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open access

Inferring Social and Internal Context Using a Mobile Phone

Description: This dissertation is composed of research studies that contribute to three research areas including social context-aware computing, internal context-aware computing, and human behavioral data mining. In social context-aware computing, four studies are conducted. First, mobile phone user calling behavioral patterns are characterized in forms of randomness level where relationships among them are then identified. Next, a study is conducted to investigate the relationship between the calling behav… more
Date: December 2009
Creator: Phithakkitnukoon, Santi
Partner: UNT Libraries
open access

The Influence of Social Network Graph Structure on Disease Dynamics in a Simulated Environment

Description: The fight against epidemics/pandemics is one of man versus nature. Technological advances have not only improved existing methods for monitoring and controlling disease outbreaks, but have also provided new means for investigation, such as through modeling and simulation. This dissertation explores the relationship between social structure and disease dynamics. Social structures are modeled as graphs, and outbreaks are simulated based on a well-recognized standard, the susceptible-infectious… more
Date: December 2010
Creator: Johnson, Tina V.
Partner: UNT Libraries
open access

Influence of Underlying Random Walk Types in Population Models on Resulting Social Network Types and Epidemiological Dynamics

Description: Epidemiologists rely on human interaction networks for determining states and dynamics of disease propagations in populations. However, such networks are empirical snapshots of the past. It will greatly benefit if human interaction networks are statistically predicted and dynamically created while an epidemic is in progress. We develop an application framework for the generation of human interaction networks and running epidemiological processes utilizing research on human mobility patterns and… more
Date: December 2016
Creator: Kolgushev, Oleg
Partner: UNT Libraries
open access

Infusing Automatic Question Generation with Natural Language Understanding

Description: Automatically generating questions from text for educational purposes is an active research area in natural language processing. The automatic question generation system accompanying this dissertation is MARGE, which is a recursive acronym for: MARGE automatically reads generates and evaluates. MARGE generates questions from both individual sentences and the passage as a whole, and is the first question generation system to successfully generate meaningful questions from textual units larger th… more
Date: December 2016
Creator: Mazidi, Karen
Partner: UNT Libraries
open access

An Integrated Architecture for Ad Hoc Grids

Description: Extensive research has been conducted by the grid community to enable large-scale collaborations in pre-configured environments. grid collaborations can vary in scale and motivation resulting in a coarse classification of grids: national grid, project grid, enterprise grid, and volunteer grid. Despite the differences in scope and scale, all the traditional grids in practice share some common assumptions. They support mutually collaborative communities, adopt a centralized control for membership… more
Date: May 2006
Creator: Amin, Kaizar Abdul Husain
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

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
Partner: UNT Libraries
open access

Integrity Verification of Applications on RADIUM Architecture

Description: Trusted Computing capability has become ubiquitous these days, and it is being widely deployed into consumer devices as well as enterprise platforms. As the number of threats is increasing at an exponential rate, it is becoming a daunting task to secure the systems against them. In this context, the software integrity measurement at runtime with the support of trusted platforms can be a better security strategy. Trusted Computing devices like TPM secure the evidence of a breach or an attack. Th… more
Date: August 2015
Creator: Tarigopula, Mohan Krishna
Partner: UNT Libraries
open access

Intelligent Memory Manager: Towards improving the locality behavior of allocation-intensive applications.

Description: Dynamic memory management required by allocation-intensive (i.e., Object Oriented and linked data structured) applications has led to a large number of research trends. Memory performance due to the cache misses in these applications continues to lag in terms of execution cycles as ever increasing CPU-Memory speed gap continues to grow. Sophisticated prefetcing techniques, data relocations, and multithreaded architectures have tried to address memory latency. These techniques are not completely… more
Date: May 2004
Creator: Rezaei, Mehran
Partner: UNT Libraries
open access

Investigating the Extractive Summarization of Literary Novels

Description: Abstract Due to the vast amount of information we are faced with, summarization has become a critical necessity of everyday human life. Given that a large fraction of the electronic documents available online and elsewhere consist of short texts such as Web pages, news articles, scientific reports, and others, the focus of natural language processing techniques to date has been on the automation of methods targeting short documents. We are witnessing however a change: an increasingly larger n… more
Date: December 2011
Creator: Ceylan, Hakan
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
open access

Investigation on Segmentation, Recognition and 3D Reconstruction of Objects Based on LiDAR Data Or MRI

Description: Segmentation, recognition and 3D reconstruction of objects have been cutting-edge research topics, which have many applications ranging from environmental and medical to geographical applications as well as intelligent transportation. In this dissertation, I focus on the study of segmentation, recognition and 3D reconstruction of objects using LiDAR data/MRI. Three main works are that (I). Feature extraction algorithm based on sparse LiDAR data. A novel method has been proposed for feature extr… more
Date: May 2015
Creator: Tang, Shijun
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

Joint Schemes for Physical Layer Security and Error Correction

Description: The major challenges facing resource constraint wireless devices are error resilience, security and speed. Three joint schemes are presented in this research which could be broadly divided into error correction based and cipher based. The error correction based ciphers take advantage of the properties of LDPC codes and Nordstrom Robinson code. A cipher-based cryptosystem is also presented in this research. The complexity of this scheme is reduced compared to conventional schemes. The securities… more
Date: August 2011
Creator: Adamo, Oluwayomi Bamidele
Partner: UNT Libraries
open access

Keywords in the mist: Automated keyword extraction for very large documents and back of the book indexing.

Description: This research addresses the problem of automatic keyphrase extraction from large documents and back of the book indexing. The potential benefits of automating this process are far reaching, from improving information retrieval in digital libraries, to saving countless man-hours by helping professional indexers creating back of the book indexes. The dissertation introduces a new methodology to evaluate automated systems, which allows for a detailed, comparative analysis of several techniques fo… more
Date: May 2008
Creator: Csomai, Andras
Partner: UNT Libraries
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
Partner: UNT Libraries

A Language and Visual Interface to Specify Complex Spatial Pattern Mining

Description: The emerging interests in spatial pattern mining leads to the demand for a flexible spatial pattern mining language, on which easy to use and understand visual pattern language could be built. It is worthwhile to define a pattern mining language called LCSPM to allow users to specify complex spatial patterns. I describe a proposed pattern mining language in this paper. A visual interface which allows users to specify the patterns visually is developed. Visual pattern queries are translated into… more
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Date: December 2006
Creator: Li, Xiaohui
Partner: UNT Libraries
open access

Layout-accurate Ultra-fast System-level Design Exploration Through Verilog-ams

Description: This research addresses problems in designing analog and mixed-signal (AMS) systems by bridging the gap between system-level and circuit-level simulation by making simulations fast like system-level and accurate like circuit-level. The tools proposed include metamodel integrated Verilog-AMS based design exploration flows. The research involves design centering, metamodel generation flows for creating efficient behavioral models, and Verilog-AMS integration techniques for model realization. The … more
Date: May 2013
Creator: Zheng, Geng
Partner: UNT Libraries
open access

Learning from small data set for object recognition in mobile platforms.

Description: Did you stand at a door with a bunch of keys and tried to find the right one to unlock the door? Did you hold a flower and wonder the name of it? A need of object recognition could rise anytime and any where in our daily lives. With the development of mobile devices object recognition applications become possible to provide immediate assistance. However, performing complex tasks in even the most advanced mobile platforms still faces great challenges due to the limited computing resources and co… more
Date: May 2016
Creator: Liu, Siyuan
Partner: UNT Libraries
open access

Location Estimation and Geo-Correlated Information Trends

Description: A tremendous amount of information is being shared every day on social media sites such as Facebook, Twitter or Google+. However, only a small portion of users provide their location information, which can be helpful in targeted advertising and many other services. Current methods in location estimation using social relationships consider social friendship as a simple binary relationship. However, social closeness between users and structure of friends have strong implications on geographic dis… more
Date: December 2017
Creator: Liu, Zhi
Partner: UNT Libraries

Logic Programming Tools for Dynamic Content Generation and Internet Data Mining

Description: The phenomenal growth of Information Technology requires us to elicit, store and maintain huge volumes of data. Analyzing this data for various purposes is becoming increasingly important. Data mining consists of applying data analysis and discovery algorithms that under acceptable computational efficiency limitations, produce a particular enumeration of patterns over the data. We present two techniques based on using Logic programming tools for data mining. Data mining analyzes data by extract… more
Access: Restricted to UNT Community Members. Login required if off-campus.
Date: December 2000
Creator: Gupta, Anima
Partner: UNT Libraries
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
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

Maintaining Web Applications Integrity Running on RADIUM

Description: Computer security attacks take place due to the presence of vulnerabilities and bugs in software applications. Bugs and vulnerabilities are the result of weak software architecture and lack of standard software development practices. Despite the fact that software companies are investing millions of dollars in the research and development of software designs security risks are still at large. In some cases software applications are found to carry vulnerabilities for many years before being ide… more
Date: August 2015
Creator: Ur-Rehman, Wasi
Partner: UNT Libraries
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