Chukotsk or Chukchi: Some Thoughts on the Transposition of Soviet Geographical Names

... To some cartographers and gazetteer writers the transposition of Russian geographical names into English may seem a subject well suited for an arbitrary rule of thumb; but is it? ... The reason for the current trend towards indiscriminate transliteration of Soviet geographical names is not far to seek. It is the simplest way to avoid the problems of adaptation, and at the same time enables all those who may now have a need to know the Russian version of the names to avoid learning the 32 letters of the Cyrillic alphabet - at the price of a minor distortion and some uncertainty in spelling and pronunciation. By the same token it is also the crudest manner of transposition. It literally deprives the English language of a galaxy of geographical names for a vast and increasingly important part of the earth. It is a way of dodging an issue instead of facing it. ..

Treatment of basal cell cancer in the periorbital area using a pulsed copper vapour laser

An increase in life expectancy in developed countries is inevitably accompanied by an increase in the number of nonmelanoma skin diseases, which are primarily represented by basal cell cancer (BCC) occurring in elderly and old-age patients. The pathogenesis of such diseases is associated both with impaired proliferation and differentiation of the keratinocytes of the epidermal basal layer, as well as with the transformation of the vasculature in the papillary dermis in the vicinity of BCC. In recent years, such conditions have been increasingly treated using CO2 , neodymium, diode and pulsed-dye lasers. In many cases, these devices allow malignant BCC cells to be successfully eliminated. However, the use of near-infrared lasers in the periorbital area is limited due to a higher risk of damaging the organs of the visual system. Therefore, a search for new laser surgery methods that can be used for treating malignant skin tumours seems to be a prospective research direction.Methods. 3 male and 9 female patients diagnosed with primary BCC were treated using a copper vapour laser (Yakhroma-Med). The age of the patients varied from 34 to 77 years. Laser treatment was carried out in one session under the following irradiation parameters: the wavelength of 511 and 578 nm, the average power of up to 3 W and a series of 15 ns pulses. The pause between the pulses was 60 μs, with the exposure time ranging from 200 to 600 ms. The light spot diameter on the skin surface was 1 mm. The follow-up monitoring duration was 24 months.Results. In all the BCC patients, one session of copper vapour laser treatment allowed malignant cells in the disease area to be completely eliminated without relapses during 2 years after the therapy. The duration of skin healing in the irradiated area was 2 weeks in patients under the age of 40 years, compared to 3–4 weeks in elderly patients. After the treatment, short-term side effects, such as a slight edema, erythema and peeling, were observed

Local multiresolution order in community detection

Community detection algorithms attempt to find the best clusters of nodes in an arbitrary complex network. Multi-scale ("multiresolution") community detection extends the problem to identify the best network scale(s) for these clusters. The latter task is generally accomplished by analyzing community stability simultaneously for all clusters in the network. In the current work, we extend this general approach to define local multiresolution methods, which enable the extraction of well-defined local communities even if the global community structure is vaguely defined in an average sense. Toward this end, we propose measures analogous to variation of information and normalized mutual information that are used to quantitatively identify the best resolution(s) at the community level based on correlations between clusters in independently-solved systems. We demonstrate our method on two constructed networks as well as a real network and draw inferences about local community strength. Our approach is independent of the applied community detection algorithm save for the inherent requirement that the method be able to identify communities across different network scales, with appropriate changes to account for how different resolutions are evaluated or defined in a particular community detection method. It should, in principle, easily adapt to alternative community comparison measures.Comment: 19 pages, 11 figure

Fast Learning In Multilayered Neural Networks By Means Of Hybrid Evolutionary And Gradient Algorithms

: This paper describes two algorithms based on cooperative evolution of internal hidden network representations and a combination of global evolutionary and local search procedures. The obtained experimental results are better in comparison with prototype methods. It is demonstrated, that the applications of pure gradient or pure genetic algorithms to the network training problem is much worse than hybrid procedures, which reasonably combine the advantages of global as well as local search. 1. INTRODUCTION Artificial Neural Networks (ANN) allows to approach effectively a large class of applications including pattern recognition, visual perception, signal processing and control systems. The most progress in this field is related to invention of the error backpropagation algorithm by Rumelhart et al. [1]. Backpropagation is now a conventional procedure for ANN training. However, the backpropagation as well as its numerous modifications, often leads to typical problems for gradient descen..

Optimization Of Fuzzy And Neuro-Fuzzy Systems By Means Of Adaptive Genetic Search

It is already known from the literature that the performance of a fuzzy control system may be significantly improved if the fuzzy reasoning model is supplemented by a genetic-based learning mechanism. In this paper an adaptive genetic search procedure for optimization of membership functions' (MF) shape forming parameters based on direct definition of the search ranges or certainty degrees (2-nd order fuzziness) is introduced. It was demonstrated that this approach allows to reduce the genetic algorithm (GA) search space and build such a representation, that automatically provides more accurate search in the areas of higher feasibility of the optimal solution location and vice versa. The derivation is performed for MF of any shape; however, particular attention is paid to hybrid NeuroFuzzy approach with Gaussian MFs. Introduction The major powerful point in fuzzy systems is easy applicability of expert knowledge on the subject domain. However, in most cases this empirical information..

Evolutionary Approach in Development of Intelligent Computer Aided Design Systems

: There is a word-wide upsurge of interest from both industry and academia in exciting novel computer technologies that are inspired by biological principles and other natural processes. Evolutionary Computing, Artificial Neural Networks, Fuzzy Systems along with other adaptive techniques constitutes a new scientific domain, which was recently named as Soft or Intelligent Computing. Nowadays this research area is under intensive investigations. However, Soft Computing based approach to development of the new generation of Computer Aided Design (CAD) systems, which are referred in this paper as Intelligent CADs (ICAD), has not been well studied yet. This paper describes basic ideas of Genetic and other Evolutionary Algorithms and their roles in the frameworks of Soft Computing based approach to ICAD development. Introduction The Intelligent Computer Aided Design Systems, which are capable of sophisticated systems design in almost human-independent mode are of great importance. Such IC..

Adaptive Genetic Search For Optimization Of Fuzzy And Neuro-Fuzzy Systems

: It is known that the performance of a fuzzy control system may be significantly improved if the fuzzy reasoning model is supplemented by a genetic-based learning mechanism. In this paper an adaptive genetic search procedure for optimization of membership functions' (MF) shape forming parameters based on direct definition of the search ranges or certainty degrees (2-nd order fuzziness) is introduced. It was demonstrated that this approach allows to reduce the genetic algorithm (GA) search space and build such a representation, which automatically provides more accurate search in the areas of higher feasibility of the optimal solution location and vice versa. The derivation is performed for MF of any shape, however, particular attention is paid to Gaussian shaped MFs. 1. INTRODUCTION The major powerful point in fuzzy systems is easy applicability of expert knowledge on the subject domain. However, in most cases this empirical information is not accurate enough to build an optimal syst..