Computer Engineering Commons^™

Deep Learning Based Power System Stability Assessment For Reduced Wecc System, Yinfeng Zhao

Doctoral Dissertations

Power system stability is the ability of power system, for a giving initial operating condition, to reach a new operation condition with most of the system variables bounded in normal range after subjecting to a short or long disturbance. Traditional power system stability mainly uses time-domain simulation which is very time consuming and only appropriate for offline assessment.

Nowadays, with increasing penetration of inverter based renewable, large-scale distributed energy storage integration and operation uncertainty brought by weather and electricity market, system dynamic and operating condition is more dramatic, and traditional power system stability assessment based on scheduling may not be …

Development Of A Soft Robotic Approach For An Intra-Abdominal Wireless Laparoscopic Camera, Hui Liu

Doctoral Dissertations

In Single-Incision Laparoscopic Surgery (SILS), the Magnetic Anchoring and Guidance System (MAGS) arises as a promising technique to provide larger workspaces and field of vision for the laparoscopes, relief space for other instruments, and require fewer incisions. Inspired by MAGS, many concept designs related to fully insertable magnetically driven laparoscopes are developed and tested on the transabdominal operation. However, ignoring the tissue interaction and insertion procedure, most of the designs adopt rigid structures, which not only damage the patients' tissue with excess stress concentration and sliding motion but also require complicated operation for the insertion. Meanwhile, lacking state tracking of …

Enabling Daily Tracking Of Individual’S Cognitive State With Eyewear, Soha Rostaminia

Doctoral Dissertations

Research studies show that sleep deprivation causes severe fatigue, impairs attention and decision making, and affects our emotional interpretation of events, which makes it a big threat to public safety, and mental and physical well-being. Hence, it would be most desired if we could continuously measure one’s drowsiness and fatigue level, their emotion while making decisions, and assess their sleep quality in order to provide personalized feedback or actionable behavioral suggestions to modulate sleep pattern and alertness levels with the aim of enhancing performance, well-being, and quality of life. While there have been decades of studies on wearable devices, we …

Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona

Doctoral Dissertations

The enormous innovation in computational intelligence has disrupted the traditional ways we solve the main problems of our society and allowed us to make more data-informed decisions. Energy systems and the ways we deliver electricity are not exceptions to this trend: cheap and pervasive sensing systems and new communication technologies have enabled the collection of large amounts of data that are being used to monitor and predict in real-time the behavior of this infrastructure. Bringing intelligence to the power grid creates many opportunities to integrate new renewable energy sources more efficiently, facilitate grid planning and expansion, improve reliability, optimize electricity …

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …

Data-Driven Control, Modeling, And Forecasting For Residential Solar Power, Akansha Singh Bansal

Doctoral Dissertations

Distributed solar generation is rising rapidly due to a continuing decline in the cost of solar modules. Most residential solar deployments today are grid-tied, enabling them to draw power from the grid when their local demand exceeds solar generation and feed power into the grid when their local solar generation exceeds demand. The electric grid was not designed to support such decentralized and intermittent energy generation by millions of individual users. This dramatic increase in solar power is placing increasing stress on the grid, which must continue to balance its supply and demand despite the potential for large solar fluctuations. …

On Improving Robustness Of Hardware Security Primitives And Resistance To Reverse Engineering Attacks, Vinay C. Patil

Doctoral Dissertations

The continued growth of information technology (IT) industry and proliferation of interconnected devices has aggravated the problem of ensuring security and necessitated the need for novel, robust solutions. Physically unclonable functions (PUFs) have emerged as promising secure hardware primitives that can utilize the disorder introduced during manufacturing process to generate unique keys. They can be utilized as \textit{lightweight} roots-of-trust for use in authentication and key generation systems. Unlike insecure non-volatile memory (NVM) based key storage systems, PUFs provide an advantage -- no party, including the manufacturer, should be able to replicate the physical disorder and thus, effectively clone the PUF. …

Resource Allocation In Distributed Service Networks, Nitish Kumar Panigrahy

Doctoral Dissertations

The past few years have witnessed significant growth in the use of distributed network analytics involving agile code, data and computational resources. In many such networked systems, for example, Internet of Things (IoT), a large number of smart devices, sensors, processing and storage resources are widely distributed in a geographic region. These devices and resources distributed over a physical space are collectively called a distributed service network. Efficient resource allocation in such high performance service networks remains one of the most critical problems. In this thesis, we model and optimize the allocation of resources in a distributed service network. This …

Sensor Fusion For Object Detection And Tracking In Autonomous Vehicles, Mohamad Ramin Nabati

Doctoral Dissertations

Autonomous driving vehicles depend on their perception system to understand the environment and identify all static and dynamic obstacles surrounding the vehicle. The perception system in an autonomous vehicle uses the sensory data obtained from different sensor modalities to understand the environment and perform a variety of tasks such as object detection and object tracking. Combining the outputs of different sensors to obtain a more reliable and robust outcome is called sensor fusion. This dissertation studies the problem of sensor fusion for object detection and object tracking in autonomous driving vehicles and explores different approaches for utilizing deep neural networks …

Towards Secure Deep Neural Networks For Cyber-Physical Systems, Jiangnan Li

Doctoral Dissertations

In recent years, deep neural networks (DNNs) are increasingly investigated in the literature to be employed in cyber-physical systems (CPSs). DNNs own inherent advantages in complex pattern identifying and achieve state-of-the-art performances in many important CPS applications. However, DNN-based systems usually require large datasets for model training, which introduces new data management issues. Meanwhile, research in the computer vision domain demonstrated that the DNNs are highly vulnerable to adversarial examples. Therefore, the security risks of employing DNNs in CPSs applications are of concern.

In this dissertation, we study the security of employing DNNs in CPSs from both the data domain …

Addressing Security Challenges In Embedded Systems And Multi-Tenant Fpgas, Georgios Provelengios

Doctoral Dissertations

Embedded systems and field-programmable gate arrays (FPGAs) have become crucial parts of the infrastructure that supports our modern technological world. Given the multitude of threats that are present, the need for secure computing systems is undeniably greater than ever. Embedded systems and FPGAs are governed by characteristics that create unique security challenges and vulnerabilities. Despite their array of uses, embedded systems are often built with modest microprocessors that do not support the conventional security solutions used by workstations, such as virus scanners. In the first part of this dissertation, a microprocessor defense mechanism that uses a hardware monitor to protect …

Instrumentation, Modeling, And Sound Metamodeling Foundations For Complex Hybrid Systems, Natasha Amelia Jarus

Doctoral Dissertations

Many of our critical infrastructures, from power grids to water distribution networks, are complex hybrid systems that use software to control their non-trivial physical dynamics. These systems must be able to capably serve their purpose, while also being reliable, dependable, safe, secure, and efficient. Representation and analysis of these features requires the creation of several distinct models. These models may encode design goals or be derived from collected instrumentation data, reflecting both how a system ought to operate and how it does operate. It is essential to ensure that all of these models consistently and accurately describe the same system. …

Leveraging Conventional Internet Routing Protocol Behavior To Defeat Ddos And Adverse Networking Conditions, Jared M. Smith

Doctoral Dissertations

The Internet is a cornerstone of modern society. Yet increasingly devastating attacks against the Internet threaten to undermine the Internet's success at connecting the unconnected. Of all the adversarial campaigns waged against the Internet and the organizations that rely on it, distributed denial of service, or DDoS, tops the list of the most volatile attacks. In recent years, DDoS attacks have been responsible for large swaths of the Internet blacking out, while other attacks have completely overwhelmed key Internet services and websites. Core to the Internet's functionality is the way in which traffic on the Internet gets from one destination …

Formal Verification Of Divider And Square-Root Arithmetic Circuits Using Computer Algebra Methods, Atif Yasin

Doctoral Dissertations

A considerable progress has been made in recent years in verification of arithmetic circuits such as multipliers, fused multiply-adders, multiply-accumulate, and other components of arithmetic datapaths, both in integer and finite field domain. However, the verification of hardware dividers and square-root functions have received only a limited attention from the verification community, with a notable exception for theorem provers and other inductive, non-automated systems. Division, square root, and transcendental functions are all tied to the basic Intel architecture and proving correctness of such algorithms is of grave importance. Although belonging to the same iterative-subtract class of architectures, they widely differ …

Trustworthy Systems And Protocols For The Internet Of Things, Arman Pouraghily

Doctoral Dissertations

Processor-based embedded systems are integrated into many aspects of everyday life such as industrial control, automotive systems, healthcare, the Internet of Things, etc. As Moore’s law progresses, these embedded systems have moved from simple microcontrollers to full-scale embedded computing systems with multiple processor cores and operating systems support. At the same time, the security of these devices has also become a key concern. Our main focus in this work is the security and privacy of the embedded systems used in IoT systems. In the first part of this work, we take a look at the security of embedded systems from …

Design Of Hardware With Quantifiable Security Against Reverse Engineering, Shahrzad Keshavarz

Doctoral Dissertations

Semiconductors are a 412 billion dollar industry and integrated circuits take on important roles in human life, from everyday use in smart-devices to critical applications like healthcare and aviation. Saving today's hardware systems from attackers can be a huge concern considering the budget spent on designing these chips and the sensitive information they may contain. In particular, after fabrication, the chip can be subject to a malicious reverse engineer that tries to invasively figure out the function of the chip or other sensitive data. Subsequent to an attack, a system can be subject to cloning, counterfeiting, or IP theft. This …

A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh

Doctoral Dissertations

High performance parallel computing and direct (factorization-based) solution methods have been the two main trends in electromagnetic computations in recent years. When time-harmonic (frequency-domain) Maxwell's equation are directly discretized with the Finite Element Method (FEM) or other Partial Differential Equation (PDE) methods, the resulting linear system of equations is sparse and indefinite, thus harder to efficiently factorize serially or in parallel than alternative methods e.g. integral equation solutions, that result in dense linear systems. State-of-the-art sparse matrix direct solvers such as MUMPS and PARDISO don't scale favorably, have low parallel efficiency and high memory footprint. This work introduces a new …

Time-Difference Circuits: Methodology, Design, And Digital Realization, Shuo Li

Doctoral Dissertations

This thesis presents innovations for a special class of circuits called Time Difference (TD) circuits. We introduce a signal processing methodology with TD signals that alters the target signal from a magnitude perspective to time interval between two time events and systematically organizes the primary TD functions abstracted from existing TD circuits and systems. The TD circuits draw attention from a broad range of application fields. In addition, highly evolved complementary metal-oxide-semiconductor (CMOS) technology suffers from various problems related to voltage and current amplitude signal processing methods. Compared to traditional analog and digital circuits, TD circuits bring several compelling features: …

Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh

Doctoral Dissertations

Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …

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 also …

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 …

Fundamental Limits Of Covert Communication In Packet Channels, Ramin Soltani

Doctoral Dissertations

This dissertation focuses on covert communication in channels where the communication takes place by the transmission of packets. Consider a channel where authorized transmitter Jack sends packets to authorized receiver Steve according to a Poisson process with rate $\lambda$ packets per second for a time period $T$. Jack's transmitted packet visit Alice, Willie, Bob and Steve, respectively. Suppose that covert transmitter Alice wishes to communicate information to covert receiver Bob without being detected by a watchful adversary Willie. We consider three sets of assumptions for this channel. For each set of assumptions, we present a technique for establishing covert communication …

Cmos Compatible Memristor Networks For Brain-Inspired Computing, Can Li

Doctoral Dissertations

In the past decades, the computing capability has shown an exponential growth trend, which is observed as Moore’s law. However, this growth speed is slowing down in recent years mostly because the down-scaled size of transistors is approaching their physical limit. On the other hand, recent advances in software, especially in big data analysis and artificial intelligence, call for a break-through in computing hardware. The memristor, or the resistive switching device, is believed to be a potential building block of the future generation of integrated circuits. The underlying mechanism of this device is different from that of complementary metal-oxide-semiconductor (CMOS) …

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 disorders …

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 problem, both academia and utilities have …

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) is …

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 …

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 or …

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 …

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 …