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Articles 1321 - 1350 of 36680
Full-Text Articles in Electrical and Computer Engineering
Remote Monitoring And Control Of Protection Relays Via Programmable Logic Controller, Rio Mcgown-Kauffman
Remote Monitoring And Control Of Protection Relays Via Programmable Logic Controller, Rio Mcgown-Kauffman
Master's Theses
The purpose of this study is to explore the ability of a programmable logic controller (PLC) to wirelessly monitor and control power protection relays. The technologies surrounding power protection and industrial automation are ever evolving and have developed significantly in recent history. Industrial power applications call for consistent condition monitoring and status updates for various high-importance components. The high-importance components have power protection schemes that are managed by digital relays to trip circuit breakers in fault or unsafe operating conditions. The smart relays have a wide range of capabilities, including communications. Cal Poly assembled a collection of relays from Schweitzer …
Developing Machine Learning Models And Graphene-Based Flexible Humidity And Temperature Sensors For Machine-Learning-Assisted Sensing, Seth Hajian
Dissertations
Flexible sensor technology has recently gained tremendous momentum in both academic research and industrial applications, transitioning from conceptual frameworks to practical implementations across diverse fields. This remarkable advancement can be attributed to several converging factors, including the maturation of nanomaterial science, the advancements of machine learning algorithms, and the critical demand for intelligent sensing solutions in healthcare, environmental monitoring, and industrial automation. The growing emphasis on personalized medicine and real-time health monitoring, accelerated by global health challenges, has further highlighted the necessity for accurate, cost-effective, and adaptable sensing platforms. This dissertation presents the fulfillment of three interconnected research projects focused …
A Parallel Fuzzy Logic Framework For Surgical Skill Evaluation Via Instance Segmentation And Deepsort Tracking, Mohsen M. Mohaidat
A Parallel Fuzzy Logic Framework For Surgical Skill Evaluation Via Instance Segmentation And Deepsort Tracking, Mohsen M. Mohaidat
Dissertations
Manual evaluation of suturing skills during laparoscopic training is often subjective and labor-intensive, resulting in the lack of scalable and consistent feedback for trainees. This study proposes an automated framework that not only significantly reduces the need for in-person assessment by experts but also ensures scalability, thereby addressing the objectivity and cost-effectiveness limitations. While low-cost laparoscopic box trainers have become increasingly popular for residency training, performance assessment still depends on expert supervision. The proposed system aims to alleviate these limitations.
This study introduces a novel automated framework incorporating an optimized DeepSORT algorithm for classifying, localizing, and tracking surgical tools using …
Optical Character Recognition For Early Handwriting Legibility Assessment, Franceli L. Cibrian, Kayla Anderson, Yingying 'Yuki' Chen, Lauren Min, Lizbeth Escobedo
Optical Character Recognition For Early Handwriting Legibility Assessment, Franceli L. Cibrian, Kayla Anderson, Yingying 'Yuki' Chen, Lauren Min, Lizbeth Escobedo
Engineering Faculty Articles and Research
Monitoring children’s handwriting, such as avoiding writing assignments, displaying uneven letter formation, or showing slow writing speed, can help identify developmental and academic issues early. Poor handwriting affects up to 34% of children, leading to academic and self-esteem challenges. Handwriting assessments, typically conducted by teachers, are often delayed due to workload and could be subjective and inconsistent. This paper explores the potential of Optical Character Recognition (OCR) technology to augment and ease handwriting assessments. Based on an evaluation of 10 OCR algorithms using 33 handwriting samples assessed by two experts, the research indicates that Pen to Print and Google are …
Ev Microgrid Inspired Open-Source Power Inverter, Bryan A. Carrillo Martinez
Ev Microgrid Inspired Open-Source Power Inverter, Bryan A. Carrillo Martinez
Master's Theses
The development of open-source power electronics platforms plays an instrumental role in accelerating microgrid deployment, electric vehicle (EV) integration, and educational access to embedded power electronic converters. This thesis presents the design, implementation, and validation of the Atinverter V2, an open-source DC to AC inverter intended for low power EV microgrid applications and educational settings. The Atinverter V2 integrates various hardware and software subsystems centered around the ATMEGA328P microcontroller, enabling PWM-based sinusoidal power inversion, DC/AC voltage and current sensing, and embedded control features. Software development leverages a C++ object-oriented library and multiple Arduino-based modules to facilitate modular and scalable operation. …
Range-Dependent Meso-Scale Geoacoustic Seabed Quantification, Tim Sonnemann, Jan Dettmer, Charles W. Holland, Stan E. Dosso
Range-Dependent Meso-Scale Geoacoustic Seabed Quantification, Tim Sonnemann, Jan Dettmer, Charles W. Holland, Stan E. Dosso
Electrical and Computer Engineering Faculty Publications and Presentations
This study presents a probabilistic one-step two-dimensional (2D) inversion method of spherical-wave reflection coefficient data to estimate the range-dependent structure and geoacoustic parameters along a track. The approach of inverting such datasets independently as one-dimensional (1D) layered models and merging them to a 2D section is feasible but computationally expensive. This study demonstrates a more parsimonious 2D parametrization for active source data recorded on a towed hydrophone array. The comparison of data variance reduction for 1D- and 2D-based results clearly favors the 2D parametrization described here.
Time Synchronization For 5g And Tsn Integrated Networking, Zixiao Wang, Zonghui Li, Cheng Long, Yiming Zheng, Bo Ai, Xiaoyu Song
Time Synchronization For 5g And Tsn Integrated Networking, Zixiao Wang, Zonghui Li, Cheng Long, Yiming Zheng, Bo Ai, Xiaoyu Song
Electrical and Computer Engineering Faculty Publications and Presentations
Emerging industrial applications involving robotic collaborative operations and mobile robots require a more reliable and precise wireless network for deterministic data transmission. To meet this demand, the 3rd Generation Partnership Project (3GPP) is promoting the integration of 5th Generation Mobile Communication Technology (5G) and Time-Sensitive Networking (TSN). Time synchronization is essential for deterministic data transmission. Based on the 3GPP’s vision of the 5G and TSN integrated networking with interoperability, we improve the time synchronization of TSN to conquer the multi-gNB competition, re-transmission, and mobility problems for the integrated 5G time synchronization. We implemented the improvement mechanisms and systematically validated the …
Hybrid Computing For Real-Time Model Predictive Control Of A Buck Converter, Grace Paladichuk
Hybrid Computing For Real-Time Model Predictive Control Of A Buck Converter, Grace Paladichuk
Master's Theses
Advancements in power electronics require high switching frequencies which the digital control routines of the systems cannot keep up with. Analog computing is added to digital control systems to prevent bottlenecks and allow real-time implementation. This paper proposes a hybrid computing model predictive control system for a buck converter. The control system implements the gradient dynamics of the optimization function using digital computing, and the gradient dynamics for the penalty function and integrator using analog computing. For the full simulations of the entire system, the PLECS RT Box is used to simulate the controller in real time with a 1 …
Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover
Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover
Theses and Dissertations
The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …
Hunting, Feiyang Zhuang
Hunting, Feiyang Zhuang
Masters Theses
This writing is about fragility and revelation of technological systems. It considers how brokenness, delay, and opacity are not flaws but openings—opportunities to reimagine our relationship to technology as something grounded, sensory, and continuous with the natural and material world.
Colloidal Quantum Dots: A Path Toward Making Mid-Wave Infrared Sensing A Ubiquitous Technology, Mohammad Mostafa Al Mahfuz
Colloidal Quantum Dots: A Path Toward Making Mid-Wave Infrared Sensing A Ubiquitous Technology, Mohammad Mostafa Al Mahfuz
Dissertations
Reducing the size, weight, power consumption, and cost (SWaP-C) of infrared detectors could make infrared sensing more widely accessible. In the critical mid-wavelength infrared (MWIR) spectral range of 3-5 gm, commercially available detectors are limited by the high costs associated with epitaxial growth and hybridization, as well as the need for cryogenic cooling. These factors restrict their use to defense and space applications.
Colloidal quantum dots present a promising material for overcoming these challenges, with wafer-scale monolithic integration and Auger suppression being the key material capabilities to minimize the sensor's SWaP-C. Infrared sensors based on colloidal quantum dots have been …
Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan
Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan
Dissertations
This dissertation presents a comprehensive automated framework for power converter design, leveraging reinforcement learning (RL) and graph-transformer networks (GTN) to address critical inefficiencies in traditional manual topology optimization. Motivated by the combinatorial increase of circuit design spaces and the computational cost of iterative simulations, this work develops a robust framework for generating energy-efficient topologies requiring rapid and reliable circuit design.
The framework integrates three key components: (1) an upper-confidence-bound-tree-based (UCT-based) RL model for circuit topology space exploration, (2) parallelized UCT algorithms to accelerate exploration processes, (3) a Graph-Transformer-based Network enabling fast circuit performance evaluation. Experimental validation demonstrates the whole framework …
The Interplay Of Accommodation And Oculomotor Vergence Within Young Adults With Binocularly Normal Vision And Typically-Occurring Convergence Insufficiency, Sebastian Fine
Dissertations
Concerted binocular coordination evoking oculomotor and refractive responses to visual stimuli are essential to daily function. Oculomotor dysfunctions can inhibit binocular responses to visually-near stimuli and have high comorbidities to accommodative dysfunctions. Three visual cues for inward (convergent) and outward (divergent) oculomotor movements, when presented concertedly create natural-viewing conditions: disparity- the binocular difference in light cast onto the fovea due to differing ocular perspectives, blur- the acuity of a visual target which stimulates accommodation, and proximal- the perceived distance of a visual stimuli based on size.
This study aims to quantitatively investigate oculomotor vergence and accommodation performances between individuals with …
Next-Generation Extended Reality Systems With Real-Time Edge Artificial Intelligence And Mobile Computing, Pedro H. Regalado
Next-Generation Extended Reality Systems With Real-Time Edge Artificial Intelligence And Mobile Computing, Pedro H. Regalado
Dissertations
Mixed reality (MR) and augmented reality (AR) systems are reshaping digital experiences by seamlessly integrating physical and virtual environments. This dissertation presents a comprehensive framework for next-generation immersive systems, combining advances in real-time data processing, multi-user synchronization, and secure communication. The core contributions are structured around three interconnected systems: MediVerse, TeleAvatar, and MultiAvatarLink, each addressing critical challenges in mobile MR.
MediVerse is a secure and scalable framework for real-time health and performance monitoring, integrating intelligent IoT sensors, wearable technologies, and MR interfaces. It supports multi-camera fusion, adaptive compression, and real-time three-dimensional (3D) point cloud generation, enhancing data accuracy and responsiveness …
A System Of Systems (Sos) Meta-Architecture Approach To Design Digital Platform-Based Domestic Worker Distribution System, Prithbey Raj Dey, Cihan H. Dagli, David Lee Enke
A System Of Systems (Sos) Meta-Architecture Approach To Design Digital Platform-Based Domestic Worker Distribution System, Prithbey Raj Dey, Cihan H. Dagli, David Lee Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
In this research, a System of Systems (SoS) meta-architecture is conceptualized to design a digital platform-based system framework for the distribution of domestic workers to boost the crowd-sourced economy. While an Object Process Methodology (OPM) is used to articulate the relationships between the objects and functions, a Design Structure Matrix (DSM) has been applied to address the interactions between individual components to categorize them into subsystems to create the SoS architecture. This SoS architecture incorporates several Key Performance Attributes (KPAs) and Key Performance Parameters (KPPs) to systematically evaluate the meta-architectures. The Analytical Hierarchical Process (AHP), Pugh’s Evaluation Matrix, and Technique …
Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh
Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh
Theses
Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …
Price-Signal-Based Control Strategy For Heat Pump Water Heaters In Demand Response Applications, Othman A. Murad
Price-Signal-Based Control Strategy For Heat Pump Water Heaters In Demand Response Applications, Othman A. Murad
Dissertations and Theses
This work presents a price-signal-based control strategy for residential Heat Pump Water Heaters (HPWHs) aimed at reducing electricity costs and shifting load away from high-price periods. By integrating the California Load Flexibility Research and Development Hub (CalFlexHub) prototype price signals, the Consumer Technology Association (CTA-2045-B) communication protocol, and the Object-oriented, Controllable, High-resolution Residential Energy (OCHRE) simulation framework, a rule-based controller was developed to align HPWH operation with dynamic electricity pricing while maintaining hot water availability.
The control strategy was evaluated through two case studies: one using a fixed water draw profile under varying levels of price signal foresight, and another …
Influencing Factors Of Angle-Of-Arrival Estimator Based On Deep Learning, Guohao Pang
Influencing Factors Of Angle-Of-Arrival Estimator Based On Deep Learning, Guohao Pang
Dissertations and Theses
Deep learning (DL)-based angle-of-arrival (AoA) estimation offers significant advantages over traditional signal processing methods, especially in complex and high-noise environments. However, situational complexity and differences in hardware can significantly impact the estimator's performance. It is therefore of interest to investigate the relationship between the performance of deep learning models and the variation of physical parameters such as the number of signal sources, the number of receiving antennas, and the signal-to-noise ratio (SNR). In this study, we investigate the impact of these variations on deep learning-based AoA estimation by systematically analyzing how the variations in the characteristics of the received signal …
Understanding The Morphology And Mass Transport Resistance Of Mesoporous Carbon-Supported Pemfc Based On Modeling Analysis, Hao Deng, Jia Liu, Zhong-Jun Hou
Understanding The Morphology And Mass Transport Resistance Of Mesoporous Carbon-Supported Pemfc Based On Modeling Analysis, Hao Deng, Jia Liu, Zhong-Jun Hou
Journal of Electrochemistry
Mesoporous carbon supports mitigate Pt sulfonic poisoning through nanopore-confined Pt deposition, yet their morphological impacts on oxygen transport remain unclear. This study integrates carbon support morphology simulation with an enhanced agglomerate model to establish a mathematical framework elucidating pore evolution, Pt utilization, and oxygen transport in catalyst layers. Results demonstrate dominant local mass transport resistance governed by three factors: (1) active site density dictating oxygen flux; (2) ionomer film thickness defining shortest transport path; (3) ionomer-to-Pt surface area ratio modulating practical pathway length. At low ionomer-to-carbon (I/C) ratios, limited active sites elevate resistance (Factor 1 dominant). Higher I/C ratios improve …
Comprehensive Risk Assessment Of Power Grids Using Fuzzy Bayesian Networks Through Expert Elicitation: A Technical Analysis, Yasir Mahmood, Nof Yasir, Nita Yodo, Ying Huang, Di Wu, Roy A. Mccann
Comprehensive Risk Assessment Of Power Grids Using Fuzzy Bayesian Networks Through Expert Elicitation: A Technical Analysis, Yasir Mahmood, Nof Yasir, Nita Yodo, Ying Huang, Di Wu, Roy A. Mccann
Electrical Engineering and Computer Science Faculty Publications and Presentations
Power grid infrastructures, essential to modern societies for electricity distribution, are prone to vulnerabilities due to their numerous sensitive components, necessitating a comprehensive risk assessment. Uncertainty in historical failure data often compromises accurate risk quantification, leading to the integration of expert elicitation as a solution. This study develops a Bayesian network (BN) risk assessment model integrated with fuzzy set theory (FST), referred to as the fuzzy Bayesian network (FBN). By incorporating expert insights, this model quantifies internal and external risk variables more comprehensively. Crisp probabilities (CPr), derived from regional transmission operator (RTO) failure incident data, are complemented by fuzzy probabilities …
Preparation And Modification Of Mxene Composites For Application In Electrochemical Energy Storage, Zhang-Hai You, Ding-Ze Lu, Kiran Kumar Kondamareddy, Wen-Ju Gu, Peng-Fei Cheng, Jing-Xuan Yang, Rui Zheng, Hong-Mei Wang
Preparation And Modification Of Mxene Composites For Application In Electrochemical Energy Storage, Zhang-Hai You, Ding-Ze Lu, Kiran Kumar Kondamareddy, Wen-Ju Gu, Peng-Fei Cheng, Jing-Xuan Yang, Rui Zheng, Hong-Mei Wang
Journal of Electrochemistry
With the acceleration of advanced industrialization and urbanization, the environment is deteriorating rapidly, and non-renewable energy resources are depleted. The gradual advent of potential clean energy storage technologies is particularly urgent. Electrochemical energy storage technologies have been widely used in multiple fields, especially supercapacitors and rechargeable batteries, as vital elements of storing renewable energy. In recent years, two-dimensional material MXene has shown great potential in energy and multiple application fields thanks to its excellent electrical properties, large specific surface area, and tunability. Based on the layered materials of MXene, researchers have successfully achieved the dual functions of energy storage and …
Theoretical Insights Into The Atomic And Electronic Structures Of Polyperyleneimide: On The Origin Of Photocatalytic Oxygen Evolution Activity, Yi-Qing Wang, Zhi Lin, Ming-Tao Li, Shao-Hua Shen
Theoretical Insights Into The Atomic And Electronic Structures Of Polyperyleneimide: On The Origin Of Photocatalytic Oxygen Evolution Activity, Yi-Qing Wang, Zhi Lin, Ming-Tao Li, Shao-Hua Shen
Journal of Electrochemistry
Polymeric perylene diimide (PDI) has been evidenced as a good candidate for photocatalytic water oxidation, yet the origin of the photocatalytic oxygen evolution activity remains unclear and needs further exploration. Herein, with crystal and atomic structures of the self-assembled PDI revealed from the X-ray diffraction pattern, the electronic structure is theoretically illustrated by the first-principles density functional theory calculations, suggesting the suitable band structure and the direct electronic transition for efficient photocatalytic oxygen evolution over PDI. It is confirmed that the carbonyl O atoms on the conjugation structure serve as the active sites for oxygen evolution reaction by the crystal …
Three-Dimensional Melamine Carbon Sponge/Nai As Cathode Materials For Sodium-Ion Batteries, Qian-Ying Huang, Yue Liu, Zi-Xin Lin, Shu-Yi Zheng, Ting-Ting Mei, Yu-Ting Tang, Ying-He Zhang, Jun Liu
Three-Dimensional Melamine Carbon Sponge/Nai As Cathode Materials For Sodium-Ion Batteries, Qian-Ying Huang, Yue Liu, Zi-Xin Lin, Shu-Yi Zheng, Ting-Ting Mei, Yu-Ting Tang, Ying-He Zhang, Jun Liu
Journal of Electrochemistry
The sodium-iodine (Na-I) battery exhibits significant potential as an alternative energy storage device to the lithium-ion battery. However, its development is hindered by inadequate electrical and thermal stability, as well as the dissolution and shuttling of polyiodide. In this study, we report a preparation method for melamine carbon sponge (MC) via carbonizing a commercially available kitchen sponge. It was revealed that the as-prepared MC, composed of unique self-growing carbon nanotubes, could provide both physical and chemical adsorption capabilities for intermediate polyiodides to improve the electrochemical performance of NaI. Consequently, the NaI/MC electrode effectively minimized polyiodide dissolution and reduced the electrochemical …
Optimization Of Renewable Energy Systems: Comparative Analysis Of Advanced Algorithms And Photovoltaic-Electrolyzer Performance For Cost Reduction And Efficiency Enhancement, Mohamed-Amine Babay, Mustapha Adar, Ahmed Chebak, Mustapha Mabroukia
Optimization Of Renewable Energy Systems: Comparative Analysis Of Advanced Algorithms And Photovoltaic-Electrolyzer Performance For Cost Reduction And Efficiency Enhancement, Mohamed-Amine Babay, Mustapha Adar, Ahmed Chebak, Mustapha Mabroukia
Journal of Electrochemistry
The increasing demand for cost-effective and efficient renewable energy solutions presents significant optimization challenges in hybrid energy systems. This paper addresses these challenges by conducting a comparative analysis of three advanced optimization algorithms—Lévy Flight Optimization (LFO), Archimedean Optimization (AO), and Quantum Gorilla Optimization (QGO)—to minimize the Total Net Present Cost (TNPC) and Levelized Cost of Energy (LCOE) in hybrid renewable energy systems. The study integrates critical cost parameters such as Capital Expenditure (CAPEX), Operational Expenditure (OPEX), replacement costs, and salvage values into an advanced optimization framework. Three system configurations are evaluated: Wind Turbines and Fuel Cells (WT/FC), Photovoltaic Systems and …
Encryption With Synchronized Chaos Using Fabricated Cobalt Ferrite Memristors, Kiran Sai Seetala
Encryption With Synchronized Chaos Using Fabricated Cobalt Ferrite Memristors, Kiran Sai Seetala
Doctoral Dissertations
No abstract provided.
The Electrostatic Charge On Exuded Liquid Drops, Schuyler Arn, Pablo Illing, Joshua Mendéz Harper, Justin C. Burton
The Electrostatic Charge On Exuded Liquid Drops, Schuyler Arn, Pablo Illing, Joshua Mendéz Harper, Justin C. Burton
Electrical and Computer Engineering Faculty Publications and Presentations
Fluid triboelectrification, also known as flow electrification, remains an under-explored yet ubiquitous phenomenon with potential applications from material science to planetary evolution. Building upon previous efforts to position water within the triboelectric series, we investigate the charge on individual, millimetric water drops falling through air. Our experiments measured the charge and mass of each drop using a Faraday cup mounted on a mass balance, and connected to an electrometer. For pure water in a glass syringe with a grounded metal tip, we find the charge per drop (Δ/Δ) was approximately -5 pC g to -1 pC g. This was independent …
Design And Optimization Of Low-Loss, High-Gain Metamaterial-Based Log-Periodic Dipole Array Antenna For Full Ka-Band Coverage, Mohamed El Moniar, Ahmed Abd El Hady, Yasser Ismail, Nihal Areed
Design And Optimization Of Low-Loss, High-Gain Metamaterial-Based Log-Periodic Dipole Array Antenna For Full Ka-Band Coverage, Mohamed El Moniar, Ahmed Abd El Hady, Yasser Ismail, Nihal Areed
Turkish Journal of Electrical Engineering and Computer Sciences
This work describes a microstrip log-periodic dipole array (MLPDA) antenna that uses metamaterials and operates across the whole Ka-band. The suggested MLPDA antenna layout provides a wide bandwidth with fewer dipole elements than traditional MLPDA antennas while maintaining the same resonance frequencies. To reduce size while covering a wide operational spectrum, the antenna design includes bending dipoles as radiating elements, as well as an incomplete ground plane. Furthermore, the proposed MLPDA antenna’s energy loss has been reduced while boosting its signal strength (gain) by inserting a metamaterial-based structure in front of it at a certain distance and on the same …
Design And Performance Evaluation Of Pv-Powered Ev Charging Stations With Grid Integration And Comparative Analysis Of Dc-Dc Converters For Offboard Chargers, Mohammad Abidur Rahman
Design And Performance Evaluation Of Pv-Powered Ev Charging Stations With Grid Integration And Comparative Analysis Of Dc-Dc Converters For Offboard Chargers, Mohammad Abidur Rahman
Theses and Dissertations
Grid-integrated photovoltaic (PV)-powered electric vehicle (EV) charging stations offer a sustainable solution for reducing grid dependency and fossil fuel consumption in workplace environments. This study proposes a PV-powered EV charging system with an AC bus configuration and grid support to ensure stable and efficient operation. A comparative analysis of four DC-DC converter topologies—Dual Active Bridge (DAB), LLC Resonant, Interleaved Buck-Boost, and Interleaved Buck—is conducted for offboard charging applications. Performance evaluation is carried out using MATLAB/Simulink, considering voltage and current ripple, power density, stress levels, bidirectional capability, and control complexity. Component-level reliability is assessed using MIL-HDBK-217 standards to estimate failure rates …
Thermaltrack Dataset - Training Labels - Sequence 1-11, Yiming Yang, Jeremy P. Bos
Thermaltrack Dataset - Training Labels - Sequence 1-11, Yiming Yang, Jeremy P. Bos
ThermalTrack
We present a wheel track detection system that leverages RGB-Thermal (RGB-T) imaging, where thermal channels reveal critical temperature differentials between compacted tracks and loose snow - tracks exhibit higher thermal inertia and lower reflectivity, emitting stronger radiation signatures even in visually homogeneous conditions. By fusing these distinctive thermal patterns with RGB spatial information, our method reliably identifies navigable tracks, enabling robust path-following in complete white-out conditions where snow textures and terrain features become indistinguishable.
Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Kyrillos Selim, Ziad Khalifa, Amira Ali, Sameh O. Abdellatif
Experimentally Driven Numerical Model Of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using A New Figure Of Merit, Kyrillos Selim, Ziad Khalifa, Amira Ali, Sameh O. Abdellatif
Electrical Engineering
This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)-based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a figure …