Computer Engineering Commons^™

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 …

Ntier Code Generator, Mohammed Qattan

Electronic Theses, Projects, and Dissertations

This project presents a software tool designed to automate the generation of standardized code for all layers of an n-tier architecture, including the Database Layer, Data Access Layer (DAL), and Business Logic Layer (BLL). By employing object-oriented principles and parsing the database structure, the tool ensures modularity, scalability, and maintainability. It efficiently formats code templates for CRUD operations, enhancing development efficiency and consistency, while streamlining database interactions and enforcing business rules.

This project presents an innovative software tool designed to automate the generation of standardized code for all layers of an n-tier architecture, including the Database Layer, Data Access Layer …

Cart To Doorstep, Giridhar Yadav Nazarapur

Electronic Theses, Projects, and Dissertations

Due to hectic schedules and long working hours, many people find it challenging to allocate time for traditional shopping in today's fast-paced world. This often leads to a preference for online shopping, as it provides convenience and flexibility. However, despite its benefits, online shopping still lacks a seamless experience where customers can easily access a wide range of products, manage their shopping preferences, and make hassle-free payments—all from the comfort of their homes. To address this, the "Cart to Doorstep" project was developed. This web application aims to create an efficient and user-friendly online shopping platform that streamlines the shopping …

Urban-Rural Dynamics And Dui Fatalities In The Inland Empire: A Neural Network Analysis Of Traffic Safety Disparities, Armando Ceja-Lua

Electronic Theses, Projects, and Dissertations

This study examines the disproportionately high traffic fatality rates in California's Inland Empire region through neural network analysis of over 500,000 accidents (2013-2022). We argue that the Inland Empire's unique hybrid urban-rural landscape creates a multiplicative risk environment unlike other California regions. Our analysis reveals that San Bernardino County's fatality rate (1.920 per 100 million VMT) significantly exceeds neighboring regions, with alcohol-impaired driving fatalities (0.586) substantially higher than California's average (0.390). Neural network models (92% validation accuracy) identify pedestrian-involved collisions (correlation value 0.164) and alcohol involvement (0.075) as the strongest predictors of fatality in urban areas, while rural crash patterns …

Optimizing Lightweight Authentication Protocols For Enhancing Security In Resource-Constrained Iot Devices, Anuj Jayeshbhai Naik

Electronic Theses, Projects, and Dissertations

IoT devices are increasingly being used in critical applications such as smart cities, healthcare, and industrial systems. However, due to their limited processing power, memory, and energy, traditional authentication methods are not suitable in these resource-constrained scenarios. To construct and evaluate a lightweight authentication system for such devices, this study incorporates secure, efficient cryptographic techniques. The following are the research questions: Q1) How can a hybrid lightweight authentication protocol that includes ECC and AES be used to safely and successfully link resource-constrained IoT devices? Q2) How can nonce-based challenge-response approaches to protect against replay threats be used to create lightweight …

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 …

Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman

Open Access Theses & Dissertations

Detecting and localizing faults in communication networks is critical to maintaining reliable and efficient network operations. The Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm has demonstrated its potential to automate this task but suffers from significant performance degradation under low network load conditions, where limited network flow data reduces its ability to localize faults. This thesis proposes and evaluates the performance of a synthetic traffic generation algorithm to be used with NLOF:MLL. This algorithm strategically injects synthetic flows that supplement the insufficient real network flows, thereby improving NLOF:MLL's performance under low-load conditions. Specifically, we select network …

Design And Implementation Of Asynchronous Communication In Multi-Chiplet Systems: A Comparative Study Of Pseudo-Crossbar And Bus Architectures, Matthew Clemence

Graduate Theses and Dissertations

System-on-Chip (SoC) complexity continues to present challenges in global clock distribution and power management. The Globally Asynchronous Locally Synchronous (GALS) approach addresses these issues by enabling asynchronous communication between locally synchronous chiplets. This thesis details the design and implementation of two GALS architectures employing asynchronous handshaking protocols through Multi-Threshold CMOS NULL Convention Logic (MTNCL). The first architecture, a pseudo-crossbar, uses arbiters and multiplexers/demultiplexers (MUX/DEMUX) for prioritized and dynamic communication between chiplets. The second, a bus-based approach, employs D-latches to manage communication sequentially with predetermined interrupts. This research explores the detailed implementation, functional distinctions, scalability, and integration trade-offs inherent to each …

Understanding The Breadth And Impact Of The Ias [President’S Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Optimization-Based Distributed Controller For Multi-Agents System In Microgrid Secondary Control, Fahad S. Alshammari, Ayman El-Refaie, Saleh Alyahya, Sheroz Khan

Electrical and Computer Engineering Faculty Research and Publications

Micro-grids function to connect to power system power produced by the renewable energy resources. In islanded micro-grids, grid-forming units collaborate to maintain the micro-grids voltage and frequency by utilizing droop control technique that includes primary, secondary and tertiary levels. Secondary control intervenes to improve power sharing and restore voltage and frequency to their nominal levels. However, the conventional droop control applied to a grid with mismatched line parameters experiences a trade-off between reactive power sharing and voltage regulations. This paper applies real-time trajectory tracking convex optimization to ensure by communicating power sharing between units in a consensus topology. The optimization …

The Impact Of System Transparency On Perceived System Reliability, Perceived System Usability, And Information Clarity In Self-Driving Car Systems, Uditkumar Nair

Theses and Dissertations

In human-computer interaction (HCI), the development of autonomous vehicle (AV) technology has created new difficulties, especially in building user confidence as well as understanding of system functioning. The effect of system transparency on user- centered outcomes, such as perceived usability, perceived system reliability, and information clarity, is examined in this thesis. In order to evaluate their experiences in both ordinary and high-stakes driving situations, participants engaged with both system- transparent user interfaces (TUIs) and non-transparent user interfaces (NTUIs) across a number of experimental scenarios. In order to assess how well each interface conveyed system logic and actions, the study included …

Improving Home Security Through User Centered Device Positioning, Lalith Nadipalli

Theses and Dissertations

In today’s world, where technology is advancing rapidly and security threats are becoming more complex, the need for effective home safety measures is more critical than ever. Homeowners are increasingly turning to a variety of smart devices, such as smoke detectors, carbon monoxide detectors, and security cameras, to protect their living spaces against potential dangers like burglary, fire, and environmental hazards. These devices offer essential protection, acting as both early warning systems and visual surveillance tools. However, their effectiveness largely hinges on how well they are placed within the home. Proper placement of these safety devices ensures that they provide …

Cross-Dataset Fairness Evaluation Of Transformer-Based Sentiment Models, Sara Zuiran

Theses and Dissertations

With the growing exploration of Natural Language Processing (NLP) systems in decision-making environments, it is essential to evaluate technical and ethical aspects of the dataset and the NLP model to improve fairness. To assess fairness, the thesis examines demographic imbalances in sentiment classification models by evaluating transformer-based models fine-tuned on the Stanford Sentiment Treebank version 2 dataset (SST-2) against the demographically annotated Comprehensive Assessment of Language Model dataset (CALM). This work identifies performance disparities in sentiment prediction across demographic groups by examining sensitive attributes such as gender and race. The study evaluates both the RoBERTa and MentalBERT transformer models using …

Expressive And Interpretable User Engagement Prediction Using Multivariate Survival Processes, Akshay Aravamudan

Theses and Dissertations

The ability to characterize how information diffuses online is of paramount importance to stakeholders that are interested in tasks such as proposing solutions for mitigating and countering dis/misinformation, predicting user engagement of content in social media, planning marketing campaigns to roll-out products and planning dissemination of political campaign messaging among others. One such facet of learning the dynamics of information diffusion is the ability to predict user engagement or the popularity of a single piece of information as it spreads through an online medium. Existing works in this regard mainly either obfuscate user level information or utilize frameworks that are …

Robot-Integrated 4d Building Information Modeling (4d Bim): Framework For Planning Safe Autonomous Construction Operations In Dynamic Environments, Hafiz Oyedimeji Oyediran

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

In the construction industry, the use of autonomous robots is considered a solution to overcome the heavy reliance on human workers to perform repetitive, strenuous, and hazardous tasks. While these robots offer the advantage of autonomous operation, ensuring their safe and efficient integration within construction sites requires precise planning. Such planning must account for the varying project complexities such as scope, site layout, tasks, timelines, existence of human workers, and other spatiotemporal conditions of the construction site. Currently, there are no methods to safely plan autonomous robot operations considering these factors within the overarching construction planning process. Thus, autonomous robots …

Physics Embedded Neural Network: A Novel Data-Free Numerical Method For Solving Computational Physics Problems, Pawan Gaire

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

A novel approach for solving partial differential equations (PDEs) using neural networks for scientific computing is introduced. The proposed approach, referred to as physics-embedded neural network (PENN), features a unique architecture that incorporates the PDE and boundary conditions information directly within the final fully-connected layer of the feed-forward neural network (NN). The key aspect of PENN is the parallel numerical embedding of a differential equation associated with physical problems within the activation function of the network’s final layer. This integration leads to a new class of computational solvers competitive with classical methods like the Finite Element Method (FEM) and capable …

A Machine Learning Framework For Packet Anomaly Detection In Smartgrid Substation Networks, Sowmya Bandari

School of Computing: Dissertations, Theses, and Student Research

The increasing reliance on Smart Grid Substation Networks for efficient electricity distribution has amplified cybersecurity vulnerabilities, particularly within Supervisory Control and Data Acquisition (SCADA) systems. The IEC 60870-5-104 (IEC-104) protocol, widely adopted for communication between Remote Terminal Units (RTUs) and Human-Machine Interfaces (HMIs), lacks inherent encryption and authentication mechanisms, rendering it susceptible to sophisticated cyberattacks. Threats such as False Data Injection Attacks (FDIAs), command injection, covert attacks and replay attacks pose significant risks by manipulating grid control signals, potentially leading to undetected operational disruptions, cascading failures, or system-wide instability. Conventional signature-based Intrusion Detection Systems (IDS) often fail to identify zero-day …

Integrating Blockchain Technology Into Telemedicine: A Framework For Enhancing Data Privacy And Security, Harsha Sammangi, Aditya Jagatha, Jun Liu

Research & Publications

This paper presents a blockchain-based framework designed to enhance data privacy, integrity, and security in telemedicine systems. The proposed architecture employs distributed ledger technology to ensure transparency, traceability, and immutability of patient data exchanges among healthcare providers. Smart contracts automate access permissions and auditing processes, reducing the risks of unauthorized data sharing. The study evaluates the framework’s performance in secure data handling, highlighting blockchain’s role in fostering patient trust and resilience against cyberattacks in remote healthcare environments.

Decentralized Multi-Hop Federated Reinforcement Learning For Energy-Efficient And Secure Routing In Lorawan-Based Smart City Infrastructure, Harsha Sammangi, Aditya Jagatha, Jun Liu

Research & Publications

This paper proposes a decentralized hybrid framework that integrates Federated Learning (FL) and Reinforcement Learning (RL) to enable energy-efficient and secure multi-hop routing in LoRaWAN-based smart city networks. The method allows local model training at gateways and relay nodes, combining real-time routing decisions with privacy-preserving federated aggregation. Key metrics such as residual energy, link quality, and node trust levels are embedded into the reward function, and lightweight encryption plus differential privacy safeguard routing metadata. Simulation results demonstrate substantial gains in packet-delivery ratio, latency, network lifetime and resilience to adversarial attacks when compared to traditional routing protocols.

Sensor Data Fusion For Air Quality Monitoring, Mirna Hesham

Theses and Dissertations

Since traditional air quality monitoring methods often rely on geographically sparse and costly air quality monitoring stations, image-based air quality method- ologies are recently offering a compelling alternative that utilizes images from sources like satellites, traffic cameras, and even smartphones to monitor pollution levels by using estimation models, image-processing techniques, and deep-learning models. In this thesis, we first conduct a systematic review, in which we categorize and discuss the existing literature work. Moreover, we introduce a novel, multi- modal dataset designed to address the limitations of existing datasets, which are restricted in size, geographical coverage, and fixed-scene imagery, impeding the …