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Full-Text Articles in Engineering

A Graph-Based Approach To Symbolic Functional Decomposition Of Finite State Machines, Piotr Szotkowski, Mariusz Rawski, Henry Selvaraj Jun 2009

A Graph-Based Approach To Symbolic Functional Decomposition Of Finite State Machines, Piotr Szotkowski, Mariusz Rawski, Henry Selvaraj

Electrical & Computer Engineering Faculty Research

This paper discusses the symbolic functional decomposition method for implementing finite state machines in field-programmable gate array devices. This method is a viable alternative to the presently widespread two-step approaches to the problem, which consist of separate encoding and mapping stages; the proposed method does not have a separate decomposition step instead, the state's final encoding is introduced gradually on every decomposition iteration. Along with general description of the functional symbolic decomposition method's steps, the paper discusses various algorithms implementing the method and presents an example realisation of the most interesting algorithm. In the end, the paper compares the results …


Automated Identification Of Tumor Microscopic Morphology Based On Macroscopically Measured Scatter Signatures, Pilar Beatriz Garcia-Allende, Venkataramanan Krishnaswamy, P Jack Hoopes, Kimberley S. Samkoe, Olga M. Conde, Brian W. Pogue May 2009

Automated Identification Of Tumor Microscopic Morphology Based On Macroscopically Measured Scatter Signatures, Pilar Beatriz Garcia-Allende, Venkataramanan Krishnaswamy, P Jack Hoopes, Kimberley S. Samkoe, Olga M. Conde, Brian W. Pogue

Dartmouth Scholarship

An automated algorithm and methodology is presented to identify tumor-tissue morphologies based on broadband scatter data measured by raster scan imaging of the samples. A quasi-confocal reflectance imaging system was used to directly measure the tissue scatter reflectance in situ, and the spectrum was used to identify the scattering power, amplitude, and total wavelength-integrated intensity. Pancreatic tumor and normal samples were characterized using the instrument, and subtle changes in the scatter signal were encountered within regions of each sample. Discrimination between normal versus tumor tissue was readily performed using a K-nearest neighbor classifier algorithm. A similar approach worked …


A Fully Automated Non-External Marker 4d-Ct Sorting Algorithm Using A Serial Cine Scanning Protocol, Greg Carnes, Stewart Gaede, Edward Yu, Jake Van Dyk, Jerry Battista, Ting-Yim Lee Apr 2009

A Fully Automated Non-External Marker 4d-Ct Sorting Algorithm Using A Serial Cine Scanning Protocol, Greg Carnes, Stewart Gaede, Edward Yu, Jake Van Dyk, Jerry Battista, Ting-Yim Lee

Edward Yu

Current 4D-CT methods require external marker data to retrospectively sort image data and generate CT volumes. In this work we develop an automated 4D-CT sorting algorithm that performs without the aid of data collected from an external respiratory surrogate. The sorting algorithm requires an overlapping cine scan protocol. The overlapping protocol provides a spatial link between couch positions. Beginning with a starting scan position, images from the adjacent scan position (which spatial match the starting scan position) are selected by maximizing the normalized cross correlation (NCC) of the images at the overlapping slice position. The process was continued by 'daisy …


Proactive Service Migration For Long-Running Byzantine Fault-Tolerant Systems, Wenbing Zhao, H. Zhang Apr 2009

Proactive Service Migration For Long-Running Byzantine Fault-Tolerant Systems, Wenbing Zhao, H. Zhang

Electrical and Computer Engineering Faculty Publications

A proactive recovery scheme based on service migration for long-running Byzantine fault-tolerant systems is described. Proactive recovery is an essential method for ensuring the long-term reliability of fault-tolerant systems that are under continuous threats from malicious adversaries. The primary benefit of our proactive recovery scheme is a reduced vulnerability window under normal operation. This is achieved in two ways. First, the time-consuming reboot step is removed from the critical path of proactive recovery. Second, the response time and the service migration latency are continuously profiled and an optimal service migration interval is dynamically determined during runtime based on the observed …


Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James Mar 2009

Blind Deconvolution Through Polarization Diversity Of Long Exposure Imagery, Steven P. James

Theses and Dissertations

The purpose of the algorithm developed in this thesis was to create a post processing method that could resolve objects at low signal levels using polarization diversity and no knowledge of the atmospheric seeing conditions. The process uses a two-channel system, one unpolarized image and one linearly polarized image, in a GEM algorithm to reconstruct the object. Previous work done by Strong showed that a two-channel system using polarization diversity on short exposure imagery could produce images up to twice the diffraction limit. In this research, long exposure images were simulated and a simple Kolmogorov model used. This allowed for …


Alliances In Graphs: Parameterized Algorithms And On Partitioning Series-Parallel Graphs, Rosa Enciso Jan 2009

Alliances In Graphs: Parameterized Algorithms And On Partitioning Series-Parallel Graphs, Rosa Enciso

Electronic Theses and Dissertations

Alliances are used to denote agreements between members of a group with similar interests. Alliances can occur between nations, biological sequences, business cartels, and other entities. The notion of alliances in graphs was first introduced by Kristiansen, Hedetniemi, and Hedetniemi in . A defensive alliance in a graph G = (V, E) is a non empty set S ⊆ V where, for all x ∈ S, |N[x] ∩ S| ≥ |N[x] − S|. Consequently, every vertex that is a member of a defensive alliance has at least as many vertices defending it as there are vertices attacking it. Alliances can …


Object Detection And Texture Classification With Applications To The Diagnosis Of Skin Cancer, Jonathan Blackledge, D. A. Dubovitskiy Jan 2009

Object Detection And Texture Classification With Applications To The Diagnosis Of Skin Cancer, Jonathan Blackledge, D. A. Dubovitskiy

Books/Book chapters

We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include fractal parameters such as the Lacunarity and Fractal Dimension. The principal issues associated with object recognition are presented and a self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory considered. The methods discussed, and the ‘system’ developed, have a range of applications in ‘machine vision’ and in this publication, we focus on the development and implementation of a skin cancer screening system that can …