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Doctoral Dissertations

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Sequence Design Via Semidefinite Programming Relaxation And Randomized Projection, Dian Mo Jan 2019

Sequence Design Via Semidefinite Programming Relaxation And Randomized Projection, Dian Mo

Doctoral Dissertations

Wideband is a booming technology in the field of wireless communications. The receivers in wideband communication systems are expected to cover a very wide spectrum and adaptively extract the parts of interest. The literature has focused on mixing the input spectrum to baseband using a pseudorandom sequence modulation and recovering the received signals from linearly independent measurements by parallel branches to mitigate the pressures from required extreme high sampling frequency. However, a pseudorandom sequence provides no rejection for the strong interferers received together with weak signals from distant sources. The interferers cause significant distortion due to the nonlinearity of the ...


Sparsity In Machine Learning: An Information Selecting Perspective, Siwei Feng Jan 2019

Sparsity In Machine Learning: An Information Selecting Perspective, Siwei Feng

Doctoral Dissertations

Today we are living in a world awash with data. Large volumes of data are acquired, analyzed and applied to tasks through machine learning algorithms in nearly every area of science, business, and industry. For example, medical scientists analyze the gene expression data from a single specimen to learn the underlying causes of disease (e.g. cancer) and choose the best treatment; retailers can know more about customers' shopping habits from retail data to adjust their business strategies to better appeal to customers; suppliers can enhance supply chain success through supply chain systems built on knowledge sharing. However, it is ...


Skybridge-3d-Cmos: A Fine-Grained Vertical 3d-Cmos Technology Paving New Direction For 3d Ic, Jiajun Shi Jan 2018

Skybridge-3d-Cmos: A Fine-Grained Vertical 3d-Cmos Technology Paving New Direction For 3d Ic, Jiajun Shi

Doctoral Dissertations

2D CMOS integrated circuit (IC) technology scaling faces severe challenges that result from device scaling limitations, interconnect bottleneck that dominates power and performance, etc. 3D ICs with die-die and layer-layer stacking using Through Silicon Vias (TSVs) and Monolithic Inter-layer Vias (MIVs) have been explored in recent years to generate circuits with considerable interconnect saving for continuing technology scaling. However, these 3D IC technologies still rely on conventional 2D CMOS’s device, circuit and interconnect mindset showing only incremental benefits while adding new challenges reliability issues, robustness of power delivery network design and short-channel effects as technology node scaling.

Skybridge-3D-CMOS (S3DC ...


Machine Learning Techniques Implementation In Power Optimization, Data Processing, And Bio-Medical Applications, Khalid Khairullah Mezied Al-Jabery Jan 2018

Machine Learning Techniques Implementation In Power Optimization, Data Processing, And Bio-Medical Applications, Khalid Khairullah Mezied Al-Jabery

Doctoral Dissertations

"The rapid progress and development in machine-learning algorithms becomes a key factor in determining the future of humanity. These algorithms and techniques were utilized to solve a wide spectrum of problems extended from data mining and knowledge discovery to unsupervised learning and optimization. This dissertation consists of two study areas. The first area investigates the use of reinforcement learning and adaptive critic design algorithms in the field of power grid control. The second area in this dissertation, consisting of three papers, focuses on developing and applying clustering algorithms on biomedical data. The first paper presents a novel modelling approach for ...


Adaptive Dynamic Programming With Eligibility Traces And Complexity Reduction Of High-Dimensional Systems, Seaar Jawad Kadhim Al-Dabooni Jan 2018

Adaptive Dynamic Programming With Eligibility Traces And Complexity Reduction Of High-Dimensional Systems, Seaar Jawad Kadhim Al-Dabooni

Doctoral Dissertations

"This dissertation investigates the application of a variety of computational intelligence techniques, particularly clustering and adaptive dynamic programming (ADP) designs especially heuristic dynamic programming (HDP) and dual heuristic programming (DHP). Moreover, a one-step temporal-difference (TD(0)) and n-step TD (TD(λ)) with their gradients are utilized as learning algorithms to train and online-adapt the families of ADP. The dissertation is organized into seven papers. The first paper demonstrates the robustness of model order reduction (MOR) for simulating complex dynamical systems. Agglomerative hierarchical clustering based on performance evaluation is introduced for MOR. This method computes the reduced order denominator of ...


Deep Learning And Localized Features Fusion For Medical Image Classification, Haidar A. Almubarak Jan 2018

Deep Learning And Localized Features Fusion For Medical Image Classification, Haidar A. Almubarak

Doctoral Dissertations

"Local image features play an important role in many classification tasks as translation and rotation do not severely deteriorate the classification process. They have been commonly used for medical image analysis. In medical applications, it is important to get accurate diagnosis/aid results in the fastest time possible.

This dissertation tries to tackle these problems, first by developing a localized feature-based classification system for medical images and using these features and to give a classification for the entire image, and second, by improving the computational complexity of feature analysis to make it viable as a diagnostic aid system in practical ...


Analog Signal Processing Solutions And Design Of Memristor-Cmos Analog Co-Processor For Acceleration Of High-Performance Computing Applications, Nihar Athreyas Jan 2018

Analog Signal Processing Solutions And Design Of Memristor-Cmos Analog Co-Processor For Acceleration Of High-Performance Computing Applications, Nihar Athreyas

Doctoral Dissertations

Emerging applications in the field of machine vision, deep learning and scientific simulation require high computational speed and are run on platforms that are size, weight and power constrained. With the transistor scaling coming to an end, existing digital hardware architectures will not be able to meet these ever-increasing demands. Analog computation with its rich set of primitives and inherent parallel architecture can be faster, more efficient and compact for some of these applications. The major contribution of this work is to show that analog processing can be a viable solution to this problem. This is demonstrated in the three ...


Hybrid Black-Box Solar Analytics And Their Privacy Implications, Dong Chen Jan 2018

Hybrid Black-Box Solar Analytics And Their Privacy Implications, Dong Chen

Doctoral Dissertations

The aggregate solar capacity in the U.S. is rising rapidly due to continuing decreases in the cost of solar modules. For example, the installed cost per Watt (W) for residential photovoltaics (PVs) decreased by 6X from 2009 to 2018 (from $8/W to $1.2/W), resulting in the installed aggregate solar capacity increasing 128X from 2009 to 2018 (from 435 megawatts to 55.9 gigawatts). This increasing solar capacity is imposing operational challenges on utilities in balancing electricity's real-time supply and demand, as solar generation is more stochastic and less predictable than aggregate demand.

To address this ...


Leveraging Eye Structure And Motion To Build A Low-Power Wearable Gaze Tracking System, Addison Mayberry Jan 2018

Leveraging Eye Structure And Motion To Build A Low-Power Wearable Gaze Tracking System, Addison Mayberry

Doctoral Dissertations

Clinical studies have shown that features of a person's eyes can function as an effective proxy for cognitive state and neurological function. Technological advances in recent decades have allowed us to deepen this understanding and discover that the actions of the eyes are in fact very tightly coupled to the operation of the brain. Researchers have used camera-based eye monitoring technology to exploit this connection and analyze mental state across across many different metrics of interest. These range from simple things like attention and scene processing, to impairments such as a fatigue or substance use, and even significant mental ...


Transiency-Driven Resource Management For Cloud Computing Platforms, Prateek Sharma Jan 2018

Transiency-Driven Resource Management For Cloud Computing Platforms, Prateek Sharma

Doctoral Dissertations

Modern distributed server applications are hosted on enterprise or cloud data centers that provide computing, storage, and networking capabilities to these applications. These applications are built using the implicit assumption that the underlying servers will be stable and normally available, barring for occasional faults. In many emerging scenarios, however, data centers and clouds only provide transient, rather than continuous, availability of their servers. Transiency in modern distributed systems arises in many contexts, such as green data centers powered using renewable intermittent sources, and cloud platforms that provide lower-cost transient servers which can be unilaterally revoked by the cloud operator.

Transient ...


An Architecture Evaluation And Implementation Of A Soft Gpgpu For Fpgas, Kevin Andryc Jan 2018

An Architecture Evaluation And Implementation Of A Soft Gpgpu For Fpgas, Kevin Andryc

Doctoral Dissertations

Embedded and mobile systems must be able to execute a variety of different types of code, often with minimal available hardware. Many embedded systems now come with a simple processor and an FPGA, but not more energy-hungry components, such as a GPGPU. In this dissertation we present FlexGrip, a soft architecture which allows for the execution of GPGPU code on an FPGA without the need to recompile the design. The architecture is optimized for FPGA implementation to effectively support the conditional and thread-based execution characteristics of GPGPU execution without FPGA design recompilation. This architecture supports direct CUDA compilation to a ...


Power Laws In Complex Graphs: Parsimonious Generative Models, Similarity Testing Algorithms, And The Origins, Shan Lu Jan 2018

Power Laws In Complex Graphs: Parsimonious Generative Models, Similarity Testing Algorithms, And The Origins, Shan Lu

Doctoral Dissertations

This dissertation mainly discussed topics related to power law graphs, including graph similarity testing algorithms and power law generative models.

For graph similarity testing, we proposed a method based on the mathematical theory of diffusion over manifolds using random walks over graphs. We show that our method not only distinguishes between graphs with different degree distributions, but also graphs with the same degree distributions. We compare the undirected power law graphs generated by Barabasi-Albert model and directed power law graphs generated by Krapivsky's model to the random graphs generated by Erdos-Renyi model. We also compare power law graphs generated ...


Integration Of Robotic Perception, Action, And Memory, Li Yang Ku Jan 2018

Integration Of Robotic Perception, Action, And Memory, Li Yang Ku

Doctoral Dissertations

In the book "On Intelligence", Hawkins states that intelligence should be measured by the capacity to memorize and predict patterns. I further suggest that the ability to predict action consequences based on perception and memory is essential for robots to demonstrate intelligent behaviors in unstructured environments. However, traditional approaches generally represent action and perception separately---as computer vision modules that recognize objects and as planners that execute actions based on labels and poses. I propose here a more integrated approach where action and perception are combined in a memory model, in which a sequence of actions can be planned based on ...


Dynamic In Vivo Skeletal Feature Tracking Via Fluoroscopy Using A Human Gait Model, William Patrick Anderson Dec 2017

Dynamic In Vivo Skeletal Feature Tracking Via Fluoroscopy Using A Human Gait Model, William Patrick Anderson

Doctoral Dissertations

The Tracking Fluoroscope System II, a mobile robotic fluoroscopy platform, developed and built at the University of Tennessee, Knoxville, presently employs a pattern matching algorithm in order to identify and track a marker placed upon a subject’s knee joint of interest. The purpose of this research is to generate a new tracking algorithm based around the human gait cycle for prediction and improving the overall accuracy of joint tracking.

This research centers around processing the acquired x-ray images of the desired knee joint obtained during standard clinical operation in order to identify and track directly through the acquired image ...


Computational Imaging Approach To Recovery Of Target Coordinates Using Orbital Sensor Data, Michael D. Vaughan Aug 2017

Computational Imaging Approach To Recovery Of Target Coordinates Using Orbital Sensor Data, Michael D. Vaughan

Doctoral Dissertations

This dissertation addresses the components necessary for simulation of an image-based recovery of the position of a target using orbital image sensors. Each component is considered in detail, focusing on the effect that design choices and system parameters have on the accuracy of the position estimate. Changes in sensor resolution, varying amounts of blur, differences in image noise level, selection of algorithms used for each component, and lag introduced by excessive processing time all contribute to the accuracy of the result regarding recovery of target coordinates using orbital sensor data.

Using physical targets and sensors in this scenario would be ...


Learning Multimodal Structures In Computer Vision, Ali Taalimi Aug 2017

Learning Multimodal Structures In Computer Vision, Ali Taalimi

Doctoral Dissertations

A phenomenon or event can be received from various kinds of detectors or under different conditions. Each such acquisition framework is a modality of the phenomenon. Due to the relation between the modalities of multimodal phenomena, a single modality cannot fully describe the event of interest. Since several modalities report on the same event introduces new challenges comparing to the case of exploiting each modality separately.

We are interested in designing new algorithmic tools to apply sensor fusion techniques in the particular signal representation of sparse coding which is a favorite methodology in signal processing, machine learning and statistics to ...


Modeling The Consumer Acceptance Of Retail Service Robots, So Young Song Aug 2017

Modeling The Consumer Acceptance Of Retail Service Robots, So Young Song

Doctoral Dissertations

This study uses the Computers Are Social Actors (CASA) and domestication theories as the underlying framework of an acceptance model of retail service robots (RSRs). The model illustrates the relationships among facilitators, attitudes toward Human-Robot Interaction (HRI), anxiety toward robots, anticipated service quality, and the acceptance of RSRs. Specifically, the researcher investigates the extent to which the facilitators of usefulness, social capability, the appearance of RSRs, and the attitudes toward HRI affect acceptance and increase the anticipation of service quality. The researcher also tests the inhibiting role of pre-existing anxiety toward robots on the relationship between these facilitators and attitudes ...


A Probabilistic Software Framework For Scalable Data Storage And Integrity Check, Sisi Xiong Aug 2017

A Probabilistic Software Framework For Scalable Data Storage And Integrity Check, Sisi Xiong

Doctoral Dissertations

Data has overwhelmed the digital world in terms of volume, variety and velocity. Data- intensive applications are facing unprecedented challenges. On the other hand, computation resources, such as memory, suffer from shortage comparing to data scale. However, in certain applications, it is a must to process large amount of data in a time efficient manner. Probabilistic approaches are compromises between these three perspectives: large amount of data, limited computation resources and high time efficiency, in the sense that those approaches cannot guarantee 100% correctness, their error rates, however, are predictable and adjustable depending on available computation resources and time constraints ...


Wide-Area Measurement-Driven Approaches For Power System Modeling And Analytics, Hesen Liu Aug 2017

Wide-Area Measurement-Driven Approaches For Power System Modeling And Analytics, Hesen Liu

Doctoral Dissertations

This dissertation presents wide-area measurement-driven approaches for power system modeling and analytics. Accurate power system dynamic models are the very basis of power system analysis, control, and operation. Meanwhile, phasor measurement data provide first-hand knowledge of power system dynamic behaviors. The idea of building out innovative applications with synchrophasor data is promising.

Taking advantage of the real-time wide-area measurements, one of phasor measurements’ novel applications is to develop a synchrophasor-based auto-regressive with exogenous inputs (ARX) model that can be updated online to estimate or predict system dynamic responses.

Furthermore, since auto-regressive models are in a big family, the ARX model ...


Adaft: A Resource-Efficient Framework For Adaptive Fault-Tolerance In Cyber-Physical Systems, Ye Xu Jan 2017

Adaft: A Resource-Efficient Framework For Adaptive Fault-Tolerance In Cyber-Physical Systems, Ye Xu

Doctoral Dissertations

Cyber-physical systems frequently have to use massive redundancy to meet application requirements for high reliability. While such redundancy is required, it can be activated adaptively, based on the current state of the controlled plant. Most of the time the physical plant is in a state that allows for a lower level of fault-tolerance. Avoiding the continuous deployment of massive fault-tolerance will greatly reduce the workload of CPSs. In this dissertation, we demonstrate a software simulation framework (AdaFT) that can automatically generate the sub-spaces within which our adaptive fault-tolerance can be applied. We also show the theoretical benefits of AdaFT, and ...


Design And Theoretical Analysis Of Advanced Power Based Positioning In Rf System, Lei Wang Jan 2017

Design And Theoretical Analysis Of Advanced Power Based Positioning In Rf System, Lei Wang

Doctoral Dissertations

"Accurate locating and tracking of people and resources has become a fundamental requirement for many applications. The global navigation satellite systems (GNSS) is widely used. But its accuracy suffers from signal obstruction by buildings, multipath fading, and disruption due to jamming and spoof. Hence, it is required to supplement GPS with inertial sensors and indoor localization schemes that make use of WiFi APs or beacon nodes. In the GPS-challenging or fault scenario, radio-frequency (RF) infrastructure based localization schemes can be a fallback solution for robust navigation. For the indoor/outdoor transition scenario, we propose hypothesis test based fusion method to ...


Survivability Modeling For Cyber-Physical Systems Subject To Data Corruption, Mark James Woodard Jan 2017

Survivability Modeling For Cyber-Physical Systems Subject To Data Corruption, Mark James Woodard

Doctoral Dissertations

"Cyber-physical critical infrastructures are created when traditional physical infrastructure is supplemented with advanced monitoring, control, computing, and communication capability. More intelligent decision support and improved efficacy, dependability, and security are expected. Quantitative models and evaluation methods are required for determining the extent to which a cyber-physical infrastructure improves on its physical predecessors. It is essential that these models reflect both cyber and physical aspects of operation and failure. In this dissertation, we propose quantitative models for dependability attributes, in particular, survivability, of cyber-physical systems. Any malfunction or security breach, whether cyber or physical, that causes the system operation to depart ...


Quantitative Dependability And Interdependency Models For Large-Scale Cyber-Physical Systems, Koosha Marashi Jan 2017

Quantitative Dependability And Interdependency Models For Large-Scale Cyber-Physical Systems, Koosha Marashi

Doctoral Dissertations

"Cyber-physical systems link cyber infrastructure with physical processes through an integrated network of physical components, sensors, actuators, and computers that are interconnected by communication links. Modern critical infrastructures such as smart grids, intelligent water distribution networks, and intelligent transportation systems are prominent examples of cyber-physical systems. Developed countries are entirely reliant on these critical infrastructures, hence the need for rigorous assessment of the trustworthiness of these systems. The objective of this research is quantitative modeling of dependability attributes -- including reliability and survivability -- of cyber-physical systems, with domain-specific case studies on smart grids and intelligent water distribution networks. To this end ...


Belief-Space Planning For Resourceful Manipulation And Mobility, Dirk Ruiken Jan 2017

Belief-Space Planning For Resourceful Manipulation And Mobility, Dirk Ruiken

Doctoral Dissertations

Robots are increasingly expected to work in partially observable and unstructured environments. They need to select actions that exploit perceptual and motor resourcefulness to manage uncertainty based on the demands of the task and environment. The research in this dissertation makes two primary contributions. First, it develops a new concept in resourceful robot platforms called the UMass uBot and introduces the sixth and seventh in the uBot series. uBot-6 introduces multiple postural configurations that enable different modes of mobility and manipulation to meet the needs of a wide variety of tasks and environmental constraints. uBot-7 extends this with the use ...


Image Processing And Understanding Based On Graph Similarity Testing: Algorithm Design And Software Development, Jieqi Kang Jan 2017

Image Processing And Understanding Based On Graph Similarity Testing: Algorithm Design And Software Development, Jieqi Kang

Doctoral Dissertations

Image processing and understanding is a key task in the human visual system. Among all related topics, content based image retrieval and classification is the most typical and important problem. Successful image retrieval/classification models require an effective fundamental step of image representation and feature extraction. While traditional methods are not capable of capturing all structural information on the image, using graph to represent the image is not only biologically plausible but also has certain advantages.

Graphs have been widely used in image related applications. Traditional graph-based image analysis models include pixel-based graph-cut techniques for image segmentation, low-level and high-level ...


Inference In Networking Systems With Designed Measurements, Chang Liu Jan 2017

Inference In Networking Systems With Designed Measurements, Chang Liu

Doctoral Dissertations

Networking systems consist of network infrastructures and the end-hosts have been essential in supporting our daily communication, delivering huge amount of content and large number of services, and providing large scale distributed computing. To monitor and optimize the performance of such networking systems, or to provide flexible functionalities for the applications running on top of them, it is important to know the internal metrics of the networking systems such as link loss rates or path delays. The internal metrics are often not directly available due to the scale and complexity of the networking systems. This motivates the techniques of inference ...


Formal Analysis Of Arithmetic Circuits Using Computer Algebra - Verification, Abstraction And Reverse Engineering, Cunxi Yu Jan 2017

Formal Analysis Of Arithmetic Circuits Using Computer Algebra - Verification, Abstraction And Reverse Engineering, Cunxi Yu

Doctoral Dissertations

Despite a considerable progress in verification and abstraction of random and control logic, advances in formal verification of arithmetic designs have been lagging. This can be attributed mostly to the difficulty in an efficient modeling of arithmetic circuits and datapaths without resorting to computationally expensive Boolean methods, such as Binary Decision Diagrams (BDDs) and Boolean Satisfiability (SAT), that require “bit blasting”, i.e., flattening the design to a bit-level netlist. Approaches that rely on computer algebra and Satisfiability Modulo Theories (SMT) methods are either too abstract to handle the bit-level nature of arithmetic designs or require solving computationally expensive decision ...


Topology Design And Delay Control For Communication Networks In Smart Grid, Xiaodong Wang Aug 2016

Topology Design And Delay Control For Communication Networks In Smart Grid, Xiaodong Wang

Doctoral Dissertations

Stability is a critical concern in the design and maintenance of power systems. Different approaches have been proposed for the analysis of power grid stability in various scenarios depending on small or large perturbations and the speed of the phenomenon of interest. In this work, we consider the power grid as a group of flocking birds, as synchronization is the key issue in both contexts. The framework of partial difference equation (PdE) is used to analyze the system stability, when designing the communication network of the power grid network for conveying measurements between different power stations. Both the cases where ...


Face Centered Image Analysis Using Saliency And Deep Learning Based Techniques, Rui Guo Aug 2016

Face Centered Image Analysis Using Saliency And Deep Learning Based Techniques, Rui Guo

Doctoral Dissertations

Image analysis starts with the purpose of configuring vision machines that can perceive like human to intelligently infer general principles and sense the surrounding situations from imagery. This dissertation studies the face centered image analysis as the core problem in high level computer vision research and addresses the problem by tackling three challenging subjects: Are there anything interesting in the image? If there is, what is/are that/they? If there is a person presenting, who is he/she? What kind of expression he/she is performing? Can we know his/her age? Answering these problems results in the saliency-based ...


Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan Aug 2016

Achieving High Reliability And Efficiency In Maintaining Large-Scale Storage Systems Through Optimal Resource Provisioning And Data Placement, Lipeng Wan

Doctoral Dissertations

With the explosive increase in the amount of data being generated by various applications, large-scale distributed and parallel storage systems have become common data storage solutions and been widely deployed and utilized in both industry and academia. While these high performance storage systems significantly accelerate the data storage and retrieval, they also bring some critical issues in system maintenance and management. In this dissertation, I propose three methodologies to address three of these critical issues.

First, I develop an optimal resource management and spare provisioning model to minimize the impact brought by component failures and ensure a highly operational experience ...