Search Results

Advanced Stochastic Signal Processing and Computational Methods: Theories and Applications

Description: Compressed sensing has been proposed as a computationally efficient method to estimate the finite-dimensional signals. The idea is to develop an undersampling operator that can sample the large but finite-dimensional sparse signals with a rate much below the required Nyquist rate. In other words, considering the sparsity level of the signal, the compressed sensing samples the signal with a rate proportional to the amount of information hidden in the signal. In this dissertation, first, we emplo… more
Date: August 2022
Creator: Robaei, Mohammadreza
open access

An Artificial Intelligence-Driven Model-Based Analysis of System Requirements for Exposing Off-Nominal Behaviors

Description: With the advent of autonomous systems and deep learning systems, safety pertaining to these systems has become a major concern. The existing failure analysis techniques are not enough to thoroughly analyze the safety in these systems. Moreover, because these systems are created to operate in various conditions, they are susceptible to unknown safety issues. Hence, we need mechanisms which can take into account the complexity of operational design domains, identify safety issues other than failu… more
Date: May 2021
Creator: Madala, Kaushik

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
open access

Building Reliable and Cost-Effective Storage Systems for High-Performance Computing Datacenters

Description: In this dissertation, I first incorporate declustered redundant array of independent disks (RAID) technology in the existing system by maximizing the aggregated recovery I/O and accelerating post-failure remediation. Our analytical model affirms the accelerated data recovery stage significantly improves storage reliability. Then I present a proactive data protection framework that augments storage availability and reliability. It utilizes the failure prediction methods to efficiently rescue dat… more
Date: August 2020
Creator: Qiao, Zhi

Combinatorial-Based Testing Strategies for Mobile Application Testing

Description: This work introduces three new coverage criteria based on combinatorial-based event and element sequences that occur in the mobile environment. The novel combinatorial-based criteria are used to reduce, prioritize, and generate test suites for mobile applications. The combinatorial-based criteria include unique coverage of events and elements with different respects to ordering. For instance, consider the coverage of a pair of events, e1 and e2. The least strict criterion, Combinatorial Coverag… more
Date: December 2020
Creator: Michaels, Ryan P.

Cooperative Perception for Connected Autonomous Vehicle Edge Computing System

Description: This dissertation first conducts a study on raw-data level cooperative perception for enhancing the detection ability of self-driving systems for connected autonomous vehicles (CAVs). A LiDAR (Light Detection and Ranging sensor) point cloud-based 3D object detection method is deployed to enhance detection performance by expanding the effective sensing area, capturing critical information in multiple scenarios and improving detection accuracy. In addition, a point cloud feature based cooperative… more
Date: August 2020
Creator: Chen, Qi

COVID-19 Diagnosis and Segmentation Using Machine Learning Analyses of Lung Computerized Tomography

Description: COVID-19 is a highly contagious and virulent disease caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). COVID-19 disease induces lung changes observed in lung computerized tomography (CT) and the percentage of those diseased areas on the CT correlates with the severity of the disease. Therefore, segmentation of CT images to delineate the diseased or lesioned areas is a logical first step to quantify disease severity, which will help physicians predict disease prognosis … more
Date: August 2021
Creator: Mittal, Bhuvan

Deep Learning Methods to Investigate Online Hate Speech and Counterhate Replies to Mitigate Hateful Content

Description: Hateful content and offensive language are commonplace on social media platforms. Many surveys prove that high percentages of social media users experience online harassment. Previous efforts have been made to detect and remove online hate content automatically. However, removing users' content restricts free speech. A complementary strategy to address hateful content that does not interfere with free speech is to counter the hate with new content to divert the discourse away from the hate. In … more
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Date: May 2023
Creator: Albanyan, Abdullah Abdulaziz

Deep Learning Optimization and Acceleration

Description: The novelty of this dissertation is the optimization and acceleration of deep neural networks aimed at real-time predictions with minimal energy consumption. It consists of cross-layer optimization, output directed dynamic quantization, and opportunistic near-data computation for deep neural network acceleration. On two datasets (CIFAR-10 and CIFAR-100), the proposed deep neural network optimization and acceleration frameworks are tested using a variety of Convolutional neural networks (e.g., L… more
This item is restricted from view until September 1, 2024.
Date: August 2022
Creator: Jiang, Beilei
open access

Epileptic Seizure Detection and Control in the Internet of Medical Things (IoMT) Framework

Description: Epilepsy affects up to 1% of the world's population and approximately 2.5 million people in the United States. A considerable portion (30%) of epilepsy patients are refractory to antiepileptic drugs (AEDs), and surgery can not be an effective candidate if the focus of the seizure is on the eloquent cortex. To overcome the problems with existing solutions, a notable portion of biomedical research is focused on developing an implantable or wearable system for automated seizure detection and contr… more
Date: May 2020
Creator: Sayeed, Md Abu
open access

An Extensible Computing Architecture Design for Connected Autonomous Vehicle System

Description: Autonomous vehicles have made milestone strides within the past decade. Advances up the autonomy ladder have come lock-step with the advances in machine learning, namely deep-learning algorithms and huge, open training sets. And while advances in CPUs have slowed, GPUs have edged into the previous decade's TOP 500 supercomputer territory. This new class of GPUs include novel deep-learning hardware that has essentially side-stepped Moore's law, outpacing the doubling observation by a factor of … more
Date: May 2021
Creator: Hochstetler, Jacob Daniel

Extracting Dimensions of Interpersonal Interactions and Relationships

Description: People interact with each other through natural language to express feelings, thoughts, intentions, instructions etc. These interactions as a result form relationships. Besides names of relationships like siblings, spouse, friends etc., a number of dimensions (e.g. cooperative vs. competitive, temporary vs. enduring, equal vs. hierarchical etc.) can also be used to capture the underlying properties of interpersonal interactions and relationships. More fine-grained descriptors (e.g. angry, rude,… more
Date: August 2020
Creator: Rashid, Farzana
open access

Extracting Possessions and Their Attributes

Description: Possession is an asymmetric semantic relation between two entities, where one entity (the possessee) belongs to the other entity (the possessor). Automatically extracting possessions are useful in identifying skills, recommender systems and in natural language understanding. Possessions can be found in different communication modalities including text, images, videos, and audios. In this dissertation, I elaborate on the techniques I used to extract possessions. I begin with extracting possessio… more
Date: May 2020
Creator: Chinnappa, Dhivya Infant

Frameworks for Attribute-Based Access Control (ABAC) Policy Engineering

Description: In this disseration we propose semi-automated top-down policy engineering approaches for attribute-based access control (ABAC) development. Further, we propose a hybrid ABAC policy engineering approach to combine the benefits and address the shortcomings of both top-down and bottom-up approaches. In particular, we propose three frameworks: (i) ABAC attributes extraction, (ii) ABAC constraints extraction, and (iii) hybrid ABAC policy engineering. Attributes extraction framework compris… more
Date: August 2020
Creator: Alohaly, Manar

Helping Students with Upper Limb Motor Impairments Program in a Block-Based Programming Environment Using Voice

Description: Students with upper body motor impairments, such as cerebral palsy, multiple sclerosis, ALS, etc., face challenges when learning to program in block-based programming environments, because these environments are highly dependent on the physical manipulation of a mouse or keyboard to drag and drop elements on the screen. In my dissertation, I make the block-based programming environment Blockly, accessible to students with upper body motor impairment by adding speech as an alternative form of in… more
Date: August 2022
Creator: Okafor, Obianuju Chinonye
open access

Hybrid Optimization Models for Depot Location-Allocation and Real-Time Routing of Emergency Deliveries

Description: Prompt and efficient intervention is vital in reducing casualty figures during epidemic outbreaks, disasters, sudden civil strife or terrorism attacks. This can only be achieved if there is a fit-for-purpose and location-specific emergency response plan in place, incorporating geographical, time and vehicular capacity constraints. In this research, a comprehensive emergency response model for situations of uncertainties (in locations' demand and available resources), typically obtainable in lo… more
Date: May 2021
Creator: Akwafuo, Sampson E
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
open access

Improving Memory Performance for Both High Performance Computing and Embedded/Edge Computing Systems

Description: CPU-memory bottleneck is a widely recognized problem. It is known that majority of high performance computing (HPC) database systems are configured with large memories and dedicated to process specific workloads like weather prediction, molecular dynamic simulations etc. My research on optimal address mapping improves the memory performance by increasing the channel and bank level parallelism. In an another research direction, I proposed and evaluated adaptive page migration techniques that o… more
Date: December 2021
Creator: Adavally, Shashank

Integrating Multiple Deep Learning Models for Disaster Description in Low-Altitude Videos

Description: Computer vision technologies are rapidly improving and becoming more important in disaster response. The majority of disaster description techniques now focus either on identify objects or categorize disasters. In this study, we trained multiple deep neural networks on low-altitude imagery with highly imbalanced and noisy labels. We utilize labeled images from the LADI dataset to formulate a solution for general problem in disaster classification and object detection. Our research integrated an… more
Date: December 2022
Creator: Wang, Haili

Integrating Multiple Deep Learning Models to Classify Disaster Scene Videos

Description: Recently, disaster scene description and indexing challenges attract the attention of researchers. In this dissertation, we solve a disaster-related multi-labeling task using a newly developed Low Altitude Disaster Imagery dataset. In the first task, we realize video content by selecting a set of summary key frames to represent the video sequence. Through inter-frame differences, the key frames are generated. The key frame extraction of disaster-related video clips is a powerful tool that can e… more
Date: December 2021
Creator: Li, Yuan
open access

An Investigation of Scale Factor in Deep Networks for Scene Recognition

Description: Is there a significant difference in the design of deep networks for the tasks of classifying object-centric images and scenery images? How to design networks that extract the most representative features for scene recognition? To answer these questions, we design studies to examine the scales and richness of image features for scenery image recognition. Three methods are proposed that integrate the scale factor to the deep networks and reveal the fundamental network design strategies. In our f… more
Date: May 2022
Creator: Qiao, Zhinan
open access

IoMT-Based Accurate Stress Monitoring for Smart Healthcare

Description: This research proposes Stress-Lysis, iLog and SaYoPillow to automatically detect and monitor the stress levels of a person. To self manage psychological stress in the framework of smart healthcare, a deep learning based novel system (Stress-Lysis) is proposed in this dissertation. The learning system is trained such that it monitors stress levels in a person through human body temperature, rate of motion and sweat during physical activity. The proposed deep learning system has been trained wit… more
Date: May 2021
Creator: Rachakonda, Laavanya
open access

Kriging Methods to Exploit Spatial Correlations of EEG Signals for Fast and Accurate Seizure Detection in the IoMT

Description: Epileptic seizure presents a formidable threat to the life of its sufferers, leaving them unconscious within seconds of its onset. Having a mortality rate that is at least twice that of the general population, it is a true cause for concern which has gained ample attention from various research communities. About 800 million people in the world will have at least one seizure experience in their lifespan. Injuries sustained during a seizure crisis are one of the leading causes of death in epilep… more
Date: August 2020
Creator: Olokodana, Ibrahim Latunde
open access

Machine-Learning-Enabled Cooperative Perception on Connected Autonomous Vehicles

Description: The main research objective of this dissertation is to understand the sensing and communication challenges to achieving cooperative perception among autonomous vehicles, and then, using the insights gained, guide the design of the suitable format of data to be exchanged, reliable and efficient data fusion algorithms on vehicles. By understanding what and how data are exchanged among autonomous vehicles, from a machine learning perspective, it is possible to realize precise cooperative perceptio… more
Date: December 2021
Creator: Guo, Jingda
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