There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

A fast-Fourier-transform method of topography and interferometry is proposed. By computer processing of a noncontour type of fringe pattern, automatic discrimination is achieved between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour-generation techniques. The method has advantages over moire topography and conventional fringe-contour interferometry in both accuracy and sensitivity. Unlike fringe-scanning techniques, the method is easy to apply because it uses no moving components.

Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry

to be done in this area. Face recognition is a problem that scarcely clamoured for attention before the computer age but, having surfaced, has involved a wide range of techniques and has attracted the attention of some fine minds (David Mumford was a Fields Medallist in 1974). This singular application of mathematical modelling to a messy applied problem of obvious utility and importance but with no unique solution is a pretty one to share with students: perhaps, returning to the source of our opening quotation, we may invert Duncan's earlier observation, 'There is an art to find the mind's construction in the face!'.

Linear and nonlinear waves, by G. B. Whitham. Pp.636. £50. 1999. ISBN 0 471 35942 4 (Wiley).

Praise for the Third Edition: "This is one of the best books available. Its excellent organizational structure allows quick reference to specific models and its clear presentation . . . solidifies the understanding of the concepts being presented."IIE Transactions on Operations EngineeringThoroughly revised and expanded to reflect the latest developments in the field, Fundamentals of Queueing Theory, Fourth Edition continues to present the basic statistical principles that are necessary to analyze the probabilistic nature of queues. Rather than presenting a narrow focus on the subject, this update illustrates the wide-reaching, fundamental concepts in queueing theory and its applications to diverse areas such as computer science, engineering, business, and operations research.This update takes a numerical approach to understanding and making probable estimations relating to queues, with a comprehensive outline of simple and more advanced queueing models. Newly featured topics of the Fourth Edition include:Retrial queuesApproximations for queueing networksNumerical inversion of transformsDetermining the appropriate number of servers to balance quality and cost of serviceEach chapter provides a self-contained presentation of key concepts and formulae, allowing readers to work with each section independently, while a summary table at the end of the book outlines the types of queues that have been discussed and their results. In addition, two new appendices have been added, discussing transforms and generating functions as well as the fundamentals of differential and difference equations. New examples are now included along with problems that incorporate QtsPlus software, which is freely available via the book's related Web site.With its accessible style and wealth of real-world examples, Fundamentals of Queueing Theory, Fourth Edition is an ideal book for courses on queueing theory at the upper-undergraduate and graduate levels. It is also a valuable resource for researchers and practitioners who analyze congestion in the fields of telecommunications, transportation, aviation, and management science.

Fundamentals of Queueing Theory

In this paper, multiresolution analysis and interpolating wavelets are investigated for finding a numeric solution of partial differential equations (PDEs) such space derivatives are computed in an irregular grid by cubic splines method. Mathematics Subject Classification: 42C40, 35G20, 65M70

/pdf/investigation-of-interpolating-wavelets-theory-for-the-rq32w6h1o0.pdf

Investigation of Interpolating Wavelets Theory for the Resolution of PDEs

This paper is concerned with the problem of designing disturbance observer for fractional order systems, of
which the disturbance is in time series expansion. The stability of a special observer with the selected nonlinear weighted
function and transient dynamics function is rigorously analyzed for slowly varying disturbance. In addition, the result is
also extended to estimate slope forms disturbance and higher order disturbance of fractional order systems. The efficacy
of the proposed method is validated through numerical examples.

/pdf/observation-of-a-class-of-disturbance-in-time-series-3rjsi0gpxn.pdf

Observation of a Class of Disturbance in Time Series Expansion for Fractional Order Systems

Comfort, reliability, functionality performance which provide a longer life cycle requires thourogh understanding and analysis of the vibrations, this is a general rule for most of the static and dynamic functionality applications. Vibrations is an extremely important issue to consider when designing various systems.

The hysteresis in the dampers is very important issue when characterizing a damper, it is a very complex phenomena but very important to consider. The hysteresis equations of Bouc-Wen, Lugre, and Dahl have been modeled and simulated in Matlab/Simulink. We have manipulated the different parameters in the models and analyzed their effects on the outcome. The hysteresis models of Bouc-Wen, Dahl and LuGre have been analyzed and compared analytically to really show the difference in the models. At last the Bouc-Wen model was implemented together with the SAS(Semi Active Suspension) system in the laboratory. The model parameters were tuned manually to try to fit the response of the system.

In this paper a predefined methodology has been applied for determining the hysteresis loop parameters using the data collected for vibration analysis under predefined test specifications. The following data has been used later to regenerate the vibration signal, so on get as closer to the real signal.

In the coming work, advanced method will be used to determine the exact parameters for the hysteresis loop as well as using the inverse hysteresis to improve the performace of the vibration suspension in the Semi Active Suspension system.

The behavior of MR dampers can be presented with different mathematical models. The Bouc-Wen model was found to be model to both illustrate the MR damper and recreate the behavior of the SAS system.

Vibration analysis for the rotational magnetorheological damper

Deep neural networks and in particular, deep neural classifiers have become an integral part of many modern applications. Despite their practical success, we still have limited knowledge of how they work and the demand for such an understanding is evergrowing. In this regard, one crucial aspect of deep neural network classifiers that can help us deepen our knowledge about their decision-making behavior is to investigate their decision boundaries. Nevertheless, this is contingent upon having access to samples populating the areas near the decision boundary. To achieve this, we propose a novel approach we call Deep Decision boundary Instance Generation (DeepDIG). DeepDIG utilizes a method based on adversarial example generation as an effective way of generating samples near the decision boundary of a neural network model. Then, we introduce a set of important characteristics that take advantage of the generated borderline instances and provide multifaceted understandings of deep neural networks. We have performed extensive experiments on multiple representative datasets across various deep neural network models and characterized their decision boundaries. The entire code is publicly available.1

Decision Boundaries of Deep Neural Networks

Genetic diversity of plant species can be evaluated by various methods. The DNA markers are one of the most powerful techniques, because they are not affected by environmental factors as well as plant developmental stages. Markers such as RAPD, AFLP, RFLP and SSR are used for studying genetic diversity of plants. In order to corroborate our results and to minimize the experimental errors, in the present study, AFLP and RAPD markers were used. Genetic similarities (GS) were calculated for both markers using the Jaccard and Dice algorithms. Six AFLP primer combinations used in this study generated 475 scorable bands, of which 336 bands were polymorphic, while the 12 RAPD primers produced 130 bands, of which 118 showed polymorphism. Using Jaccard and Dice algorithms, correlation between the genetic similarity and cophenetic coefficient (CCC) for RAPD marker were 0.82 and 0.77, respectively. In the case of AFLP, CCC was 0.91 and 0.89, respectively. The highest CCCs were calculated with the Jaccard method.

Hamid Reza Karimi

Papers

Investigation of Interpolating Wavelets Theory for the Resolution of PDEs

Observation of a Class of Disturbance in Time Series Expansion for Fractional Order Systems

Vibration analysis for the rotational magnetorheological damper

Decision Boundaries of Deep Neural Networks

Genetic Relationships of Some Pistacia Species Using RAPD and AFLP Markers