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Full-Text Articles in Computer Engineering

Proactive Safety Reasoning In Human-Robot Collaboration In Disassembly Through Llm-Augmented Stpa And Fmea, Morteza Jalali Alenjareghi, Fardin Ghorbani, Samira Keivanpour, Yuvin Adnarain Chinniah, Sabrina Jocelyn Jan 2026

Proactive Safety Reasoning In Human-Robot Collaboration In Disassembly Through Llm-Augmented Stpa And Fmea, Morteza Jalali Alenjareghi, Fardin Ghorbani, Samira Keivanpour, Yuvin Adnarain Chinniah, Sabrina Jocelyn

Études primaires

Disassembly tasks in human–robot collaboration (HRC) environments present safety challenges due to hazardous materials, control system variability, and physically demanding operator tasks. To address these challenges, we propose an AI-augmented risk assessment framework integrating System-Theoretic Process Analysis (STPA) and Failure Mode and Effects Analysis (FMEA). This framework is implemented in four configurations: Term Frequency– Inverse Document Frequency (TF-IDF), Fine-tuned Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and RAG with a structured Knowledge Graph (KG) built from safety standards. The system supports real-time, standards-compliant safety reasoning by generating interpretable, context-specific recommendations. We evaluate these configurations across GPT-3.5 TURBO, GPT-4o, GPT-4.1, and …


Lidar-Based Framework For Detecting Suspicious Human Activities, Ahd Aljumah, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Gianluca Setti Jan 2026

Lidar-Based Framework For Detecting Suspicious Human Activities, Ahd Aljumah, Charalampos Antoniadis, Hakim Ghazzai, Nawfal Guefrachi, Ahmad Alsharoa, Gianluca Setti

Electrical and Computer Engineering Faculty Research & Creative Works

This study explores the development of Human Activity Recognition (HAR) systems capable of identifying suspicious activities to enhance security in public spaces. We propose an innovative solution that integrates LiDAR sensors with deep learning technologies. Our method employs advanced models operating on LiDAR point cloud, PV-RCNN for human detection, and LidarGait++ for classifying activities into categories such as standing or walking (non-suspicious) and sneaking or fighting (suspicious). Due to the scarcity of suitable real-world datasets for training such systems, we utilize a 3D simulation tool, Blender, to create realistic environments and generate labeled point cloud data. This synthetic dataset allows …


A 1d Symmetric Interior Penalty Discontinuous Galerkin Solver In Rust, William Aey Jan 2026

A 1d Symmetric Interior Penalty Discontinuous Galerkin Solver In Rust, William Aey

Williams Honors College, Honors Research Projects

This honors project will build a 1D Symmetric Interior Discontinuous Galerkin (SIPDG) solver in Rust for Stum-Liouville type problems such as the Poisson equation, with Robin, Dirichlet, and Neumann boundary conditions. The work will cover the full pipeline: starting from the strong form of the PDE, deriving the DG weak form, implementing element and interface operators, and assembling or apply the discrete operator. Rust's safety and concurrency (e.g, via Rayon) will be used to explore serial and parallel performance. A test-driven development approach will be used to maintain a strong suite of tests. The project will result in a documented …


Security Onion Ids Case Study: Detecting And Investigating Threat Traffic Using Suricata, Zeek, And Pcap Evidence, Daryna Myroniuk Jan 2026

Security Onion Ids Case Study: Detecting And Investigating Threat Traffic Using Suricata, Zeek, And Pcap Evidence, Daryna Myroniuk

Williams Honors College, Honors Research Projects

A key component of cybersecurity is network intrusion detection, which is used to examine network traffic for any malicious activity. Many organizations deploy intrusion detection systems (IDS) but still face challenges such as validating detections, investigating alerts in a timely manner, and producing clear and repeatable evidence of what has occurred, especially when live traffic capture may be limited to risks, permissions, or privacy concerns. The goal of this project was to use Security Onion, which includes Suricata and Zeek to create and demonstrate a controllable and manageable evidence-based IDS investigation workflow. This project is focused on deploying and validating …


Analyzing Network Traffic And Data Exfiltration Via Smb In Post-Vm Escape Scenarios, Noah M. Disanza Jan 2026

Analyzing Network Traffic And Data Exfiltration Via Smb In Post-Vm Escape Scenarios, Noah M. Disanza

Williams Honors College, Honors Research Projects

Virtual machines (VMs) play a crucial role in modern IT infrastructure environments by providing isolation and enhanced security, among other things, for both personal and corporate systems. VMs are heavily rely upon to safely test malware, manage infrastructure, and reduce risk to host systems. This reliance is so substantial that the idea of reducing risk to the host system is believed to be erasing risk entirely. However, this mindset has shown to be challenged time and time again by the emergence of exploits known as virtual machine escapes. These exploits allow malicious actors to break out of the virtualized environment …


Ai-Based Music Mood Analysis With Historical And Real-Time Data, Biswash Bhattarai Jan 2026

Ai-Based Music Mood Analysis With Historical And Real-Time Data, Biswash Bhattarai

Williams Honors College, Honors Research Projects

The Music Mood Analyzer Dashboard identifies and visualizes the emotional tone of songs using audio features like tempo, energy, and valence. It classifies tracks into moods such as happy, sad, or calm and presents insights through an interactive dashboard. The project combines music analysis and data visualization to help users understand how sound relates to emotion.


Nail Salon Appointment Management System., Alexander Tran Jan 2026

Nail Salon Appointment Management System., Alexander Tran

Williams Honors College, Honors Research Projects

I will create an appointment management system for my family's nail salon. This will contain a database and tables that keep track of data of the employees, customers, and the receptionist to make it easier to book appointments for the nail salon. This was originally made to create an appointment system because I have family members who don't understand technology well and wanted to make something simple and intuitive for anyone to use, since the appointment system that we currently use is extremely off the cuff, and this should remedy that.


Network Merge, Alexander York Jan 2026

Network Merge, Alexander York

Williams Honors College, Honors Research Projects

This project will be simulating the merge of two company's networks. Company A will contain two sties connected with a VPN, and will extend this VPN to one site for Company B. This project will focus on researching how merging a network works, how routes are commonly redistributed across different routing protocols, and how each site can run their own but link servers(DHCP, DNS, etc.). Both sites will be secured from both outside and inside attacks through passwords and other network security features such as VLANs & BPDU Guard.


Dashboard And Racing Telemetry, Cole Barach, Jacob Koshel, Ethan Zifzal, Matthew Sullivan Jan 2026

Dashboard And Racing Telemetry, Cole Barach, Jacob Koshel, Ethan Zifzal, Matthew Sullivan

Williams Honors College, Honors Research Projects

The main goal of the project is to design and manufacture a combined dashboard and data logger for the vehicles produced by the Zips Racing design team. The dashboard will intuitively display real-time information to the driver and record all received information while driving. This information may be pulled off the device later for performing data analysis. This project will incorporate custom PCB design, surface mount soldering, embedded software development, and the CAN communication protocol.


Clear Skies, Avery C. Munn Jan 2026

Clear Skies, Avery C. Munn

Williams Honors College, Honors Research Projects

Air quality impacts public health, environmental sustainability, and quality of life. However, accurate and easily accessible short-term air quality forecasting is challenging to find. This project, Clear Skies, presents a machine learning–based system for forecasting next-day Air Quality Index (AQI) levels across regions in Ohio. By using historical pollutant data with variables such as temperature, humidity, wind speed, and atmospheric pressure, the system finds relationships that traditional statistical models often don’t show.

Machine learning models are evaluated alongside AI techniques to find the environmental factors that influence AQI predictions. This helps reduce the “black box” nature of many AI systems …


Secure Peer-To-Peer Messaging Using Distributed Servers, Jack Stoller Jan 2026

Secure Peer-To-Peer Messaging Using Distributed Servers, Jack Stoller

Williams Honors College, Honors Research Projects

Traditional messaging systems that rely on centralized infrastructure often introduce three security vulnerabilities: single points of failure susceptible to availability attacks, metadata leakage, and man-in-the-middle attacks.

This project designs, implements, and validates a distributed peer-to-peer messaging system that addresses each of these concerns through architectural design. A consistent hash ring is used with virtual nodes to distribute user data across a mesh of connected nodes, eliminating centralized dependency on any single server. Message contents travel directly between browser clients over a WebRTC data channel secured with end-to-end DTLS encryption, bypassing the server infrastructure. Inter-node communication is protected by mutual TLS …


Brrbox, Shawn J. Myers, Lane Cline, Michael Davis, Christian Secrest Jan 2026

Brrbox, Shawn J. Myers, Lane Cline, Michael Davis, Christian Secrest

Williams Honors College, Honors Research Projects

This report details the project known as “The BRRBOX”, a reusable, insulated thermoelectric cooler developed to keep internal temperatures at refrigeration levels or cooler for at least 48 hours. The cooler will track its internal temperature during this period and be able to give the data at the end of its delivery cycle to keep up with food and pharmaceutical standards during delivery. The BRRBOX uses Peltier-based cooling alongside vacuum insulation panels and fans to achieve efficient thermal control. An onboard microcontroller will monitor temperature, record the data, and adjust the cooling output to minimize power consumption. The box will …


Automated Pill Dispenser, Ryan Oderkirk, Connor Beaven, Rachelle Labrie, Josue Panchana Jan 2026

Automated Pill Dispenser, Ryan Oderkirk, Connor Beaven, Rachelle Labrie, Josue Panchana

Williams Honors College, Honors Research Projects

The project we propose is an automated system for dispensing dosages of medication throughout the day. It will be able to alert a user when their pills need to be taken and give them the correct dosages of up to four different medications. These dosages are configurable as well as the scheduled time they are to be taken. In addition, the pill dispenser will alert users when they are low on medications and need to refill the machine.


Proof Of Recovery: A Model To Enhance Data Integrity In Data Management Systems, Gustaf Barkstrom Jan 2026

Proof Of Recovery: A Model To Enhance Data Integrity In Data Management Systems, Gustaf Barkstrom

Theses and Dissertations

Businesses lose millions of dollars every year when they can’t restore data from backups. Research shows that Disaster Recovery Plan (DRP) testing is not conducted frequently enough, nor are records maintained that demonstrate full data recovery from backups. This work introduces a design science artifact called PRTOK that aims to increase DRP testing. The design science artifact is a software solution that integrates with Data Management Systems (DMS)

such as iRODS and DSpace, and can work with formats such as HDF5 and BagIt. Proof-of- recovery records, or tokens, are recorded in a replicated, resilient, and indelible proof-of- authority blockchain data …


Learning-Enabled Methods For Optimal, Constrained, And Fault-Tolerant Robot Motion Planning, Charles L. Clark Jan 2026

Learning-Enabled Methods For Optimal, Constrained, And Fault-Tolerant Robot Motion Planning, Charles L. Clark

Theses and Dissertations--Electrical and Computer Engineering

Safe and efficient motion planning is a core requirement for robots operating in complex real-world environments, yet traditional model-based approaches struggle to simultaneously achieve computational efficiency, solution optimality, and the ability to handle complex constraints and potential hardware failures. This dissertation investigates how neural networks, as general purpose function approximators, can be leveraged in both traditional and novel ways to overcome these limitations and advance beyond what purely model-based methods can offer. Three distinct contributions are presented. First, a new motion planner is developed that uses ReLU neural networks to decompose the configuration space into linear cost regions, enabling existing …


Lecture Notes On Cloud Computing (Ver. Winter 2026), Jun Li Jan 2026

Lecture Notes On Cloud Computing (Ver. Winter 2026), Jun Li

Open Educational Resources

This collection of lecture notes provides a comprehensive technical foundation for modern cloud computing, spanning from physical infrastructure to high-level application patterns. The text explores how warehouse-scale computers and virtualization transformed traditional data centers into flexible, on-demand resource pools characterized by elasticity and a pay-as-you-go economic model. Detailed chapters examine core architectural components, including Kubernetes orchestration, serverless computing (FaaS), and distributed key-value stores like Dynamo. The sources also emphasize the critical nature of fault tolerance, utilizing techniques like erasure coding and replication to manage the statistical inevitability of hardware failure. Security and management are addressed through frameworks like the Shared …


Determinants Of Digital Piracy: An Integrated Model, C. Christopher Lee, Peiyao Chen Jan 2026

Determinants Of Digital Piracy: An Integrated Model, C. Christopher Lee, Peiyao Chen

Journal of International Technology and Information Management

Digital piracy is a form of copyright infringement, and challenges persist in addressing it effectively. Accordingly, understanding why people engage in digital piracy is crucial. Although prior studies have examined digital piracy from multiple perspectives, existing studies on the explanatory factors of digital piracy remain fragmented. To address this research gap, this study develops an integrated model that incorporates key theoretical perspectives, neutralization theory, social learning theory, and the theory of planned behavior (TPB), along with key determinants including gender, age, and the technology factor. Rather than conducting a meta-analysis of previous studies, this study adopts a survey-based approach to …


Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu Jan 2026

Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu

Journal of International Technology and Information Management

While crowdfunding is often heralded as a democratized funding avenue that empowers women with higher success rates, this study reveals a more nuanced picture of gender dynamics. The Stereotype Content Model suggests that women are often perceived as warmer but less competent. Using a large dataset from Kickstarter, we find that female-led projects can attract more backers, likely due to warmth-driven appeal, but receive smaller average contributions, potentially due to concerns about risk linked to lower perceived competence. However, the total funding raised by female-led campaigns is comparable to that of male-led ones, showing no clear advantage or disadvantage. This …


Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events, Anushka Jaint, Yashodhan Karulkar, Kashish Jindal, Sri Sai Harshita Gadavarthi, Sanya Gulati Jan 2026

Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events, Anushka Jaint, Yashodhan Karulkar, Kashish Jindal, Sri Sai Harshita Gadavarthi, Sanya Gulati

Journal of International Technology and Information Management

With the power of social media transforming the way people connect and interact with each other, the dynamics of community formation on platforms such as X during major events are of crucial importance. While social media is an increasingly key driver in determining interactions, little is known about the online influence forming and developing fan communities in high-stakes events. This study looks into the development of user communities for datasets drawn from Kaggle on two of the world’s largest sporting events: the FIFA World Cup 2022, or football, and the T20 World Cup 2022, or cricket, with the aim of …


Modern (Networked) Warfare: Its Concepts, Evolution, And Issues, Ramesh Subramanian Jan 2026

Modern (Networked) Warfare: Its Concepts, Evolution, And Issues, Ramesh Subramanian

Journal of International Technology and Information Management

The on-going Russo-Ukraine war (February 2012-present), the recent India-Pakistan war (May 7-10, 2025), and the Israel-US attacks on Iran (June 13, 2025) have become interesting for a variety of reasons, and garnered a lot of attention in international defense publications and weapons manufacturers. To many defense analysts and defense industry professionals, these wars have become real-life testing platforms to examine and evaluate various present-day war technologies. They have opened up discussion on the future of war, the increasing use of inter-connected networks in warfare, and the increasing use of remote-operated drones in conducting surveillance and in offensive actions against …


Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework, Cherie Bakker Noteboom, Sai Neelima Seru, Aravindh Sekar Jan 2026

Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework, Cherie Bakker Noteboom, Sai Neelima Seru, Aravindh Sekar

Journal of International Technology and Information Management

Blockchain technology has gained increasing attention as a digital infrastructure capable of improving transparency, trust, and coordination in complex, multi-organizational project environments. However, existing research on blockchain-enabled project management remains fragmented and industry-focused, providing limited guidance for organizational adoption and integration. This study addresses this gap through a systematic literature review of 29 peer-reviewed studies, following PRISMA guidelines, to examine how blockchain capabilities are incorporated into project management practices across industries and maturity stages.

Grounded in Resource-Based View and Coordination Theory, the analysis employs a feature-to-process mapping approach to link six core blockchain capabilities—decentralization, transparency, immutability, smart contracts, traceability, and …


The Value Of Personal Data Ecosystems: A Flemish Media Sector Case Study, Maarten De Mildt, Melanie Verstraete, Sofie Verbrugge, Didier Colle Jan 2026

The Value Of Personal Data Ecosystems: A Flemish Media Sector Case Study, Maarten De Mildt, Melanie Verstraete, Sofie Verbrugge, Didier Colle

Journal of International Technology and Information Management

Personal Data Stores (PDSs) have been proposed as a privacy-preserving approach to data sharing that increases individual control over personal data while enabling new forms of cross-organizational collaboration. This collaboration leads to the emergence of Personal Data Ecosystems (PDEs). Despite growing interest in PDEs, limited research has examined how the organizational and economic barriers identified in prior studies manifest in practice. This paper investigates these challenges through a case study of the Flemish media sector within the Solid4Media project, which explores the use of PDSs to support data sharing and personalization across media organizations. Using a qualitative research design, data …


Responsible People Analytics For Remote-Work Decisions: A Machine-Learning Benchmark For Classifying Perceived Productivity, Ruth Menjivar, Nima Molavi, Narges Mashhadi Nejad Jan 2026

Responsible People Analytics For Remote-Work Decisions: A Machine-Learning Benchmark For Classifying Perceived Productivity, Ruth Menjivar, Nima Molavi, Narges Mashhadi Nejad

Journal of International Technology and Information Management

This study examines whether employee-perception survey data can support responsible people-analytics decisions about remote-work productivity. Using the public New South Wales (NSW) Remote Working Survey 2021 (N=1,512), the study benchmarks statistical and machine-learning classifiers for self-reported perceived productivity classes (same, less, or more productive when working remotely relative to onsite work), not objective output, under default, class-weighted, and resampling protocols. Main evidence comes from 5×5 repeated stratified cross-validation using macro F1 and balanced accuracy with fixed model specifications. Class-balanced separability is modest. Random Forest, CatBoost, and LightGBM form a leading cluster with overlapping confidence intervals (macro F1 ≈0.51–0.52). Affective/well-being items, …


Towards Developing A Career Technology Fit Framework And Analyzing Its Influence On Work-Related Outcomes Among It Professionals, Gunjan Tomer Jan 2026

Towards Developing A Career Technology Fit Framework And Analyzing Its Influence On Work-Related Outcomes Among It Professionals, Gunjan Tomer

Journal of International Technology and Information Management

With growing attrition rate and significant demand for skilled IT professionals, the importance of studying their behaviour has become important for both academia and industry. Despite ample amount of research, there is still a gap between theory and practice. Based on our qualitative study conducted on Indian IT professionals we propose that technology allocation might contribute in understanding the behaviour of IT professionals. We found that IT professionals evaluate the technology allocated to them based on their individual career motives. This evaluation, either positive or negative, influences their job outcomes. Further, we explored the factors that make a technology preferable …


High Technology And The Developing State: The Arrival Of Supercomputers In India, Ramesh Subramanian Jan 2026

High Technology And The Developing State: The Arrival Of Supercomputers In India, Ramesh Subramanian

Journal of International Technology and Information Management

While India has made vast strides in information technology in the last few decades, its success is mainly attributed to its software, rather than its hardware sector. In fact, India’s attempts at developing computer hardware that can match international standards have largely been unsuccessful. A notable exception is its development of a series of supercomputers that match and exceed many international standards. This paper looks at an interesting period in India’s computing history – namely the 1980s and 1990s – focusing on its development of an indigenous supercomputer. During that period, supercomputers were thought to be the sole privy of …


Sharing Patient-Generated Health Data With Electronic Health Record: A Standardised Provenance And Context-Rich Information Model And Clinician Evaluation, Abdullahi Abubakar Kawu Jan 2026

Sharing Patient-Generated Health Data With Electronic Health Record: A Standardised Provenance And Context-Rich Information Model And Clinician Evaluation, Abdullahi Abubakar Kawu

Dissertations

With the advent of Patient-Generated Health Data (PGHD) through wearable, mobile, and home monitoring systems, there is immense potential for ongoing monitoring and patient engagement. But integrating PGHD with Electronic Health Record (EHR) is challenged by sub-optimal support for contextual metadata and its relevant elements, lack of semantic interoperability among disparate systems, poor knowledge regarding the factors that impact clinician acceptance, and absence of globally agreed standards for data exchange. This thesis explores how contextually relevant patient-generated health data can be shared with EHRs through a FAIR standardized information model that ensures semantic and syntactic interoperability.

The study addresses six …


Comprehensive Performance Evaluation Of Devops Infrastructure Under Dynamic Workloads, Abdulrazaq Mamud Jan 2026

Comprehensive Performance Evaluation Of Devops Infrastructure Under Dynamic Workloads, Abdulrazaq Mamud

College of Graduate Studies: Theses & Dissertations

This research aims to investigate performance optimization and reliability issues related to cloud-based computing environments through an analysis of three key infrastructure components: virtualized CPU resource management, distributed API rate limiting, and web server deployment architectures. This research combines machine learning and system experimentation as a way of exploring the impact of infrastructure-level behaviors on overall system performance and scalability. The first component of the research focuses on analyzing CPU Fragmentation in Virtualized Environments, where unbalanced workload allocation on Virtual CPU Cores causes increased tail latency, resulting in Service Level Agreement violations. Metrics are analyzed using the Random Forest classifier …


End-To-End Development And Experimental Validation Of A 1/10-Scale Autonomous Vehicle, Rikkin Pankaj Panchal Jan 2026

End-To-End Development And Experimental Validation Of A 1/10-Scale Autonomous Vehicle, Rikkin Pankaj Panchal

Electrical Engineering Theses

Autonomous vehicle development demands vast resources, making scaled down platforms a critical alternative for solving core algorithmic challenges. The primary contribution of this thesis is the end to end development and validation of a complete real time autonomous driving pipeline deployed on a one tenth scale vehicle. To streamline platform development, an AI assisted annotation framework automates dataset generation, significantly reducing manual labor while improving training data quality. The system perception stack features a reinforcement learning guided online multi camera calibration framework that enables adaptive surround view stitching without the need for offline recalibration. This is paired with robust lane …


Heterogeneous Robots Cooperation Via Multi-Agent Reinforcement Learning, Rehab Uddin Shawon Jan 2026

Heterogeneous Robots Cooperation Via Multi-Agent Reinforcement Learning, Rehab Uddin Shawon

Graduate Theses/Dissertations

Enabling heterogeneous robots with diverse capabilities, roles, and task responsibilities to coordinate effectively in complex, dynamic environments remains a fundamental challenge in autonomous multi-robot systems. Multi-Agent Reinforcement Learning (MARL) provides a promising framework for decentralized cooperation. However, most existing MARL approaches assume homogeneous agents or fixed single-task settings and suffer significant performance degradation as the number of robot and task types increases. This thesis presents a scalable shared-policy MARL framework that allows heterogeneous robots to learn specialized behaviors for individual, sequential, and collaborative tasks involving temporal and spatial dependencies through a single neural policy. I first embed robot identity directly …


Probing Proficiency-Related Neural Representations With Pca And Ica, Onila R. Narayana Mudalige Don Jan 2026

Probing Proficiency-Related Neural Representations With Pca And Ica, Onila R. Narayana Mudalige Don

Graduate Student Theses, Dissertations, & Professional Papers

How proficiency-related information is represented in task fMRI depends not only on the data themselves, but on the representational lens used to summarize them. This thesis examines second-language (L2) proficiency as a problem of representational organization rather than as a simple classification exercise. Using task fMRI from adult language learners performing semantic animacy judgments in their native language (L1) and second language (L2), I derive shared low-dimensional network representations with principal component analysis (PCA) and independent component analysis (ICA), then evaluate those representations under matched leakage-controlled decoding pipelines.

Across analyses, the central comparison is between representational frameworks rather than between …