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Full-Text Articles in Computer Engineering

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 ...


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 ...


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 ...


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 ...


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 ...


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 ...


Intrinsic Functions For Securing Cmos Computation: Variability, Modeling And Noise Sensitivity, Xiaolin Xu Jan 2016

Intrinsic Functions For Securing Cmos Computation: Variability, Modeling And Noise Sensitivity, Xiaolin Xu

Doctoral Dissertations

A basic premise behind modern secure computation is the demand for lightweight cryptographic primitives, like identifier or key generator. From a circuit perspective, the development of cryptographic modules has also been driven by the aggressive scalability of complementary metal-oxide-semiconductor (CMOS) technology. While advancing into nano-meter regime, one significant characteristic of today's CMOS design is the random nature of process variability, which limits the nominal circuit design. With the continuous scaling of CMOS technology, instead of mitigating the physical variability, leveraging such properties becomes a promising way. One of the famous products adhering to this double-edged sword philosophy is the ...


Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich Dec 2015

Neuron Clustering For Mitigating Catastrophic Forgetting In Supervised And Reinforcement Learning, Benjamin Frederick Goodrich

Doctoral Dissertations

Neural networks have had many great successes in recent years, particularly with the advent of deep learning and many novel training techniques. One issue that has affected neural networks and prevented them from performing well in more realistic online environments is that of catastrophic forgetting. Catastrophic forgetting affects supervised learning systems when input samples are temporally correlated or are non-stationary. However, most real-world problems are non-stationary in nature, resulting in prolonged periods of time separating inputs drawn from different regions of the input space.

Reinforcement learning represents a worst-case scenario when it comes to precipitating catastrophic forgetting in neural networks ...


Computational Framework For Small Animal Spect Imaging: Simulation And Reconstruction, Sang Hyeb Lee May 2015

Computational Framework For Small Animal Spect Imaging: Simulation And Reconstruction, Sang Hyeb Lee

Doctoral Dissertations

Small animal Single Photon Emission Computed Tomography (SPECT) has been an invaluable asset in biomedical science since this non-invasive imaging technique allows the longitudinal studies of animal models of human diseases. However, the image degradation caused by non-stationary collimator-detector response and single photon emitting nature of SPECT makes it difficult to provide a quantitative measure of 3D radio-pharmaceutical distribution inside the patient. Moreover, this problem exacerbates when an intra-peritoneal X-ray contrast agent is injected into a mouse for low-energy radiotracers.

In this dissertation, we design and develop a complete computational framework for the entire SPECT scan procedure from the radio-pharmaceutical ...


Learning Parameterized Skills, Bruno Castro Da Silva Feb 2015

Learning Parameterized Skills, Bruno Castro Da Silva

Doctoral Dissertations

One of the defining characteristics of human intelligence is the ability to acquire and refine skills. Skills are behaviors for solving problems that an agent encounters often—sometimes in different contexts and situations—throughout its lifetime. Identifying important problems that recur and retaining their solutions as skills allows agents to more rapidly solve novel problems by adjusting and combining their existing skills.

In this thesis we introduce a general framework for learning reusable parameterized skills. Reusable skills are parameterized procedures that—given a description of a problem to be solved—produce appropriate behaviors or policies. They can be sequentially and ...


Design And Implementation Of An Economy Plane For The Internet, Xinming Chen Jan 2015

Design And Implementation Of An Economy Plane For The Internet, Xinming Chen

Doctoral Dissertations

The Internet has been very successful in supporting many network applications. As the diversity of uses for the Internet has increased, many protocols and services have been developed by the industry and the research community. However, many of them failed to get deployed in the Internet. One challenge of deploying these novel ideas in operational network is that the network providers need to be involved in the process.

Many novel network protocols and services, like multicast and end-to-end QoS, need the support from network providers. However, since network providers are typically driven by business reasons, if they can not get ...


Energy-Efficient Content Delivery Networks, Vimal Mathew Jan 2015

Energy-Efficient Content Delivery Networks, Vimal Mathew

Doctoral Dissertations

Internet-scale distributed systems such as content delivery networks (CDNs) operate hundreds of thousands of servers deployed in thousands of data center locations around the globe. Since the energy costs of operating such a large IT infrastructure are a significant fraction of the total operating costs, we argue for redesigning them to incorporate energy optimization as a first-order principle. We focus on CDNs and demonstrate techniques to save energy while meeting client-perceived service level agreements (SLAs) and minimizing impact on hardware reliability.

Servers deployed at individual data centers can be switched off at low load to save energy. We show that ...


Threat Analysis, Countermeaures And Design Strategies For Secure Computation In Nanometer Cmos Regime, Raghavan Kumar Jan 2015

Threat Analysis, Countermeaures And Design Strategies For Secure Computation In Nanometer Cmos Regime, Raghavan Kumar

Doctoral Dissertations

Advancements in CMOS technologies have led to an era of Internet Of Things (IOT), where the devices have the ability to communicate with each other apart from their computational power. As more and more sensitive data is processed by embedded devices, the trend towards lightweight and efficient cryptographic primitives has gained significant momentum. Achieving a perfect security in silicon is extremely difficult, as the traditional cryptographic implementations are vulnerable to various active and passive attacks. There is also a threat in the form of "hardware Trojans" inserted into the supply chain by the untrusted third-party manufacturers for economic incentives. Apart ...


3d Robotic Sensing Of People: Human Perception, Representation And Activity Recognition, Hao Zhang Aug 2014

3d Robotic Sensing Of People: Human Perception, Representation And Activity Recognition, Hao Zhang

Doctoral Dissertations

The robots are coming. Their presence will eventually bridge the digital-physical divide and dramatically impact human life by taking over tasks where our current society has shortcomings (e.g., search and rescue, elderly care, and child education). Human-centered robotics (HCR) is a vision to address how robots can coexist with humans and help people live safer, simpler and more independent lives.

As humans, we have a remarkable ability to perceive the world around us, perceive people, and interpret their behaviors. Endowing robots with these critical capabilities in highly dynamic human social environments is a significant but very challenging problem in ...


Reliable And Efficient Multithreading, Tongping Liu May 2014

Reliable And Efficient Multithreading, Tongping Liu

Doctoral Dissertations

The advent of multicore architecture has increased the demand for multithreaded programs. It is notoriously far more challenging to write parallel programs correctly and efficiently than sequential ones because of the wide range of concurrency errors and performance problems. In this thesis, I developed a series of runtime systems and tools to combat concurrency errors and performance problems of multithreaded programs.

The first system, Dthreads, automatically ensures determinism for unmodified C/C++ applications using the pthreads library without requiring programmer intervention and hardware support. Dthreads greatly simplifies the understanding and debugging of multithreaded programs. Dthreads often matches or even exceeds ...


Exploiting Energy Harvesting For Passive Embedded Computing Systems, Jeremy Joel Gummeson Feb 2014

Exploiting Energy Harvesting For Passive Embedded Computing Systems, Jeremy Joel Gummeson

Doctoral Dissertations

The key limitation in mobile computing systems is energy - without a stable power supply, these systems cannot process, store, or communicate data. This problem is of particular interest since the storage density of battery technologies do not follow scaling trends similar to Moore's law. This means that depending on application performance requirements and lifetime objectives, a battery may dominate the overall system weight and form factor; this could result in an overall size that is either inconvenient or unacceptable for a particular application. As device features have scaled down in size, entire embedded systems have been implemented on a ...


Online Multi-Stage Deep Architectures For Feature Extraction And Object Recognition, Derek Christopher Rose Aug 2013

Online Multi-Stage Deep Architectures For Feature Extraction And Object Recognition, Derek Christopher Rose

Doctoral Dissertations

Multi-stage visual architectures have recently found success in achieving high classification accuracies over image datasets with large variations in pose, lighting, and scale. Inspired by techniques currently at the forefront of deep learning, such architectures are typically composed of one or more layers of preprocessing, feature encoding, and pooling to extract features from raw images. Training these components traditionally relies on large sets of patches that are extracted from a potentially large image dataset. In this context, high-dimensional feature space representations are often helpful for obtaining the best classification performances and providing a higher degree of invariance to object transformations ...


Using Power-Law Properties Of Social Groups For Cloud Defense And Community Detection, Justin L. Rice Jan 2013

Using Power-Law Properties Of Social Groups For Cloud Defense And Community Detection, Justin L. Rice

Doctoral Dissertations

The power-law distribution can be used to describe various aspects of social group behavior. For mussels, sociobiological research has shown that the Lévy walk best describes their self-organizing movement strategy. A mussel's step length is drawn from a power-law distribution, and its direction is drawn from a uniform distribution. In the area of social networks, theories such as preferential attachment seek to explain why the degree distribution tends to be scale-free. The aim of this dissertation is to glean insight from these works to help solve problems in two domains: cloud computing systems and community detection.

Privacy and security ...


Exploring Computational Chemistry On Emerging Architectures, David Dewayne Jenkins Dec 2012

Exploring Computational Chemistry On Emerging Architectures, David Dewayne Jenkins

Doctoral Dissertations

Emerging architectures, such as next generation microprocessors, graphics processing units, and Intel MIC cards, are being used with increased popularity in high performance computing. Each of these architectures has advantages over previous generations of architectures including performance, programmability, and power efficiency. With the ever-increasing performance of these architectures, scientific computing applications are able to attack larger, more complicated problems. However, since applications perform differently on each of the architectures, it is difficult to determine the best tool for the job. This dissertation makes the following contributions to computer engineering and computational science. First, this work implements the computational chemistry variational ...


Parallel For Loops On Heterogeneous Resources, Frederick Edward Weber Dec 2012

Parallel For Loops On Heterogeneous Resources, Frederick Edward Weber

Doctoral Dissertations

In recent years, Graphics Processing Units (GPUs) have piqued the interest of researchers in scientific computing. Their immense floating point throughput and massive parallelism make them ideal for not just graphical applications, but many general algorithms as well. Load balancing applications and taking advantage of all computational resources in a machine is a difficult challenge, especially when the resources are heterogeneous. This dissertation presents the clUtil library, which vastly simplifies developing OpenCL applications for heterogeneous systems. The core focus of this dissertation lies in clUtil's ParallelFor construct and our novel PINA scheduler which can efficiently load balance work onto ...


Dynamic Task Execution On Shared And Distributed Memory Architectures, Asim Yarkhan Dec 2012

Dynamic Task Execution On Shared And Distributed Memory Architectures, Asim Yarkhan

Doctoral Dissertations

Multicore architectures with high core counts have come to dominate the world of high performance computing, from shared memory machines to the largest distributed memory clusters. The multicore route to increased performance has a simpler design and better power efficiency than the traditional approach of increasing processor frequencies. But, standard programming techniques are not well adapted to this change in computer architecture design.

In this work, we study the use of dynamic runtime environments executing data driven applications as a solution to programming multicore architectures. The goals of our runtime environments are productivity, scalability and performance. We demonstrate productivity by ...


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 ...