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Full-Text Articles in Other Electrical and Computer Engineering

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 Oct 2024

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 …


Predictive Residual Neural Networks For Optical Trapping Of Small Particles, Nasim Mohammadi Estrakhri, Ponthea Zahraii, Saman Kashanchi, Nooshin M. Estakhri Oct 2024

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 Oct 2024

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 Sep 2024

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

Al-Bahir Journal for Engineering and Pure Sciences

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.


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 Aug 2024

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 …


Convex Approach To Data-Driven Optimal Control With Safety Constraints Using Linear Transfer Operator, Joseph Raphel Moyalan Aug 2024

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 …


Novel Polymer-Derived Ceramic Antennas For Hypersonic Applications, Peter J. Alley Aug 2024

Novel Polymer-Derived Ceramic Antennas For Hypersonic Applications, Peter J. Alley

Masters Theses

With recent advances in three dimensional [3D] printing of polymer-derived ceramics [PDCs], and the controllability of electrical continuity thereof, interest has risen in potential applications resultant from these techniques in the realm of radio communication, particularly in cases where extreme high temperatures are ambient. The following investigates the electrical properties of both insulating and conductive variants of these PDCs, the interaction between each, and the performance characteristics observed when combined using microstrip antenna design theory for high temperature applications.


Heat And Mass Transfer Characteristics During Vacuum Drying Of Wood, Mohamed Salah Elmetwaly, Lotfy Hassan Rabie Saker, Mohamed Sameh Salem Jul 2024

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 Jul 2024

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 Jun 2024

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 Jun 2024

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 Jun 2024

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 Jun 2024

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 …


Improving Fused Filament Fabrication Additive Manufacturing Through Computer Vision Analysis And Fabrication Optimization, Aliaksei Petsiuk May 2024

Improving Fused Filament Fabrication Additive Manufacturing Through Computer Vision Analysis And Fabrication Optimization, Aliaksei Petsiuk

Electronic Thesis and Dissertation Repository

Additive manufacturing (AM), also known as 3-D printing, is one of the fundamental elements of Industry 4.0. According to ASTM standards, AM can be classified by production principles, types of raw materials, energy sources, and fabrication volumes. Fused filament fabrication (FFF) is one of the most accessible technologies that offers independent manufacturers great opportunities due to its simplicity, scalability, and low cost.

Modern 3-D printing is moving from single-material prototyping to complex multi-material product creation. It is firmly established in a wide range of applications, significantly expanding manufacturing horizons, providing innovative design capabilities, and improving product quality through the optimal …


Machine Learning For Graph Algorithms And Representations, Allison Gunby-Mann May 2024

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.


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 May 2024

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 May 2024

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 May 2024

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

McKelvey School of Engineering 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 May 2024

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 …


Optimization Of Reactive Power Compensation Settings For Solar Power Plants In Volt/Var Mode, Samuel Eniola Aremu May 2024

Optimization Of Reactive Power Compensation Settings For Solar Power Plants In Volt/Var Mode, Samuel Eniola Aremu

Electronic Theses and Dissertations

Due to advancements in smart inverter technologies, distributed energy resources, such as solar photovoltaic systems, can contribute to network voltage and reactive power regulation in accordance with the IEEE 1547a standard. Depending on the penetration level, the solar photovoltaic system often causes a voltage rise at its connection point and surrounding nodes.

To resolve the voltage rise issue, utilities and developers use strategies like voltage/Var (Volt/Var) and voltage/wattage (Volt/Watt) control, among others. Some electric utilities prefer the Volt/Var control. During Volt/Var operation, PV inverters, based on the Volt/Var settings, can consume reactive power from the network when the voltage at …


Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach May 2024

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 …


Exploration Of Event-Based Camera Data With Spiking Neural Networks, Charles Peter Rizzo May 2024

Exploration Of Event-Based Camera Data With Spiking Neural Networks, Charles Peter Rizzo

Doctoral Dissertations

Neuromorphic computing is a novel, non-von Neumann computing architecture that employs power efficient spiking neural networks on specialized hardware. Taking inspiration from the human brain, spiking neural networks are temporal computation units that propagate information throughout the network via binary spikes. Compared to conventional artificial neural networks, these networks can be more sparse, smaller in size, and more efficient power-wise when realized on neuromorphic hardware. Event-based cameras are novel vision sensors that capture visual information through a temporal stream of events instead of as a conventional RGB frame. These cameras are low-power collections of pixels that asynchronously emit events over …


Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman May 2024

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 …


An Investigation Of Information Structures In Dna, Joel Mohrmann May 2024

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. …


Design And Optimization Of A Novel Monolithic Spring For High-Frequency Press-Pack Sic Fet Modules, Bogac Canbaz May 2024

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 …


Effectiveness Of Cnn-Lstm Models Used For Apple Stock Forecasting, Ethan White May 2024

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 Apr 2024

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

ATU Research 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.


Machine Learning Classifiers For Chronic Obstructive Pulmonary Disease Assessment Using Lung Ct Data., Halimah Alsurayhi Apr 2024

Machine Learning Classifiers For Chronic Obstructive Pulmonary Disease Assessment Using Lung Ct Data., Halimah Alsurayhi

Electronic Thesis and Dissertation Repository

Chronic Obstructive Pulmonary Disease (COPD) is a condition characterized by persistent inflammation and airflow blockages in the lungs, contributing to a significant number of deaths globally each year. To guide tailored treatment strategies and mitigate future risks, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) employs a multifaceted assessment system of COPD severity, considering patient's lung function, symptoms, and exacerbation history. COPD staging systems, such as the high-resolution eight-stage COPD system and the GOLD 2023 three staging systems, have been later developed based on these factors. Lung Computed Tomography (CT) is becoming increasingly crucial in investigating COPD as it …


Data-Driven Approaches For Enhancing Power Grid Reliability, Behrouz Sohrabi Mar 2024

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 Mar 2024

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 …