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The aim of this paper is to discuss some applications of general topology in computer algorithms including modeling and simulation, and also in computer graphics and image processing. While the progress in these areas heavily depends on advances in computing hardware, the major intellectual achievements are the algorithms. The applications of general topology in other branches of mathematics are not discussed, since they are not applications of mathematics outside of mathematics.

The aim of this paper is to discuss some applications of general topology in computer algorithms including modeling and simulation, and also in computer graphics and image processing. While the progress in these areas heavily depends on advances in computing hardware, the major intellectual achievements are the algorithms. The applications of general topology in other branches of mathematics are not discussed, since they are not applications of mathematics outside of mathematics.

The aim of this paper is to discuss some applications of general topology in computer algorithms including modeling and simulation, and also in computer graphics and image processing. While the progress in these areas heavily depends on advances in computing hardware, the major intellectual achievements are the algorithms. The applications of general topology in other branches of mathematics are not discussed, since they are not applications of mathematics outside of mathematics.

The aim of this paper is to discuss some applications of general topology in computer algorithms including modeling and simulation, and also in computer graphics and image processing. While the progress in these areas heavily depends on advances in computing hardware, the major intellectual achievements are the algorithms. The applications of general topology in other branches of mathematics are not discussed, since they are not applications of mathematics outside of mathematics.

The aim of this paper is to discuss some applications of general topology in computer algorithms including modeling and simulation, and also in computer graphics and image processing. While the progress in these areas heavily depends on advances in computing hardware, the major intellectual achievements are the algorithms. The applications of general topology in other branches of mathematics are not discussed, since they are not applications of mathematics outside of mathematics.

The aim of this paper is to discuss some applications of general topology in computer algorithms including modeling and simulation, and also in computer graphics and image processing. While the progress in these areas heavily depends on advances in computing hardware, the major intellectual achievements are the algorithms. The applications of general topology in other branches of mathematics are not discussed, since they are not applications of mathematics outside of mathematics.

Digital enhancement of cometary images is a necessary tool in studying cometary morphology. Many image processing algorithms, some developed specifically for comets, have been used to enhance the subtle, low contrast coma and tail features. We compare some of the most commonly used algorithms on two different images to evaluate their strong and weak points, and conclude that there currently exists no single 'ideal' algorithm, although the radial gradient spatial filter gives the best overall result. This comparison should aid users in selecting the best algorithm to enhance particular features of interest.

Digital enhancement of cometary images is a necessary tool in studying cometary morphology. Many image processing algorithms, some developed specifically for comets, have been used to enhance the subtle, low contrast coma and tail features. We compare some of the most commonly used algorithms on two different images to evaluate their strong and weak points, and conclude that there currently exists no single 'ideal' algorithm, although the radial gradient spatial filter gives the best overall result. This comparison should aid users in selecting the best algorithm to enhance particular features of interest.

A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time of at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. This paper considers factoring integers and finding discrete logarithms, two problems which are generally thought to be hard on a classical computer and have been used as the basis of several proposed cryptosystems. Efficient randomized algorithms are given for these two problems on a hypothetical quantum computer. These algorithms take a number of steps polynomial in the input size, e.g., the number of digits of the integer to be factored.

A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time of at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration. This paper considers factoring integers and finding discrete logarithms, two problems which are generally thought to be hard on a classical computer and have been used as the basis of several proposed cryptosystems. Efficient randomized algorithms are given for these two problems on a hypothetical quantum computer. These algorithms take a number of steps polynomial in the input size, e.g., the number of digits of the integer to be factored.

In this paper, we present a web application designed for learning and visualizing Support Vector Machine (SVM) algorithms, which are key components in the fields of machine learning and data processing. The application was developed as an interactive tool that allows students and researchers to experiment with SVM models, providing insight into their structure and functionality. By using modern web technologies, the application offers a user environment that is accessible, intuitive, and adaptable for learning and research. In addition to implementing a web tool for learning the SVM algorithm, this study proposes a method for its application in teaching and analyzes the impact of applying the new interactive method on final learning outcomes. To assess the effectiveness of this tool, an experiment was conducted consisting of three phases: pre-testing, training, and post-testing. To evaluate students’ experiences with the applied alternative learning method using the auxiliary tool and their perception of the software system’s effectiveness, the standardized System Usability Scale (SUS) was used. Enable Ginger Cannot connect to Ginger Check your internet connection or reload the browserDisable GingerRephraseRephrase with Ginger (Ctrl+Alt+E) Edit in Ginger Ginger is checking your text for mistakes... Disable Ginger in this text fieldDisable Ginger on this website×

The Beauty and Joy of Computing

The report is organized in three volumes. The two computer programs presented in Volume II provide some of the basic digital implementation tools required in the analysis and synthesis of hybrid systems. The DISCRET computer program converts a general analog or continuous model expressed in the s-plane to the z-, w-, or w'-plane. DISCRET can calculate the standard, delayed, or advanced discrete transform. Data holds including the zero order, first order, second order, and slewer can be inserted into the transformation. The second program, TXCONV, implements the conversion of a high-rate discrete transform to a low-rate discrete transform. Detailed descriptions of the DISCRET and TXCONV computer programs are provided. This includes the available program options, theoretical basis for the mechanization algorithms, general and detailed program structure, required input data, and typical program output.

A FORTRAN program, published in the open literature, for the design of linear phase finite impulse response digital filters has been installed on the BRL CDC computer. Portions of this program have been extracted and combined to form a subroutine for filter design. Ancillary subroutines have been developed to assist in the formulation of filter design parameters. A subroutine for convolution of data with digital filters of finite odd length has also been written.

A FORTRAN program, published in the open literature, for the design of linear phase finite impulse response digital filters has been installed on the BRL CDC computer. Portions of this program have been extracted and combined to form a subroutine for filter design. Ancillary subroutines have been developed to assist in the formulation of filter design parameters. A subroutine for convolution of data with digital filters of finite odd length has also been written.

A FORTRAN program, published in the open literature, for the design of linear phase finite impulse response digital filters has been installed on the BRL CDC computer. Portions of this program have been extracted and combined to form a subroutine for filter design. Ancillary subroutines have been developed to assist in the formulation of filter design parameters. A subroutine for convolution of data with digital filters of finite odd length has also been written.

Substantial contributions have been made to understanding of fundamental processes in two-dimensional inviscid and nearly dissipationless vortex dynamics through an approach we call complementary modeling. We have identified and studied physical-space processes like merger, binding, axisymmetrization-and-gradient-intensification of near-isolated regions of vorticity. We have employed a variety of algorithms and codes including pseudo-spectral, contour dynamical, and our recently introduced moment model. Through the last application, we have solved analytically an asymptotical representation of the symmetric merger problem and provided causes and conditions for merger that agree with pseudospectral and contour dynamical simulations. We have also delineated the essential parameters which control the final state of two nonidentical nearby vortices (asymmetric merger). Keywords: Computer simulation, Algorithms, Vorticity, Vortex dynamics, Coherent structures, Chaotic structures.

The Connection Machine is a fine-grained parallel computer having up to 64K processors. It supports both local communication among the processors, which are situated in a two-dimensional mesh, and high bandwidth communication among processors at arbitrary locations, using a message-passing network. We present solutions to a set of Image Understanding problems for the Connection Machine. These problems were proposed by DARPA to evaluate architectures for Image Understanding systems, and are intended to comprise a representative sample of fundamental procedures to be used in Image Understanding. The solutions on the Connection Machine embody general methods for filtering images, determining connectivity among image elements, determining spatial relations of image elements and computing graph properties, such as matchings and shortest paths.

The process of effectively coordinating and controlling resources during a military engagement is known as Battle Management/ Command, Control, and Communications (BM/C3). One key task of BM/C3 is allocating weapons to destroy targets. The focus of this research is on developing parallel methods to achieve fast and cost effective assignment of weapons to targets. Using the sequential Hungarian method for solving the assignment problem as a basis, this report presents the development and relative performance comparison of four parallel assignment algorithms implemented on the Intel iPSC hypercube computer. The first approach partitions the problem space into smaller, independent subproblems and assigns each to a processing node in the hypercube. The second and third approaches also partition the problem space, but they assign each partition to a group of processing nodes. Each group is controlled by a separate node which further subdivides the partition among members of the group. In the second approach, the control node acts as an arbitrator to eliminate the redundant assignment of weapons to targets by idling redundantly allocated weapons. The third approach eliminates redundant weapon allocations by selecting the least costly redundant allocations and directing additional processing to reallocate the more costly weapons. The fourth approach is a parallel implementation of the Hungarian algorithm, where certain subtasks are performed in parallel. This approach produces an optimal assignment instead of the sub-optimal assignment generally obtained using either of the three heuristic approaches.

For many communication applications with time constraints (e.g., transmission of packetized voice messages), a critical performance measure is the percentage of messages which are transmitted within a given amount of time after their generation at the transmitting station. In this talk we present a random access algorithm (RAA) suitable for time-constrained applications. Performance analysis demonstrates that significant message delay improvement is attained, at the expense of minimal traffic loss. We also consider the case of noisy channels. The noise effect appears at erroneously observed channel feedback. Error sensitivity analysis shows that the proposed random access algorithm is insensitive to feedback channel errors. Window Random Access Algorithms (RAAs) are considered next. These algorithms constitute an important subclass of Multiple Access Algorithms (MAAs); they are distributive and they attain high throughput and low delays by controlling the number of simultaneously transmitting users. Theses. (FR)

An important problem in solid modeling systems is the creation of surfaces that blend together two or more surfaces that describe objects. The purpose of blending is to create a single, more complex object. The blending surface itself is generally not of any special importance in this context but is intended to provide a smooth transition between the surfaces to be blended. The most complete results were obtained for the blending of surfaces that are described by either the explicit or implicit boundary representations. The final report provides a description of the results.

One of the most important computer architecture innovations to appear in the market place during the last ten years is parallel processing on a shared memory multicomputer. This report presents new algorithms for a variety of network models along with empirical analysis on both sequential and parallel computers. An empirical study on the AT and T KORBX system is also presented. This system uses eight processors each of which has vector capability. Our research program objective is to develop and empirically test new parallel algorithms and software for a wide variety of optimization problems. The problems studied this past year include the shortest path problem, the assignment problem, the semi-assignment problem, the transportation problem, and the generalized network problem. Algorithms for all of these models have been developed and empirically tested on a variety of computers. In addition, we worked with the Military Airlift Command to test the AT&T KORBX system located at Scott Air Force Base. (kr)

One of the most important computer architecture innovations to appear in the market place during the last ten years is parallel processing on a shared memory multicomputer. This report presents new algorithms for a variety of network models along with empirical analysis on both sequential and parallel computers. An empirical study on the AT and T KORBX system is also presented. This system uses eight processors each of which has vector capability. Our research program objective is to develop and empirically test new parallel algorithms and software for a wide variety of optimization problems. The problems studied this past year include the shortest path problem, the assignment problem, the semi-assignment problem, the transportation problem, and the generalized network problem. Algorithms for all of these models have been developed and empirically tested on a variety of computers. In addition, we worked with the Military Airlift Command to test the AT&T KORBX system located at Scott Air Force Base. (kr)

One of the most important computer architecture innovations to appear in the market place during the last ten years is parallel processing on a shared memory multicomputer. This report presents new algorithms for a variety of network models along with empirical analysis on both sequential and parallel computers. An empirical study on the AT and T KORBX system is also presented. This system uses eight processors each of which has vector capability. Our research program objective is to develop and empirically test new parallel algorithms and software for a wide variety of optimization problems. The problems studied this past year include the shortest path problem, the assignment problem, the semi-assignment problem, the transportation problem, and the generalized network problem. Algorithms for all of these models have been developed and empirically tested on a variety of computers. In addition, we worked with the Military Airlift Command to test the AT&T KORBX system located at Scott Air Force Base. (kr)

In this lecture, we will study various applications of the theory of Multiplicative Weights (MW). In this section, we brie�y review the general version of the MW algorithm that we studied in the previous lecture. The following sections then show how the theory can be applied to approximately solve zero-sum games and linear programs, and how it connects with the theory of boosting and approximation algorithms.

In this lecture, we will study various applications of the theory of Multiplicative Weights (MW). In this section, we brie�y review the general version of the MW algorithm that we studied in the previous lecture. The following sections then show how the theory can be applied to approximately solve zero-sum games and linear programs, and how it connects with the theory of boosting and approximation algorithms.

We use computers every day, but how often do we stop and think, “How do they do what they do?” This video series explains some of the core concepts behind computer science. To view the entire playlist, visit https://www.youtube.com/playlist?list=PLpQQipWcxwt-Q9izCl0mm-QZ4seuBdUtr. We hope you enjoy!

We use computers every day, but how often do we stop and think, “How do they do what they do?” This video series explains some of the core concepts behind computer science. To view the entire playlist, visit https://www.youtube.com/playlist?list=PLpQQipWcxwt-Q9izCl0mm-QZ4seuBdUtr. We hope you enjoy!

This volume was digitized and made accessible online due to deterioration of the original print copy.

This volume was digitized and made accessible online due to deterioration of the original print copy.

The focus of this project is to aid the IGOAL in researching and implementing algorithms for advanced computer graphics. First, this project focused on porting the current International Space Station (ISS) Xbox experience to the web. Previously, the ISS interior fly-around education and outreach experience only ran on an Xbox 360. One of the desires was to take this experience and make it into something that can be put on NASA s educational site for anyone to be able to access. The current code works in the Unity game engine which does have cross platform capability but is not 100% compatible. The tasks for an intern to complete this portion consisted of gaining familiarity with Unity and the current ISS Xbox code, porting the Xbox code to the web as is, and modifying the code to work well as a web application. In addition, a procedurally generated cloud algorithm will be developed. Currently, the clouds used in AGEA animations and the Xbox experiences are a texture map. The desire is to create a procedurally generated cloud algorithm to provide dynamically generated clouds for both AGEA animations and the Xbox experiences. This task consists of gaining familiarity with AGEA and the plug-in interface, developing the algorithm, creating an AGEA plug-in to implement the algorithm inside AGEA, and creating a Unity script to implement the algorithm for the Xbox. This portion of the project was unable to be completed in the time frame of the internship; however, the IGOAL will continue to work on it in the future.

Includes index

Includes index

Includes bibliographical references and index

Includes bibliographical references and index

Talk given by Tom Dean, of Google. Given to the Redwood Center for Theoretical Neuroscience at UC Berkeley on January 20, 2010.. Abstract. Graphics processors (GPUs) and massively-multi-core architectures are becoming more powerful, less costly and more energy efficient, and the related programming language issues are beginning to sort themselves out. That said most researchers don’t want to be writing code that depends on any particular architecture or parallel programming model. Linear algebra, Fourier analysis and image processing have standard libraries that are being ported to exploit SIMD parallelism in GPUs. We can depend on the massively-multiple-core machines du jour to support these libraries and on the high-performance-computing (HPC) community to do the porting for us or with us. These libraries can significantly accelerate important applications in image processing, data analysis and information retrieval. We can develop APIs and the necessary run-time support so that code relying on these libraries will run on any machine in a cluster of computers but exploit GPUs whenever available. This strategy allows us to move toward hybrid computing models that enable a wider range of opportunities for parallelism without requiring the special training of programmers or the disadvantages of developing code that depends on specialized hardware or programming models. This talk summarizes the state of the art in massively-multi-core architectures, presents experimental results that demonstrate the potential for significant performance gains in the two general areas of image processing and machine learning, provides examples of the proposed programming interface, and some more detailed experimental results on one particular problem involving video-content analysis.

The development of vector processing computers of the streaming array architectures has made possible a dramatic decrease in the time required for the solution of problems, i.e., for those algorithms which readily lend themselves to sequential operations on long vectors. There has concurrently been rapid growth in the applications of the techniques generally known as mathematical digital filtering, also called signal analysis, digital signal processing, time series analysis, and digital image processing. The best known applications of these techniques is to seismic data and two-dimensional images, data types consisting of very large collections of numbers. A major limitation for these cases is the size and speed of the computer available. Therefore, a move to the streaming array architecture can result in marked improvement in the data analysis techniques which may be employed.

Includes bibliographies

Includes bibliographies

The algorithms necessary for the computer aided design of digital filters from lowpass prototypes has been developed and compared, then implemented in a computer program to aid in the instruction of digital filter design. The procedure for the design of lowpass, highpass, bandpass, and bandstop digital filters from lowpass prototypes is well established, and is based on transforming the prototype frequency response to meet desired characteristics. This transformation can be accomplished in either the analog (s) domain or the digital (z) domain. Therefore, the two classical design techniques, analog-digital and digital-digital design, are based on doing the frequency response transformations in their respective analog or digital domains. Since the theory for the standard filter types (Butterworth, Chebyshev, and elliptic) is developed in the analog or 's' domain, the two methods for designing digital filters differ basically in the sequence of the design steps. In the analog-digital method the analog prototype is transformed and then digitized, while in the digital-digital method the analog prototype is digitized and then transformed. Keywords: Theses.

A computation scheme for solving elliptic boundary value problems with axially symmetric confining potentials using different sets of one-parameter basis functions is presented. The efficiency of the proposed symbolic-numerical algorithms implemented in Maple is shown by examples of spheroidal quantum dot models, for which energy spectra and eigenfunctions versus the spheroid aspect ratio were calculated within the conventional effective mass approximation. Critical values of the aspect ratio, at which the discrete spectrum of models with finite-wall potentials is transformed into a continuous one in strong dimensional quantization regime, were revealed using the exact and adiabatic classifications.

The objective of this project was to apply computational methods for microstructures suspended in a viscous liquid, to the calculation of slow dynamics in protein folding and association reactions. A fast Brownian dynamics algorithm was developed, as well as a knowledge-based potential of mean force for interactions protein segments.

A FORTRAN program, published in the open literature, for the design of linear phase finite impulse response digital filters has been installed on the BRL CDC computer. Portions of this program have been extracted and combined to form a subroutine for filter design. Ancillary subroutines have been developed to assist in the formulation of filter design parameters. A subroutine for convolution of data with digital filters of finite odd length has also been written.

A FORTRAN program, published in the open literature, for the design of linear phase finite impulse response digital filters has been installed on the BRL CDC computer. Portions of this program have been extracted and combined to form a subroutine for filter design. Ancillary subroutines have been developed to assist in the formulation of filter design parameters. A subroutine for convolution of data with digital filters of finite odd length has also been written.

Algorithm development should have two phases. The computer portion and the portion to be incorporated in operator analyst training. A knowledgeable operator analyst should be able to perform analysis beyond the means of any particular computerized algorithm available to that analyst. This follows from the fact that humans can understand the consequences of the limitations of particular computer implementations and correct, in part, for them. Computer based algorithm limitations may have different causes: 1) The algorithms may be based on incomplete or inaccurate models; 2) The algorithms may not be flexible enough to adapt to the need for changes in analysis criteria; 3) The algorithms may take shortcuts because of limitations in computer storage or speed; 4) There may be refinements in the analysis which could be computed but are not because they depend on parameters which are insufficiently well known; and 5) Computer output formates may be restrictive.

This thesis presents a fully developed, tactically oriented computer aided mission planning system for the A7E aircraft. The system is designed to be extremely easy to operate by someone with no computer experience, and is a replacement for 53 NATOPS performance charts that are most applicable to flight and mission planning. High altitude performance, as well as low altitude and maximum range performance, are available. Tactical navigation routes may be entered, edited, and saved in a disk file. Navigation computations are linked with aircraft performance to provide printout of a completed mission planning jet log. Numerical techniques for obtaining analytical expressions from chart and tabular data included multiple linear regression analysis, curve fitting, and cross plotting of regression coefficients. The computer program results have been correlated with NATOPS data and actual flight test, and have been found to be highly accurate. The program is designed to be run on the IBM /PC/XT/AT and compatible computers with a minimum of 256K memory available. Keywords: Aircraft performance, Computerized Mission Planning, IBM-PC, Attack bombers.

This project is concerned with the optimisation of objective functions F(x) in a large dimensional space R to the n power on highly parallel computers. It has been established that the truncated Newton method introduced by Dembo & Steihang is an efficient method for solving large optimisation algorithms on a sequential machine, Dixon & Price. The truncated Newton method consists of two main steps: 1) the calculation of the function value F(x),, gradient vector g(x) and Hessian matrix H(x) at a sequence of points x to the (k) power. 2) solving the set of linear equations H(x) d = - g(x) approximately for the search direction d.