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Articles 2011 - 2040 of 37177

Full-Text Articles in Electrical and Computer Engineering

Hardware Trojan Detection In A Segmented Mixed-Signal Circuit Via Leakage Current, Christopher James Otey Jan 2025

Hardware Trojan Detection In A Segmented Mixed-Signal Circuit Via Leakage Current, Christopher James Otey

Browse all Theses and Dissertations

As computers and integrated circuits become more commonplace, the risk of a Hardware Trojan attack becomes more worrisome. Trojans can exploit design flaws or be inserted between essential components to leak information, change the circuit function, or destroy the circuit altogether. Several methods of trojan detection and prevention have been introduced, however few can handle combined analog and digital circuits, known as mixed-signal circuits. This thesis demonstrates a Hardware Trojan detection method implemented in an Analog-to-Digital Converter (ADC), which is a mixed-signal circuit. The detection method involves splitting the circuit into segments with approximately equal leakage currents (a large part …


Reinforcement Learning For Adversarial Systems Using Relational Observations, Sophia Christine Gilson Jan 2025

Reinforcement Learning For Adversarial Systems Using Relational Observations, Sophia Christine Gilson

Browse all Theses and Dissertations

This thesis investigates the integration of relational observations with the reinforcement learning (RL) framework for improved generalization capability. A hide-and-seek simulation environment is designed in Unity for proof-of-concept demonstration. Two observation representations—relational (analogical) and standard positional—are designed to evaluate agent learning and generalization capabilities. Agents are trained using the Proximal Policy Optimization (PPO) and Soft Actor Critic (SAC) algorithms in a random-room environment and tested in both the random-room environment and a novel environment with greater spatial complexity and path obstructions. Comparative studies indicate that relational representation of objects in the adversarial environment could potentially improve the generalization capability of …


Quantized Average Agreement Algorithms With Error Correction For Digraphs, Shuaib A. Mughal Jan 2025

Quantized Average Agreement Algorithms With Error Correction For Digraphs, Shuaib A. Mughal

Honors Undergraduate Theses

Multi-agent systems have become more and more prevalent as technology increasingly gets integrated into our daily lives. Some of these technological systems are large in size; for example, the smart grid where multiple devices are used to monitor and control different aspects of the energy grid. Another example is a team of autonomous systems deployed for a specific task. When these systems are spatially distributed, an important component of distributed algorithms is the ability for the agents to reach consensus on the global state of the system. Reaching agreement enables the spatially distributed agent make decisions or determine the next …


Behavior Analysis Of Simple And Complex Workloads, Davi D. Dantas Jan 2025

Behavior Analysis Of Simple And Complex Workloads, Davi D. Dantas

Honors Undergraduate Theses

Complex tasks have evolved rapidly in recent times due to tremendous advancements in computational power and data availability. With the ever-increasing presence of complex applications, this paper attempts to distinguish between complex and simple applications. This paper explored side-channel analysis as a method to differentiate complex workloads from simple workloads by monitoring system-level metrics such as power consumption, cache behavior, and memory accesses. By leveraging side-channel effects such as power analysis and memory access, this study seeks to establish unique hardware signatures for complex workloads. Using tools such as Intel Pin, the data will be collected from complex and simple …


Neural Network-Based Image Compression, Atefeh Khoshkhahtinat Jan 2025

Neural Network-Based Image Compression, Atefeh Khoshkhahtinat

Graduate Theses, Dissertations, and Problem Reports (ETD)

The rapid advancement of information technology and the exponential growth of digital communication have significantly increased the demand for efficient data compression techniques that reduce storage requirements, minimize bandwidth consumption, and accelerate data transmission—without substantially compromising data quality. This dissertation addresses these challenges by investigating and developing advanced learned image compression (LIC) methods, with a particular focus on lossy compression for both natural images and scientific imagery obtained from NASA’s Solar Dynamics Observatory (SDO) mission. Traditional image compression standards—such as JPEG, JPEG2000, BPG, and HEVC—rely on manually engineered transforms and heuristic rules, which often lack the adaptability required to accommodate …


Review: Dielectric Barrier Discharge Plasma Actuators For In-Flight Applications, Sabeel Saleem Mohammed Jan 2025

Review: Dielectric Barrier Discharge Plasma Actuators For In-Flight Applications, Sabeel Saleem Mohammed

Anthós

Dielectric barrier discharge (DBD) is a phenomenon observed when high voltage is passed through a dielectric barrier at high frequencies. Current DBD plasma actuators (PAs) excel at laminar fluid boundary layer control but suffer from limited momentum flux and fluid mechanic inefficiencies. In this article, Mohammed analyzes previous discourse on DBD PAs and offers directions for future research and potential DBD PA applications. Previous work on DBD PAs documented thrust generation at high voltages and frequencies, thrust in varying fluid compositions, and vortex generation. However, certain arrangements hinder flow magnitudes, limiting the use of multiple DBD PAs in close proximity. …


Fault Identification And Localization In Distribution Grids Based On An Attention-Hybrid Graph Neural Network, Xingjian Shan Jan 2025

Fault Identification And Localization In Distribution Grids Based On An Attention-Hybrid Graph Neural Network, Xingjian Shan

Theses and Dissertations--Electrical and Computer Engineering

This thesis proposes a multi-task fault diagnosis framework for distribution systems based on Graph Convolutional Networks (GCN) and an enhanced Graph Attention Network (GATv2). By representing the power grid as a graph with electrical features and topological connections, the model simultaneously performs fault type classification and fault location prediction. The architecture incorporates residual connections, multi-head attention, and a Jumping Knowledge module to capture multi-scale structural patterns, while dynamic loss weighting ensures balanced task optimization under noise and sparsity. Experimental results on the IEEE 123-node test feeder demonstrate a fault classification accuracy of 96.43%, and fault localization accuracies of 84.64% (strict), …


Surface Morphology And Moisture Adsorption/Desorption Characteristics Of Hybrid-Dielectric Moisture Sensors, Ronak Ali Jan 2025

Surface Morphology And Moisture Adsorption/Desorption Characteristics Of Hybrid-Dielectric Moisture Sensors, Ronak Ali

Theses and Dissertations--Electrical and Computer Engineering

Relative humidity sensors are used for high-humidity measurement. Moisture sensors, or dew point sensors are used for low-humidity measurement (< 1 ppmv). The dissertation contains two parts of studies. In the first part, the effect of surface morphology on the response speed of moisture sensors is studied. Moisture sensors using α-Al2O3 films as porous dielectric materials deposited by anodic spark deposition are studied. In this part of the study, a variety of small pores have been studied to investigate the response speed of moisture sensors. Three different surface morphologies have been studied using scanning electron microscopy. One …


Measurement Of Moisture Levels In Oils And Lubricants Using A Novel Moisture Sensor, Aaron Swartz Jan 2025

Measurement Of Moisture Levels In Oils And Lubricants Using A Novel Moisture Sensor, Aaron Swartz

Theses and Dissertations--Electrical and Computer Engineering

It is very challenging to measure moisture levels in oils. There is not a good method to measure it. Using the novel moisture sensor, we tried various methods to measure the moisture levels in oils. The initial trials are to immerse the sensor chip into the oils to see any sensor reading changes with the change of moisture levels in oils. It was observed that the sensor reading was unstable. The idea for immersion of the sensor chip into the oils failed. The last idea is to heat the oil to let all moisture evaporate fully. Before heating, the dew …


Mathematical-Programming Modeling Of Power-Electronics-Based Microgrid Systems, Jack A. Robey Jan 2025

Mathematical-Programming Modeling Of Power-Electronics-Based Microgrid Systems, Jack A. Robey

Theses and Dissertations--Electrical and Computer Engineering

The emergence of power-electronics-based microgrid systems is driven by the shift to cleaner energy, transportation electrification, renewable integration, grid modernization through smart grid advancements, and growing demand for energy-efficient solutions. For utilities, these systems present unique opportunities for enhancing grid resilience, improving load management, and enabling distributed energy resource integration. This work presents a modeling and simulation approach for microgrid systems that uses mathematical programming to represent power flow and capture the system dynamics. By solving an optimization problem at each time step, the method enables evaluation of power distribution and system performance under a range of operating conditions, without …


Computing With Photonic Phase Change Memory, David B. Pippen Jan 2025

Computing With Photonic Phase Change Memory, David B. Pippen

Theses and Dissertations--Electrical and Computer Engineering

A recent breakthrough in silicon photonics includes the discovery and use of phase changing materials (PCMs). These materials can be programmed to store nonvolatile values, and when a stored value in a PCM cell is read, it changes the amplitude of the read signal, imprinting the value held into the PCM cell on the amplitude of the read signal. This thesis proposes a new approach to using PCM cells not only for photonic memory but also as a substrate to perform multiplications in the photonic domain. The proposed multiplier uses PCM cells to encode amplitude-analog weight values and differing lengths …


Scalable Hypergraph Structure Learning With Diverse Smoothness Priors, Benjamin T. Brown Jan 2025

Scalable Hypergraph Structure Learning With Diverse Smoothness Priors, Benjamin T. Brown

Theses and Dissertations--Electrical and Computer Engineering

In graph signal processing, learning weighted connections between nodes from signals is a fundamental task when the underlying relationships are unknown. With the extension of graphs to hypergraphs, where edges can connect more than two nodes, graph learning methods have similarly been generalized to hypergraphs. However, the absence of a unified framework for calculating total variation has led to divergent definitions of smoothness and, consequently, differing approaches to hyperedge recovery. This challenge is confronted in this work through generalization of several previously proposed hypergraph total variations, allowing ease of substitution into a vector-based optimization. To this end, a novel hypergraph …


Electromagnetic Integral Equation Methods For High-Order Field Predictions, Jordon N. Blackburn Jan 2025

Electromagnetic Integral Equation Methods For High-Order Field Predictions, Jordon N. Blackburn

Theses and Dissertations--Electrical and Computer Engineering

Methods like the Method of Moments (MoM) or the locally-corrected Nyström (LCN) method are employed to discretize and solve electromagnetic integral equations. This process results in large, dense systems of linear equations that must be solved. In many cases, the elements of the system matrix can be computed analytically or approximated with high-order numerical methods. In this thesis, various approaches are presented to improve the accuracy and efficiency of integral equation solutions.

The second chapter derives a modified form of the low-rank matrix approximation algorithm known as the adaptive cross approximation (ACA). The original ACA has been observed to lose …


Lifecycle Carbon Footprint And Sustainability Evaluation Of Dram-Based Processing In Memory Computing Architectures, Samrat Pravin Patel Jan 2025

Lifecycle Carbon Footprint And Sustainability Evaluation Of Dram-Based Processing In Memory Computing Architectures, Samrat Pravin Patel

Theses and Dissertations--Electrical and Computer Engineering

The use of computing technologies has significantly enhanced several aspects of our day-to-day lives. But it has still revealed significant environmental concerns, primarily related to greenhouse gas emissions and energy consumption. Initially, the primary environmental problems associated with computing were energy consumption during device operation. However, with the rapid advancement of technology and increasing computational demands, attention has shifted towards the embodied carbon footprint. This term refers to the total greenhouse gas emissions throughout a product’s lifecycle from the extraction of raw materials to end-of-life processing. It has become increasingly significant in the context of manufacturing integrated circuits (ICs), such …


Scalable Systems And Devices For Wireless Charging Of Electric Vehicles, Donovin D. Lewis Jan 2025

Scalable Systems And Devices For Wireless Charging Of Electric Vehicles, Donovin D. Lewis

Theses and Dissertations--Electrical and Computer Engineering

The rising adoption of electric vehicles creates new opportunities that are not possible with conventional gas-powered vehicles such as wireless charging of electric vehicles (EV). Wide-scale implementation of wireless charging could result in benefits unique to EVs such as operation without human intervention, improved charging accessibility, and even in-route wireless charging for charge-sustaining or extended driving range operation. As the technology is in the early stages of development, there are many open-ended challenges to tackle including but not limited to coil and systems cost, weight and size, stray field emissions in high-power, high-frequency operation, and dynamic wireless charging system design …


Analysis And Design Optimization Of Electric Machines With Field Intensifying Configuration, Ali Mohammadi Jan 2025

Analysis And Design Optimization Of Electric Machines With Field Intensifying Configuration, Ali Mohammadi

Theses and Dissertations--Electrical and Computer Engineering

The design and optimization of electric machines face increasing demands for efficiency, improved torque density, manufacturability, and effective utilization of materials. Meeting these demands is particularly vital in for example, electric vehicles (EVs) and renewable energy systems, where performance, reliability, and cost are critical. In this dissertation innovative field-intensifying electric machine configurations have been explored, emphasizing advanced topologies, computational modeling, and optimization techniques to advance the state of the art in electric machine design and analysis.

Electric machines with high torque density are essential for many low-speed direct-drive systems, such as wind turbines, in-wheel traction, and industrial automation. This dissertation …


Multi-Objective Design Optimization Of Power Converters For Electric Aircraft Propulsion, Ben Luckett Jan 2025

Multi-Objective Design Optimization Of Power Converters For Electric Aircraft Propulsion, Ben Luckett

Theses and Dissertations--Electrical and Computer Engineering

As global focus shifts to the electrification of the aviation sector, the need for high efficiency, lightweight, and reliable electric aircraft propulsion power converter systems has become apparent. These goals can be somewhat conflicting with each other, and a single multi-domain-optimized solution is not guaranteed. The search for a design which presents satisfactory merits becomes a drudge through various trade-off studies which can expend vast quantities of manpower and time. As a remedy to this, design automation allows the process to be computer-assisted. This dissertation presents the core fundamentals for a general multi-objective design optimization framework intended for the design …


Emi Mitigation, Material Characterization, Transformer Equivalent Circuit Modeling, Reza Vahdani Jan 2025

Emi Mitigation, Material Characterization, Transformer Equivalent Circuit Modeling, Reza Vahdani

Masters Theses

Modern high-frequency electronic systems demand precise characterization and modeling techniques to ensure signal integrity and electromagnetic compatibility. This thesis presents three core studies focused on real-world challenges in high-speed and power electronics: EMI mitigation using 3D printed absorbers, wideband liquid dielectric characterization, and accurate transformer modeling.

The first study demonstrates a targeted approach to mitigating electromagnetic interference (EMI) in a commercial router. By using holography imaging to identify radiation hotspots, custom absorber structures were designed with commercially available materials, fabricated via 3D printing, and applied directly to emission sources. Radiated emission tests in a reverberation chamber showed up to 9 …


Implementation Of Quantized Artificial Neural Networks With Spintronic Stochastic Computing, Saadi Sabyasachi Mr. Jan 2025

Implementation Of Quantized Artificial Neural Networks With Spintronic Stochastic Computing, Saadi Sabyasachi Mr.

Theses and Dissertations

Artificial intelligence or machine learning is going through a rapid expansion. It also incurs significant costs for power and device footprints. Various approaches are being explored to design energy and hardware efficient machine learning models. Stochastic computing has been proposed for efficient machine learning implementation. It requires a source of random number generation which poses some practical challenges. So spintronic solutions such as magnetic tunnel junction has been used for random number generation. Again, spintronic random number generation to implement high precision circuit is prone to device-to-device variations. Hence we designed quantized artificial neural network with spintronic stochastic computing which …


Advancing Electrical Stimulation: Full-Head Mri Segmentation For Abnormal Brain Anatomy With Tdcs, Andrew Birnbaum Jan 2025

Advancing Electrical Stimulation: Full-Head Mri Segmentation For Abnormal Brain Anatomy With Tdcs, Andrew Birnbaum

Dissertations and Theses

Evaluating the effectiveness of transcranial direct current stimulation (tDCS) is essential for guiding its integration into therapeutic and performance-enhancement applications. In our laboratory, we investigate the efficacy of tDCS across multiple experimental models, including both animal and human studies. I have contributed significantly to the execution and analysis of these experiments, which include studies in rats and healthy human participants aimed at evaluating whether electrical stimulation of the motor cortex can enhance motor learning. These studies assess improvements in fine motor performance resulting from tDCS. In stroke patients, I contribute to our investigation of tDCS as a rehabilitative intervention, particularly …


A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu Jan 2025

A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu

Engineering Technology Faculty Publications

The global energy sector is undergoing a significant transformation driven by decarbonization and digitalization, leading to the emergence of Distributed Ledger Technology (DLT) — particularly blockchain — as a promising tool for enhancing transparency, security, and efficiency in modern power systems. This study aims to provide a comprehensive academic and industrial survey of blockchain applications in the energy sector and develop a robust decision-making framework to identify and prioritize the most promising real-world use cases based on multidisciplinary criteria. A three-stage methodology was adopted: (i) a literature and market review encompassing over 300 academic publications and commercial blockchain initiatives in …


Differential Equations' Coverage In Circuits And Heat Transfer Courses In An Engineering Technology Curricula, Otilia Popescu, Orlando Ayala Jan 2025

Differential Equations' Coverage In Circuits And Heat Transfer Courses In An Engineering Technology Curricula, Otilia Popescu, Orlando Ayala

Engineering Technology Faculty Publications

Differential equations are at the core of any undergraduate engineering as well as of science programs. While a course in differential equations is required by any engineering degree, it is not a requirement for engineering technology programs, which usually require mathematics up to calculus I. This paper discusses the undergraduate engineering technology curricula, focusing on how differential equations are taught to engineering technology students and how they are covered in the programs. In particular, the paper will discuss the treatment of differential equations in electrical circuits and heat transfer courses.


Waveforms For Next Generation Non-Stationary Channels, Zhibin Zou Jan 2025

Waveforms For Next Generation Non-Stationary Channels, Zhibin Zou

Electronic Theses & Dissertations (2024 - present)

Waveform design aims to achieve orthogonality among data signals/symbols across all available Degrees of Freedom (DoF) to avoid interference while transmitted over the channel. Precoding involves the decomposition of the channel matrix into orthogonal components for the purpose of constructing a precoding matrix that is then combined with the data signal to achieve orthogonality in the spatial dimension. On the other hand, modulation uses orthogonal carriers in a certain signal space to carry data symbols with minimal interference from other symbols. However, it is widely evident that next Generation (xG) wireless systems will experience very high mobility, density and time-varying …


Design Of Fast Start-Up High-Q Oscillator For Wireless Sensor Nodes Transceiver Frequency Reference, Abdolraouf Rahmani Jan 2025

Design Of Fast Start-Up High-Q Oscillator For Wireless Sensor Nodes Transceiver Frequency Reference, Abdolraouf Rahmani

Student Works (2020-2029)

With the prevalence of wireless sensor networks and the Internet of Things (IoT), optimizing power in battery-powered wireless nodes is crucial due to the inconvenience and cost of replacing batteries in remote areas. Synchronized power modulation between "Sleep" and "Active" states, known as burst mode activation, allows nodes to conserve power. However, frequent transitions between these states consume significant energy, highlighting the need to reduce the start-up time of the slowest component, the high-Q crystal oscillator. Additionally, to ensure improved synchronization within the network and a cost-effective IoT device manufacturing, the device should be produced with low start-up time variations …


Bright And Dark Pulsed Fiber Lasers Based On Multimode Interference, Yu Chen Jan 2025

Bright And Dark Pulsed Fiber Lasers Based On Multimode Interference, Yu Chen

Student Works (2020-2029)

Pulsed lasers, particularly ultrashort pulsed lasers, find widespread application across various fields including telecommunications, bio-imaging, spectroscopy, atmospheric measurements, surgery, and material processing. This study focuses on harnessing the potential of the single mode-multimode-single mode (SMS) structure as a robust avenue for developing simple, compact, and cost-effective bright and dark pulsed erbium-doped fiber lasers (EDFLs). The SMS configuration serves as an ingenious artificial saturable absorber (SA), facilitating the generation of ultrashort pulsed lasers through the Kerr Effect with nonlinear multimode interference. By precisely fusion-splicing single mode fibers to both ends of a designated length of multimode fiber, the SMS architecture is …


The Space Rescue Professional: Operationalizing Guardians For The Future, Benjamin Johnis, Robert Bettinger, James Dean Jan 2025

The Space Rescue Professional: Operationalizing Guardians For The Future, Benjamin Johnis, Robert Bettinger, James Dean

Faculty Publications

The escalating competition in space exploration demands a dedicated space rescue capability. This article argues for the establishment of a space rescue professional (SRP) career field within the Department of Defense and the US Space Force. By harnessing existing US Air Force combat rescue expertise and partnering with the National Aeronautics and Space Administration, the Space Force can rapidly develop a robust SRP program with the warrant officer corps as its backbone. This article addresses a critical gap in national space policy to outline a cost-effective dual-service training pipeline and SRP operational roles. Such an investment safeguards astronauts, bolsters US …


Optimizing Ai Language Models: A Study Of Chatgpt-4 Vs. Chatgpt-4o, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md Fayaz Bin Hossen, Muhammad Rezaur Rahman, Md. Shahadat Jaman Jan 2025

Optimizing Ai Language Models: A Study Of Chatgpt-4 Vs. Chatgpt-4o, Md Nurul Absar Siddiky, Muhammad Enayetur Rahman, Md Fayaz Bin Hossen, Muhammad Rezaur Rahman, Md. Shahadat Jaman

Electrical & Computer Engineering Faculty Publications

This paper presents a comparative analysis of OpenAI's GPT-4 and its optimized variant, GPT-4o, focusing on their architectural differences, performance, and real-world applications. GPT-4, built upon the Transformer architecture, has set new standards in natural language processing (NLP) with its capacity to generate coherent and contextually relevant text across a wide range of tasks. However, its computational demands, requiring substantial hardware resources, make it less accessible for smaller organizations and real-time applications. In contrast, GPT-4o addresses these challenges by incorporating optimizations such as model compression, parameter pruning, and memory-efficient computation, allowing it to deliver similar performance with significantly lower computational …


Optimizing Superconducting Nb Film Cavities By Mitigating Medium-Field Q-Slope Through Annealing, B. Abdisatarov, G. Eremeev, H. E. Elsayed-Ali, D. Bafia, A. Murthy, Z. Sung, A. Netepenko, A. Romanenko, C. P.A. Carlos, G. J. Rosaz, S. Calatroni, S. Leith, A. Grassellino Jan 2025

Optimizing Superconducting Nb Film Cavities By Mitigating Medium-Field Q-Slope Through Annealing, B. Abdisatarov, G. Eremeev, H. E. Elsayed-Ali, D. Bafia, A. Murthy, Z. Sung, A. Netepenko, A. Romanenko, C. P.A. Carlos, G. J. Rosaz, S. Calatroni, S. Leith, A. Grassellino

Electrical & Computer Engineering Faculty Publications

Niobium films are of interest in applications in various superconducting devices, such as superconducting radiofrequency cavities for particle accelerators and superconducting qubits for quantum computing. In this study, we address the persistent medium-field Q-slope issue in Nb film cavities, which, despite their high-quality factor at low RF fields, exhibit a significant Q-slope at medium RF fields compared to bulk Nb cavities. Traditional heat treatments, effective in reducing surface resistance and mitigating the Q-slope in bulk Nb cavities, are challenging for Nb-coated copper cavities. To overcome this challenge, we employed DC bias high-power impulse magnetron sputtering to deposit …


High-Fidelity Soh Prediction In Lithium-Ion Batteries Using Hybrid Ml Networks, Shafiyee Islam, Gon Namkoong Jan 2025

High-Fidelity Soh Prediction In Lithium-Ion Batteries Using Hybrid Ml Networks, Shafiyee Islam, Gon Namkoong

Electrical & Computer Engineering Faculty Publications

Accurate and efficient prediction of lithium-ion battery state of health (SOH) is critical for ensuring reliability in electric vehicles, grid storage, and aerospace systems. Traditional SOH estimation methods often struggle with nonlinear degradation behaviors and lack sensitivity to subtle electrochemical signals, limiting their real-world deployment. To address these challenges, this study examines hybrid deep learning models that integrate differential capacity (dQ/dV) analysis to enhance predictive accuracy. Four hybrid architectures - hybrid CNN-LSTM multihead, CNN extractor for LSTM, DNN-LSTM, and DNN Bi-LSTM - were developed and evaluated using the NASA randomized battery usage dataset, offering a realistic benchmark under diverse operational …


A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian Jan 2025

A Method For Ultrasound Servo Tracking For Puncture Needle, Shitong Ye, Bo Yang, Hao Quan, Shan Liu, Minyu Tang, Jiawei Tian

Electrical & Computer Engineering Faculty Publications

Computer-aided surgical navigation technology helps and guides doctors to complete the operation smoothly, which simulates the whole surgical environment with computer technology, and then visualizes the whole operation link in three dimensions. At present, common image-guided surgical techniques such as computed tomography (CT) and X-ray imaging (X-ray) will cause radiation damage to the human body during the imaging process. To address this, we propose a novel Extended Kalman filter-based model that tracks the puncture needle-point using an ultrasound probe. To address the limitations of Kalman filtering methods based on position and velocity, our method of Kalman filtering uses the position …