Physical Sciences and Mathematics Commons^™

Gt-Ches And Dycon: Improved Classification For Human Evolutionary Systems, Joseph S. Johnson

Theses and Dissertations

The purpose of this work is to rethink the process of learning in human evolutionary systems. We take a sober look at how game theory, network theory, and chaos theory pertain specifically to the modeling, data, and training components of generalization in human systems. The value of our research is three-fold. First, our work is a direct approach to align machine learning generalization with core behavioral theories. We made our best effort to directly reconcile the axioms of these heretofore incompatible disciplines -- rather than moving from AI/ML towards the behavioral theories while building exclusively on AI/ML intuition. Second, this …

Predictive Machine Learning And Its Future In Professional Basketball, Zachary Harmon

Honors College Theses

Artificial Intelligence (AI) is an ever-evolving field, transforming various aspects of contemporary life. From language models to immersive gaming experiences, AI technologies have become integral to our daily existence. Among the most promising arenas for AI integration is the world of sports. This research delves into the application of machine learning models to predict NBA game outcomes, shedding light on the profound impact of machine learning in the realm of professional basketball. Beyond the scope of game prediction, this study explores the broader implications, such as optimizing the selection of televised games, assisting players in showcasing their skills, and much …

Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan

Computer Science Senior Theses

We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …

Algorithmic Bias: Causes And Effects On Marginalized Communities, Katrina M. Baha

Undergraduate Honors Theses

Individuals from marginalized backgrounds face different healthcare outcomes due to algorithmic bias in the technological healthcare industry. Algorithmic biases, which are the biases that arise from the set of steps used to solve or analyze a problem, are evident when people from marginalized communities use healthcare technology. For example, many pulse oximeters, which are the medical devices used to measure oxygen saturation in the blood, are not able to accurately read people who have darker skin tones. Thus, people with darker skin tones are not able to receive proper health care due to their pulse oximetry data being inaccurate. This …

Universal Back-End Design, Jason Kalili

LMU/LLS Theses and Dissertations

Accessibility in back-end development is often overlooked, with the majority of discussions and efforts centered on front-end design. To make applications usable for a wider audience, developers must also prioritize incorporating accessibility from the back-end. Back-end web accessibility encompasses the design and development of web-based systems and applications that are accessible to all users, including those with disabilities. This involves optimizing the underlying code and infrastructure for accessibility and implementing features that enable users with disabilities to navigate and interact with the site or application. Ensuring back-end web accessibility is crucial for creating an inclusive online environment accessible to everyone, …

Making Music Social: Creating A Spotify-Based Social Media Platform, Dalton J. Craven

Senior Theses

DKMS is a new type of social media platform for music lovers and groups of friends. It integrates tightly with Spotify, one of the largest music streaming services in the world. Users of DKMS can see what their friends are listening to, receive recommendations of new songs to listen to, and analyze their several key numerical metrics (happiness, danceability, loudness, and energy) of their top songs.

DKMS was built as part of the year-long Capstone senior design course at the University of South Carolina. A deployed app is visible at https://dkms.vercel.app, and the open-source code is visible at https://github.com/SCCapstone/DKMS.

Making Sense Of Big (Kinematic) Data: A Comprehensive Analysis Of Movement Parameters In A Diverse Population, Naomi Wilma Nunis

University of the Pacific Theses and Dissertations

OBJECTIVE

The purpose of this study was to determine how kinematic, big data can be evaluated using computational, comprehensive analysis of movement parameters in a diverse population.

METHODS

Retrospective data was collected, cleaned, and reviewed for further analysis of biomechanical movement in an active population using 3D collinear resistance loads. The active sample of the population involved in the study ranged from age 7 to 82 years old and respectively identified as active in 13 different sports. Moreover, a series of exercises were conducted by each participant across multiple sessions. Exercises were measured and recorded based on 6 distinct biometric …

Randomized Algorithms For Resource Allocation In Device To Device Communication., Subhankar Ghosal Dr.

Doctoral Theses

In device to device (D2D) communication, two users residing in close proximity can directly communicate between them, through a common channel, without the need of a base station. A pair of D2D users forms a link and a channel needs to be allocated to it. The interference relationship among the active links at time t is modelled as an interference graph g(t). To establish interference-free communication, we have to assign a channel vector C(t) and a power vector corresponding to the active links such that the required signal to interference plus noise ratio (SINR) is satisfied for each link. Since …

Obstacles In Learning Algorithm Run-Time Complexity Analysis, Bailey Licht

Theses/Capstones/Creative Projects

Algorithm run-time complexity analysis is an important topic in data structures and algorithms courses, but it is also a topic that many students struggle with. Commonly cited difficulties include the necessary mathematical background knowledge, the abstract nature of the topic, and the presentation style of the material. Analyzing the subject of algorithm analysis using multiple learning theories shows that course materials often leave out key steps in the learning process and neglect certain learning styles. Students can be more successful at learning algorithm run-time complexity analysis if these missing stages and learning styles are addressed.

Constructions And Analyses Of Efficient Symmetric-Key Primitives For Authentication And Encryption., Sebati Ghosh Dr.

Doctoral Theses

In symmetric key cryptography there are two fundamental objectives, viz. 1. confidentiality or secrecy of message from unexpected party and 2. authentication of message which includes authenticating the source of the message as well as integrity of the message against any unwanted modification. Let us first concentrate on confidentiality. In classical symmetric key cryptography two parties, say Alice and Bob, first secretly exchange a key-pair (e, d). Later, if Alice wishes to send a secret message m ∈ M to Bob, she computes c = Ee(m) and transmits c to Bob. Upon receiving c, Bob computes Dd(c) = m and …

Morphological Network: Network With Morphological Neurons., Ranjan Mondal Dr.

Doctoral Theses

Image processing with traditional approaches mainly use the tools of linear systems. However, linear approaches are not well suited and may even fail to solve problems involving geometrical aspects of the image. Thus, nonlinear geometric approaches like morphological operations are very popular in those cases. Morphological operations are nonlinear operations based on a set and lattice-theoretic methodology for image analysis that are capable of describing the geometrical structure of image objects quantitatively. It is suitable for various problems in image processing, computer vision, and pattern recognition. While solving problems with morphology, a particular structuring element is defined. Structuring elements have …

Computing Well-Structured Subgraphs In Geometric Intersection Graphs., Satyabrata Jana Dr.

Doctoral Theses

For a set of geometric objects, the associative geometric intersection graph is the graph with a vertex for each object and an edge between two vertices if and only if the corresponding objects intersect. Geometric intersection graphs are very important due to their theoretical properties and applicability. Based on the different geometric objects, several types of geometric intersection graphs are defined. Given a graph G, an induced (either vertex or edge) subgraph H ⊆ G is said to be an well-structured subgraph if H satisfies certain properties among the vertices in H. This thesis studies some well-structured subgraphs finding problems …

Temporal Sentiment Mapping System For Time-Synchronized Data, Jiachen Ma

Dissertations (1934 -)

Temporal sentiment labels are used in various multimedia studies. They are useful for numerous classification and detection tasks such as video tagging, segmentation, and labeling. However, generating a large-scale sentiment dataset through manual labeling is usually expensive and challenging. Some recent studies explored the possibility of using online Time-Sync Comments (TSCs) as the primary source of their sentiment maps. Although the approach has positive results, existing TSCs datasets are limited in scale and content categories. Guidelines for generating such data within a constrained budget are yet to be developed and discussed. This dissertation tries to address the above issues by …

Understanding User Perceptions Of Voice Personal Assistants, Ha Young Kim

All Theses

As the artificial intelligence (AI) technique improves, voice assistant (smart speaker) such as Amazon Alexa and Google Assistant are quickly, surely permeating into people's daily lives. With its powerful and convenient benefits and the circumstances that people started to stay at their home longer due to the pandemic, reliance on smart speakers has increased rapidly. But at the same time, concerns of security on smart speakers have increased.

In this thesis, we conducted an online user survey of smart speaker users with five different perspectives – 1) Users’ engagement with privacy policy; 2) Awareness of different policy requirements defined by …

Simulating Polistes Dominulus Nest-Building Heuristics With Deterministic And Markovian Properties, Benjamin Pottinger

Undergraduate Honors Theses

European Paper Wasps (Polistes dominula) are social insects that build round, symmetrical nests. Current models indicate that these wasps develop colonies by following simple heuristics based on nest stimuli. Computer simulations can model wasp behavior to imitate natural nest building. This research investigated various building heuristics through a novel Markov-based simulation. The simulation used a hexagonal grid to build cells based on the building rule supplied to the agent. Nest data was compared with natural data and through visual inspection. Larger nests were found to be less compact for the rules simulated.

Efficient Handover Mechanisms For Heterogeneous Networks., Shankar Kumar Ghosh Dr.

Doctoral Theses

In this thesis, some analytical frameworks have been developed to analyze the effect of different system parameters on handover performances in heterogeneous network (HetNet) and based on such frameworks, some efficient handover algorithms have been proposed. The study starts with an analytical framework to investigate the effect of resource allocation mechanisms, upper layer mobility management protocols (MMPs) and handover decision metrics on user perceived throughput. This analysis reveals that among other factors, handover decision metric plays a crucial role in determining user perceived throughput in HetNet. Subsequently, we develop two handover decision metrics for ultra dense networks (UDN) and unlicensed …

Cook-It!: A Web Application For Easy Meal Planning, Carol Juneau

Senior Theses

Cook-it! is a web application for meal planning based on the Django framework and deployed on the Heroku platform. This application has an intuitive interface to make it easy to use. The project has been developed over two semesters, roughly separated into a planning phase and an implementation phase. Cook-it! incorporates a robust feature set and an attractive design. Its core purpose is to make it easy for users to plan meals, interact with other users, and keep track of user information such as a grocery list.

Zero-Knowledge Proof, Deniability And Their Applications In Blockchain, E-Voting And Deniable Secret Handshake Protocols., Somnath Panja Dr.

Doctoral Theses

In this thesis, we propose a cryptographic technique for an authenticated, end-to-end verifiable and secret ballot election. Currently, almost all verifiable e-voting systems require trusted authorities to perform the tallying process except for the DRE-i and DRE-ip systems. We have shown a weaknesses in the DRE-ip system and proposed a solution. We have modified the DRE-ip system so that no adversary can create and post a valid ballot on the public bulletin board without detection. We provide security proofs to prove the security properties of the proposed scheme. We propose two methods to store these ballots using blockchain and cloud …

Many-Objective Evolutionary Algorithms: Objective Reduction, Decomposition And Multi-Modality., Monalisa Pal Dr.

Doctoral Theses

Evolutionary Algorithms (EAs) for Many-Objective Optimization (MaOO) problems are challenging in nature due to the requirement of large population size, difficulty in maintaining the selection pressure towards global optima and inability of accurate visualization of high-dimensional Pareto-optimal Set (in decision space) and Pareto-Front (in objective space). The quality of the estimated set of Pareto-optimal solutions, resulting from the EAs for MaOO problems, is assessed in terms of proximity to the true surface (convergence) and uniformity and coverage of the estimated set over the true surface (diversity). With more number of objectives, the challenges become more profound. Thus, better strategies have …

Mathematical Formulations For Complex Resource Scheduling Problems., T. R. Lalita Dr.

Doctoral Theses

This thesis deals with development of effective models for large scale real-world resource scheduling problems. Efficient utilization of resources is crucial for any organization or industry as resources are often scarce. Scheduling them in an optimal way can not only take care of the scarcity but has potential economic benefits. Optimal utilization of resources reduces costs and thereby provides a competitive edge in the business world. Resources can be of different types such as human (personnel-skilled and unskilled), financial(budgets), materials, infrastructures(airports and seaports with designed facilities, windmills, warehouses’ area, hotel rooms etc) and equipment (microprocessors, cranes, machinery, aircraft simulators for …

On Class Imbalanced Learning:Design Of Non-Parametricclassifiers, Performance Indices, And Deep Oversampling Strategies., Sankha Mullick Dr.

Doctoral Theses

The relevance of classification is almost endless in the everyday application of machine learning. However, the performance of a classifier is only limited to the fulfillment of the inherent assumptions it makes about the training examples. For example, to facilitate unbiased learning a classifier is expected to be trained with an equal number of labeled data instances from all of the classes. However, in a large number of practical applications such as anomaly detection, semantic segmentation, disease prediction, etc. it may not be possible to gather an equal number of diverse training points for all the classes. This results in …

Optimal Eavesdropping In Quantum Cryptography, Atanu Acharyya Dr.

Doctoral Theses

Quantum key distribution (QKD) has raised some promise for more secured communication than its classical counterpart. It allows the legitimate parties to detect eavesdropping which introduces error in the channel. If disturbed, there are ways to distill a secure key within some threshold error-rate. The amount of information gained by an attacker is generally quantified by (Shannon) mutual information. Knowing the maximum amount of information that an intruder can gain is important for post-processing purposes, and we mainly focus on that side in the thesis. Renyi information is also useful especially when post-processing is considered. The scope of this thesis …

Utilization Of Virtual Reality For General Education Purposes, Amit Lal

University of the Pacific Theses and Dissertations

The use of Virtual Reality (VR) in a variety of professional, military, governmental, and educational fields has continued to expand over the past several decades, and the recent Covid-19 pandemic has brought attention to this field. This study surveys 154 college students over 23 questions that include various demographics that can be used to look for discriminators, multiple-choice VR-related questions, as well as a few free-form questions about use of VR in learning environments. The students’ experience with, interest in, and thoughts on how to best use VR vary considerably. The Covid-19 pandemic is found to have limited impact thus …

Secret Sharing And Its Variants, Matroids,Combinatorics., Shion Samadder Chaudhury Dr.

Doctoral Theses

The main focus of this thesis is secret sharing. Secret Sharing is a very basic and fundamental cryptographic primitive. It is a method to share a secret by a dealer among different parties in such a way that only certain predetermined subsets of parties can together reconstruct the secret while some of the remaining subsets of parties can have no information about the secret. Secret sharing was introduced independently by Shamir [139] and Blakely [20]. What they introduced is called a threshold secret sharing scheme. In such a secret sharing scheme the subsets of parties that can reconstruct a secret …

Some Nonparametric Hybrid Predictive Models : Asymptotic Properties And Applications., Tanujit Chakraborty Dr.

Doctoral Theses

Prediction problems like classification, regression, and time series forecasting have always attracted both the statisticians and computer scientists worldwide to take up the challenges of data science and implementation of complicated models using modern computing facilities. But most traditional statistical and machine learning models assume the available data to be well-behaved in terms of the presence of a full set of essential features, equal size of classes, and stationary data structures in all data instances, etc. Practical data sets from the domain of business analytics, process and quality control, software reliability, and macroeconomics, to name a few, suffer from various …

Space Science And Social Media: Automating Science Communication On Twitter, Maia Williams

Honors Projects

This project analyzes how social media is used to engage general audiences in astronomy and space science, as well as ways to improve engagement through automation. Tweets from five space science organizations were sampled. The engagement rate for each tweet was calculated from the number of interactions it received. Accounts that tweet more per day had more followers, and accounts with more followers received more interactions. This project also investigated how to build a Twitter bot to automate science communication. Using NASA Application Programming Interfaces, a Twitter bot was written in Python to tweet images taken by the NASA Mars …

Actors For The Internet Of Things, Arjun Shukla

Boise State University Theses and Dissertations

The actor model is a model for concurrent computation, centered around message passing between entities in a system. It is well suited for distributed programming, due to its semantics including very little guarantees or assumptions of reliability. Actor model implementations have grown more widespread in many languages.

The library Akka (written in Scala) is one of the most popular actor libraries. However, Akka is missing some key features. Our goal is to create our own actor library called Aurum, which not only has these features but exhibits higher performance. The new features include easy ways to forge references, configure and …

Dealing With Classification Irregularities In Real-World Scenarios., Payel Sadhukhan Dr.

Doctoral Theses

Data processing by the human sensory system comes naturally. This processing, commonly denoted as pattern recognition and analysis are carried out spontaneously by humans. In day to day life, in most cases, decision making by humans come without any conscious effort. From the middle of the past century, humans have shown interest to render their abstraction capabilities (pattern recognition and analysis) to the machine. The abstraction capability of the machine is ’machine intelligence’ or ’machine learning’ [87].The primary goal of machine learning methods is to extract some meaningful information from the ’data’. Data refers to the information or attributes that …

Studies On Diagnostic Coverage And X-Sensitivity In Logic Circuits., Manjari Pradhan Dr.

Doctoral Theses

Today’s integrated circuits comprise billions of interconnected transistors assembled on a tiny silicon chip, and testing them to ensure functional and timing correctness continues to be a major challenge to designers and test engineers with further downscaling of transistors. Although substantial progress has been witnessed during the last five decades in the area of algorithmic test generation and fault diagnosis, applications of combinatorial and machinelearning (ML) techniques to solve these problems remain largely unexplored till date. In this thesis, we study three problems in the context of digital logic test and diagnosis. The first problem is that of fault diagnosis …

Investigating Pre-Service Teachers’ Perceptions Of The Virginia Computer Science Standards Of Learning: A Qualitative Multiple Case Study, Valerie Sledd Taylor

Educational Foundations & Leadership Theses & Dissertations

Computer science education is being recognized globally as necessary to better prepare students in all grade levels, K-12, for future success. As a result of this focus on computer science education in the United States and around the world, there is an increased demand for highly qualified teachers with content and pedagogical knowledge to successfully support student learning. As a result, there is a call to include and improve the computer science training offered to pre-service teachers in their educator preparation programs from methods courses to practicum and student teaching experiences. Thus, it is important to understand how pre-service teachers …