Detection and Classification of Heart Sounds Using a Heart-Mobile Interface (open access)

Detection and Classification of Heart Sounds Using a Heart-Mobile Interface

An early detection of heart disease can save lives, caution individuals and also help to determine the type of treatment to be given to the patients. The first test of diagnosing a heart disease is through auscultation - listening to the heart sounds. The interpretation of heart sounds is subjective and requires a professional skill to identify the abnormalities in these sounds. A medical practitioner uses a stethoscope to perform an initial screening by listening for irregular sounds from the patient's chest. Later, echocardiography and electrocardiography tests are taken for further diagnosis. However, these tests are expensive and require specialized technicians to operate. A simple and economical way is vital for monitoring in homecare or rural hospitals and urban clinics. This dissertation is focused on developing a patient-centered device for initial screening of the heart sounds that is both low cost and can be used by the users on themselves, and later share the readings with the healthcare providers. An innovative mobile health service platform is created for analyzing and classifying heart sounds. Certain properties of heart sounds have to be evaluated to identify the irregularities such as the number of heart beats and gallops, intensity, frequency, and duration. Since …
Date: December 2016
Creator: Thiyagaraja, Shanti
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Influence of Underlying Random Walk Types in Population Models on Resulting Social Network Types and Epidemiological Dynamics (open access)

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

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 agent-based modeling. The interaction networks are dynamically constructed by incorporating different types of Random Walks and human rules of engagements. We explore the characteristics of the created network and compare them with the known theoretical and empirical graphs. The dependencies of epidemic dynamics and their outcomes on patterns and parameters of human motion and motives are encountered and presented through this research. This work specifically describes how the types and parameters of random walks define properties of generated graphs. We show that some configurations of the system of agents in random walk can produce network topologies with properties similar to small-world networks. Our goal is to find sets of mobility patterns that lead to empirical-like networks. The possibility of phase transitions in the graphs due to changes in the parameterization of agent …
Date: December 2016
Creator: Kolgushev, Oleg
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Real Time Assessment of a Video Game Player's State of Mind Using Off-the-Shelf Electroencephalography (open access)

Real Time Assessment of a Video Game Player's State of Mind Using Off-the-Shelf Electroencephalography

The focus of this research is on the development of a real time application that uses a low cost EEG headset to measure a player's state of mind while they play a video game. Using data collected using the Emotiv EPOC headset, various EEG processing techniques are tested to find ways of measuring a person's engagement and arousal levels. The ability to measure a person's engagement and arousal levels provide an opportunity to develop a model that monitor a person's flow while playing video games. Identifying when certain events occur, like when the player dies, will make it easier to identify when a player has left a state of flow. The real time application Brainwave captures data from the wireless Emotiv EPOC headset. Brainwave converts the raw EEG data into more meaningful brainwave band frequencies. Utilizing the brainwave frequencies the program trains multiple machine learning algorithms with data designed to identify when the player dies. Brainwave runs while the player plays through a video gaming monitoring their engagement and arousal levels for changes that cause the player to leave a state of flow. Brainwave reports to researchers and developers when the player dies along with the identification of the players …
Date: December 2016
Creator: McMahan, Timothy
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Infusing Automatic Question Generation with Natural Language Understanding (open access)

Infusing Automatic Question Generation with Natural Language Understanding

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 than a sentence. Prior work in automatic question generation from text treats a sentence as a string of constituents to be rearranged into as many questions as allowed by English grammar rules. Consequently, such systems overgenerate and create mainly trivial questions. Further, none of these systems to date has been able to automatically determine which questions are meaningful and which are trivial. This is because the research focus has been placed on NLG at the expense of NLU. In contrast, the work presented here infuses the questions generation process with natural language understanding. From the input text, MARGE creates a meaning analysis representation for each sentence in a passage via the DeconStructure algorithm presented in this work. Questions are generated from sentence meaning analysis representations using templates. The generated questions are automatically …
Date: December 2016
Creator: Mazidi, Karen
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Simulink Based Modeling of a Multi Global Navigation Satellite System (open access)

Simulink Based Modeling of a Multi Global Navigation Satellite System

The objective of this thesis is to design a model for a multi global navigation satellite system using Simulink. It explains a design procedure which includes the models for transmitter and receiver for two different navigation systems. To overcome the problem, where less number of satellites are visible to determine location degrades the performance of any positioning system significantly, this research has done to make use of multi GNSS satellite signals in one navigation receiver.
Date: December 2016
Creator: Mukka, Nagaraju
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Privacy Preserving EEG-based Authentication Using Perceptual Hashing (open access)

Privacy Preserving EEG-based Authentication Using Perceptual Hashing

The use of electroencephalogram (EEG), an electrophysiological monitoring method for recording the brain activity, for authentication has attracted the interest of researchers for over a decade. In addition to exhibiting qualities of biometric-based authentication, they are revocable, impossible to mimic, and resistant to coercion attacks. However, EEG signals carry a wealth of information about an individual and can reveal private information about the user. This brings significant privacy issues to EEG-based authentication systems as they have access to raw EEG signals. This thesis proposes a privacy-preserving EEG-based authentication system that preserves the privacy of the user by not revealing the raw EEG signals while allowing the system to authenticate the user accurately. In that, perceptual hashing is utilized and instead of raw EEG signals, their perceptually hashed values are used in the authentication process. In addition to describing the authentication process, algorithms to compute the perceptual hash are developed based on two feature extraction techniques. Experimental results show that an authentication system using perceptual hashing can achieve performance comparable to a system that has access to raw EEG signals if enough EEG channels are used in the process. This thesis also presents a security analysis to show that perceptual hashing …
Date: December 2016
Creator: Koppikar, Samir Dilip
Object Type: Thesis or Dissertation
System: The UNT Digital Library

An Interactive Model for Vector Borne Diseases: A Simulation for Zika in French Polynesia

Post presented at Contagion 2016, a satellite meeting at the 2016 Conference on Complex Systems. This poster presents a stochastic agent-based model that simulates the transmission of ZIKA via mosquitoes in 11 islands in the French Polynesia.
Date: September 21, 2016
Creator: Gwalani, Harsha; Alshammari, Sultanah M. & Mikler, Armin R.
Object Type: Poster
System: The UNT Digital Library
Evaluation Techniques and Graph-Based Algorithms for Automatic Summarization and Keyphrase Extraction (open access)

Evaluation Techniques and Graph-Based Algorithms for Automatic Summarization and Keyphrase Extraction

Automatic text summarization and keyphrase extraction are two interesting areas of research which extend along natural language processing and information retrieval. They have recently become very popular because of their wide applicability. Devising generic techniques for these tasks is challenging due to several issues. Yet we have a good number of intelligent systems performing the tasks. As different systems are designed with different perspectives, evaluating their performances with a generic strategy is crucial. It has also become immensely important to evaluate the performances with minimal human effort. In our work, we focus on designing a relativized scale for evaluating different algorithms. This is our major contribution which challenges the traditional approach of working with an absolute scale. We consider the impact of some of the environment variables (length of the document, references, and system-generated outputs) on the performance. Instead of defining some rigid lengths, we show how to adjust to their variations. We prove a mathematically sound baseline that should work for all kinds of documents. We emphasize automatically determining the syntactic well-formedness of the structures (sentences). We also propose defining an equivalence class for each unit (e.g. word) instead of the exact string matching strategy. We show an evaluation …
Date: August 2016
Creator: Hamid, Fahmida
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Modeling and Simulation of the Vector-Borne Dengue Disease and the Effects of Regional Variation of Temperature in  the Disease Prevalence in Homogenous and Heterogeneous Human Populations (open access)

Modeling and Simulation of the Vector-Borne Dengue Disease and the Effects of Regional Variation of Temperature in the Disease Prevalence in Homogenous and Heterogeneous Human Populations

The history of mitigation programs to contain vector-borne diseases is a story of successes and failures. Due to the complex interplay among multiple factors that determine disease dynamics, the general principles for timely and specific intervention for incidence reduction or eradication of life-threatening diseases has yet to be determined. This research discusses computational methods developed to assist in the understanding of complex relationships affecting vector-borne disease dynamics. A computational framework to assist public health practitioners with exploring the dynamics of vector-borne diseases, such as malaria and dengue in homogenous and heterogeneous populations, has been conceived, designed, and implemented. The framework integrates a stochastic computational model of interactions to simulate horizontal disease transmission. The intent of the computational modeling has been the integration of stochasticity during simulation of the disease progression while reducing the number of necessary interactions to simulate a disease outbreak. While there are improvements in the computational time reducing the number of interactions needed for simulating disease dynamics, the realization of interactions can remain computationally expensive. Using multi-threading technology to improve performance upon the original computational model, multi-threading experimental results have been tested and reported. In addition, to the contact model, the modeling of biological processes specific to …
Date: August 2016
Creator: Bravo-Salgado, Angel D
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Network Security Tool for a Novice (open access)

Network Security Tool for a Novice

Network security is a complex field that is handled by security professionals who need certain expertise and experience to configure security systems. With the ever increasing size of the networks, managing them is going to be a daunting task. What kind of solution can be used to generate effective security configurations by both security professionals and nonprofessionals alike? In this thesis, a web tool is developed to simplify the process of configuring security systems by translating direct human language input into meaningful, working security rules. These human language inputs yield the security rules that the individual wants to implement in their network. The human language input can be as simple as, "Block Facebook to my son's PC". This tool will translate these inputs into specific security rules and install the translated rules into security equipment such as virtualized Cisco FWSM network firewall, Netfilter host-based firewall, and Snort Network Intrusion Detection. This tool is implemented and tested in both a traditional network and a cloud environment. One thousand input policies were collected from various users such as staff from UNT departments' and health science, including individuals with network security background as well as students with a non-computer science background to analyze …
Date: August 2016
Creator: Ganduri, Rajasekhar
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Effects of UE Speed on MIMO Channel Capacity in LTE (open access)

Effects of UE Speed on MIMO Channel Capacity in LTE

With the introduction of 4G LTE, multiple new technologies were introduced. MIMO is one of the important technologies introduced with fourth generation. The main MIMO modes used in LTE are open loop and closed loop spatial multiplexing modes. This thesis develops an algorithm to calculate the threshold values of UE speed and SNR that is required to implement a switching algorithm which can switch between different MIMO modes for a UE based on the speed and channel conditions (CSI). Specifically, this thesis provides the values of UE speed and SNR at which we can get better results by switching between open loop and closed loop MIMO modes and then be scheduled in sub-channels accordingly. Thus, the results can be used effectively to get better channel capacity with less ISI. The main objectives of this thesis are: to determine the type of MIMO mode suitable for a UE with certain speed, to determine the effects of SNR on selection of MIMO modes, and to design and implement a scheduling algorithm to enhance channel capacity.
Date: August 2016
Creator: Shukla, Rahul
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Data-Driven Decision-Making Framework for Large-Scale Dynamical Systems under Uncertainty (open access)

Data-Driven Decision-Making Framework for Large-Scale Dynamical Systems under Uncertainty

Managing large-scale dynamical systems (e.g., transportation systems, complex information systems, and power networks, etc.) in real-time is very challenging considering their complicated system dynamics, intricate network interactions, large scale, and especially the existence of various uncertainties. To address this issue, intelligent techniques which can quickly design decision-making strategies that are robust to uncertainties are needed. This dissertation aims to conquer these challenges by exploring a data-driven decision-making framework, which leverages big-data techniques and scalable uncertainty evaluation approaches to quickly solve optimal control problems. In particular, following techniques have been developed along this direction: 1) system modeling approaches to simplify the system analysis and design procedures for multiple applications; 2) effective simulation and analytical based approaches to efficiently evaluate system performance and design control strategies under uncertainty; and 3) big-data techniques that allow some computations of control strategies to be completed offline. These techniques and tools for analysis, design and control contribute to a wide range of applications including air traffic flow management, complex information systems, and airborne networks.
Date: August 2016
Creator: Xie, Junfei
Object Type: Thesis or Dissertation
System: The UNT Digital Library
New Frameworks for Secure Image Communication in the Internet of Things (IoT) (open access)

New Frameworks for Secure Image Communication in the Internet of Things (IoT)

The continuous expansion of technology, broadband connectivity and the wide range of new devices in the IoT cause serious concerns regarding privacy and security. In addition, in the IoT a key challenge is the storage and management of massive data streams. For example, there is always the demand for acceptable size with the highest quality possible for images to meet the rapidly increasing number of multimedia applications. The effort in this dissertation contributes to the resolution of concerns related to the security and compression functions in image communications in the Internet of Thing (IoT), due to the fast of evolution of IoT. This dissertation proposes frameworks for a secure digital camera in the IoT. The objectives of this dissertation are twofold. On the one hand, the proposed framework architecture offers a double-layer of protection: encryption and watermarking that will address all issues related to security, privacy, and digital rights management (DRM) by applying a hardware architecture of the state-of-the-art image compression technique Better Portable Graphics (BPG), which achieves high compression ratio with small size. On the other hand, the proposed framework of SBPG is integrated with the Digital Camera. Thus, the proposed framework of SBPG integrated with SDC is suitable …
Date: August 2016
Creator: Albalawi, Umar Abdalah S
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Sensing and Decoding Brain States for Predicting and Enhancing Human Behavior, Health, and Security (open access)

Sensing and Decoding Brain States for Predicting and Enhancing Human Behavior, Health, and Security

The human brain acts as an intelligent sensor by helping in effective signal communication and execution of logical functions and instructions, thus, coordinating all functions of the human body. More importantly, it shows the potential to combine prior knowledge with adaptive learning, thus ensuring constant improvement. These qualities help the brain to interact efficiently with both, the body (brain-body) as well as the environment (brain-environment). This dissertation attempts to apply the brain-body-environment interactions (BBEI) to elevate human existence and enhance our day-to-day experiences. For instance, when one stepped out of the house in the past, one had to carry keys (for unlocking), money (for purchasing), and a phone (for communication). With the advent of smartphones, this scenario changed completely and today, it is often enough to carry just one's smartphone because all the above activities can be performed with a single device. In the future, with advanced research and progress in BBEI interactions, one will be able to perform many activities by dictating it in one's mind without any physical involvement. This dissertation aims to shift the paradigm of existing brain-computer-interfaces from just ‘control' to ‘monitor, control, enhance, and restore' in three main areas - healthcare, transportation safety, and cryptography. …
Date: August 2016
Creator: Bajwa, Garima
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Simulink® Based Design and Implementation of a Solar Power Based Mobile Charger (open access)

Simulink® Based Design and Implementation of a Solar Power Based Mobile Charger

Electrical energy is used at approximately the rate of 15 Terawatts world-wide. Generating this much energy has become a primary concern for all nations. There are many ways of generating energy among which the most commonly used are non-renewable and will extinct much sooner than expected. Very active research is going on both to increase the use of renewable energy sources and to use the available energy with more efficiency. Among these sources, solar energy is being considered as the most abundant and has received high attention. The mobile phone has become one of the basic needs of modern life, with almost every human being having one.Individually a mobile phone consumes little power but collectively this becomes very large. This consideration motivated the research undertaken in this masters thesis. The objective of this thesis is to design a model for solar power based charging circuits for mobile phone using Simulink(R). This thesis explains a design procedure of solar power based mobile charger circuit using Simulink(R) which includes the models for the photo-voltaic array, maximum power point tracker, pulse width modulator, DC-DC converter and a battery. The first part of the thesis concentrates on electron level behavior of a solar cell, …
Date: May 2016
Creator: Mukka, Manoj Kumar
Object Type: Thesis or Dissertation
System: The UNT Digital Library
An Empirical Study of How Novice Programmers Use the Web (open access)

An Empirical Study of How Novice Programmers Use the Web

Students often use the web as a source of help for problems that they encounter on programming assignments.In this work, we seek to understand how students use the web to search for help on their assignments.We used a mixed methods approach with 344 students who complete a survey and 41 students who participate in a focus group meetings and helped in recording data about their search habits.The survey reveals data about student reported search habits while the focus group uses a web browser plug-in to record actual search patterns.We examine the results collectively and as broken down by class year.Survey results show that at least 2/3 of the students from each class year rely on search engines to locate resources for help with their programming bugs in at least half of their assignments;search habits vary by class year;and the value of different types of resources such as tutorials and forums varies by class year.Focus group results exposes the high frequency web sites used by the students in solving their programming assignments.
Date: May 2016
Creator: Tula, Naveen
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Analysis and Optimization of Graphene FET based Nanoelectronic Integrated Circuits (open access)

Analysis and Optimization of Graphene FET based Nanoelectronic Integrated Circuits

Like cell to the human body, transistors are the basic building blocks of any electronics circuits. Silicon has been the industries obvious choice for making transistors. Transistors with large size occupy large chip area, consume lots of power and the number of functionalities will be limited due to area constraints. Thus to make the devices smaller, smarter and faster, the transistors are aggressively scaled down in each generation. Moore's law states that the transistors count in any electronic circuits doubles every 18 months. Following this Moore's law, the transistor has already been scaled down to 14 nm. However there are limitations to how much further these transistors can be scaled down. Particularly below 10 nm, these silicon based transistors hit the fundamental limits like loss of gate control, high leakage and various other short channel effects. Thus it is not possible to favor the silicon transistors for future electronics applications. As a result, the research has shifted to new device concepts and device materials alternative to silicon. Carbon is the next abundant element found in the Earth and one of such carbon based nanomaterial is graphene. Graphene when extracted from Graphite, the same material used as the lid in pencil, …
Date: May 2016
Creator: Joshi, Shital
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Exploring Analog and Digital Design Using the Open-Source Electric VLSI Design System (open access)

Exploring Analog and Digital Design Using the Open-Source Electric VLSI Design System

The design of VLSI electronic circuits can be achieved at many different abstraction levels starting from system behavior to the most detailed, physical layout level. As the number of transistors in VLSI circuits is increasing, the complexity of the design is also increasing, and it is now beyond human ability to manage. Hence CAD (Computer Aided design) or EDA (Electronic Design Automation) tools are involved in the design. EDA or CAD tools automate the design, verification and testing of these VLSI circuits. In today’s market, there are many EDA tools available. However, they are very expensive and require high-performance platforms. One of the key challenges today is to select appropriate CAD or EDA tools which are open-source for academic purposes. This thesis provides a detailed examination of an open-source EDA tool called Electric VLSI Design system. An excellent and efficient CAD tool useful for students and teachers to implement ideas by modifying the source code, Electric fulfills these requirements. This thesis' primary objective is to explain the Electric software features and architecture and to provide various digital and analog designs that are implemented by this software for educational purposes. Since the choice of an EDA tool is based on the …
Date: May 2016
Creator: Aluru, Gunasekhar
Object Type: Thesis or Dissertation
System: The UNT Digital Library
Learning from small data set for object recognition in mobile platforms. (open access)

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

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 computing power. In this thesis, we present an object recognition system that resides and executes within a mobile device, which can efficiently extract image features and perform learning and classification. To account for the computing constraint, a novel feature extraction method that minimizes the data size and maintains data consistency is proposed. This system leverages principal component analysis method and is able to update the trained classifier when new examples become available . Our system relieves users from creating a lot of examples and makes it user friendly. The experimental results demonstrate that a learning method trained with a very small number of examples can achieve recognition accuracy above 90% in various acquisition conditions. In …
Date: May 2016
Creator: Liu, Siyuan
Object Type: Thesis or Dissertation
System: The UNT Digital Library