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Scalable Next Generation Blockchains for Large Scale Complex Cyber-Physical Systems and Their Embedded Systems in Smart Cities

Description: The original FlexiChain and its descendants are a revolutionary distributed ledger technology (DLT) for cyber-physical systems (CPS) and their embedded systems (ES). FlexiChain, a DLT implementation, uses cryptography, distributed ledgers, peer-to-peer communications, scalable networks, and consensus. FlexiChain facilitates data structure agreements. This thesis offers a Block Directed Acyclic Graph (BDAG) architecture to link blocks to their forerunners to speed up validation. These data block… more
Date: July 2023
Creator: Alkhodair, Ahmad Jamal M
Partner: UNT Libraries
open access

Improving Communication and Collaboration Using Artificial Intelligence: An NLP-Enabled Pair Programming Collaborative-ITS Case Study

Description: This dissertation investigates computational models and methods to improve collaboration skills among students. The study targets pair programming, a popular collaborative learning practice in computer science education. This research led to the first machine learning models capable of detecting micromanagement, exclusive language, and other types of collaborative talk during pair programming. The investigation of computational models led to a novel method for adapting pretrained language model… more
Date: July 2023
Creator: Ubani, Solomon
Partner: UNT Libraries
open access

A Platform for Aligning Academic Assessments to Industry and Federal Job Postings

Description: The proposed tool will provide users with a platform to access a side-by-side comparison of classroom assessment and job posting requirements. Using techniques and methodologies from NLP, machine learning, data analysis, and data mining: the employed algorithm analyzes job postings and classroom assessments, extracts and classifies skill units within, then compares sets of skills from different input volumes. This effectively provides a predicted alignment between academic and career sources, b… more
Date: July 2023
Creator: Parks, Tyler J.
Partner: UNT Libraries

Blockchain for AI: Smarter Contracts to Secure Artificial Intelligence Algorithms

Description: In this dissertation, I investigate the existing smart contract problems that limit cognitive abilities. I use Taylor's serious expansion, polynomial equation, and fraction-based computations to overcome the limitations of calculations in smart contracts. To prove the hypothesis, I use these mathematical models to compute complex operations of naive Bayes, linear regression, decision trees, and neural network algorithms on Ethereum public test networks. The smart contracts achieve 95\% predict… more
Date: July 2023
Creator: Badruddoja, Syed
Partner: UNT Libraries
open access

Deep Learning Approaches to Radio Map Estimation

Description: Radio map estimation (RME) is the task of predicting radio power at all locations in a two-dimensional area and at all frequencies in a given band. This thesis explores four deep learning approaches to RME: dual path autoencoders, skip connection autoencoders, diffusion, and joint learning with transmitter localization.
Date: July 2023
Creator: Locke IV, William Alexander
Partner: UNT Libraries
open access

Paradigm Shift from Vague Legal Contracts to Blockchain-Based Smart Contracts

Description: In this dissertation, we address the problem of vagueness in traditional legal contracts by presenting novel methodologies that aid in the paradigm shift from traditional legal contracts to smart contracts. We discuss key enabling technologies that assist in converting the traditional natural language legal contract, which is full of vague words, phrases, and sentences to the blockchain-based precise smart contract, including metrics evaluation during our conversion experiment. To address the c… more
Date: July 2023
Creator: Upadhyay, Kritagya Raj
Partner: UNT Libraries
open access

Reinforcement Learning-Based Test Case Generation with Test Suite Prioritization for Android Application Testing

Description: This dissertation introduces a hybrid strategy for automated testing of Android applications that combines reinforcement learning and test suite prioritization. These approaches aim to improve the effectiveness of the testing process by employing reinforcement learning algorithms, namely Q-learning and SARSA (State-Action-Reward-State-Action), for automated test case generation. The studies provide compelling evidence that reinforcement learning techniques hold great potential in generating tes… more
Date: July 2023
Creator: Khan, Md Khorrom
Partner: UNT Libraries
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