Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases (open access)

Bayesian Probabilistic Reasoning Applied to Mathematical Epidemiology for Predictive Spatiotemporal Analysis of Infectious Diseases

Abstract Probabilistic reasoning under uncertainty suits well to analysis of disease dynamics. The stochastic nature of disease progression is modeled by applying the principles of Bayesian learning. Bayesian learning predicts the disease progression, including prevalence and incidence, for a geographic region and demographic composition. Public health resources, prioritized by the order of risk levels of the population, will efficiently minimize the disease spread and curtail the epidemic at the earliest. A Bayesian network representing the outbreak of influenza and pneumonia in a geographic region is ported to a newer region with different demographic composition. Upon analysis for the newer region, the corresponding prevalence of influenza and pneumonia among the different demographic subgroups is inferred for the newer region. Bayesian reasoning coupled with disease timeline is used to reverse engineer an influenza outbreak for a given geographic and demographic setting. The temporal flow of the epidemic among the different sections of the population is analyzed to identify the corresponding risk levels. In comparison to spread vaccination, prioritizing the limited vaccination resources to the higher risk groups results in relatively lower influenza prevalence. HIV incidence in Texas from 1989-2002 is analyzed using demographic based epidemic curves. Dynamic Bayesian networks are integrated with …
Date: May 2006
Creator: Abbas, Kaja Moinudeen
System: The UNT Digital Library
Boosting for Learning From Imbalanced, Multiclass Data Sets (open access)

Boosting for Learning From Imbalanced, Multiclass Data Sets

In many real-world applications, it is common to have uneven number of examples among multiple classes. The data imbalance, however, usually complicates the learning process, especially for the minority classes, and results in deteriorated performance. Boosting methods were proposed to handle the imbalance problem. These methods need elongated training time and require diversity among the classifiers of the ensemble to achieve improved performance. Additionally, extending the boosting method to handle multi-class data sets is not straightforward. Examples of applications that suffer from imbalanced multi-class data can be found in face recognition, where tens of classes exist, and in capsule endoscopy, which suffers massive imbalance between the classes. This dissertation introduces RegBoost, a new boosting framework to address the imbalanced, multi-class problems. This method applies a weighted stratified sampling technique and incorporates a regularization term that accommodates multi-class data sets and automatically determines the error bound of each base classifier. The regularization parameter penalizes the classifier when it misclassifies instances that were correctly classified in the previous iteration. The parameter additionally reduces the bias towards majority classes. Experiments are conducted using 12 diverse data sets with moderate to high imbalance ratios. The results demonstrate superior performance of the proposed method compared …
Date: December 2013
Creator: Abouelenien, Mohamed
System: The UNT Digital Library
Online Construction of Android Application Test Suites (open access)

Online Construction of Android Application Test Suites

Mobile applications play an important role in the dissemination of computing and information resources. They are often used in domains such as mobile banking, e-commerce, and health monitoring. Cost-effective testing techniques in these domains are critical. This dissertation contributes novel techniques for automatic construction of mobile application test suites. In particular, this work provides solutions that focus on the prohibitively large number of possible event sequences that must be sampled in GUI-based mobile applications. This work makes three major contributions: (1) an automated GUI testing tool, Autodroid, that implements a novel online approach to automatic construction of Android application test suites (2) probabilistic and combinatorial-based algorithms that systematically sample the input space of Android applications to generate test suites with GUI/context events and (3) empirical studies to evaluate the cost-effectiveness of our techniques on real-world Android applications. Our experiments show that our techniques achieve better code coverage and event coverage compared to random test generation. We demonstrate that our techniques are useful for automatic construction of Android application test suites in the absence of source code and preexisting abstract models of an Application Under Test (AUT). The insights derived from our empirical studies provide guidance to researchers and practitioners involved …
Date: December 2017
Creator: Adamo, David T., Jr.
System: The UNT Digital Library
Joint Schemes for Physical Layer Security and Error Correction (open access)

Joint Schemes for Physical Layer Security and Error Correction

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 of the ciphers are analyzed against known-plaintext and chosen-plaintext attacks and are found to be secure. Randomization test was also conducted on these schemes and the results are presented. For the proof of concept, the schemes were implemented in software and hardware and these shows a reduction in hardware usage compared to conventional schemes. As a result, joint schemes for error correction and security provide security to the physical layer of wireless communication systems, a layer in the protocol stack where currently little or no security is implemented. In this physical layer security approach, the properties of powerful error correcting codes are exploited to deliver reliability to the intended parties, high security against eavesdroppers and efficiency in communication system. The notion of a highly secure and reliable …
Date: August 2011
Creator: Adamo, Oluwayomi Bamidele
System: The UNT Digital Library
VLSI Architecture and FPGA Prototyping of a Secure Digital Camera for Biometric Application (open access)

VLSI Architecture and FPGA Prototyping of a Secure Digital Camera for Biometric Application

This thesis presents a secure digital camera (SDC) that inserts biometric data into images found in forms of identification such as the newly proposed electronic passport. However, putting biometric data in passports makes the data vulnerable for theft, causing privacy related issues. An effective solution to combating unauthorized access such as skimming (obtaining data from the passport's owner who did not willingly submit the data) or eavesdropping (intercepting information as it moves from the chip to the reader) could be judicious use of watermarking and encryption at the source end of the biometric process in hardware like digital camera or scanners etc. To address such issues, a novel approach and its architecture in the framework of a digital camera, conceptualized as an SDC is presented. The SDC inserts biometric data into passport image with the aid of watermarking and encryption processes. The VLSI (very large scale integration) architecture of the functional units of the SDC such as watermarking and encryption unit is presented. The result of the hardware implementation of Rijndael advanced encryption standard (AES) and a discrete cosine transform (DCT) based visible and invisible watermarking algorithm is presented. The prototype chip can carry out simultaneous encryption and watermarking, which …
Date: August 2006
Creator: Adamo, Oluwayomi Bamidele
System: The UNT Digital Library
Improving Memory Performance for Both High Performance Computing and Embedded/Edge Computing Systems (open access)

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

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 obviates the need for offline analysis of an application to determine page migration strategies. Furthermore, I explored different migration strategies like reverse migration, sub page migration that I found to be beneficial depending on the application behavior. Ideally, page migration strategies redirect the demand memory traffic to faster memory to improve the memory performance. In my third contribution, I worked and evaluated a memory-side accelerator to assist the main computational core in locating the non-zero elements of a sparse matrix that are typically used in scientific, machine learning workloads on a low-power embedded system configuration. Thus my contributions narrow the speed-gap by improving the latency and/or bandwidth between CPU and memory.
Date: December 2021
Creator: Adavally, Shashank
System: The UNT Digital Library
Qos Aware Service Oriented Architecture (open access)

Qos Aware Service Oriented Architecture

Service-oriented architecture enables web services to operate in a loosely-coupled setting and provides an environment for dynamic discovery and use of services over a network using standards such as WSDL, SOAP, and UDDI. Web service has both functional and non-functional characteristics. This thesis work proposes to add QoS descriptions (non-functional properties) to WSDL and compose various services to form a business process. This composition of web services also considers QoS properties along with functional properties and the composed services can again be published as a new Web Service and can be part of any other composition using Composed WSDL.
Date: August 2013
Creator: Adepu, Sagarika
System: The UNT Digital Library
Evaluating Appropriateness of Emg and Flex Sensors for Classifying Hand Gestures (open access)

Evaluating Appropriateness of Emg and Flex Sensors for Classifying Hand Gestures

Hand and arm gestures are a great way of communication when you don't want to be heard, quieter and often more reliable than whispering into a radio mike. In recent years hand gesture identification became a major active area of research due its use in various applications. The objective of my work is to develop an integrated sensor system, which will enable tactical squads and SWAT teams to communicate when there is absence of a Line of Sight or in the presence of any obstacles. The gesture set involved in this work is the standardized hand signals for close range engagement operations used by military and SWAT teams. The gesture sets involved in this work are broadly divided into finger movements and arm movements. The core components of the integrated sensor system are: Surface EMG sensors, Flex sensors and accelerometers. Surface EMG is the electrical activity produced by muscle contractions and measured by sensors directly attached to the skin. Bend Sensors use a piezo resistive material to detect the bend. The sensor output is determined by both the angle between the ends of the sensor as well as the flex radius. Accelerometers sense the dynamic acceleration and inclination in 3 …
Date: May 2013
Creator: Akumalla, Sarath Chandra
System: The UNT Digital Library
Hybrid Optimization Models for Depot Location-Allocation and Real-Time Routing of Emergency Deliveries (open access)

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

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 low-resource countries, is designed. It involves the development of algorithms for optimizing pre-and post-disaster activities. The studies result in the development of four models: (1) an adaptation of a machine learning clustering algorithm, for pre-positioning depots and emergency operation centers, which optimizes the placement of these depots, such that the largest geographical location is covered, and the maximum number of individuals reached, with minimal facility cost; (2) an optimization algorithm for routing relief distribution, using heterogenous fleets of vehicle, with considerations for uncertainties in humanitarian supplies; (3) a genetic algorithm-based route improvement model; and (4) a model for integrating possible new locations into the routing network, in real-time, using emergency severity ranking, with a high priority on the most-vulnerable population. The clustering approach to solving dept location-allocation problem produces a better time complexity, and the …
Date: May 2021
Creator: Akwafuo, Sampson E
System: The UNT Digital Library
Traffic Forecasting Applications Using Crowdsourced Traffic Reports and Deep Learning (open access)

Traffic Forecasting Applications Using Crowdsourced Traffic Reports and Deep Learning

Intelligent transportation systems (ITS) are essential tools for traffic planning, analysis, and forecasting that can utilize the huge amount of traffic data available nowadays. In this work, we aggregated detailed traffic flow sensor data, Waze reports, OpenStreetMap (OSM) features, and weather data, from California Bay Area for 6 months. Using that data, we studied three novel ITS applications using convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The first experiment is an analysis of the relation between roadway shapes and accident occurrence, where results show that the speed limit and number of lanes are significant predictors for major accidents on highways. The second experiment presents a novel method for forecasting congestion severity using crowdsourced data only (Waze, OSM, and weather), without the need for traffic sensor data. The third experiment studies the improvement of traffic flow forecasting using accidents, number of lanes, weather, and time-related features, where results show significant performance improvements when the additional features where used.
Date: May 2020
Creator: Alammari, Ali
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
System: The UNT Digital Library

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

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 this dissertation, we complement the lack of previous work on counterhate arguments by analyzing and detecting them. Firstly, we study the relationships between hateful tweets and replies. Specifically, we analyze their fine-grained relationships by indicating whether the reply counters the hate, provides a justification, attacks the author of the tweet, or adds additional hate. The most obvious finding is that most replies generally agree with the hateful tweets; only 20% of them counter the hate. Secondly, we focus on the hate directed toward individuals and detect authentic counterhate arguments from online articles. We propose a methodology that assures the authenticity of the argument and its specificity to the individual of interest. We show that finding arguments in online articles is an efficient alternative compared to …
Date: May 2023
Creator: Albanyan, Abdullah Abdulaziz
System: The UNT Digital Library

Comparison and Evaluation of Existing Analog Circuit Simulator using Sigma-Delta Modulator

Access: Use of this item is restricted to the UNT Community
In the world of VLSI (very large scale integration) technology, there are many different types of circuit simulators that are used to design and predict the circuit behavior before actual fabrication of the circuit. In this thesis, I compared and evaluated existing circuit simulators by considering standard benchmark circuits. The circuit simulators which I evaluated and explored are Ngspice, Tclspice, Winspice (open source) and Spectre® (commercial). I also tested standard benchmarks using these circuit simulators and compared their outputs. The simulators are evaluated using design metrics in order to quantify their performance and identify efficient circuit simulators. In addition, I designed a sigma-delta modulator and its individual components using the analog behavioral language Verilog-A. Initially, I performed simulations of individual components of the sigma-delta modulator and later of the whole system. Finally, CMOS (complementary metal-oxide semiconductor) transistor-level circuits were designed for the differential amplifier, operational amplifier and comparator of the modulator.
Date: December 2006
Creator: Ale, Anil Kumar
System: The UNT Digital Library

Toward Leveraging Artificial Intelligence to Support the Identification of Accessibility Challenges

The goal of this thesis is to support the automated identification of accessibility in user reviews or bug reports, to help technology professionals prioritize their handling, and, thus, to create more inclusive apps. Particularly, we propose a model that takes as input accessibility user reviews or bug reports and learns their keyword-based features to make a classification decision, for a given review, on whether it is about accessibility or not. Our empirically driven study follows a mixture of qualitative and quantitative methods. We introduced models that can accurately identify accessibility reviews and bug reports and automate detecting them. Our models can automatically classify app reviews and bug reports as accessibility-related or not so developers can easily detect accessibility issues with their products and improve them to more accessible and inclusive apps utilizing the users' input. Our goal is to create a sustainable change by including a model in the developer's software maintenance pipeline and raising awareness of existing errors that hinder the accessibility of mobile apps, which is a pressing need. In light of our findings from the Blackboard case study, Blackboard and the course material are not easily accessible to deaf students and hard of hearing. Thus, deaf students …
Date: May 2023
Creator: Aljedaani, Wajdi Mohammed R M., Sr.
System: The UNT Digital Library
Scalable Next Generation Blockchains for Large Scale Complex Cyber-Physical Systems and Their Embedded Systems in Smart Cities (open access)

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

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 blocks are securely linked. This dissertation introduces Proof of Rapid Authentication, a novel consensus algorithm. This innovative method uses a distributed file to safely store a unique identifier (UID) based on node attributes to verify two blocks faster. This study also addresses CPS hardware security. A system of interconnected, user-unique identifiers allows each block's history to be monitored. This maintains each transaction and the validators who checked the block to ensure trustworthiness and honesty. We constructed a digital version that stays in sync with the distributed ledger as all nodes are linked by a NodeChain. The ledger is distributed without compromising node autonomy. Moreover, FlexiChain Layer 0 distributed ledger is also introduced and can connect and validate Layer 1 blockchains. This project produced a DAG-based blockchain integration platform with hardware security. The results illustrate a practical technique …
Date: July 2023
Creator: Alkhodair, Ahmad Jamal M
System: The UNT Digital Library
FruitPAL: An IoT-Enabled Framework for Automatic Monitoring of Fruit Consumption in Smart Healthcare (open access)

FruitPAL: An IoT-Enabled Framework for Automatic Monitoring of Fruit Consumption in Smart Healthcare

This research proposes FruitPAL and FruitPAL 2.0. They are full automatic devices that can detect fruit consumption to reduce the risk of disease. Allergies to fruits can seriously impair the immune system. A novel device (FruitPAL) detecting fruit that can cause allergies is proposed in this thesis. The device can detect fifteen types of fruit and alert the caregiver when an allergic reaction may have happened. The YOLOv8 model is employed to enhance accuracy and response time in detecting dangers. The notification will be transmitted to the mobile device through the cloud, as it is a commonly utilized medium. The proposed device can detect the fruit with an overall precision of 86%. FruitPAL 2.0 is envisioned as a device that encourages people to consume fruit. Fruits contain a variety of essential nutrients that contribute to the general health of the human body. FruitPAL 2.0 is capable of analyzing the consumed fruit and then determining its nutritional value. FruitPAL 2.0 has been trained on YOLOv5 V6.0. FruitPAL 2.0 has an overall precision of 90% in detecting the fruit. The purpose of this study is to encourage fruit consumption unless it causes illness. Even though fruit plays an important role in people's …
Date: December 2023
Creator: Alkinani, Abdulrahman Ibrahim M.
System: The UNT Digital Library

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

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 comprises of five modules that operate together to extract attributes values from natural language access control policies (NLACPs); map the extracted values to attribute keys; and assign each key-value pair to an appropriate entity. For ABAC constraints extraction framework, we design a two-phase process to extract ABAC constraints from NLACPs. The process begins with the identification phase which focuses on identifying the right boundary of constraint expressions. Next is the normalization phase, that aims at extracting the actual elements that pose a constraint. On the other hand, our hybrid ABAC policy engineering framework consists of 5 modules. This framework combines top-down and bottom-up policy engineering techniques to overcome the shortcomings of both approaches and to generate policies that are more intuitive and relevant to actual organization policies. With this, we believe that our work takes essential steps towards …
Date: August 2020
Creator: Alohaly, Manar
System: The UNT Digital Library
3GPP Long Term Evolution LTE Scheduling (open access)

3GPP Long Term Evolution LTE Scheduling

Future generation cellular networks are expected to deliver an omnipresent broadband access network for an endlessly increasing number of subscribers. Long term Evolution (LTE) represents a significant milestone towards wireless networks known as 4G cellular networks. A key feature of LTE is the implementation of enhanced Radio Resource Management (RRM) mechanism to improve the system performance. The structure of LTE networks was simplified by diminishing the number of the nodes of the core network. Also, the design of the radio protocol architecture is quite unique. In order to achieve high data rate in LTE, 3rd Generation Partnership Project (3GPP) has selected Orthogonal Frequency Division Multiplexing (OFDM) as an appropriate scheme in terms of downlinks. However, the proper scheme for an uplink is the Single-Carrier Frequency Domain Multiple Access due to the peak-to-average-power-ratio (PAPR) constraint. LTE packet scheduling plays a primary role as part of RRM to improve the system’s data rate as well as supporting various QoS requirements of mobile services. The major function of the LTE packet scheduler is to assign Physical Resource Blocks (PRBs) to mobile User Equipment (UE). In our work, we formed a proposed packet scheduler algorithm. The proposed scheduler algorithm acts based on the number …
Date: December 2013
Creator: Alotaibi, Sultan
System: The UNT Digital Library
Radio Resource Control Approaches for LTE-Advanced Femtocell Networks (open access)

Radio Resource Control Approaches for LTE-Advanced Femtocell Networks

The architecture of mobile networks has dramatically evolved in order to fulfill the growing demands on wireless services and data. The radio resources, which are used by the current mobile networks, are limited while the users demands are substantially increasing. In the future, tremendous Internet applications are expected to be served by mobile networks. Therefore, increasing the capacity of mobile networks has become a vital issue. Heterogeneous networks (HetNets) have been considered as a promising paradigm for future mobile networks. Accordingly, the concept of small cell has been introduced in order to increase the capacity of the mobile networks. A femtocell network is a kind of small cell networks. Femtocells are deployed within macrocells coverage. Femtocells cover small areas and operate with low transmission power while providing high capacity. Also, UEs can be offloaded from macrocells to femtocells. Thus, the capacity can be increased. However, this will introduce different technical challenges. The interference has become one of the key challenges for deploying femtocells within a certain macrocells coverage. Undesirable impact of the interference can degrade the performance of the mobile networks. Therefore, radio resource management mechanisms are needed in order to address key challenges of deploying femtocells. The objective of …
Date: August 2018
Creator: Alotaibi, Sultan Radhi
System: The UNT Digital Library
A Data-Driven Computational Framework to Assess the Risk of Epidemics at Global Mass Gatherings (open access)

A Data-Driven Computational Framework to Assess the Risk of Epidemics at Global Mass Gatherings

This dissertation presents a data-driven computational epidemic framework to simulate disease epidemics at global mass gatherings. The annual Muslim pilgrimage to Makkah, Saudi Arabia is used to demonstrate the simulation and analysis of various disease transmission scenarios throughout the different stages of the event from the arrival to the departure of international participants. The proposed agent-based epidemic model efficiently captures the demographic, spatial, and temporal heterogeneity at each stage of the global event of Hajj. Experimental results indicate the substantial impact of the demographic and mobility patterns of the heterogeneous population of pilgrims on the progression of the disease spread in the different stages of Hajj. In addition, these simulations suggest that the differences in the spatial and temporal settings in each stage can significantly affect the dynamic of the disease. Finally, the epidemic simulations conducted at the different stages in this dissertation illustrate the impact of the differences between the duration of each stage in the event and the length of the infectious and latent periods. This research contributes to a better understanding of epidemic modeling in the context of global mass gatherings to predict the risk of disease pandemics caused by associated international travel. The computational modeling and …
Date: May 2019
Creator: Alshammari, Sultanah
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
System: The UNT Digital Library
Towards a Unilateral Sensing System for Detecting Person-to-Person Contacts (open access)

Towards a Unilateral Sensing System for Detecting Person-to-Person Contacts

The contact patterns among individuals can significantly affect the progress of an infectious outbreak within a population. Gathering data about these interaction and mixing patterns is essential to assess computational modeling of infectious diseases. Various self-report approaches have been designed in different studies to collect data about contact rates and patterns. Recent advances in sensing technology provide researchers with a bilateral automated data collection devices to facilitate contact gathering overcoming the disadvantages of previous approaches. In this study, a novel unilateral wearable sensing architecture has been proposed that overcome the limitations of the bi-lateral sensing. Our unilateral wearable sensing system gather contact data using hybrid sensor arrays embedded in wearable shirt. A smartphone application has been used to transfer the collected sensors data to the cloud and apply deep learning model to estimate the number of human contacts and the results are stored in the cloud database. The deep learning model has been developed on the hand labelled data over multiple experiments. This model has been tested and evaluated, and these results were reported in the study. Sensitivity analysis has been performed to choose the most suitable image resolution and format for the model to estimate contacts and to analyze …
Date: December 2018
Creator: Amara, Pavan Kumar
System: The UNT Digital Library
Real-time Rendering of Burning Objects in Video Games (open access)

Real-time Rendering of Burning Objects in Video Games

In recent years there has been growing interest in limitless realism in computer graphics applications. Among those, my foremost concentration falls into the complex physical simulations and modeling with diverse applications for the gaming industry. Different simulations have been virtually successful by replicating the details of physical process. As a result, some were strong enough to lure the user into believable virtual worlds that could destroy any sense of attendance. In this research, I focus on fire simulations and its deformation process towards various virtual objects. In most game engines model loading takes place at the beginning of the game or when the game is transitioning between levels. Game models are stored in large data structures. Since changing or adjusting a large data structure while the game is proceeding may adversely affect the performance of the game. Therefore, developers may choose to avoid procedural simulations to save resources and avoid interruptions on performance. I introduce a process to implement a real-time model deformation while maintaining performance. It is a challenging task to achieve high quality simulation while utilizing minimum resources to represent multiple events in timely manner. Especially in video games, this overwhelming criterion would be robust enough to sustain …
Date: August 2013
Creator: Amarasinghe, Dhanyu Eshaka
System: The UNT Digital Library
An Integrated Architecture for Ad Hoc Grids (open access)

An Integrated Architecture for Ad Hoc Grids

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, and assume a well-defined non-changing collaboration. To support grid applications that do not confirm to these assumptions, we propose the concept of ad hoc grids. In the context of this research, we propose a novel architecture for ad hoc grids that integrates a suite of component frameworks. Specifically, our architecture combines the community management framework, security framework, abstraction framework, quality of service framework, and reputation framework. The overarching objective of our integrated architecture is to support a variety of grid applications in a self-controlled fashion with the help of a self-organizing ad hoc community. We introduce mechanisms in our architecture that successfully isolates malicious elements from the community, inherently improving the quality of grid services and extracting deterministic quality assurances from the underlying infrastructure. We also emphasize on the technology-independence of our …
Date: May 2006
Creator: Amin, Kaizar Abdul Husain
System: The UNT Digital Library