Electrical and Computer Engineering Commons^™

Lgformer: Informer-Based Personalized Modeling For Blood Glucose Prediction, Xue Yuewei, Shaopeng Guan, Jia Wanhai

Turkish Journal of Electrical Engineering and Computer Sciences

Effective diabetes management relies on precise prediction of blood glucose levels to minimize complications. However, the patterns and fluctuations in blood glucose vary significantly among patients, posing a challenge for existing prediction methods. Many current approaches fail to accommodate these individual differences, leading to less reliable predictions. In response to this challenge, we present LGformer, a novel prediction model based on the Informer architecture, designed to enhance both flexibility and accuracy. LGformer improves upon Informer by integrating LSTM and GRU layers into its probSparse Self-attention mechanism, allowing for personalized processing of blood glucose data tailored to each patient's unique profile. …

Uniform 3d Scattering Point Model For Simulating The Dynamic Radar Echo From Wind Farm, Bo Tang, Zhendong Zhu, Zhiyu Shang, Huanghai Xie, Feng Wang, Jiaxu Chen

Turkish Journal of Electrical Engineering and Computer Sciences

The calculation scale of simulating wind farm dynamic radar echo is gradually growing with the increasing scale of wind farms, which can hardly meet the requirements of real-time radar echo simulation. Considering that the method of surface element division can greatly influence the result of simulation, uniform surface element division is applied to accelerate the traditional simulation algorithm based on the refined 3D scattering point model and enhance the main characteristics of the radar echo. The solution time of dynamic radar echoes from 1-8 wind turbines is calculated to test the average speed that the uniform 3D scattering point model …

An Improved Conditional Integrator Sliding Mode Controller Based On Swarm Intelligence For A Magnetic Levitation System, Abdelkader Kerraci, Mohamed Fayçal Khelfi, Zoubir Ahmed-Foitih

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes an enhanced Conditional Integrator Sliding Mode Controller using Particle Swarm Optimization (CISMCPSO) for a magnetic levitation system (MLS). The main advantage of this controller is its robustness to uncertainties and disturbances, which also avoids chattering and ensures zero static steady-state error. The main idea of CISMCPSO is to activate its integral action only when the sliding surface reaches the boundary layer while it is reduced to zero or close to zero elsewhere, which avoids destroying the transient response caused by the conventional integral sliding-mode controller. A particle swarm optimization algorithm schedules the conditional integral term parameter of …

Developing Linguistic Patterns To Mitigate Inherent Human Bias In Offensive Language Detection, Toygar Tanyel, Besher Alkurdi, Serkan Ayvaz

Turkish Journal of Electrical Engineering and Computer Sciences

With the proliferation of social media, there has been a sharp increase in offensive content, particularly targeting vulnerable groups, exacerbating social problems such as hatred, racism, and sexism. Detecting offensive language use is crucial to prevent offensive language from being widely shared on social media. However, the accurate detection of irony, implication, and various forms of hate speech on social media remains a challenge. Natural language-based deep learning models require extensive training with large, comprehensive, and labeled datasets. Unfortunately, manually creating such datasets is both costly and error-prone. Additionally, the presence of human-bias in offensive language datasets is a major …

Motivating Sustainability Through The State Of Biologically Inspired Design, Bryan Watson

Sustainability Conference

There are multiple arguements for sustainability, but one that resonates with environmentalists and the public alike is the need for preservation to all us to discovery natural solutions to our problems. Common examples often given include medical discoveries, unique mechanisms, and new materials. This presentation focuses on two ideas to motivate sustainability. First, what is the current state of biologically inspired design? Is there more to learn from nature? To answer these questions, recent research is presented which examined 660 Biologically Inspired Design samples from three data sources: Google Scholar, Google News, and the Asknature.org “Innovations” database. The data were …

Model-Based Navigation And Control Of Multirotor Uavs: A Machine Learning Approach, Serhat Sönmez

Electronic Theses and Dissertations

In recent decades, unmanned systems, particularly Unmanned Aerial Vehicles (UAVs), have seen significant advancement and unprecedented growth in military, civilian and public domain applications. Scientists have focused on enhancing UAV navigation and control through cutting-edge technologies and support tools. UAVs find applications in many fields, except military, such as agriculture, infrastructure inspection, wildlife monitoring, search and rescue, emergency response, border protection, to name but a few relevant civilian applications. Given the faster-than-exponential increase of available computational power, learning-based algorithms have emerged as a prominent tool for (real-time) multirotor UAV navigation and control. This dissertation centers around the fusion of conventional …

It's Not As Bad As You Think: Detecting Ai-Generated Voices, Yong Qin Xu

Undergraduate Research Symposium Lightning Talks

Advances in machine learning have opened up the world to a brand new frontier of fraudulent phone calls which the average person may not be in any way prepared for. From imitations of a loved one's voice to lifelike mimicry of human callers, telephone scams may become harder than ever to anticipate or prevent now that criminals have the help of AI on their side. This is why in my research paper, I aim to analyze and compare two existing methods of detecting the authenticity of human voice recordings in order to demonstrate and explain currently available technology that's capable …

Dynamic And Harmonic Studies Of Inverter Based Resources, Rabi Shankar Kar

USF Tampa Graduate Theses and Dissertations

As the inverter-based generation is the primary technology driving renewable energy sources such as solar photovoltaic and wind turbines, its penetration is increasing rapidly. Due to the high penetration, there are multiple situations of IBR misoperation due to any type of grid contingency. This dissertation focuses on exploring the response of IBR towards grid contingency.

The primary objectives of the study are as follows: 1. Conducting a harmonic analysis of inverter-based resources when subjected to balanced and unbalanced grid conditions, 2. The use of a circuit simplification method to streamline the analysis process and study the dynamic response of IBR …

Smartphone Haptics Can Uncover Differences In Touch Interactions Between Asd And Neurotypicals, Ivonne Monarca, Franceli L. Cibrian, Isabel López Hurtado, Monica Tentori

Engineering Faculty Articles and Research

Utilizing touch interactions from smartphones for gathering data and identifying digital markers for screening and monitoring neurological disorders, such as Autism Spectrum Disorder (ASD), is an emerging area of research. Smartphones provide multiple benefits for this kind of study, including unobtrusive data collection via built-in sensors, integrated haptic feedback systems, and the capability to create specialized applications. Acknowledging the significant yet understudied presence of tactile processing differences in individuals with ASD, we designed and developed Feel and Touch, a mobile game that leverages the haptic capabilities of smartphones. This game provides vibrotactile feedback in response to touch interactions and collects …

How Does Original And Disruptive Innovation Lead Modern Industrial System: Insights From Revolutionary Frontier Of Next-Generation Chip Manufacturing Technology, Jiang Yu, Yue Guo, Shiguang Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Original and disruptive innovation is the foundation for tackling key technological challenges and nurturing the development of new forms of productive forces. The breakthrough of FinFET (Fin field-effect transistor) technology, a frontier manufacturing process for chips, represents a typical example of original and disruptive innovation. This breakthrough extended Moore’s Law, catalyzed the transition of semiconductor manufacturing from 2D to 3D structures, and significantly advanced the global high-tech industry, positioning it at the core of international technological competition. This study reviews the breakthrough journey of FinFET technology, specifically focusing on its development stages from “scientific discovery—formation of new technological pathways—systematization of …

Strategies To Alleviate Flickering: Bayesian And Smoothing Methods For Deep Learning Classification In Video, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce A. Cox, Trevor Bihl

Faculty Publications

Excerpt: Increasing reliance on autonomous systems requires confidence in the accuracies produced from computer vision classification algorithms. Computer vision (CV) for video classification provides phenomenal abilities, but it often suffers from “flickering” of results. Flickering occurs when the CV algorithm switches between declared classes over successive frames. Such behavior causes a loss of trust and confidence in their operations.

Soc-Based Control System Performance Analysis For Trapped-Ion Quantum Computing, Tiamike Dudley

Electrical and Computer Engineering ETDs

Scatter-gather dynamic-memory-access (SG-DMA) is utilized in applications that require high bandwidth and low latency data transfers between memory and peripherals, where data blocks, described using buffer descriptors (BDs), are distributed throughout the memory system. The data transfer organization and requirements of a Trapped-Ion Quantum Computer (TIQC) possess characteristics similar to those targeted by SG-DMA. In particular, the ion qubits in a TIQC are manipulated by applying control sequences consisting primarily of modulated laser pulses. These optical pulses are defined by parameters that are (re)configured by the electrical control system. Variations in the operating environment and equipment make it necessary to …

Automated Solutions For Hydroponic Plant Growth, Sydney Mcclure, Adam Lachguar

Sustainability Conference

Within the past year, Project H.O.M.E. has been focusing on the design and development of a semi-automatic hydroponic system specifically for sustaining plant life in Martian-like conditions. Given the significance of extended space-based travel, where the duration of human life in space is a crucial factor, growing food becomes imperative. This project has integrated electrical engineering and computer science, with features like automated pH testing and sensor-based evaluations. Key functionalities, including timed watering and automatic adjustments, were coded to enhance plant care. Initially, the project’s comprehensive research and strategic planning resulted in detailed blueprints and computer-aided design models for the …

Modeling W/V-Band Satellite Communications In The Presence Of Noise Jamming, Ryan Michael Eckman

Electrical and Computer Engineering ETDs

Understanding the performance of wideband modulated signals under noise jamming conditions is important for advancing W/V-band military satellite communications. This research developed and validated models to predict performance degradation of a communication channel in the presence of wideband noise jamming. Channel models were developed that included both modulated communication signals and jammer signals. Integrated models included environmental link factors and practical implementation factors. Integrated models were verified and validated using outdoor radio frequency environments utilizing two W/V-band transceivers, a portable W-band jammer, and software defined radios. Experimental results demonstrated excellent agreement with integrated model predictions. Channel degradation due to the …

Trust-Me: Resource Allocation And Server Selection Based On Trust In Multi-Access Edge Computing, Sean Tsikteris

Electrical and Computer Engineering ETDs

Multi-access Edge Computing (MEC) is crucial for Internet of Things (IoT) applications by optimizing data processing and reducing latency. This thesis presents contributions to resource allocation and decision-making in edge computing environments. The TRUST-ME model is introduced, involving multiple edge servers and IoT devices (users) offloading computing tasks to MEC servers. A utility function is designed to assess latency and cost benefits for IoT devices using server resources. The core innovation is a novel trust model that evaluates IoT devices’ confidence in MEC servers by integrating both direct and indirect trust, based on interactions and feedback from other devices. In …

Performance Optimization And Application Of P-Type Transparent Semiconductors In The Cdte Solar Cells, Md Zahangir Alom

USF Tampa Graduate Theses and Dissertations

CdTe thin-film solar cells are one of the major interests in the solar industry for their favorable properties. For example, CdTe has a near-ideal bandgap (1.45 eV) for absorption of the solar spectrum, and a high absorption coefficient ( ̴ 105 cm-1) and can capture 99% of light with only 2 µm of film thickness. Moreover, CdTe can be doped both n and p-type. Additionally, low production costs contribute to more affordable panel prices (0.40 $/W) [1]. The highest efficiency achieved to-date for this material is 23.1% demonstrated by First Solar, which is still lower than the theoretical limit [2]. …

Sustainable Mobility: Machine Learning-Driven Deployment Of Ev Charging Points In Dublin, Ruairí De Fréin, Alexander Mutiso Mutua Mr

Articles

Electric vehicle (EV) drivers in urban areas face range anxiety due to the fear of running out of charge without timely access to charging points (CPs). The lack of sufficient numbers of CPs has hindered EV adoption and negatively impacted the progress of sustainable mobility. We propose a CP distribution algorithm that is machine learning-based and leverages population density, points of interest (POIs), and the most used roads as input parameters to determine the best locations for deploying CPs. The objects of the following research are as follows: (1) to allocate weights to the three parameters in a $6$ km …

Electrochemical Copper Printing For Wearable Electronics, Nirmita Roy

USF Tampa Graduate Theses and Dissertations

Wearable electronics have become a transformative force across industries like healthcare, aerospace, and military applications. However, a significant challenge persists in directly integrating electronic circuits onto fabrics. Addressing this challenge, the aim of this research is to introduce a novel sequential manufacturing process. Initially, a fabric is coated with a customized ink containing lignin, establishing a conductive template through laser burning. Subsequently, a localized Hydrogen Evolution Assisted (HEA) copper electroplating method is applied, resulting in a low-resistive circuit layout. Our investigations encompassed nanostructure analyses using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), Raman Spectroscopy, and Fourier Transform Infrared …

Use Of Electrical Bone Growth Stimulators In High-Risk Patients Following Spinal Fusion, Soumya Malhotra, Khavir Sharieff

HCA-NSU MD Research Day

Title: Use of Electrical Bone Growth Stimulators in High-Risk Patients Following Spinal Fusion Authors: Soumya Malhotra, BA., MS1 & Khavir Sharieff, DO, MBA2 1Class of 2027, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Fort Lauderdale, FL 2Assistant Professor of Surgery, Nova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine, Tampa Bay, FLNova Southeastern University Dr. Kiran C. Patel College of Osteopathic Medicine Objective: This study aimed to elucidate the advantages of EBGSs following high-risk spinal fusions. Background: Pseudarthrosis is a condition where bones fail to fuse after an injury or surgery. It causes significant …

Collapse Of Pre-Covid-19 Differences In Performance In Online Vs. In-Person College Science Classes, And Continued Decline In Student Learning, Gregg R. Davidson, Hong Xiao, Kristin Davidson

Faculty and Student Publications

Abstract: Studies comparing student outcomes for online vs. in-person classes have reported mixed results, though with a majority finding that lower-performing students, on average, fare worse in online classes, attributed to the lack of built-in structure provided by in-person instruction. The online/in-person outcome disparity was normative for non-major geology classes at the University of Mississippi prior to COVID-19, but the difference disappeared in the years after 2020. Previously distinct trendlines of GPA-based predictions of earned-grade for online and in-person classes merged. Of particular concern, outcomes for in-person classes declined to match pre-COVID-19 online expectations, with lower-GPA students disproportionally impacted. Objective …

Advanced Strategies For Improving The Robustness Of Deep Learning, Keyu Chen

USF Tampa Graduate Theses and Dissertations

Machine Learning (ML) and Deep Learning (DL) have achieved great success across diverse fields in the last decades, such as facial recognition, medical diagnosis, and language translation. The success, however, largely hinges on the assumption that the training and testing data share the same distribution or domain. In practice, real-world data often exhibits domain shifts, leading to notable degradation in model performance. Hence, the generalization capability of machine lea=rning models is of great importance, which refers to the domain generalization problem. In this dissertation, we present DADG, an effective algorithm for domain generalization, aiming to learn domain-invariant features from seen …

Investigation On The Impact Of Loading Effect Of Fruit Juices On The Performance Of Pulsed Electric Field Generators, Devi S

Theses and Dissertations

Pulsed Electric Field (PEF) treatment is one of the efficient non-thermal food processing techniques which is being preferred as a replacement for thermal pasteurization methods. The effectiveness of PEF treatment was measured in terms of reduction in the microbial load in the food, extension of shelf life of the food and retention of nutritional properties of the food. The successful implementation of the PEF treatment depends upon various aspects such as design of pulse generator, parameters of pulse generator, shape and size of the treatment chamber and most importantly the characteristics of each food items. Design and fabrication of a …

Design, Fabrication, And Characterization Of Electro-Optic Radio-Frequency Probes For High Field Environments, Michael D. Sherburne

Electrical and Computer Engineering ETDs

Design, Fabrication, and Characterization of Electro-Optic Radio-Frequency Probes For High Field Environments

A Benchmark Knowledge Graph Of Driving Scenes For Knowledge Completion Tasks, Ruwan Wickramarachchi, Cory Henson, Amit Sheth

Publications

Knowledge graph completion (KGC) is a problem of significant importance due to the inherent incompleteness in knowledge graphs (KGs). The current approaches for KGC using link prediction (LP) mostly rely on a common set of benchmark datasets that are quite different from real-world industrial KGs. Therefore, the adaptability of current LP methods for real-world KGs and domain-specific ap- plications is questionable. To support the evaluation of current and future LP and KGC methods for industrial KGs, we introduce DSceneKG, a suite of real-world driving scene knowledge graphs that are currently being used across various industrial applications. The DSceneKG is publicly …

Biocorrosion Analysis Via Multiscale Time Series Analysis, Victor Hugo Mendoza Vejar, Eliseo Hernandez Martinez, Hector Puebla

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Physical Layer Entropy Analysis For Physical Unclonable Functions, Jenilee Jao

Electrical and Computer Engineering ETDs

Process variations within Field Programmable Gate Arrays (FPGAs) provide a rich source of entropy, making them well-suited for the implementation of Physical Unclonable Functions (PUFs). This dissertation presents three studies on FPGA-based PUFs. First, we explore a ring-oscillator (RO) PUF that leverages localized entropy from individual look-up table (LUT) primitives, analyzing design bias. Next, we investigate delay variations that occur through the routing network and switch matrices of FPGAs using a feature of Xilinx called dynamic partial reconfiguration (DPR). Finally, we evaluate entropy across FPGAs from Xilinx, Altera, and Microsemi using the Shift-Register Reconvergent-Fanout (SiRF) PUF architecture to compare path …

Advancing Drug Discovery And Disease Understanding Through Knowledge Graphs And Machine Learning Techniques, Swastika Tenkila Purushotham

Electrical and Computer Engineering ETDs

This thesis investigates knowledge graphs with particular reference to the NIH-funded Common Fund Data Ecosystem Data Distillery project. By combining data from nine Common Fund projects and other sources, this project has created a large knowledge graph using Neo4j. To find new and undiscovered drug targets, UNM’s Illuminating the Druggable Genome (IDG) Data Coordinating Center has supplied data and use cases. Condensed Knowledge Graph, a condensed version that is based on the Data Distillery Knowledge Graph, improves usability for IDG applications. Condensed Knowledge Graph research endeavors to enhance data organization through the categorization of disease terms, examination of Cerebellar Stroke …

Reducing Carbon Footprint In Ai: A Framework For Sustainable Training Of Large Language Models, Sunbal Iftikhar, Steven Davy

Conference papers

In the world of artificial intelligence (AI), large language models (LLMs) are leading the way, transforming how people understand and use language. These models have significantly impacted various domains, from natural language processing (NLP) to content generation, sparking a wave of innovation and exploration. However, this rapid progress brings to light the environmental implications of LLMs, particularly the significant energy consumption and carbon emissions during their training and operational phases. This requires a shift towards more energy-efficient practices in training and deploying LLMs, balancing AI innovation with environmental responsibility. This paper emphasizes the need for improving the energy efficiency of …

Digital Health Intervention For Children With Adhd To Improve Mental Health Intervention, Patient Experiences, And Outcomes: A Study Protocol, Nancy Herrera, Franceli L. Cibrian, Lucas M. Silva, Jesus Armando Beltran, Sabrina E. B. Schuck, Gillian R. Hayes, Kimberley D. Lakes

Engineering Faculty Articles and Research

Background

Attention Deficit Hyperactivity Disorder (ADHD) is the most prevalent childhood psychiatric condition with profound public health, personal, and family consequences. ADHD requires comprehensive treatment; however, lack of communication and integration across multiple points of care is a substantial barrier to progress. Given the chronic and pervasive challenges associated with ADHD, innovative approaches are crucial. We developed the digital health intervention (DHI)—CoolTaCo [Cool Technology Assisting Co-regulation] to address these critical barriers. CoolTaCo uses Patient-Centered Digital Healthcare Technologies (PC-DHT) to promote co-regulation (child/parent), capture patient data, support efficient healthcare delivery, enhance patient engagement, and facilitate shared decision-making, thereby improving access to …

A 3d Memristor Architecture For In-Memory Computing Demonstrated With Sha3, Muayad J. Aljafar, Rasika Joshi, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

Security is a growing problem that needs hardware support. Memristors provide an alternative technology for hardware-supported security implementation. This paper presents a specific technique that utilizes the benefits of hybrid CMOS-memristors technology demonstrated with SHA3 over implementations that use only memristor technology. In the proposed technique, SHA3 is implemented in a set of perpendicular crossbar arrays structured to facilitate logic implementation and circular bit rotation (Rho operation), which is perhaps the most complex operation in SHA3 when carried out in memristor arrays. The Rho operation itself is implemented with CMOS multiplexers (MUXs). The proposed accelerator is standby power-free and circumvents …