Other Computer Sciences Commons^™

Educational Opportunities Of Participatory Gis For Accessibility On A College Campus, Shiya Cao, Heather Rosenfeld, Sarah Susnea

Statistical and Data Sciences: Faculty Publications

The educational benefits of Participatory GIS (PGIS) in geographic higher education have received limited direct attention, often because of the complexities of integrating PGIS into university curricula. While a few exceptions found important educational benefits of PGIS, extant studies focused primarily on the educational benefits for students who worked in the research teams, instead of participants who contributed their local knowledge and perspectives to mapping. Our research aims to understand the educational benefits of PGIS for participants in a campus accessibility mapping project using the modes of experiential learning, positionality, and service learning. Through this, we also provide strategies for …

Dynamic Mutational Profiling Of Binding Interactions And Allosteric Networks In Conformational Ensembles Of The Sars-Cov-2 Spike Protein Complexes With Classes Of Antibodies Targeting Cryptic Binding Sites: Confluence Of Binding And Allostery Determines Molecular Mechanisms And Hotspots Of Immune Escape, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The ongoing evolution of SARS-CoV-2 variants has underscored the need to understand not only the structural basis of antibody recognition but also the dynamic and allosteric mechanisms that could underlie complexity of broad and escape-resistant neutralization. In this study, we employed a multi-scale approach integrating structural analysis, hierarchical molecular simulations, mutational scanning and network-based allosteric modeling to dissect how Class 4 antibodies (represented by S2X35, 25F9, and SA55) and Class 5 antibodies (represented by S2H97, WRAIR-2063 and WRAIR-2134) can modulate conformational behavior, binding energetics, allosteric interactions and immune escape patterns of the SARS-CoV-2 spike protein. Using hierarchical simulations of the …

Optimizing Sensor Placement For Drone Detection According To A Grid Pattern, António Martinho Do Rosário Marçal

Masters Theses

In applications such as drone detection, it’s essential to place sensors efficiently, not only considering the cost of placement and operation, but also the maximization of the area covered.

This study presents an algorithmic approach to a placement strategy, which can be applied over any arbitrary area by defining the parameters of the grid according to which the sensors will be placed. The problem is framed as a multi-objective optimization task, considering trade-offs between sensor count and coverage.

One of the principal decision variables chosen is the shape of the cell blocks of the grid, for which two different values …

Fact-Checker: A Web Application For Leveraging Large Language Models For Fact-Checking Youtube Videos, Andrew R. Craig

Electronic Theses, Projects, and Dissertations

Fact-Checker is a web application that allows users to fact-check YouTube videos. It feeds YouTube’s closed captioning transcript to a large language model (LLM) to extract claims. It then uses multiple LLMs, such as Gemini, Llama, and Claude, to verify these claims. The modular design makes it easy to change to a different LLM or model if needed. The application is built using Python for access to Application Programming Interfaces (APIs) and Streamlit as the front-end framework. The utilization of Docker and Dockerfiles enables easy distribution and deployment. It enables the application to be deployed on almost any hardware platform …

Predicting Music Origin With Deep Learning, Fruzsina Ladanyi

Electronic Theses, Projects, and Dissertations

This project explores the usage of a late fusion deep learning architecture to predict the geographic origin of music. Mel-Frequency Cepstral Coefficients (MFCCs) and the language of the music sample are used as features. MFCCs were extracted from audio files to capture sound features. The language was identified using OpenAI’s Whisper model to provide additional context. A late fusion neural network architecture combining Long Short-Term Memory (LSTM) layers for sequential MFCC input and dense layers for non-sequential language features were employed to support both classification and regression tasks. The classification model achieved an accuracy of 33.03% across 56 countries or …

Revolutionizing Digital Privacy Education For Older Adults: Enhanced Interventions And Ai-Assisted Learning Strategies, Heba Aly

All Dissertations

As older adults increasingly engage with digital platforms, they face unique privacy risks stemming from limited digital literacy, reduced trust in AI technologies, and constrained access—especially in rural or underserved communities. While digital tools offer benefits like social connection and information access, current privacy education efforts often neglect the needs of older adults. This dissertation addresses this gap by developing, testing, and refining digital privacy education interventions tailored for older adults, with a focus on trust, personalization, and AI-assisted learning.

Study 1 evaluates multiple instructional modalities across age groups, revealing older adults prefer structured videos and interactive tutorials, while younger …

Out-Of-Band Anomaly Detection For Real Time Operating Systems, Jeffrey K. Holifield

Graduate Theses and Dissertations (2019 - present)

Real Time Operating Systems (RTOS) are increasing present throughout the industrial, business, defense, and healthcare spaces. These lightweight and efficient operating systems are designed to run on embedded, resource constrained devices, often within cyber-physical systems (CPS). A defining characteristic ofRTOSs is that they are deterministic. Tasks are scheduled to run on fixed timelines within guaranteed execution windows. In Industry 4.0 applications for example, sensors must receive and process inputs within a fixed schedule to ensure products are properly manufactured. This requires guaranteed service at fixed time periods. To accomplish this, RTOSs must conform to worst case execution times (WCETs) as …

Optimizing Distributed Boundary Exchanges For Benchmarks, Solvers And Sparse Matrix Operations, Gerald Collom

Computer Science ETDs

Boundary exchanges dominate the cost of both stenciled codes and those that rely on sparse matrix operations. The performance of large boundary exchanges is limited by synchronization overheads and injection bandwidth limitations. Irregular boundary exchanges incur additional overheads due to the large number of required messages. This thesis investigates multiple methods for improving the performance and scalability of both Cartesian and irregular boundary exchanges. Since boundary exchanges are typically performed iteratively, persistent communication presents an opportunity for optimization by sharing and amortizing setup costs. Partitioned communication is also explored to increase asynchrony, reducing bottlenecks from synchronization overheads and data congestion. …

Exploring Adversarial Threats To Neuralhash: A Perceptual Hashing Algorithm, Gurleen Kaur

Student Theses

Perceptual hashing algorithms are algorithms that generate content-based image hashes by extracting perceptual features from the images. Unlike cryptographic hashes, which exhibit significant changes with even slight input alterations, perceptual hashes do not change when modifications like compression, color correction and brightness are applied to the images. These hashes are designed to remain similar for inputs that are visually or perceptually alike, which has led to their widespread application in detecting duplicate images, finding similar images for reverse image search and to detecting inappropriate content of Child sexual abuse (CSAM) images by comparing image hashes with dataset of known perceptual …

Multiscale Modeling And Dynamic Mutational Profiling Of Binding Energetics And Immune Escape For Class I Antibodies With Sars-Cov-2 Spike Protein: Dissecting Mechanisms Of High Resistance To Viral Escape Against Emerging Variants, Mohammed Alshahrani, Vedant Parikh, Brandon Foley, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope …

Legislative And Security Confrontation Of Crimes Artificial Intelligence In The State Of Kuwait (An Analytical Study), Rashid Mohammed Al Marri

Journal of Police and Legal Sciences

The study aimed to demonstrate the mechanisms of legislative and security confrontation of artificial intelligence crimes. The use of technologies associated with artificial intelligence may go beyond the imposed limits, whether by exploiting it through its program developers & specialists to commit crimes in the cyber field, or it may be with the growing capabilities of artificial intelligence to make decisions in the field. Many behaviors occur automatically. Our research also aims to study the criminal responsibility for these crimes, & determine it in order to hold the real perpetrator accountable in accordance with the legal rules in force to …

Coordinating Instruments For Multi-Messenger Astrophysics, Daisy Wang, Ye Htet, Marion Sudvarg, Roger Chamberlain, Jeremy Buhler, James Buckley

Computer Science Faculty Research & Creative Works

In multi-messenger astrophysics, signals of multiple types (e.g., gravitational waves, neutrinos, electromagnetic waves) are combined in an effort to learn more about the observed phenomena of interest. The Advanced Particle-astrophyics Telescope (APT) is a mission concept for a space-borne instrument that detects gammaray bursts (GRBs) omnidirectionally, facilitating multi-messenger observations by identifying and localizing celestial events of interest. Here, we describe the on-instrument computations for APT and its Antarctic Demonstrator (ADAPT) as well as techniques for follow-up observations of transient events.

8-Page Zine Extra Credit Assignment, Ricaute Rogers

Open Educational Resources

This is an 8-page minizine extra credit assignment that put into practice the concepts learned in CIS100.

Pure And Strong Nash Equilibrium Computation In Compactly Representable Aggregate Games, Jared Soundy, Mohammad T. Irfan, Hau Chan

Research & Publications

Aggregate games model interdependent decision making when an agent’s utility depends on their own choice and the aggregation of everyone's choices. We define a compactly representable subclass of aggregate games we call additive aggregate games, which encompasses popular games like congestion games, anonymous games, Schelling games, etc. We study computational questions on pure Nash equilibrium (PNE) and pure strong Nash equilibrium (SNE). We show that PNE existence is NP-complete for very simple cases of additive aggregate games. We devise an efficient algorithmic scheme for deciding the existence of a PNE and computing one (if it exists) for bounded aggregate space. …

Full-Stack Web Applications: Infrastructure, Development Pipelines & Devsecops, Yassine Chahid, Patrick Slattery

Publications and Research

This research explores emerging development methodologies and technologies which facilitate the deployment and maintenance of software applications. It evaluates architectural styles for the development of software such as monolithic (legacy) and microservice models, with a focus on their key differences such as scalability or project structure through to the development of an application. By examining methodologies such as Agile and continuous integration/continuous development pipelines along with the deployment tools Docker and Git for version/release control, the study analyzes how these innovations speed up development, improve existing practices, and serve as the foundation for development operations. Cloud solutions for tasks such …

Advancements In Refreshable Braille Display Technology: A Comprehensive Survey, Maryam Etezad, Rajeev Joshi, Franceli L. Cibrian

Engineering Faculty Articles and Research

This paper provides a comprehensive mapping literature review of the advancements in refreshable Braille display (RBD) technology, which employs dynamically movable pins or dots to render Braille characters for individuals with blindness and visual impairment. This literature review, which includes 96 papers, aims to summarize the current evidence on six distinct types of RBDs: piezoelectric, electromagnetic, electroactive polymer (EAP), pneumatic, shape memory alloy (SMA), and microfluidic technologies. For each type, we discuss the underlying mechanisms, alongside the current trends and research opportunities. This comparative analysis aims to inform the selection of appropriate RBD technology based on specific user needs and …

Machine Learning: Neural Networking With Relu And Optimization, Aidan Redmond Brownell

Undergraduate Theses, Capstones, and Recitals

At its core, learning is an algorithmic process: it begins with input data, undergoes a series of transformations or computations, and yields an output intended to solve a specific task. This output is then compared against a target or desired result, and the internal mechanisms are updated based on how well the output aligns with expectations. While this feedback-driven process occurs almost effortlessly in humans, it is a far more structured, deliberate, and computationally intensive undertaking for machines.

Improving Culinary Informatics Through Meaningful Social Web Engineering, Suraya Nurain Kalid, Fahmi Mikail Fahrid, Sin-Ban Ho

Journal of Informatics and Web Engineering

This paper gives a good reflection about social web engineering aspirations to ardently see the truth to enlighten culinary concentration and wisdom. With the compassionate path to discover food and engage customers to share content with loving kindness spread to every corner. There are so many features realized, which include direct interfaces through intuitive interfaces to lead the daily food streamlining. May one engaged with constructive creation to grow compassions in every culinary living sharing. Contentment would develop in our heart involved in different phases put forward in this paper. The initial phase begins with honesty in planning and design. …

Basic Theory And Implementations Of Quantum Error Correction, Derek Rodriguez

Undergraduate Theses, Capstones, and Recitals

The introduction of quantum computing has presented algorithmic solutions to computationally difficult challenges that are far more efficient than those of classical computers. These algorithms leverage the properties of quantum mechanics to manipulate the quantum properties of subatomic particles, requiring immense precision and stability. Current quantum hardware, however, is too noisy and introduces too many errors for these algorithms to be useful in practice, necessitating the use of error correction algorithms. This field survey seeks to introduce various principles of quantum mechanics relevant to quantum computing and quantum error correction (QEC), detail the implementation and motivations of a basic QEC …

K-Means Clustering Optimization Of Toddler Malnutrition Status Using Elbow Method, Femmi Widyawati, Ahmad Yahya Dawod, Heru Agus Santoso

Journal of Informatics and Web Engineering

The problem of nutritional status is still a major challenge in the health sector in developing countries, including Indonesia. Malnutrition in toddlers can have serious long-term impacts on children's growth and development, including increased risk of disease, impaired cognitive function, and low productivity in the future. To overcome this problem, an in-depth analysis is needed to determine the distribution of nutritional status of toddlers in one of the provincial capitals in Indonesia, which can be used as a basis for planning more effective interventions. This study uses the K-Means algorithm to classify areas based on the prevalence of malnutrition in …