Computer Engineering Commons^™

The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …

Implications Of Quantum Computing For Enterprise Cybersecurity And Data Integrity, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Quantum computing represents a paradigm shift in computational capabilities that poses both unprecedented threats and opportunities for enterprise cybersecurity. This research examines the implications of quantum computing advancement on current cryptographic systems, data protection mechanisms, and organizational security frameworks. Through analysis of quantum computing developments from 2019-2024 and surveys of 280 cybersecurity professionals across various industries, this study identifies critical vulnerabilities in existing encryption standards and explores emerging quantum-resistant solutions. The findings reveal that approximately 78% of enterprises remain unprepared for quantum threats, with current RSA and ECC encryption systems facing potential compromise within the next 10-15 years. The research …

Minimizing Performance Overheads For Crash-Consistency In Disaggregated Persistent Memory, Khan Shaikhul Hadi

Graduate Studies Theses and Dissertations 2026

Compute express link (CXL) enables persistent memory disaggregation with memory pooling and hardware managed multi-host memory sharing capability, resulting in better resource utilization, increased scalability. Persistency-aware applications need to manage crash consistency across the system which results in significant performance overhead. This dissertation systematically investigates performance overhead to achieve crash consistency in disaggregated persistent memory and proposes solutions to enable persistency-aware application scaling for distributed system. First, we study persistent parallel programming to scale computation capability beyond single processor and determine the underlying hardware limitation to adopt lock-free data structure. We propose hardware support to design durable atomic instruction (DAI) …

Real-Time Deep Learning Detection Of Toraja Carving Motifs Using Yolo11m For Cultural Heritage Preservation, Herman Herman, Farid Wajdi Mufti, Abdul Rachman Manga, Haidawati Nasir

Knowledge Engineering and Data Science

Toraja carvings are an important part of Indonesia’s cultural heritage, rich in symbolic, aesthetic, and philosophical meaning. However, the identification and preservation of carving motifs still rely on subjective, time-consuming manual processes, limiting scalability and inconsistent knowledge transmission. From a Knowledge Engineering and Cognitive Data Science perspective, this challenge highlights the need for mechanisms that can transform visual cultural artifacts into structured, machine-interpretable knowledge. This study investigates the use of the YOLO11m model as a data-driven approach for modeling cultural knowledge through automated detection of three Toraja carving motifs: pa_tedong, pa_kapu_baka, and pa_manu_londongan using original images collected directly from traditional …

Heathammer: Effects Of Thermal Stress On Dram Technology Reliability Using Rowpress And Rowhammer, Filip Roth Tronnes-Christensen

Theses

Modern DRAM scaling has reduced cell capacitance and increased thermal sensitivity, making disturbance-based faults such as RowHammer and RowPress increasingly significant reliability and security concerns. RowHammer induces bit flips through repeated row activations, while RowPress does so by holding a wordline open for an extended duration; both exploit inherent capacitive coupling and leakage mechanisms in dense DRAM arrays. This thesis introduces HeatHammer, a thermally assisted disturbance exploit that interleaves RowPress and RowHammer operations to amplify charge leakage and trigger row-traversing bit flips. Using the FPGA-based DRAM-Bender test platform, HeatHammer is evaluated on four commercially available DDR4 modules from different manufacturers …

Implementing Controls To Mitigate The 2013 Target Data Breach: A Cost Benefit Analysis, Pricilia R. Fajong

Dissertations, Theses, and Projects

In 2013 Target had a data breach, which compromised 40 million credit/debit card accounts and 70 million customer records. The attackers exploited a vulnerability in a third-party vendor (Fazio Mechanical Services), to gain access to Target's systems. The breach cost Target over $250 Million (USD) in legal fees, investigation expenses, and reputational damage (Jones, 2025). Based on inflation rate, the 2013 Target data breach would cost over $340 Million (USD) today. In this study, a cost-benefit analysis was done to determine whether it would have been more cost-effective for Target to have invested in security controls rather than paying for …

Construction Of A Unified Knowledge Graph For Cyber Threat Intelligence, Moaz Usama Hassan Mr, Khaled , Nagaty, Noura Elmaghawry

Computer Networks

The rapid expansion and variety of cyber-threat information put enormous pressure on security operations centers (SOCs) that must convert unstructured data into understandable signals and make decisions upon it. This paper develops a Cyber-Threat-Intelligence (CTI) framework that integrates vulnerability information, product inventories, and weakness taxonomies into a domain-specific knowledge graph via automatic fusing. The proposed solution covers 284,296 CVEs, 101,644 CPE identifiers, and 965 CWE weaknesses, generating more than 800,000 typed edges linking threats, assets, tactics, and mitigations in an integrated CTI Knowledge graph. The graph was cross validated against four external standard datasets achieves full coverage of ATT&CK CAPEC, …

A Predictive Model For Multi- Week Respiratory Risk From Red Tide On Florida’S Gulf Coast., Elmer S. Ochaeta

Computer Science and Engineering Faculty Publications

Florida’s Gulf Coast red tide (Karenia brevis) can put toxins into the air, making people cough, irritating the throat, and worsening asthma or other breathing problems especially when winds blow from the ocean toward the beach. Right now, most public updates don’t really help with the question people actually ask when planning a weekend or vacation: “Will going to or close to the beach be risky in the next few weeks?”.

In this project, I build a weekly early warning system that estimates respiratory risk for specific beaches and predicts that risk 2 to 4 weeks ahead. The study covers …

Turboindex: Making A Page-Based Db Index Both Memory-Space And Disk-I/O Efficient, Sujit Maharjan, Shuaihua Zhao, Song Jiang

Computer Science and Engineering Faculty Publications - Archive

Traditional Database (DB) systems use a DB buffer, a page-based cache management system, to load data and indexes from block storage devices into byte-addressable main memory. However, this approach is inefficient in terms of space and I/O when key-value pair sizes are significantly smaller than the page size. Inserting a single key-value pair results in reading and writing an entire page, consuming a full page's worth of memory in the buffer. Moreover, the entire page is immediately loaded even when just a single key-value pair is inserted into the page. Also, an infrequently accessed page is likely to be evicted …

Sistemas De Información Geográfica En La Era De La Digitalización, Jairo Eduardo Márquez Díaz, Luis Gonzalo Benavides Ramírez, Arles Prieto Moreno, Martha Andrea Manrique Castro

Ingeniería

En la era digital, la información geográfica es esencial para la toma de decisiones en áreas como la planificación urbana, la gestión de recursos naturales y la seguridad. Los Sistemas de Información Geográfica (SIG) se han establecido como herramientas indispensables para gestionar, analizar y visualizar datos georreferenciados que permite la creación de mapas digitales y la toma de decisiones basada en evidencia. Este libro aborda los fundamentos, las tecnologías y las aplicaciones de los SIG, explorando su evolución y su potencial en un entorno digital en constante transformación. A lo largo de sus cinco capítulos, el libro aborda temas esenciales …

Foundations For Multi-Bit-Per-Cell Phase Change Memory Modeling Gst Crossbar Arrays, Sashah Wilson-Thompson

Holster Scholar Projects

This project builds a simulation foundation for selective cell heating in a phase-change memory (PCM) crossbar using Ge2Sb2Te5 (GST) as the active material. Using COMSOL Multiphysics® a 3D modeling software, couples Electric Currents, Electric Circuits, Heat Transfer in Solids, and Electromagnetic Heating for the simulation. A parameterized Tungsten (W)/GST-Amorphous/GST-Crystalline(phases) /W embedded in Silica Dioxide (SiO2) and surrounded in Silica Nitride (Si3N4) is validated at the single-cell level and scaled to small GST crossbars A terminal voltage (V_active/V_inactive, or 0 V if unselected) is applied through MOSFET and diode selector elements at the ends of each word line and bit line. …

Csc36000 - Modern Distributed Computing Assignment, Saptarashmi Bandyopadhyay

Open Educational Resources

This assignment covers standard performance metrics for Distributed Systems and the basics of Multiprocessing for CSC36000 - Modern Distributed Computing at the City College of New York CUNY. It is an interactive coding assignment intended to be executed in a Python notebook.

Storage Location Optimization In Automated Storage And Retrieval Systems: A Deep Reinforcement Learning Approach, Lingjun Wang, Aldy Gunawan, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

This study investigates the optimization of storage location in automated storage and retrieval systems (AS/RS). We introduce an optimization approach based on the Deep Q-Network (DQN) algorithm to enhance warehouse task efficiency and minimize stacker travel during storage and retrieval. To accelerate the algorithm training process, we integrate a prioritized experience replay mechanism. Furthermore, we decouple action selection from value estimation within the DQN framework to address the issue of value overestimation. The proposed model is evaluated against three heuristic methods. The experimental results demonstrate that our approach significantly outperforms these baselines.

Adaptive Multi-Agent Reinforcement Learning For Electric Vehicle Charging Optimization Under Dynamic Traffic Conditions, Shaghayegh Rabbanian

LSU Master's Theses

Electric vehicle (EV) charging optimization is a critical challenge in sustainable transportation. This study focuses on three fundamental questions: (1) when is the best time to charge an EV, (2) where is the optimal charging location, and (3) how should charging be planned considering navigation and routing decisions. Our primary objective is to determine the optimal time and location for EV charging while accounting for key factors such as real-time traffic conditions, spatial distribution of charging stations, and EV-specific attributes such as state of charge (SOC), driving range, and efficiency. To develop a robust and adaptive EV charging recommendation system, …

Syntax-Enhanced Boundary-Aware Named Entity Recognition Model, Chuanming Yu, Bin Deng, Zhengang Zhang

Journal of Scientific Information Research

[Purpose/significance] This study addresses the issue of inadequate perception of entity boundaries in traditional character-level modeling-based named entity recognition models by integrating syntax information containing entity boundary features into the task using a multi-head graph attention network with dense connections. This integration enhances the effectiveness of named entity recognition.

[Method/process] This study proposes a Syntax-enhanced Boundary-aware Named Entity Recognition Model (SynBNER), which utilizes BERT for text semantic representation and integrates syntax information using a dense-connected graph attention network. This integration incorporates implicit entity boundary information from syntax information into word representations, thereby enhancing the model's entity boundary perception capability.

[Result/conclusion] …

Advancing Food Nutrition Estimation Via Visual-Ingredient Feature Fusion, Huiyan Qi, Bin Zhu, Chong-Wah Ngo, Jingjing Chen, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Nutrition estimation is an important component of promoting healthy eating and mitigating diet-related health risks. Despite advances in tasks such as food classification and ingredient recognition, progress in nutrition estimation is limited due to the lack of datasets with nutritional annotations. To address this issue, we introduce FastFood, a dataset with 84,446 images across 908 fast food categories, featuring ingredient and nutritional annotations. In addition, we propose a new model-agnostic Visual-Ingredient Feature Fusion (VIF2 ) method to enhance nutrition estimation by integrating visual and ingredient features. Ingredient robustness is improved through synonym replacement and resampling strategies during training. The ingredient-aware …

Custom Data Acquisition System For The Cal Poly Racing Baja Team, Joe Keenan

Computer Engineering

The Cal Poly Racing Baja team relies on data to analyze and improve upon various vehicle systems in an off-road style vehicle. In order to accomplish this, some data logging or data acquisition (DAQ) is required to collect the data. This project explores the use of a controller area network with flexible data rate (CAN FD) bus along with a custom file format to store data on an SD card that can be made easily acceptable to engineers on the team.

Implementation Of Area-Based Aggregation On Multivariate Continuous Uncertain Data, Rahul Nair

Master's Theses

Uncertain data is incredibly widespread - from sensor data to AI-based learned information, there exists a need to associate information with a certain probability of its veracity. Traditional relational databases lack a built-in functionality to support uncertain data, instead assigning them boilerplate values. Probabilistic databases tackle this problem by assigning non-deterministic data with an associated, often discrete, probability. Variants of probabilistic databases, namely continuous uncertain databases, are used to better model data represented through ranges and distributions. This is especially applicable with sensor-based geographic data as most commercial equipment contains some inherent margin of error.

While uncertain and probabilistic databases …

A Data-Driven Approach To Smart Shopping: Optimizing Grocery Trips Using Geolocation And Store Inventory Data, Kien T. Giang

Honors Theses

This project presents a data-driven web-based application, Smart Shopping, designed to help customers optimize their grocery purchases based on location and store inventory information. The application allows users to add items to a shopping list and either enter an address or use their browser’s location services to identify nearby stores. It then retrieves product availability and prices from a mock database representing stores at user’s selected locations. The program compares prices across stores to provide users with two optimized options: the cheapest shopping bill from a single store, and the lowest individual item prices across multiple stores. Additionally, the …

Development Of A Cost-Effective Daq For Measuring Brake Performance In Race Cars, Adrin Alias

2025 Spring Honors Capstone Projects - Archive

This project explores the feasibility of creating a cost-effective data acquisition (DAQ) system for high-speed, real-time brake performance testing of Formula SAE racecars. The research addresses the limitations of the current MoTeC DAQ system currently employed by the team, which is costly and time-consuming to set up for on-car testing. The team will use a brake dynamometer for steady-state comparisons of different brake pad compounds (senior design project), but evaluating real-world performance requires on-car testing. By systematically comparing various hardware platforms, sensors, communication protocols, and storage solutions, this project aims to balance cost-efficiency with reliability and performance. The research evaluates …

A Data Driven Approach To Student Success: Visualizing Engagement And Performance Metrics, Araohat Kokate

2025 Spring Honors Capstone Projects - Archive

Many tutoring centers lack tools to analyze and visualize key performance metrics, limiting data driven decision making. This study develops a data visualization feature for the CSE Student Success Center App at the University of Texas at Arlington, enabling administrators to track student engagement, tutor performance and session trends. Using the data of students and tutors, the feature provides interactive dashboards for real-time insights. Administrators can monitor attendance patterns, tutor workloads and booking trends, optimizing resource allocation. Findings indicate that real-time data visualization enhances decision-making, reducing manual effort while improving operational efficiency. This can further help improve student support services. …

Performance Of Inline Compression With Software Caching For Reducing The Memory Footprint In Pysdc, Emily Lattanzio

All Theses

The volume of data required for High Performance Computing (HPC) applications is growing faster than the memory storage available to store the required data, leading to performance bottlenecks in transferring data. Whether sending data from main memory to computation nodes or between parallel processes during runtime, the more data there is to send, the longer it will take to for that data to be sent from one location to the next. Hence the need for inline data compression, which reduces the amount of allocated memory needed by storing the largest data structures in a compressed format and decompressing/recompressing single variables …

Computer Vision In Soccer: Yolov11 Analytics Engine For Quantifying Game Strategy, Connor S. Maurer

Data Science Undergraduate Honors Theses

Single-shot object detection capabilities significantly reduce computational overhead for real-time computer vision in sports analytics at 60 FPS. YOLO11’s lightweight CNN gives promising accuracy while meeting the low-latency demand of dynamic soccer matches. As data-driven approaches take over the sport of soccer, efficient player tracking systems become critical for informing coach’s strategies. I prototype the ETL (Extract, Transform, Load) process of data collected from a single- shot detection program and evaluate its viability for estimating player fatigue. YOLO11 detects players, the ball, and other characteristics, with the output transformed by homography to estimate the positions in the real world. These …

Cellular Telemetry For Real-Time River Flow Velocity Data From Fluvial Acoustic Tomography Loggers, Joshua Lee Seymour

Honors Theses

Streamflow is a critical element in understanding watershed processes and the effects of land use on those processes because it is the primary medium through which water, sediment, nutrients, organic material, thermal energy, and aquatic species move. Fluvial Acoustic Tomography (FAT) systems offer accurate direct measurements of river section-averaged flow velocity by measuring reciprocal acoustic travel times between at least two acoustic nodes positioned on opposite riverbanks. However, similar to many in-situ sensors used in estuarine and riverine environments, FAT loggers require manual data retrieval, which is time-consuming, labor-intensive, and limits real-time access and increases maintenance costs. This project presents …

Virtual Makeup And Technology Integration, Vishwa Bhatt

Electronic Theses, Projects, and Dissertations

The Virtual Makeup Streamlit application presents an advanced approach to digital cosmetic try-on by allowing users to apply makeup to their facial images in real time. This project uses computer vision and web technologies to create an interactive and user-friendly platform that capitalizes on the increasing popularity of virtual try-on solutions in the cosmetics industry.

At its core, the system uses effective facial detection and semantic segmentation techniques to recognize and separate facial areas such as lips and hair. Techniques such as U-Net and Resnet, and Midepipe are used to create accurate segmentation masks, which are essential for accurate makeup …

Blockchain-Integrated Version Control For Secure And Transparent Software Supply Chains, Iwinosa W. Aideyan

All Theses

The software supply chain encompasses all stages of software development and delivery from initial coding and version control to integration and deployment. As development environments become increasingly distributed and reliant on external dependencies, ensuring the integrity, auditability, and consistency of code changes has become a pressing challenge. Traditional version control systems like Git, while effective for collaboration and tracking revisions, do not inherently provide tamper-evident commit histories. Features such as history rewriting (e.g., git rebase, git push --force) can be exploited to manipulate commit logs without detection, posing risks in security-sensitive domains. This thesis proposes a blockchain-integrated version control framework …

Evaluating Hyper-V Vs Proxmox: Performance Comparison For Virtualization*, Ivan Vakal, Edwin Regalado

Campus Research Month

Virtual environments play a significant role in the IT industry, with many companies relying on this technology. With VMware’s increasing licensing costs following its acquisition by Broadcom, many businesses are seeking alternative virtualization solutions. This study evaluates the performance of Proxmox and Hyper-V by implementing a three-node high-availability cluster for each platform and conducting benchmarking tests on CPU performance, storage efficiency, and network throughput. Our results indicate that Hyper-V performs better with Windows-based virtual machines, while Proxmox demonstrates superior performance with Linux-based workloads. Additionally, Proxmox offers a more user-friendly cluster setup, whereas Hyper-V requires greater technical expertise.

Comparative Performance Analysis Of Cryptographic Workloads Across Cloud Providers: A Multi-Language Study On Faas And Iaas Platforms Dataset, Jeremiah Webb

Doctoral Dissertations and Master's Theses

Cloud computing has become a relatively new paradigm for the delivery of compute resources, with key management services (KMS) playing a crucial role in securely handling cryptographic operations in the cloud. This paper presents the microbenchmark of cloud cryptographic workloads, including SHA HMAC generation, AES encryption/decryption, ECC signature/verification, and RSA encryption/decryption, across Function-as-a-Service (FaaS) and Infrastructure-as-a-Service (IaaS) in conjunction with KMS offerings from Ama- zon Web Services (AWS) and Microsoft Azure to conduct a comparative performance analysis. The methodology involves the AWS Cloud Development Kit (CDK) and the Bicep language to deploy AWS Lambda Functions and Azure Functions, respectively, to …

On The Provenance Of Software Systems: Automating Software Traceability With Knowledge Graph And Large Language Model Synergy, Tyler Procko

Doctoral Dissertations and Master's Theses

The present dissertation delineates a system that enables those engaged in software development to automatically generate and maintain project life cycle provenance. All projects are implemented and made manifest with the development of artifacts, e.g., papers, code files, etc. Tools exist to accelerate artifact creation, but little focus is paid to the processes that produce them. In terms of Ontology, or, from Ancient Greek, the study of being, the two most basic entities in reality are Continuant and Occurrent, or, roughly, “Artifact” and “Process”. This dissertation posits that for any created artifact, its process of creation, i.e., its life …

Llm-Enhanced Multiple Instance Learning For Joint Rumor And Stance Detection With Social Context Information, Ruichao Yang, Jing Ma, Wei Gao, Hongzhan Lin

Research Collection School Of Computing and Information Systems

The proliferation of misinformation, such as rumors on social media, has drawn significant attention, prompting various expressions of stance among users. Although rumor detection and stance detection are distinct tasks, they can complement each other. Rumors can be identified by cross-referencing stances in related posts, and stances are influenced by the nature of the rumor. However, existing stance detection methods often require post-level stance annotations, which are costly to obtain. We propose a novel LLM-enhanced Multiple Instance Learning (MIL) approach to jointly predict post stance and claim class labels, supervised solely by claim labels, using an undirected microblog propagation model. …