Computer Engineering Commons^™

Self-Organizing Microstructures Orientation Control In Femtosecond Laser Patterning On Silicon Surface, Pengjun Liu, Lan Jiang, Jie Hu, Shuai Zhang, Yongfeng Lu

Department of Electrical and Computer Engineering: Faculty Publications

Self-organizing rippled microstructures are induced on silicon surface by linearly polarized femtosecond laser pulses. At a near threshold fluence, it is observed that ripple orientation is co-determined by the laser polarization direction and laser scanning parameters (scanning direction and scanning speed) in surface patterning process. Under fixed laser polarization, the ripple orientation can be controlled to rotate by about 40° through changing laser scanning parameters. In addition, it is also observed that the ripple morphology is sensitive to the laser scanning direction, and it is an optimal choice to obtain ordered ripple structures when the angle between laser scanning and …

Oswald Physical And Engineering Sciences Honorable Mention: Summer 2012 Lip6 Write Up, Josiah Hanna

Kaleidoscope

Planning under uncertainty is a central problem in developing intelligent autonomous systems. The traditional representation for these problems is a Markov Decision Process (MDP). The MDP model can be extended to a Multi-criteria MDP (MMDP) for planning under uncertainty while trying to optimize multiple criteria. However, due to the trade-offs involved in multi criteria problems there may be infinitely many optimal solutions. The focus of this project has been to find a method that efficiently computes a subset of solutions that represents the entire set of optimal solutions for bi-objective MDPs.

Human Brain Networks: Spiking Neuron Models, Multistability, Synchronization, Thermodynamics, Maximum Entropy Production, And Anesthetic Cascade Mechanisms, Wassim H. Haddad, Qing Hui, James M. Bailey

Department of Electrical and Computer Engineering: Faculty Publications

Advances in neuroscience have been closely linked to mathematical modeling beginning with the integrate-and-fire model of Lapicque and proceeding through the modeling of the action potential by Hodgkin and Huxley to the current era. The fundamental building block of the central nervous system, the neuron, may be thought of as a dynamic element that is “excitable”, and can generate a pulse or spike whenever the electrochemical potential across the cell membrane of the neuron exceeds a threshold. A key application of nonlinear dynamical systems theory to the neurosciences is to study phenomena of the central nervous system that exhibit nearly …

Simulation Of Light Propagation In Skin And Subcutaneous Blood Vessels, Robert Polski, Ricardo Huancaya, Hyun J. Kwon

Posters, Presentations, and Papers

The VeinViewer, produced by the Luminetx Corporation, projects an image of subcutaneous veins onto the surface of the skin by using the discovery that near infrared (NIR) light passes through and transmits back out of the skin issue except at the blood vessels as a result of the presence of hemoglobin¹. We aim to improve the function of the VeinViewer by using computational models to interpret changes in properties of the subject,such as skin pigmentation, and settings on the device, such as light frequency. We also look to decrease error, as a result of the geometry of veins …

Ultimate Codes: Near-Optimal Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Chong Wang, Ke Zhou, Yuhong Zhao

CSE Technical Reports

As modern storage systems have grown in size and complexity, RAID-6 is poised to replace RAID-5 as the dominant form of RAID architectures due to its ability to protect against double disk failures. Many excellent erasure codes specially designed for RAID-6 have emerged in recent years. However, all of them have limitations. In this paper, we present a class of near perfect erasure codes for RAID-6, called the Ultimate codes. These codes encode, update and decode either optimally or nearly optimally, regardless of what the code length is. This implies that utilizing these codes we can build highly efficient and …

S-Code: Lowest Density Mds Array Codes For Raid-6, Zhijie Huang, Hong Jiang, Ke Zhou, Yuhong Zhao, Chong Wang

CSE Technical Reports

RAID, a storage architecture designed to exploit I/O parallelism and provide data reliability, has been deployed widely in computing systems as a storage building block. In large scale storage systems, in particular, RAID-6 is gradually replacing RAID-5 as the dominant form of disk arrays due to its capability of tolerating concurrent failures of any two disks. MDS (maximum distance separable) array codes are the most popular erasure codes that can be used for implementing RAID-6, since they enable optimal storage efficiency and efficient encoding and decoding algorithms. In this paper, we propose a new class of MDS array codes called …

An Examination Of The Factors Determining Successful Implementation Of An Electronic Medical Record (Emr) System In A Regional Hospital, Mehrdad Motamed

Morehead State Theses and Dissertations

A Thesis Presented to the Faculty of the College of Business and Public Affairs Morehead State University in Partial Fulfillment of the Requirements for the Degree Master of Science by Mehrdad Motamed in July of 2014.

Stochastic Analysis Of Cascading-Failure Dynamics In Power Grids, Mahshid Rahnamay-Naeini, Zhuoyao Wang, Nasir Ghani, Andrea Mammoli, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

A scalable and analytically tractable probabilistic model for the cascading failure dynamics in power grids is constructed while retaining key physical attributes and operating characteristics of the power grid. The approach is based upon extracting a reduced abstraction of large-scale power grids using a small number of aggregate state variables while modeling the system dynamics using a continuous-time Markov chain. The aggregate state variables represent critical power-grid attributes, which have been shown, from prior simulation-based and historical-data-based analysis, to strongly influence the cascading behavior. The transition rates among states are formulated in terms of certain parameters that capture grid's operating …

Getting It Right The First Time: Verification Of Behavior-Based Multirobot Missions, Damian M. Lyons, Ronald C. Arkin, Shu Jiang, Dagon Harrington, Matthew O'Brien

Faculty Publications

No abstract provided.

Leveraging Area Bounds Information For Autonomous Multi-Robot Exploration, Tsung-Ming Liu, Damian M. Lyons

Faculty Publications

In this paper we propose an approach, the Space-Based Potential Field (SBPF) approach, to controlling multiple robots for area exploration missions that focus on robot dispersion. The SBPF method is based on a potential field approach that leverages knowledge of the overall bounds of the area to be explored. This additional information allows a simpler potential field control strategy for all robots but which nonetheless has good dispersion and overlap performance in all the multi-robot scenarios while avoiding potential minima. Both simulation and robot experimental results are presented as evidence.

Increased Climate Variability Is More Visible Than Global Warming: A General System-Theory Explanation, Octavio Lerma, Craig Tweedie, Vladik Kreinovich

Departmental Technical Reports (CS)

While global warming is a statistically confirmed long-term phenomenon, its most visible consequence is not the warming itself but, somewhat surprisingly, the increased climate variability. In this paper, we use the general system theory ideas to explain why increased climate variability is more visible than the global warming itself.

How To Estimate Forecasting Quality: A System-Motivated Derivation Of Symmetric Mean Absolute Percentage Error (Smape) And Other Similar Characteristics, Vladik Kreinovich, Hung T. Nguyen, Rujira Ouncharoen

Departmental Technical Reports (CS)

When comparing how well different algorithms forecast time series, researchers use an average value of the ratio |x-y|/(|x|+|y|)/2), known as the Symmetric Mean Absolute Percentage Error (SMAPE). In this paper, we provide a system-motivated explanation for this formula. We also explain how this formula explains the use of geometric mean to combine different forecasts.

Querie: Collaborative Database Exploration, Magdalini Eirinaki, Suju Abraham, Neoklis Polyzotis, Naushin Shaikh

Faculty Publications

No abstract provided.

Forensicloud: An Architecture For Digital Forensic Analysis In The Cloud, Cody Miller, Dae Glendowne, David Dampier, Kendall Blaylock

Computer Sciences and Electrical Engineering Faculty Research

The amount of data that must be processed in current digital forensic examinations continues to rise. Both the volume and diversity of data are obstacles to the timely completion of forensic investigations. Additionally, some law enforcement agencies do not have the resources to handle cases of even moderate size. To address these issues we have developed an architecture for a cloud-based distributed processing platform we have named Forensicloud. This architecture is designed to reduce the time taken to process digital evidence by leveraging the power of a high performance computing platform and by adapting existing tools to operate within this …

Nonlocal And Quantum-Tunneling Contributions To Harmonic Generation In Nanostructures: Electron-Cloud-Screening Effects, Michael Scalora, Maria Antonietta Vincenti, Domenico De Ceglia, Joseph W. Haus

Electrical and Computer Engineering Faculty Publications

Our theoretical examination of second- and third-harmonic generation from metal-based nanostructures predicts that nonlocal and quantum-tunneling phenomena can significantly exceed expectations based solely on local, classical electromagnetism. Mindful that the diameter of typical transition-metal atoms is approximately 3 Å, we adopt a theoretical model that treats nanometer-size features and/or subnanometer-size gaps or spacers by taking into account (i) the limits imposed by atomic size to fulfill the requirements of continuum electrodynamics, (ii) spillage of the nearly free electron cloud into the surrounding vacuum, and (iii) the increased probability of quantum tunneling as objects are placed in close proximity.

Our approach …

Design Of Robust Spin-Transfer Torque Magnetic Random Access Memories For Ultralow Power High Performance On-Chip Cache Applications, Xuanyao Fong

Open Access Dissertations

Spin-transfer torque magnetic random access memories (STT-MRAMs) based on magnetic tunnel junction (MTJ) has become the leading candidate for future universal memory technology due to its potential for low power, non-volatile, high speed and extremely good endurance. However, conflicting read and write requirements exist in STT-MRAM technology because the current path during read and write operations are the same. Read and write failures of STT-MRAMs are degraded further under process variations. The focus of this dissertation is to optimize the yield of STT- MRAMs under process variations by employing device-circuit-architecture co-design techniques. A devices-to-systems simulation framework was developed to evaluate …

Paxos Based Directory Updates For Geo-Replicated Cloud Storage, Srivathsava Rangarajan

Open Access Theses

Modern cloud data stores (e.g., Spanner, Cassandra) replicate data across geographically distributed data centers for availability, redundancy and optimized latencies.^ An important class of cloud data stores involves the use of directories to track the location of individual data objects. Directory-based datastores allow flexible data placement, and the ability to adapt placement in response to changing workload dynamics. However, a key challenge is maintaining and updating the directory state when replica placement changes.^ In this thesis, we present the design and implementation of a system to address the problem of correctly updating these directories. Our system is built around JPaxos, …

Nn-X - A Hardware Accelerator For Convolutional Neural Networks, Vinayak A. Gokhale

Open Access Theses

Convolutional neural networks (ConvNets) are hierarchical models of the mammalian visual cortex. These models have been increasingly used in computer vision to perform object recognition and full scene understanding. ConvNets consist of multiple layers that contain groups of artificial neurons, which are mathematical approximations of biological neurons. A ConvNet can consist of millions of neurons and require billions of computations to produce one output. ^ Currently, giant server farms are used to process information in real time. These supercomputers require a large amount of power and a constant link to the end-user. Low powered embedded systems are not able to …

Developing Digital Media Platforms For Early Design, Sriram Karthik Badam

Open Access Theses

In recent times, mobile devices are becoming an integral part of our daily life. Software applications on these handheld devices are successfully migrating the traditional paper-based activities such as reading news, books, and even navigating through maps, onto the digital medium. While these applications allow information access anywhere and anytime, there is still a necessity for repurposing these digital media to support content/information creation especially in domains such as industrial design where paper-based activities are common. To utilize direct-touch tablets for collaborative conceptual design, we studied their affordances and iteratively developed a web-based wiki system, named skWiki. In this thesis, …

Getting It Right The First Time: Verification Of Autonomous Behavior-Based Multirobot Missions, Ronald C. Arkin, Damian M. Lyons

Faculty Publications

No abstract provided.