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Full-Text Articles in Engineering

Accelerating Iterative Computations For Large-Scale Data Processing, Jiangtao Yin Nov 2016

Accelerating Iterative Computations For Large-Scale Data Processing, Jiangtao Yin

Doctoral Dissertations

Recent advances in sensing, storage, and networking technologies are creating massive amounts of data at an unprecedented scale and pace. Large-scale data processing is commonly leveraged to make sense of these data, which will enable companies, governments, and organizations, to make better decisions and bring convenience to our daily life. However, the massive amount of data involved makes it challenging to perform data processing in a timely manner. On the one hand, huge volumes of data might not even fit into the disk of a single machine. On the other hand, data mining and machine learning algorithms, which are usually …


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


Multi-Classifier Fusion Strategy For Activity And Intent Recognition Of Torso Movements, Abhijit Kadrolkar Nov 2016

Multi-Classifier Fusion Strategy For Activity And Intent Recognition Of Torso Movements, Abhijit Kadrolkar

Doctoral Dissertations

As assistive, wearable robotic devices are being developed to physically assist their users, it has become crucial to develop safe, reliable methods to coordinate the device with the intentions and motions of the wearer. This dissertation investigates the recognition of user intent during flexion and extension of the human torso in the sagittal plane to be used for control of an assistive exoskeleton for the human torso. A multi-sensor intent recognition approach is developed that combines information from surface electromyogram (sEMG) signals from the user’s muscles and inertial sensors mounted on the user’s body. Intent recognition is implemented by following …


Variation Aware Placement For Efficient Key Generation Using Physically Unclonable Functions In Reconfigurable Systems, Shrikant S. Vyas Nov 2016

Variation Aware Placement For Efficient Key Generation Using Physically Unclonable Functions In Reconfigurable Systems, Shrikant S. Vyas

Masters Theses

With the importance of data security at its peak today, many reconfigurable systems are used to provide security. This protection is often provided by FPGA-based encrypt/decrypt cores secured with secret keys. Physical unclonable functions (PUFs) use random manufacturing variations to generate outputs that can be used in keys. These outputs are specific to a chip and can be used to create device-tied secret keys. Due to reliability issues with PUFs, key generation with PUFs typically requires error correction techniques. This can result in substantial hardware costs. Thus, the total cost of a $n$-bit key far exceeds just the cost of …


Intent Recognition Of Rotation Versus Translation Movements In Human-Robot Collaborative Manipulation Tasks, Vinh Q. Nguyen Nov 2016

Intent Recognition Of Rotation Versus Translation Movements In Human-Robot Collaborative Manipulation Tasks, Vinh Q. Nguyen

Masters Theses

The goal of this thesis is to enable a robot to actively collaborate with a person to move an object in an efficient, smooth and robust manner. For a robot to actively assist a person it is key that the robot recognizes the actions or phases of a collaborative tasks. This requires the robot to have the ability to estimate a person’s movement intent. A hurdle in collaboratively moving an object is determining whether the partner is trying to rotate or translate the object (the rotation versus translation problem). In this thesis, Hidden Markov Models (HMM) are used to recognize …


Infrastructure-Free Secure Pairing Of Mobile Devices, Chunqiu Liu Nov 2016

Infrastructure-Free Secure Pairing Of Mobile Devices, Chunqiu Liu

Masters Theses

Mobile devices have advanced tremendously during the last ten years and have changed our daily life in various ways. Secure pairing of mobile devices has become a significant issue considering the huge quantity of active mobile device connections and mobile traffic. However, current commonly used file sharing mobile applications rely on servers completely that are always targeted by attackers. In this thesis work, an innovative mechanism is proposed to generate symmetric keys on both mobile devices independently from a shared movement in arbitrary pattern, which means no server needs to be involved and no data exchange needed. A secret wireless-communication …


Protecting Controllers Against Denial-Of-Service Attacks In Software-Defined Networks, Jingrui Li Nov 2016

Protecting Controllers Against Denial-Of-Service Attacks In Software-Defined Networks, Jingrui Li

Masters Theses

Connection setup in software-defined networks (SDN) requires considerable amounts of processing, communication, and memory resources. Attackers can target SDN controllers defense mechanism based on a proof-of-work protocol. This thesis proposes a new protocol to protect controllers against such attacks, shows implementation of the system and analyze the its performance. The key characteristics of this protocol, namely its one-way operation, its requirement for freshness in proofs of work, its adjustable difficulty, its ability to work withmultiple network providers, and its use of existing TCP/IP header fields, ensure that this approach can be used in practice.


Spotlight: An Information Service For The Cloud, Xue Ouyang Jul 2016

Spotlight: An Information Service For The Cloud, Xue Ouyang

Masters Theses

Infrastructure-as-a-Service cloud platforms are incredibly complex: they rent hundreds of different types of servers across multiple geographical regions under a wide range of contract types that offer varying tradeoffs between risk and cost. Unfortunately, the internal dynamics of cloud platforms are opaque in several dimensions. For example, while the risk of servers not being available when requested is critical in optimizing these risk-cost tradeoffs, it is not typically made visible to users. Thus, inspired by prior work on Internet bandwidth probing, we propose actively probing cloud platforms to explicitly learn such information, where each "probe'' is a request for a …


A Haptic Surface Robot Interface For Large-Format Touchscreen Displays, Mark Price Jul 2016

A Haptic Surface Robot Interface For Large-Format Touchscreen Displays, Mark Price

Masters Theses

This thesis presents the design for a novel haptic interface for large-format touchscreens. Techniques such as electrovibration, ultrasonic vibration, and external braked devices have been developed by other researchers to deliver haptic feedback to touchscreen users. However, these methods do not address the need for spatial constraints that only restrict user motion in the direction of the constraint. This technology gap contributes to the lack of haptic technology available for touchscreen-based upper-limb rehabilitation, despite the prevalent use of haptics in other forms of robotic rehabilitation. The goal of this thesis is to display kinesthetic haptic constraints to the touchscreen user …


Accelerated Iterative Algorithms With Asynchronous Accumulative Updates On A Heterogeneous Cluster, Sandesh Gubbi Virupaksha Mar 2016

Accelerated Iterative Algorithms With Asynchronous Accumulative Updates On A Heterogeneous Cluster, Sandesh Gubbi Virupaksha

Masters Theses

In recent years with the exponential growth in web-based applications the amount of data generated has increased tremendously. Quick and accurate analysis of this 'big data' is indispensable to make better business decisions and reduce operational cost. The challenges faced by modern day data centers to process big data are multi fold: to keep up the pace of processing with increased data volume and increased data velocity, deal with system scalability and reduce energy costs. Today's data centers employ a variety of distributed computing frameworks running on a cluster of commodity hardware which include general purpose processors to process big …


Processor Temperature And Reliability Estimation Using Activity Counters, Mayank Chhablani Mar 2016

Processor Temperature And Reliability Estimation Using Activity Counters, Mayank Chhablani

Masters Theses

With the advent of technology scaling lifetime reliability is an emerging threat in high-performance and deadline-critical systems. High on-chip thermal gradients accelerates localised thermal elevations (hotspots) which increases the aging rate of the semiconductor devices. As a result, reliable operation of the processors has become a challenging task. Therefore, cost effective schemes for estimating temperature and reliability are crucial. In this work we present a reliability estimation scheme that is based on a light-weight temperature estimation technique that monitors hardware events. Unlike previously pro- posed hardware counter-based approaches, our approach involves a linear-temporal-feedback estimator, taking into account the effects of …


Intrinsically Motivated Exploration In Hierarchical Reinforcement Learning, Christopher M. Vigorito Mar 2016

Intrinsically Motivated Exploration In Hierarchical Reinforcement Learning, Christopher M. Vigorito

Doctoral Dissertations

The acquisition of hierarchies of reusable skills is one of the distinguishing characteristics of human intelligence, and the learning of such hierarchies is an important open problem in computational reinforcement learning (RL). In humans, these skills are learned during a substantial developmental period in which individuals are intrinsically motivated to explore their environment and learn about the effects of their actions. The skills learned during this period of exploration are then reused to great effect later in life to solve many unfamiliar problems very quickly. This thesis presents novel methods for achieving such developmental acquisition of skill hierarchies in artificial …