Digital Commons Network^™

Analysis Of Myoelectrical Signals For Building A Dextrous Hand, Christopher T. Creel, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka

Electrical Engineering and Computer Science - Technical Reports

We analyze techniques for myoelectrical signals classification for the purpose of designing a multifunctional prosthetic device for human amputees. The main advantage of our system over existing models is that it is more robust, easier to work with, more general, and efficient enough to run in real time. We achieve this with the help of "Supervised Growing Cell Structures." an artificial neural network model designed by Fritzke [10]. The current paper focuses on the flexion of the index, middle and ring fingers, as these are the most difficult movements to tackle.

Wright State University College Of Engineering And Computer Science Bits And Pcs Newsletter, Volume 10, Number 6, June 1994, College Of Engineering And Computer Science, Wright State University

BITs and PCs Newsletter

A ten page newsletter created by the Wright State University College of Engineering and Computer Science that addresses the current affairs of the college.

Feature And Model Selection In Feedforward Neural Networks, Jean M. Steppe

Theses and Dissertations

This research advances feature and model selection for feedforward neural networks. Feature selection involves determining a good feature subset given a set of candidate features. Model selection involves determining an appropriate architecture number of middle nodes for the neural network. Specific advances are made in neural network feature saliency metrics used for evaluating or ranking features, statistical identification of irrelevant noisy features, and statistical investigation of reduced neural network architectures and reduced feature subsets. New feature saliency metrics are presented which provide a more succinct quantitative measure of a features importance than other similar metrics. A catalogue of feature saliency …

A Conceptual Model For Multimedia Database Systems, Shunge Li, Xiangning Liu, Bharat Bhargava

Department of Computer Science Technical Reports

No abstract provided.

Eppod: A Problem Solving Environment For Parallel Electronic Prototyping Of Physical Object Design, Poting Wu, Elias N. Houstis, John R. Rice

Department of Computer Science Technical Reports

No abstract provided.

Curvature Continuous Spline Surfaces Over Irregular Meshes, Jörg Peters

Department of Computer Science Technical Reports

No abstract provided.

Indexing And Distributing A General Patterned Spare Array, Daria Dooling, Lenore Mullin

Computer Science Technical Reports

High performance computing and communication (HPCC) requires that space and time usage are kept to a minimum when solving very large scientific problems. These problems often are represented by sparse systems, and in particular banded systems. In this paper, a new banded array index algorithm is presented that uses substantially less memory than the BLAS (Basic Linear Algebra Subroutines) representation. The algorithm presented here works for multi-dimensional arrays and on all bandwidths. It is visualized as a layer between the applications and the data, thus shielding the caller from the complexities of the sparse representation. Information is returned to the …

Ccsp - A Formal System For Distributed Program Debugging, Beth Arrowsmith, Bruce Mcmillin

Computer Science Technical Reports

One of the major problems with programming in a parallel/distributed environment is the difficulty in debugging the programs due to their complex interactions. One can have results that appear random, but when given a complete knowledge of the specific run-time behavior, the results are foregone. Unfortunately, this complete knowledge is not generally attainable in a distributed system. In order to develop a system for debugging distributed program and, for the more general case, ensuring their correctness at run-time, we built a distributed execution enviromnent based on Hoare's CSP [5] which allows for the execution and evaluation of embedded assertions within …

Parallel Adaptive Mesh Refinement Algorithms, Mustafa Keskin, Fikret Ercal

Computer Science Technical Reports

This study is aimed at developing 2D parallel adaptive mesh refinement algorithms for engineering applications such as penetration mechanics, manufacturing and combustion which use the finite element method for simulation. A new algorithmic approach, called piecewise adaptive mesh refinement for parallelization, is developed and implemented to run on a sequential machine. Performance of the new method is compared against a conventional advancing front technique proposed earlier. A parallel implementation model to run on a massively parallel computer is proposed and its expected efficiency is analyzed theoretically. Furthermore, some issues concerning parallelization and task partitioning are also discussed. In addition, a …

A Deterministic Membership Algorithm In Asynchronous Distributed Systems, P. Su, B. Mcmillin, A. Dekock

Computer Science Technical Reports

This work presents a deterministic asynchronous membership protocol (AMP). Conceptually a membership algorithm provides a means of recruiting members (machines) in a distributed system. Currently most of the research in membership recruiting emphasizes how to obtain the members after a machine fail-stop has occurred during the system operation, and the membership algorithms proposed arc non-deterministic. This work extends the research to develop a deterministic membership algorithm to recruit machines dynamically at the system cold-start. Once it is possible to recruit machines at system cold-start, then it is trivial to recruit members after a machine fail-stop has occurred during the system …

Using Temporal Subsumption To Generate Efficient Error-Detecting Distributed Algorithms, Martina Schollmeyer, Bruce Mcmillin

Computer Science Technical Reports

Distributed algorithms can use executable assertions, which can be derived from program verificatioll or specified in an ad hoc manner, to detect. errors at run-time. However, there may be more assertions available than are really unecessary, and embedding all of them into the program to be checked at run-time would make error-detection very inefficient. For safety-critical systems we often need to make decisions very quickly and cannot allow too much time to be spent on error detection.

The new technique of temporal submission, which is introduced in this dissertation, examines the dependencies between the individual assertions along program execution paths. …

The Formal Description Of Resource Deadlock In Distributed Systems, P. Lu, B. Mcmillin

Computer Science Technical Reports

Deadlock detection is a fundamental problem in a distributed system and has been extensively studied in the past few years. Many distributed deadlock detection/resolution alg·orithms have been proposed, but most of them either have not given a correctness proof or have given an informal proof by using intuitive operational arguments. Informal arguments are prone to errors and many of the published algorithms have been fouud to be incorrect. In trying to avoid this situation, the development of a formal approach to the algorithm correctness proof is required.

In this work, a formal resource deadlock model with global and local clocks …

Production And Decay Of D1 (2420)0 And D2* (2460)0, Avery, P.; Et Al., M. Thulasidas

Research Collection School Of Computing and Information Systems

No abstract provided.

Hardware Assists For High Performance Computing Using A Mathematics Of Arrays, H. Pottinger, W. Eatherton, L. Mullin, T. Schiefelbein

Computer Science Technical Reports

Work in progress at the University of Missouri - Rolla on hardware assists for high performance computing and communication is presented. This research consists of a field programmable gate array based rapid prototyping environment (Chameleon) being used to evaluate hardware architectures for speedup of array partitioning and routing algorithms. These algorithms have been developed using a Mathematics of Arrays (MOA) and are optimal in the sense that they reduce normal array indexing operations to a series of primitive additions based on array shape. The method is simple yet powerful, produces algorithms which are provably correct, and are independent of dimensionality. …

An Fpga Based Reconfigurable Coprocessor Board Utilizing A Mathematics Of Arrays, H. Pottinger, W. Eatherton, T. Schiefelbein, L. Mullin, R. Ziegler

Computer Science Technical Reports

Work in progress at the University of Missouri-Rolla on hardware assists for high performance computing is presented. This research consists of a novel field programmable gate array (FPGA) based reconfigurable coprocessor board (the Chameleon Coprocessor) being used to evaluate hardware architectures for speedup of array computation algorithms. These algorithms have been developed using a Mathematics of Arrays (MOA) and are optimal in the sense that they reduce normal array cartesian indexing operations to a series of primitive additions and offsets based on array shape. The method is simple yet powerful, produces algorithms which are provably correct, and are independent of …

Extracting Parallelism At Compile-Time Through Dependence Analysis & Cloning Techniques In An Object-Based Paradigm, Binoy Ravindran

Theses

The construct of Abstract Data Type (ADT) modules and Abstract Data Object (ADO) modules supported by most object-based languages are a great source for developing reusable code. To improve the run time performance of such object-based programs, we consider the asynchronous remote procedure call (ARPC) model of parallel execution, in which concurrency is achieved by having the caller and the callee (which are module instances) running on different processors. Frequently, an ADT module is needed simultaneously by other modules, thus causing contention. To resolve this, we clone the module instance in demand and distribute the copies across different processors, so …

Fast Greedy Triangulation Algorithms, Matthew T. Dickerson, Robert L. Scot Drysdale, Scott A. Mcelfresh, Emo Welzl

Computer Science Technical Reports

The greedy triangulation of a set $S$ of $n$ points in the plane is the triangulation obtained by starting with the empty set and at each step adding the shortest compatible edge between two of the points, where a compatible edge is defined to be an edge that crosses none of the previously added edges. In this paper we present a simple, practical algorithm that computes the greedy triangulation in expected time $O(n \log n)$ and space $O(n)$ for points uniformly distributed over any convex shape. A variant of this algorithm should be fast for some other distributions. As part …

Multirate Time-Frequency Distributions, John R. O'Hair

Theses and Dissertations

Multirate systems, which find application in the design and analysis of filter banks, are demonstrated to also be useful as a computational paradigm. It is shown that any problem which can be expressed a set of vector-vector, matrix-vector or matrix-matrix operations can be recast using multirate. This means all of numerical linear algebra can be recast using multirate as the underlying computational paradigm. As a non-trivial example, the multirate computational paradigm is applied to the problem of Generalized Discrete Time- Frequency Distributions GDTFD to create a new family of fast algorithms. The first of this new class of distributions is …

Subgrouped Real Time Recurrent Learning Neural Networks, Jeffrey S. Dean

Theses and Dissertations

A subgrouped Real Time Recurrent Learning (RTRL) network was evaluated. The one layer net successfully learns the XOR problem, and can be trained to perform time dependent functions. The net was tested as a predictor on the behavior of a signal, based on past behavior. While the net was not able to predict the signal's future behavior, it tracked the signal closely. The net was also tested as a classifier for time varying phenomena; for the differentiation of five classes of vehicle images based on features extracted from the visual information. The net achieved a 99.2% accuracy in recognizing the …

Polynomial Surface Patch Representations, Chandrajit L. Bajaj

Department of Computer Science Technical Reports

No abstract provided.

Building Information Systems For Mobile Environments, Evaggelia Pitoura, Bharat Bhargava

Department of Computer Science Technical Reports

No abstract provided.

Providing Assurance For Reponsive Computing Systems, G. Tsai, B. Mcmillin

Computer Science Technical Reports

A responsive computing system is a hybrid of real-time, distributed and fault-tolerant systems. In such a system, severe consequences will occur if the logical and physical specifications of the system are not met. In this dissertation, an approach to ensure satisfaction of specifications in the operational environment is presented as follows. First, we specify properties of the system using ITL formulas. Next, we collect, at runtime, events and maintain equivalent event histories to represent system execution. Finally, we apply a decision procedure to determine satisfaction of the formulas. A run-time evaluation system was built according to this approach and we …

Skin Cancer Diagnosis Using Hierarchal Neural Networks And Fuzzy Logic, H. C. Lee, F. Ercal

Computer Science Technical Reports

Skin cancer, the most common cancer in the United States that affects about 600,000 Americans every year, accounts for 1% of all cancer deaths. Among all, Malignant Melanoma is the most virulent form of skin cancer that is responsible for 75% of all deaths from skin cancer. In 1992, approximately 32,000 people are expected to develop melanoma and about 6,700 will die. However, even malignant melanoma can be treated successfully if detected in the early phase. Therefore, our research goal is to diagnose skin cancer, especially malignant melanoma.

In this study, only the digitized images obtained from color tumor slides …

Classification Characteristics Of Som And Art2, J. Aleshunas, D. St. Clair, W. Bond

Computer Science Technical Reports

Artificial neural network algorithms were originally designed to model human neural activities. They attempt to recreate the processes involved in such activities as learning, short term memory, and long term memory. Two widely used artificial neural network algorithms are the Self-Organizing Map (SOM) and the Adaptive Resonance Theory (ART2). Each was designed to simulate a particular biological neural activity. Both can be used as unsupervised data classifiers.

This paper compares performance characteristics of two unsupervised artificial neural network architectures; the SOM and the ART2 networks. The primary factors analyzed were classification accuracy, sensitivity to data noise, and sensitivity to the …

Image Processing Techniques And Implementations In Software For Use With A Ccd Camera, Clarence Franklin Jr.

Opportunities for Undergraduate Research Experience Program (OURE)

The concept of image processing is used whenever there is a reference to digital images. By random and natural errors introduced into the image during collection and transmission, the images are distorted. Image processing techniques are used to eliminate these error before viewing of the images. For this experiment, the images provided by the ST-6 CCD Camera System will be used in the development and implementation of image processing techniques into a software package.

A User-Level Process Package For Concurrent Computing, Ravi Konuru, Steve Otto, Jonathan Walpole, Robert Prouty, Jeremy Casas

Computer Science Faculty Publications and Presentations

A lightweight user-level process(ULP) package for parallel computing is described. Each ULP has its own register context, stack, data and heap space and communication with other ULPs is performed using locally synchronous, location transparent, message passing primitives. The aim of the package is to provide support for lightweight over-decomposition, optimized local communication and transparent dynamic migration. The package supports a subset of the Parallel Virtual Machine(PVM) interface[Sun90).

Knowledge-Based Nonuniform Crossover, Harpal Maini, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka

Electrical Engineering and Computer Science - Technical Reports

We present a new "knowledge-based non-uniform crossover" (KNUX) operator for genetic algorithms (GA's) that generalizes uniform crossover. We extend this to "Dynamic KNUX" (DKNUX), which constantly updates the knowledge extracted so far from the environment's feedback on previously generated chromosomes. KNUX can improve on good solutions previously obtained by using other algorithms. The modifications made by KNUX are orthogonal to other changes in parameters of GA's, and can be pursued together with any other proposed improvements. Whereas most genetic search methods focus on improving the move-selection procedures, after having chosen a fixed move-generation mechanism, KNUX and DKNUX make the move-generation …

Classification Characteristics Of Som And Art2, J. J. Aleshunas, Daniel C. St. Clair, William E. Bond

Mathematics and Statistics Faculty Research & Creative Works

Artificial neural network algorithms were originally designed to model human neural activities. They attempt to recreate the processes involved in such activities as learning, short term memory, and long-term memory. Two widely used unsupervised artificial neural network algorithms are the Self-Organizing Map (SOM) and Adaptive Resonance Theory (ART2). Each was designed to simulate a particular biological neural activity. Both can be used as unsupervised data classifiers. This paper compares performance characteristics of two unsupervised artificial neural network architectures; the SOM and the ART2 networks. The primary factors analyzed were classification accuracy, sensitivity to data noise, and sensitivity of the algorithm …

Generating Indexing Functions Of Regularly Sparse Arrays For Array Compilers, Scott Thibault, Lenore Mullin, Matt Insall

Computer Science Technical Reports

There are many applications involving arrays that contain non-zero components in regular geometric partitions. These include triangular, diagonal, tridiagonal, banded, etc. When computing with this type of arrays, they are usually stored in a packed form and computations are performed with only the non-zero components. This packed form requires an indexing function that maps an index of the array to an index of the packed lexico-graphically stored array. This paper presents a method of describing regular partitions and of automatically generating an indexing function from that description. These methods enable an array compiler to compile array operations on these type …

Polylog Depth Circuits For Integer Factoring And Discrete Logarithms, Jonathan P. Sorenson

Scholarship and Professional Work - LAS

AbstractIn this paper, we develop parallel algorithms for integer factoring and for computing discrete logarithms. In particular, we give polylog depth probabilistic boolean circuits of subexponential size for both of these problems, thereby solving an open problem of Adleman and Kompella.

Existing sequential algorithms for integer factoring and discrete logarithms use a prime base which is the set of all primes up to a bound B. We use a much smaller value for B for our parallel algorithms than is typical for sequential algorithms. In particular, for inputs of length n, by setting B = nlogdn with d a positive …