The Significance of the K-Representations Theory for the Studies on Automatic Semantic Role Labeling
The paper shows an incompleteness of theoretical foundations of the Computational Semantics branches called Semantic Role Labeling and Frame-Semantic Parsing. This situation is a consequence of a seeming lack of a semantic formalism allowing to describe semantic structures of complex sentences and discourses pertaining to arbitrary application domains. It is concluded that the theory of K-representations (knowledge representations) provides a formalism of the kind, determining a new class of formal languages — the class of SK-languages (standard knowledge languages). Some new expressive mechanisms of SK-languages are illustrated. The central ideas of a method of semantic parsing of natural language (NL) texts proposed by the theory of K-representations are set forth. The method employs the class of SK-languages for constructing semantic representations of texts. The final part of the paper considers the application of the method to designing NL-interfaces for software management. A file manager with a NL-interface NLC-1 (Natural Language Commander — Version One) has been developed, the system is implemented with the help of the functional programming language Haskell.
P. A. Borisovsky, Associated Professor, firstname.lastname@example.org, Omsk State University Dostoyevsky, A. V. Eremeev, Senior Researcher, email@example.com, Omsk Branch of Sobolev Institute of Mathematics
Production Scheduling of a Multi-Product Plant Using Integer Linear Programming and Evolutionary Computations
V. V. Vorobyev, Postgraduate student, e-mail: firstname.lastname@example.org, E. A. Parshikova, Postgraduate student, e-mail: Parshikoff87@gmail.com, Moscow Institute of Electronics and Mathematics National Research University "High School of Economics, Moscow
Application of Multisets for Assessment of the Situation by the Mobile Agent
The mobile agent needs the developed receptors for existence in a dynamic environment with unknown characteristics. But the increase in the number of receptors leads to a significant increase in the complexity of the processing of the signals coming from these sensors. The problem of the dimension of the input sensory data of agent occurs. The article discusses the possibility of using of multisets to reduce the dimension of the input data vector from sensors and the possibility of using of multisets for further assessment of the situation by the mobile agent. On the example of the mobile agent reinforcement learning it is shown that the presentation of the properties of the environment in the form of multisets allows to aggregate the sensory data of agent, thereby reducing the dimension of the input data vector.
G. G. Bulychev, Professor, e-mail: email@example.com, Moscow State University of RadioEngineering, Electronics and Automation
Numerical Modeling of Dynamical Destruction Hollow Bodies by Detonation Products
By numerical method of spatial characteristics there is solved the problem of impulsive destruction of thin-walled isotropic body. The impulse is made by point explosion in the center of body or by moving detonation point of explosive cord, located along the perimeter of the inner cavity of the body. Limit of destruction’s stress is determined by as function of velocity of detonation, thickness of walls and Puasson’s factor of a body material.
K. A. Shcheglov, Graduate Student, A. Yu. Shcheglov, Professor, Saint-Petersburg National Research University of Information Technologies, Mechanics and Optics, Russia
Network Informational System Data Securing Technology
We review the new network informational system data securing approach based on newly created objects (file system objects and clipboard) access control methods implementation, which allows to exclude object from access policy (with help of created objects automatic labeling). Practical implementation of such approach (while saving labeling directly in created file) allows to formulate and solve the task of implementing data (processed in network informational system) access policy in a view of different possible ways of data exchange between computers in such system. Herewith we implement data streams managing already within whole system. Reviewed protection method is based on practical realization which was patented by authors of "File objects access control system based on auto-labeling" solution. This solution allows to rethink known realization of both access control methods including discretionary and mandate ones. This not only dramatically simplifies setting file objects access policy (by eliminating the "access object" essence from access control scheme), but also settings correct implementation in the general case is provided in the same time.
Y. N. Imamverdiyev, Head of Laboratory, e-mail: firstname.lastname@example.org, Institute of Information Technology of Azerbaijan National Academy of Sciences
A Fuzzy Cognitive Model for the Strategic Management of Information Security of E-Government
The article studies the nature and application of cognitive modeling in the strategic management of information security of e-government. Factors of strategic management of information security are defined and the fuzzy cognitive map for strategic management of e-government information security is built on the basis of expert assessments. Based on the developed cognitive model results of different strategies for e-government information security management are analyzed.
S. I. Smetanin, Graduate Student, V. A. Ignatyuk, Dr. Sci Sciences, prof., e-mail; email@example.com, A. A. Evstifeev, Graduate Student Department of Electronics, Vladivostok State University of Economics and Service, Vladivostok
Implementation of the Software Part of the System of Satellite Monitoring
V. G. Getmanov1, 2, Professor, Chief Researcher, G. I. Borzunov2, 3, Professor,
The Algorithm of Parallel Calculations for a Problem of the Spectral-Time Analysis on Basic Polyharmonic Functions
Yu. G. Tabakov, Graduate Student, e-mail: firstname.lastname@example.org, Voronezh State Academy of Forestry Engineering, Voronezh
Problems Processing LF Signals in of Intellectual Information Systems
The article describes and shows the basic problems in the processing of low-frequency signals removed from the cerebral cortex and possible solutions. Proposed a specially designed mathematical models and algorithms for processing low-frequency signals. These model and algorithms constructed on a specially designed and modified Daubechies and Morlaix wavelet-transform, which allow processing low-frequency signals in real time and analyze the data obtained. Present detailed block diagram of the low-frequency signal processing module, which demonstrates the work of the mathematical model. Present a block diagram of the developed mathematical algorithm demonstrating phased operation of processing from low-frequency signal captured from human cerebral cortex. Obtained in the course research results, as well as the developed mathematical models and algorithms can be used in specialized medical institutions dealing with problems rehabilitation of the musculoskeletal system of the person. The purpose of such research — process and analyze low frequency signals taken from the human cerebral cortex, and the data obtained reveal the control signals for intellectual simulators to restore the musculoskeletal system of the person.
Clustering and Classification of Multidimensional Data by Kohonen's Cellular Neural Network
The paper presents experimental results of multidimensional data clustering and classification by help of Kohonen's cellular neural network (CNN). An important feature of our study is that Kohonen's CNN and visualization tools (self-organizing map (SOM), U-, H- and P-matrixes, coordinate maps, map of data classes) have been implemented in Microsoft Excel spreadsheet, without programming in VBA. The user interface of this spreadsheet model makes it easy to change the configurable parameters and visually observe the neural network learning process and data classification results using cluster grouping method.
A. A. Uskov, Professor, e-mail: email@example.com, A. G. Zhukova, Russian University of Cooperation
Neural Network Assessment Challenges IDEF-Charts
Considered neural network system for estimating the complexity of perception IDEF-human model, characterized by the use of expert-based method of paired comparisons for the data used for training multilayer perceptron, which allows for arbitrary IDEF-charts to predict its factor of perception, where you can make a comparison and optimization IDEF-models. The results presented in this paper may be useful in the construction of IDEF-models as well as the design of CASE-tools based on them.