Other Electrical and Computer Engineering Commons^™

Exploring Smart Thermostat, Don P. Dang

2024 Fall Honors Capstone Projects - Archive

This study examines the security, privacy, and compatibility challenges associated with smart thermostats in smart home systems. Smart thermostats, as part of the growing Internet of Things (IoT) ecosystem, face vulnerabilities such as unauthorized access, data breaches, and inconsistent security protocols. Using a mixed-methods approach, this research evaluates encryption techniques, communication protocols (Zigbee, Z-Wave, Wi Fi), and user behaviors that impact system security and efficiency. Key findings indicate that 35% of users are concerned about hacking risks, while 25% express data privacy concerns. Many users lack awareness of security measures, such as firmware updates and password management, which increases vulnerabilities. …

Enhancing Webtas: From An Atam Simulator To A Developmental Environment, Elizabeth G. Schmidt

Electrical Engineering and Computer Science Undergraduate Honors Theses

As interest in a niche research area, like the abstract Tile Assembly Model (aTAM), grows it is crucial to ensure that simulation tools are accessible and user-friendly for a broad audience. Existing resources can pose challenges for less experienced users, highlighting the need for enhancements that improve usability and functionality. To address these issues, key upgrades to the current online simulation platform, WebTAS, were implemented, including breakpoint functionality and nondeterminism checks, alongside features such as XML file integration, image capturing, and simulation view resets. These enhancements collectively elevate the platform from a basic learning tool to a comprehensive environment for …

Perceptual Hash Based Content Matching, Nicholas Daniel Chenevey

Master's Theses

The proliferation of video content and AI generated imagery has introduced a number of new challenges in content identification and verification. The ability to trace content back to its source has become a critical problem as video content increases both naturally and synthetically through AI generation. This thesis provides the design, analysis, and experimental verification for a perceptual hash based framework aimed at addressing these challenges. Perceptual hashing is a method for encoding the visual content of images into compact and easily comparable binary strings. This process is used as the foundation for content matching in videos and source verification …

Spectrum Optimization For Advanced Air Mobility Communications Using Deep Reinforcement Learning., Rafael D. Apaza

Electronic Theses and Dissertations

As aviation operations expand and new participants enter the National Airspace System (NAS), the demand for aeronautical communications will experience a significant rise. This surge is propelled by increased air travel and the emergence of Urban Air Mobility (UAM) operations, a subset of Advanced Air Mobility (AAM). UAM aims to facilitate intra-city transportation of people and cargo utilizing remotely piloted aircraft capable of electric vertical takeoff and landing operations. The growing dependence on efficient wireless communication systems underscores the critical importance of intelligent spectrum allocation and effective airspace management to ensure safe, seamless, and technologically advanced air operations. However, the …

Three-Dimensional Environmentally Sustainable Neuromorphic Computing System Based On Natural Organic Memristor, Mohammed Rafeeq Khan

Graduate Theses and Dissertations (2019 - present)

A three-dimensional neuromorphic (3D) computing architecture based on environmentally sustainable natural organic honey memristors is proposed in this thesis. A set of comprehensive and experimental results indicate that the proposed systems exhibit remarkable inference accuracy, consistently surpassing the 90% threshold, even with different challenges such as device variations and nonlinearity. This study also considers four different conductance drift situations, the effects of analog-to-digital converter (ADC) quantization, and multiple algorithms, such as VGG8 and DenseNet-40. The deliverable of this thesis will test the stability of the proposed systems and explore their potential applications and scalability in real-world situations.

Virtual Control: A Comparison Of Methods For Hand-Tracking Implementation, Nathan Roberts

Honors Program: Senior Projects (Public)

This thesis examines the design philosophy of modern virtual reality applications that utilize hand-tracking as a primary form of user input. The analysis presented hopes to provide ideas for future implementations of this technology so that more immersive experiences are developed. This analysis starts with the discussion of a modern example of successful hand-tracking implementation, then comparing that implementation to a recent senior design project. This comparison is primarily based on each experience’s ability to create interactivity and immediacy. Interactivity is the degree to which the user can quickly and reliably make changes to their virtual environment, while immediacy is …

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 …

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 …

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 …

Hypoxic Incubator: Improving Robustness/Reliability And Demonstrating Physiological Efficacy, Damon Dennis Tan

Master's Theses

The Microphysiological Systems Laboratory aims to develop colorectal cancer tumor models under a hypoxic environment to assess model response to pharmaceutical compounds in vitro. To perform relevant studies, researchers have attempted to use different hypoxic inducing strategies such as a nitrogen pod and hypoxic incubator to recreate in vivo physiological responses to hypoxia. However, studies would be interrupted due to incubator functionality failure. To ensure successful and physiologically relevant studies, I improved and verified the robustness and reliability of a hypoxic incubator previously designed and manufactured in the lab. Through the testing and iterating design processes, I engineered and implemented …

3d Printed Microfluidic Fabrication Methodology, Characterization, Mechanical Design, And Applications In Electrostatic Artificial Muscles And Benthic Microbial Fuel Cells, Terak B. Hornik

Master's Theses

The fabrication of microfluidic devices often requires specialized methods. The development of these methods requires careful characterization and understanding of the processes involved. Using primarily PolyJet 3D printing technology, microfluidics offers a wide scope of applications such as microfluidic benthic microbial fuel cells (MBMFCs) and electrostatic artificial muscles. MBMFCs benefit from the confinement of the microbes resulting in close proximity between the electrode and the organisms. Using a modular design called the Sponge, assembly and upscaling is possible. Electrostatic artificial muscles benefit from a microfluidic approach due to the non-linearity of electrostatic attraction creating disproportionate benefits when miniaturized. When designed …

Joint Modeling Of Degradation Signals And Time-To-Event Data For The Prediction Of Remaining Useful Life, Sebastian Brumm, Erik Linstead, Junde Chen, Narayanaswamy Balakrishnan, Yuxin Wen

Engineering Faculty Articles and Research

Accurate prediction of remaining useful life (RUL) for in-service systems plays an important role in ensuring efficient operation of industrial equipment and in preventing unexpected equipment failures. In this paper, we present a prognostic framework for real-time RUL prediction based on joint modeling of both degradation signals and time-to-event data. The proposed model employs a change point-based general path model to capture signal non-linearity and Neural network (NN) based Cox model to link the time-to-event data with the estimated degradation trend. An empirical two-step scheme for hyperparameter estimation is proposed to enhance prognostic accuracy. Furthermore, an efficient Bayesian model updating …

Long-Distance Photon-Mediated And Short-Distance Entangling Gates In Three-Qubit Quantum Dot Spin Systems, Nooshin M. Estakhri, Ada Warren, Sophia E. Economou, Edwin Barnes

Engineering Faculty Articles and Research

Superconducting resonator couplers will likely become an essential component in modular semiconductor quantum dot (QD) spin qubit processors, as they help alleviate crosstalk and wiring issues as the number of qubits increases. Here, we focus on a three-qubit system composed of two modules: a two-electron triple QD resonator coupled to a single-electron double QD. Using a combination of analytical techniques and numerical results, we derive an effective Hamiltonian that describes the three-qubit logical subspace and show that it accurately captures the dynamics of the system. We examine the performance of short-range and long-range entangling gates, revealing the effect of a …

M3t-Lm: A Multi-Modal Multi-Task Learning Model For Jointly Predicting Patient Length Of Stay And Mortality, Junde Chen, Qing Li, Feng Liu, Yuxin Wen

Engineering Faculty Articles and Research

Ensuring accurate predictions of inpatient length of stay (LoS) and mortality rates is essential for enhancing hospital service efficiency, particularly in light of the constraints posed by limited healthcare resources. Integrative analysis of heterogeneous clinic record data from different sources can hold great promise for improving the prognosis and diagnosis level of LoS and mortality. Currently, most existing studies solely focus on single data modality or tend to single-task learning, i.e., training LoS and mortality tasks separately. This limits the utilization of available multi-modal data and prevents the sharing of feature representations that could capture correlations between different tasks, ultimately …

Predictive Residual Neural Networks For Optical Trapping Of Small Particles, Nasim Mohammadi Estrakhri, Ponthea Zahraii, Saman Kashanchi, Nooshin M. Estakhri

Engineering Faculty Articles and Research

Optical tweezers provide a non-contact method to trap, move, and manipulate micro- and nano-sized objects. Using properly designed dielectric and plasmonic nanostructure configurations, optical tweezers have been tailored to create stable and precise trapping for nanoscale objects. Recent advances in numerical optimization techniques allow further enhancement in nanoscale optical traps through inverse optimization of such configurations. One of the main challenges in such optimization approaches is the time-consuming nature of full-wave simulation of nanostructures and postprocessing steps to extract optical forces. To address this challenge, we introduce a surrogate solver based on residual neural networks that can accurately predict the …

Distributed Multi-Robot Localization And Coordination Framework For Mobile Robots, Dmitri Dobrynin, Indigo T. Garcia

College of Engineering Summer Undergraduate Research Program

This project aims to develop an experimental framework for multiple mobile robots, both in simulation and real-world hardware, using ROS 2 as the primary operating system. Utilizing TurtleBot 3 platforms, the team will establish a robust setup that enables tasks such as distributed localization, autonomous navigation, path planning, and formation control for mobile robots. Leveraging simulation environments like Gazebo, the project will replicate real-world setups in a simulated environment for testing and development. All tasks, communication, and sensor integration will be implemented using ROS 2, ensuring seamless coordination and interoperability among the robots. The project involves integrating various sensors and …

Review Of Hardware Implementation For The Two-Wheeled Self-Balancing Robot, Ghaidaa Hadi Salih Elias

Al-Bahir

The working principle of a self-balancing robot is similar to that of an inverted pendulum, with the mobile robot's controller playing a crucial part in both self-balancing and stabilization. It is the kind that constantly modifies itself to keep balance when it rides on two wheels. This review will center on the basic construction of the suggested robot, summarize the recent studies relative to control methods and the building of the two-wheeled self-balancing robot, and discuss the outcomes of control experiments conducted on hardware systems. It will assist researchers in building and designing two-wheeled mobile robots in the future.

Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition, Junde Chen, Yun Wang, Adnan Zeb, M. D. Suzauddola, Yuxin Wen

Engineering Faculty Articles and Research

Early recognition of Alzheimer’s disease (AD) and its precursor state, mild cognitive impairment (MCI), is pivotal in interrupting the progression of the disease and providing suitable treatment. Recent development in deep learning techniques has drawn great research attention for improving the efficacy of AD recognition. However, numerous current methods solely utilize data from a single auxiliary domain, limiting their ability to harness valuable intrinsic insights from multiple domains. To cope with the challenge, this paper is devoted to establishing an innovative multimodal medical data fusion model, termed as MMDF, to perform Alzheimer’s disease recognition. Multimodal data including clinical records and …

Fpca-Setcn: A Novel Deep Learning Framework For Remaining Useful Life Prediction, Junde Chen, Yuxin Wen, Xuxue Sun, Adnan Zeb, Mohammad Saleh Meiabadi, Sasan Sattarpanah Karganroudi

Engineering Faculty Articles and Research

The accurate prediction of remaining useful life (RUL) can serve as a reliable foundation for equipment maintenance, thereby effectively reducing the incidence of failure and maintenance costs. In this study, a novel deep learning (DL) framework that incorporates functional principal component analysis (FPCA) and enhanced temporal convolutional network (TCN) is proposed for RUL prediction. Precisely, FPCA is employed to capture the changing patterns in multistream degradation trajectories. Subsequently, the reconstructed signals from FPCA are fed into a convolutional block for extracting deep-level features. An enhanced squeeze-and-excitation (ESE) block is then incorporated into the network for adaptive feature recalibration, enhancing the …

Engineering Ecological Analysis Of Rise Of Huawei’S Harmonyos And Its Implications, Dazhou Wang, Yishi Lyu, Zhihuan Fu

Bulletin of Chinese Academy of Sciences (Chinese Version)

This study aims to explore the rise of the Harmony operating system from the perspective of engineering ecology. In the face of increasingly fierce global technological competition, Huawei, as a leading Chinese information technology enterprise, launched its self-developed HarmonyOS and has progressively built the Harmony ecosystem, providing foundational support for the development of all sectors. The development path of HarmonyOS can be divided into three main phases based on its strategic goals, technological and product characteristics, and ecological construction: the initial phase, the acceleration phase, and the transformation phase. It is revealed that, throughout this development, various construction strategies for …

Esd-Robust 4h-Sic Low-Voltage Cmos Technology Development For High Temperature, Hui Wang

Graduate Theses and Dissertations

This dissertation explores the development and optimization of electrostatic discharge (ESD)-robust, low-voltage CMOS technology using 4H-silicon carbide (SiC) tailored for high-temperature applications, addressing the critical need for reliable semiconductor devices in harsh environmental conditions. The advent of SiC as a semiconductor material offers significant advantages over traditional silicon (Si) in harsh environments, including higher thermal conductivity, greater electron mobility, and improved electrical characteristics at elevated temperatures. This research explores the integration of 4H-SiC into CMOS technology to enhance device reliability and performance in extreme conditions such as those found in aerospace, automotive, and energy sectors. The study begins with a …

Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan

All Dissertations

This thesis is concerned with the data-driven solution to the optimal control problem with safety constraints for a class of control-affine nonlinear systems. Designing optimal control satisfying safety constraints is a problem of interest in various applications, including robotics, power systems, transportation networks, and manufacturing. This problem is known to be non-convex. One of this thesis's main contributions is providing a convex formulation to this non-convex problem. The second main contribution is providing a data-driven framework for solving the control problem with safety constraints. The linear operator theoretic framework involving Perron-Frobenius and Koopman operators provides the convex formulation and associated …

Reinforcement Learning Assisted Communication Resources Optimization In Advanced Air Mobility., Ruixuan Han

Electronic Theses and Dissertations

Advanced air mobility (AAM), which envisages a safe and efficient aviation transportation system, has drawn significant attention to support the increasing mobility demand in metropolitan areas. Communication services for AAM aerial vehicles (AVs) are crucial for ensuring flight safety. This dissertation explores three research topics on communication resource allocation problems in AAM applications. The first topic, addressed in Chapter II, investigates the joint velocity selection and spectrum allocation problem for AAM applications to enhance spectrum utilization efficiency (SUE). In the AAM scenario, multiple AVs travel along predefined paths for passenger and cargo deliveries. Given that AAM aims to provide fast …

Heat And Mass Transfer Characteristics During Vacuum Drying Of Wood, Mohamed Salah Elmetwaly, Lotfy Hassan Rabie Saker, Mohamed Sameh Salem

Journal of Engineering Research

The properties affecting the characteristics of heat and mass transfer during vacuum drying of wood are studied in this paper. The experimental work is carried out in 0.0365 m³ test rig vacuum dryer. The drying chamber dimensions are 0.5 m long and 0.305 m diameter carbon steel cylinder. This drying chamber is internally coated with epoxy paint, also this chamber is detachable closing caps at both ends meaning welded at one end and bolted at the other end to facilitate loading and unloading of the specimen. Two stainless steel heat exchanger plates with dimensions 0.3 m length, 0.15 m …

Balloon Borne Gps-Enabled Radiosondes That Enable Simultaneous Multi-Point Atmospheric Sensing With A Single Ground Station, Peter A. Ribbens

Doctoral Dissertations and Master's Theses

Radiosondes are balloon borne atmospheric instruments that are a critical tool for understanding dynamics in the lower layers of the atmosphere. The low-cost radiosondes developed in the Space and Atmospheric Instrumentation Lab have been further developed to improve the system's use as a science-quality atmospheric instrument that is unique in its ability to simultaneously track multiple sondes with a single ground station. Sensors to measure temperature and pressure were added to improve measurements of the atmospheric state. A printed circuit board shield and 3D-printed shell were designed to make mass manufacturing possible. A thermistor-based temperature sensor was developed and tested …

Creative Insights Into Motion: Enhancing Human Activity Understanding With 3d Data Visualization And Annotation, Isaac Browen, Hector M. Camarillo-Abad, Franceli L. Cibrian, Trudi Di Qi

Engineering Faculty Articles and Research

This paper presents a novel 3D system for human motion analysis - Motion Data Visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening …

Evaluating Visual Dependence In Postural Stability Using Smartphone And Stroboscopic Glasses, Brent A. Harper, Michael Shiraishi, Rahul Soangra

Physical Therapy Faculty Articles and Research

This study explores the efficacy of integrating stroboscopic glasses with smartphone-based applications to evaluate postural control, offering a cost-effective alternative to traditional forceplate technology. Athletes, particularly those with visual and visuo-oculomotor enhancements due to sports, often suffer from injuries that necessitate reliance on visual inputs for balance—conditions that can be simulated and studied using visual perturbation methods such as stroboscopic glasses. These glasses intermittently occlude vision, mimicking visual impairments that are crucial in assessing dependency on visual information for postural stability. Participants performed these tasks under three visual conditions: full vision, partial vision occlusion via stroboscopic glasses, and no vision …

Autonomous Apple Harvester Robot, Jack Ryan Cline, Tyus Green, Devon Woolston

Electrical Engineering

As agricultural demands rise and manual labor costs increase, there has become a dire need to automate apple harvesting. However, the precision and speed necessary for cost-efficient apple harvesting pose a significant challenge for robotic automation. To maintain cost-effective production, a harvester must be able to operate fast enough and long enough to compete with human labor. It must also be able to navigate and traverse apple orchards autonomously and pick apples without damaging the fruit or tree. This project presents an apple harvesting robot that uses a Mask R-CNN vision system with an RGB-D camera to detect the location …

Cal Poly Gen 2 Battlebot Electrical System, Kelvin C. Villago

Electrical Engineering

BattleBots is a popular robot combat sport where engineers from all over the world design and construct a robot with the aim to disable or impair the opposing robot. The Cal Poly Gen 2 BattleBot aims to complete a robot from scratch with hopes to compete in the official competition. This report focuses on the electronic design behind the robot, specifically the printed circuit board (PCB) and component selection. The design process of this project involved choosing specific motors and microcontrollers based on cost, efficiency, and benefits with the end goal of a complete printed circuit board (PCB). Brushed motors …

Machine Learning For Graph Algorithms And Representations, Allison Gunby-Mann

Dartmouth College Ph.D Dissertations

This thesis explores a variety of common graph theoretic problems from a machine learning perspective. The topics covered include fundamental network problems such as distance approximation, distance sensitivity, community detection, cross-network alignment, and graph embedding dimension reduction. These projects are unified by the theme of machine learning on graphs, graph embeddings, and representations of graphs.