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Articles 91 - 120 of 1219
Full-Text Articles in Engineering
A Cmos Ldo Voltage Regulator For Low Power Applications, Nicolaus Vail
A Cmos Ldo Voltage Regulator For Low Power Applications, Nicolaus Vail
Graduate Theses and Dissertations
This thesis presents the design, simulation, layout, and testing of a low dropout linear voltage regulator (LDO) in a 180 nm CMOS process. The LDO is intended for use in low-power, battery-operated applications, and it has an adjustable output for a variety of different implementations. It can supply up to 100 mA of current, which is enough to power many small electronic circuits. It has a dropout voltage of 150 mV, and it consumes less than 200 μA of current during operation, which is on par with many commercial regulators. The line regulation is also comparable to commercially available LDOs, …
Synthesis And Process Optimization Of Cellulose Nanocrystals From Miscanthus X. Giganteus For Commercial Viability, Jaspreet Kaur
Synthesis And Process Optimization Of Cellulose Nanocrystals From Miscanthus X. Giganteus For Commercial Viability, Jaspreet Kaur
Graduate Theses and Dissertations
Cellulose nanocrystals (CNCs), derivatives of an abundant biopolymer, i.e., cellulose, are emerging as promising alternatives to petrochemical-based products due to their unique properties, including biodegradability, low toxicity, high strength, low density, large surface area and low coefficient of expansion. CNCs have diverse applications ranging from food packaging and textiles to drug delivery and medical implants, etc. Despite their potential, the widespread commercialization of CNCs faces significant hurdles owing to the high environmental burden and production costs. They are mainly driven by the commonly used source utilized for CNC synthesis i.e., wood and the intensive synthesis process i.e., requirement of …
Investigating Functionalized Cvd Graphene Heterostructures As Platforms For Hydrogen Gas Sensing, Evans Asiedu Addo-Mensah
Investigating Functionalized Cvd Graphene Heterostructures As Platforms For Hydrogen Gas Sensing, Evans Asiedu Addo-Mensah
Graduate Theses and Dissertations
The hydrogen economy is rapidly advancing and is poised to become one of the world's largest economies, driven by the abundance of hydrogen gas. Several organizations, particularly in the United States of America, are closely or have been monitoring this development, with rapidly increasing interest. Considering that hydrogen gas has no taste, smell (odor), or color, and very combustible, it’s imperative to develop detectors and sensors capable of rapidly detecting leaks to prevent application disasters. Owing to its extraordinary mechanical and electrical characteristics, graphene is the material that has been studied the most. When combined with hexagonal boron nitride (hBN), …
Multimodal Spectroscopy To Study Tumor Microenvironmental Changes In Vivo, April Mordi
Multimodal Spectroscopy To Study Tumor Microenvironmental Changes In Vivo, April Mordi
Graduate Theses and Dissertations
Every year there are millions of new cancer diagnoses and deaths worldwide. While great strides have been made in technologies and drugs for cancer treatment, there is still a need to understand tumor response to therapy as many patients still endure treatment failure after completing their treatment regimen. Current clinical imaging techniques for detecting response to therapy are utilized weeks to months after the course of treatment, and present limitations to measuring response during treatment. Optical spectroscopy techniques can help meet this need to determine the response of tumors to treatment as it allows for near real-time in vivo characterization …
Causal Discovery In Time Series Data Using Deep Learning Techniques, Saima Zahin Farhana Absar
Causal Discovery In Time Series Data Using Deep Learning Techniques, Saima Zahin Farhana Absar
Graduate Theses and Dissertations
Causal structure learning from observational data has been an active field of research over the past decades. In the literature, different algorithms and models have been proposed, such as constrained-based methods and score-based methods including the emerging deep learning-based methods. However, most of the approaches apply to static and non-dynamic data only. In many applications, the data is temporal. For example, monitoring systems, weather surveillance systems, and stock data, to name but a few. Incorporating temporal information is an important extension of the causal discovery field. With the growth of observational data these days, the discovery of causal relationships from …
Neural Network Architecture Search Enabled Wide-Deep Learning (Nas-Wd) Integrated Hyperspectral Imaging Understanding For Woody Breast In Poultry Processing, Chaitanya Kumar Reddy Pallerla
Neural Network Architecture Search Enabled Wide-Deep Learning (Nas-Wd) Integrated Hyperspectral Imaging Understanding For Woody Breast In Poultry Processing, Chaitanya Kumar Reddy Pallerla
Graduate Theses and Dissertations
The development and implementation of a Wide & Deep (WD) learning model tailored for classification and regression tasks utilizing spectral data provides a robust solution to evaluate woody breast (WB) conditions in poultry fillets. This process begins with thorough data preprocessing, which includes loading spectral and classification datasets, imputing missing values with medians, and splitting the data into training and testing sets to ensure rigorous model evaluation. The WD model architecture integrates wide linear models and deep neural networks to harness the strengths of both approaches. The wide component excels at memorizing sparse feature interactions, while the deep component captures …
Two-Photon Imaging For Characterizing Tumor Microenvironmental Changes In Non-Small Cell Lung Cancer Associated With Metastatic Recurrence, Paola Monterroso Diaz
Two-Photon Imaging For Characterizing Tumor Microenvironmental Changes In Non-Small Cell Lung Cancer Associated With Metastatic Recurrence, Paola Monterroso Diaz
Graduate Theses and Dissertations
Lung cancer remains the leading cause of cancer deaths, comprising nearly 25% of all cancer deaths (Sung et al., 2021a). The five-year survival rate of patients with non-small cell lung carcinoma (NSCLC) remains significantly low given that over half present with locally advanced or metastatic disease at time of diagnosis, and experience tumor recurrence following therapeutic intervention (Tamura et al., 2015; Uramoto & Tanaka, 2014). Current evaluation techniques to assess treatment response are lacking, given they are implemented several weeks after treatment completion and are solely based on anatomical changes in tumor size, forgoing other criteria such as functional or …
Design And Optimization Of Matrix Core Transformer For High Power Bidirectional Isolated Dc/Dc Converter, Zhe Zhao
Graduate Theses and Dissertations
Thanks to the advancement of semiconductor technology, the silicon carbide (SiC) devices with high voltage and power capability are developed and widely used in several industry applications, e.g., gird-connected photovoltaic (PV) system, data center power supply, and electrical vehicle (EV) charging station. After the concept of solid-state transformer (SST) was proposed as an important solution to the medium voltage (MV) power conversion systems, this bidirectional isolated DC/DC converter has attracted much attention in academia and industry. One of the main advantages of SST is to improve both the power density and efficiency of the power conversion system by replacing the …
An Automated Design Flow From Synchronous Rtl To Optimized Layout Using Commercial Eda Tools For Multi-Threshold Null Convention Logic Circuits, Cole Harrington Sherrill
An Automated Design Flow From Synchronous Rtl To Optimized Layout Using Commercial Eda Tools For Multi-Threshold Null Convention Logic Circuits, Cole Harrington Sherrill
Graduate Theses and Dissertations
This work presents the first automated design flow from synchronous RTL to highly optimized layout for Multi-Threshold NULL Convention Logic (MTNCL) circuits. The developed synthesis flow overcomes many of the drawbacks of existing attempts and leverages the advanced optimization features provided by modern synthesis tools. The remaining timing race conditions native to the MTNCL architecture have been identified and thoroughly explored. Two sets of novel timing constraints were devised: the first responds to these race conditions, yielding highly reliable MTNCL circuits; the second directly targets the critical paths within MTNCL circuits, allowing the designer to optimize the target circuit for …
Interaction-Sensitive Tree-Based Statistical Models, Xiaotong Sun
Interaction-Sensitive Tree-Based Statistical Models, Xiaotong Sun
Graduate Theses and Dissertations
This dissertation introduces a tree-based framework to improve the interpretability and modeling of interaction effects among variables, essential in fields like biostatistics, healthcare, science and engineering. Traditional regression methods often fail to clearly capture complex interactions, while tree-based approaches, despite their interpretability, face performance limitations and overfitting concerns. Our proposed interaction-sensitive tree-based method, designed for seamless integration, combines various statistical techniques tailored to different data types, leveraging ensemble learning methods to enhance accuracy and mitigate overfitting. We present methods for regression, survival analysis, and classification, validated with case studies and benchmarked against traditional models using metrics like BIC and R-squared. …
Learning To Accelerate Globally Optimal Solutions: Applications In The Ac Optimal Power Flow Problem, Muhammet Fatih Cengil
Learning To Accelerate Globally Optimal Solutions: Applications In The Ac Optimal Power Flow Problem, Muhammet Fatih Cengil
Graduate Theses and Dissertations
The Alternating Current Optimal Power Flow (AC-OPF) problem is a fundamental optimization challenge critical to ensuring the economical and reliable operation of power grids. While fast heuristic methods provide upper-bound solutions, assessing their quality requires lower bounds obtained from relaxations of the AC-OPF problem. This dissertation focuses on finding globally optimal solutions to the AC-OPF problem by enhancing the effectiveness and efficiency of Quadratic Convex (QC) relaxations. Leveraging machine learning techniques, we aim to achieve tighter relaxations faster and improve computational performance, enabling practical scalability for real-time applications.
In Chapter 2, we propose a machine learning-based method to accelerate the …
Wind Tunnel Investigation Of The Along-Wind Dispersion In Finite-Duration Neutrally Buoyant Gas Releases, Daniel Williams
Wind Tunnel Investigation Of The Along-Wind Dispersion In Finite-Duration Neutrally Buoyant Gas Releases, Daniel Williams
Graduate Theses and Dissertations
This thesis investigates the along-wind dispersion of hazardous gas releases within a turbulent boundary layer using controlled experiments in an ultra-low-speed wind tunnel, recognizing the limitations of numerical modeling and field tests. This study utilizes a neutrally buoyant gas mixture and dual Flame Ionization Detectors (FIDs) to capture representative, repeatable data on gas cloud behavior over finite durations. Ensemble averaging of 65 trials across varying release durations and downwind distances provided detailed insights into gas dispersion and the distinct time phases within finite-duration releases. Analysis revealed that along-wind dispersion coefficients depend on turbulence and vertical wind shear, with normalized coefficients …
Batch And Placement Size Effects On The Setting Time Of Bcsa Cement Concrete, Micaiah Rivers
Batch And Placement Size Effects On The Setting Time Of Bcsa Cement Concrete, Micaiah Rivers
Graduate Theses and Dissertations
Belitic calcium sulfoaluminate cement (BCSA) is an alternative to portland cement which offers numerous benefits due to its rapid-setting behavior and sustainability properties. BCSA cement concrete has many potential applications, particularly for structural and transportation infrastructure repair. Due to the rapid-setting properties of BCSA cement, a comprehensive understanding of the setting process is critical for efficient and effective use of this material. The primary objective of this research was to determine the effects of mixture size on the setting time and temperature behavior of BCSA cement concrete, and to investigate the relationship between initial set time and workability. Using a …
An Investigation Of The Effect Of Performance Engineered Mixture (Pem) Design On Durability And Air Void Matrix Of Concrete Pavements, Jacob Ortlieb
An Investigation Of The Effect Of Performance Engineered Mixture (Pem) Design On Durability And Air Void Matrix Of Concrete Pavements, Jacob Ortlieb
Graduate Theses and Dissertations
Performance Engineered Mixture (PEM) design is a novel method of creating concrete pavement that is economical achieving desirable performance properties such as durability, strength, and workability. Performance-based design is critical for concrete pavements, so the fresh concrete can be placed without issue and the hardened concrete can withstand deterioration and environmental damage such as freezing and thawing. To achieve economical concrete, PEM utilizes tools such as the tarantula curve for aggregate grading, and the Super Air Meter (SAM) test, providing information regarding the air void matrix while the concrete is fresh. To achieve these properties with less cement will lead …
Development Of An Innovative Rapidly Constructible Bridge, Swikar N. Pyakurel
Development Of An Innovative Rapidly Constructible Bridge, Swikar N. Pyakurel
Graduate Theses and Dissertations
Rapidly deployable temporary bridges are critical for military operations in hostile environments. The research focuses on conceptualizing bridge solutions for MLC 40 loading and 30 feet span that can be operational within hours, require minimal personnel and equipment, and are compact for logistics. An extensive literature review covered historic deployable structures, retractable stadium roofs, structures in aerospace, permanent deployable bridges, current military bridges, innovative deck solutions, lightweight structural materials, and compliant mechanisms. The study then investigated bridge superstructures made of lightweight Aluminum 6061-T6 alloy utilizing tensegrity and prefabricated aluminum extruded decks to meet the criteria. Two concepts, expandable scissor truss …
Impact Of Equipment Type On Measured Particle Size Of Civil Engineering Materials, Tanner Turben
Impact Of Equipment Type On Measured Particle Size Of Civil Engineering Materials, Tanner Turben
Graduate Theses and Dissertations
Particle size analysis (PSA) captures the size distribution of fine-grained or emulsified materials with particles generally smaller than 1000 microns. Asphalt emulsions and many other civil engineering materials do not leverage PSA for material specifications or acceptance despite the insight into material performance and quality gained through understanding the particle size. The objectives of this study are to compare PSA measurement principles by testing 13 civil engineering materials by laser diffraction, Coulter counter, and microscopy and to develop a draft standard procedure for asphalt emulsion PSA. Asphalt emulsions, cementitious materials, sands, clays, and biological samples were selected to represent a …
Identifying Waterway Traffic Flow Patterns Using Modified Clustering, Shihao Pang
Identifying Waterway Traffic Flow Patterns Using Modified Clustering, Shihao Pang
Graduate Theses and Dissertations
Efficient management of inland waterways is essential for the economic and operational efficiency of transportation networks. Characterization and prediction of waterway vessel traffic flow patterns by time of day are critical for optimizing planned disruptive events like maintenance activities. This study identifies and predicts inland waterway traffic flow patterns along the Lower Mississippi River (LMR) using a modified clustering approach. A five-year period of Automatic Identification System (AIS) data, which tracks vessel movements in real-time, is used for model development and evaluation. The model first segments the river into approximately one-mile-long traffic message channels (TMCs) to estimate vessel counts and …
Applying Uas Lidar For Developing Small Project Terrain Models, Ashraf Siddiqui
Applying Uas Lidar For Developing Small Project Terrain Models, Ashraf Siddiqui
Graduate Theses and Dissertations
Unmanned aerial systems (UAS) LiDAR was used to collect survey data for small-area projects, particularly bridge replacement projects. The project aimed to compare UAS LiDAR data with conventional surveying methods. For the project, five bridge sites were selected for UAS LiDAR and conventional survey data collection, which include Lincoln Bridge 1 (East), Lincoln Bridge 2 (West), Humnoke, Frenchman’s Bayou, and Mountain Home. Data for each site was collected during the 2021–2022 winter. A DJI M600 Pro and Phoenix LiDAR Systems AL3-16 LiDAR unit were used for the UAS LiDAR measurements. The conventional survey equipment used included a global navigation satellite …
Real-Time Barge Detection Using Traffic Cameras And Deep Learning On Inland Waterways, Geoffery Eyram Agorku
Real-Time Barge Detection Using Traffic Cameras And Deep Learning On Inland Waterways, Geoffery Eyram Agorku
Graduate Theses and Dissertations
Inland waterways are critical for freight movement, but limited means exist for monitoring their performance and usage by freight-carrying vessels, e.g., barges. While methods to track vessels, e.g., tug and tow boats, are publicly available through Automatic Identification Systems (AIS), ways to track freight tonnages and commodity flows carried on barges along these critical marine highways are non-existent, especially in real-time settings. This paper develops a method to detect barge traffic on inland waterways using existing traffic cameras with opportune viewing angles. Deep learning models, specifically, You Only Look Once (YOLO), Single Shot MultiBox Detector (SSD), and EfficientDet are employed. …
Exploring Telehealth Utilization Through Data Analytics, Statistical Analyses, And Machine Learning Techniques, Aysenur Betul Cengil
Exploring Telehealth Utilization Through Data Analytics, Statistical Analyses, And Machine Learning Techniques, Aysenur Betul Cengil
Graduate Theses and Dissertations
This dissertation investigates the utilization of telehealth services, initially focusing on the Arkansas healthcare system and then extending the analysis nationwide. It aims to understand the factors influencing telehealth adoption and its impact on healthcare delivery. After examining telehealth utilization in Arkansas from 2018 to 2022, the research utilizes a comprehensive dataset from Epic Cosmos, which includes a wide range of patient and visit data from multiple healthcare facilities across the United States from 2018 to 2023. This timeframe allows for a detailed analysis of telehealth trends before, during, and after the COVID-19 pandemic. In Chapter 2, we analyze key …
Synthesis Of Nanoparticles And Their Applications In Power Module Packaging And Organic Electronics, Xinsong Zhang
Synthesis Of Nanoparticles And Their Applications In Power Module Packaging And Organic Electronics, Xinsong Zhang
Graduate Theses and Dissertations
Nanoparticles can greatly change the properties of regular materials due to their special structures. In this research nanoparticles, such as silver nanowires, silver nanospheres and expanded graphite, are used in interconnection materials for power module packaging, and in conductive films for organic electronics. Silver nanowires synthesized by polyol synthesis, are used as fillers in micron silver paste. The electrical and mechanical properties of the sintered hybrid silver paste are investigated and compared with those of micron silver paste. The composites of silver nanospheres and expanded graphite are mixed with PEDOT:PSS solutions in 5 different weight ratio. The electrical and optical …
Development Of A High-Throughput Screening Platform To Profile Gene Delivery And Transcriptional Control In Macrophages, Alexis Ivy
Graduate Theses and Dissertations
Macrophages are an important cell type in the body responsible for orchestrating the inflammatory response and return to homeostasis. Macrophages are often implicated in a multitude of disease pathologies including delayed wound healing, excessive fibrosis, autoimmune disease, and immunosuppression within the tumor microenvironment. Although macrophages have been targeted for therapeutic applications, success in utilizing them has remained elusive due to their relative ease of phenotype switching between inflammatory and anti-inflammatory. The challenge that remains is developing clinically relevant delivery vehicles that can target macrophages without causing a phenotypic switch counter-productive to the desired response. This is especially important when targeting …
Investigating The Detection And Transport Of Low Molecular Weight Species To Better Understand Their Impact On Disease Pathology And Treatment, Haley Michelle Duncan
Investigating The Detection And Transport Of Low Molecular Weight Species To Better Understand Their Impact On Disease Pathology And Treatment, Haley Michelle Duncan
Graduate Theses and Dissertations
Due to the drastic differences in the projects involved, this dissertation will be split into two sections: Alzheimer’s disease and chronic kidney disease. Each chapter will contain an introduction, materials and methods section, results and discussion, conclusions, and works cited section. The Alzheimer’s disease chapter will also have a supplemental figures section containing the polyacrylamide gels that were silver stained and quantified via ImageJ. The presence of elevated levels of amyloid beta oligomeric species in the brain has been related to the pathology of Alzheimer’s disease. As these oligomeric species are transient in nature, their kinetics pose a challenge to …
Esd-Robust 4h-Sic Low-Voltage Cmos Technology Development For High Temperature, Hui Wang
Esd-Robust 4h-Sic Low-Voltage Cmos Technology Development For High Temperature, Hui Wang
Graduate Theses and Dissertations
This dissertation explores the development and optimization of electrostatic discharge (ESD)-robust, low-voltage CMOS technology using 4H-silicon carbide (SiC) tailored for high-temperature applications, addressing the critical need for reliable semiconductor devices in harsh environmental conditions. The advent of SiC as a semiconductor material offers significant advantages over traditional silicon (Si) in harsh environments, including higher thermal conductivity, greater electron mobility, and improved electrical characteristics at elevated temperatures. This research explores the integration of 4H-SiC into CMOS technology to enhance device reliability and performance in extreme conditions such as those found in aerospace, automotive, and energy sectors. The study begins with a …
Computational Alchemy: Pioneering Spintronic, Thermoelectric, And Optoelectronic Materials Design Through First-Principles Calculations And Machine Learning, Eesha Sanjay Andharia
Computational Alchemy: Pioneering Spintronic, Thermoelectric, And Optoelectronic Materials Design Through First-Principles Calculations And Machine Learning, Eesha Sanjay Andharia
Graduate Theses and Dissertations
Intelligent materials discovery and design plays a pivotal role in advancement of spintronics, optoelectronics and thermoelectric devices and technology. In this study, we investigate three types of materials using first principles calculations. First, the structural, electronic, and magnetic properties of CrTiCoZ (Z = Al, Si) equiatomic quaternary Heusler alloys were investigated. CrTiCoAl compound was found to exhibit a half metallic ferromagnetic structure and Curie temperature above room temperature, which makes it an ideal candidate for magnetic tunnel junction, the basic building block of Spintronic devices. Second, we use Green’s function to obtain the finite temperature phonons by including quartic anharmonicity …
Remodel-Fpga: Reconfigurable Memory-Centric Array Processor Architecture For Deep-Learning Acceleration On Fpga, Md Arafat Kabir
Remodel-Fpga: Reconfigurable Memory-Centric Array Processor Architecture For Deep-Learning Acceleration On Fpga, Md Arafat Kabir
Graduate Theses and Dissertations
Deep-Learning has become a dominant computing paradigm across a broad range of application domains. Different architectures of Deep-Networks like CNN, MLP, and RNN have emerged as the prominent machine-learning approaches for today’s application domains. These architectures are heavily data-dependent, requiring frequent access to memory. As a result, these applications suffer the most from the memory bottleneck of the von Neumann architectures. There is an imminent need for memory-centric architectures for deep-learning and big-data analytic applications that are memory intensive. Modern Field Programmable Gate Arrays (FPGAs) are ideal programmable substrates for creating customized Processor in/near Memory (PIM) accelerators. Modern FPGAs contain …
Ω-Shaped Rogowski Coil Current Sensor Optimization Design In Power Electronics Applications, Xia Du
Ω-Shaped Rogowski Coil Current Sensor Optimization Design In Power Electronics Applications, Xia Du
Graduate Theses and Dissertations
Accurate switching current measurement plays a pivotal role in characterization of power devices, overcurrent protection, and real-time control of system-level operations in power electronics applications. However, the ongoing revolution in power electronics, driven by the emergence of wide bandgap power devices operating at megahertz (MHz) switching frequencies, introduces challenges for current sensor design. The urgent issue now is the need to increase current sensor bandwidth significantly to adeptly capture the rapid switching speed current. Additionally, the trend towards high power density and compact power converters in various applications demands current sensors that are not only compact and nonintrusive but can …
Molecular Beam Epitaxy Of Gesn On Iii-V Substrates For Photonic Applications, Calbi Gunder
Molecular Beam Epitaxy Of Gesn On Iii-V Substrates For Photonic Applications, Calbi Gunder
Graduate Theses and Dissertations
This dissertation explores the advancement of germanium-tin (GeSn) as a tuneable narrow bandgap material, crucial for the development of high-efficiency photodetectors and laser devices in near- and mid-infrared technologies. We investigate the synthesis challenges, particularly the lattice mismatch between GeSn alloys and substrates, which significantly affects their crystalline and optical qualities. Through molecular beam epitaxy, we examine the growth of Ge and GeSn on GaAs (001) substrates, employing Ge/GaAs and Ge/AlAs buffer layers to investigate these challenges. Our findings, characterized by X-ray diffraction, atomic force microscopy, reflection high-energy electron diffraction, and photoluminescence, demonstrate the production of high-quality Ge layers, achieving …
Advancing Prediction And Decision Analytics Techniques To Improve Treatment Of Tuberculosis, Maryam Kheirandish Borujeni
Advancing Prediction And Decision Analytics Techniques To Improve Treatment Of Tuberculosis, Maryam Kheirandish Borujeni
Graduate Theses and Dissertations
Tuberculosis (TB) remains a global health challenge, significantly impacting morbidity and mortality rates worldwide. Despite advancements in diagnosis and treatment, TB continues to pose substantial challenges, particularly in low-resource settings. This dissertation aims to develop a robust treatment monitoring framework for TB patients to ensure personalized and effective treatment using demographic and clinical information. The current standard TB treatment framework, recommended by the World Health Organization (WHO), involves monitoring patients through laboratory tests such as smear and culture sputum tests at specific time points during treatment. These tests, however, are not fast and accurate enough to determine the severity of …
High-Power Power Conditioning Systems For Medium-Voltage Applications, Ahmed Rahouma Fares Rahouma
High-Power Power Conditioning Systems For Medium-Voltage Applications, Ahmed Rahouma Fares Rahouma
Graduate Theses and Dissertations
The purpose of this dissertation is to address the background, theoretical analyses, design methodologies, and evaluation techniques relevant to high-power power conditioning systems (PCSs) tailored for medium-voltage (MV) applications. Conventional PCSs, reliant on line-frequency transformers (LFTs), suffer from many problems including low power densities, inflexible designs, and scalability constraints. Employing multilevel converters (MLCs), particularly cascaded H-bridge topology, eliminates the need for these LFTs. A key focus lies in minimizing the number of cascaded building blocks by harnessing MV power switching modules. The dissertation makes two primary contributions: firstly, it offers a design methodology for MV-PCS, facilitating the selection of the …