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Articles 1 - 30 of 42
Full-Text Articles in Computer Engineering
Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi
Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi
Theses and Dissertations--Electrical and Computer Engineering
The long-standing technological pillars for computing systems evolution, namely Moore's law and Von Neumann architecture, are breaking down under the pressure of meeting the capacity and energy efficiency demands of computing and communication architectures that are designed to process modern data-centric applications related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In response, both industry and academia have turned to 'more-than-Moore' technologies for realizing hardware architectures for communication and computing. Fortunately, Silicon Photonics (SiPh) has emerged as one highly promising ‘more-than-Moore’ technology. Recent progress has enabled SiPh-based interconnects to outperform traditional electrical interconnects, offering advantages like high bandwidth density, …
Parallel Real Time Rrt*: An Rrt* Based Path Planning Process, David Yackzan
Parallel Real Time Rrt*: An Rrt* Based Path Planning Process, David Yackzan
Theses and Dissertations--Mechanical Engineering
This thesis presents a new parallelized real-time path planning process. This process is an extension of the Real-Time Rapidly Exploring Random Trees* (RT-RRT*) algorithm developed by Naderi et al in 2015 [1]. The RT-RRT* algorithm was demonstrated on a simulated two-dimensional dynamic environment while finding paths to a varying target state. We demonstrate that the original algorithm is incapable of running at a sufficient rate for control of a 7-degree-of-freedom (7-DoF) robotic arm while maintaining a path planning tree in 7 dimensions. This limitation is due to the complexity of maintaining a tree in a high-dimensional space and the network …
Application Of Conventional Feedforward And Deep Neural Networks To Power Distribution System State Estimation And State Forecasting, James Paul Carmichael
Application Of Conventional Feedforward And Deep Neural Networks To Power Distribution System State Estimation And State Forecasting, James Paul Carmichael
Theses and Dissertations--Electrical and Computer Engineering
Classical neural networks such as feedforward multilayer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. This research investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) to mitigate challenges in power distribution system state estimation and forecasting based upon conventional analytic methods. The ability of MLPs to perform regression to perform power system state estimation will be investigated. MLPs are considered based upon their promise to learn …
Formation Control With Bounded Controls And Collision Avoidance: Theory And Application To Quadrotor Unmanned Air Vehicles, Zachary S. Lippay
Formation Control With Bounded Controls And Collision Avoidance: Theory And Application To Quadrotor Unmanned Air Vehicles, Zachary S. Lippay
Theses and Dissertations--Mechanical Engineering
This dissertation presents new results on multi-agent formation control and applies the new control algorithms to quadrotor unmanned air vehicles. First, this dissertation presents a formation control algorithm for double-integrator agents, where the formation is time varying and the agents’ controls satisfy a priori bounds (e.g., the controls accommodate actuator saturation). The main analytic results provide sufficient conditions such that all agents converge to the desired time-varying relative positions with one another and the leader, and have a priori bounded controls (if applicable). We also present results from rotorcraft experiments that demonstrate the algorithm with time-varying formations and bounded controls. …
Synthesizing Dysarthric Speech Using Multi-Speaker Tts For Dsyarthric Speech Recognition, Mohammad Soleymanpour
Synthesizing Dysarthric Speech Using Multi-Speaker Tts For Dsyarthric Speech Recognition, Mohammad Soleymanpour
Theses and Dissertations--Electrical and Computer Engineering
Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility through slow, uncoordinated control of speech production muscles. Automatic Speech recognition (ASR) systems may help dysarthric talkers communicate more effectively. However, robust dysarthria-specific ASR requires a significant amount of training speech is required, which is not readily available for dysarthric talkers.
In this dissertation, we investigate dysarthric speech augmentation and synthesis methods. To better understand differences in prosodic and acoustic characteristics of dysarthric spontaneous speech at varying severity levels, a comparative study between typical and dysarthric speech was conducted. These characteristics are important components for dysarthric speech modeling, …
Protocols And Architecture For Privacy-Preserving Authentication And Secure Message Dissemination In Vehicular Ad Hoc Networks, Shafika Showkat Moni
Protocols And Architecture For Privacy-Preserving Authentication And Secure Message Dissemination In Vehicular Ad Hoc Networks, Shafika Showkat Moni
Theses and Dissertations--Computer Science
The rapid development in the automotive industry and wireless communication technologies have enhanced the popularity of Vehicular ad hoc networks (VANETs). Today, the automobile industry is developing sophisticated sensors that can provide a wide range of assistive features, including accident avoidance, automatic lane tracking, semi-autonomous driving, suggested lane changes, and more. VANETs can provide drivers a safer and more comfortable driving experience, as well as many other useful services by leveraging such technological advancements. Even though this networking technology enables smart and autonomous driving, it also introduces a plethora of attack vectors. However, the main issues to be sorted out …
Improving Network Policy Enforcement Using Natural Language Processing And Programmable Networks, Pinyi Shi
Improving Network Policy Enforcement Using Natural Language Processing And Programmable Networks, Pinyi Shi
Theses and Dissertations--Computer Science
Computer networks are becoming more complex and challenging to operate, manage, and protect. As a result, Network policies that define how network operators should manage the network are becoming more complex and nuanced. Unfortunately, network policies are often an undervalued part of network design, leaving network operators to guess at the intent of policies that are written and fill in the gaps where policies don’t exist. Organizations typically designate Policy Committees to write down the network policies in the policy documents using high-level natural languages. The policy documents describe both the acceptable and unacceptable uses of the network. Network operators …
On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae
On The Impact Of Gravity Compensation On Reinforcement Learning In Goal-Reaching Tasks For Robotic Manipulators, Jonathan Fugal, Hasan A. Poonawala, Jihye Bae
Electrical and Computer Engineering Faculty Publications
Advances in machine learning technologies in recent years have facilitated developments in autonomous robotic systems. Designing these autonomous systems typically requires manually specified models of the robotic system and world when using classical control-based strategies, or time consuming and computationally expensive data-driven training when using learning-based strategies. Combination of classical control and learning-based strategies may mitigate both requirements. However, the performance of the combined control system is not obvious given that there are two separate controllers. This paper focuses on one such combination, which uses gravity-compensation together with reinforcement learning (RL). We present a study of the effects of gravity …
Re-Designing Main Memory Subsystems With Emerging Monolithic 3d (M3d) Integration And Phase Change Memory Technologies, Chao-Hsuan Huang
Re-Designing Main Memory Subsystems With Emerging Monolithic 3d (M3d) Integration And Phase Change Memory Technologies, Chao-Hsuan Huang
Theses and Dissertations--Electrical and Computer Engineering
Over the past two decades, Dynamic Random-Access Memory (DRAM) has emerged as the dominant technology for implementing the main memory subsystems of all types of computing systems. However, inferring from several recent trends, computer architects in both the industry and academia have widely accepted that the density (memory capacity per chip area) and latency of DRAM based main memory subsystems cannot sufficiently scale in the future to meet the requirements of future data-centric workloads related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In fact, the achievable density and access latency in main memory subsystems presents a very fundamental …
Designing Novel Hardware Security Primitives For Smart Computing Devices, Amitkumar Degada
Designing Novel Hardware Security Primitives For Smart Computing Devices, Amitkumar Degada
Theses and Dissertations--Electrical and Computer Engineering
Smart computing devices are miniaturized electronics devices that can sense their surroundings, communicate, and share information autonomously with other devices to work cohesively. Smart devices have played a major role in improving quality of the life and boosting the global economy. They are ubiquitously present, smart home, smart city, smart girds, industry, healthcare, controlling the hazardous environment, and military, etc. However, we have witnessed an exponential rise in potential threat vectors and physical attacks in recent years. The conventional software-based security approaches are not suitable in the smart computing device, therefore, hardware-enabled security solutions have emerged as an attractive choice. …
Toward Intelligent Welding By Building Its Digital Twin, Qiyue Wang
Toward Intelligent Welding By Building Its Digital Twin, Qiyue Wang
Theses and Dissertations--Electrical and Computer Engineering
To meet the increasing requirements for production on individualization, efficiency and quality, traditional manufacturing processes are evolving to smart manufacturing with the support from the information technology advancements including cyber-physical systems (CPS), Internet of Things (IoT), big industrial data, and artificial intelligence (AI). The pre-requirement for integrating with these advanced information technologies is to digitalize manufacturing processes such that they can be analyzed, controlled, and interacted with other digitalized components. Digital twin is developed as a general framework to do that by building the digital replicas for the physical entities. This work takes welding manufacturing as the case study to …
Resource Efficient Design Of Quantum Circuits For Cryptanalysis And Scientific Computing Applications, Edgard Munoz-Coreas
Resource Efficient Design Of Quantum Circuits For Cryptanalysis And Scientific Computing Applications, Edgard Munoz-Coreas
Theses and Dissertations--Electrical and Computer Engineering
Quantum computers offer the potential to extend our abilities to tackle computational problems in fields such as number theory, encryption, search and scientific computation. Up to a superpolynomial speedup has been reported for quantum algorithms in these areas. Motivated by the promise of faster computations, the development of quantum machines has caught the attention of both academics and industry researchers. Quantum machines are now at sizes where implementations of quantum algorithms or their components are now becoming possible. In order to implement quantum algorithms on quantum machines, resource efficient circuits and functional blocks must be designed. In this work, we …
Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?, Hana Khamfroush, Nathaniel Hudson, Samuel Iloo, Mahshid R. Naeini
Influence Spread In Two-Layer Interdependent Networks: Designed Single-Layer Or Random Two-Layer Initial Spreaders?, Hana Khamfroush, Nathaniel Hudson, Samuel Iloo, Mahshid R. Naeini
Computer Science Faculty Publications
Influence spread in multi-layer interdependent networks (M-IDN) has been studied in the last few years; however, prior works mostly focused on the spread that is initiated in a single layer of an M-IDN. In real world scenarios, influence spread can happen concurrently among many or all components making up the topology of an M-IDN. This paper investigates the effectiveness of different influence spread strategies in M-IDNs by providing a comprehensive analysis of the time evolution of influence propagation given different initial spreader strategies. For this study we consider a two-layer interdependent network and a general probabilistic threshold influence spread model …
Anonymous And Efficient Message Authentication Scheme For Smart Grid, Libing Wu, Jing Wang, Sherali Zeadally, Debiao He
Anonymous And Efficient Message Authentication Scheme For Smart Grid, Libing Wu, Jing Wang, Sherali Zeadally, Debiao He
Information Science Faculty Publications
Smart grid has emerged as the next-generation electricity grid with power flow optimization and high power quality. Smart grid technologies have attracted the attention of industry and academia in the last few years. However, the tradeoff between security and efficiency remains a challenge in the practical deployment of the smart grid. Most recently, Li et al. proposed a lightweight message authentication scheme with user anonymity and claimed that their scheme is provably secure. But we found that their scheme fails to achieve mutual authentication and mitigate some typical attacks (e.g., impersonation attack, denial of service attack) in the smart grid …
Automated Network Security With Exceptions Using Sdn, Sergio A. Rivera Polanco
Automated Network Security With Exceptions Using Sdn, Sergio A. Rivera Polanco
Theses and Dissertations--Computer Science
Campus networks have recently experienced a proliferation of devices ranging from personal use devices (e.g. smartphones, laptops, tablets), to special-purpose network equipment (e.g. firewalls, network address translation boxes, network caches, load balancers, virtual private network servers, and authentication servers), as well as special-purpose systems (badge readers, IP phones, cameras, location trackers, etc.). To establish directives and regulations regarding the ways in which these heterogeneous systems are allowed to interact with each other and the network infrastructure, organizations typically appoint policy writing committees (PWCs) to create acceptable use policy (AUP) documents describing the rules and behavioral guidelines that all campus network …
Curricular Optimization: Solving For The Optimal Student Success Pathway, William G. Thompson-Arjona
Curricular Optimization: Solving For The Optimal Student Success Pathway, William G. Thompson-Arjona
Theses and Dissertations--Electrical and Computer Engineering
Considering the significant investment of higher education made by students and their families, graduating in a timely manner is of the utmost importance. Delay attributed to drop out or the retaking of a course adds cost and negatively affects a student’s academic progression. Considering this, it becomes paramount for institutions to focus on student success in relation to term scheduling.
Often overlooked, complexity of a course schedule may be one of the most important factors in whether or not a student successfully completes his or her degree. More often than not students entering an institution as a first time full …
Novel Applications Of Machine Learning In Bioinformatics, Yi Zhang
Novel Applications Of Machine Learning In Bioinformatics, Yi Zhang
Theses and Dissertations--Computer Science
Technological advances in next-generation sequencing and biomedical imaging have led to a rapid increase in biomedical data dimension and acquisition rate, which is challenging the conventional data analysis strategies. Modern machine learning techniques promise to leverage large data sets for finding hidden patterns within them, and for making accurate predictions. This dissertation aims to design novel machine learning-based models to transform biomedical big data into valuable biological insights. The research presented in this dissertation focuses on three bioinformatics domains: splice junction classification, gene regulatory network reconstruction, and lesion detection in mammograms.
A critical step in defining gene structures and mRNA …
Facepet: Enhancing Bystanders' Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jaouad A. Mouloud, Scott Griffith
Facepet: Enhancing Bystanders' Facial Privacy With Smart Wearables/Internet Of Things, Alfredo J. Perez, Sherali Zeadally, Luis Y. Matos Garcia, Jaouad A. Mouloud, Scott Griffith
Information Science Faculty Publications
Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the …
Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson
Advanced Recurrent Network-Based Hybrid Acoustic Models For Low Resource Speech Recognition, Jian Kang, Wei-Qiang Zhang, Wei-Wei Liu, Jia Liu, Michael T. Johnson
Electrical and Computer Engineering Faculty Publications
Recurrent neural networks (RNNs) have shown an ability to model temporal dependencies. However, the problem of exploding or vanishing gradients has limited their application. In recent years, long short-term memory RNNs (LSTM RNNs) have been proposed to solve this problem and have achieved excellent results. Bidirectional LSTM (BLSTM), which uses both preceding and following context, has shown particularly good performance. However, the computational requirements of BLSTM approaches are quite heavy, even when implemented efficiently with GPU-based high performance computers. In addition, because the output of LSTM units is bounded, there is often still a vanishing gradient issue over multiple layers. …
Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally
Compact Hardware Implementation Of A Sha-3 Core For Wireless Body Sensor Networks, Yi Yang, Debiao He, Neeraj Kumar, Sherali Zeadally
Information Science Faculty Publications
One of the most important Internet of Things applications is the wireless body sensor network (WBSN), which can provide universal health care, disease prevention, and control. Due to large deployments of small scale smart sensors in WBSNs, security, and privacy guarantees (e.g., security and safety-critical data, sensitive private information) are becoming a challenging issue because these sensor nodes communicate using an open channel, i.e., Internet. We implement data integrity (to resist against malicious tampering) using the secure hash algorithm 3 (SHA-3) when smart sensors in WBSNs communicate with each other using the Internet. Due to the limited resources (i.e., storage, …
Fault Identification And Location For Distribution Network With Distributed Generations, Wen Fan, Yuan Liao
Fault Identification And Location For Distribution Network With Distributed Generations, Wen Fan, Yuan Liao
Electrical and Computer Engineering Faculty Publications
Power distribution networks with distributed generations may experience faults. It is essential to promptly locate the fault for fast repair and restoration. This paper presents a novel method for identifying the faulted section and accurate location of faults that occur on power distribution grid. Appropriate matrices are set up to represent meter locations on the grid and the topology of the grid. The voltage and current measurements obtained are utilized to decide the fault sections. Then fault location is determined by solving equations that link measurements and fault locations through bus impedance matrix. The method is applicable to both single …
A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo
A Fast And Robust Extrinsic Calibration For Rgb-D Camera Networks, Po-Chang Su, Ju Shen, Wanxin Xu, Sen-Ching S. Cheung, Ying Luo
Electrical and Computer Engineering Faculty Publications
From object tracking to 3D reconstruction, RGB-Depth (RGB-D) camera networks play an increasingly important role in many vision and graphics applications. Practical applications often use sparsely-placed cameras to maximize visibility, while using as few cameras as possible to minimize cost. In general, it is challenging to calibrate sparse camera networks due to the lack of shared scene features across different camera views. In this paper, we propose a novel algorithm that can accurately and rapidly calibrate the geometric relationships across an arbitrary number of RGB-D cameras on a network. Our work has a number of novel features. First, to cope …
Design Of A Machine Vision Camera For Spatial Augmented Reality, Matt Phillip Ruffner
Design Of A Machine Vision Camera For Spatial Augmented Reality, Matt Phillip Ruffner
Theses and Dissertations--Electrical and Computer Engineering
Structured Light Imaging (SLI) is a means of digital reconstruction, or Three-Dimensional (3D) scanning, and has uses that span many disciplines. A projector, camera and Personal Computer (PC) are required to perform such 3D scans. Slight variances in synchronization between these three devices can cause malfunctions in the process due to the limitations of PC graphics processors as real-time systems. Previous work used a Field Programmable Gate Array (FPGA) to both drive the projector and trigger the camera, eliminating these timing issues, but still needing an external camera. This thesis proposes the incorporation of the camera with the FPGA SLI …
Interactive Clinical Event Pattern Mining And Visualization Using Insurance Claims Data, Zhenhui Piao
Interactive Clinical Event Pattern Mining And Visualization Using Insurance Claims Data, Zhenhui Piao
Theses and Dissertations--Computer Science
With exponential growth on a daily basis, there is potentially valuable information hidden in complex electronic medical records (EMR) systems. In this thesis, several efficient data mining algorithms were explored to discover hidden knowledge in insurance claims data. The first aim was to cluster three levels of information overload(IO) groups among chronic rheumatic disease (CRD) patient groups based on their clinical events extracted from insurance claims data. The second aim was to discover hidden patterns using three renowned pattern mining algorithms: Apriori, frequent pattern growth(FP-Growth), and sequential pattern discovery using equivalence classes(SPADE). The SPADE algorithm was found to be the …
Iot Development For Healthy Independent Living, Shalom Greene
Iot Development For Healthy Independent Living, Shalom Greene
Theses and Dissertations--Electrical and Computer Engineering
The rise of internet connected devices has enabled the home with a vast amount of enhancements to make life more convenient. These internet connected devices can be used to form a community of devices known as the internet of things (IoT). There is great value in IoT devices to promote healthy independent living for older adults.
Fall-related injuries has been one of the leading causes of death in older adults. For example, every year more than a third of people over 65 in the U.S. experience a fall, of which up to 30 percent result in moderate to severe injury. …
Contributions To Edge Computing, Vernon K. Bumgardner
Contributions To Edge Computing, Vernon K. Bumgardner
Theses and Dissertations--Computer Science
Efforts related to Internet of Things (IoT), Cyber-Physical Systems (CPS), Machine to Machine (M2M) technologies, Industrial Internet, and Smart Cities aim to improve society through the coordination of distributed devices and analysis of resulting data. By the year 2020 there will be an estimated 50 billion network connected devices globally and 43 trillion gigabytes of electronic data. Current practices of moving data directly from end-devices to remote and potentially distant cloud computing services will not be sufficient to manage future device and data growth.
Edge Computing is the migration of computational functionality to sources of data generation. The importance of …
Novel Resource Efficient Circuit Designs For Rebooting Computing, Sai Subramanya Varun Thogarcheti
Novel Resource Efficient Circuit Designs For Rebooting Computing, Sai Subramanya Varun Thogarcheti
Theses and Dissertations--Electrical and Computer Engineering
CMOS based computing is reaching its limits. To take computation beyond Moores law (the number of transistors and hence processing power on a chip doubles every 18 months to 3 years) requires research explorations in (i) new materials, devices, and processes, (ii) new architectures and algorithms, (iii) new paradigm of logic bit representation. The focus is on fundamental new ways to compute under the umbrella of rebooting computing such as spintronics, quantum computing, adiabatic and reversible computing. Therefore, this thesis highlights explicitly Quantum computing and Adiabatic logic, two new computing paradigms that come under the umbrella of rebooting computing. Quantum …
Autonomous Quadrotor Collision Avoidance And Destination Seeking In A Gps-Denied Environment, Thomas C. Kirven
Autonomous Quadrotor Collision Avoidance And Destination Seeking In A Gps-Denied Environment, Thomas C. Kirven
Theses and Dissertations--Mechanical Engineering
This thesis presents a real-time autonomous guidance and control method for a quadrotor in a GPS-denied environment. The quadrotor autonomously seeks a destination while it avoids obstacles whose shape and position are initially unknown. We implement the obstacle avoidance and destination seeking methods using off-the-shelf sensors, including a vision-sensing camera. The vision-sensing camera detects the positions of points on the surface of obstacles. We use this obstacle position data and a potential-field method to generate velocity commands. We present a backstepping controller that uses the velocity commands to generate the quadrotor's control inputs. In indoor experiments, we demonstrate that the …
Per-Pixel Calibration For Rgb-Depth Natural 3d Reconstruction On Gpu, Sen Li
Per-Pixel Calibration For Rgb-Depth Natural 3d Reconstruction On Gpu, Sen Li
Theses and Dissertations--Electrical and Computer Engineering
Ever since the Kinect brought low-cost depth cameras into consumer market, great interest has been invigorated into Red-Green-Blue-Depth (RGBD) sensors. Without calibration, a RGBD camera’s horizontal and vertical field of view (FoV) could help generate 3D reconstruction in camera space naturally on graphics processing unit (GPU), which however is badly deformed by the lens distortions and imperfect depth resolution (depth distortion). The camera’s calibration based on a pinhole-camera model and a high-order distortion removal model requires a lot of calculations in the fragment shader. In order to get rid of both the lens distortion and the depth distortion …
Hybrid Single And Dual Pattern Structured Light Illumination, Minghao Wang
Hybrid Single And Dual Pattern Structured Light Illumination, Minghao Wang
Theses and Dissertations--Electrical and Computer Engineering
Structured Light Illumination is a widely used 3D shape measurement technique in non-contact surface scanning. Multi-pattern based Structured Light Illumination methods reconstruct 3-D surface with high accuracy, but are sensitive to object motion during the pattern projection and the speed of scanning process is relatively long. To reduce this sensitivity, single pattern techniques are developed to achieve a high speed scanning process, such as Composite Pattern (CP) and Modified Composite Pattern (MCP) technique. However, most of single patter techniques have a significant banding artifact and sacrifice the accuracy. We focus on developing SLI techniques can achieve both high speed, high …