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Advanced Digital Wideband Receiver Design: High Dynamic Range And Enhanced Multi-Signal Detection With Fpga-Based Custom Fft And Nyquist Folding, Kiran Jayarama

Browse all Theses and Dissertations

In modern wideband receiver standards, efficient frequency spectrum utilization is essential to meet demands for high data rates, reduced latency, and enhanced connectivity. The Fast Fourier Transform (FFT) stands as a pivotal technology, particularly in radar signal processing, where it supports tasks such as target detection, range estimation, and velocity estimation by analyzing the frequency content of the received radar signals. This dissertation introduces the design of an advanced digital wideband receiver featuring a high dynamic range for multiple signals, with a focus on improved performance, compact size, and reduced power consumption, implemented on an FPGA using custom hardware. Key …

Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor physical activity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a millimeter-wave (mmwave) radar sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can …

Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Convolutional neural networks (CNNs) have become instrumental in advancing multi-frame image super-resolution (SR), a technique that merges multiple low-resolution images of the same scene into a high-resolution image. In this paper, a novel deep learning multi-frame SR algorithm is introduced. The proposed CNN model, named Exponential Fusion of Interpolated Frames Network (EFIF-Net), seamlessly integrates fusion and restoration within an end-to-end network. Key features of the new EFIF-Net include a custom exponentially weighted fusion (EWF) layer for image fusion and a modification of the Residual Channel Attention Network for restoration to deblur the fused image. Input frames are registered with subpixel …

Parameter Identifiability Analysis And Calibration For Power System Dynamic Models, Lei Wang

Electronic Theses and Dissertations

Accurate dynamic models are crucial for stable and reliable power system operation, making their validation essential. The accuracy of parameter estimation is influenced by several factors, including available observables, model structure, and estimation methods. However, in dynamic models, estimating parameters can be difficult when some of them are unidentifiable, meaning their values cannot be uniquely determined from the available data. This challenge may stem from limited impact of parameters on the measured outputs, parameter interactions, or poor data quality. Therefore, an identifiability analysis should be conducted prior to parameter estimation or model calibration. This preliminary step helps to determine which …

Optimization Of Energy From Building Integrated Photovoltaic Of High-Rise Buildings In Thailand, Min Khant

Chulalongkorn University Theses and Dissertations (Chula ETD)

This project is to find the method to optimize the energy from Building Integrated Photovoltaic System in high rise building. Firstly, the solar irradiance potential of vertical surfaces of high-rise building is analyzed in Bangkok, Thailand. With these irradiance values, the optimal size and placement of BIPV module on east, west and south façades of the building is analyzed in order to minimize the building energy usage from the electricity grid. The BIPV system is optimized using the Genetic Algorithm Optimization method in MATLAB. The output results include the optimal surface area used by BIPV module in east, west and …

Modeling And Mitigating Power Grid Vulnerabilities: A Comprehensive Analysis Of Renewable Energy Integration, Cascading Failures, And Microgrid Resilience, Saikat Das

Theses and Dissertations

In modern power systems, rapid integration of renewable energy and the emergence of microgrid technology emphasize the necessity for a comprehensive understanding of vulnerabilities and robust defense mechanisms. The research begins with an exploration of power grid vulnerabilities to cascading failure amidst the increasing integration of renewable energy sources. A novel power balance technique is employed for cascading failure analysis and power grid vulnerability measurement. Simulation results indicate that the growing penetration of renewable energy has a proportionally higher impact on grid vulnerability to cascading failures. After a certain level of renewable energy penetration, some systems may deteriorate rapidly, necessitating …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ben Robinson, Ali Mohammadi, Mark Thiele, Dean Patterson, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

Simulation Of A Pick And Place System For Electronic Cards Using A Yumi Cobot, Derrick Sze, Rosula Sj Reyes, Patricia Angela R. Abu

Electronics, Computer, and Communications Engineering Faculty Publications

Collaborative Robots are one of the main drivers of Industry 4.0, which started as a vision focusing on industrial production. It addresses several challenges in the current manufacturing industry such as performing repetitive work and requiring highly skilled workers. The goal of the research is to be able to simulate a pick and place environment with electronic cards using a YuMi cobot and mobile platforms in Coppeliasim. The mobile robot is responsible for transporting the electronic cards to the target location through path planning implemented using the OMPL plug-in. After arriving at the target location, YuMi will then perform the …

Federated Learning: Overview, Strategies, Applications, Tools And Future Directions, Betul Yurdem, Murat Kuzlu, Mehmet Kemal Gullu, Maliha Tabassum

Engineering Technology Faculty Publications

Federated learning (FL) is a distributed machine learning process, which allows multiple nodes to work together to train a shared model without exchanging raw data. It offers several key advantages, such as data privacy, security, efficiency, and scalability, by keeping data local and only exchanging model updates through the communication network. This review paper provides a comprehensive overview of federated learning, including its principles, strategies, applications, and tools along with opportunities, challenges, and future research directions. The findings of this paper emphasize that federated learning strategies can significantly help overcome privacy and confidentiality concerns, particularly for high-risk applications.

Generation Expansion Planning In Isolated Power Systems: A Robust Approach With Dunkelflaute Assessment, Taraneh Ghanbarzadeh, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

Generation expansion planning is vital for decarbonizing power systems and ensuring a reliable and sustainable energy future. Strategically adding new generation and grid capacity is essential for supporting a seamless transition to renewable energy while reducing greenhouse gas emissions. However, achieving the optimal capacity mix of energy resources to ensure network reliability and economic efficiency presents significant challenges, particularly for isolated electricity grids. These challenges are exacerbated during periods of low renewable generation and due to the inherent intermittency of weather-dependent energy resources. This paper presents a comprehensive approach to optimizing long-term expansion planning for an isolated electricity grid, focusing …

Photoluminescence Switching In Quantum Dots Connected With Fluorinated And Hydrogenated Photochromic Molecules, Ephraiem S. Sarabamoun, Jonathan M. Bietsch, Pramod Aryal, Amelia G. Reid, Maurice Curran, Grayson Johnson, Esther H. R. Tsai, Charles W. Machan, Guijun Wang, Joshua J. Choi

Chemistry & Biochemistry Faculty Publications

We investigate switching of photoluminescence (PL) from PbS quantum dots (QDs) crosslinked with two different types of photochromic diarylethene molecules, 4,4'-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (1H) and 4,4'-(1-perfluorocyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (2F). Our results show that the QDs crosslinked with the hydrogenated molecule (1H) exhibit a greater amount of switching in photoluminescence intensity compared to QDs crosslinked with the fluorinated molecule (2F). With a combination of differential pulse voltammetry and density functional theory, we attribute the different amount of PL switching to the different energy levels between 1H and 2F molecules which result in different potential barrier …

A Comprehensive Review Of Piezoelectric Ultrasonic Motors: Classifications, Characterization, Fabrication, Applications, And Future Challenges, Sidra Naz, Tian-Bing Xu

Mechanical & Aerospace Engineering Faculty Publications

Piezoelectric ultrasonic motors (USMs) are actuators that use ultrasonic frequency piezoelectric vibration-generated waves to transform electrical energy into rotary or translating motion. USMs receive more attention because they offer distinct qualities over traditional magnet-coil-based motors, such as miniaturization, great accuracy, speed, non-magnetic nature, silent operation, straightforward construction, broad temperature operations, and adaptability. This review study focuses on the principle of USMs and their classifications, characterization, fabrication methods, applications, and future challenges. Firstly, the classifications of USMs, especially, standing-wave, traveling-wave, hybrid-mode, and multi-degree-of-freedom USMs, are summarized, and their respective functioning principles are explained. Secondly, finite element modeling analysis for design and …

Real-Time Occupancy-Based Control Of Hvac Systems In Office Buildings Considering Energy Saving And Thermal Comfort, Emmanuel Agabi

Chulalongkorn University Theses and Dissertations (Chula ETD)

Traditional heating, ventilation, and air conditioning (HVAC) control systems often waste energy and fail to maintain thermal comfort due to their reliance on static setpoints, manual on/off control, and limited responsiveness to occupancy and weather conditions. With advancements in the Internet of Things (IoT), integrating occupancy data into building energy management systems, including HVAC systems, has progressed beyond conventional sensor-based approaches. This thesis addresses the inefficiency of traditional control of HVAC systems by proposing two strategies for a single-zone office building. The first one is occupancy-based control (OBC), and the second is data-driven supervisory model predictive control (SMPC). By leveraging …

Contextual Matching And Aggregation Network For Mri Image Super-Resolution, Abdulhamid Muhammad

Chulalongkorn University Theses and Dissertations (Chula ETD)

High-resolution (HR) Magnetic Resonance Imaging (MRI) provides detailed visualization of healthy and pathological tissues, making it a vital tool for accurate diagnosis, and enhancing physicians’ ability to detect lesions with better precision. However, obtaining HR MRI images in practice is often challenging due to hardware limitations, extended scan durations, and patient discomfort. Super-resolution (SR) techniques have been developed to recover HR image from LR image. However, capturing and integrating local and global features remains a significant challenge, as many approaches inadequately model the complex contextual correlations across multiple scales thereby degrading reconstruction quality. To address these limitations, we propose an …

An Attention-Guided Image Super-Resolution For Scene Text, Tithnorakneath Em

Chulalongkorn University Theses and Dissertations (Chula ETD)

Scene Text Image Super-Resolution (STISR) is crucial in enhancing text recognition for low-resolution images, often degraded due to environmental and device limitations. While many existing STISR approaches leverage super-resolution techniques to refine image quality, they frequently need specialized mechanisms to extract text-specific features. Most existing methods were based on feature extraction methods that missed critical details, such as edges and text-background contrasts, that are usually important for recognition. In this work, we propose a new feature extraction method that uses Channel Attention and Spatial Attention mechanisms to emphasize features related to text, namely edges, contours, and spatial alignment. We add …

Structured Invariant Subspace And Decomposition Of Systems With Time Delays And Uncertainties, Huan Phan-Van, Keqin Gu

SIUE Faculty Research, Scholarship, and Creative Activity

This article discusses invariant subspaces of a matrix with a given partition structure. The existence of a nontrivial structured invariant subspace is equivalent to the possibility of decomposing the associated system with multiple feedback blocks such that the feedback operators are subject to a given constraint. The formulation is especially useful in the stability analysis of time-delay systems using the Lyapunov-Krasovskii functional approach where computational efficiency is essential in order to achieve accuracy for large scale systems. The set of all structured invariant subspaces are obtained (thus all possible decompositions are obtained as a result) for the coupled differential-difference equations …

A Novel Computational Analysis Of Boundary-Driven Two-Dimensional Heat Flow With Internal Heat Generation, Muhammad Abid, Madiha Bibi, Nasir Yasin, Muhammad Shahid

Mathematics & Statistics Faculty Publications

Accurate numerical solution of parabolic and elliptic partial differential equations governing two-dimensional heat transfer is critical for engineering simulations but computationally challenging. This work employs key numerical techniques finite differences, conjugate gradients, and Crank-Nicolson time stepping to solve the heat diffusion equation and analyze method performance. The Poisson equation is discretized using second-order central finite differences and solved with the conjugate gradient approach to determine the steady state solution. The transient heat equation is integrated in time via the Crank-Nicolson implicit scheme, also utilizing conjugate gradients. The methods effectively compute solutions matching analytical and boundary conditions. Convergence and stability are …

Tunable Metasurface For Efficient Harmonic Generation And Amplitude Modulation, Steve Mares

Masters Theses

The manipulation of microwave signals is critical in the information and communication technology industry. This research investigates the application of time-coding techniques on metasurfaces to achieve tunable control of electromagnetic signal transmission. The integration of mounted PIN diodes facilitates dynamic modulation of signal behavior. Both passive (without PIN diodes) and active (with PIN diodes) metasurfaces were analyzed through simulations using Ansys HFSS and validated with experimental measurements. A major contribution of this work is the design and testing of active metasurfaces that leverage PIN diodes for harmonic generation and amplitude modulation. The study reveals a clear relationship between modulating signal …

Integrating Generative Artificial Intelligence With Systems Architecting Diagram Creation: Advancement, Challenges, Opportunities And Future Perspectives, Cansu Yalim, Holly H. Handley

Engineering Management & Systems Engineering Faculty Publications

Generative AI (GenAI) serves as a powerful tool that can create a wide range of content, including but not limited to text, speech, images, code, videos, and 3D models. ChatGPT stands out as a particularly appealing Generative Pretrained Transformer (GPT) model that offers supplementary capabilities through GPTs and plugins. These extensions enable users to engage with the chatbot and improve its functionality, surpassing mere content generation. Our study delves into the potential of ChatGPT, specifically GPT-4, to expedite the creation of diagrams to support the system architecting process. To this end, we explored the use of ChatGPT's Diagrams Show Me …

Design And Control Of Axial Flux Permanent Magnet Coreless Machines With Special Windings, Yaser Chulaee

Theses and Dissertations--Electrical and Computer Engineering

Permanent magnet synchronous machines (PMSMs), particularly those of the axial flux type, are being researched and developed for various applications such as HVAC systems, aviation propulsion, and electric vehicles. The coreless (air-cored) stator axial flux permanent magnet (AFPM) machine topology offers notable advantages over conventional designs by eliminating magnetic cores and their associated losses. These advantages include potentially higher efficiency, zero cogging torque, and reduced audible noise and vibration. Eliminating the magnetic core also allows for more effective cooling systems, as coolants can be in direct contact with the stator windings, potentially improving power density and specific torque.

The absence …

Ultra‐Fast Finite Element Analysis Of Coreless Axial Flux Permanent Magnet Synchronous Machines, Yaser Chulaee, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Large‐scale design optimisation techniques enable the design of high‐performance electric machines. Electromagnetic 3D finite element analysis (FEA) is typically employed in optimisation studies for accurate analysis of axial flux permanent magnet (AFPM) machines, which require extensive computational resources. To reduce the computational burden, a FEA‐based mathematical method relying on the geometric and magnetic symmetry of coreless AFPM machines is proposed to estimate the machine performance indicators using the least number of FEA solutions, thereby significantly lowering the running time. This method is generally applicable to AFPM machines with low saturation effects and cogging torque as exemplified for a printed circuit …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ali Mohammadi, Mark Thiele, Dan M. Ionel, Ben Robinson

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

Design Optimization Of A Direct-Drive Wind Generator With A Reluctance Rotor And A Flux Intensifying Stator Using Different Pm Types, Ali Mohammadi, Oluwaseun A. Badewa, Yaser Chulaee, Donovin D. Lewis, Somasundaram Essakiappan, Madhav Manjrekar

Electrical and Computer Engineering Graduate Research

This paper presents a large-scale multi-objective design optimization for a direct-drive wind turbine generator concept that is based upon an experimentally validated computational model for a small-scale prototype motor of the same type. By integrating an outer reluctance-type rotor and a segmented stator with toroidally wound single-coil modules containing spoke-type PMs, the design optimization aims to minimize losses, active mass, and torque ripple while adhering to a power factor constraint. The AC windings and PMs are positioned in the stator and this concept enhances flux concentration, enabling the use of more affordable high energy non-rare-earth (special type) magnets. The exterior …

Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Periodontitis is a high prevalence dental disease caused by bacterial infection of the bone that surrounds the tooth. Early detection and precision treatment can prevent more severe symptoms such as tooth loss. Traditionally, periodontal disease is identified and labeled manually by dental professionals. The task requires expertise and extensive experience, and it is highly repetitive and time-consuming. The aim of this study is to explore the application of AI in the field of dental medicine. With the inherent learning capabilities, AI exhibits remarkable proficiency in processing extensive datasets and effectively managing repetitive tasks. This is particularly advantageous in professions demanding …

Photoluminescence Switching In Quantum Dots Connected With Carboxylic Acid And Thiocarboxylic Acid End-Group Diarylethene Molecules, Ephraiem S. Sarabamoun, Pramod Aryal, Jonathan M. Bietsch, Maurice Curran, Sugandha Verma, Grayson Johnson, Lucy U. Yoon, Amelia G. Reid, Esther H. R. Tsai, Charles W. Machan, Christopher Paolucci, Guijun Wang, Joshua J. Choi

Chemistry & Biochemistry Faculty Publications

We contrast the switching of photoluminescence (PL) of PbS quantum dots (QDs) cross-linked with photochromic diarylethene molecules with different end groups, 4,4′-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (1C) and 4,4′-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenethiocarboxylic acid] (2T). Our results show that the QDs cross-linked with the carboxylic acid end group molecules (1C) exhibit a greater amount of switching in photoluminescence intensity compared to QDs cross-linked with the thiocarboxylic acid end group (2T). We also demonstrate that regardless of the molecule used, greater switching amounts are observed for smaller quantum dots. Varying these parameters allows for the fabrication of photoswitches with tunable PL change. We relate these observations to the …

Semiconductor Photonic Crystal Surface Emitting Lasers For High Power, High Brightness And High Speed Applications, Chhabindra Gautam

Electrical Engineering Dissertations - Archive

Photonic Crystal Surface Emitting Laser (PCSEL) is the promising third generation semiconductor laser technology as it addresses the challenges of the conventional semiconductor lasers (EEL/VCSEL) by providing single mode high power output with good beam quality (thus high brightness). The large area in plane coupling resulting from the multiple Bragg’s diffraction conditions in the periodic 2D photonic crystal cavities in the lasing cladding region leads to single mode operation over very large area. By model design engineering, such in plane lasing cavity can leak the light out of the plane, which result in surface emission. The ability to scale the …

Eece 7220/8220: Scientific Computing (Syllabus), Madhusudhanan Balasubramanian

Electrical and Computer Engineering Syllabi Archive

Course Description: Review of scientific computing mathematical preliminaries. Topics include numerical linear algebra, orthogonality, eigenvalues, boundary value problems, integral equations and Green's functions, numerical integration, basic iterative methods, preconditioning, parallel programming, and advanced topics.

Artificial Intelligence Enabled Machinery Fault Detection And Diagnosis Using Vibro-Acoustic Signals, Srinivasa Rao Ippili

Theses and Dissertations--Mechanical and Aerospace Engineering

In various industries, the early detection of faults in rotating machinery is crucial to prevent system failures and ensure customer satisfaction. Typically, vibration measurement and diagnosis are employed for fault detection, but this process faces challenges in automation due to the complexity of installing and maintaining accelerometers, particularly in end-of-line quality control or pre-installed machinery health assessments. Acoustic signals, as a form of mechanical wave, offer an alternative for monitoring machinery while in operation. Unlike accelerometers, acoustic transducers are non-contact and easy to set up, enabling real-time data collection without interrupting equipment operation. However, utilizing acoustic signals in manufacturing poses …

Application Of Fusion Based Deep Learning Models To Improve Millimeter Wave Beamforming, Abishek Subramanian

Dissertations, Master's Theses and Master's Reports

This study addresses the challenge of selecting millimeter Wave (mmWave) beamforming pairs for vehicle-to-infrastructure (V2I) communication, to mitigate latency in highly dynamic vehicular environments. We investigate the use of out-of-band sensor data as side information to model mmWave ray tracing paths and predicting a subset of top-K optimal beamforming pairs for efficient and low-latency searches. Unimodal-Fusion Deep Learning (F-DL) networks was applied to enhance mmWave beamforming process. We started by first investigating the centralized architecture, and then explored a novel distributed architecture through federated learning to minimize resource and latency overheads. The distributed architecture incorporates two biased client selection strategies: …

Transient Simulations Of Power Systems With Inverter Interfaced Resources, Gaurish Shreedhar Gokhale

Dissertations, Master's Theses and Master's Reports

Renewable energy sources are interfaced with the electrical grid using power electronic inverters. These inverter-interfaced resources have been deployed for nearly 20 years. Still, NERC only recently highlighted the vast gap between the actual behavior of these inverters during power system transients and those observed in simulations. Simulation models need significant improvements, mainly for developing accurate inverter current controls, phase-locked loops, and fault response during different power priority modes. Additionally, only time-domain electromagnetic transient simulation tools can fully represent the fault response of the inverter-interfaced resources.

The developed simulation model of the inverter-interfaced resource is based on the recommendations made …