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Doctoral Dissertations

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Full-Text Articles in Computer Engineering

Null Convention Logic Applications Of Asynchronous Design In Nanotechnology And Cryptographic Security, Jun Wu Jan 2012

Null Convention Logic Applications Of Asynchronous Design In Nanotechnology And Cryptographic Security, Jun Wu

Doctoral Dissertations

"This dissertation presents two Null Convention Logic (NCL) applications of asynchronous logic circuit design in nanotechnology and cryptographic security. The first application is the Asynchronous Nanowire Reconfigurable Crossbar Architecture (ANRCA); the second one is an asynchronous S-Box design for cryptographic system against Side-Channel Attacks (SCA). The following are the contributions of the first application: 1) Proposed a diode- and resistor-based ANRCA (DR-ANRCA). Three configurable logic block (CLB) structures were designed to efficiently reconfigure a given DR-PGMB as one of the 27 arbitrary NCL threshold gates. A hierarchical architecture was also proposed to implement the higher level logic that requires a ...


Collaborative Solutions To Visual Sensor Networks, Mahmut Karakaya Aug 2011

Collaborative Solutions To Visual Sensor Networks, Mahmut Karakaya

Doctoral Dissertations

Visual sensor networks (VSNs) merge computer vision, image processing and wireless sensor network disciplines to solve problems in multi-camera applications in large surveillance areas. Although potentially powerful, VSNs also present unique challenges that could hinder their practical deployment because of the unique camera features including the extremely higher data rate, the directional sensing characteristics, and the existence of visual occlusions.

In this dissertation, we first present a collaborative approach for target localization in VSNs. Traditionally; the problem is solved by localizing targets at the intersections of the back-projected 2D cones of each target. However, the existence of visual occlusions among ...


Performance Controlled Power Optimization For Virtualized Internet Datacenters, Yefu Wang Aug 2011

Performance Controlled Power Optimization For Virtualized Internet Datacenters, Yefu Wang

Doctoral Dissertations

Modern data centers must provide performance assurance for complex system software such as web applications. In addition, the power consumption of data centers needs to be minimized to reduce operating costs and avoid system overheating. In recent years, more and more data centers start to adopt server virtualization strategies for resource sharing to reduce hardware and operating costs by consolidating applications previously running on multiple physical servers onto a single physical server. In this dissertation, several power efficient algorithms are proposed to effectively reduce server power consumption while achieving the required application-level performance for virtualized servers.

First, at the server ...


Feature-Based Image Comparison And Its Application In Wireless Visual Sensor Networks, Yang Bai May 2011

Feature-Based Image Comparison And Its Application In Wireless Visual Sensor Networks, Yang Bai

Doctoral Dissertations

This dissertation studies the feature-based image comparison method and its application in Wireless Visual Sensor Networks.

Wireless Visual Sensor Networks (WVSNs), formed by a large number of low-cost, small-size visual sensor nodes, represent a new trend in surveillance and monitoring practices. Although each single sensor has very limited capability in sensing, processing and transmission, by working together they can achieve various high level tasks. Sensor collaboration is essential to WVSNs and normally performed among sensors having similar measurements, which are called neighbor sensors. The directional sensing characteristics of imagers and the presence of visual occlusion present unique challenges to neighborhood ...


Agent-Based Analysis And Mitigation Of Failure For Cyber-Physical Systems, Jing Lin Jan 2011

Agent-Based Analysis And Mitigation Of Failure For Cyber-Physical Systems, Jing Lin

Doctoral Dissertations

"Techniques exist for assessment, modeling, and simulation of physical and cyber infrastructures, respectively; but such isolated analysis is incapable of fully capturing the interdependencies that occur when they intertwine to create a cyber-physical system (CPS). The first contribution of this doctoral research includes qualitative representation of the operation of a CPS in a single multi-agent model. Dependable operation of a CPS is contingent upon correct interpretation of data describing the state of the system. To this end, we propose agent-based semantic interpretation services that extract useful information from raw sensor data. We utilize the summary schemas model to reconcile differences ...


Data Mining Based Learning Algorithms For Semi-Supervised Object Identification And Tracking, Michael P. Dessauer Jan 2011

Data Mining Based Learning Algorithms For Semi-Supervised Object Identification And Tracking, Michael P. Dessauer

Doctoral Dissertations

Sensor exploitation (SE) is the crucial step in surveillance applications such as airport security and search and rescue operations. It allows localization and identification of movement in urban settings and can significantly boost knowledge gathering, interpretation and action. Data mining techniques offer the promise of precise and accurate knowledge acquisition techniques in high-dimensional data domains (and diminishing the “curse of dimensionality” prevalent in such datasets), coupled by algorithmic design in feature extraction, discriminative ranking, feature fusion and supervised learning (classification). Consequently, data mining techniques and algorithms can be used to refine and process captured data and to detect, recognize, classify ...


Sub Pixel Analysis And Processing Of Sensor Data For Mobile Target Intelligence Information And Verification, Theresa Allen Williams Jan 2011

Sub Pixel Analysis And Processing Of Sensor Data For Mobile Target Intelligence Information And Verification, Theresa Allen Williams

Doctoral Dissertations

This dissertation introduces a novel process to study and analyze sensor data in order to obtain information pertaining to mobile targets at the sub-pixel level. The process design is modular in nature and utilizes a set of algorithmic tools for change detection, target extraction and analysis, super-pixel processing and target refinement. The scope of this investigation is confined to a staring sensor that records data of sub-pixel vehicles traveling horizontally across the ground. Statistical models of the targets and background are developed with noise and jitter effects. Threshold Change Detection, Duration Change Detection and Fast Adaptive Power Iteration (FAPI) Detection ...


Nonlinear Control Strategy For A Cost Effective Myoelectric Prosthetic Hand, Cristian Federico Pasluosta Oct 2010

Nonlinear Control Strategy For A Cost Effective Myoelectric Prosthetic Hand, Cristian Federico Pasluosta

Doctoral Dissertations

The loss of a limb tremendously impacts the life of the affected individual. In the past decades, researchers have been developing artificial limbs that may return some of the missing functions and cosmetics. However, the development of dexterous mechanisms capable of mimicking the function of the human hand is a complex venture. Even though myoelectric prostheses have advanced, several issues remain to be solved before an artificial limb may be comparable to its human counterpart. Moreover, the high cost of advanced limbs prevents their widespread use among the low-income population.

This dissertation presents a strategy for the low-level of control ...


Adaptive Performance And Power Management In Distributed Computing Systems, Ming Chen Aug 2010

Adaptive Performance And Power Management In Distributed Computing Systems, Ming Chen

Doctoral Dissertations

The complexity of distributed computing systems has raised two unprecedented challenges for system management. First, various customers need to be assured by meeting their required service-level agreements such as response time and throughput. Second, system power consumption must be controlled in order to avoid system failures caused by power capacity overload or system overheating due to increasingly high server density. However, most existing work, unfortunately, either relies on open-loop estimations based on off-line profiled system models, or evolves in a more ad hoc fashion, which requires exhaustive iterations of tuning and testing, or oversimplifies the problem by ignoring the coupling ...


Anomaly Detection In Unknown Environments Using Wireless Sensor Networks, Yuanyuan Li May 2010

Anomaly Detection In Unknown Environments Using Wireless Sensor Networks, Yuanyuan Li

Doctoral Dissertations

This dissertation addresses the problem of distributed anomaly detection in Wireless Sensor Networks (WSN). A challenge of designing such systems is that the sensor nodes are battery powered, often have different capabilities and generally operate in dynamic environments. Programming such sensor nodes at a large scale can be a tedious job if the system is not carefully designed. Data modeling in distributed systems is important for determining the normal operation mode of the system. Being able to model the expected sensor signatures for typical operations greatly simplifies the human designer’s job by enabling the system to autonomously characterize the ...


A Novel Technique For Ctis Image-Reconstruction, Mitchel Dewayne Horton May 2010

A Novel Technique For Ctis Image-Reconstruction, Mitchel Dewayne Horton

Doctoral Dissertations

Computed tomography imaging spectrometer (CTIS) technology is introduced and its use is discussed. An iterative method is presented for CTIS image-reconstruction in the presence of both photon noise in the image and post-detection Gaussian system noise. The new algorithm assumes the transfer matrix of the system has a particular structure. Error analysis, performance evaluation, and parallelization of the algorithm is done. Complexity analysis is performed for the proof of concept code developed. Future work is discussed relating to potential improvements to the algorithm.

An intuitive explanation for the success of the new algorithm is that it reformulates the image reconstruction ...


Adaptive Resource Allocation For Cognitive Wireless Ad Hoc Networks, Behdis Eslamnour Jan 2010

Adaptive Resource Allocation For Cognitive Wireless Ad Hoc Networks, Behdis Eslamnour

Doctoral Dissertations

"Widespread use of resource constrained wireless ad hoc networks requires careful management of the network resources in order to maximize the utilization. In cognitive wireless networks, resources such as spectrum, energy, communication links/paths, time, space, modulation scheme, have to be managed to maintain quality of service (QoS). Therefore in the first paper, a distributed dynamic channel allocation scheme is proposed for multi-channel wireless ad hoc networks with single-radio nodes. The proposed learning scheme adapts the probabilities of selecting each channel as a function of the error in the performance index at each step.

Due to frequent changes in topology ...


Accelerating Quantum Monte Carlo Simulations With Emerging Architectures, Akila Gothandaraman Aug 2009

Accelerating Quantum Monte Carlo Simulations With Emerging Architectures, Akila Gothandaraman

Doctoral Dissertations

Scientific computing applications demand ever-increasing performance while traditional microprocessor architectures face limits. Recent technological advances have led to a number of emerging computing platforms that provide one or more of the following over their predecessors: increased energy efficiency, programmability/flexibility, different granularities of parallelism, and higher numerical precision support. This dissertation explores emerging platforms such as reconfigurable computing using fieldprogrammable gate arrays (FPGAs), and graphics processing units (GPUs) for quantum Monte Carlo (QMC), a simulation method widely used in physics and physical chemistry. This dissertation makes the following significant contributions to computational science. First, we develop an open-source userfriendly hardware-accelerated ...


Meta-Learning Computational Intelligence Architectures, Ryan J. Meuth Jan 2009

Meta-Learning Computational Intelligence Architectures, Ryan J. Meuth

Doctoral Dissertations

"In computational intelligence, the term 'memetic algorithm' has come to be associated with the algorithmic pairing of a global search method with a local search method. In a sociological context, a 'meme' has been loosely defined as a unit of cultural information, the social analog of genes for individuals. Both of these definitions are inadequate, as 'memetic algorithm' is too specific, and ultimately a misnomer, as much as a 'meme' is defined too generally to be of scientific use. In this dissertation the notion of memes and meta-learning is extended from a computational viewpoint and the purpose, definitions, design guidelines ...


Safdetection:Sensor Analysis Based Fault Detection In Tightly-Coupledmulti-Robot Team Tasks, Xingyan Li Dec 2008

Safdetection:Sensor Analysis Based Fault Detection In Tightly-Coupledmulti-Robot Team Tasks, Xingyan Li

Doctoral Dissertations

This dissertation addresses the problem of detecting faults based on sensor analysis for tightly-coupled multi-robot team tasks. The approach I developed is called SAFDetection, which stands for Sensor Analysis based Fault Detection, pronounced “Safe Detection”. When dealing with robot teams, it is challenging to detect all types of faults because of the complicated environment they operate in and the large spectrum of components used in the robot system. The SAFDetection approach provides a novel methodology for detecting robot faults in situations when motion models and models of multi-robot dynamic interactions are unavailable. The fundamental idea of SAFDetection is to build ...


Integration Of Spatial And Spectral Information For Hyperspectral Image Classification, Zheng Du Aug 2008

Integration Of Spatial And Spectral Information For Hyperspectral Image Classification, Zheng Du

Doctoral Dissertations

Hyperspectral imaging has become a powerful tool in biomedical and agriculture fields in the recent years and the interest amongst researchers has increased immensely. Hyperspectral imaging combines conventional imaging and spectroscopy to acquire both spatial and spectral information from an object. Consequently, a hyperspectral image data contains not only spectral information of objects, but also the spatial arrangement of objects. Information captured in neighboring locations may provide useful supplementary knowledge for analysis. Therefore, this dissertation investigates the integration of information from both the spectral and spatial domains to enhance hyperspectral image classification performance.

The major impediment to the combined spatial ...


Computationally Efficient Mixed Pixel Decomposition Using Constrained Optimizations, Lidan Miao Dec 2007

Computationally Efficient Mixed Pixel Decomposition Using Constrained Optimizations, Lidan Miao

Doctoral Dissertations

Sensors with spatial resolution larger than targets yield mixed pixel, i.e., pixel whose measurement is a composite of different sources (endmembers). The analysis of mixed pixels demands subpixel methods to perform source separation and quantification, which is a problem of blind source separation (BSS). Although various algorithms have been proposed, several important issues remain unresolved. First, assuming the endmembers are known, the abundance estimation is commonly performed by employing a least squares criterion, which however makes the estimation sensitive to noise and outliers, and the endmembers with very similar signatures are difficult to differentiate. In addition, the nonnegative con- ...


Fabric-On-A-Chip: Toward Consolidating Packet Switching Functions On Silicon, William B. Matthews Dec 2007

Fabric-On-A-Chip: Toward Consolidating Packet Switching Functions On Silicon, William B. Matthews

Doctoral Dissertations

The switching capacity of an Internet router is often dictated by the memory bandwidth required to bu¤er arriving packets. With the demand for greater capacity and improved service provisioning, inherent memory bandwidth limitations are encountered rendering input queued (IQ) switches and combined input and output queued (CIOQ) architectures more practical. Output-queued (OQ) switches, on the other hand, offer several highly desirable performance characteristics, including minimal average packet delay, controllable Quality of Service (QoS) provisioning and work-conservation under any admissible traffic conditions. However, the memory bandwidth requirements of such systems is O(NR), where N denotes the number of ports ...


Hardware-Efficient Scalable Reinforcement Learning Systems, Zhenzhen Liu Dec 2007

Hardware-Efficient Scalable Reinforcement Learning Systems, Zhenzhen Liu

Doctoral Dissertations

Reinforcement Learning (RL) is a machine learning discipline in which an agent learns by interacting with its environment. In this paradigm, the agent is required to perceive its state and take actions accordingly. Upon taking each action, a numerical reward is provided by the environment. The goal of the agent is thus to maximize the aggregate rewards it receives over time. Over the past two decades, a large variety of algorithms have been proposed to select actions in order to explore the environment and gradually construct an e¤ective strategy that maximizes the rewards. These RL techniques have been successfully ...


Automated Genome-Wide Protein Domain Exploration, Bhanu Prasad Rekepalli Dec 2007

Automated Genome-Wide Protein Domain Exploration, Bhanu Prasad Rekepalli

Doctoral Dissertations

Exploiting the exponentially growing genomics and proteomics data requires high quality, automated analysis. Protein domain modeling is a key area of molecular biology as it unravels the mysteries of evolution, protein structures, and protein functions. A plethora of sequences exist in protein databases with incomplete domain knowledge. Hence this research explores automated bioinformatics tools for faster protein domain analysis. Automated tool chains described in this dissertation generate new protein domain models thus enabling more effective genome-wide protein domain analysis. To validate the new tool chains, the Shewanella oneidensis and Escherichia coli genomes were processed, resulting in a new peptide domain ...


Self-Certified Public Key Cryptographic Methodologies For Resource-Constrained Wireless Sensor Networks, Ortal Arazi Dec 2007

Self-Certified Public Key Cryptographic Methodologies For Resource-Constrained Wireless Sensor Networks, Ortal Arazi

Doctoral Dissertations

As sensor networks become one of the key technologies to realize ubiquitous computing, security remains a growing concern. Although a wealth of key-generation methods have been developed during the past few decades, they cannot be directly applied to sensor network environments. The resource-constrained characteristics of sensor nodes, the ad-hoc nature of their deployment, and the vulnerability of wireless media pose a need for unique solutions.

A fundamental requisite for achieving security is the ability to provide for data con…dential- ity and node authentication. However, the scarce resources of sensor networks have rendered the direct applicability of existing public key ...


Personalized Health Monitoring Using Evolvable Block-Based Neural Networks, Wei Jiang Aug 2007

Personalized Health Monitoring Using Evolvable Block-Based Neural Networks, Wei Jiang

Doctoral Dissertations

This dissertation presents personalized health monitoring using evolvable block-based neural networks. Personalized health monitoring plays an increasingly important role in modern society as the population enjoys longer life. Personalization in health monitoring considers physiological variations brought by temporal, personal or environmental differences, and demands solutions capable to reconfigure and adapt to specific requirements. Block-based neural networks (BbNNs) consist of 2-D arrays of modular basic blocks that can be easily implemented using reconfigurable digital hardware such as field programmable gate arrays (FPGAs) that allow on-line partial reorganization. The modular structure of BbNNs enables easy expansion in size by adding more blocks ...


Energy-Aware And Secure Routing With Trust Levels For Wireless Ad Hoc And Sensor Networks, Eyad Taqieddin Jan 2007

Energy-Aware And Secure Routing With Trust Levels For Wireless Ad Hoc And Sensor Networks, Eyad Taqieddin

Doctoral Dissertations

"This dissertation focuses on the development of routing algorithms for secure and trusted routing in wireless ad hoc and sensor network. The first paper presents the Trust Level Routing (TLR) protocol, an extension of the optimized energy-delay routing (OEDR) protocol, focusing on the integrity, reliability and survivability of the wireless network...The second paper analyzes both OLSR and TLR in terms of survivability and reliability to emphasize the improved performance of the network in terms of lifetime and proper delivery of data...The third paper proposes a statistical reputation model that uses the watchdog mechanism to observe the cooperation of ...


Scheduling Algorithms For Scalable High-Performance Packet Switching Architectures, Xike Li Dec 2006

Scheduling Algorithms For Scalable High-Performance Packet Switching Architectures, Xike Li

Doctoral Dissertations

Packet switching fabrics constitute a fundamental building block of all Internet routers. As a core technology, the switching engine is responsible for enabling multiple input (ingress) ports to be dynamically linked to output (egress) ports, thereby allowing packets to effectively traverse the router. Scheduling algorithms, which play a key role in switching fabrics, determine the dynamic configurations of the input-output matchings. The ever growing need for additional bandwidth and more sophisticated service provisioning in next- generation networks necessitates the introduction of scalable packet scheduling solutions that go beyond legacy schemes.

Switch architectures can be coarsely classified into two categories, in ...


Efficient Image Processing In Resource-Constrained Visual Sensor Networks, Hongtao Du Dec 2006

Efficient Image Processing In Resource-Constrained Visual Sensor Networks, Hongtao Du

Doctoral Dissertations

Visual sensor networks (VSNs) that employ content-rich 2-D images or image sequences as the basic media have been evolving rapidly in recent years. Besides the critical resource constraints that are already inherent in any micro-sensor networks, the development of VSNs also faces challenges from device design, image transmission, and onboard image processing, among which efficient onboard processing is the most difficult to tackle. The focus of this dis- sertation is to develop efficient image processing solutions from three aspects: to improve the time-consuming image processing algorithms using pipelined and parallel computing; to dis- tribute the computation more effectively through novel ...


Accelerating Exact Stochastic Simulation Of Biochemical Systems, James Michael Mccollum Aug 2006

Accelerating Exact Stochastic Simulation Of Biochemical Systems, James Michael Mccollum

Doctoral Dissertations

The ability to accurately and efficiently simulate computer models of biochemical systems is of growing importance to the molecular biology and pharmaceutical research communities. Exact stochastic simulation is a popular approach for simulating such systems because it properly represents genetic noise and it accurately represents systems with small populations of chemical species. Unfortunately, the computational demands of exact stochastic simulation often limit its applicability. To enable next-generation whole-cell and multi-cell stochastic modeling, advanced tools and techniques must be developed to increase simulation efficiency. This work assesses the applicability of a variety of hardware and software acceleration approaches for exact stochastic ...


Topics In Graph Algorithms: Structural Results And Algorithmic Techniques, With Applications, Faisal Nabih Abu Khzam Aug 2003

Topics In Graph Algorithms: Structural Results And Algorithmic Techniques, With Applications, Faisal Nabih Abu Khzam

Doctoral Dissertations

Coping with computational intractability has inspired the development of a variety of algorithmic techniques. The main challenge has usually been the design of polynomial time algorithms for NP-complete problems in a way that guarantees some, often worst-case, satisfactory performance when compared to exact (optimal) solutions. We mainly study some emergent techniques that help to bridge the gap between computational intractability and practicality. We present results that lead to better exact and approximation algorithms and better implementations. The problems considered in this dissertation share much in common structurally, and have applications in several scientific domains, including circuit design, network reliability, and ...


Swarm Engineering, S. Kazadi '90 May 2000

Swarm Engineering, S. Kazadi '90

Doctoral Dissertations

Swarm engineering is the natural evolution of the use of swarm-based techniques in the accomplishment of high level tasks using a number of simple robots. In this approach, one seeks not to generate a class of behaviors designed to accomplish a given global goal, as is the approach typically found in mainstream robotics. Once the class of behaviors has been understood and decided upon, specific behaviors designed to accomplish this goal may be generated that will complete the desired task without any concern about whether or not the final goal will actually be completed. As long as the generated behaviors ...