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“Informatics and Applications” scientific journalVolume 10, Issue 3, 2016Content Abstract and Keywords About Authors INTEGRATION OF STATISTICAL AND DETERMINISTIC METHODS FOR ANALYSIS OF INFORMATION SECURITY.
Abstract: The paper is devoted to the methods of automatic analysis of information security and control mechanisms in cloudy computing environments. The considered approaches are based on synthesis of probabilistic and statistical and deterministic methods. The statistical analysis allows creating a set of objects for the deterministic (logical) analysis. As deterministic methods demand large volumes of calculations, preliminary statistical processing allows to reduce volumes of data for the deterministic (logical) analysis. In the paper, deterministic methods are presented by analogs of search of causal relationships. Application of heuristic and plausible reasonings can generate doubtful conclusions which are connected with random character of source data. Therefore, the analysis of random generation of deterministic conclusions is considered. The suggested methods of the analysis are focused on two-level architecture of information security system in cloudy computing environments. In this architecture, a slow automatic data mining generates at the top level fast reaction for resolution of conflicts in computing processes or identification of malicious code functioning. Keywords: cloudy computing environments; information security; probabilistic and statistical and deterministic (logical) methods of the analysis; heuristic algorithms; mutual influence of data ON RELATIONSHIP BETWEEN QUEUING SYSTEMS WITH RESOURCES AND ERLANG NETWORKS.
Abstract: The paper considers a model of a multiserver queuing system (QS) with losses caused by the lack of resources required to service customers. During its service, each customer occupies a particular amount of resources of several types. Random vectors, describing the requirements of customers to resources, do not depend on the arrival process and service times and are mutually independent and identically distributed with the general cumulative distribution function. Like in the Erlang problem, the task is to calculate the probability of losses of an arriving customer caused by the lack of resources. The paper shows the relationship between multiservice loss networks and queuing systems with resources, which makes it possible to solve the problem of calculating the loss probability in the queuing systems with resources using known methods developed for multiservice loss networks. Keywords: multiservice network; Erlang network; queuing system; queuing system with resources; random amount of resources; loss probability; arithmetic probability distribution ANALYSIS OF A QUEUEING SYSTEM WITH AUTOREGRESSIVE ARRIVALS AND NONPREEMPTIVE PRIORITY.
Abstract: The paper studies a single server queueing system with infinite capacity and with two arrival streams, one of which is Poisson and the other is batch Poisson. The customers from the first stream have nonpreemptive priority over the customers from the second. A feature of the system under study is autoregressive dependence of the sizes of the batches from the second arrival stream: the size of the nth batch is equal to the size of the (n - 1)st batch with a fixed probability and is an independent random variable with complementary probability Service times of the customers from each stream are supposed to be independent random variables with specified distributions. The main object of the study is the number of the customers from each stream in the system at an arbitrary moment.
Keywords: queueing theory; transient behavior; batch arrivals; nonpreemptive priority PERFORMANCE ANALYSIS OF A WIRELESS DATA AGGREGATION SYSTEM WITH CONTENTION FOR CONTEMPORARY SENSOR NETWORKS.
Abstract: The paper considers a wireless communication system with a number of sensing devices that transmit their data to multiple aggregating nodes connected to Internet via IEEE 802.11-2012 (WiFi) technology. It is assumed that an aggregator retransmits data from many sensors by competing with other aggregators for the shared channel.
Keywords: Internet of Things; wireless sensor networks; saturated system; regenerative analysis; WLAN; IEEE 802.11-2014 standard SIGNIFICANCE TESTS OF FEATURE SELECTION FOR CLASSIFICATION.
Abstract: The paper considers the problem of feature selection for classification and issues related to the assessment of the quality of the solutions. Among the different methods of feature selection, attention is paid to sequential procedures; the probability of the correct classification is used to measure the quality of the classification. To evaluate this indicator, it is proposed to use cross-validation and the bootstrap method. At the same time, to investigate the set of sample values of probability of the correct classification, it is suggested to use comparative analysis of confidence intervals and the test for homogeneity of binomial proportions. While constructing Bayesian classifier as the data model mixture of normal distributions is adopted, the model parameters are estimated by the expectation-maximization algorithm. As an experiment, the paper considers the problem of well-thoughtout choice of classification characteristics when predicting the type of urinary stones in urology. It is demonstrated that the set of used features can be reduced not only without losing the quality of decisions, but also with increase of probability of correct prediction of the stone type. Keywords: feature selection; sequential forward and backward selections; Bayes classification; test of homogeneity of binomial proportions; prediction of stone types in urology THE STRONG LAW OF LARGE NUMBERS FOR THE RISK ESTIMATE IN THE PROBLEM OF TOMOGRAPHIC IMAGE RECONSTRUCTION FROM PROJECTIONS WITH A CORRELATED NOISE.
Abstract: Methods of wavelet analysis based on thresholding of coefficients of the projection decomposition are widely used for solving the problems of tomographic image reconstruction in medicine, biology, astronomy, and other areas. These methods are easily implemented through fast algorithms; so, they are very appealing in practical situations. Besides, they allow the reconstruction of local parts of the images using incomplete projection data, which is essential, for example, for medical applications, where it is not desirable to expose the patient to the redundant radiation dose. Wavelet thresholding risk analysis is an important practical task, because it allows determining the quality of the techniques themselves and of the equipment which is being used. The present paper considers the problem of estimating the function by inverting the Radon transform in the model of data with correlated noise. The paper considers the wavelet-vaguelette decomposition method of reconstructing tomographic images in the model with a correlated noise. It is proven that the unbiased mean squared error risk estimate for thresholding wavelet-vaguelette coefficients of the image function satisfies the strong law of large numbers, i. e., it is a strongly consistent estimate. Keywords: wavelets; thresholding; MSE risk estimate; Radon transform PRECISION ANALYSIS OF WAVELET PROCESSING OF AERODYNAMIC FLOW PATTERNS.
Abstract: This paper is devoted to a new method of aerodynamic flow pattern processing based on the wavelet analysis. Wavelet thresholding techniques are widely used in signal and image processing. These methods are easily implemented through fast algorithms; so, they are very appealing in practical situations. Besides, they adapt to function classes with different amounts of smoothness in different locations more effectively than the usual linear methods. Wavelet thresholding risk analysis is an important practical task, because it allows determining the quality of the techniques themselves and the equipment which is being used. Comparative analysis using the discriminant method was carried out to verify the new method. The empirical estimated error of processing is consistent with theoretical results for this estimate. Keywords: wavelet analysis; thresholding; unbiased risk estimate; aerodynamic flow ANALYTICAL MODELING OF PROCESSES IN STOCHASTIC SYSTEMS WITH COMPLEX FRACTIONAL ORDER BESSEL NONLINEARITIES.
Abstract: Methods of analytical modeling for normal (Gaussian) processes in Gaussian and non-Gaussian stochastic systems with complex fractional order Bessel nonlinearities (spherical, modificated spherical, and Airy) are developed. Necessary information about Bessel fractional order functions is given. Coefficients of statistical linearization for typical fractional order Bessel nonlinearities are presented. Special attention is paid to the series algorithms. Analytical modeling algorithms have been developed for nonstationary and stationary normal processes. Test examples are presented. Main conclusions and generalizations are mentioned. Keywords: Airy nonlinearity; Bessel function of fractional order; Bessel nonlinearity; method of analytical modeling; method of normal approximation; method of statistical linearization; modificated spherical Bessel function; normal (Gaussian) process; spherical Bessel function; stochastic process ASYMPTOTIC EXPANSIONS OF MEAN ABSOLUTE ERROR OF UNIFORMLY MINIMUM VARIANCE UNBIASED AND MAXIMUM LIKELIHOOD ESTIMATORS ON THE ONE-PARAMETER EXPONENTIAL FAMILY MODEL OF LATTICE DISTRIBUTIONS.
Abstract: The paper considers a model of duplicate sampling with the fixed size n from a lattice distribution belonging to the natural one-parameter exponential family Asymptotic expansions of the mean absolute errors of the uniformly minimum variance unbiased estimator (UMVUE) and the maximum likelihood estimator (MLE) of the given parametric function are obtained in the case of infinite size of the sample. The case when G'[a] = 0 and G" [a] = 0 was studied separately. The relative error in calculating the difference in the mean absolute error UMVUE and MLE was evaluated in the case of the Poisson distribution for the two parametric functions. This error was received via the asymptotic expansions. It was found that the asymptotic results with a sufficiently large sample size allows one to compare UMVUE and MLE using such indicator of quality assessment as the mean absolute error. Keywords: exponential family; lattice distribution; unbiased estimator; maximum likelihood estimator; asymptotic expansion CHARACTERISTICS DEPENDENT ON THE BALANCE COEFFICIENT IN BAYESIAN MODELS WITH COMPACT SUPPORT OF A PRIORI DISTRIBUTIONS.
Abstract: Distributions of some characteristics dependent on the balance coefficient, which is defined as a ratio of two parameters that are interpreted as the parameter "obstructing" the functioning of the system and the parameter "conducing" the functioning of the system, are presented. In the queuing theory for M|M|1 models, such characteristics are interpreted as an average amount of claims in the system, the readiness coefficient, the probability that the claim will not be lost and as the marginal system's reliability for the discrete exponential reliability model. In the framework of the Bayesian approach, it is supposed that initial parameters are random and have a priori distributions with compact support. Keywords: Bayesian approach; mass service theory; reliability theory; mixed distributions; distributions with compact support "VIRTUAL COUNCIL" - SOURCE ENVIRONMENT SUPPORTING COMPLEX DIAGNOSTIC DECISION MAKING.
Abstract: The paper considers the problem of individual decision making during diagnostics of patients in outpatient clinics by the example of arterial hypertension diagnostics. It is proposed to raise the quality of individual decision making by means of consultations with the "Virtual council" decision support system, which models the work of physician councils in inpatient multifield clinics. The results of development and experimental research of the laboratory prototype of "Virtual council" are presented. Keywords: decision support system; virtual council; functional hybrid intellectual system THE OPTION TO CREATE A LOCAL COORDINATE SYSTEM FOR SYNCHRONIZATION OF SELECTED IMAGES.
Abstract: While comparing pairs of images, in most cases, the problem of misalignment of images arises in which one image is distortion of translation and rotation relative to another image. Such an image is quite difficult to compare in automatic mode. Existing methods of image pairs synchronize a large number of constraints due to which most of them are rarely used. The proposed option to create a local coordinate system for synchronizing images is based on the analysis of color spots presented on the images. It is assumed that successful synchronization of two images on their total amount of colored spots is to be found that match on the data images. For comparison, it is suggested to use colored spots and distances between spots. In order to successfully synchronize, one needs at least three colored spots, which would coincide in all modes of filtration. The experiments show acceptable results of synchronization. Keywords: algorithm; local coordinate system; color image; synchronization; pixel; colored spot; filtration SPEEDED-UP STEREO MATCHING USING GEODESIC SUPPORT WEIGHTS.
Abstract: In local stereo matching, the algorithms based on the adaptive support weights have good-quality results. This paper presents a modified version of the local matching with geodesic support. The proposed algorithm considerably reduces computation time at the cost of insignificant loss of quality that is experimentally confirmed with Middlebury Stereo Evaluation SDK. The key idea is to combine geodesic support weights and image segmentation for recoloring the reference image. This transformation makes it possible to use partial sums for matching cost computation. Keywords: stereo matching; segmentation; geodesic support weights WHAT IS BEHIND THE CONCEPT OF "KNOWLEDGE IN SMALL PACKAGES".
Abstract: An attempt has been made to analyze the electronic presentation ofeducational material as automated process. The reasons for the reduction of the length of video lectures for massive open online courses and other educational electronic resources as well as the requirement of reducing the time required for multimedia electronic educational resources and paragraphs of electronic tutor books are analyzed. It is shown that the reason for these requirements is not the resource duration, but rather the volume of the educational material that can be learned in one session. To determine the limits of this volume the amount of presented information, measured in terms of new concepts and related already learned concepts-links, was compared with the limited number of items processed in the human memory simultaneously. As a result, it is concluded that the requirement of reducing the length of lectures is necessary to limit the scope of the educational information presented. This circumstance has made it possible to formulate the concept of a task set and to make a proposal for automated training procedures. The paper is published in order to discuss this problem. Keywords: e-learning tools; microlearning; concept; link; "Miller purse;" task set; automated training HUMANITARIAN ASPECTS OF INFORMATION SECURITY.
Abstract: The paper analyzes humanitarian aspects of information security, which is regarded as the most important component of national and global security. It is shown that in modern conditions, the formation of the global information society and strengthening of geopolitical confrontation in the information space of information security of state, individual, and society is becoming a global problem for the further development of civilization. The humanitarian component of this problem comes to the forefront. The structure of humanitarian problems of information security is described. Priority measures for their solution in Russia are proposed. Keywords: global security; humanitarian issues; information security; information culture; information ethics; national security
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