scholarly journals Semantic analysis of fluctuations of a radar pack for identification of air objects

Radiotekhnika ◽  
2020 ◽  
pp. 197-203
Author(s):  
V. Zhyrnov ◽  
S. Solonskaya

A method for semantic analysis of amplitude fluctuations of the radar pack to identify air objects in surveillance radars has been developed and implemented in software. This method is based on the determination of semantic components at the stage of formation and analysis of the symbolic model of a burst of impulse signals from mobile aircraft. Signal information is described by the predicate function of the process knowledge of the formation and analysis of the symbolic model of a burst of impulse signals from mobile aircraft such as an airplane, helicopter, UAV, and from atmospheric inhomogeneities of the angel-echo type. As a result of semantic analysis of the amplitude fluctuations, classification distinguishing attributes of fluctuations from interfering reflections and air objects are obtained. The semantic components of the decision-making algorithm, which are similar to decision-making algorithms by the operator, are investigated. In the developed algorithm, the signal information is described by a predicate function on the set of amplitudes of burst pulses exceeding a certain threshold value. Identification of the types of fluctuations is carried out by solving the developed equations of predicate operations. Based on these equations, a functional diagram of automatic determination of the fluctuation types is synthesized. The verification of the developed method was carried out on real data obtained on a survey centimeter-band radar (pulse duration 1 μs, sounding frequency 365 Hz, survey period 10 s). Based on these data, types of characteristic packs of radar signals are simulated. According to the results of the experiments, they were all correctly identified.

Radiotekhnika ◽  
2021 ◽  
pp. 115-121
Author(s):  
V. Zhyrnov ◽  
S. Solonskaya ◽  
V. Zarytskyi

The article discusses a method for dealing with non-stationary natural and simulating interference in intelligent surveillance radars. When creating simulating marks, the introduction of amplitude modulation into the relayed radar sounding signal is used. As a result of the analysis, it was possible to find out that in the imitating noise, in this case, the so-called "intelligent" fluctuations of the burst structure of false marks appear, which differ from the fluctuations of the packs of real marks and can be easily detected by a human operator. The method is based on the definition of semantic components at the stage of formation and analysis of a symbolic model of amplitude fluctuations of a burst of signals from non-stationary natural and simulating interference and from real moving objects. In this case, the semantic features of amplitude fluctuations are determined by solving predicate equations for transforming these fluctuations into symbolic images of noise marks and real mobile aircraft. As a result of semantic analysis of the amplitude fluctuations of the burst in the time domain, classification distinctive features of fluctuations in the burst of signals from natural imitating noise and air objects were obtained. The semantic components of the decision-making algorithm are investigated, which are similar to the decision-making algorithms by a human operator. Process knowledge of transforming radar signals into symbolic images of amplitude fluctuations of a burst in the time domain is formalized. The formalization of the processing of symbolic images includes a system of predicate equations, by solving which the types of amplitude fluctuations of the burst are identified. Based on the results of experimental data, the transformations of real radar signals into symbolic images of burst fluctuations were carried out on the basis of the algebra of finite predicates. The authors also managed to propose these transformations to be used as the basis of an effective toolkit for obtaining classification distinctive features of packet fluctuations from interference and from aircraft.


2018 ◽  
Vol 19 (2) ◽  
pp. 104-120
Author(s):  
Maulana Khusen

Abstract: The results of the study show that: (1) Tahfidzul Qur'an learning planning is done through the preparation of memorization targets and the determination of effective weeks and days in each semester; (2) Organizing is carried out through the division of tasks and responsibilities as well as the construction of the structure of the tutoring teacher; (3) The mobilization is carried out through the coordination meeting of the Tahfidz coordinator as a shering forum for decision making and direction of the Tahfidzul Qur'an learning program and the implementation of learning is carried out every Monday-Friday; and (4) Supervision is carried out through assessing teacher performance at the end of December and June. The highest achievement target for the second year of the implementation of the Tahfidzul Qur'an's 2017/2018 year program is juz 29 and 30, the lowest target for class 1 is juz 30 to Surat al Ghosyiyyah. For class 1, 85% of the target is achieved and 11% of students exceed the target. Class 2 targets reached 19%. Class 3, 10.86% reached the target and 0.35% of students exceeded the target. Class 4 tarjet reached 12.44%. Class 5 targets reached 4.24%, and the last grade 6 target reached 13.79% and 1.5% of students exceeded the target. Keywords: Learning Management, Tahfidzul Qur'an.


Author(s):  
P.L. Nikolaev

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.


Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1554
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Muzafer Saračević ◽  
...  

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn.


2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.


2021 ◽  
pp. 107754632110069
Author(s):  
Sandeep Sony ◽  
Ayan Sadhu

In this article, multivariate empirical mode decomposition is proposed for damage localization in structures using limited measurements. Multivariate empirical mode decomposition is first used to decompose the acceleration responses into their mono-component modal responses. The major contributing modal responses are then used to evaluate the modal energy for the respective modes. A damage localization feature is proposed by calculating the percentage difference in the modal energies of damaged and undamaged structures, followed by the determination of the threshold value of the feature. The feature of the specific sensor location exceeding the threshold value is finally used to identify the location of structural damage. The proposed method is validated using a suite of numerical and full-scale studies. The validation is further explored using various limited measurement cases for evaluating the feasibility of using a fewer number of sensors to enable cost-effective structural health monitoring. The results show the capability of the proposed method in identifying as minimal as 2% change in global modal parameters of structures, outperforming the existing time–frequency methods to delineate such minor global damage.


Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 766
Author(s):  
Rashad A. R. Bantan ◽  
Ramadan A. Zeineldin ◽  
Farrukh Jamal ◽  
Christophe Chesneau

Deanship of scientific research established by the King Abdulaziz University provides some research programs for its staff and researchers and encourages them to submit proposals in this regard. Distinct research study (DRS) is one of these programs. It is available all the year and the King Abdulaziz University (KAU) staff can submit more than one proposal at the same time up to three proposals. The rules of the DSR program are simple and easy so it contributes in increasing the international rank of KAU. The authors are offered financial and moral reward after publishing articles from these proposals in Thomson-ISI journals. In this paper, multiplayer perceptron (MLP) artificial neural network (ANN) is employed to determine the factors that have more effect on the number of ISI published articles. The proposed study used real data of the finished projects from 2011 to April 2019.


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