Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Robotics (4)
- Hardware Security (3)
- Hardware security (3)
- Machine Learning (3)
- Machine learning (3)
-
- Reinforcement learning (3)
- ASIC (2)
- Algorithms (2)
- Cloud Computing (2)
- Computer Vision (2)
- Computer vision (2)
- Diversity (2)
- Energy efficiency (2)
- FPGA (2)
- Fault Tolerance (2)
- Information Theory (2)
- Internet of Things (2)
- Management (2)
- Memristor (2)
- Neural network (2)
- Obfuscation (2)
- Physically Unclonable Functions (2)
- Reliability (2)
- SRAM (2)
- Security (2)
- Time (2)
- #KRKTR (1)
- 3D Architecture (1)
- 3D Circuits (1)
- 3D IC (1)
Articles 1 - 30 of 71
Full-Text Articles in Engineering
An Efficient Privacy-Preserving Framework For Video Analytics, Tian Zhou
An Efficient Privacy-Preserving Framework For Video Analytics, Tian Zhou
Doctoral Dissertations
With the proliferation of video content from surveillance cameras, social media, and live streaming services, the need for efficient video analytics has grown immensely. In recent years, machine learning based computer vision algorithms have shown great success in various video analytic tasks. Specifically, neural network models have dominated in visual tasks such as image and video classification, object recognition, object detection, and object tracking. However, compared with classic computer vision algorithms, machine learning based methods are usually much more compute-intensive. Powerful servers are required by many state-of-the-art machine learning models. With the development of cloud computing infrastructures, people are able …
Learning To Rig Characters, Zhan Xu
Learning To Rig Characters, Zhan Xu
Doctoral Dissertations
With the emergence of 3D virtual worlds, 3D social media, and massive online games, the need for diverse, high-quality, animation-ready characters and avatars is greater than ever. To animate characters, artists hand-craft articulation structures, such as animation skeletons and part deformers, which require significant amount of manual and laborious interaction with 2D/3D modeling interfaces. This thesis presents deep learning methods that are able to significantly automate the process of character rigging. First, the thesis introduces RigNet, a method capable of predicting an animation skeleton for an input static 3D shape in the form of a polygon mesh. The predicted skeletons …
Design And Analysis Of Content Caching Systems, Anirudh Sabnis
Design And Analysis Of Content Caching Systems, Anirudh Sabnis
Doctoral Dissertations
Caching is a simple yet powerful technique that has had a significant impact on improving the performance of various computer systems. From internet content delivery to CPUs, domain name systems, and database systems, caching has played a pivotal role in making these systems faster and more efficient. The basic idea behind caching is to store frequently accessed data locally, so that future requests for that data can be served more quickly. For example, a Content Delivery Network (CDN) like Akamai deploys thousands of edge caches across the globe, so that end-user requests can be served from a nearby cache, rather …
Enabling Daily Tracking Of Individual’S Cognitive State With Eyewear, Soha Rostaminia
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 …
Data Scarcity In Event Analysis And Abusive Language Detection, Sheikh Muhammad Sarwar
Data Scarcity In Event Analysis And Abusive Language Detection, Sheikh Muhammad Sarwar
Doctoral Dissertations
Lack of data is almost always the cause of the suboptimal performance of neural networks. Even though data scarce scenarios can be simulated for any task by assuming limited access to training data, we study two problem areas where data scarcity is a practical challenge: event analysis and abusive content detection} Journalists, social scientists and political scientists need to retrieve and analyze event mentions in unstructured text to compute useful statistical information to understand society. We claim that it is hard to specify information need about events using keyword-based representation and propose a Query by Example (QBE) setting for event …
Data Parallel Frameworks For Training Machine Learning Models, Guoyi Zhao
Data Parallel Frameworks For Training Machine Learning Models, Guoyi Zhao
Doctoral Dissertations
Machine learning is the study of computer algorithms that focuses on analyzing and interpreting patterns and structures in data. It has been successfully applied to many areas in computer science and achieved state-of-the-art results to enable learning, reasoning, and decision-making without human interactions. This research aims to develop innovated data parallel frameworks to accommodate the computing resources to parallelize different machine learning and deep learning algorithms and speed up the training. To achieve that, we explore three interesting frameworks in this dissertation: (1) Sync-on-the-fly framework for gradient descent algorithms on transient resources; (2) Asynchronous Proactive Data Parallel framework for both …
Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona
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
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, …
Distributed Learning Algorithms: Communication Efficiency And Error Resilience, Raj Kumar Maity
Distributed Learning Algorithms: Communication Efficiency And Error Resilience, Raj Kumar Maity
Doctoral Dissertations
In modern day machine learning applications such as self-driving cars, recommender systems, robotics, genetics etc., the size of the training data has grown to the point that it has become essential to design distributed learning algorithms. A general framework for the distributed learning is \emph{data parallelism} where the data is distributed among the \emph{worker machines} for parallel processing and computation to speed up learning. With billions of devices such as cellphones, computers etc., the data is inherently distributed and stored locally in the users' devices. Learning in this set up is popularly known as \emph{Federated Learning}. The speed-up due to …
Data-Driven Control, Modeling, And Forecasting For Residential Solar Power, Akansha Singh Bansal
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
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
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 …
Cost-Efficient Resource Provisioning For Cloud-Enabled Schedulers, Lurdh Pradeep Reddy Ambati
Cost-Efficient Resource Provisioning For Cloud-Enabled Schedulers, Lurdh Pradeep Reddy Ambati
Doctoral Dissertations
Since the last decade, public cloud platforms are rapidly becoming de-facto computing platform for our society. To support the wide range of users and their diverse applications, public cloud platforms started to offer the same VMs under many purchasing options that differ across their cost, performance, availability, and time commitments. Popular purchasing options include on-demand, reserved, and transient VM types. Reserved VMs require long time commitments, whereas users can acquire and release the on-demand (and transient) VMs at any time. While transient VMs cost significantly less than on-demand VMs, platforms may revoke them at any time. In general, the stronger …
Addressing Security Challenges In Embedded Systems And Multi-Tenant Fpgas, Georgios Provelengios
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 …
Performance Evaluation Of Classical And Quantum Communication Systems, Gayane Vardoyan
Performance Evaluation Of Classical And Quantum Communication Systems, Gayane Vardoyan
Doctoral Dissertations
The Transmission Control Protocol (TCP) is a robust and reliable method used to transport data across a network. Many variants of TCP exist, e.g., Scalable TCP, CUBIC, and H-TCP. While some of them have been studied from empirical and theoretical perspectives, others have been less amenable to a thorough mathematical analysis. Moreover, some of the more popular variants had not been analyzed in the context of the high-speed environments for which they were designed. To address this issue, we develop a generalized modeling technique for TCP congestion control under the assumption of high bandwidth-delay product. In a separate contribution, we …
Design And Implementation Of Path Finding And Verification In The Internet, Hao Cai
Design And Implementation Of Path Finding And Verification In The Internet, Hao Cai
Doctoral Dissertations
In the Internet, network traffic between endpoints typically follows one path that is determined by the control plane. Endpoints have little control over the choice of which path their network traffic takes and little ability to verify if the traffic indeed follows a specific path. With the emergence of software-defined networking (SDN), more control over connections can be exercised, and thus the opportunity for novel solutions exists. However, there remain concerns about the attack surface exposed by fine-grained control, which may allow attackers to inject and redirect traffic. To address these opportunities and concerns, we consider two specific challenges: (1) …
Improving Computer Network Operations Through Automated Interpretation Of State, Abhishek Dwaraki
Improving Computer Network Operations Through Automated Interpretation Of State, Abhishek Dwaraki
Doctoral Dissertations
Networked systems today are hyper-scaled entities that provide core functionality for distributed services and applications spanning personal, business, and government use. It is critical to maintain correct operation of these networks to avoid adverse business outcomes. The advent of programmable networks has provided much needed fine-grained network control, enabling providers and operators alike to build some innovative networking architectures and solutions. At the same time, they have given rise to new challenges in network management. These architectures, coupled with a multitude of devices, protocols, virtual overlays on top of physical data-plane etc. make network management a highly challenging task. Existing …
Formal Verification Of Divider And Square-Root Arithmetic Circuits Using Computer Algebra Methods, Atif Yasin
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 …
Towards Optimized Traffic Provisioning And Adaptive Cache Management For Content Delivery, Aditya Sundarrajan
Towards Optimized Traffic Provisioning And Adaptive Cache Management For Content Delivery, Aditya Sundarrajan
Doctoral Dissertations
Content delivery networks (CDNs) deploy hundreds of thousands of servers around the world to cache and serve trillions of user requests every day for a diverse set of content such as web pages, videos, software downloads and images. In this dissertation, we propose algorithms to provision traffic across cache servers and manage the content they host to achieve performance objectives such as maximizing the cache hit rate, minimizing the bandwidth cost of the network and minimizing the energy consumption of the servers. Traffic provisioning is the process of determining the set of content domains hosted on the servers. We propose …
Trustworthy Systems And Protocols For The Internet Of Things, Arman Pouraghily
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
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 …
Qoe-Aware Content Distribution Systems For Adaptive Bitrate Video Streaming, Divyashri Bhat
Qoe-Aware Content Distribution Systems For Adaptive Bitrate Video Streaming, Divyashri Bhat
Doctoral Dissertations
A prodigious increase in video streaming content along with a simultaneous rise in end system capabilities has led to the proliferation of adaptive bit rate video streaming users in the Internet. Today, video streaming services range from Video-on-Demand services like traditional IP TV to more recent technologies such as immersive 3D experiences for live sports events. In order to meet the demands of these services, the multimedia and networking research community continues to strive toward efficiently delivering high quality content across the Internet while also trying to minimize content storage and delivery costs. The introduction of flexible and adaptable technologies …
A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh
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 …
Service Competition And Data-Centric Protocols For Internet Access, Thiago Teixeira
Service Competition And Data-Centric Protocols For Internet Access, Thiago Teixeira
Doctoral Dissertations
The Internet evolved in many aspects, from the application to the physical layers. However, the evolution of the Internet access technologies, most visible in dense urban scenarios, is not easily noticeable in sparsely populated and rural areas. In the United States, for example, the FCC identified that 50% of the census blocks have access to up to two broadband providers; however, these providers do not necessarily compete. Additionally, due to the methodology of the study, there is evidence that the number of actual customers without broadband access is higher since the FCC considers the entire block to have broadband if …
Time-Difference Circuits: Methodology, Design, And Digital Realization, Shuo Li
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: …
Stealthy Parametric Hardware Trojans In Vlsi Circuits, Samaneh Ghandali
Stealthy Parametric Hardware Trojans In Vlsi Circuits, Samaneh Ghandali
Doctoral Dissertations
Over the last decade, hardware Trojans have gained increasing attention in academia, industry and by government agencies. In order to design reliable countermeasures, it is crucial to understand how hardware Trojans can be built in practice. This is an area that has received relatively scant treatment in the literature. In this thesis, we examine how particularly stealthy parametric Trojans can be introduced to VLSI circuits. Parametric Trojans do not require any additional logic and are purely based on subtle manipulations on the sub-transistor level to modify the parameters of few transistors which makes them very hard to detect. We introduce …
Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh
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
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 …
Improving And Understanding Data Quality In Large-Scale Data Systems, Xiaolan Wang
Improving And Understanding Data Quality In Large-Scale Data Systems, Xiaolan Wang
Doctoral Dissertations
Systems and applications rely heavily on data, which makes data quality a critical factor for their function. In turn, low quality data can be incredibly costly and disruptive, leading to loss of revenue, incorrect conclusions, and misguided policy decisions. Improving data quality is far more than purging datasets of errors; it is more important to improve the processes that produce the data, to collect good data sources that are used for generating the data, and to truly understand the quality of the data. Therefore, the objective of this thesis is to improve and understand data quality from the above aspects. …
Modeling Temporal Structures In Time-Varying Networks, Kun Tu
Modeling Temporal Structures In Time-Varying Networks, Kun Tu
Doctoral Dissertations
A dynamic network is a network whose structure changes because of the emergence and disappearance of node or edges. It can be used to study complex systems where individuals in a system are represented as nodes and their relations/interactions are represented as edges. Studying dynamic network structures helps to better understand changes in relationships. Considerable work has been conducted on learning network structure. However, due to the complexity of dynamic networks, there is considerable room for improvement to obtain better analysis results. This thesis studies different aspects of characteristic and dynamics of a network, focusing on their application in link …