Physical Sciences and Mathematics Commons^™

Trajectory Analysis For Driving Safety Quantification, Michael I. Chang

UNLV Theses, Dissertations, Professional Papers, and Capstones

In order to evaluate the efficacy of the skid recovery exercise in the Driver’s Edge teenage driving program, a process is established to determine the trajectories of vehicles from recorded videos, compare them in terms of similarity through dynamic time warping (DTW), and then analyze the similarity measurements to assess whether the program has a significant effect on driving ability by repeated measures analysis of variance (rANOVA). The video is analyzed by Harris corner detection and Lucas-Kanade optical flow method to ascertain the vehicle trajectories. A homography is then estimated to translate coordinates from video into real-world. The instructor and …

Measurements Of Magnetic Field Penetration Of Materials For Superconducting Radiofrequency Cavities, Iresha Harshani Senevirathne

Physics Theses & Dissertations

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently high purity niobium is the material of choice for SRF cavities which have been optimized to operate near their theoretical field limits. This brings about the need for significant R&D efforts to develop next generation superconducting materials which could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under high RF magnetic field without penetration of quantized …

Cobalt/Carbon Composites As Sulfur Hosts For High-Performance Lithium-Sulfur Batteries, Yun-Rui Yang, Huan-Huan Dong, Zhi-Qiang Hao, Xiang-Xi He, Zhuo Yang, Lin Li, Shu-Lei Chou

Journal of Electrochemistry

Lithium-sulfur (Li-S) battery is one of the promising energy storage devices because of its high energy density. However, the sulfur cathode suffers from sluggish electrochemical reaction kinetics, slow charge transfer, large volume expansion and severe shuttle effect of lithium polysulfides inevitably resulting in low reversible capacity, poor rate performance and short cycle life, limiting its practical applications. Herein, the recent progress of cobalt/carbon composites, including cobalt nanoparticles and cobalt single atoms, as the sulfur host materials in Li-S batteries is overviewed. In general, cobalt plays the role of electrocatalyst, which inhibits the shuttle effect of lithium polysulfides, accelerates the electrochemical …

Ultraviolet-Initiated In-Situ Cross-Linking Of Multifunctional Binder Backbones Enables Robust Lithium-Sulfur Batteries, Sha Li, Xiao Zhan, Gu-Lian Wang, Hui-Qun Wang, Wei-Ming Xiong, Li Zhang

Journal of Electrochemistry

Lithium-sulfur (Li-S) batteries show attractive prospects owing to their high theoretical energy density, but their commercialization still faces such challenges as lithium polysulfides shuttling, severe volume change and considerable polarization. These stubborn issues place higher demands on each component in the battery, such as the development of multifunctional binders with superior mechanical properties. Herein, ethoxylated trimethylolpropane triacrylate was firstly introduced into sulfur cathodes, and in-situ cross-linked by ultraviolet (UV) curing combined with traditional polyvinylidene difluoride binder (i.e., forming a binary binder, denoted as c-ETPTA/PVDF) to construct high-loading and durable Li-S batteries. The covalently cross-linked ETPTA framework not …

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

Journal of Electrochemistry

No abstract provided.

Recent Advances Of Functional Electrolyte Additives For Lithium-Sulfur Batteries, Xiu-Qing Zhang, Shuai Tang, Yong-Zhu Fu

Journal of Electrochemistry

Lithium-sulfur (Li-S) batteries have become one of the most promising next-generation battery systems due to their high energy density and low cost. However, the application of Li-S batteries still faces critical challenges, such as the low conductivities of S and Li₂S, shuttle effect of polysulfides and dendrite growth of Li, etc. The optimization of the electrolyte can ameliorate the electrolyte|electrode interphase, conveniently regulating the parasitic reaction and improving the performance of the resultant batteries. The functional additives in electrolytes provide chances to tune the interphase and even the redox mechanism to improve the performance of the batteries. In …

Metals And Alloys As Catalytic Hosts Of Sulfur Cathode For Lithium-Sulfur Batteries, Zhen-Yu Wang, Xue-Ping Gao

Journal of Electrochemistry

Lithium-sulfur batteries are recognized as one of the most promising next-generation energy storage devices, owing to the high theoretical energy density of 2600 Wh·kg^–1. However, their application has been seriously hindered by the sluggish electrochemical reaction kinetics of elemental sulfur and discharged products (Li₂S₂/Li₂S), and the notorious “shuttle effect” of soluble intermediate lithium polysulfide species, leading to poor cycle stability, low sulfur utilization and inferior coulombic efficiency. Introducing catalytic hosts into sulfur cathode is an efficient path to propel the conversion of sulfur-contained species, thus preventing the dissolution and loss of active-sulfur …

Gpu Utilization: Predictive Sarimax Time Series Analysis, Dorothy Dorie Parry

Modeling, Simulation and Visualization Student Capstone Conference

This work explores collecting performance metrics and leveraging the output for prediction on a memory-intensive parallel image classification algorithm - Inception v3 (or "Inception3"). Experimental results were collected by nvidia-smi on a computational node DGX-1, equipped with eight Tesla V100 Graphic Processing Units (GPUs). Time series analysis was performed on the GPU utilization data taken, for multiple runs, of Inception3’s image classification algorithm (see Figure 1). The time series model applied was Seasonal Autoregressive Integrated Moving Average Exogenous (SARIMAX).

Automatic Generation Of Virtual Work Guide For Complex Procedures: A Case, Shan Liu, Yuzhong Shen

Modeling, Simulation and Visualization Student Capstone Conference

Practical work guides for complex procedures are significant and highly affect the efficiency and accuracy of on-site users. This paper presents a technique to generate virtual work guides automatically for complex procedures. Firstly, the procedure information is extracted from the electronic manual in PDF format. And then, the extracted procedure steps are mapped to the virtual model parts in preparation for animation between adjacent steps. Next, smooth animations of the procedure are generated based on a 3D natural cubic spline curve to improve the spatial ability of the work guide. In addition, each step's annotation is automatically adjusted to improve …

Counterventions: A Reparative Reflection On Interventionist Hci, Rua Mae Williams, Louanne E. Boyd, Juan E. Gilbert

Engineering Faculty Articles and Research

Research in HCI applied to clinical interventions relies on normative assumptions about which bodies and minds are healthy, valuable, and desirable. To disrupt this normalizing drive in HCI, we define a “counterventional approach” to intervention technology design informed by critical scholarship and community perspectives. This approach is meant to unsettle normative assumptions of intervention as urgent, necessary, and curative. We begin with a historical overview of intervention in HCI and its critics. Then, through reparative readings of past HCI projects in autism intervention, we illustrate the emergent principles of a counterventional approach and how it may manifest research outcomes that …

Investigating The Use Of Recurrent Neural Networks In Modeling Guitar Distortion Effects, Caleb Koch, Scott Hawley, Andrew Fyfe

Belmont University Research Symposium (BURS)

Guitar players have been modifying their guitar tone with audio effects ever since the mid-20th century. Traditionally, these effects have been achieved by passing a guitar signal through a series of electronic circuits which modify the signal to produce the desired audio effect. With advances in computer technology, audio “plugins” have been created to produce audio effects digitally through programming algorithms. More recently, machine learning researchers have been exploring the use of neural networks to replicate and produce audio effects initially created by analog and digital effects units. Recurrent Neural Networks have proven to be exceptional at modeling audio effects …

Para Cima Y Pa’ Abajo: Building Bridges Between Hci Research In Latin America And In The Global North, Pedro Reynolds-Cuéllar, Marisol Wong-Villacres, Karla A. Badillo-Urquiola, Mayra Donaji Barrera-Machuca, Franceli L. Cibrian, Marianela Ciolfi Felice, Carolina Fuentes, Laura Sanely Gaytán-Lugo, Vivian Genaro Motti, Monica Perusquía-Hernández, Oscar A. Lemus

Engineering Faculty Articles and Research

The Human-computer Interaction (HCI) community has the opportunity to foster the integration of research practices across the Global South and North to begin overcoming colonial relationships. In this paper, we focus on the case of Latin America (LATAM), where initiatives to increase the representation of HCI practitioners lack a consolidated understanding of the practices they employ, the factors that influence them, and the challenges that practitioners face. To address this knowledge gap, we employ a mixed-methods approach, comprising a survey (66 respondents) and in-depth interviews (19 interviewees). Our analyses characterize a set of research perspectives on how HCI is practiced …

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 …

Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …

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. …

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.

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 …

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 …

Remote Medical Diagnosis Via Infrared Thermography And Augmented Reality, Frederick M. Selkey

USF Tampa Graduate Theses and Dissertations

Fast, accurate, and non-invasive diagnostic techniques are required by the medical industry to increase the success of medical treatments and enhance the quality of patient care. Medical IRT has been demonstrated reasonably effective at diagnosing and monitoring several physiological conditions. Diversities in the human body, physical and psychological condition, measurement equipment, and environment all influence the sensitive readings obtained by passive IR measurement devices. New standards for medical IRT and fever screening have been demonstrated effective, but there is limited adherence to the guidelines [36]. Absolute temperature readings require regular calibration checks and can easily be thrown off by noise. …

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 …

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 …

The Electromagnetic Bayonet: Development Of A Scientific Computing Method For Aperture Antenna Optimization, Michael P. Ingold

Theses and Dissertations

The quiet zone of a radar range is the region over which a transmitted EM field approximates a uniform plane wave to within some finite error tolerance. Any target to be measured must physically fit within this quiet zone to prevent excess measurement error. Compact radar ranges offer significant operational advantages for performing RCS measurements but their quiet zone sizes are constrained by space limitations. In this work, a scientific computing approach is used to investigate whether equivalent-current transmitters can be designed that generate larger quiet zones than a conventional version at short range. A time-domain near-field solver, JefimenkoModels, was …

Validation Of Bottom-Up Gnss Radio Occultation Method To Measure D- And E-Region Electron Density, Dylan J. Shaver

Theses and Dissertations

An in-depth validation of a new bottom-up approach using GNSS Radio Occultation (GNSS-RO) data to generate electron density profiles in the D- and E-region ionosphere. This comparison was completed using daytime ionosonde profiles when sporadic-E (E_s) was not present, and corresponding FIRI profiles. The average GNSS-RO profile is a few kilometers higher in altitude than the ionosonde profiles at the minimum frequency, f min. When the ionosonde profiles are shifted so that the altitudes match at f min, they are in good agreement up to the E-region peak altitude, hmE. Below f min, the …

Design And Modeling Of A Pvdf-Trfe Flexible Wind Energy Harvester, Berkay Kullukçu, Levent Beker

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the simulation, experimentation, and design considerations of a Poly(vinylidene fluoride co-trifluoroethylene)/ Polyethylene Terephthalate (PVDF-TrFe / PET), laser-cut, flexible piezoelectric energy harvester. It is possible to obtain energy from the environment around autonomous sensor systems, which can then be used to power various equipment. This article investigates the actuation means of ambient vibration, which is a good candidate for using piezoelectric energy harvester (PEH) devices. The output voltage characteristics were analyzed in a wind test apparatus. Finite element modeling (FEM) was done for von Mises stress and modal analysis. Resonance frequency sweeps, quality factors, and damping ratios of …

An Exploratory Study On The Effect Of Applying Various Artificial Neural Networks To The Classification Of Lower Limb Injury, Rachel Yun, May Salama, Lamiaa Elrefaei

Turkish Journal of Electrical Engineering and Computer Sciences

This paper explores the application of a deep neural network (DNN) framework to human gait analysis for injury classification. The paper aims to identify whether a subject is healthy or has an injury of the ankle, knee, hip, or heel solely based on ground reaction force plate measurements. We consider how three DNNs-the multi-layer perceptron (MLP), fully convolutional network (FCN), and residual network (ResNet)-can be applied to gait analysis when the number of trainable network parameters far exceeds the number of training samples, and benchmark their performance in this context against that of shallow neural networks. The DNN architectures outperformed …

3d Point Cloud Classification With Acgan-3d And Vacwgan-Gp, Onur Ergün, Yusuf Sahi̇lli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Machine learning and deep learning techniques are widely used to make sense of 3D point cloud data which became ubiquitous and important due to the recent advances in 3D scanning technologies and other sensors. In this work, we propose two networks to predict the class of the input 3D point cloud: 3D Auxiliary Classifier Generative Adversarial Network (ACGAN-3D) and Versatile Auxiliary Conditional Wasserstein Generative Adversarial Network with Gradient Penalty (VACWGAN-GP). Unlike other classifiers, we are able to enlarge the limited data set with the data produced by generative models. We consequently aim to increase the success of the model by …

Study Of Helical Antenna Endowing Short Wire Length And Compact Structure For High-Frequency Operations And Its Exclusive Manufacturing Process, Meli̇h Aslan, Kaan Şik, İzzet Güzelkara, İbrahi̇m Tuna Özdür, Veli̇ Tayfun Kiliç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a study of a helical antenna resonating at high-frequency (HF) band with a very compact structure is reported. The designed antenna's S11 parameter magnitude change with frequency was calculated for different geometrical parameters. For each case, first, only a single parameter was changed. Then for a fair comparison, multiple parameters were changed simultaneously while the total wire length was set to be constant. Also, shifts in resonance frequencies and variations in -10 dB bandwidths were investigated. Our results show that resonance behaviour changes distinctively with the geometrical parameters and it allows shortening of the antenna wire length. …

Solving Turkish Math Word Problems By Sequence-To-Sequence Encoder-Decoder Models, Esi̇n Gedi̇k, Tunga Güngör

Turkish Journal of Electrical Engineering and Computer Sciences

Solving math word problems (MWP) is a challenging task due to the semantic gap between natural language texts and mathematical equations. The main purpose of the task is to take a written math problem as input and produce a proper equation as output for solving that problem. This paper describes a sequence-to-sequence (seq2seq) neural model for automatically solving Turkish MWPs based on their semantic meanings in the text. It comprises a bidirectional encoder to comprehend the semantics of the problem by encoding the input sequence and a decoder with attention to extract the equation by tracking the semantic meanings of …