Reviewerly/exHarmony huggingface dataset:
A morpho-technological analysis of bifaces from the Satani-Dar Locality in Armenia: a case study of the Late Acheulean with large flake bifaces in the Caucasus

In the Caucasus, one of the largest collections of Acheulean bifaces is known from the Satani-Dar locality in Armenia. Since the mid-20th century, bifaces from this site have been described using both traditional typological methods and a technological chaîne opératoire approach characteristics. In this paper, we report results of a morpho-technological analysis of biface reduction undertaken by L. Golovanova, verifying significance of variability in the morphometric datа using modern statistical methods. The analysis indicates that in the Satani-Dar site there are three biface groups, differentiated on the basis of morphological features. A comparison of the biface groups using statistical tests and principal component analysis confirms this apparent division. Our study indicates that these biface groups represent distinct tool models. The results suggest that a morphological variability is mainly related to the technological sequence applied to produce tools on different blanks. We discuss significance of these results for modern research of the Late Acheulean in the Caucasus.
Creativity of Modern Russian Writers in Teaching Russian Language to Tajik High School Students: Theoretical and Practical Aspects

In this article we are talking about the appeal in teaching the Russian language to the work of modern Russian writers who are known in Russia and abroad, when teaching the Russian language to Tajik high school students. As a work, the analysis of which can serve as an example for work in the lessons of Russian language and literature in a Tajik school, the story of Evgeny G. Vodolazkin “Kunstkamera in faces” was chosen. The article provides a rationale for its methodological value in teaching the Russian language, a linguistic analysis of the text is carried out, accompanied by tasks and exercises that are aimed at understanding the content of the text, at fixing the grammatical and lexical material used in it, and at developing students’ communicative skills. On this basis, it is recommended to work with the works of other contemporary Russian writers: Dina Rubina, Zakhar Prilepin. Lyudmila Ulitskaya, Lyudmila Petrushevskaya, Svetlana Mosova, Sergei Shargunov, Tatyana Tolstaya. The specific material presented is chosen taking into account the situation of the Russian language in the Tajik Soviet Socialist Republic and in modern Tajikistan. It is emphasized that the use of literary texts in the Tajik school has a long tradition of referring to the work of classic writers of Russian and Soviet literature, which requires, however, the expansion of the studied material at the expense of the works of contemporary Russian writers. Obviously, the study of the works of the 21st century will contribute to the interested study of the Russian language by Tajik students, as well as to acquaint them with the modern culture of the Russian people.
Identification of Signals Against Transformative Type Interference with Erasure

The problem of identification of two sources of binary signals against a background of transforming and erasing types of noise under counteraction conditions is considered. The situation is described by an antagonistic game, the analytical solution of which gives the optimal strategies of the players and the price of the game as a function of the a priori probability of the appearance of one of the sources. Particular cases are considered.
Sets of Nonbinary Sequences with a Low Level of Mutual Correlation for Systems of Digital Information Transmission

The sets of nonbinary pseudorandom sequences (NPSs) for periods N = p^S– 1 20 000 (p = 3, 5,7, and 11) generated in finite fields GF(pS) whose power is V = N + 1 and the maximum of the module of peaks of the periodic autocorrelation function (PACF) and periodic cross-correlation function (PCCF) satisfy the bounds obtained by Sidel’nikov. In addition to the minimal polynomials of elements α and α^2 , where α is a primitive element of field GF(p^S), the minimal polynomials of elements α and α^(i_d)(i_d is the decimation index) are determined on the basis of which the new sets of NPSs can be formed with the equivalent correlation properties. Sets of indices i_d 2 are determined for various combinations of parameters p and S. The cases of even and odd values of parameter S are considered, for which the values of the PACF and PCCF with the maximum module are obtained and the number and values of different levels of correlation functions are determined.
Method for the Formation of Non-Binary Gordon – Mills – Welch Sequences for Digital Information Transmission Systems

In this paper, we develop a method for the formation of non-binary Gordon–Mills–Welch sequences (GMWSs) with a period of N = p^(mn) – 1 that are formed over field GF(p) based on the generalization of the binary sequence formation method. An expression for calculating the vector of decimation indices А_m,n,r of the basic M-sequence (MS) for summable sequences in the synthesis of GMWS is obtained. A method for the formation of non-binary GMWSs for arbitrary MSs is presented. The values of the components of the C_m,n,r shift vector of a basic MS are shown to depend on the distribution of digits at the positions of the pth representation of the corresponding decimation indices.
Algorithm for Estimating the Spectral Correlation Function Using the 2D Fast Fourier Transform

An algorithm for estimating the spectral correlation function of cyclostationary random processes on the basis of their finite-time realization is proposed. The main algorithm steps are described and the main operations performed at each of them are formalized. The presented estimates of the spectral correlation function in the presence of a correlated stationary noise overlapping the analyzed cyclostationary random process in the frequency domain confirm the efficiency of the algorithm with a low signal-to-noise ratio. The number of required computational operations and the amount of computer memory required for storing intermediate results are estimated.
A parametric family of spline-based finite impulse response filters and a method for finding the optimal parameter

A new parametric family of filters with finite impulse response is proposed based on convolutions of splines with a rectangular impulse. An algorithm for searching for a parameter that optimizes the deviation of the amplitude-frequency characteristic in passbands and suppression bands. A numerical experiment was carried out, which involved comparing research of new filters with window filters and optimal Chebyshev filters.
Optimal Discrete Estimation of Reference Points of a Discrete-Continuous Markov Process against the Background of Correlated Markov Noise

In this paper, we solve the problem of synthesizing optimal and quasi-optimal algorithms for estimating the reference points of continuous components of a vector discrete-continuous Markov random process with allowance for the known statistical characteristics of additive Markovian correlated noise using the methods of the Markov theory of estimation of random processes. The method of difference measurements was used while synthesizing the algorithms. A block diagram of a quasi-optimal digital filter is given. Using a simple example, simulation shows the performance of a quasi-optimal algorithm in statistically uncertain situations.
Increasing the Quality Indicators of the Functioning of Fuzzy Solvers at the Defuzzification Stage

An approach to the implementation of the defuzzification procedure in microprocessor systems of fuzzy information processing is proposed. A computationally efficient model of the defuzzification operation is considered, based on the use of the concept of the measure of validity of a logical conclusion as a composition of the current values of the reliability of all elements of the conditional part of the rule that proposes this conclusion. The application of the approach provides a significant improvement in the quality of fuzzy approximation with little complexity of algorithmic and hardware-software tools. Examples of the use of this approach in practical problems are given.
SCENARIO OF INFORMATION FLOW ANALYSIS IMPLEMENTATION IN PL/SQL PROGRAM UNITS WITH PLIF PLATFORM

Formal proof of security measure effectiveness and computation security is vitally important for trust in critical information systems. It should be realized that formal security verification must be carried out at each infrastructural level (from the hardware level to the application level) in the process of system design. Currently, computation security analysis on the application level remains the major challenge as it requires complex labeling of computing environment elements. Traditionally, to solve this problem, information flow control (IFC) methods are employed. Unlike access control mechanisms widely used in modern operating systems (OSs) and database management systems (DBMSs), IFC has limited application in software design and mostly comes down to trivial taint tracking. This paper describes an approach to full-fledged implementation of IFC in PL/SQL program units with the use of the PLIF platform. In addition, a general scheme of computation security analysis for enterprise applications that work with relational DBMSs is considered. The key advantage of our approach is the explicit separation of functions between software developers and security analysts.
AUGMENTING THE TRAINING SET OF HISTOLOGICAL IMAGES WITH ADVERSARIAL EXAMPLES

In this paper, we consider the problem of augmenting a set of histological images with adversarial examples to improve the robustness of the neural network classifiers trained on the augmented set against adversarial attacks. In recent years, neural network methods have been developed rapidly, achieving impressive results. However, they are subjected to the so-called adversarial attacks; i.e., they make incorrect predictions on input images with added imperceptible noise. Hence, the reliability of neural network methods remains an important area of research. In this paper, we compare different methods for training set augmentation to improve the robustness of neural histological image classifiers against adversarial attacks. For this purpose, we augment the training set with adversarial examples generated by several popular methods.
3D SCENE RECONSTRUCTION AND DIGITIZATION METHOD FOR MIXED REALITY SYSTEMS

Mixed reality systems are a promising direction of research that opens up great opportunities forinteraction with virtual objects in the real world. Like any promising direction, mixed reality has a number of unresolved problems. One of these problems is the synthesis of natural lighting conditions for virtual objects, including the correct light interaction of virtual objects with the real world. Since virtual and real objects are located in different spaces, it is difficult to ensure their correct interaction. To create digital copies of realworld objects, machine learning tools and neural network technologies are employed. These methods are successfully used in computer vision for space orientation and environment reconstruction. As a solution, it is proposed to transfer all objects into the same information space: virtual space. This makes it possible to solve most of the problems associated with visual discomfort caused by the unnatural light interaction of real and virtual objects. Thus, the basic idea of the method is to recognize physical objects from point clouds and replace these objects with virtual CAD models. In other words, it implies semantic analysis of a scene and classification of objects with their subsequent transformation into polygonal models. In this study, we use competitive neural network architectures, which can provide state-of-the-art results. The test experiments are carried out on Semantic3D, ScanNet, and S3DIS, which are currently the largest datasets with point clouds that represent indoor scenes. For semantic segmentation and classification of 3D point clouds, we use the PointNeXt architecture based on PointNet, as well as modern methods of data augmentation in the process of learning. For geometry reconstruction, the Soft Rasterizer differentiable rendering method and the Total3Understanding neural network are considered.
APPLICATION OF SIMULATED COMPUTER SIMULATION TO THE TASK OF PERSONAL DEPERSONALIZATION DATA. MODEL AND ALGORITHM FOR DECONTAMINATION BY SYNTHESIS

The second part of the study on the topic of automated depersonalization of personal data is presented. The review and analysis of the prospects for research, performed earlier, is supplemented here by a practical result. A model of the depersonalization process is proposed, reducing task of ensuring anonymity of personal data to manipulation of samples of different types of random elements. Accordingly, the key idea of transforming data to ensure their anonymity, provided that utility is maintained, is to apply the synthesis method, i.e. complete replacement of all unpublished data with synthetic values. The proposed model identifies a set of element types for which synthesis patterns are proposed. The set of patterns compiles the depersonalization algorithm by the synthesis method. Methodically, each template is based on a typical statistical tool – frequency probability estimates, nuclear Rosenblatt-Parsen density estimates, statistical averages and covariances. The application of the algorithm is illustrated by a simple example from the field of civil air transportation.
SYMBOLIC ALGORITHM FOR FINDING ZEROS OF A SYSTEM OF &#x0D; OLOMORPHIC FUNCTIONS

Based on the Bochner–Martinelli integral representation, an algorithm for determining the number of zeros of a system of holomorphic functions is developed. We search for zeros of the system in a polycube. The use of computer algebra methods in this problem is due to the computational complexity of the developed algorithms and final results. The algorithm is implemented in Maple, which makes it possible to significantly facilitate the necessary computations.
AN ALGORITHM FOR DETECTING PRECIPITATION IN COMPUTER PROCESSING OF VIDEO IMAGES

The importance of detecting and reducing the visibility of precipitation in video images obtained by fixed cameras is shown. A statistical analysis of the geometric (area, shape factor, and orientation deviation from the frame average), and color–brightness (intensity and color saturation) characteristics of rain and snow particles is performed in order to substantiate decision rules for detecting pixels corresponding to precipitation particles. This analysis consists in obtaining distributions of the particle parameters and approximating them by known distribution laws using the family of Pearson’s curves, the Kolmogorov criterion, and the Nelder–Mead simplex algorithm. An algorithm for detecting raindrops and snowflakes in video sequences is developed, which is supposed to be used as part of an algorithm for reducing the visibility of precipitation. The proposed approach is presented in the form of a multistage classification of frame pixels into zones with moving objects and regions of a stationary background distorted and undistorted by precipitation particles in accumulated frames. Depending on the region to which the processed pixel belongs, the final decision to assign it to the class of precipitation is made using the proposed decision rules or the developed thresholding procedure with automatic determination of local threshold values. The proposed algorithm is experimentally investigated and, using a two-criteria approach, the optimal values for the number of accumulated frames for the correct operation of the algorithm are determined—100 frames for video images with rain and 140 frames for video with snow. The gain of the developed approach in comparison with the known estimates of the probabilities of false positives and false negatives is up to 1.7% and 9.1%, respectively.
APPLICATION OF COMPUTER SIMULATION TO THE ANONYMIZATION OF PERSONAL DATA: STATE-OF-THE-ART AND KEY POINTS

A new version of GInv (Gröbner Involutive) for computing involutive Gröbner bases is presented as a library in C++11. GInv uses object-oriented memory reallocation for dynamic data structures, such as lists, red-black trees, binary trees, and GMP libraries for arbitrary-precision integer calculations. The interface of the package is designed as a Python3 module.
AUTOMATED METHOD FOR OPTIMUM SCALE SEARCH WHEN USING TRAINED MODELS FOR HISTOLOGICAL IMAGE ANALYSIS

Preparation of input data for an artificial neural network is a key step to achieve a high accuracy of its predictions. It is well known that convolutional neural models have low invariance to changes in the scale of input data. For instance, processing multiscale whole-slide histological images by convolutional neural networks naturally poses a problem of choosing an optimal processing scale. In this paper, this problem is solved by iterative analysis of distances to a separating hyperplane that are generated by a convolutional classifier at different input scales. The proposed method is tested on the DenseNet121 deep architecture pretrained on PATH-DT-MSU data, which implements patch classification of whole-slide histological images.
TWENTY SIMILARITY FUNCTIONS OF TWO FINITE SEQUENCES

The article discusses the various numerical functions that determine the degree of "similarity" of the two given final sequences. These similarity measures are based on the concept we define of embedding in a sequence. A special case of such an attachment is the usual sub-subsequence. Other cases further require equality of distances between adjacent sub-sequence symbols in both sequences. This is generalization of the concept of a sequence segment (substring) in which these distances are unit. In addition, equality of distances from the beginning of the sequences to the first embedding symbol or from the last embedding symbol to the end of the sequences may be required. Except these last two cases, the attachment can be in a sequence several times. The literature uses functions such as the number of common attachments or the number of attachment occurrence pairs in a sequence. In addition to them, we enter three more functions: the sum of the lengths of total investments, the sum of the minima of the number of occurrences of a common embedding in both sequences and the similarity function based on the largest number of symbols of the common embedding. Intotal, 20 numerical functions are considered, for 17 of which algorithms (including new ones) of polynomial complexity are proposed, for two more functions, algorithms have exponential complexity with reduced a measure of degree. The Conclusion gives a brief comparative description of these investments and functions.
On Integral Funnel of Control Systems, Changed at Several Small Time Interval

A nonlinear control system in a finite-dimensional Euclidean space and on a finite time interval is considered, the dynamics of which changes significantly over several small sections from a given time interval. We study the degree of change in the reachable sets and integral funnels of the system under consideration when it varies in these sections. The corresponding changes are estimated in the Hausdorff metric.
On the Kinematic Description of the Motion of a Rigid Body

A system of ordinary differential equations is derived for a vector of finite rotation corresponding to Euler’s theorem: the vector of finite rotation is directed along the axis of finite rotation of a solid and its length is equal to the angle of plane rotation around this axis. The system of equations is explicitly resolved with respect to the time derivative of the components of the rotation vector. The right part of the system depends on the rotation vector and the angular velocity vector in the main axes. The equivalence of the obtained system of equations to the system of equations for quaternions is shown. The coordinates of the orts of the main axes of a rigid body in fixed axes are expressed in terms of the angles of final rotation and the components of angular velocity according to simple analytical formulas.
Research on Digital Application of the Bronze Carriage in Emperor Qinshihuang's Mausoleum Site Museum: Development of an Immersive Virtual Assembly System

Abstract: This paper discusses the design and development of an immersive virtual reality assembly system for the bronze carriage unearthed in Emperor Qinshihuang's Mausoleum Site Museum. First, it was necessary to obtain high-precision 3D data and texture mapping of cultural relics, which solved challenges in the process of data collection and processing. Then, the authors analyzed the structure of the bronze carriage and the requirements of the virtual assembly system. Finally, the authors described the design and development process of the system in detail. By considering the problems faced by human-computer interaction in the virtual environment, the system used HTC Pro VR helmet and the Unity3D engine. Therefore, it has the advantages of high simulation, good usability, and positive user experiences. The system provides researchers with a close virtual contact, which is of great significance for understanding the structure of the bronze carriage. This is an important practical work for the acquisition, processing, and application of high-precision 3D data of high-complexity and large-scale cultural relics. In addition, the digital data collected by the cultural relics play a key role in the protection, utilization, and dissemination of cultural heritage and can provide important support for multiple application fields and even the construction of intelligent museums.
The history of criminological research in the activities of the State Institute for the Study of Crime and the Criminal and the Irkutsk Cabinet in the 1920s

The 100th anniversary of the Institute of Legislation and Comparative Law under the Government of the Russian Federation (1923) makes us look at the role of the Institute in developing a methodology for studying crime and the criminal. The State Institute for the Study of Crime and the Criminal under the NKVD of the RSFSR from its foundation in 1925 actually became a center for the study of crime in the country. The Institute brought together specialists from completely different fields of knowledge about a person. Currently, the names of these scientists and leaders are not forgotten. These scientists are the pride of Russian legal science.
Identifying Factors Encouraging University Students to Play Computer Games

The study employed a quantitative research design using the general survey model to understand a large research population without intervening in variables. It involved 552 teacher candidates from an education faculty in Eastern Anatolia, Turkey, with 142 males and 410 females participating voluntarily. Data were collected using the Computer Game Motivation Scale (CGMS) with 17 items and five sub-dimensions (Concentration, Enjoyment, Escape, Learning, and Socialization), assessed on a five-point Likert scale (1 = Strongly Disagree, 5 = Strongly Agree). The reliability coefficients (Cronbach's Alpha) ranged from .77 to .95 for scale structures and were .94 for the entire scale. Internal consistency coefficients for sub-dimensions varied from .78 to .94, with .93 for the overall scale. The information form included gender, department/unit, perceived income status, and place of residence inquiries. Male students had higher gaming addiction scores than females, and those in verbal programs scored higher than numerical programs. 2nd and 3rd-year students had higher gaming addiction scores, and students with a perception of very poor income also scored higher in gaming addiction. Interestingly, the place of residence did not significantly affect gaming addiction, likely due to widespread internet and technology access. In summary, this study highlighted how gender, program, class level, and income perception impact gaming addiction among university students, while place of residence does not seem to play a significant role.