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Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
This thesis presents the Scalable Parallel Random Number Generators Library (SPRNG) version 4.0. SPRNG is a widely used software package for both serial and parallel pseudorandom number generation. Its generators satisfy every known...
We present two studies incorporating existing biological knowledge into differential gene expression analysis that attempt to place the results within a broader biological context. The studies investigate breast cancer health disparity...
In this dissertation, I explore different types of applications in the area of applied machine learning, time series analysis, and prediction. Time series forecasting is a fundamental task in machine learning and data mining. It is an...
Ensemble learning algorithms are among the most widely used and indispensable tools in machine learning, data science and predictive analytics. Their widespread use can be attributed to the success of ensemble learning algorithms in...
The fast increasing length of random number streams, the application of more powerful cores and emerging various Random Number Generators (RNGs) lead to a revolution from traditional RNGs. The authentic RNGs are mainly based on the...
In 4D-Var data assimilation for geophysical models, the goal is to reduce the lack of fit between model and observations (strong constraint approach assuming perfect model). In the last two decades four dimensional variational technique...
Alzheimer's disease (AD) is one of the top 10 leading causes of death in the US; it debilitates memory and impairs cognition. The current core clinical criteria for diagnosis of AD are based on functional deficits and cognitive...
Metadata is an important aspect in learning resource discovery, reuse of learning resources, within-collection organization of learning resources, retrieval of non-textual media, and interoperability among learning resources. This paper...
Since 2008, the Android ecosystem has been tremendously popular with consumers, developers, and manufacturers due to the open nature of the operating system and its compatibility and availability on a range of devices. This, however, ...
Pattern recognition is fundamental to a variety of significant applications that includes but is not limited to medical diagnoses, speech recognition, and object recognition. The increased security concerns in the aftermath of the 9/11...
The most common approaches to analyzing algorithms are worst-case analysis, average-case analysis, and experimental analysis. In most cases, until recently, experimental analysis has not been given priority. The theoretical computer...
Mobility models, or the mobility patterns used to simulate the motion of participating nodes, play a vital role in the simulation of Vehicular Ad Hoc Networks (VANET). Even with recent research focusing on development of mobility models...
In many pattern classification problems, efficiently learning a suitable low-dimensional representation of high dimensional data is essential. The advantages of linear dimension reduction methods are their simplicity and efficiency....
This dissertation is concerned with efficient compilation of our Java-based, high- performance, library-oriented, SPMD style, data parallel programming language: HPJava. It starts with some historical review of data-parallel languages...
I/O services provided by general-purpose operating systems and commodity hardware are designed for achieving high average-case performance without worrying about timing constraints. A common trend is to use such components to build...
We construct a phase field model for simulating the adhesion of a cell membrane to a substrate. The model features two phase field functions which are used to simulate the membrane and the substrate. An energy model is defined which...
As the world is moving towards exascale computing, interconnect networks are becoming more and more important because of their omnipresent use in high performance computing systems and in large scale data centers. The performance of an...
The demand for high performance wireless networks and systems have become increasingly high over the last decade. This dissertation addresses three systems that were designed to improving the efficiency, reliability and security of...
This thesis studies the 1-center problem on road networks, an important problem in GIS. Using Euclidean embeddings, and reduction to fast nearest neighbor search, an approximation algorithm is devised for this problem. On real world data...
Level-one data cache (L1 DC) accesses impact energy usage as they frequently occur and use signif icantly more energy than register file accesses. Modern processors use virtually-indexed, physically tagged caches to reduce the L1 DC...
The computer architecture community relies on standard benchmark suites like MiBench, NAS, PARSEC, SPEC CPU2006 (SPEC)®, and SPLASH to study different hardware designs, but such suites are insufficient for evaluating mobile platforms...
Universal Global Adaptive routing (UGAL) is a common routing scheme used in systems based on the Dragonfly interconnect topology. UGAL uses information about local link-loads to make adaptive routing decisions. Traffic Pattern-based...
The Prisoners' Problem can be stated as follows: Two prisoners, Alice and Bob, want to communicate a secret escape plan under the surveillance of a warden, Wendy. To be indiscernible, the communication must appear to Wendy to be `...
The most common method of preventing unauthorized access to digital information is through the use of a password-based authentication system. The strength of a password-based authentication system relies on a humans ability to generate a...
Mobile computing is the new norm. As people feel increasingly comfortable computing in public places such as coffee shops and transportation hubs, the threat of exposing sensitive information increases. While solutions exist to guard the...
As the gap between CPU speed and memory speed widens, it is appropriate to investigate alternative storage systems. One approach is to use a large data register file. Registers, in general, offer several advantages when accessing data, ...
In addition to requiring routing to be dead-lock free and deterministic, Infiniband networks adopt destination based routing, which further complicates the routing design by putting additional constraints on the paths that can be...
Compromised machines are one of the key security threats on the Internet; they are often used to launch various security attacks such as DDoS, spamming, and identity theft. In this thesis we address this issue by investigating effective...
Artificial Neural Networks form the basis of very powerful learning methods. It has been observed that a naive application of fully connected neural networks often leads to overfitting. In an attempt to circumvent this issue, a prior...
This research presents several important developments in pattern classification using fuzzy neural networks and BK-Square products and presents extensions to max-min fuzzy neural network research. In this research, the max and min...
Mobile Ad Hoc Networks (MANETs) are a collection of wireless mobile nodes with links that are made and broken arbitrarily. They have limited resources in power, computation, broadcast range, and a dynamic topology with no fixed...
This dissertation addresses the creation of a unique, adaptable, and light-weight core methodology to address the problem of Soft Error Modeling and Simulation. This core methodology was successfully tailored, validated, and expanded to...
Monte Carlo applications are widely perceived as computationally intensive but naturally parallel. Therefore, they can be effectively executed on the grid using the dynamic bag-of-work model. We improve the efficiency of the subtask...
Statistical analysis methods are used by neuroscience researchers to obtain meaningful information from functional magnetic resonance imaging data to learn more about mind and brain. Machine learning, more specifically pattern...
This paper will discuss the development of a music classification system as a component in a music recommendation system. The front-end portion of the system is an Android Media Player application named SmartPlayer. The player is an...
The computing power on the leadership-class supercomputers has been growing exponentially over the past few decades, and is projected to reach exascale in the near future. This trend, however, will continue to push forward the peak I/O...
Recent advances in multicasting present new opportunities for improving communication performance for clusters of workstations. The standard IP multicast, however, only supports unreliable multicast, which is diffcult to use for building...
Recently, the prevalence of WiFi devices and ubiquitous coverage of WiFi network provide us the opportunity to extend WiFi capabilities beyond communication, particularly in sensing the physical environment. Most existing systems that...
Random number generators have been studied and used for decades, and various kinds of generators have been proposed and improved to fit different types of problems. Better generators fit the problem tightly and utilize the architecture...
The computing capabilities of the high performance computing systems have increased manyfold over the span of years following Moores law and have achieved petascale recently. Following the trend, the computation cababilities are expected...
There are a wide variety of clustering and optimization algorithms which work in vector spaces, but relatively fewer that work on graphs. An algorithm to embed road network metrics into vector spaces is presented in this document, which...
Anonymous networks play a critical role in supporting free speech and user privacy on the Internet. Over the years, many fundamental algorithms and schemes have been proposed to facilitate the development of anonymous networks, including...
In this paper we show that botnets and specifically peer-to-peer botnets, pose a considerable threat to our national security. We examine the rise of the botnet threat and the technology that makes this threat possible. We also examine...
Mobile agent systems provide a new method for computer communication. A mobile agent can migrate from platform to platform, performing a task or computation for its originator. Mobile agents are a promising new technology; however, there...
Internet of Things (IOT) systems are becoming a popular concept of every smart system. Many people intend to develop various IOT systems which could be smart socket can be controlled remotely and tracking the electricity consumption to...
Thesis abstract With the continuous expansion of the Big Data universe, researchers have been relentlessly searching for ways to improve the efficiency of big data services, including data analytics and data infrastructures. In the...
This thesis describes two algorithms for face detection that rely on a generic feature representation called spectral histogram representation. The sufficiency and generalization of this representation is demonstrated through a...
Fuzzy relational calculi based on BK products of relations have representational and computational means for handling both concrete numerical representations of relations and symbolic manipulation of relations. BK calculus of relations...
A functional relation between two chemical species puts observational constraints on attempts to model the atmosphere. For example, adequate representation of these relations is important when modeling the depletion of stratospheric...
Diffusion Monte Carlo is the most popular Quantum Monte Carlo method used for obtaining accurate results. Unlike with simpler Monte Carlo techniques, load imbalance can be a significant factor affecting its performance on massively...
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