Computer Sciences Commons^™

Exploration Of Computational Methods For Classification Of Movement Intention During Human Voluntary Movement From Single Trial Eeg, Ou Bai, Peter Lin, Sherry Vorbach, Jiang Li, Steve Furlani, Mark Hallett

Electrical & Computer Engineering Faculty Publications

Objective: To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG).

Methods: Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis …

Extraction Of Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

In information retrieval, retrieving relevant passages, as opposed to whole documents, not only directly benefits the end user by filtering out the irrelevant information within a long relevant document, but also improves retrieval accuracy in general. A critical problem in passage retrieval is to extract coherent relevant passages accurately from a document, which we refer to as passage extraction. While much work has been done on passage retrieval, the passage extraction problem has not been seriously studied. Most existing work tends to rely on presegmenting documents into fixed-length passages which are unlikely optimal because the length of a relevant passage …

Apparatus And Method For Using Adaptive Algorithms To Exploit Sparsity In Target Weight Vectors In An Adaptive Channel Equalizer, Richard K. Martin, Robert C. Williamson, William A. Sethares

AFIT Patents

An apparatus and method is disclosed for using adaptive algorithms to exploit sparsity in target weight vectors in an adaptive channel equalizer. An adaptive algorithm comprises a selected value of a prior and a selected value of a cost function. The present invention comprises algorithms adapted for calculating adaptive equalizer coefficients for sparse transmission channels. The present invention provides sparse algorithms in the form of a Sparse Least Mean Squares (LMS) algorithm and a Sparse Constant Modulus Algorithm (CMA) and a Sparse Decision Directed (DD) algorithm.

Engineering A Suburban Ad-Hoc Network, Mike Tyson, Ronald D. Pose, Carlo Kopp, Mohammad Rokonuzzaman, Muhammad Mahmudul Islam

Australian Information Warfare and Security Conference

Networks are growing in popularity, as wireless communication hardware, both fixed and mobile, becomes more common and affordable. The Monash Suburban Ad-Hoc Network (SAHN) project has devised a system that provides a highly secure and survivable ad-hoc network, capable of delivering broadband speeds to co-operating users within a fixed environment, such as a residential neighbourhood, or a campus. The SAHN can be used by residents within a community to exchange information, to share access to the Internet, providing last-mile access, or for local telephony and video conferencing. SAHN nodes are designed to be self-configuring and selfmanaging, relying on no experienced …

Type Ii Quantum Computing Algorithm For Computational Fluid Dynamics, James A. Scoville

Theses and Dissertations

An algorithm is presented to simulate fluid dynamics on a three qubit type II quantum computer: a lattice of small quantum computers that communicate classical information. The algorithm presented is called a three qubit factorized quantum lattice gas algorithm. It is modeled after classical lattice gas algorithms which move virtual particles along an imaginary lattice and change the particles’ momentums using collision rules when they meet at a lattice node. Instead of moving particles, the quantum algorithm presented here moves probabilities, which interact via a unitary collision operator. Probabilities are determined using ensemble measurement and are moved with classical communications …

Multiframe Shift Estimation, Stephen A. Bruckart

Theses and Dissertations

The purpose of this research was to develop a fundamental framework for a new approach to multiframe translational shift estimation in image processing. This thesis sought to create a new multiframe shift estimator, to theoretically prove and experimentally test key properties of it, and to quantify its performance according to several metrics. The new estimator was modeled successfully and was proven to be an unbiased estimator under certain common image noise conditions. Furthermore its performance was shown to be superior to the cross correlation shift estimator, a robust estimator widely used in similar image processing cases, according to several criteria. …

An Estimation Theory Approach To Detection And Ranging Of Obscured Targets In 3-D Ladar Data, Charles R. Burris

Theses and Dissertations

The purpose of this research is to develop an algorithm to detect obscured images in 3-D LADAR data. The real data used for this research was gathered using a FLASH LADAR system under development at AFRL/SNJM. The system transmits light with a wavelength of 1.55 micrometers and produces 20 128 X 128 temporally resolved images from the return pulse separated by less than 2 nanoseconds in time. New algorithms for estimating the range to a target in 3-D FLASH LADAR data were developed. Results from processing real data are presented and compared to the traditional correlation receiver for extracting ranges …

A Monocular Vision Based Approach To Flocking, Brian Kirchner

Theses and Dissertations

Flocking is seen in nature as a means for self protection, more efficient foraging, and other search behaviors. Although much research has been done regarding the application of this principle to autonomous vehicles, the majority of the research has relied on GPS information, broadcast communication, an omniscient central controller, or some other form of "global" knowledge. This approach, while effective, has serious drawbacks, especially regarding stealth, reliability, and biological grounding. This research effort uses three Pioneer P2-AT8 robots to achieve flocking behavior without the use of global knowledge. The sensory inputs are limited to two cameras, offset such that the …

Toward The Static Detection Of Deadlock In Java Software, Jose E. Fadul

Theses and Dissertations

Concurrency is the source of many real-world software reliability and security problems. Concurrency defects are difficult to detect because they defy conventional software testing techniques due to their non-local and non-deterministic nature. We focus on one important aspect of this problem: static detection of the possibility of deadlock - a situation in which two or more processes are prevented from continuing while each waits for resources to be freed by the continuation of the other. This thesis proposes a flow-insensitive interprocedural static analysis that detects the possibility that a program can deadlock at runtime. Our analysis proceeds in two steps. …

Crosscutting Score: An Indicator Metric For Aspect Orientation, Subhajit Datta

Research Collection School Of Computing and Information Systems

Aspect Oriented Programming (AOP) provides powerful techniques for modeling and implementing enterprise software systems. To leverage its full potential, AOP needs to be perceived in the context of existing methodologies such as Object Oriented Programming (OOP). This paper addresses an important question for AOP practitioners - how to decide whether a component is best modeled as a class or an aspect? Towards that end, we present an indicator metric, the Crosscutting Score and a method for its calculation and interpretation. We will illustrate our approach through a sample calculation.

Unsymmetrical And Symmetrical Sparse Iterative Algorithm With Multiple Right-Hand-Sides Strategies, D. T. Nguyen, A. P. Honrao, G. Hou, O. Akan, O. Baysal

Civil & Environmental Engineering Faculty Publications

Unified unsymmetrical and symmetrical iterative solvers for handling multiple right-hand-side vectors are examined in this work. Efficient computer implementation strategies (to reduce computational time and in-core memory requirements) are proposed. In-core, out-of-core, linear, multiple right hand side (RHS) vectors, non-linear, symmetrical, and unsymmetrical capabilities of the developed software are demonstrated by solving variety of problems selected form different engineering disciplines. Results indicate that the developed algorithm and software is reliable and efficient.

Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …

Boosted Decision Trees For Word Recognition In Handwritten Document Retrieval, Nicholas Howe, Toni M. Rath, R. Manmatha

Computer Science: Faculty Publications

Recognition and retrieval of historical handwritten material is an unsolved problem. We propose a novel approach to recognizing and retrieving handwritten manuscripts, based upon word image classification as a key step. Decision trees with normalized pixels as features form the basis of a highly accurate AdaBoost classifier, trained on a corpus of word images that have been resized and sampled at a pyramid of resolutions. To stem problems from the highly skewed distribution of class frequencies, word classes with very few training samples are augmented with stochastically altered versions of the originals. This increases recognition performance substantially. On a standard …

Hot Event Detection And Summarization By Graph Modeling And Matching, Yuxin Peng, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

This paper proposes a new approach for hot event detection and summarization of news videos. The approach is mainly based on two graph algorithms: optimal matching (OM) and normalized cut (NC). Initially, OM is employed to measure the visual similarity between all pairs of events under the one-to-one mapping constraint among video shots. Then, news events are represented as a complete weighted graph and NC is carried out to globally and optimally partition the graph into event clusters. Finally, based on the cluster size and globality of events, hot events can be automatically detected and selected as the summaries of …

Live Data Views: Programming Pervasive Applications That Use “Timely” And “Dynamic” Data, Jay Black, Paul Castro, Archan Misra, Jerome White

Research Collection School Of Computing and Information Systems

In the absence of generic programming abstractions for dynamic data in most enterprise programming environments, individual applications treat data streams as a special case requiring custom programming. With the growing number of live data sources such as RSS feeds, messaging and presence servers, multimedia streams, and sensor data. a general-purpose client-server programming model is needed to easily incorporate live data into applications. In this paper, we present Live Data Views, a programming abstraction that represents live data as a time-windowed view over a set of data streams. Live Data Views allow applications to create and retrieve stateful abstractions of dynamic …

An Efficient Scheme For Authenticating Public Keys In Sensor Networks, Wenliang Du, Ronghua Wang, Peng Ning

Electrical Engineering and Computer Science - All Scholarship

With the advance of technology, Public Key Cryptography (PKC) will sooner or later be widely used in wireless sensor networks. Recently, it has been shown that the performance of some public key algorithms, such as Elliptic Curve Cryptography (ECC), is already close to being practical on sensor nodes. However, the energy consumption of PKC is still expensive, especially compared to symmetric-key algorithms. To maximize the lifetime of batteries, we should minimize the use of PKC whenever possible in sensor networks. This paper investigates how to replace one of the important PKC operations–the public key authentication–with symmetric key operations that are …

Integrated Coverage And Connectivity Configuration For Energy Conservation In Sensor Networks, Guoliang Xing, Xiaorui Wang, Yuanfang Zhang, Chenyang Lu, Robert Pless, Christopher Gill

All Computer Science and Engineering Research

An effective approach for energy conservation in wireless sensor networks is scheduling sleep intervals for extraneous nodes, while the remaining nodes stay active to provide continuous service. For the sensor network to operate successfully, the active nodes must maintain both sensing coverage and network connectivity. Fur-thermore, the network must be able to configure itself to any feasible degrees of coverage and connectivity in order to support different applications and environments with diverse requirements. This paper presents the design and analysis of novel protocols that can dynamically configure a network to achieve guaranteed degrees of coverage and connectivity. This work differs …

Pattern Search Ranking And Selection Algorithms For Mixed-Variable Optimization Of Stochastic Systems, Todd A. Sriver

Theses and Dissertations

A new class of algorithms is introduced and analyzed for bound and linearly constrained optimization problems with stochastic objective functions and a mixture of design variable types. The generalized pattern search (GPS) class of algorithms is extended to a new problem setting in which objective function evaluations require sampling from a model of a stochastic system. The approach combines GPS with ranking and selection (R&S) statistical procedures to select new iterates. The derivative-free algorithms require only black-box simulation responses and are applicable over domains with mixed variables (continuous, discrete numeric, and discrete categorical) to include bound and linear constraints on …

A Subgroup Algorithm To Identify Cross-Rotation Peaks Consistent With Non-Crystallographic Symmetry, Ryan H. Lilien, Chris Bailey-Kellogg, Amy C. Anderson, Bruce R. Donald

Dartmouth Scholarship

Molecular replacement (MR) often plays a prominent role in determining initial phase angles for structure determination by X-ray crystallography. In this paper, an efficient quaternion-based algorithm is presented for analyzing peaks from a cross-rotation function in order to identify model orientations consistent with proper non-crystallographic symmetry (NCS) and to generate proper NCS-consistent orientations missing from the list of cross-rotation peaks. The algorithm, CRANS, analyzes the rotation differences between each pair of cross-rotation peaks to identify finite subgroups. Sets of rotation differences satisfying the subgroup axioms correspond to orientations compatible with the correct proper NCS. The CRANS algorithm was first …

Dynamic Shared State Maintenance In Distributed Virtual Environments, Felix George Hamza-Lup

Electronic Theses and Dissertations

Advances in computer networks and rendering systems facilitate the creation of distributed collaborative environments in which the distribution of information at remote locations allows efficient communication. Particularly challenging are distributed interactive Virtual Environments (VE) that allow knowledge sharing through 3D information. In a distributed interactive VE the dynamic shared state represents the changing information that multiple machines must maintain about the shared virtual components. One of the challenges in such environments is maintaining a consistent view of the dynamic shared state in the presence of inevitable network latency and jitter. A consistent view of the shared scene will significantly increase …

Comparison Of Inheritance Evaluation Algorithms For Express Edition 3., Judy Dawn Greer

Electronic Theses and Dissertations

Information exchanged between computer applications is difficult, thus the need for data exchange standards. The ISO STEP project defines data exchange standards using the EXPRESS language, which supports inheritance. Currently there are two algorithms used to evaluate an inheritance hierarchy: the Test and Generate algorithms. In this thesis, enhancements are made to both algorithms to support the Total Over Constraint, which is proposed for the third edition of EXPRESS. A formal algorithm is derived for the Test algorithm. The two enhanced algorithms are compared and shown to be result equivalent. However, it is shown that the Test algorithm is the …

Translation And Rotation Invariant Multiscale Image Registration, Jennifer L. Manfra

Theses and Dissertations

The most recent research involved registering images in the presence of translations and rotations using one iteration of the redundant discrete wavelet transform. We extend this work by creating a new multiscale transform to register two images with translation or rotation differences, independent of scale differences between the images. Our two-dimensional multiscale transform uses an innovative combination of lowpass filtering and the continuous wavelet transform to mimic the two-dimensional redundant discrete wavelet transform. This allows us to obtain multiple subbands at various scales while maintaining the desirable properties of the redundant discrete wavelet transform. Whereas the discrete wavelet transform produces …

Fast Implementation Of Depth Contours Using Topological Sweep, Kim Miller, Suneeta Ramaswami, Peter Rousseeuw, Toni Sellarès, Diane Souvaine, Ileana Streinu, Anja Struyf

Computer Science: Faculty Publications

The concept of location depth was introduced in statistics as a way to extend the univariate notion of ranking to a bivariate configuration of data points. It has been used successfully for robust estimation, hypothesis testing, and graphical display. These reguire the computation of depth regions, which form a collection of nested polygons. The center of the deepest region is called the Tukey median. The only available implemented algorithms for the depth contours and the Tukey median are slow, which limits their usefulness. In this paper we describe an optimal algorithm which computes all depth contours in &Ogr;(n 2) time …

A Review Of Data Mining Techniques, Sang Jun Lee, Keng Siau

Research Collection School Of Computing and Information Systems

Terabytes of data are generated everyday in many organizations. To extract hidden predictive information from large volumes of data, data mining (DM) techniques are needed. Organizations are starting to realize the importance of data mining in their strategic planning and successful application of DM techniques can be an enormous payoff for the organizations. This paper discusses the requirements and challenges of DM, and describes major DM techniques such as statistics, artificial intelligence, decision tree approach, genetic algorithm, and visualization.

Effect Of Exponential Averaging On The Variability Of A Red Queue, Archan Misra, Teunis Ott, John Baras

Research Collection School Of Computing and Information Systems

The paper analyzes how using a longer memory of the past queue occupancy in computing the average queue occupancy affects the stability and variability of a RED queue. Extensive simulation studies with both persistent and Web TCP sources are used to study the variance of the RED queue as a function of the memory of the averaging process. Our results show that there is very little performance improvement (and in fact, possibly significant performance degradation) if the length of memory is increased beyond a very small value. Contrary to current practice, our results show that a longer memory reduces the …

A Pairwise Key Pre-Distribution Scheme For Wireless Sensor Networks, Wenliang Kevin Du, Jing Deng, Yunghsiang S. Han, Pramod K. Varshney

Electrical Engineering and Computer Science - All Scholarship

This paper, we provide a framework in which to study the security of key pre-distribution schemes, propose a new key pre-distribution scheme which substantially improves the resilience of the network compared to previous schemes, and give an in-depth analysis of our scheme in terms of network resilience and associated overhead. Our scheme exhibits a nice threshold property: when the number of compromised nodes is less than the threshold, the probability that communications between any additional nodes are compromised is close to zero. This desirable property lowers the initial payoff of smaller-scale network breaches to an adversary, and makes it necessary …

Upper Bounds To The Clique Width Of Graphs, Bruno Courcelle, Stephan Olariu

Computer Science Faculty Publications

Hierarchical decompositions of graphs are interesting for algorithmic purposes. Many NP complete problems have linear complexity on graphs with tree-decompositions of bounded width. We investigate alternate hierarchical decompositions that apply to wider classes of graphs and still enjoy good algorithmic properties. These decompositions are motivated and inspired by the study of vertex-replacement context-free graph grammars. The complexity measure of graphs associated with these decompositions is called clique width. In this paper we bound the clique width of a graph in terms of its tree width on the one hand, and of the clique width of its edge complement on …

An Efficient Gps Position Determination Algorithm, Carlos R. Colon

Theses and Dissertations

The use of detect, or closed-form solutions of the trilateration equations used to obtain the position fix in GPS receivers is investigated. The paper is concerned with the development of an efficient new position determination algorithm that uses the closed-form solution of the trilateration equations and works in the presence of pseudorange measurement noise and for an arbitrary number of satellites. in addition, an initial position guess is not required and good estimation performance is achieved even under high GDOP conditions. A two step GPS position determination algorithm which 1) entails the solution of a linear regression problem and, 2) …

Neural Computation Of All Eigenpairs Of A Matrix With Real Eigenvalues, Serafim Theodore Perlepes

Theses Digitization Project

No abstract provided.

Even Subgraphs Of A Graph, Hong-Jian Lai, Zhi-Hong Chen

Scholarship and Professional Work - LAS

No abstract provided.