Other Electrical and Computer Engineering Commons^™

Toward Intuitive 3d Interactions In Virtual Reality: A Deep Learning- Based Dual-Hand Gesture Recognition Approach, Trudi Di Qi, Franceli L. Cibrian, Meghna Raswan, Tyler Kay, Hector M. Camarillo-Abad, Yuxin Wen

Engineering Faculty Articles and Research

Dual-hand gesture recognition is crucial for intuitive 3D interactions in virtual reality (VR), allowing the user to interact with virtual objects naturally through gestures using both handheld controllers. While deep learning and sensor-based technology have proven effective in recognizing single-hand gestures for 3D interactions, research on dual-hand gesture recognition for VR interactions is still underexplored. In this work, we introduce CWT-CNN-TCN, a novel deep learning model that combines a 2D Convolution Neural Network (CNN) with Continuous Wavelet Transformation (CWT) and a Temporal Convolution Network (TCN). This model can simultaneously extract features from the time-frequency domain and capture long-term dependencies using …

Co-Designing Situated Displays For Family Co-Regulation With Adhd Children, Lucas M. Silva, Franceli L. Cibrian, Clarisse Bonang, Arpita Bhattacharya, Aehong Min, Elissa M. Monteiro, Jesus A. Beltran, Sabrina E. B. Schuck, Kimberley D. Lakes, Gillian R. Hayes, Daniel A. Epstein

Engineering Faculty Articles and Research

Family informatics often uses shared data dashboards to promote awareness of each other’s health-related behaviors. However, these interfaces often stop short of providing families with needed guidance around how to improve family functioning and health behaviors. We consider the needs of family co-regulation with ADHD children to understand how in-home displays can support family well-being. We conducted three co-design sessions with each of eight families with ADHD children who had used a smartwatch for self-tracking. Results indicate that situated displays could nudge families to jointly use their data for learning and skill-building. Accommodating individual needs and preferences when family members …

Enhancing Fpga Synthesis For Space Applications: Performance Evaluation Of Scalehls In The Adapt Project, Ruoxi Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis investigates the application of ScaleHLS, a high-level synthesis (HLS) tool, to enhance Field-Programmable Gate Array (FPGA) synthesis for space applications, with a focus on the Antarctic Demonstrator Advanced Particle-astrophysics Telescope (ADAPT) project. The study explores how ScaleHLS optimizes the transformation of C code into FPGA-compatible designs to improve computational efficiency and resource utilization.

The research details the process of adapting ADAPT's computational algorithms for FPGA using ScaleHLS, emphasizing the tool's effectiveness in streamlining the code-to-hardware translation. A performance evaluation highlights significant improvements in resource management and operational speed, demonstrating the tool's impact on FPGA synthesis.

These findings illustrate …

Machine Learning For Intrusion Detection Into Unmanned Aerial System 6g Networks, Faisal Alrefaei

Doctoral Dissertations and Master's Theses

Progress in the development of wireless network technology has played a crucial role in the evolution of societies and provided remarkable services over the past decades. It remotely offers the ability to execute critical missions and effective services that meet the user's needs. This advanced technology integrates cyber and physical layers to form cyber-physical systems (CPS), such as the Unmanned Aerial System (UAS), which consists of an Unmanned Aerial Vehicle (UAV), ground network infrastructure, communication link, etc. Furthermore, it plays a crucial role in connecting objects to create and develop the Internet of Things (IoT) technology. Therefore, the emergence of …

Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Wind power is one of the world's fastest-growing renewable energy resources and has expanded quickly within the US electric grid. Currently, wind power producers (WPPs) may sell energy products in US markets but are not allowed to sell reserve products, due to the uncertain and intermittent nature of wind power. However, as wind’s share of the power supply grows, it may eventually be necessary for WPPs to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The …

Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

As technology advances, the field of electrical and computer engineering continuously demands innovative tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. Through a comprehensive literature review, it was discovered that there was a gap in the current research on using VR technology to effectively visualize and comprehend non-observable electrical characteristics of electronic circuits. This thesis explores the integration of Virtual Reality (VR) technology and real-time electronic circuit simulation with enhanced visualization of non-observable concepts such as voltage distribution and current flow within these circuits. The primary objective is to develop an immersive educational platform that makes …

Design And Optimization Of A Novel Monolithic Spring For High-Frequency Press-Pack Sic Fet Modules, Bogac Canbaz

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Silicon Carbide (SiC) Field-Effect Transistor (FET) modules lead the way in power electronics, being superior in efficiency and robustness for high-frequency applications. The shift towards SiC from traditional silicon (Si)-based devices is driven by its superior thermal conductivity, higher electric field strength, and operational efficiency at elevated temperatures. These features are critical for the development of next-generation, grid-oriented power converters aimed at enhancing the reliability and sustainability of power systems. This research focuses on high-frequency press-pack (HFPP) SiC FET modules, addressing the primary challenge of miniaturizing SiC FET dies without compromising performance, through an innovative press-contact design essential for increased …

An Investigation Of Information Structures In Dna, Joel Mohrmann

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The information-containing nature of the DNA molecule has been long known and observed. One technique for quantifying the relationships existing within the information contained in DNA sequences is an entity from information theory known as the average mutual information (AMI) profile. This investigation sought to use principally the AMI profile along with a few other metrics to explore the structure of the information contained in DNA sequences.

Treating DNA sequences as an information source, several computational methods were employed to model their information structure. Maximum likelihood and maximum a posteriori estimators were used to predict missing bases in DNA sequences. …

Surface Chemistry Of Femtosecond Laser Processed Surfaces, Graham Kaufman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Micromachining and surface functionalization with femtosecond lasers is a rapidly developing technology in the field of materials and interfacial sciences due to its flexibility towards materials, tunability in surface features, and prospects for scalability. Many interfacial applications have been shown to be enhanced with femtosecond laser-induced surface texturing including two-phase heat transfer, antimicrobial properties, electrochemical systems and more. However, without ideal surface chemistry, the enhancements cannot be optimized for a given application. Surfaces functionalized by femtosecond lasers tend to have transient surface chemistries when exposed to the atmosphere, changing important interfacial properties like the interaction of the solid surfaces and …

Optical Wavelength Measurement Based On Microwave-Photonics And Fiber Dispersion, Yongji Wu

All Dissertations

In modern photonics, combining microwave techniques with optical measurements has introduced a novel research direction. This study introduces a novel Microwave Photonics Wavelength Measurement System (MP-WMS), integrating microwave photonics with fiber chromatic dispersion to achieve direct wavelength measurement. Utilizing cost effective single mode optical fibers as dispersion devices, this system employs chromatic dispersion to convert optical frequency domain measurements into microwave time domain measurements. We established a mathematical model to describe how different wavelengths are detected, enhancing the system's effectiveness. The MP-WMS system offers an affordable solution with high resolution. In the experiment, we used a 35km long SM-28 single-mode …

Effectiveness Of Cnn-Lstm Models Used For Apple Stock Forecasting, Ethan White

Electronic Theses, Projects, and Dissertations

This culminating experience project investigates the effectiveness of convolutional neural networks mixed with long short-term memory (CNN-LSTM) models, and an ensemble method, extreme gradient boosting (XGBoost), in predicting closing stock prices. This quantitative analysis utilizes recent AAPL stock data from the NASDAQ index. The chosen research questions (RQs) are: RQ1. What are the optimal hyperparameters for CNN-LSTM models in stock price forecasting? RQ2. What is the best architecture for CNN-LSTM models in this context? RQ3. How can ensemble techniques like XGBoost effectively enhance the predictions of CNN-LSTM models for stock price forecasting?

The research questions were answered through a thorough …

Applications Of Supercapacitors In Robotic Systems, Charles Davis, Zachary Giese, Joseph Gober, Samuel Grisham, Avery Mahan

ATU Scholars Symposium

This project explores the utilization of a bespoke supercapacitor system to energize and propel a robot across various challenging courses. The custom supercapacitor setup serves as the primary power source, providing rapid charging capabilities and high energy density. The research investigates the integration of this innovative power solution into the robot's design, aiming to optimize its performance and endurance in competitive environments.

Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi

Electronic Theses and Dissertations

This thesis explores the transformative potential of data-driven approaches in addressing key operational and reliability issues in power systems. The first part of this thesis addresses a prevalent problem in power distribution networks: the accurate identification of load phases. This study develops a data-driven model leveraging consumption measurements from smart meters and corresponding substation data to reconstruct topology information in low-voltage distribution networks. The proposed model is extensively tested using a dataset with more than 5,000 real load profiles, demonstrating satisfactory performance for large-scale networks. The second part of the thesis pivots to a crucial safety concern: the risk and …

A Study Of Random Partitions Vs. Patient-Based Partitions In Breast Cancer Tumor Detection Using Convolutional Neural Networks, Joshua N. Ramos

Master's Theses

Breast cancer is one of the deadliest cancers for women. In the US, 1 in 8 women will be diagnosed with breast cancer within their lifetimes. Detection and diagnosis play an important role in saving lives. To this end, many classifiers with varying structures have been designed to classify breast cancer histopathological images. However, randomly partitioning data, like many previous works have done, can lead to artificially inflated accuracies and classifiers that do not generalize. Data leakage occurs when researchers assume that every image in a dataset is independent of each other, which is often not the case for medical …

A Study On The Incentives And Barriers For The Adoption Of Electric Vehicles In South Alabama, Marianne Loes, Daniela Wolter Ferreira Touma, Jennifer C. Zoghby

AMTP Proceedings 2024

ABSTRACT

Through a series of public policy incentives and consumer demand, more electric vehicles are being sold nationwide than ever before. Although electric vehicles (EVs) are being adopted nationwide by many consumers in recent years, car-buyers across South Alabama have not followed the trend. This research considers different stakeholders in the complex consumer buying process of car purchases, and it uses the extant technology adoption models to assess the public policy incentives, as well as statewide roadblocks, to EV adoption.

The Sensory Accommodation Framework For Technology: Bridging Sensory Processing To Social Cognition, Louanne Boyd

Engineering Faculty Books and Book Chapters

This book provides a thorough introduction to the many facets of designing technologies for autism, with a particular focus on optimizing visual attention frameworks. This book is designed to provide a detailed overview of several aspects of technology for autism. Each Chapter illustrates different parts of the Sensory Accommodation Framework and provides examples of relevant available technologies. The books first discusses a variety of skills that make up human development as well as a history of autism as a diagnosis and the birth of the neurodiversity movement. It goes on to detail individual types of therapy and how they interact …

Pulsed Dielectric Breakdown And Permittivity Characterization Of Composite Solid Insulators In Pulsed Power Systems, Shawn T. Scoggin

Electrical Engineering Dissertations - Archive

In high voltage pulsed power systems, liquids and gases are often used as insulating materials because they offer high breakdown strengths, conform around complex geometries, and are self-healing, but they can introduce significant engineering challenges and restrictions when it comes to implementing them. Solid dielectrics can be desirable for improving the maintenance requirements, shelf life, and power/energy density metrics associated with insulating high voltage pulsed power systems, however they possess design challenges of their own. Solid dielectrics are not self-healing and can be difficult to manufacture, especially around complex geometries. Epoxy dielectrics are of high interest because of their naturally …

Intelligent Millimeter-Wave System For Human Activity Monitoring For Telemedicine, Abdullah K. Alhazmi, Mubarak A. Alanazi, Awwad H. Alshehry, Saleh M. Alshahry, Jennifer Jaszek, Cameron Djukic, Anna Brown, Kurt Jackson, Vamsy P. Chodavarapu

Electrical and Computer Engineering Faculty Publications

Telemedicine has the potential to improve access and delivery of healthcare to diverse and aging populations. Recent advances in technology allow for remote monitoring of physiological measures such as heart rate, oxygen saturation, blood glucose, and blood pressure. However, the ability to accurately detect falls and monitor physical activity remotely without invading privacy or remembering to wear a costly device remains an ongoing concern. Our proposed system utilizes a millimeter-wave (mmwave) radar sensor (IWR6843ISK-ODS) connected to an NVIDIA Jetson Nano board for continuous monitoring of human activity. We developed a PointNet neural network for real-time human activity monitoring that can …

Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Convolutional neural networks (CNNs) have become instrumental in advancing multi-frame image super-resolution (SR), a technique that merges multiple low-resolution images of the same scene into a high-resolution image. In this paper, a novel deep learning multi-frame SR algorithm is introduced. The proposed CNN model, named Exponential Fusion of Interpolated Frames Network (EFIF-Net), seamlessly integrates fusion and restoration within an end-to-end network. Key features of the new EFIF-Net include a custom exponentially weighted fusion (EWF) layer for image fusion and a modification of the Residual Channel Attention Network for restoration to deblur the fused image. Input frames are registered with subpixel …

Application Of The Mixed Integer Nonlinear Programming Technique For The Economic Planning Of Transmission Networks In New Manner, Nader Shawky Abdelhakeem, Maged Gamal Lotfy, Mohamed Shibl Albags, Ahmed Saied Elzawawy

Mansoura Engineering Journal

In the recent years, the mathematical planning model of transmission networks based on full AC load flow has been developed. But, due to the model non-convexity and the existing of large number of local solutions, this model can only be used for small size networks as it consumes large unreasonable computation time in addition to its incapability to yield global solution in most cases. To overcome these problems, two new iterative solution procedures have been presented in this paper. In the first one, the objective function is changed to the minimization of the number of new lines required to satisfy …