You limited your search to:

  Partner: UNT Libraries
 Department: Department of Computer Science and Engineering
 Collection: UNT Theses and Dissertations
Rapid Prototyping and Design of a Fast Random Number Generator

Rapid Prototyping and Design of a Fast Random Number Generator

Date: May 2012
Creator: Franco, Juan
Description: Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. the core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable. the fundamental hurdle is that digital computers cannot generate truly random numbers because the states and transitions of digital systems are well understood and predictable. Nothing in a digital computer happens truly randomly. Digital computers are sequential machines that perform a current state and move to the next state in a deterministic fashion. to generate any secure hash or encrypted word a random number is needed. But since computers are not random, random sequences are commonly used. Random sequences are algorithms that generate a pattern of values that appear to be random but after some time start repeating. This thesis implements a digital random number generator using MATLAB, FGPA prototyping, and custom silicon design. This random number generator is able to use a truly random CMOS source to generate the random number. Statistical benchmarks are used to test the results and to show that the design works. Thus the proposed random number generator will be useful ...
Contributing Partner: UNT Libraries
Region aware DCT domain invisible robust blind watermarking for color images.

Region aware DCT domain invisible robust blind watermarking for color images.

Date: December 2008
Creator: Naraharisetti, Sahasan
Description: The multimedia revolution has made a strong impact on our society. The explosive growth of the Internet, the access to this digital information generates new opportunities and challenges. The ease of editing and duplication in digital domain created the concern of copyright protection for content providers. Various schemes to embed secondary data in the digital media are investigated to preserve copyright and to discourage unauthorized duplication: where digital watermarking is a viable solution. This thesis proposes a novel invisible watermarking scheme: a discrete cosine transform (DCT) domain based watermark embedding and blind extraction algorithm for copyright protection of the color images. Testing of the proposed watermarking scheme's robustness and security via different benchmarks proves its resilience to digital attacks. The detectors response, PSNR and RMSE results show that our algorithm has a better security performance than most of the existing algorithms.
Contributing Partner: UNT Libraries
Resource Efficient and Scalable Routing using Intelligent Mobile Agents

Resource Efficient and Scalable Routing using Intelligent Mobile Agents

Date: May 2003
Creator: Amin, Kaizar Abdul Husain
Description: Many of the contemporary routing algorithms use simple mechanisms such as flooding or broadcasting to disseminate the routing information available to them. Such routing algorithms cause significant network resource overhead due to the large number of messages generated at each host/router throughout the route update process. Many of these messages are wasteful since they do not contribute to the route discovery process. Reducing the resource overhead may allow for several algorithms to be deployed in a wide range of networks (wireless and ad-hoc) which require a simple routing protocol due to limited availability of resources (memory and bandwidth). Motivated by the need to reduce the resource overhead associated with routing algorithms a new implementation of distance vector routing algorithm using an agent-based paradigm known as Agent-based Distance Vector Routing (ADVR) has been proposed. In ADVR, the ability of route discovery and message passing shifts from the nodes to individual agents that traverse the network, co-ordinate with each other and successively update the routing tables of the nodes they visit.
Contributing Partner: UNT Libraries
Resource Management in Wireless Networks

Resource Management in Wireless Networks

Date: August 2006
Creator: Arepally, Anurag
Description: A local call admission control (CAC) algorithm for third generation wireless networks was designed and implemented, which allows for the simulation of network throughput for different spreading factors and various mobility scenarios. A global CAC algorithm is also implemented and used as a benchmark since it is inherently optimized; it yields the best possible performance but has an intensive computational complexity. Optimized local CAC algorithm achieves similar performance as global CAC algorithm at a fraction of the computational cost. Design of a dynamic channel assignment algorithm for IEEE 802.11 wireless systems is also presented. Channels are assigned dynamically depending on the minimal interference generated by the neighboring access points on a reference access point. Analysis of dynamic channel assignment algorithm shows an improvement by a factor of 4 over the default settings of having all access points use the same channel, resulting significantly higher network throughput.
Contributing Partner: UNT Libraries
Rhythms of Interaction in Global Software Development Teams

Rhythms of Interaction in Global Software Development Teams

Date: August 2010
Creator: Kesavan Nair Meena, Suneetha Nair
Description: Researchers have speculated that global software teams have activity patterns that are dictated by work-place schedules or a client's need. Similar patterns have been suggested for individuals enrolled in distant learning projects that require students to post feedback in response to questions or assignments. Researchers tend to accept the notion that students' temporal patterns adjust to academic or social calendars and are a result of choices made within these constraints. Although there is some evidence that culture do have an impact on communication activity behavior, there is not a clear how each of these factors may relate to work done in online groups. This particular study represents a new approach to studying student-group communication activities and also pursues an alternative approach by using activity data from students participating in a global software development project to generate a variety of complex measures that capture patterns about when students work. Students work habits are also often determined by where they live and what they are working on. Moreover, students tend to work on group projects in cycles, which correspond to a start, middle, and end time period. Knowledge obtained from this study should provide insight into current empirical research on global software ...
Contributing Partner: UNT Libraries
The Role of Intelligent Mobile Agents in Network Management and Routing

The Role of Intelligent Mobile Agents in Network Management and Routing

Date: December 2000
Creator: Balamuru, Vinay Gopal
Description: In this research, the application of intelligent mobile agents to the management of distributed network environments is investigated. Intelligent mobile agents are programs which can move about network systems in a deterministic manner in carrying their execution state. These agents can be considered an application of distributed artificial intelligence where the (usually small) agent code is moved to the data and executed locally. The mobile agent paradigm offers potential advantages over many conventional mechanisms which move (often large) data to the code, thereby wasting available network bandwidth. The performance of agents in network routing and knowledge acquisition has been investigated and simulated. A working mobile agent system has also been designed and implemented in JDK 1.2.
Contributing Partner: UNT Libraries
Scene Analysis Using Scale Invariant Feature Extraction and Probabilistic Modeling

Scene Analysis Using Scale Invariant Feature Extraction and Probabilistic Modeling

Access: Use of this item is restricted to the UNT Community.
Date: August 2011
Creator: Shen, Yao
Description: Conventional pattern recognition systems have two components: feature analysis and pattern classification. For any object in an image, features could be considered as the major characteristic of the object either for object recognition or object tracking purpose. Features extracted from a training image, can be used to identify the object when attempting to locate the object in a test image containing many other objects. To perform reliable scene analysis, it is important that the features extracted from the training image are detectable even under changes in image scale, noise and illumination. Scale invariant feature has wide applications such as image classification, object recognition and object tracking in the image processing area. In this thesis, color feature and SIFT (scale invariant feature transform) are considered to be scale invariant feature. The classification, recognition and tracking result were evaluated with novel evaluation criterion and compared with some existing methods. I also studied different types of scale invariant feature for the purpose of solving scene analysis problems. I propose probabilistic models as the foundation of analysis scene scenario of images. In order to differential the content of image, I develop novel algorithms for the adaptive combination for multiple features extracted from images. I ...
Contributing Partner: UNT Libraries
Sentence Similarity Analysis with Applications in Automatic Short Answer Grading

Sentence Similarity Analysis with Applications in Automatic Short Answer Grading

Date: August 2012
Creator: Mohler, Michael A.G.
Description: In this dissertation, I explore unsupervised techniques for the task of automatic short answer grading. I compare a number of knowledge-based and corpus-based measures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel technique to improve the performance of the system by integrating automatic feedback from the student answers. I continue to combine graph alignment features with lexical semantic similarity measures and employ machine learning techniques to show that grade assignment error can be reduced compared to a system that considers only lexical semantic measures of similarity. I also detail a preliminary attempt to align the dependency graphs of student and instructor answers in order to utilize a structural component that is necessary to simulate human-level grading of student answers. I further explore the utility of these techniques to several related tasks in natural language processing including the detection of text similarity, paraphrase, and textual entailment.
Contributing Partner: UNT Libraries
A Smooth-turn Mobility Model for Airborne Networks

A Smooth-turn Mobility Model for Airborne Networks

Date: August 2012
Creator: He, Dayin
Description: In this article, I introduce a novel airborne network mobility model, called the Smooth Turn Mobility Model, that captures the correlation of acceleration for airborne vehicles across time and spatial coordinates. E?ective routing in airborne networks (ANs) relies on suitable mobility models that capture the random movement pattern of airborne vehicles. As airborne vehicles cannot make sharp turns as easily as ground vehicles do, the widely used mobility models for Mobile Ad Hoc Networks such as Random Waypoint and Random Direction models fail. Our model is realistic in capturing the tendency of airborne vehicles toward making straight trajectory and smooth turns with large radius, and whereas is simple enough for tractable connectivity analysis and routing design.
Contributing Partner: UNT Libraries
Social Network Simulation and Mining Social Media to Advance Epidemiology

Social Network Simulation and Mining Social Media to Advance Epidemiology

Date: August 2009
Creator: Corley, Courtney David
Description: Traditional Public Health decision-support can benefit from the Web and social media revolution. This dissertation presents approaches to mining social media benefiting public health epidemiology. Through discovery and analysis of trends in Influenza related blogs, a correlation to Centers for Disease Control and Prevention (CDC) influenza-like-illness patient reporting at sentinel health-care providers is verified. A second approach considers personal beliefs of vaccination in social media. A vaccine for human papillomavirus (HPV) was approved by the Food and Drug Administration in May 2006. The virus is present in nearly all cervical cancers and implicated in many throat and oral cancers. Results from automatic sentiment classification of HPV vaccination beliefs are presented which will enable more accurate prediction of the vaccine's population-level impact. Two epidemic models are introduced that embody the intimate social networks related to HPV transmission. Ultimately, aggregating these methodologies with epidemic and social network modeling facilitate effective development of strategies for targeted interventions.
Contributing Partner: UNT Libraries