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open access

Trajectories As a Unifying Cross Domain Feature for Surveillance Systems

Description: Manual video analysis is apparently a tedious task. An efficient solution is of highly importance to automate the process and to assist operators. A major goal of video analysis is understanding and recognizing human activities captured by surveillance cameras, a very challenging problem; the activities can be either individual or interactional among multiple objects. It involves extraction of relevant spatial and temporal information from visual images. Most video analytics systems are constra… more
Date: December 2014
Creator: Wan, Yiwen
Partner: UNT Libraries
open access

Capacity and Throughput Optimization in Multi-cell 3G WCDMA Networks

Description: User modeling enables in the computation of the traffic density in a cellular network, which can be used to optimize the placement of base stations and radio network controllers as well as to analyze the performance of resource management algorithms towards meeting the final goal: the calculation and maximization of network capacity and throughput for different data rate services. An analytical model is presented for approximating the user distributions in multi-cell third generation wideband c… more
Date: December 2005
Creator: Nguyen, Son
Partner: UNT Libraries
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
Partner: UNT Libraries
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
Partner: UNT Libraries

Understanding and Reasoning with Negation

Description: In this dissertation, I start with an analysis of negation in eleven benchmark corpora covering six Natural Language Understanding (NLU) tasks. With a thorough investigation, I first show that (a) these benchmarks contain fewer negations compared to general-purpose English and (b) the few negations they contain are often unimportant. Further, my empirical studies demonstrate that state-of-the-art transformers trained using these corpora obtain substantially worse results with the instances that… more
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Date: December 2022
Creator: Hossain, Md Mosharaf
Partner: UNT Libraries

Secure and Decentralized Data Cooperatives via Reputation Systems and Blockchain

Description: This dissertation focuses on a novel area of secure data management referred to as data cooperatives. A data cooperative solution promises its users better protection and control of their personal data as compared to the traditional way of their handling by the data collectors (such as governments, big data companies, and others). However, despite the many interesting benefits that the data cooperative approach tends to provide its users, it suffers from a few challenges hindering its developme… more
This item is restricted from view until January 1, 2025.
Date: December 2022
Creator: Salau, Abiola
Partner: UNT Libraries

Registration of Point Sets with Large and Uneven Non-Rigid Deformation

Description: Non-rigid point set registration of significantly uneven deformations is a challenging problem for many applications such as pose estimation, three-dimensional object reconstruction, human movement tracking. In this dissertation, we present a novel probabilistic non-rigid registration method to align point sets with significantly uneven deformations by enforcing constraints from corresponding key points and preserving local neighborhood structures. The registration method is treated as a densit… more
This item is restricted from view until January 1, 2025.
Date: December 2022
Creator: Maharjan, Amar Man
Partner: UNT Libraries
open access

Machine Learning Methods for Data Quality Aspects in Edge Computing Platforms

Description: In this research, three aspects of data quality with regard to artifical intelligence (AI) have been investigated: detection of misleading fake data, especially deepfakes, data scarcity, and data insufficiency, especially how much training data is required for an AI application. Different application domains where the selected aspects pose issues have been chosen. To address the issues of data privacy, security, and regulation, these solutions are targeted for edge devices. In Chapter 3, two so… more
Date: December 2022
Creator: Mitra, Alakananda
Partner: UNT Libraries
open access

Reliability and Throughput Improvement in Vehicular Communication by Using 5G Technologies

Description: The vehicular community is moving towards a whole new paradigm with the advancement of new technology. Vehicular communication not only supports safety services but also provides non-safety services like navigation support, toll collection, web browsing, media streaming, etc. The existing communication frameworks like Dedicated Short Range Communication (DSRC) and Cellular V2X (C-V2X) might not meet the required capacity in the coming days. So, the vehicular community needs to adopt new technol… more
Date: December 2022
Creator: Dey, Utpal-Kumar
Partner: UNT Libraries

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
Partner: UNT Libraries
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
Partner: UNT Libraries

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
Partner: UNT Libraries
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
Partner: UNT Libraries
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
Partner: UNT Libraries

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
Partner: UNT Libraries
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
Partner: UNT Libraries

Optimization of Massive MIMO Systems for 5G Networks

Description: In the first part of the dissertation, we provide an extensive overview of sub-6 GHz wireless access technology known as massive multiple-input multiple-output (MIMO) systems, highlighting its benefits, deployment challenges, and the key enabling technologies envisaged for 5G networks. We investigate the fundamental issues that degrade the performance of massive MIMO systems such as pilot contamination, precoding, user scheduling, and signal detection. In the second part, we optimize the perfor… more
Date: August 2020
Creator: Chataut, Robin
Partner: UNT Libraries
open access

Shepherding Network Security Protocols as They Transition to New Atmospheres: A New Paradigm in Network Protocol Analysis

Description: The solutions presented in this dissertation describe a new paradigm in which we shepherd these network security protocols through atmosphere transitions, offering new ways to analyze and monitor the state of the protocol. The approach involves identifying a protocols transitional weaknesses through adaption of formal models, measuring the weakness as it exists in the wild by statically analyzing applications, and show how to use network traffic analysis to monitor protocol implementations goin… more
Date: December 2019
Creator: Talkington, Gregory Joshua
Partner: UNT Libraries
open access

Event Sequence Identification and Deep Learning Classification for Anomaly Detection and Predication on High-Performance Computing Systems

Description: High-performance computing (HPC) systems continue growing in both scale and complexity. These large-scale, heterogeneous systems generate tens of millions of log messages every day. Effective log analysis for understanding system behaviors and identifying system anomalies and failures is highly challenging. Existing log analysis approaches use line-by-line message processing. They are not effective for discovering subtle behavior patterns and their transitions, and thus may overlook some critic… more
Date: December 2019
Creator: Li, Zongze
Partner: UNT Libraries

Spatial Partitioning Algorithms for Solving Location-Allocation Problems

Description: This dissertation presents spatial partitioning algorithms to solve location-allocation problems. Location-allocations problems pertain to both the selection of facilities to serve demand at demand points and the assignment of demand points to the selected or known facilities. In the first part of this dissertation, we focus on the well known and well-researched location-allocation problem, the "p-median problem", which is a distance-based location-allocation problem that involves selection and… more
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Date: December 2019
Creator: Gwalani, Harsha
Partner: UNT Libraries

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.
Partner: UNT Libraries
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
Partner: UNT Libraries

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
Partner: UNT Libraries

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
Partner: UNT Libraries
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