Electrical and Computer Engineering Commons^™

Soft Electronics And Sensors For Wearable Healthcare Applications, Li-Wei Lo

McKelvey School of Engineering Graduate Student Theses & Dissertations

Wearable electronics are becoming increasingly essential to personalized medicine by collecting and analyzing massive amounts of biological signals from internal organs, muscles, and blood vessels. Conventional rigid electronics may lead to motion artifacts and errors in collected data due to the mismatches in mechanical properties between human skin. Instead, soft wearable electronics provide a better platform and interface that can form intimate contact and conformably adapt to human skin. In this respect, this thesis focuses on new materials formulation, fabrication, characterization of low-cost, high sensitivity and reliable sensors for wearable health monitoring applications.

More specifically, we have studied the silver …

Model-Based Deep Learning For Computational Imaging, Xiaojian Xu

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation addresses model-based deep learning for computational imaging. The motivation of our work is driven by the increasing interests in the combination of imaging model, which provides data-consistency guarantees to the observed measurements, and deep learning, which provides advanced prior modeling driven by data. Following this idea, we develop multiple algorithms by integrating the classical model-based optimization and modern deep learning to enable efficient and reliable imaging. We demonstrate the performance of our algorithms by validating their performance on various imaging applications and providing rigorous theoretical analysis.

The dissertation evaluates and extends three general frameworks, plug-and-play priors (PnP), regularized …

Analysis Of The Temperature Characteristics Of High-Speed Train Bearings Based On A Dynamics Model And Thermal Network Method, Baosen Wang, Yongqiang Liu, Bin Zhang, Wenqing Huai

Faculty Publications

High-speed trains often use temperature sensors to monitor the motion state of bearings. However, the temperature of bearings can be affected by factors such as weather and faults. Therefore, it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors. In this study, a dynamics model of the axle box bearing of high-speed trains is established. The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring, inner-ring, and rolling-element faults. Based on the model, a thermal network method is introduced to study the temperature …

Low-Cost And Biodegradable Thermoelectric Devices Based On Van Der Waals Semiconductors On Paper Substrates, Gulsum Ersu, Carmen Munuera, Federico J. Mompean, Daniel Vaquero, Jorge Quereda, Jooao Elias Rodrigues, Jose A. Alonso, Eduardo Flores, Jose R. Ares, Isbael J. Ferrer, Adbullah M. Al-Enizi, Ayman Nafady, Sruthi Kuriakose, Joshua O. Island, Andres Castellanos-Gomez

Physics & Astronomy Faculty Research

We present a method to fabricate handcrafted thermoelectric devices on standard office paper substrates. The devices are based on thin films of WS2, Te, and BP (P-type semiconductors) and TiS3 and TiS2 (N-type semiconductors), deposited by simply rubbing powder of these materials against paper. The thermoelectric properties of these semiconducting films revealed maximum Seebeck coefficients of (+1.32 ± 0.27) mV K−1 and (−0.82 ± 0.15) mV K−1 for WS2 and TiS3, respectively. Additionally, Peltier elements were fabricated by interconnecting the P- and N-type films with graphite electrodes. A thermopower value up to 6.11 mV K−1 was obtained when the Peltier …

Short-Term Electricity Price Point And Probabilistic Forecasts, Chenxu Zhang

Theses and Dissertations

Accurate short-term electricity price forecasts are essential to all electricity market participants. Generation companies adopt price forecasts to hedge generation shortage risks; load serving entities use price forecasts to purchase energy with low cost; and trading companies utilize price forecasts to arbitrage between markets.

Currently, researches on point forecast mainly focus on exploring periodic patterns of electricity price in time domain. However, frequency domain enables us to identify more information within price data to facilitate forecast. Besides, price spike forecast has not been fully studied in the existing works. Therefore, we propose a short-term electricity price forecast framework that analyzes …

Modeling Supercritical Fluids And Fabricating Electret Films To Address Dielectric Challenges In High-Power-Density Systems, Farhina Haque

Theses and Dissertations

Wide bandgap (WBG) devices and power electronic converters (PEC) that enable the dynamic control of energy and high-power density designs inevitably contain defects including sharp edges, triple points, and cavities, which result in local electric field enhancements. The intensified local electric stresses cause either immediate dielectric breakdown or partial discharge (PD) that erodes electrical insulators and accelerates device aging. With the goal of addressing these dielectric challenges emerging in power-dense applications, this dissertation focuses on 1) modeling the dielectric characteristics of supercritical fluids (SCFs), which is a new dielectric medium with high dielectric strength and high cooling capability; and 2) …

Development Of The Subwave Rov And Neural-Inertial Positioning System, Jason Farmer

Theses and Dissertations

This report documents the development of the Subwave, a remotely-operated underwater vehicle (ROV), and an artificial neural network based inertial positioning system. The Subwave uses the open-source ArduSub software framework, commercial-off-the-shelf hardware components, and several custom systems. It is designed as a platform for researching autonomous underwater vehicles (AUVs). The first step for an AUV is navigating waypoints, which requires the AUV to know its global position. Since global navigation satellite systems (GNSSs) are denied underwater, the available underwater positioning systems were surveyed and determined that all the available systems were too large and expensive for the Subwave. It was …

28 Ghz Patch Antenna Array With Reduced Mutual Coupling For 5g Communications Systems, Rahabu F. Mwang’Amba, Hashimu Uledi Iddi

Tanzania Journal of Engineering and Technology (TJET)

A 28 GHz patch antenna array with reduced mutual coupling for 5G communication systems is presented in this paper. Two elements antenna array was simulated with a periodic boundary to represent an infinity array. The antenna array is attached with a pair of the coupled directional coupler with a coupling value of -3.47 dB, and transmission lengths of 3.40 mm and 7.62 mm depending on the antenna array's magnitude and phase coefficient were designed and simulated. A reduced mutual coupling of -31.86 dB compared to -10.75 dB for an array without a decoupling network was observed. The wide scanning angle …

Evaluating Serverless Computing, Charitra Maharjan

LSU Master's Theses

Function as a Service (FaaS) is gaining admiration because of its way of deploying the computations to serverless backends in the different clouds. It transfers the complexity of provisioning and allocating the necessary resources for an application to the cloud providers. The cloud providers also give an illusion of always availability of resources to the users. Among the cloud providers, AWS serverless platform offers a new paradigm for developing cloud applications without worrying about the underlying hardware infrastructure. It manages not only the resource provisioning and scaling of an application but also provides an opportunity to reimagine the cloud infrastructure …

Nbt (No-Boundary Thinking): Needed To Attend To Ethical Implications Of Data And Ai, Joan Peckham, Andy Perkins, Tayo Obafemi-Ajayi, Xiuzhen Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In this era of Big Data and AI, expertise in multiple aspects of data, computing, and the domains of application is needed. This calls for teams of experts with different training and perspectives. Because data analysis can have serious ethical implications, it is important that these teams are well and deeply integrated. No-Boundary Thinking (NBT) teams can provide support for team formation and maintenance, thereby attending to the many dimensions of the ethics of data and analysis. In this NBT workshop session, we discuss the ethical concerns that arise from the use of data and AI, and the implications for …

Team Building Without Boundaries, Andy Perkins, Joan Peckham, Tayo Obafemi-Ajayi, Xiuzhen Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Team building can be challenging when participants are from the same discipline or sub-discipline, but needs special attention when participants use a different vocabulary and have different cultural views on what constitutes viable problems and solutions. Essential to No Boundary Thinking (NBT) teams is proper formulation of the problem to be solved, and a basic tenant is that the NBT team must come together with diverse perspectives to decide the problem before solutions can be considered. Given that participants come with different views on problem formulation and solution, it is important to consider a robust process for team formation and …

Ultraviolet Chiral Plasmonics, Tiago Ramos Leite Da Silva

LSU Doctoral Dissertations

The far- (λ < 250 nm) ultraviolet (UV) chiroptical response from protein secondary structures can aid in understanding protein interactions for drug discovery. Chiral metasurfaces have attracted attention to enhance the intrinsically weak biomolecular optical activity for improved structural biology characterization. However, due to materials and fabrication challenges, current metasurfaces mostly operate in the visible and near-infrared regimes with limited, if any, response in far-UV. The large spectral mismatch between metasurface and biomolecular resonances limits the chiral enhancement factor. In this work, we study aluminum planar metamaterials which display optical activity in the UV region. In the first part of this work, we experimentally and computationally investigate the resonant plasmonic-biomolecular interactions in the far-UV. To the best of our knowledge, our work is the first to experimentally explore these resonant interactions in the biologically relevant far-UV regime. We demonstrate experimentally and computationally enhanced chiral sensing of sub-10 nm amino acid films. We develop a full-wave computational model of a biomolecular film on an aluminum gammadion array using experimentally derived chiral parameters (κ) for L- and DTyrosine films. Our model shows that detectable enhancements in the circular dichroism (CD) and birefringence (CB) signals from small amounts of biomolecules are only possible when tight spectral overlap exists between the plasmonic and biomolecular chiroptical signals. We support this conclusion experimentally by fabricating aluminum gammadion arrays on fused silica substrates and sublimating ultrathin racemic, L- and D- Tyrosine films on the arrays. Complete Mueller matrix analysis of the resonant plasmonic-biomolecular system agrees with our computational results and demonstrates the importance of using far-UV active metasurfaces for enhancing natural optical activity. In the second part of this work, we study hybrid aluminum reflective metasurfaces, which leverage both local and propagating surface plasmons (PSP). These materials display strong bi-anisotropy with rich polarization conversion properties. We explore several geometries and verify how their symmetry properties affect their far-field response. Our observations provide an opportunity for researchers to improve the chiral response of plasmonic metasurfaces, especially in the challenging ultraviolet regime.

Zigbee Wireless Sensor Networks: Performance Study In An Apartment-Based Indoor Environment, Biswajit Kumar Dash, Jun Peng

Electrical and Computer Engineering Faculty Publications

Zigbee is a very popular technology for Internet of things (IoT) networks mainly because of its low power consumption and low-cost features. It shares the unlicensed 2.4 GHz Industrial, Scientific, and Medical (ISM) radio band with other wireless networks such as Wi-Fi. Usually, Zigbee and Wi-Fi networks coexist in indoor environments for their respective applications. Hence, the coexistence introduces interference for both types of networks lowering the performance of the networks, but Zigbee suffers more significant performance losses because of its lower transmission power than Wi-Fi. Since the number of IoT devices is increasing at an unprecedented rate due to …

A New Implementation Of Federated Learning For Privacy And Security Enhancement, Xiang Ma, Haijian Sun, Rose Qingyang Hu, Yi Qian

Department of Electrical and Computer Engineering: Faculty Publications

Motivated by the ever-increasing concerns on personal data privacy and the rapidly growing data volume at local clients, federated learning (FL) has emerged as a new machine learning setting. An FL system is comprised of a central parameter server and multiple local clients. It keeps data at local clients and learns a centralized model by sharing the model parameters learned locally. No local data needs to be shared, and privacy can be well protected. Nevertheless, since it is the model instead of the raw data that is shared, the system can be exposed to the poisoning model attacks launched by …

Golightly : A Gpu Implementation Of The Finite-Difference Time-Domain Method, S. David Lively

Electrical Engineering Theses and Dissertations

Traditionally, optical circuit design is tested and validated using software which implement numerical modeling techniques such as Beam Propagation, Finite Element Analysis and the Finite-Difference Time-Domain (FDTD) method. FDTD simulations require significant computational power. Existing installations may distribute the computational requirements across large clusters of high-powered servers. This approach entails significant expense in terms of hardware, staffing and software support which may be prohibitive for some research facilities and private-sector engineering firms. The application of modern programmable GPUs to problems in scientific visualization and computation has facilitated faster development cycles for a variety of industry segments including large dataset visualization, …

Raman Thermometry Of Graphene Based Thermal Materials, Pengcheng Xu

Electrical Engineering Theses and Dissertations

With the growing demand for high performance computing, we are pushing for higher performance integrated circuits at an ever faster rate. Recent advances in semiconductor production technology sees transistors with a 5 nm process devices being produced for consumer use. This enabled engineers to pack tens of billions of transistors in a package no larger than a fingernail. However, that brings up a problem that we have been long battling against. How can we get rid of the heat produced by these billions of transistors. The current electronic performance is bottle-necked by the ability of the package taking heat away …

Advances In Power System Operation And Optimization, You Lin

Electrical Engineering Theses and Dissertations

The modern power system has witnessed an increasing penetration of distributed energy resources and modern loads with variable frequency drives. The increasing complexity brings great challenges to modern power system operations. Significant efforts have been made to develop more accurate power system operation and optimization methods. The tradeoff between computation and the model structure makes the problem nontrivial to solve and analyze. Enabled by the wide deployment of PMUs and advanced machine learning algorithms, we improve the conventional power system operation and optimization techniques by improving the accuracy of power system measurements, implementing new power system modeling structures, and performing …

Charger Robotic Air Hockey-Modified Air Hockey Table Featuring Automated Play Against A Human Opponent, Robert Geren

Honors Capstone Projects and Theses

No abstract provided.

Optofluidic Droplet Lasers Enabled By Fluorescence Resonance Energy Transfer, Fariba Kenarangi

Electrical Engineering Dissertations - Archive

ABSTRACT: Over the past decade, optofluidic lasers have gained much popularity owing to their unique optical and mechanical properties. Optofluidic lasers are flexible, reconfigurable, easy to fabricate and their emission spectrum can be dynamically tuned. One type of these lasers with high Q-factors, is optofluidic droplet laser, which is a miniaturized ring resonator consists of liquid gain medium and optical microcavity made of two immiscible liquid phases. As light couples into the cavity, the whispering gallery mode will be guided around the concaved closed loop surface and it will be constantly reflected owing to total internal reflection. Due to its …

Ultra-Compact Hybrid Silicon: Chalcogenide Waveguide Temperature Sensor, Bahareh Badamchi, Wei-Che Hsu, Al-Amin Ahmed Simon, Zong Yin Chi, Jacob Manzi, Maria Mitkova, Alan X. Wang, Harish Subbaraman

Electrical and Computer Engineering Faculty Publications and Presentations

We demonstrate a real-time, reusable, and reversible integrated optical sensor for temperature monitoring within harsh environments. The sensor architecture combines the phase change property of chalcogenide glasses (ChG) with the high-density integration advantages of high index silicon waveguides. To demonstrate sensor feasibility, ChG composition Ge₄₀S₆₀, which is characterized by a sharp phase transition from amorphous to crystalline phase around 415 °C, is deposited over a 50 µm section of a single mode optical waveguide. The phase transition changes the behavior of Ge₄₀S₆₀ from a low loss to high loss material, thus significantly …

Enhanced Supervised Descent Learning Technique For Electromagnetic Inverse Scattering Problems By The Deep Convolutional Neural Networks, He Ming Yao, Rui Guo, Maokun Li, Lijun Jiang, Michael Kwok Po Ng

Electrical and Computer Engineering Faculty Research & Creative Works

This work proposes a novel deep learning (DL) framework to solve the electromagnetic inverse scattering (EMIS) problems. The proposed framework integrates the complex-valued deep convolutional neural network (DConvNet) into the supervised descent method (SDM) to realize both off-line training and on-line 'imaging' prediction for EMIS. The offline training consists of two parts: 1) DConvNet training: the training dataset is created, and the proposed DConvNet is trained to realize the EM forward process and 2) SDM training: the trained DConvNet is integrated into the SDM framework, and the average descent directions between the initial prediction and the true label of SDM …

Huber Kalman Filter For Wi-Fi Based Vehicle Driver's Respiration Detection, Yang Yang, Yunlong Luo, Alex Qi, Ge Shi, Miao Miao, Jun Fan, Jianhua Ma, Yihong Qi

Electrical and Computer Engineering Faculty Research & Creative Works

The use of breath detection in vehicles can reduce the number of vehicular accidents caused by drivers in poor physical condition. Prior studies of contactless respiration detection mainly targeted a static person. However, there are emerging applications to sense a driver, with emphasis on contactless methods. For example, being able to detect a driver's respiration while driving by using a vehicular Wi-Fi system can significantly enhance driving safety. The sensing system can be mounted on the back of the driver's seat, and it can sense the tiny chest displacement of the driver via Wi-Fi signals. The body displacement and car …

Towards On-Chip Integrated Sensors: Photonic Crystal Optical Sensors And Lasers, Zhonghe Liu

Electrical Engineering Dissertations - Archive

Supervising Professor: Weidong Zhou The field of compact integrated optical platform has developed into a new era in the past two decades. On one hand, the semiconductor optoelectronic devices are becoming smaller and cheaper thanks to the development of complementary metal-oxide semiconductor (CMOS) fabrication technologies; on the other hand, the applications of optoelectronics have been deeply coupled to other fields to realize more complicated implementations. Photonic crystal slab (PCS) structure has been playing an increasingly important role in these optical devices, active or passive, by enabling a variety of light-matter interaction mechanisms. The objective of this dissertation is to investigate …

Data-Driven Distributed Modeling, Operation, And Control Of Electric Power Distribution Systems, Hasala Dharmawardena

All Dissertations

The power distribution system is disorderly in design and implementation, chaotic in operation, large in scale, and complex in every way possible. Therefore, modeling, operating, and controlling the distribution system is incredibly challenging. It is required to find solutions to the multitude of challenges facing the distribution grid to transition towards a just and sustainable energy future for our society. The key to addressing distribution system challenges lies in unlocking the full potential of the distribution grid. The work in this dissertation is focused on finding methods to operate the distribution system in a reliable, cost-effective, and just manner.

In …

System Identification Of Linear And Non-Linear Dynamical Systems Using Semi-Definite Programming Via Penalized Parabolic Relaxation Method, Adnan Nasir

Electrical Engineering Dissertations - Archive

This document is prepared to highlight the difference between two very important fields in the realm of Convex Optimization, Machine Learning, Artificial Intelligence and many such sprouting advance fields currently impacting the whole world. The main aim of the recent SDP algorithms is to relax the NP-Hard Convex optimization problems and transform them into amenable jobs without strong theoretical guarantees, but these algorithms tends to approximate the practical in demand applications in many of the aforementioned fields. Moreover, The lack of theoretical guarantee makes the SDP relaxation in-exact and unoptimizable in finite duration. The actual world applications most of the …

Embedding A Grid Of Load Cells Into A Dining Table For Automatic Monitoring And Detection Of Eating Events, Mohammad Mayyan

All Dissertations

This dissertation describes a “smart dining table” that can detect and measure consumption events. This work is motivated by the growing problem of obesity, which is a global problem and an epidemic in the United States and Europe. Chapter 1 gives a background on the economic burden of obesity and its comorbidities. For the assessment of obesity, we briefly describe the classic dietary assessment tools and discuss their drawback and the necessity of using more objective, accurate, low-cost, and in-situ automatic dietary assessment tools. We explain in short various technologies used for automatic dietary assessment such as acoustic-, motion-, or …

Hierarchical And Distributed Architecture For Large-Scale Residential Demand Response Management, Pramod Herath Mudiyanselage

All Dissertations

The implementation of smart grid brings several challenges to the power system. The ‘prosumer’ concept, proposed by the smart grid, allows small-scale ‘nano-grids’ to buy or sell electric power at their own discretion. One major problem in integrating prosumers is that they tend to follow the same pattern of generation and consumption, which is un-optimal for grid operations. One tool to optimize grid operations is demand response (DR). DR attempts to optimize by altering the power consumption patterns. DR is an integrated tool of the smart grid. FERC Order No. 2222 caters for distributed energy resources, including demand response resources, …

Towards A Low-Cost Solution For Gait Analysis Using Millimeter Wave Sensor And Machine Learning, Mubarak A. Alanazi, Abdullah K. Alhazmi, Osama Alsattam, Kara Gnau, Meghan Brown, Shannon Thiel, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Human Activity Recognition (HAR) that includes gait analysis may be useful for various rehabilitation and telemonitoring applications. Current gait analysis methods, such as wearables or cameras, have privacy and operational constraints, especially when used with older adults. Millimeter-Wave (MMW) radar is a promising solution for gait applications because of its low-cost, better privacy, and resilience to ambient light and climate conditions. This paper presents a novel human gait analysis method that combines the micro-Doppler spectrogram and skeletal pose estimation using MMW radar for HAR. In our approach, we used the Texas Instruments IWR6843ISK-ODS MMW radar to obtain the micro-Doppler spectrogram …

Glaciernet2: A Hybrid Multi-Model Learning Architecture For Alpine Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Michael P. Bishop, Jeffrey S. Kargel, Theus Aspiras

Electrical and Computer Engineering Faculty Publications

In recent decades, climate change has significantly affected glacier dynamics, resulting in mass loss and an increased risk of glacier-related hazards including supraglacial and proglacial lake development, as well as catastrophic outburst flooding. Rapidly changing conditions dictate the need for continuous and detailed ob-servations and analysis of climate-glacier dynamics. Thematic and quantitative information regarding glacier geometry is fundamental for understanding climate forcing and the sensitivity of glaciers to climate change, however, accurately mapping debris-cover glaciers (DCGs) is notoriously difficult based upon the use of spectral information and conventional machine-learning techniques. The objective of this research is to improve upon an …

Materials Design For Energy Applications Using Ab- Initio Calculations, Hind Hemaidee Alqurashi

Graduate Theses and Dissertations

The structural, dynamical, electronic, and thermoelectric properties of rock-salt and wurtzite Cd1-xZnxO alloys, VTiRhZ (Al, Ga, In, Si, Ge, Sn) and ZrTiRhZ (Ge, Sn) quaternary Heusler alloys (QHAs) were investigated using density functional theory (DFT) and semi-classical Boltzmann transport theory. From these calculations, the alloys were identified as potential materials for future thermoelectric applications. Furthermore, the magnetic and spin-polarization properties of these QHAs were investigated. The total magnetic moments were found to be integer values for all QHAs. In addition, all studied QHAs except VTiRhAl possess a half-metallic behavior with a 100% spin-polarization. The half-metallic ferromagnetic behavior makes them promising …