Physical Sciences and Mathematics Commons^™

Crash Detecting System Using Deep Learning, Yogesh Reddy Muddam

Electronic Theses, Projects, and Dissertations

Accidents pose a significant risk to both individual and property safety, requiring effective detection and response systems. This work introduces an accident detection system using a convolutional neural network (CNN), which provides an impressive accuracy of 86.40%. Trained on diverse data sets of images and videos from various online sources, the model exhibits complex accident detection and classification and is known for its prowess in image classification and visualization.

CNN ensures better accident detection in various scenarios and road conditions. This example shows its adaptability to a real-world accident scenario and enhances its effectiveness in detecting early events. A key …

Code For Care: Hypertension Prediction In Women Aged 18-39 Years, Kruti Sheth

Electronic Theses, Projects, and Dissertations

The longstanding prevalence of hypertension, often undiagnosed, poses significant risks of severe chronic and cardiovascular complications if left untreated. This study investigated the causes and underlying risks of hypertension in females aged between 18-39 years. The research questions were: (Q1.) What factors affect the occurrence of hypertension in females aged 18-39 years? (Q2.) What machine learning algorithms are suited for effectively predicting hypertension? (Q3.) How can SHAP values be leveraged to analyze the factors from model outputs? The findings are: (Q1.) Performing Feature selection using binary classification Logistic regression algorithm reveals an array of 30 most influential factors at an …

Traffic Analysis Of Cities In San Bernardino County, Sai Kalyan Ayyagari

Electronic Theses, Projects, and Dissertations

This research offers an in-depth analysis of vehicular traffic within San Bernardino County, California, aiming to spotlight congestion areas and suggest improvements for more efficient and sustainable transportation. Leveraging 2021 data from StreetLight Data, traffic patterns in 15 key cities were examined based on their population sizes, covering various vehicle types to dissect dynamics and flow. The methodology focused on analyzing trip purposes and metrics to calculate Vehicle Miles Traveled (VMT) and its influence on congestion and environmental factors.

Findings indicate considerable disparities in traffic volume, purposes, and timings across different urban areas, with population density and intercity connections significantly …

Artificial Intelligence's Ability To Detect Online Predators, Olatilewa Osifeso

Electronic Theses, Projects, and Dissertations

Online child predators pose a danger to children who use the Internet. Children fall victim to online predators at an alarming rate, based on the data from the National Center of Missing and Exploited Children. When making online profiles and joining websites, you only need a name, an email and a password without identity verification. Studies have shown that online predators use a variety of methods and tools to manipulate and exploit children, such as blackmail, coercion, flattery, and deception. These issues have created an opportunity for skilled online predators to have fewer obstacles when it comes to contacting and …

An Empirical Study On The Efficacy Of Llm-Powered Chatbots In Basic Information Retrieval Tasks, Naja Faysal

Electronic Theses, Projects, and Dissertations

The rise of conversational user interfaces (CUIs) powered by large language models (LLMs) is transforming human-computer interaction. This study evaluates the efficacy of LLM-powered chatbots, trained on website data, compared to browsing websites for finding information about organizations across diverse sectors. A within-subjects experiment with 165 participants was conducted, involving similar information retrieval (IR) tasks using both websites (GUIs) and chatbots (CUIs). The research questions are: (Q1) Which interface helps users find information faster: LLM chatbots or websites? (Q2) Which interface helps users find more accurate information: LLM chatbots or websites?. The findings are: (Q1) Participants found information significantly faster …

Leveraging Blockchain Technology To Revamp The Vehicle Electrification Journey: Perspectives Of Accountability And Economic Circularity, Eva Escobar Brown

Electronic Theses, Projects, and Dissertations

The automotive industry is undergoing a significant transition accelerated by global emission regulations for a phase out of internal combustion engines (ICEs) and a transition toward the adoption of electric vehicles (EVs). While regulatory measures and incentivized adoption for EVs presents opportunities for reducing emissions and promoting sustainability, it also poses complex challenges. The EV industry faces potential production challenges, particularly in the sourcing, manufacturing, and lifecycle management of critical minerals and raw materials for electric vehicle batteries (EVBs). With a heavy reliance on a steady and diversified supply of critical minerals such as lithium, cobalt and rare earth elements, …

Information Based Approach For Detecting Change Points In Inverse Gaussian Model With Applications, Alexis Anne Wallace

Electronic Theses, Projects, and Dissertations

Change point analysis is a method used to estimate the time point at which a change in the mean or variance of data occurs. It is widely used as changes appear in various datasets such as the stock market, temperature, and quality control, allowing statisticians to take appropriate measures to mitigate financial losses, operational disruptions, or other adverse impacts. In this thesis, we develop a change point detection procedure in the Inverse Gaussian (IG) model using the Modified Information Criterion (MIC). The IG distribution, originating as the distribution of the first passage time of Brownian motion with positive drift, offers …

Truck Traffic Analysis In The Inland Empire, Bhavik Khatri

Electronic Theses, Projects, and Dissertations

This study undertakes a meticulous examination of truck traffic within the Inland Empire, focusing on the distribution and dynamics of medium and heavy-duty vehicles, to advocate for the region's transition to electric trucks. Utilizing advanced spatial analysis and data from Streetlight Data, it segments the region into six subregions, revealing distinct traffic patterns and environmental impacts. Notably, the research uncovers that the North Center and West zones, integral to the logistics and warehousing sectors, exhibit the highest traffic volumes, significantly influencing air quality and infrastructure.

Quantitative results from 2021 illustrate a pronounced disparity in truck activity: medium-weight vehicles accounted for …

Classification Of Remote Sensing Image Data Using Rsscn-7 Dataset, Satya Priya Challa

Electronic Theses, Projects, and Dissertations

A novel technique for remote sensing image scene classification is employed using the Compact Vision Transformer (CVT) architecture. This model strengthens the power of deep learning and self-attention algorithms to significantly intensify the accuracy and efficiency of scene classification in remote sensing imagery. Through extensive training and evaluation of the RSSCNN7 dataset, our CVT-based model has achieved an impressive accuracy rate of 87.46% on the original dataset. This remarkable result underscores the prospect of CVT models in the domain of remote sensing and underscores their applicability in real-world scenarios. Our report furnishes an elaborate account of the model's architecture, training …

On Cheeger Constants Of Knots, Robert Lattimer

Electronic Theses, Projects, and Dissertations

In this thesis, we will look at finding bounds for the Cheeger constant of links. We will do this by analyzing an infinite family of links call two-bridge fully augmented links. In order to find a bound on the Cheeger constant, we will look for the Cheeger constant of the link’s crushtacean. We will use that Cheeger constant to give us insight on a good cut for the link itself, and use that cut to obtain a bound. This method gives us a constructive way to find an upper bound on the Cheeger constant of a two-bridge fully augmented link. …

Post-Wildfire Effects On A Headwater Stream In The San Bernardino National Forest, Kelley Giron

Electronic Theses, Projects, and Dissertations

Southern California has experienced prolonged drought conditions that have supported frequent wildfires that adversely impact ecosystems, natural resources, and human development. A primary consequence of these events is the impact on water quality and quantity. Of equal concern is evaluating how diverse land use configurations within a watershed can alter the physio-chemical properties of headwater reaches where drought and wildfire conditions are prevalent. To better understand the extent to which wildfires impact water quality and quantity across a headwater watershed, this study investigates wildfire impacts from the 2021 South Fire to Lytle Creek, a headwater stream of the Santa Ana …

Hypothyroid Disease Analysis By Using Machine Learning, Sanjana Seelam

Electronic Theses, Projects, and Dissertations

Thyroid illness frequently manifests as hypothyroidism. It is evident that people with hypothyroidism are primarily female. Because the majority of people are unaware of the illness, it is quickly becoming more serious. It is crucial to catch it early on so that medical professionals can treat it more effectively and prevent it from getting worse. Machine learning illness prediction is a challenging task. Disease prediction is aided greatly by machine learning. Once more, unique feature selection strategies have made the process of disease assumption and prediction easier. To properly monitor and cure this illness, accurate detection is essential. In order …

Disease Of Lung Infection Detection Using Cnn Model -Bayesian Optimization, Poojitha Gutha

Electronic Theses, Projects, and Dissertations

Auscultation plays a role, in diagnosing and identifying diseases during examinations. However, it requires training and expertise, for application. This study aims to tackle this challenge by introducing a model that categorizes respiratory sounds into eight groups: URTI, Healthy, Asthma, COPD, LRTI, Bronchiectasis, Pneumonia, and Bronchiolitis. To achieve this categorization the study utilizes a Convolutional Neural Network (CNN) model that has been optimized using techniques. The dataset used in the study consists of 920 audio samples obtained from 126 patients with durations ranging from 10 to 90 seconds. Impressively, the model demonstrates a noteworthy 83% validation accuracy and an impressive …

Analysis And Assessment Of Land Use / Land Cover Impact On Human And Natural Ecosystems In The Salton Sea Watershed, 2013 - 2021, Diego Ramirez

Electronic Theses, Projects, and Dissertations

This study represents an interdisciplinary analysis of the changing landscape of the Salton Sea Watershed from 2013 to 2021, focusing on land use land cover (LULC) category changes, climatic variations, and socioeconomic factors. The findings of this research show a shift in land cover categories, portrayed by the changes of natural landscapes and vegetative areas into rapidly increasing urbanized expansion and increased impervious surfaces. These changes pose concerns about increased temperature in the region, a decrease in overall water availability and groundwater infiltration, and an increase in pollution. The study explores 10 sub-watersheds within the Salton Sea Watershed basin, focusing …

Twitter Policing, Hemanth Kumar Medisetty

Electronic Theses, Projects, and Dissertations

Police departments are frequently utilizing social media platforms to actively interact with the public. Social media offers an opportunity to share information, facilitate communication, and foster stronger connections between police departments and the communities they serve. In this context sentiment analysis of social media data has become a tool, for identifying sentiments and tracking emerging trends.

This project utilizes sentiment analysis to examine the social media interactions with particular data obtained from the Twitter (X). Initially, the project gathers social media data, from twitter mentioned accounts on Twitter utilizing web scraping techniques. Afterwards, we perform a thorough sentiment analysis using …

Predictive Model For Cfpb Consumer Complaints, Vyshnavi Nalluri

Electronic Theses, Projects, and Dissertations

Within the dynamic and highly competitive financial industry, the timely and efficient resolution of customer complaints stands as a central challenge, particularly in the intricate domain of mortgage services. The traditional processes for handling these complaints have long been recognized as laborious and resource-intensive, a situation that financial institutions, including the esteemed Wells Fargo, are keen to improve.

Currently, the industry largely relies on basic data analytics for identifying trends in customer complaints. However, this approach has its limitations, especially when dealing with complaints within the mortgage services domain. In response to this challenge, this research advocates the adoption of …

Statistical Analysis Of Health Habits For Incoming College Students, Wendy Isamara Lizarraga Noriega

Electronic Theses, Projects, and Dissertations

Health habits among college students are commonly overseen, especially for students transitioning from high school right into college. These students are becoming independent young adults, and learning how to adapt to a different scenery when it comes to their learning environment. As these young adults transition into college, this is the perfect time for the students to become more vulnerable and comfortable with their independence, and their weight begins to fluctuate. Many variables come into consideration when increasing weight as an incoming first-year student. Students are more likely to live alone, get a job, and rely on fast food and …

An Exposition Of The Curvature Of Warped Product Manifolds, Angelina Bisson

Electronic Theses, Projects, and Dissertations

The field of differential geometry is brimming with compelling objects, among which are warped products. These objects hold a prominent place in differential geometry and have been widely studied, as is evident in the literature. Warped products are topologically the same as the Cartesian product of two manifolds, but with distances in one of the factors in skewed. Our goal is to introduce warped product manifolds and to compute their curvature at any point. We follow recent literature and present a previously known result that classifies all flat warped products to find that there are flat examples of warped products …

General Population Projection Model With Census Population Data, Takenori Tsuruga

Electronic Theses, Projects, and Dissertations

The US Census Bureau offers a wide range of data, and within this array, the American Community Survey 5-Year Estimate (ACS5) serves as a valuable resource for understanding the US population. This project embarks on an exploration of Machine Learning and the Software Development process with the goal of generating effective population projections from ACS5 data. The project aims to provide methods to make predictions for every city and town in the US, encompassing their total population and population divided into 5-year age groups. It's worth noting that while the generation of these projections is grounded in the generalized statistical …

Review Classification Using Natural Language Processing And Deep Learning, Brian Nazareth

Electronic Theses, Projects, and Dissertations

Sentiment Analysis is an ongoing research in the field of Natural Language Processing (NLP). In this project, I will evaluate my testing against an Amazon Reviews Dataset, which contains more than 100 thousand reviews from customers. This project classifies the reviews using three methods – using a sentiment score by comparing the words of the reviews based on every positive and negative word that appears in the text with the Opinion Lexicon dataset, by considering the text’s variating sentiment polarity scores with a Python library called TextBlob, and with the help of neural network training. I have created a neural …

Dna Self-Assembly Of Trapezohedral Graphs, Hytham Abdelkarim

Electronic Theses, Projects, and Dissertations

Self-assembly is the process of a collection of components combining to form an organized structure without external direction. DNA self-assembly uses multi-armed DNA molecules as the component building blocks. It is desirable to minimize the material used and to minimize genetic waste in the assembly process. We will be using graph theory as a tool to find optimal solutions to problems in DNA self-assembly. The goal of this research is to develop a method or algorithm that will produce optimal tile sets which will self-assemble into a target DNA complex. We will minimize the number of tile and bond-edge types …

Restaurant Management Website, Akhil Sai Gollapudi

Electronic Theses, Projects, and Dissertations

In the ever-evolving corporate landscape of today, it is crucial to respond to customer needs as efficiently and in a timely manner as possible. The project's primary objective is to create a method for clients to make reservations for restaurants online. This makes life easier for busy customers in their daily life.

Today, people are looking for comfort thanks to rapidly developing technology. As we can see, people invent and implement new technologies in all fields according to customer needs.

We got a unique restaurant idea that helps people save time. People prefer quick methods to get things done. With …

Web Based Management System For Housing Society, Likhitha Reddy Eddala

Electronic Theses, Projects, and Dissertations

Web Based Management System for Housing Society plays a major role in our day-to-day life. We develop a global web dependent application using AngularJS, Node JS and MySQL, with Xampp as the server to make an effective management system. This system is designed to provide a user-friendly and efficient platform for managing all the details of daily notices, monthly meetings, events, payments, maids etc., This system mainly consists of three modules, they are: Admin, User and Security. Each module here serves specific features and functionalities present within society. Admin module provides the features for managing user, houses, security, maids, notices, …

Contactless Food Ordering System, Rishivar Kumar Goli

Electronic Theses, Projects, and Dissertations

Contactless food ordering has revolutionized the way a customer interacts with restaurants by allowing them to place orders and make transactions. Through these web-based platforms, customers can now browse menus, customize orders, and make payments seamlessly. By scanning the restaurant’s QR code, customers can reserve a table. If the table is available, then automatically it will be reserved. However, if the table is occupied the customer will be added to the waiting list. Once the customer selects desired food then they can securely make payments based on ordered food items. The food will be delivered straight to the customer's table. …

Geospatial Wildfire Risk Prediction Using Deep Learning, Abner Alberto Benavides

Electronic Theses, Projects, and Dissertations

This report introduces a thorough analysis of wildfire prediction using satellite imagery by applying deep learning techniques. To find wildfire-prone geographical data, we use U-Net, a convolutional neural network known for its effectiveness in biomedical image segmentation. The input to the model is the Sentinel-2 multispectral images to supply a complete view of the terrain features.

We evaluated the wildfire risk prediction model’s performance using several metrics. The model showed high accuracy, with a weighted average F1 score of 0.91 and an AUC-ROC score of 0.972. These results suggest that the model is exceptionally good at predicting the location of …

Aerosol Mutagenicity In San Bernardino, California Via Bacterial Fluctuation Tests, Sean Murphy

Electronic Theses, Projects, and Dissertations

San Bernardino, California’s poor air quality is a health risk to its population with some of the highest concentrations of ozone and aerosol in the United States. Aerosols are solid or liquid particles suspended in the air. Smaller aerosol particles are the most harmful as they are more likely to penetrate further into the respiratory system. These aerosols can cause respiratory issues and contain toxic compounds. One measure of aerosol toxicity is to study the mutagenicity of the aerosol. To study the mutagenicity of aerosol samples collected in San Bernardino in 2022, fluctuation tests (based on the Ames test for …

Genetic Programming To Optimize Performance Of Machine Learning Algorithms On Unbalanced Data Set, Asitha Thumpati

Electronic Theses, Projects, and Dissertations

Data collected from the real world is often imbalanced, meaning that the distribution of data across known classes is biased or skewed. When using machine learning classification models on such imbalanced data, predictive performance tends to be lower because these models are designed with the assumption of balanced classes or a relatively equal number of instances for each class. To address this issue, we employ data preprocessing techniques such as SMOTE (Synthetic Minority Oversampling Technique) for oversampling data and random undersampling for undersampling data on unbalanced datasets. Once the dataset is balanced, genetic programming is utilized for feature selection to …

Mathematics Behind Machine Learning, Rim Hammoud

Electronic Theses, Projects, and Dissertations

Artificial intelligence (AI) is a broad field of study that involves developing intelligent
machines that can perform tasks that typically require human intelligence. Machine
learning (ML) is often used as a tool to help create AI systems. The goal of ML is
to create models that can learn and improve to make predictions or decisions based on given data. The goal of this thesis is to build a clear and rigorous exposition of the mathematical underpinnings of support vector machines (SVM), a popular platform used in ML. As we will explore later on in the thesis, SVM can be implemented …

Jackknife Empirical Likelihood Tests For Equality Of Generalized Lorenz Curves, Anton Butenko

Electronic Theses, Projects, and Dissertations

A Lorenz curve is a graphical representation of the distribution of income or wealth within a population. The generalized Lorenz curve can be created by scaling the values on the vertical axis of a Lorenz curve by the average output of the distribution. In this thesis, we propose two nonparametric methods for testing the equality of two generalized Lorenz curves. Both methods are based on empirical likelihood and utilize a U -statistic. We derive the limiting distribution of the likelihood ratio, which is shown to follow a chi-squared distribution with one degree of freedom. We conduct simulations to compare the …

Late Holocene Slip History Of The Central Garlock Fault, Mojave Desert, California, James Eric Burns

Electronic Theses, Projects, and Dissertations

This study investigates the late Holocene slip history of the central Garlock Fault, using measurements of left-lateral offsets of alluvial features from airborne and hand-held LiDAR imagery, drone photogrammetry, and field measurements. IRSL dating of the offset late Holocene alluvial deposits was compared to published paleoseismic records to estimate the number of earthquakes that contributed to the offsets. Focus was given to geomorphic features offset in the past 1-4 earthquakes. Results indicate the average slip per earthquake was about 5.75 m (range: 4.75 to 6.25 m) in the past four events in the El Paso Mountains (EPM) and was 4.3-7.3 …