Electrical and Computer Engineering Commons^™

Frequency Domain Diffuse Optics Spectroscopies For Quantitative Measurement Of Tissue Optical Properties, Sadhu Moka

USF Tampa Graduate Theses and Dissertations

Tissue oxygen saturation, blood flow and blood volume are physiological bio-markers of tissue health. Diffuse Optical Spectroscopy(DOS) and Diffuse Correlation Spectroscopy (DCS) are two complementary approaches to measure tissue oxygen saturation and blood flow respectively. Quantitative Diffuse Optical Spectroscopy (DOS) uses multi-spectral intensities of near-infrared light that have been modulated at RF frequencies to estimate static tissue optical properties and hence concentrations of oxygenated and de-oxygenated hemoglobin. Diffuse Correlation Spectroscopy estimates tissue dynamics - i.e., blood flow, by measuring temporal intensity auto-correlation function of backscattered light diffusing through the tissue. Conventionally, DCS instruments use coherent light sources with constant intensity. …

Reducing Instrumentation Barriers Of Diffuse Correlation Spectroscopy For Low-Cost Deep Tissue Blood Flow Monitoring, Arindam Biswas

USF Tampa Graduate Theses and Dissertations

Cerebral blood flow (CBF) is a good indicator of brain health as blood carries necessary nutrients, oxygen, and metabolic byproducts. Quantitative blood flow information can be used in several clinical and therapeutic applications such as stroke detection, measuring autoregulation, evaluating brain injury, or determining neuronal activity. Over the past few decades, light-based deep tissue hemodynamic detection modalities have become popular for non-invasive CBF measurements. In particular, noninvasive Diffuse Correlation Spectroscopy (DCS), has become a tool of choice for research and clinical applications due to its depth sensitivity (>1 cm), portability, validity against other technologies such as Magnetic Resonance Imaging …

Information Dissemination And Perpetual Network, Harshit Srivastava

USF Tampa Graduate Theses and Dissertations

Social networks have attracted increasing attention from both physical and social scientists. Social networks are essential elements in societies, serving as channels for exchanging various benefits, such as innovation, information, and social support. Moreover, research in social networks helps explain macro-level social phenomena, such as social polarization and social contagion. An understanding of social networks has significant implications, such as improving social welfare and political participation. Modeling social network formation has typically employed game theory or agent-based modeling. These studies typically propose simple and tractable micro-level rules for link formation mechanisms and show that these rules have implications for known …

Efficient Interface Enabled By Nano-Hydroxyapatite@Porous Carbon For Lithium-Sulfur Batteries, Jia-Yu Wang, Xue-Feng Tong, Qi-Fan Peng, Yue-Peng Guan, Wei-Kun Wang, An-Bang Wang, Nai-Qiang Liu, Ya-Qin Huang

Journal of Electrochemistry

The dissolution and “shuttle effect” of lithium polysulfides (LiPSs) hinder the application of lithium-sulfur (Li-S) batteries. To solve those problems, inspired by natural materials, a nano-hydroxyapatite@porous carbon derived from chicken cartilage (nano-HA@CCPC) was fabricated by employing a simple pre-carbonization and carbonization method, and applied in Li-S batteries. The nano-HA@CCPC would provide a reactive interface that allows efficient LiPSs reduction. With a strong affinity for LiPSs and an excellent electronic conductive path for converting LiPSs, the shuttle effect of LiPSs was confined and the redox kinetics of LiPSs was substantially enhanced. Li-S batteries employing nano-HA@CCPC-modified separators exhibited long cycle life and …

Advances And Atomistic Insights Of Electrolytes For Lithium-Ion Batteries And Beyond, Tingzheng Hou, Xiang Chen, Lu Jiang, Cheng Tang

Journal of Electrochemistry

Electrolytes and the associated electrode-electrolyte interfaces are crucial for the development and application of high-capacity energy storage systems. Specifically, a variety of electrolyte properties, ranging from mechanical (compressibility, viscosity), thermal (heat conductivity and capacity), to chemical (solubility, activity, reactivity), transport, and electrochemical (interfacial and interphasial), are correlated to the performance of the resultant full energy storage device. In order to facilitate the operation of novel electrode materials, extensive experimental efforts have been devoted to improving these electrolyte properties by tuning the physical design and/or chemical composition. Meanwhile, the recent development of theoretical modeling methods is providing atomistic understandings of the …

Insight Into The Effects Of Cation Disorder And Surface Chemical Residues On The Initial Coulombic Efficiency Of Layered Oxide Cathode, Jin-Li Liu, Han-Feng Wu, Zhi-Bei Liu, Ying-Qiang Wu, Li Wang, Feng-Li Bei, Xiang-Ming He

Journal of Electrochemistry

Lithium layered oxide LiNi_0.6Co_0.2Mn_0.2O₂ (NCM622) is one of the most promising cathode materials in high-energy lithium-ion batteries for electric vehicles. However, one drawback for NCM622 is that its initial coulombic efficiency (ICE) is only about 87%, which is at least 6% lower than that of LiCoO₂ or LiFePO₄. In this work, we investigated the effects of surface chemical residues (e.g., LiOH and Li₂CO₃) and Li/Ni cation disorder resulted during the sintering on the ICE. We found that the ICE of the as-prepared samples could be boosted …

Which Factor Dominates Battery Performance: Metal Ion Solvation Structure-Derived Interfacial Behavior Or Solid Electrolyte Interphase Layer?, Hao-Ran Cheng, Zheng Ma, Ying-Jun Guo, Chun-Sheng Sun, Qian Li, Jun Ming

Journal of Electrochemistry

Solid-electrolyte interphase (SEI) layer formed on the electrode by electrolyte decomposition has been considered to be one of the most important factors affecting the battery performance. We discover that the metal ion solvation structure can also influence the performance, particularly, it can elucidate many phenomena that the SEI cannot. In this review, we summarize the importance of the metal ion solvation structure and the derived metal ion de-solvation behaviors, by which we can build an interfacial model to show the relationship between the interfacial behavior and electrode performance, and then apply to different electrode and battery systems. We emphasize the …

Modeling, Control, And Operation Of A Grid-Tied Solar Photovoltaic Inverter In Unbalanced Conditions, Abdulhakim Alsaif

USF Tampa Graduate Theses and Dissertations

With the increasing penetration of inverter-based resources (IBRs) integrated into powersystem grids as well as in microgrids (MGs), operational challenges and stability issues have been identified by the industry. In the last few years, solar Photovoltaic (PV) farm plants were allowed to be disconnected (isolated from the grid) during abnormal operation conditions to not only avoid stability issues but also to protect any damage to the solar PV inverter from such overcurrent or overvoltage. Most solar PV inverters operate in a conventional grid-following (GFL) control, where unbalanced operation becomes a critical issue. This control scheme regulates only positive sequence currents. …

Dynamic Study Of Inverter-Based Resources In Weak Grids, Zhengyu Wang

USF Tampa Graduate Theses and Dissertations

As the main technology behind renewable energy resources, such as solar PV and wind turbines, inverter-based generation penetration is increasing aggressively. Besides the congestion concerns when interconnecting a large-scale inverter-based resource (IBR) into the power grid, stability issues are commonly existing. The stability events occur more frequently when the resources are in remote area because the transmission line is long and grid strength is weak. One of the most representative and widely observed phenomena of IBR instability is low-frequency oscillation. And this dissertation focuses on investigating the low-frequency oscillations of IBR in weak grids.

The main objectives of the investigation …

Cocm: Co-Occurrence-Based Consistency Matching In Domain-Adaptive Segmentation, Siyu Zhu, Yingjie Tian, Fenfen Zhou, Kunlong Bai, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

This paper focuses on domain adaptation in a semantic segmentation task. Traditional methods regard the source domain and the target domain as a whole, and the image matching is determined by random seeds, leading to a low degree of consistency matching between domains and interfering with the reduction in the domain gap. Therefore, we designed a two-step, three-level cascaded domain consistency matching strategy—co-occurrence-based consistency matching (COCM)—in which the two steps are: Step 1, in which we design a matching strategy from the perspective of category existence and filter the sub-image set with the highest degree of matching from the image …

Passive Cooling Analysis Of An Electronic Chipset Using Nanoparticles And Metal-Foam Composite Pcm: An Experimental Study, Faisal Hassan, Abid Hussain, Furqan Jamil, Adeel Arshad, Hafiz Muhammad Ali

Research outputs 2022 to 2026

Thermal management of electronic components is critical for long-term reliability and continuous operation, as the over-heating of electronic equipment leads to decrement in performance. The novelty of the current experimental study is to investigate the passive cooling of electronic equipment, by using nano-enriched phase change material (NEPCM) with copper foam having porosity of 97 %. The phase change material of PT-58 was used with graphene nanoplatelets (GNPs) and magnesium oxide (MgO) nanoparticles (NPs), having concentrations of 0.01 wt. % and 0.02 wt. %. Three power levels of 8 W, 16 W, and 24 W, with corresponding heating inputs of 0.77 …

A Patient-Specific Algorithm For Lung Segmentation In Chest Radiographs, Manawaduge Supun De Silva, Barath Narayanan Narayanan, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Lung segmentation plays an important role in computer-aided detection and diagnosis using chest radiographs (CRs). Currently, the U-Net and DeepLabv3+ convolutional neural network architectures are widely used to perform CR lung segmentation. To boost performance, ensemble methods are often used, whereby probability map outputs from several networks operating on the same input image are averaged. However, not all networks perform adequately for any specific patient image, even if the average network performance is good. To address this, we present a novel multi-network ensemble method that employs a selector network. The selector network evaluates the segmentation outputs from several networks; on …

Computer Engineering Education, Marilyn Wolf

School of Computing: Conference and Workshop Papers

Computer engineering is a rapidly evolving discipline. How should we teach it to our students?

This virtual roundtable on computer engineering education was conducted in summer 2022 over a combination of email and virtual meetings. The panel considered what topics are of importance to the computer engineering curriculum, what distinguishes computer engineering from related disciplines, and how computer engineering concepts should be taught.

Transition-Metal Ions In Β-Ga2O3 Crystals: Identification Of Ni Acceptors, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway, J. Jesenovec, B. L. Dutton, M. D. Mccluskey, Larry E. Halliburton

Faculty Publications

Excerpt: Transition-metal ions (Ni, Cu, and Zn) in β-Ga₂O₃ crystals form deep acceptor levels in the lower half of the bandgap. In the present study, we characterize the Ni acceptors in a Czochralski-grown crystal and find that their (0/−) level is approximately 1.40 eV above the maximum of the valence band.

Digitally Predicting Protein Localization And Manipulating Protein Activity In Fluorescence Images Using 4d Reslicing Gan, Yang Jiao, Lingkun Gu, Yingtao Jiang, Mo Weng, Mei Yang

Electrical & Computer Engineering Faculty Research

While multi-channel fluorescence microscopy is a vital imaging method in biological studies, the number of channels that can be imaged simultaneously is limited by technical and hardware limitations such as emission spectra cross-talk. One solution is using deep neural networks to model the localization relationship between two proteins so that the localization of one protein can be digitally predicted. Furthermore, the input and predicted localization implicitly reflect the modeled relationship. Accordingly, observing the response of the prediction via manipulating input localization could provide an informative way to analyze the modeled relationships between the input and the predicted proteins.

Material Characterization And Comparison Of Sol-Gel Deposited And Rf Magnetron Deposited Lead Zirconate Titanate Thin Films, Katherine Lynne Miles

Mechanical Engineering ETDs

Lead zirconate titanate (PZT) has been a material of interest for sensor, actuator, and transducer applications in microelectromechanical systems (MEMS). This is due to their favorable piezoelectric, pyroelectric and ferroelectric properties. While various methods are available to deposit PZT thin films, radio frequency (RF) magnetron sputtering was selected to provide high quality PZT films with the added capability of batch processing. These sputter deposited PZT films were characterized to determine their internal film stress, Young’s modulus, composition, and structure. After characterization, the sputtered PZT samples were poled using corona poling and direct poling methods. As a means of comparison, commercially …

Rdlnn-Based Image Forgery Detection And Forged Region Detection Using Mot, Akram Hatem Saber, Mohd Ayyub Khan, Basim Galeb Mejbel

Karbala International Journal of Modern Science

Image forgery detection TEMPhas become an emerging research area due to the increasing number of forged images circulating on the internet and other social media, which leads to legal and social issues. Image forgery detection includes the classification of an image as forged or authentic and as well as localizing the forgery wifin the image. In this paper, we propose a Regression Deep Learning Neural Network (RDLNN) based image forgery detection followed by Modified Otsu Thresholding (MOT) algorithm to detect the forged region. The proposed model comprises five steps that are preprocessing, image decomposition, feature extraction, classification and block matching. …

Submillimeter-Wave Cornea Phantom Sensing Over An Extended Depth Of Field With An Axicon-Generated Bessel Beam, Mariangela Baggio, Aleksi Tamminen, Joel Lamberg, Roman Grigorev, Samu-Ville Pälli, Juha Ala-Laurinaho, Irina Nefedova, Jean-Louis Bourges, Sophie X. Deng, Elliott R. Brown, Vincent P. Wallace, Zachary D. Taylor

Electrical Engineering Faculty Publications

The feasibility of a 220 - 330 GHz zero order axicon generated Bessel beam for corneal water content was explored. Simulation and experimental data from the 25-degree cone angle hyperbolic-axicon lens illuminating metallic spherical targets demonstrate a monotonically decreasing, band integrated, backscatter intensity for increasing radius of curvature from 7 - 11 mm, when lens reflector and optical axis are aligned. Further, for radii >= 9.5 mm, maximum signal was obtained with a 1 mm transverse displacement between lens and reflector optical axes arising from spatial correlation between main lobe and out of phase side lobes. Thickness and permittivity parameter …

Development Of An Automated Platform For Sensing And Differentiating Vapor-Phase Btex Constituents, Jonathan Samuelson

USF Tampa Graduate Theses and Dissertations

Light aromatic hydrocarbons are an inevitable byproduct of fossil fuel extraction, refinement, distribution, and use. The four lightest and most prevalent of these are benzene, toluene, ethylbenzene, and xylene, which are known collectively as BTEX. In spite of their chemical similarity these species have markedly different effects on human health and substantially different concentrations are permitted by OSHA in workplaces and by the EPA in ambient air and groundwater. Real-time detection, identification, and quantification of these species is therefore of great importance wherever they see industrial use.This work represents the continuation and advancement of a line of research in which …

Long-Distance Propagation Of 162 Mhz Shipping Information Links Associated With Sporadic E, Alex T. Chartier, Thomas R. Hanley, Daniel J. Emmons

Faculty Publications

This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.

Deepdemod: Bpsk Demodulation Using Deep Learning Over Software-Defined Radio, Arhum Ahmad, Satyam Agarwal, Sam Darshi, Sumit Chakravarty

Open Access Publishing Fund Collection

In wireless communication, signal demodulation under non-ideal conditions is one of the important research topic. In this paper, a novel non-coherent binary phase shift keying demodulator based on deep neural network, namely DeepDeMod, is proposed. The proposed scheme makes use of neural network to decode the symbols from the received sampled signal. The proposed scheme is developed to demodulate signal under fading channel with additive white Gaussian noise along with hardware imperfections, such as phase and frequency offset. The time varying nature of hardware imperfections and channel poses a additional challenge in signal demodulation. In order to address this issue, …

Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors, Travis D. Lecompte

LSU Doctoral Dissertations

Modern computers can experience a variety of transient errors due to the surrounding environment, known as soft faults. Although the frequency of these faults is low enough to not be noticeable on personal computers, they become a considerable concern during large-scale distributed computations or systems in more vulnerable environments like satellites. These faults occur as a bit flip of some value in a register, operation, or memory during execution. They surface as either program crashes, hangs, or silent data corruption (SDC), each of which can waste time, money, and resources. Hardware methods, such as shielding or error correcting memory (ECM), …

Spam Detection Using Machine Learning And Deep Learning, Olubodunde Agboola

LSU Doctoral Dissertations

Text messages are essential these days; however, spam texts have contributed negatively to the success of this communication mode. The compromised authenticity of such messages has given rise to several security breaches. Using spam messages, malicious links have been sent to either harm the system or obtain information detrimental to the user. Spam SMS messages as well as emails have been used as media for attacks such as masquerading and smishing ( a phishing attack through text messaging), and this has threatened both the user and service providers. Therefore, given the waves of attacks, the need to identify and remove …

Sers Platform For Single Fiber Endoscopic Probes, Debsmita Biswas

LSU Doctoral Dissertations

Molecular detection techniques have huge potential in clinical environments. In addition to many other molecular detection techniques, endoscopic Raman spectroscopy has great ability in terms of minimal invasiveness and real-time spectra acquisition. However, Raman Effect is low in sensitivity, limiting the application. Surface-Enhanced Raman Scattering (SERS), addresses this limitation. SERS brings rough nano-metallic surfaces in contact with specimen molecules which enormously enhances Raman signals. This provides Raman spectroscopy with immense capabilities for diverse fields of applications.

Generally, in clinical probe applications, the spectrometer is brought near the target molecules for detection. Typically, optical fibers are used to couple spectrometers to …

A Field-Deployable Quartz Crystal Microbalance System For Gas Detection, Jongyoon Park

LSU Doctoral Dissertations

Quartz crystal microbalance (QCM) has been widely studied as a mass sensing technique in laboratory environments and has shown a wide range of industrial applications such as food quality control, various forms of chemical detection, and biomolecular recognition under gas phase as well as liquid phase media. The construction of multi-sensor arrays combined with special sensor coatings enables multiple analyte detections and discrimination of multi-analyte along with statistical analysis. Despite the great sensing capabilities of QCM and growing interest in practical applications beyond the laboratory setup, most QCM studies are still performed in laboratory settings with benchtop QCM instruments. Therefore, …

Redefining Research In Nanotechnology Simulations: A New Approach To Data Caching And Analysis, Darin Tsai, Alan Zhang, Aloysius Rebeiro

The Journal of Purdue Undergraduate Research

No abstract provided.

Ethics In Engineering Education: Is Abet Enough?, Alyssa Delouise

The Journal of Purdue Undergraduate Research

No abstract provided.

Hypoxic Incubation Chamber, Simone Lisette Helfrich, Makenzie Nicole Jones

Biomedical Engineering: Graduate Reports and Projects

This paper describes the design, manufacturing, and testing of a novel controllable hypoxic incubator with fully functional oxygen gas control and temperature control in a humid environment. On the current market, a majority of the few hypoxic incubators use pre-mixed gas that does not offer precise control over gas concentration. The objective for this project was to create a chamber that allows the user to set the O2 concentration to varying set points of % O2 while maintaining the chamber at a constant body temperature, CO2 level, humidity, and sterility. To start the project, multiple concepts were developed for the …

Hypoxic Incubation Chamber, Simone Lisette Helfrich, Makenzie Nicole Jones

Master's Theses

This paper describes the design, manufacturing, and testing of a novel controllable hypoxic incubator with fully functional oxygen gas control and temperature control in a humid environment. On the current market, a majority of the few hypoxic incubators use pre-mixed gas that does not offer precise control over gas concentration. The objective for this project was to create a chamber that allows the user to set the O2 concentration to varying set points of % O2 while maintaining the chamber at a constant body temperature, CO2 level, humidity, and sterility. To start the project, multiple concepts were developed for the …

Solid State Lighting/Led Lighting, With Reliability Analysis And Smart Sustainable Energy Solutions, Anjan N. Padmasali Dr.

Technical Collection

Reliability analysis of LED based lighting solutions used in general applications. Daily use LED luminaire performance analysis at different accelerated conditions and prediction of performance for any other conditions. System and component level reliability study and analysis. Develop LED based solutions for any specific application requirements. Currently working on developing measurements, data analysis and solutions in lines with providing smart and sustainable solution applicable to lighting and also energy usage optimizations in any system.

1. https://ieeexplore.ieee.org/document/9537294
2. https://journals.sagepub.com/doi/10.1177/1477153520976936
3. https://ieeexplore.ieee.org/document/9559924
4. https://ieeexplore.ieee.org/document/9108554
5. https://ieeexplore.ieee.org/document/8930628