Structure and features of the Russian Linguistics (RUSLING) system

We present information on a specific system developed at the Department of Linguistic Research at VINITI. It is the information Internet portal Russian Linguistics (RUSLING). The system prototype is the well-known system LINGUIST List—the main worldwide linguistic resource. RUSLING can be considered a localization of LINGUIST List for Russian linguistics. The usefulness of such a localization is discussed.     

On the theory of realization of quasilinear systems described by differential equations in a Hilbert space

We consider a system-theoretic methodology of mathematical modeling involved in the structural identification of continuous nonlinear dynamic systems with programmable position control. We present various functional-analytical modifications of a characteristic criterion for exogenous (“input-output”) behavior of these systems that permit, by virtue of this criterion, model realizations in the class of quasilinear nonstationary ordinary differential equations describing states in a separable Hilbert space. The study was sponsored by the Russian Foundation for Basic Research (Grant No. 05-01-00623), Basic Research Program No. 22 of the Presidium of the Russian Academy of Sciences, Grant of the President of the Russian Federation for the Governmental Support of Scientific Schools of the Russian Federation (No. NSh-1676.2008). __________ Translated from Kibernetika i Sistemnyi Analiz, No. 5, pp. 82–95, September–October 2008.     

Automatic recognition fingerspelling gestures in multiple languages for a communication interface for the disabled

This paper presents the design and evaluation of a multi-lingual fingerspelling recognition module that is designed for an information terminal. Through the use of multimodal input and output methods, the information terminal acts as a communication medium between deaf and blind people. The system converts fingerspelled words to speech and vice versa using fingerspelling recognition, fingerspelling synthesis, speech recognition and speech synthesis in Czech, Russian, and Turkish languages. We describe an adaptive skin color based fingersign recognition system with a close to real-time performance and present recognition results on 88 different letters signed by five different signers, using above four hours of training and test videos.     

Classifying the subjects of the Russian Federation on the basis of analysis of results of Gallup polling

The problem of processing of Gallup poll results by cluster analysis methods is considered. The aim of these polls, performed in different subjects of the Russian Federation, is to extract main characteristics of the regions. Demyanov Egor A. Born 1982. Graduated from the Moscow State University in 2004. Post-graduate student of the same university. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of two publications. Djukova Elena V. Born 1945. Graduated from the Moscow State University in 1967. Received candidate’s degree in Physics and Mathematics in 1979, Doctoral degree in Physics and Mathematics in 1997. Dorodnicyn Computing Center, Russian Academy of Sciences, leading researcher. Moscow State University, lecturer. Moscow Pedagogical University, lecturer. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of 76 papers. Peskov Nikolai V. Born 1978. Graduated from the Moscow State University in 2000. Received candidate’s degree in Physics and Mathematics in 2004. Dorodnicyn Computing Center, Russian Academy of Sciences, junior researcher. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of 17 papers. Inyakin Andrey S. Born 1978. Graduated from the Moscow State University in 2000. Received candidate’s degree in 2006. Dorodnicyn Computing Center, Russian Academy of Sciences, junior researcher. Scientific interests: discrete mathematics and mathematical methods of pattern recognition. Author of 16 papers.     

Multi-lingual fingerspelling recognition for handicapped kiosk

This paper presents the design and evaluation of a multi-lingual fingerspelling recognition module that is designed for an information terminal. Through the use of multimodal input and output methods, the information terminal acts as a communication medium between deaf and blind people. The system converts fingerspelled words to speech and vice versa using fingerspelling recognition, fingerspelling synthesis, speech recognition and speech synthesis in Czech, Russian and Turkish Languages. We describe an adaptive skin color based fingersign recognition system with a close to real-time performance and present recognition results on 88 different letters signed by five different signers, using more than four hours of training and test videos.     

Functionally based augmented sculpting

In this paper we describe an approach to computer‐aided sculpting concerned with the creation and modification of digital models based on physical abstract sculptures. We begin by presenting a survey of current methods for the creation of computer‐aided sculptured artefacts. Then we proceed to present some original methods and tools based on the function representation of geometric models. We introduce a specialized computer language, named HyperFun, which facilitates the modelling of complex objects. As well as presenting computer‐generated animated models of pre‐existing sculptures by Russian artist Igor Seleznev, we also show how some interesting novel shapes can be generated using the HyperFun system. Finally we outline two advanced projects concerned with creating a sculpture‐based augmented reality which allows for the interactive participation of the observer. In this paper, we present experimental results, which hopefully have some artistic appeal. These results were produced by an international team of researchers and students collaborating through the Internet. Copyright © 2005 John Wiley & Sons, Ltd.     

Experimental investigation of forecasting methods based on data compression algorithms

We suggest and experimentally investigate a method to construct forecasting algorithms based on data compression methods (or the so-called archivers). By the example of predicting currency exchange rates we show that the precision of thus obtained predictions is relatively high.Translated from Problemy Peredachi Informatsii, No. 1, 2005, pp. 74–78.Original Russian Text Copyright © 2005 by Ryabko, Monarev.Supported in part by the Russian Foundation for Basic Research, project no. 03-01-00495, and INTAS, Grant 00-738.     

Satellite monitoring of ice conditions in polar regions

Data obtained by Russian and foreign polar-orbital satellites for remote sensing (RS) of the Earth is used for monitoring the ice cover of the polar regions. State Research Center of Space Hydrometeorology “Planeta” (SRC “Planeta”) and the Institute of Computational Mathematics and Mathematical Geophysics (CMMGI), have developed methods and technologies for processing the satellite data. Russian and foreign satellites (active and developing) including the satellite Arktika are described in the present paper. Procedures and techniques for monitoring the ice cover and examples of satellite data related to Arctic and Antarctic territories are given below.     

Statistical economic feasibility estimates of the Russian CMTPL automobile insurance system as a reliability theory problem

We show a method of representing basic economic characteristics of the functioning of the Russian Compulsory Motor Third Party Liability (CMTPL) system as a reliability theory system of a special kind with independent components. Each component is characterized by the number of faults (i.e., the number of road traffic accidents), its damage level (i.e., the amount of damage inflicted on third parties), and the initial endurance characteristic (i.e., the insurance premium). We mainly deal with statistical methods of graphical and analytic computerized methods for analyzing the system’s operation and further recommendations on keeping the system operational.     

Simplified scoring methods for HMM-based speech recognition

Most of the contemporary speech recognition systems exploit complex algorithms based on Hidden Markov Models (HMMs) to achieve high accuracy. However, in some cases rich computational resources are not available, and even isolated words recognition becomes challenging task. In this paper, we present two ways to simplify scoring in HMM-based speech recognition in order to reduce its computational complexity. We focus on core HMM procedure—forward algorithm, which is used to find the probability of generating observation sequence by given HMM, applying methods of dynamic programming. All proposed approaches were tested on Russian words recognition and the results were compared with those demonstrated by conventional forward algorithm.     

面向俄文NLP的形态自动分析研究与实现

在俄文自然语言处理中形态分析往往是必不可少的模块,在国内虽有个别理论研究,却还没有可以应用于生产的案例。该文系统归纳了国内外俄文形态自动分析方法,深入剖析了俄罗斯以及欧美等其他国家具有代表意义的俄文形态分析器,并在此基础上提出了多策略融合的俄文形态自动分析方法,测试表明即使将该方法应用于专业领域,也能取得令人较为满意的效果。     

Software environment for simulating algorithms for image analysis and processing

We consider the purpose, functionality, configuration, and structure of a software environment designed for simulation and investigation of methods, algorithms, and information technology for digital images analysis and processing. Mikhail V. Gashnikov. Born 1975. Graduated from the Samara State Airspace University (SSAU) in 1998. Received candidate’s degree in Technology in 2004. He is now an assistant professor at the chair of earth information of the SSAU. Scientific interests: image processing, compression, statistical coding. Author of more than 30 publications, including 12 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis. Evgenii V. Myasnikov. Born 1981. Graduated from the Samara State Airspace University in 2004. He is now a post-graduate student at the Chair of Earth Information of the Samara State Airspace University. Scientific interests: development of software systems, image processing, image retrieval in databases. Author of 6 publications, including one paper. Member of the Russian Association for Pattern Recognition and Image Analysis. Andrei V. Chernov. Born 1975. Graduated from the Samara State Airspace University (SSAU) in 1998. Received candidate’s degree in Technology in 2004. He is now an assistant professor at the Chair of Earth Information of the SSAU and a research fellow at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing, pattern recognition, geoinformation systems. Author of more than 50 publications, including 11 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis. Nikolai I. Glumov. Born 1962. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1985. Received candidate’s degree in Technology in 1994. He is now a senior researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing and pattern recognition, compression of images, simulation of systems of digital image formation. Author of more than 50 publications, including 21 papers and one monographs (in coauthorsip). Member of the Russian Association for Pattern Recognition and Image Analysis. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1974. Received doctoral degree in Technology in 1993. Head of the Laboratory of Mathematical Methods for Image Processing at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, earth information. Author of more than 150 publications, including approximately 40 papers and two monographs (in coauthorship). President of the Povolzh’e Branch of the Russian Association for Pattern Recognition and Image Analysis. Corresponding member of the Russian Ecological Academy and of the Russian Academy of Engineering Sciences. Member of the International Society for Optical Engineering. A laureate of the Samara Provincial Government prize in science and engineering. Marina A. Chicheva. Born 1964. Graduated from the Kuibyshev Airspace Institute (at present, the Samara State Airspace University) in 1987. Received candidate’s degree in Technology in 1998. She is now a senior researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image recognition, compression, fast algorithms for discrete transformations. Author of more than 40 publications, including 15 papers and one monograph (in coauthorship). Member of the Russian Association for Pattern Recognition and Image Analysis.     

Event detection and evolution in multi-lingual social streams

Real-life events are emerging and evolving in social and news streams. Recent methods have succeeded in capturing designed features of monolingual events, but lack of interpretability and multi-lingual considerations. To this end, we propose a multi-lingual event mining model, namely MLEM, to automatically detect events and generate evolution graph in multilingual hybrid-length text streams including English, Chinese, French, German, Russian and Japanese. Specially, we merge the same entities and similar phrases and present multiple similarity measures by incremental word2vec model. We propose an 8-tuple to describe event for correlation analysis and evolution graph generation. We evaluate the MLEM model using a massive humangenerated dataset containing real world events. Experimental results show that our new model MLEM outperforms the baseline method both in efficiency and effectiveness.     

Mathematical methods of detection of biological and heliogeophysical rhythms in the light of developments in modern heliobiology: A platform for discussion

Conclusion Analysis of the currently available mathematical methods for the detection of biological and heliogeophysical rhythms, and also methods for comparison of independent oscillatory processes shows that the Russian and the International Societies of Chronobiologists, despite the abundance of journals and monographs that they publish, have so far been unable to fully exploit and develop the original contribution that A. L. Chizhevskii made to world science 50 years ago. The work of the present author and her colleagues has been driven entirely by their own enthusiasm, and carried out contrary to the plans of official Councils on Chronobiology, in an atmosphere of an information blockade. Their studies have not been discussed in any survey article or textbook on chronobiology, not listed in the relevant sections of the VINITI Journals of Abstracts or in the subject catalogs of scientific libraries, not accepted for presentation at representative sessions and conferences on biorhythmology, not cited in dissertations devoted to the development of mathematical methods of detection of biorhythms. We can thus safely say that the fate of the science of heliobiology during the last 25 years remains as complex as it was in Chizhevskii's life time. Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 139–157, November–December, 1995.     

Computers in Russian schools: current conditions,main problems,and prospects for the future

This paper illustrates the current conditions of Russian schools and describes the major problems of Russian education. It also examines the past and present technological resources used in Russian classrooms, the variety and availability of hardware and software, and the prospects for Russia's future computerization. The information provided has been compiled from research, media, personal observation, surveys, and interacting with teachers, school administrators, students and other individuals.     

Optimal image reconstruction by results of two-coordinate subpixel scanning

We develop and present a fast decision method in a spatial domain for a problem related to reconstructing an input signal (image) by an ensemble of observed low quality images which differ from each other by a mutual coordinate displacement. The presented algorithms and a computational scheme, which is implemented on their basis, are built in such a way that, from a class of digital signals satisfying a recorded system of observations, the signal with a minimal energy (dispersion) is selected. Aleksandr L. Reznik. Born 1948. Graduated from the Novosibirsk State University in 1969. Received candidate’s degree in 1981. Head of a laboratory of the Institute of Automatics and Electrometry, Siberian Division, Russian Academy of Sciences. Scientific interests: analytical and numerical methods for solving complex probability problems with computer calculations. Author of 64 papers. Vitalii M. Efimov. Born 1933. Graduated from the Moscow Institute of Aviation in 1957. Received candidate’s degree in 1964. Leading researcher at the Institute of Automatics and Electrometry, Siberian Division, Russian Academy of Sciences. Scientific interests: discretization, signal quantization, processing and compression of digital data. Author of 85 papers. Semen T. Vas’kov. Born 1934. Graduated from the Leningrad Institute of Aviation Instrumentation in 1959. Corresponding member of the USSR Academy of Sciences since 1990. Consultant of the Russian Academy of Sciences to the Institute of Automatics and Electrometry. Author of more than 96 papers.     

Hierarchy of problems of surface syntactic analysis of the Russian sentence

The paper considers the linguistic basis and algorithmic structure of the system of surface syntactic analysis of the Russian sentence, which is being developed at present at the Institute of Linguistics of the Russian State University for the Humanities. The possibilities of the suggested approach are discussed with regard for the results of experimental realizations of system fragments. The linguistic basis of modules and their program realization may be useful in searching for the solution of particular problems of automatic text analysis and information search.     

Stabilization of the compressed data formation rate in hierarchical image compression

A new method is proposed for stabilizing the rate of compressed data formation in the case of hierarchical image compression. The method is based on using various values of the control parameter (maximum error) for various scale levels of image representation and for error correction at the last level depending on the received compressed information content. Gashnikov Mikhail Valer’evich (b. 1975) graduated from the Samara State Aerospace University (SSAU) in 1998. In 2004, he defended his Ph.D. thesis in engineering. At present, Gashnikov is an associate lecturer at the Department of Geoinformatics (SSAU). The scope of his scientific interests includes image processing, compression, and statistical coding. He has 30 publications, including 12 papers and a monograph (with co-authors). He is a member of the Russian Association for Image Recognition and Analysis. Glumov Nikolai Ivanovich (b. 1962) graduated from the Kuibyshev Aviation Institute (now Samara State Aerospace University) in 1985. In 1994, he defended his Ph.D. thesis in engineering. At present, Glumov is a senior scientist at the Institute of Image Processing Systems, Russian Academy of Sciences. His scientific interests include image processing and recognition, image compression, and simulation of digital image formation systems. He has more than 60 publications, including 20 articles and a monograph (with co-authors). He is a member of the Russian Association of Image Recognition and Analysis. Sergeyev Vladislav Viktorovich (b. 1951) graduated from the Kuibyshev Aviation Institute (now Samara State Aerospace University) in 1974. In 1993, he defended his D.Sc. (eng.) thesis. At present, V.V. Sergeyev heads the Laboratory of Mathematical Methods of Image Processing at the Institute of Image Processing Systems, Russian Academy of Sciences. His scientific interests include digital signal processing, image analysis, image recognition, and geoinformatics. He has more than 150 publications, including 40 articles and two monographs (with co-authors). V.V. Sergeyev is the chairman of the Povolzh’e Division of the Russian Association for Pattern Recognition and Image Analysis and a Corresponding Member of the Russian Academy of Ecology and the Academy of Engineering Sciences of the Russian Federation, a member of SPIE (International Society for Optical Engineering), and a winner of the Samara Regional Award in Science and Engineering.     

The Tools of a Machine Grammar of the Russian Language (based on G.G. Belonogov)

The principles and methods of creating program and declarative tools of a machine grammar of the Russian language are considered. These tools were based on original algorithms developed by the scientific team of the staff of the VINITI (All-Russian Institute for Scientific and Technical Information), the 27th Central Scientific Research Institute, Ministry of Defense (Russia) and the Informatics and Management Federal Research Center of the Russian Academy of Sciences (FIC IU RAS). Declarative tools, which are a complex of dictionaries and grammatical tables in machine form, were created on the basis of large-scale studies of large volumes of polythematic textual information (measured in tens of millions of words) using linguistic-statistical methods. The complex of declarative tools consists of grammatical tables and machine dictionaries that include the main types of inflectional and derivational transformations, as well as representative dictionaries of word stems. Unique algorithms of machine grammar of the Russian language were developed through the use of these declarative tools. The described tools are now widely used in a number of industrial information systems for solving complex problems of automatic processing and semantic analysis of textual information.