Using Multi-Agent Reinforcement Learning, Waleed Amer, Owolabi Oluwadamilola, Bassey Ogbonnaya
SMU Data Science Review
Abstract. The integration of large-scale wind power into modern electrical grids presents persistent challenges due to variability, curtailment, and compliance with operational constraints. This study proposes a multi-agent reinforcement learning (MARL) framework for optimizing wind energy distribution within the Texas power grid. The system employs three specialized agents—managing wind curtailment, storage utilization, and load adjustments—to collaboratively balance supply and demand under dynamic grid conditions. Using historical operational data from the Electric Reliability Council of Texas (ERCOT), the framework was trained and evaluated on a range of scenarios encompassing both typical and extreme operating conditions. Results demonstrate substantial performance improvements compared …
Energy Management Of Battery Supercapacitor Hybrid Storage In Electric Vehicles With Solar Integration: Review,
2025
Kennesaw State University
Energy Management Of Battery Supercapacitor Hybrid Storage In Electric Vehicles With Solar Integration: Review, Islam Sayed, Yousef Mahmoud
Faculty Articles
Hybrid energy storage systems (HESS) integrating batteries and supercapacitors offer a promising solution to overcome the limitations of battery-only architectures in electric vehicles (EVs). By leveraging the high energy density of batteries and the high power density of supercapacitors, HESS can enhance power delivery, improve energy efficiency, and extend battery lifespan. The effectiveness of HESS, however, is largely determined by the energy management system (EMS) that coordinates power flow under dynamic driving conditions. Unlike existing reviews, this work addresses common gaps in the literature, including the lack of industrial energy storage component examples, limited coverage of recently developed EMS strategies, …
Field Canals Improvement Projects Duration Prediction: A Comparative Analysis Of Machine Learning Models,
2025
Muffakham Jah College of Engineering and Technology
Field Canals Improvement Projects Duration Prediction: A Comparative Analysis Of Machine Learning Models, Hania Ghouse, Ukaegbu Chinonso Ishmael, Edgar Dario Obando-Paredes, Hashem Shafik Shakir, Ali Al-Bayaty
Electrical and Computer Engineering Faculty Publications and Presentations
There are several essential elements in project construction management to be studied appropriately, and priority to these elements, such as cost and duration, is predominantly interesting to be investigated. In this research, the duration of field canal improvement projects (DFCIP) was predicted using two relatively new machine learning (ML) models - the Multivariate Adaptive Regression Spline (MARS) and Extreme Learning Machine (ELM). The targeted DFCIP was calculated using other dependent parameters, such as the length of the pipe, years of construction, the geographical zone of the network, the supplied area with water, and finally the actual cost of the field …
Yolo-Based Marine Search And Rescue Using Uav Multi-Dataset In Challenging Weather Conditions,
2025
United Arab Emirates University
Yolo-Based Marine Search And Rescue Using Uav Multi-Dataset In Challenging Weather Conditions, Aysha Alshebli
Thesis/ Dissertation Defenses
Object detection models, powered by deep learning and computer vision, are revolutionizing marine search and rescue (SAR). By analyzing aerial imagery and live drone footage, these systems automatically identify critical targets like survivors, life rafts, and debris across vast and treacherous ocean areas. This capability enhances operational efficiency by reducing human workload and accelerating response times, even in challenging conditions such as poor light, high seas, or cluttered backgrounds. The result is continuous monitoring, faster decision-making, and a significantly improved probability of successful rescue.
Departing from prior methodologies, YOLO introduced a paradigm shift through its single-shot architecture, which concurrently predicts …
High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology.,
2025
University of Denver
High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief
Electronic Theses and Dissertations
The performance of DC-DC power converters is a cornerstone of modern electric vehicle (EV) powertrains, directly governing overall system efficiency, size, cost, and reliability. This dissertation presents a comprehensive performance analysis and optimization of DC-DC converter topologies to determine the most suitable design for high voltage EV applications. The evaluation rigorously compares efficiency, power losses, and physical size under a range of harsh operating conditions. A primary objective is to leverage Wide Bandgap (WBG) semiconductors, specifically Silicon Carbide (SiC), to push the performance boundaries of power conversion. While SiC devices are known for their superior material properties, a clear understanding …
Rail Anomalies Dataset For Semantic Segmentation Analysis,
2025
University of Nevada, Las Vegas
Rail Anomalies Dataset For Semantic Segmentation Analysis, Saarah Majid, Arian Izadi, Paul Stanik
Undergraduate Research Symposium Posters
Rail maintenance is a core necessity of upkeep, maintenance, deterioration, and safety implications of large rail systems. Doing so in an orderly and uniform way, however, has proven difficult with the thousands of miles that railways span. Use of computer vision on locomotives during normal operation can allow for a more streamlined process that would eliminate the need for costly specialized equipment and disruptions of normal operations. This project aims to efficiently detect vegetation overgrowth, mud-pumping, and standing water on railways. With the use of machine learning algorithms and dataset curation, models can be trained, allowing them to gain a …
Spatiotemporal Feature Extraction From Vertical Grf Signals For Parkinson’S Disease Severity Assessment Using Physionet And Gaitpd,
2025
University of Nevada, Las Vegas
Spatiotemporal Feature Extraction From Vertical Grf Signals For Parkinson’S Disease Severity Assessment Using Physionet And Gaitpd, Nitya Jadeja
Undergraduate Research Symposium Posters
Parkinson’s Disease (PD) is a progressive neurodegenerative disorder that impairs motor coordination, often resulting in measurable gait disturbances. Vertical ground reaction force (VGRF) signals provide a quantitative means of capturing these abnormalities and monitoring disease progression. This study focuses on the extraction and analysis of spatiotemporal gait features such as stride variability, stance duration, and force imbalance, from the PhysioNet Gait dataset to better understand their correlation with PD severity. Using gait analysis and machine learning techniques, recent computational models are reviewed and evaluated for their ability to assess PD progression through VGRF data. The analysis compares data-driven approaches with …
Real-Time Ai-Enabled Therapeutic Device For Improving Peripheral Perfusion And Glucose Regulation In Type 2 Diabetes,
2025
University of Nevada, Las Vegas
Real-Time Ai-Enabled Therapeutic Device For Improving Peripheral Perfusion And Glucose Regulation In Type 2 Diabetes, Torryana Tanis
Undergraduate Research Symposium Posters
Type 2 Diabetes Mellitus is frequently accompanied by peripheral microvascular disease, leading to impaired lower limb perfusion, impaired healing, and vulnerability to ulcers and amputation. The existing medical devices are predominantly aimed at systemic glucose control and do not have local therapeutic intervention to improve circulation or allow muscular glucose delivery. To meet this crucial demand, we have developed a portable, two-in-one biofeedback device that combines non-invasive blood glucose monitoring and Electronic Muscle Stimulation (EMS) therapy for the calf muscle. The glucose monitoring subsystem implements near-infrared (NIR) spectroscopy to measure skin light absorptance on the index finger. Real-time blood glucose …
Digital Twin Of The Unlv Campus For Safe Autonomous Vehicle Simulation,
2025
University of Nevada, Las Vegas
Digital Twin Of The Unlv Campus For Safe Autonomous Vehicle Simulation, Carlos Funes
Undergraduate Research Symposium Posters
With the rise of artificial intelligence and machine learning algorithms, self-driving cars are becoming increasingly prevalent on our roads. By utilizing these technologies, we can reduce the number of accidents caused by distracted driving. Before implementing these systems in vehicles, however, it is essential to conduct numerous tests. Traditional evaluation of driverless cars on real-world roads can be both expensive and hazardous. To address this, creating a digital twin of an actual road minimizes unexpected hazards, allowing researchers to safely and efficiently test self-driving car programs in high-risk scenarios using computer simulations. This research outlines the process of generating a …
