Engineering Commons^™

Implementation Of The Downlink Communication System Of The Lmu Cubesat, Mohammed Alrabeeah

LMU/LLS Theses and Dissertations

In this thesis, we present the design and implementation of a CubeSat receiver system using the Universal Software Radio Peripheral (USRP) and GNU Radio. The goal of this project is to develop a low-cost and flexible ground station capable of receiving telemetry and payload data from CubeSats in real time. The CubeSat receiver operates in the UHF frequency range with a center frequency of 435 MHz and uses a software-defined radio (SDR) approach to provide wideband signal processing and demodulation capabilities. The satellite transceiver transmits an Ax.25 Transciever packet every 1 second using the Pumpkin CubeSat kit programmed in MPLab. …

Fast Full-Wave Electromagnetic Forward Solver Based On Deep Conditional Convolutional Autoencoders, Huan Huan Zhang, He Ming Yao, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

This letter proposes a novel deep learning (DL) based fast solver for the electromagnetic forward (EMF) process. This proposed fast full-wave solver for EMF process is designed based on the deep conditional convolutional autoencoder (DCCAE), consisting of a complex-valued deep convolutional encoder network and its corresponding complex-valued deep convolutional decoder network. The encoder network makes use of the input consisting of the incident electromagnetic (EM) wave and the contrast (permittivities) distribution of the target domain, while the corresponding decoder network predicts the total EM field illuminated by the input incident EM wave. The training of the proposed DCCAE solver for …

Computational Design Of Fiber-Optic Probes For Biosensing, Suwarna Karna

Electrical Engineering Theses

This thesis presents a study on the optical characteristics of hollow-core photonic crystal fibers (HC-PCFs) with a band gap cladding structure and their applications in optical fiber sensing. This 800B HC-PCF exhibited excellent optical properties and has a flexible structure, which makes them suitable for a wide range of industrial applications. Finite element simulations and structural optimization designs were conducted using the surface plasmon resonance (SPR) technique to determine the optimal performance parameters of the 800B HC-PCF. The fiber was further modified using the SPR technique to improve its practical detection capabilities. The performance of the modified fiber was observed …

Detecting Fast Frequency Events In Power System: Development And Comparison Of Two Methods, Hussain A. Alghamdi, Midrar Adham, Umar Farooq, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

In power systems, frequency deviation from nominal value can occur due to reasons such as loss of generation, loss of load, or major faults in the grid. Such frequency fluctuations can lead to serious subsequent outages and damages to both end-user and utility equipment. Therefore, a proper frequency deviation detection methodology must be in place to effectively identify frequency events in a timely manner. This manuscript provides a comparative analysis between two frequency deviation detection algorithms. One is based on signal processing and statistical analysis. The other is a regression-based algorithm. Both of these algorithms have multiple adjustable parameters, making …

Trust Model System For The Energy Grid Of Things Network Communications, Narmada Sonali Fernando, Zhongkai Zheng, John M. Acken, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

Network communication is crucial in the Energy Grid of Things (EGoT). Without a network connection, the energy grid becomes just a power grid where the energy resources are available to the customer uni-directionally. A mechanism to analyze and optimize the energy usage of the grid can only happen through a medium, a communications network, that enables information exchange between the grid participants and the service provider. Security implementers of EGoT network communication take extraordinary measures to ensure the safety of the energy grid, a critical infrastructure, as well as the safety and privacy of the grid participants. With the dynamic …

Approximate Computing Based Processing Of Mea Signals On Fpga, Mohammad Emad Hassan

Dissertations

The Microelectrode Array (MEA) is a collection of parallel electrodes that may measure the extracellular potential of nearby neurons. It is a crucial tool in neuroscience for researching the structure, operation, and behavior of neural networks. Using sophisticated signal processing techniques and architectural templates, the task of processing and evaluating the data streams obtained from MEAs is a computationally demanding one that needs time and parallel processing.

This thesis proposes enhancing the capability of MEA signal processing systems by using approximate computing-based algorithms. These algorithms can be implemented in systems that process parallel MEA channels using the Field Programmable Gate …

Physics-Based And Behavioral Models For Fuel Cells, Charles Chima Anyim

Theses and Dissertations

In recent times there has been renewed interest in fuel cells for electricity production, especially for transportation applications. Fuel cells are attractive because the electricity production process from chemical energy does not cause pollution, and no carbon emissions occur. In this work, we will focus on Proton Exchange Membrane (PEM) fuel cells that use hydrogen and oxygen to generate electricity, producing only electricity, heat and water. If hydrogen can be produced in a green, non-polluting way, fuel cells can truly be an environmentally benign energy source.

In this work, we will look at the modeling of a fuel cell system. …

Novel Structures And Thin Film Techniques For Reconfigurable Rf Technologies With Improved Signal Integrity, Jinqun Ge

Theses and Dissertations

Over the past several decades, wireless communications have been tremendously developed with multiple frequency bands, standards, and functions to provide more convenient communication services. Nowadays, commercial wireless devices, especially customer premises equipment, are required for smaller size, higher integration, and higher data rates to meet the ever-increasing demands of communications. The transceiver front ends inside these devices need to provide high-speed and high-quality communication services without a substantial increase in cost and size. Hence, the primary objective of this research is to develop a few miniaturized, multifunctional, and reconfigurable RF technologies and to provide several signal integrity and heat dissipation …

High-Performance Wide Bandgap Semiconductor Power Modules Enabled By Advanced Two-Phase Mini-Channel Cooling, Bo Tian

Theses and Dissertations

There is a widespread need for high performance wide bandgap power modules in both commercial and military applications. However, given the rapid advancements of wide bandgap power module technology, conventional cooling solutions have not kept up and do not provide the thermal management performance needed for high power density. Based on the two-phase cooling approach, two-phase microchannels operating at low fluid flow rates with low pressure drops have huge potential in enabling higher power density applications. Several studies have illustrated the potential great advantages of two-phase cooling compared to single-phase cooling in terms of maximum device temperature, spatial thermal distribution …

Quantized State Simulation Of Electrical Power Systems, Joseph Micah Hood

Theses and Dissertations

An alternative is proposed to the current state-of-the-art simulation methods for the transient simulation of electrical power systems. The proposed method combines the Latency Insertion Method (LIM), the Quantized Discrete Event Specification (QDEVS), and the Quantized State System (QSS) method of integration. Using LIM, the power system state equations are decoupled in a way that allows the formulation of the system into a QDEVS-compliant model, which can then be directly solved with various QSS integration techniques. This combination of methods is called the Quantized DEVS-LIM method, or simply, QDL. A key feature of QDL is the asynchronous updates of all …

Artificial Neural Network-Based Prediction Assessment Of Wire Electric Discharge Machining Parameters For Smart Manufacturing, Itagi Vijayakumar Manoj, Sannayellappa Narendranath, Peter Madindwa Mashinini, Hargovind Soni, Shanay Rab, Shadab Ahmad, Ahatsham Hayat

Department of Electrical and Computer Engineering: Faculty Publications

Artificial intelligence (AI), robotics, cybersecurity, the Industrial Internet of Things, and blockchain are some of the technologies and solutions that are combined to produce “smart manufacturing,” which is used to optimize manufacturing processes by creating and/or accepting data. In manufacturing, spark erosion technique such as wire electric discharge machining (WEDM) is a process that machines different hard-to-cut alloys. It is regarded as the solution for cutting intricate parts and materials that are resistant to conventional machining techniques or are required by design. In the present study, holes of different radii, i.e. 1, 3, and 5mm, have been cut on Nickelvac-HX. …

Unsupervised Bidirectional Mr To Ct Synthesis Based On Generative Adversarial Networks, Jiayuan Wang

Electronic Theses and Dissertations

Magnetic resonance (MR) and computer tomography (CT) images are two typical types of medical images that provide mutually-complementary information for accurate clinical diagnosis and treatment. However, obtaining both images may be limited due to some considerations such as cost, radiation dose, and modality missing. Recently, medical image synthesis has aroused gaining research interest to cope with this limitation. In this thesis, we proposed unsupervised bidirectional learning models based on generative adversarial networks (GANs) to synthesize medical images from unpaired data. The first model is dual contrast CycleGAN (DC-cycleGAN), where a dual contrast (DC) loss is introduced into the CycleGAN's discriminators …

A Review On Solid-State Li-S Battery: From The Conversion Mechanism Of Sulfur To Engineering Design, Huan-Huan Jia, Chen-Ji Hu, Yi-Xiao Zhang, Li-Wei Chen

Journal of Electrochemistry

Lithium-sulfur (Li-S) batteries attract sustained attention because of their ultrahigh theoretical energy density of 2567 Wh·kg^–1 and the actual value over 600 Wh·kg^–1. Solid-state Li-S batteries (SSLSBs) emerge in the recent two decades because of the enhanced safety when compared to the liquid system. As for the SSLSBs, except for the difference in the conversion mechanism induced by the cathode materials themselves, the physical-chemical property of solid electrolytes (SEs) also significantly affects their electrochemical behaviors. On account of various reported Li-S batteries, the advantages and disadvantages in performance and the failure mechanism are discussed in this review. …

Bimetallic Compound Catalysts With Multiple Active Centers For Accelerated Polysulfide Conversion In Li-S Batteries, Wu-Xing Hua, Jing-Yi Xia, Zhong-Hao Hu, Huan Li, Wei Lv, Quan-Hong Yang

Journal of Electrochemistry

Practical applications of lithium-sulfur (Li-S) batteries are hindered mainly by the low sulfur utilization and severe capacity fading derived from the polysulfide shuttling. Catalysis is an effective remedy to those problems by promoting the conversion of polysulfides to reduce their accumulation in the electrolyte, which needs the catalyst to have efficient adsorption ability to soluble polysulfides and high activity for their conversion. In this work, we have proposed a bimetallic compound of NiCo₂S₄ anchored onto sulfur-doped graphene (NCS@SG) to fabricate a catalytic interlayer for Li-S batteries. Compared to CoS, the NiCo₂S₄ demonstrated much higher …

Recent Research Progresses Of Solid-State Lithium-Sulfur Batteries, Yu Luo, Ru-Qin Ma, Zheng-Liang Gong, Yong Yang

Journal of Electrochemistry

All solid-state lithium-sulfur batteries (ASSLSBs) are considered to be one of the most promising next-generation energy storage systems, due to the promises of high energy density and safety. Although the use of solid-state electrolytes could effectively suppress the "shuttle effect" and self-discharge of the conventional liquid lithium-sulfur (Li-S) battery, the commercialization of ASSLSBs has been seriously hampered by the electrolyte degradation, electrode/electrolyte interfacial deterioration, electrochemo-mechanical failure, lithium dendrite growth and electrode pulverization, etc. This paper provides a comprehensive review of recent research progresses on the solid-state electrolytes, sulfur-containing composite cathodes, lithium metal and lithium alloy anodes, and electrode/electrolyte interfaces in …

Coni-Based Bimetal-Organic Framework Derived Carbon Composites Multifunctionally Modified Separators For Lithium-Sulfur Batteries, Yan-Jie Wang, Hong-Yu Cheng, Ji-Yue Hou, Wen-Hao Yang, Rong-Wei Huang, Zhi-Cong Ni, Zi-Yi Zhu, Ying Wang, Ke-Yi Wei, Yi-Yong Zhang, Xue Li

Journal of Electrochemistry

The commercial application of lithium-sulfur batteries (LSB) is still limited by the irreversible capacity fading caused by the shuttle of lithium polysulfides (LIPS). To address this issue, a bimetal (nickel, cobalt)-organic framework (MOF) derived carbon, (Ni, Co)/C, was prepared to modify the separator. The multifunctionally modified separator effectively captures LIPS, ensuring the stability and reversibility of sulfur fixation, while providing catalytic activity and improving ionic conductivity. The cobalt metal has a larger coordination number, more pore structure distribution, larger specific surface area, more surface C=O, and smaller particle size to achieve a large and rapid chemical sulfur fixation. The high …

Preface To The Special Issue On Lithium-Sulfur Batteries, Jia-Jia Chen, Ren-Jie Chen, Zhong Jin

Journal of Electrochemistry

No abstract provided.

Measuring Energy Deposition From A Laser Induced Plasma In Air Which Generates Broadband Microwave Radiation, Anna M. Janicek

Electrical and Computer Engineering ETDs

The absorbed energy from a short pulse laser produced plasma is proportional to the magnitude of the acoustic wave the plasma launches; however, methods to resolve absolute energy from the acoustic signal are still being developed. This is the first report of quantitatively estimating the energy deposited by a femtosecond laser-induced plasma using a shock wave approximation from acoustic measurements. To further understand energy deposition mechanisms, two diagnostics, a single microphone which measures the acoustic signal propagation and an array of microphones which measure the changing acoustic signal longitudinally along the plasma were developed and implemented to measure the energy …

Pvpbc: Privacy- And Verifiability-Preserving E-Voting Based On Permissioned Blockchain, Muntadher Sallal, Ruairí De Fréin, Ali Malik

Articles

Privacy and verifiability are crucial security requirements in e-voting systems and combining them is considered to be a challenge given that they seem to be contradictory. On one hand, privacy means that cast votes cannot be traced to the corresponding voters. On the other hand, linkability of voters and their votes is a requirement of verifiability which has the consequence that a voter is able to check their vote in the election result. These two contradictory features can be addressed by adopting privacy-preserving cryptographic primitives, which at the same time as achieving privacy, achieve verifiability. Many end-to-end schemes that support …

Deep Reinforcement Learning For Articulatory Synthesis In A Vowel-To-Vowel Imitation Task, Denis Shitov, Elena Pirogova, Tadeusz A. Wysocki, Margaret Lech

Department of Electrical and Computer Engineering: Faculty Publications

Articulatory synthesis is one of the approaches used for modeling human speech production. In this study, we propose a model-based algorithm for learning the policy to control the vocal tract of the articulatory synthesizer in a vowel-to-vowel imitation task. Our method does not require external training data, since the policy is learned through interactions with the vocal tract model. To improve the sample efficiency of the learning, we trained the model of speech production dynamics simultaneously with the policy. The policy was trained in a supervised way using predictions of the model of speech production dynamics. To stabilize the training, …

Development And Implementation Of Telemetry Devices To Identify And Characterize Sources Of Intraocular Pressure Variability In Rats, Christina M. Nicou

USF Tampa Graduate Theses and Dissertations

Eye health depends partially on intraocular pressure (IOP) as abnormal levels can lead to ocular tissue damage. Glaucoma is a neurodegenerative disease that affects nearly 80 million people worldwide [1]. It is associated with elevated IOP, which can lead to irreversible blindness. Relatively little is known about IOP dynamics and the physiological factors that affect it as IOP is typically monitored using tonometry. Tonometry is a common tool used by clinicians and researchers to measure IOP noninvasively. It provides a good estimate of IOP mean but not variance because data collection takes time. Readings can also be influenced by subject …

Implementing Commercial Inverse Design Tools For Compact, Phase-Encoded, Plasmonic Digital Logic Devices, Michael Efseaff, Kyle Wynne, Krishna Narayan, Mark C. Harrison

Engineering Faculty Articles and Research

Numerical simulations have become an essential design tool in the field of photonics, especially for nanophotonics. In particular, 3D finite-difference-time-domain (FDTD) simulations are popular for their powerful design capabilities. Increasingly, researchers are developing or using inverse design tools to improve device footprints and performance. These tools often make use of 3D FDTD simulations and the adjoint optimization method. We implement a commercial inverse design tool with these features for several plasmonic devices that push the boundaries of the tool. We design a logic gate with complex design requirements as well as a y-splitter and waveguide crossing. With minimal code changes, …

Utilizing Inverse Design To Create Plasmonic Waveguide Devices, Michael Efseaff, Kyle Wynne, Mark C. Harrison

Engineering Faculty Articles and Research

In modern communications networks, data is transmitted over long distances using optical fibers. At nodes in the network, the data is converted to an electrical signal to be processed, and then converted back into an optical signal to be sent over fiber optics. This process results in higher power consumption and adds to transmission time. However, by processing the data optically, we can begin to alleviate these issues and surpass systems which rely on electronics. One promising approach for this is plasmonic devices. Plasmonic waveguide devices have smaller footprints than silicon photonics for more compact photonic integrated circuits, although they …

Compressive Sensing Via Variational Bayesian Inference Under Two Widely Used Priors: Modeling, Comparison And Discussion, Mohammad Shekaramiz, Todd K. Moon

Electrical and Computer Engineering Faculty Publications

Compressive sensing is a sub-Nyquist sampling technique for efficient signal acquisition and reconstruction of sparse or compressible signals. In order to account for the sparsity of the underlying signal of interest, it is common to use sparsifying priors such as Bernoulli-Gaussian-inverse Gamma (BGiG) and Gaussian-inverse Gamma (GiG) priors on the compounds of the signal. With the introduction of variational Bayesian inference, the sparse Bayesian learning (SBL) methods for solving the inverse problem of compressive sensing have received significant interest as the SBL methods become more efficient in terms of execution time. In this paper, we consider the sparse signal recovery …

Statistical Analysis And Degradation Pathway Modeling Of Photovoltaic Minimodules With Varied Packaging Strategies, Sameera Nalin Venkat, Xuanji Yu, Jiqi Liu, Jakob Wegmueller, Jayvic Cristian Jimenez, Erika I. Barcelos, Hein Htet Aung, Roger H. French, Laura S. Bruckman

Faculty Scholarship

Degradation pathway models constructed using network structural equation modeling (netSEM) are used to study degradation modes and pathways active in photovoltaic (PV) system variants in exposure conditions of high humidity and temperature. This data-driven modeling technique enables the exploration of simultaneous pairwise and multiple regression relationships between variables in which several degradation modes are active in specific variants and exposure conditions. Durable and degrading variants are identified from the netSEM degradation mechanisms and pathways, along with potential ways to mitigate these pathways. A combination of domain knowledge and netSEM modeling shows that corrosion is the primary cause of the power …

Full-Scale Testing Of Power Transfer Roadways, Oscar Moncada

Purdue Road School

A dynamic wireless power transfer roadway refers to the integration of wireless power transfer technology into a new and existing road infrastructure to provide motive power, battery charging, or both to electric vehicles. The objective of this presentation is to evaluate the mechanical and thermal performance of the system when incorporated in both flexible and rigid pavement structures.

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Process Automation And Robotics Engineering For Industrial Processing Systems, Drake Stimpson

USF Tampa Graduate Theses and Dissertations

Automation in industrial systems applications has emerged as the fundamental solution for improving quality, production rate, and efficiency of a process. Much of the recent popularity surrounding the transition of processes from manually operated tasks to automated systems can be attributed to the concept of Industry 4.0, which outlines the fundamental guidelines for integrating cyber-physical systems into industrial processes. Due to rapid advancement of technology in robotics and automation as well as the increase in accessibility of resources to this technology, the capability to develop automated systems has become feasible for small-scale enterprise. This work presents a two-part initiative to …

Deep Reinforcement Learning Based Optimization Techniques For Energy And Socioeconomic Systems, Salman Sadiq Shuvo

USF Tampa Graduate Theses and Dissertations

Optimization, which refers to making the best or most out of a system, is critical for an organization's strategic planning. Optimization theories and techniques aim to find the optimal solution that maximizes/minimizes the values of an objective function within a set of constraints. Deep Reinforcement Learning (DRL) is a popular Machine Learning technique for optimization and resource allocation tasks. Unlike the supervised ML that trains on labeled data, DRL techniques require a simulated environment to capture the stochasticity of real-world complex systems. This uncertainty in future transitions makes the planning authorities doubt real-world implementation success. Furthermore, the DRL methods have …

Low-Power Redundant-Transition-Free Tspc Dual-Edge-Triggering Flip-Flop Using Single-Transistor-Clocked Buffer, Zisong Wang, Peiyi Zhao, Tom Springer, Congyi Zhu, Jaccob Mau, Andrew Wells, Yinshui Xia, Lingli Wang

Engineering Faculty Articles and Research

In the modern graphics processing unit (GPU)/artificial intelligence (AI) era, flip-flop (FF) has become one of the most power-hungry blocks in processors. To address this issue, a novel single-phase-clock dual-edge-triggering (DET) FF using a single-transistor-clocked (STC) buffer (STCB) is proposed. The STCB uses a single-clocked transistor in the data sampling path, which completely removes clock redundant transitions (RTs) and internal RTs that exist in other DET designs. Verified by post-layout simulations in 22 nm fully depleted silicon on insulator (FD-SOI) CMOS, when operating at 10% switching activity, the proposed STC-DET outperforms prior state-of-the-art low-power DET in power consumption by 14% …