bluuebunny/crossref_metadata_2025 huggingface dataset:
The External Technological Context of Artificial Intelligence in Financial Services
Authors:   Bucharest University of Economic Studies, Romania, DUTESCU Adriana , MIHAI Mirela-Simina
Published: November 2023

The purpose of this research is to improve the understanding of the external technological context of Artificial Intelligence applied in financial services, together with other technological solutions such as digitization, automation, cloud computing and licensing. The authors studied the external technological context by analyzing the technology providers that are represented by the companies with CAEN code 620 – Service activities in information technology. The purpose of this study was to obtain and analyze answers to six research questions, as follows: what is the role of service providers, what are the other technologies offered by them together with Artificial Intelligence, how can this technology be effectively implemented, what is the involvement users in application development, if there will be specific training and what is the level of implementation of Artificial Intelligence in financial services. The authors found that often the investigated companies use their technology services only for banks, Fintech and large financial companies. Therefore, for small and medium-sized companies, the service providers included in the study are not suitable, and further research should be carried out in this regard. An interesting result emerged from the study of long-term relationships between the technology company and the financial company to improve the solutions and provide the necessary maintenance services until the solutions provide results with close to 100% accuracy.
Modeling of Landscape Features by Means of Point Clouds in Virtual Environment Systems
Authors: Timokhin P.Yu. , Mikhaylyuk M.V.
Published: November 2023

The paper studies the direction of modeling and visualization of procedural objects in virtual environment systems, using hardware-accelerated ray tracing. In particular, the task of modeling objects defined by point clouds is considered, exemplified on landscape elements with negative slopes (caves, tunnels, cliffs, etc.). An approach to solve this task on the ray tracing pipeline is proposed, based on constructing bounding boxes, inside which cloud points retain proximity to each other. The paper describes methods and algorithms of forming such local point groups and bounding boxes, basing on a sparse voxel octree. Based on methods and algorithms proposed, a software complex was implemented and tested on a number of point clouds. The approbation showed that developed solution allows landscape features containing tens of millions of points to be modelled in real-time without consuming the power of unified GPU cores. The solutions obtained can be applied in virtual environment systems, scientific visualization, video simulators, geoinformation systems, etc.
Application of Discontinuous Particle Method to Problems with Viscosity and Its Visualization
Authors: Bogomolov S.V. , Kuvshinnikov Artyom Evgenyevich
Published: November 2023

In past papers it has been shown that the discontinuous particle method copes well with computational fluid dynamics problems having a strong gradient, the problem of oblique stress jump formation being an example. This paper deals with the application of the discontinuous particle method to viscosity problems. In the study, a one-dimensional Burgers equation with an initial condition in the form of a smoothed wave and a two-dimensional Blasius problem were taken. Numerical experiments showed the correspondence of the obtained solution to the analytical one, but in the two-dimensional case the performance of the algorithm drops strongly due to the necessity to determine the neighbours of the particle. It is concluded that the discontinuous particle method can solve viscosity problems in the one-dimensional case, but modifications of the existing algorithm are required for higher dimensional cases. The application of the discontinuous particle method to viscous problems was studied as part of a general comprehensive study of the comparative accuracy of numerical methods on reference solution.
Visualization of Supersonic Flow Around Wing Tandem
Authors: Kostantinovskaya Tatiana Vitalievna , Borisov Vitaly Evgenyevich , Lutsky Alexander Evgenievich
Published: November 2023

The paper presents the analysis results of the supersonic flow around a wings tandem using the methods of scientific visualization. Two tandem configurations were considered, differing from each other by the vertical position of the generator wing relative to the plane of symmetry of the main wing. The data are obtained as a result of numerical simulations carried out with the Mach number of the incoming flow M? = 3. In the model the wings were straight, rectangular in plan with sharp front, side and trailing edges with the same chord and the span of the main wing exceeding the span of the generator wing by two times. The generator wing was located at an attack angle of 10° degrees to the incoming flow, the main wing is located at zero attack angle. The simulation was carried out on the basis of URANS equations with the Spalart-Allmaras (SA) turbulence model. Numerical calculations were carried out on the hybrid supercomputer system K-60 at the Keldysh Institute of Applied Mathematics RAS. An approach using the Liutex criterion for the vortex structures identification was applied for scientific visualization of the simulation results.
Visualization of Interstructural Collaborations in Publication Activity of Teaching Staff
Authors: Masalsky L.S. , Logunova O.S. , Ilina E.A. , Arefeva D.Y.
Published: November 2023

In this paper visualizing module developed by authors for data analysis of publication activity of educational organization is considered. The relevance of scientometrics visualizing usage is substantiated. Graph models used for interstructural and intrastructural collaborations are described. Technological solutions for combined evaluation of quantitative and qualitative properties using the visualized models are presented. The ability to use the system for retrospective and variability analysis is marked. The drawbacks of proposed methods of graph visualization are identified and alternative ways for improving the image quality are proposed. Based on the results of testing by Nosov Magnitogorsk State Technical University scientometrics department staff, practical appropriateness of proposed methods and solutions for decision-making on building the research teams is proved.
Forecasting and Management of the Process of Career Guidance Classification in Groups of Technical Specialties
Authors: Tarasova Iuliia , Andreev Vyacheslav , Farafontov Maxim , Toskin Denis
Published: November 2023

This paper is devoted to the evaluation of the results of the introduction of the ColourUnique Pro career guidance software package into the process of career guidance support in control groups of subjects tested on the basis of the technical University. The peculiarity of the testing methodology used in the research is the generation by the subject of a unique color image that characterizes the individual style of activity. The types of personalities that are more common in creative and technical environments have been derived, which allows forecasting and management in the process of career guidance support of an individual. However, in a larger sample, a previously rarely encountered type of individual made itself felt, which was not previously considered characteristic of the technical environment, which may be erroneous. In the paper, the authors make the assumption that they can predict such images.
Transformations of Macadam Ellipses in a Wide Range of Brightness
Authors: Budak Vladimir Pavlovich , Delian Ruzana Ashotovna
Published: November 2023

In the utilitarian and interior lighting of the last decade, light-emitting diodes (LED) are becoming increasingly popular. This is due to the advantages of this light source, which include: high energy efficiency, long service life, ease of light flow control and environmental friendliness. All this allows LED to displace discharge light sources from the market. However, the use of LED in artificial lighting began relatively recently, which determines the need for a better study of the features of the light source and the constant improvement of the regulatory framework. The uniformity of the chromaticity of the radiation is estimated using the color thresholds obtained in the Macadam experiment and called by their shape – Macadam ellipses. This experiment was conducted under the same observation conditions. Their application in practice is limited and requires research in a wide range of observation conditions. In this paper, two models are considered: the CIECAM02 color perception model, which is approved by the ICO (International Commission on Lighting) and the Belyaeva–Matveev model, developed in 1964, at the MPEI. The choice of the second model is due to the fact that it is more accurate in comparison with the generally accepted CIELUV and CIELAB models. A study of the transformation of Macadam ellipses in two models was carried out under changing observation conditions in both brightness and chromaticity and further comparison of the results obtained. The data obtained allow us to speak about the relevance of further studies of the perception of white color radiation in wide ranges of chromaticity and brightness to improve the algorithms of the color perception model.
Visualization of Water Flow by Multicolor PIV
Authors: Usmanova S.S. , Skornyakova N.M. , Sapronov M.V. , Sofuyev D.V. , Kuchmenko A.V. , Netkachev V.V.
Published: November 2023

The work is devoted to the study the water flow structure formed in a glass tube with an outer diameter of 10 mm by multicolor particle image velocimetry (MPIV). The multicolor particle image velocimetry method is one of the modern modifications of the particle image velocimetry. The main difference between MPIV and classical particle image velocimetry is the number of probing laser planes. Three laser planes of red, green and blue radiation are supposed to be used for MPIV measurements. Such modernization makes it possible to visualize the flow structure and obtain velocity vector fields simultaneously in three planes. The paper formulates an algorithm for carrying out MPIV measurements and processing the recorded data. An experimental setup was developed and assembled, a series of MPIV measurements was carried out, the structure of the water flow was visualized, velocity vector fields in three laser planes were obtained, velocity distributions in the horizontal section of the tube were constructed.
3D Approach to Visualization of Error Function in the Neural Network Tuning Problem
Authors: Khaniev R.E. , Diane S.A.K.
Published: November 2023

The report presents an approach to visualization and analysis of the effectiveness of a neural network using one-dimensional and three-dimensional graphs. A generalized block diagram of algorithmic support for solving the problems of configuring and visualizing neural network models is proposed. As part of the study of the influence of several macroparameters on the quality of network learning, particular one-dimensional dependencies of RMSE errors and a generalized three-dimensional error function are given, which takes into account the number of neurons in the hidden layer, the number of training examples and the number of training epochs. Software implementation of algorithms for calculation, training and visualization of neural networks is carried out in Python. The analysis of the obtained three-dimensional graph made it possible to conclude about the nonlinear nature of the obtained multidimensional dependence and to determine the best combination of macroparameters using the expert evaluation function.
DINONAT: Exploring Self-Supervised training with Neighbourhood Attention Transformers
Authors: Kniaz Vladimir Vladimirovich , Knyaz Vladimir Alexandrovich , Moshkantsev Petr Vladislavovich , Melnikov Sergey
Published: November 2023

Data-driven methods achieved great progress in wide variety of machine vision and data analysis applications due to new possibilities for collecting, annotating and processing huge amounts of data, with supervised learning having the most impressive results. Unfortunately, the extremely time-consuming process of data annotation restricts wide applicability of deep learning in many applications. Several approaches, such as unsupervised learning or weakly supervised learning has been proposed recently to overcome this problem. Nowadays self-supervised learning demonstrates state-of-the-art performance and outperforms supervised one for many tasks. Another state-of-the-art neural network models are transformer networks, that can rich high performance due to flexibility of the model. Moreover, the quality of the annotation directly influences the quality of the network operating. From this point of view it is important to analyse what features the network uses during the training process. The study of the self attention mechanism allows to identify these features, and use it in annotation process. The current study addresses the problem of self-supervised learning of transformer networks as a promise approach for making a step forward in self-adapting of neural network models. Specifically, we study the the cross-modal applicability of self-supervised learning using Transformer network pretrained on color images for data distilling in thermal images datasets. The results of evaluation demonstrate that Transformer network based on self-attention mechanism identifies the same features both in color and in thermal image datasets.
Deep Learning-based Polygonal Mesh Reconstruction from Point Clouds for Mixed Reality Visualization
Authors: Sorokin Maxim Igorevich , Zhdanov Dmitri Dmitrievich , Zhdanov Andrei Dmitrievich
Published: November 2023

Mixed reality systems create new forms of interaction between the physical and digital world by overlaying digital elements on the physical environment or creating virtual environments with physical elements. A key component for mixed reality are 3D scanning systems that capture the shape and texture of objects or scenes in the form of point clouds. For effective use of these data in mixed reality applications, they are transformed into polygonal meshes suitable for rendering, animation, and interaction. The proposed method includes the application of ResNet blocks for feature extraction, the use of an autoencoder to obtain latent 3D shapes, and the definition of wall and ceiling geometry using bounding boxes. The method allows obtaining a complete 3D model of the scene from a point cloud using deep learning and geometric analysis. In this work, two datasets were used for training and experiments: ShapeNet and ScanNet. These datasets represent a large and diverse collection of three-dimensional objects and scanned scenes with detailed annotation.
Data Augmentation Based on Wavelet Filtration During Neural Network Training
Authors: Alimagadov Kurban Alimagadovich , Umnyashkin Sergei Vladimirovich
Published: November 2023

The research is devoted to studying the influence of data augmentation by means of wavelet filtration on recognition accuracy of noised images by the neural network detector. It is proposed adding noise to samples of the training dataset and then processing them by Wiener filter in the domain of discrete wavelet transform (DWT). Generating of input training images uses the model applying white additive Gaussian noise to distort them. In addition to the Wiener filtering, we considered some thresholding methods in the domain of DWT for images denoising. Based on the obtained experimental data, we compare the results of the detector recognition for the different values of noise standard deviation. Also, we considered the case, when the neural network was trained on noised-augmented images without subsequent filtering. It is shown that the proposed approach allows higher accuracy of recognition to be achieved, than the augmentation, which doesn’t use noise suppression.
Polyhierarchical Image Structure and Invariant Object Detection
Authors: Kharinov Mikhail Vyacheslavovich
Published: November 2023

The paper is related to interdisciplinary research in cluster analysis of big data and primary data acquisition from a color image for object detection using the optimal piecewise constant image approximations with a really minimized total squared error or RMSE. Image segmentation is performed via pixel clustering. Ward's clustering is considered as the main method for minimizing RMSE. For Ward's method, the variability property is disclosed, which consists in a pronounced dependence of RMSE obtained for a given color number on the calculation algorithm or slight modification of input data. To overcome excessive computational complexity avoiding timeconsuming programming, parallel execution of pixel clustering algorithms is used with simultaneous selection of approximation hierarchies that reach RMSE minimums for the color numbers in a given range. The problem of invariant hierarchical object segmentation regardless of the image content is studied. The solution is provided by adjusting the tuning parameters from the condition of segmentation invariance in the given image content. The experiments are presented.
Influence of the Accuracy of Estimation of Coordinates of Reference Areas on the Accuracy of Image Registration
Authors: Babayan P.V. , Kozhina E.S.
Published: November 2023

The problem of estimating the accuracy of geometric registration of images when using registration methods based on the choice of reference areas is considered. As a mathematical model of geometric transformations of images, a scale-shift transformation is used, which is typical for stationary video surveillance systems equipped with a rotary device and a camera with a variable focal length. The choice of reference areas is carried out by a multi-reference algorithm with a random search for reference points. Expressions are given for the correlation matrix of errors in determining the parameters of geometric transformations and the correlation matrices of alignment errors at different points of the image. The dependence of the variance of the alignment error on the coordinates of the reference areas is obtained. Experimental studies were carried out on full-scale images formed in the vehicle traffic control system. The results obtained can be used in the development of algorithms for image stabilization, selection of moving objects, detection of scene changes.
Influence of Non-Equilateral Apertures on the Characteristics of Digital Filters "Truncated Pyramid" Laplacian and "Double Pyramid" Laplacian
Authors: Kupriyanova K.S. , Rylov K.A. , Kamenskiy A.V.
Published: November 2023

In the process of processing digital images, an important role is played by increasing the efficiency of the applied methods and processing algorithms. One way to improve efficiency is to convert spatial filters into recursively separable digital filters. The use of such filters makes it possible to reduce the number of computational operations. This article presents digital recursively-separable Laplacian filters "truncated pyramid" and "double pyramid" converted into non-equilateral form. This transformation allows to further reduce the number of computational operations and speed up the processing. Also, the article discusses the principle of operation of these filters, their structure and operation algorithm. Based on the results of image processing by a digital recursively separable filter Laplacian "double pyramid", the quality of processing by a filter with a base mask of 7x7 elements and non-equilateral apertures is evaluated and compared.
Strokes classification of handwritten text based on the Frechet distance
Authors: Pronina N.M. , Mestetskiy Leonid Moiseevich
Published: November 2023

The paper aims to develop an interpretable similarity metric of the calligraphic handwritten elements, strokes. The need for such a metric often arises in text navigation tasks. To extract strokes, the text is converted into a binary image and a skeletal representation is constructed for all connected components. It provides accurate information about how the pen moved while writing the text. Next, the skeletal representation is sliced into a geometric graph. The strokes are formed as subgraphs. As a result, the new method is proposed which is based on the use of Frechet distance between plane curves. The presented metric has been applied to the tasks of stroke classification and letter recognition based on stroke bigrams and trigrams.
Detection, localization and Transformation of twoDimensional Graphic Code
Authors: Trubitsyn A.A. , Shadrin M.V.
Published: November 2023

The ROI of the article relates to computer vision. Mathematical foundations and algorithms for preparing two-dimensional graphic codes for data decoding are presented. The preparation stages include the detection, localization and transformation of the code to a decoding-friendly form. The brightness oscillation function proposed in the paper serves to reliably detect codes in the image, the Hough transform is the basis for solving the localization problem, and the formulas for the inverse transformation of a square into an arbitrary quadrilateral allow you to transform localized quadrangular areas into squares with a horizontally oriented base. The work of algorithms on a set of test and real images is studied, the practically permissible level of distortion during the transformation of detected and localized two-dimensional codes into the original square form is shown.
Interphase FISH-analysis Processing of Chromosomal Mosaicism on Blood Cell Nuclei Preparations
Authors: Trykin Alexander Mikhailovich
Published: November 2023

Fluorescence in situ hybridization (FISH) is a molecular cytogenetic technique. It provides a powerful tool for understanding genetic and genomic processes, diagnosing genetic disorders, and studying the structure and function of genes and chromosomes. This paper proposes a method for automatic object segmentation of preparations of blood cell nuclei and a method for detecting chromosomes with the aim of further studying them for chromosomal mosaicism. Based on the data provided by the laboratory of the Institute of Biology and Biomedicine of Lobachevsky University, the SOTA deep learning model YOLOv8-seg was trained. This was made possible by marking up a small portion of the 87 images. Experiment on model training for segmentation showed very good quality metrics: Precision = 0.940, Recall = 0.980, mAP[0.5] = 0.991 and mAP[0.5:0.95] = 0.764. After that, a method for detecting chromosomes was proposed, based on the classical principles of image processing and computer vision, due to the lack of the necessary labelled data.
The problem of Data Augmentation in the Preparing of Three-Dimensional Medical Datasets
Authors: Vasiliev Evgeni Pavlovich
Published: November 2023

The task of three-dimensional data augmentation is computingly coslty and may require a large number of calculations and slow down the process of teaching deep models. You can reduce learning time by optimizing the use of augmentations during training. The article discusses various tools for threedimensional data augmentation: BatchGenerators, Torchio, Rising. The working time of the common three-dimensional augmentations is given: rotation, flip, data crop, blur, application of affine transformations and changes in the size of three-dimensional data on the central processor (CPU) and graphic accelerator (GPU). The advantage of performing augmentation on the GPU in comparison with the CPU is demonstrated, the resulting acceleration is 1-2 orders for most augmentations. A comparison of the time of various augmentations relative to each framework is presented for a more visual choice of augmentations with an emphasis at their time.
Mobile Laser Scanning of Urban Roads: Cost Estimation for a High-quality Result
Authors: Grebenyuk E.A. , Rotkov Sergei Igorevich
Published: November 2023

Mobile laser scanning is the most comprehensive type of engineering surveys for the preparation of information models of highways with adjacent infrastructure. This article presents the author's observations based on the processing of the results of mobile laser scanning of roads of the regional center of the Russian Federation in the summer of 2021 as part of the tender for updating the CSODD (comprehensive scheme organization of road's traffics) for urban roads subordinated to the regional transport committee. The article also provides numerical formulas to use it to estimate the labor costs for conducting and processing scanning results (expressed in man-hours and rubles), which can be used to calculate the preliminary cost of public tenders for conducting and processing the results of mobile laser scanning of public roads. So, for 1000 km of urban roads, the price can range from 59.6 million to 150.1 million rubles in prices for the middle of 2023.
Application of Artificial Intelligence in Remote Monitoring Data Processing Tasks
Authors: Gromov Yuri Yurievich , Ishchuk Igor Nikolaevich , Rodionov V.V.
Published: November 2023

This article presents a method for classifying multi-time multispectral images of the Earth's surface using the convolutional deep learning neural network U-net. Images of visible and infrared wavelengths were obtained using a multispectral optoelectronic system of an unmanned aerial vehicle and were used to construct orthophotoplanes of the terrain. Based on the data obtained, a neural network was trained to solve the problems of detecting man-made objects. The method of intelligent recognition of remote monitoring objects, based on deep learning and assessments of thermophysical parameters, allows you to create a phono-target environment using a genetic algorithm. This algorithm solves the coefficient inverse problem of thermal conductivity and provides estimates of the thermophysical parameters of materials. To train the model, 18 classes of objects were introduced, which were studied based on the difference in thermal contrast between man-made objects and the background (anthropogenic or natural landscape). The survey of the earth's surface was carried out 6 times during the day with an interval of 4 hours. The experiment was conducted in the summer of 2021, on specific dates of August 4-5. In the tasks of detecting and classifying man-made objects, it was found that the model demonstrates applicability with varying reliability. The conducted research shows that during the operation of the model, the desired classes of objects were discovered.
Descriptive Geometry for Designers
Authors: Knyazeva E.V.
Published: November 2023

The work highlights the problems of improving geometric-graphic training in modern education. The stages of formation of a new structure of the course “Descriptive Geometry” for design students are analyzed. Stage 1 - search, is presented by the author's elective course for pre-university preparation "Descriptive Geometry and Engineering Graphics", consisting of two structurally and methodologically coordinated sections: Descriptive Geometry and Technical Drawing - 10th grade, Engineering Graphics - 11th grade. Stage 2 - constructed and filling, presented by an analysis of dissertation research and educational materials from leading universities in St. Petersburg and Moscow. Course sections are accompanied by brief thematic content. A list of educational, methodological and information support developed for lectures, practical classes and independent work is provided. Examples of geometric-graphic and creative tasks, as well as models of geometric surfaces and folded reliefs, made by design students as part of their learning processes and included in the methodological fund of the Higher School of Design and Architecture of St. Petersburg Polytechnic University. The issues of interdisciplinary integration of geometric and graphic tasks into artistic disciplines, tested and introduced into the educational process at the Higher School of Design and Architecture of Peter the Great St. Petersburg Polytechnic University, are touched upon.
Experiments with a Number of Convolutional Neural Networks for Evaluating the Super-Resolution Technique
Authors: Strokova A.V.
Published: November 2023

The work is devoted the study of the models of convolutional neural networks SRCNN, FSRCNN, and SubPixel CNN, which solve the Super-Resolution task, for finding the optimal parameters during the training stage. To evaluate the results, the standard PNSR metric was used, BSD was taken as the dataset. During analyzing activation functions and optimizers from the PyTorch library, the best combinations, that give a higher quality metric, were identified. Using the weights of the three best combinations obtained, a comparative characterization of the images belonging to the classes of text, face, night, nature, and the generated image was given. The conclusion is made about the evaluation of a particular architecture to obtain an image of a certain class. The finishing results can be used in further studies for improving the productivity and accuracy of SuperResolution methods.
Automatic Identification and Description of Surfaces in 2D Drawings
Authors: Kasimov D.R. , Koroleva M.R. , Chernova A.A.
Published: November 2023

The paper describes one of the stages of building an automated system for technological preparation of production. Generalized algorithms for the formation of the technological process and the route technological process are presented. As part of the automation of the design of technological processes, the task of preparing the initial information for creating a digital route map of the technological process in a semi-automatic or automatic mode is solved. A standard two-dimensional drawing of a part acts as design documentation at the input to the design system. The software system used in the work allows identifying and describing the main types of surfaces presented in the drawing. The program works with a graph representation of a drawing image, which can be preliminarily vectorized. The paper describes the stages of drawing processing, as well as a flowchart of the recursive procedure, which is the core of the identification of the main surfaces. The information obtained during the identification process allows proceeding to the next stage of the route technological process - the choice of types of part processing.
Application of Coons and Gordon Surface Modeling Apparatus in Reverse Engineering of Turbomachinery Components
Authors: Krylova Elizaveta E. , Slyadnev Sergey Evgenjevich , Turlapov Vadim Evgenjevich
Published: November 2023

The article discusses a pragmatic approach to surface modeling of turbomachinery components using the Koons and Gordon surface apparatus. These surface modeling techniques are used to prepare CAE models from highly detailed and often unusable computational models. A rationale is given for the usefulness of the Koons-Gordon algorithm in the field of turbomachinery, as well as its application in various geometric scenarios. A positive feature of the algorithm is the possibility of more flexible adjustment of models when new structural patterns are discovered during the development of a patch, having only four curves as input. The result is a 3D mesh generated from a set of surfaces. The motivation for the work was that at the moment there was no open source project capable of building such a mesh from a set of Coons patches. The presented Gordon surface interpolation algorithms are implemented and published in the open source CAD system “Analysis Situs”.
Study of the Possibility of Parallelization of the Lempel-Ziv- Welch (LZW) Algorithm in Import-Substituting Telecommunication Multimedia Technologies
Authors: Vasin Dmitry Yurievich
Published: November 2023

The article discusses the results of the author's research in the field of serial/parallel compression of one-dimensional, adaptive audio signals. An overview of many well-known compression algorithms is provided, including the basic LZW algorithm and its components, and a detailed analysis of two parallelization schemes is presented: a serial time scheme divided into several parts for compression, and parallelization using a prefix tree using expansion inner loops. The possibility of parallelization of the LZW algorithm for compression and evaluation of its performance is investigated. An estimation of acceleration according to Amdahl's law and an estimation of scaling due to an increase in the number of threads and processes are described. The results of experiments comparing serial and parallel LZW algorithms in terms of compression ratio, quality, and computational complexity are presented.
VR-simulator for Driver Training in an Urban Environment with Difficult Terrain and Meteorological Conditions
Authors: Ermolaeva A.D. , Eliseev M.E. , Tomchinskaya Tatyana Nikolaevna
Published: November 2023

The development of a hardware-software-information complex of a VR simulator for training drivers in the environment of a large city with difficult terrain and weather conditions has been studied using the example of Nizhny Novgorod. A three-dimensional model of the Oka exit to one of the city's bridges has been built. Based on the geometry of the model and accident statistics, the most dangerous sections of the road with small turning radii and a large elevation difference were identified. Based on the geometry of the model and accident statistics, the most dangerous sections of the road with small turning radii and a large elevation difference were identified. To develop automatic reaction in difficult conditions, the simulator used the following components: driving through difficult sections of the city, testing knowledge of traffic rules, demonstrating traffic accidents in case of violation of the rules and demonstrating how to act correctly. The simulator is planned to be used both for training novice and experienced drivers in a "live" environment of a real city, and for studying road conditions and alerting drivers in a dynamic mode about the traffic situation, the recommended safe speed in poor visibility conditions (fog, night) and under variable weather conditions (rain, snow, ice). that is, as a recommender system.
Development of a Mobile Application Testing Methodology Based on Eye-tracking Technology
Authors: Pletneva A.O. , Yanchus Viktor Edmundasovich
Published: November 2023

Nowadays, there are numerous mobile applications that, for one reason or another, are used by people to solve everyday problems. From a design perspective, in this paper, 3 factors were identified as influencing the perception of information in the mobile app: color solution, composition solution and font. An experiment was developed, which was carried out using eye- tracking technologies in a special software module. It includes 24 incentives and 2 tasks that participants in the experiment need to solve. The study showed that in incentives in a blue-orange color scheme with a composition in the form of square tiles and a serif font, subjects solve the task faster than in stimuli with a different color scheme with a composition in the form of rectangular tiles and a sans-serif font. Approbation of the developed methodology showed a positive result, but additional research is required for further testing of mobile applications.
Using Embree Technologies for Ray Tracing in Optical Systems with Free-form Surfaces
Authors: Zhdanov Dmitri Dmitrievich , Potemin Igor Stanislavovich , Zhdanov Andrei Dmitrievich
Published: November 2023

The paper considers the possibility of using a two-level representation of the geometry of free-form surfaces to speed up the ray tracing process and increase the stability of the tracing results for cases of "unnatural" ray propagation, for example, in the analysis of scattered light in optical systems. Surfaces defined by high-order polynomials (up to the 34th order), as well as Jacobi polynomials, were considered as free-form surfaces. The analysis was carried out and the shortcomings of the representation of this geometry in an explicit form and in the form of a triangular grid were revealed. A method was proposed for the double representation of geometry in the form of a coarse triangular grid and the original analytical expression. Based on the Embree library, ray tracing methods were developed for geometric surfaces that have a dual representation. The developed methods have shown a significant acceleration of the ray tracing while maintaining the accuracy and high stability of calculations. The paper presents the results of calculating the point spread function and flare for lenses with aspherical surfaces given by Jacobi polynomials.
Informational Recommendatory System of Selection and Ranking of Works of Graphic Digital Art using Combined Collaborative and Content-based Approach
Authors: Pronin D.S. , Zarubin I.B.
Published: November 2023

The use of several methods of recommendations in the development of a recommendatory system of works of digital art makes it possible to increase the accuracy and uniqueness of the selected objects. The «Weighted Hybrid Recommendation» methodology combines content-oriented and collaborative methods of constructing recommendations. The content-oriented method analyses features and user profiles, and the collaborative method takes into account user evaluations and feedback. The presented mathematical model allows to dynamically prioritize intermediate predicted estimates depending on the quality and quantity of available data algorithm. The recommendation system is implemented in the Java programming language in the Spring Boot web application hosted on the Linux cloud server. The developed model was tested on the focus group of students. The elements of the web application’s user interface were demonstrated, such as an initial survey, a slider with recommendations, displaying features of objects and the ability to evaluate an object. The technical solutions used, their advantages and disadvantages, as well as alternative technical solutions are described. A further way of development of recommendatory system is outlined.
Investigation of Point Cloud Filtering Algorithms for Robust Surface Reconstruction
Authors: Glumova E.S. , Serova M.A.
Published: November 2023

This paper considers methods of point cloud processing for noise-resistant 3D reconstruction in the context of surface reconstruction under limited computational power. The main causes of point cloud errors and methods of their elimination are presented. The errors in point cloud include noise obtained during object scanning, point cloud redundancy, and visual incompleteness. In the area of point cloud processing, point cloud filtering algorithms are key tools for improving accuracy and reducing noise in the resulting data. An iterative algorithm for filtering out erroneous points using the mean value of neighbouring points' coordinates, as well as a point cloud segmentation algorithm based on the detection of connected regions are considered. It was found that combining several filtering algorithms can lead to better results compared to using separate algorithms.
Detection of Hidden Subsurface Objects Based on the Processing of Multispectral Data Obtained from an Unmanned Aerial Vehicle
Authors: Gromov Yuri Yurievich , Ishchuk Igor Nikolaevich , Zenkin A.A.
Published: November 2023

To analyze the visibility of remote monitoring objects based on the data of different-time images in the visible and infrared wave ranges, it is important to know the patterns of temperature changes both of the Earth's surface itself and of objects. The study of the dynamics of temperature changes using a mathematical model of heat transfer allows us to obtain additional unmasking feature. As an additional unmasking feature, numerical estimates of the thermophysical parameters of hidden subsurface objects can be calculated based on the application of a genetic optimization algorithm. Grouping thermophysical parameters into separate classes allows you to highlight the boundaries of objects and unmask the area of their occurrence under the ground. To solve the problem of correct processing of a large amount of data, reducing the processing time of aerial photographs, it is advisable to use the method of machine learning based on neural networks. The article presents the process of segmentation of objects using deep learning, a mathematical model of thermophysical processes is formed to obtain numerical estimates of the thermophysical parameters of hidden subsurface objects in the course of solving the coefficient inverse problem of thermal conductivity based on a genetic algorithm.
Sultan II. Abdülhamid Döneminde Paskalya Yortusu Özelinde Gayrimüslimlere Yapılan Yardımlar
Authors: KOCAOĞLU Burak
Published: November 2023

Sultan II. Abdülhamid dönemi sosyal devlet anlayışının başarılı bir şekilde yürütüldüğü ve toplumda yardıma muhtaç her kesime imkanlar ölçüsünde yardım elinin uzatıldığı bir dönem olmuştur. Şüphesiz ki yürütülen yardım faaliyetlerinin Sultan’ın himayesinde yapılması yürütülen yardım faaliyetlerinin başarılı olmasını sağlamıştır. Çoğu araştırmacı tarafından Sultan II. Abdülhamid’in zamanla toplum içerisindeki görünürlüğünün azalmasından dolayı meşruiyetini arttırmak adına yardım faaliyetlerine ağırlık vererek himaye ettiği yönünde düşünceler dile getirilmiştir. Bu düşüncelerin haklılık payı olmakla birlikte Sultan’ın bizzat bu faaliyetlerle ilgilenmesini sadece siyasi sebeplerle açıklayamayız. Sultan II. Abdülhamid’in yardımsever bir yapıya sahip olması göz ardı edilmeyecek bir gerçekliktir. Bu çalışmada Sultan II. Abdülhamid döneminde çok geniş bir yelpazede yürütülen yardım faaliyetlerinden biri olan Paskalya Yortusu’nda Gayrimüslimlere yapılan maddi yardımlar ele alınmıştır. Çalışmamızın sınırları içerisinde kısaca Paskalya Yortusu’ndan bahsedildikten sonra hangi Gayrimüslim gruba ne kadar ödeme yapıldığı, yapılan ödemelerin finanse edilmesinde hangi kaynaklara başvurulduğu, bu süreçte yaşanan sorunların neler olduğu ve Sultan’ın tahttan indirilmesinden sonra ödemeler konusu arşiv belgeleri ışığı altında gösterilmiştir.
An Evaluation of the Reliability of Manual Landmark Identification on 3D Segmented Wrists
Authors: Winter Rémy , Citarel Arnaud , Chabrand Patrick , Chenel Audrey , Bronsard Nicolas , Poujade Thibault , Gauci Marc-Olivier
Published: November 2023

Background:

Three-dimensional (3D) preoperative planning is increasingly used in orthopaedic surgery. Two-dimensional (2D) characterization of distal radial deformities remains inaccurate, and 3D planning requires a reliable reference frame at the wrist. We aim to evaluate the reliability of the determination of anatomical points placed manually on 3D models of the radius to determine which of those points allow reliable morphometric measurements.

Methods:

Twenty-three radial scans were reconstructed in 3D. Five operators specialized in the upper limb manually positioned 8 anatomical points on each model. One of the operators repeated the operation 6 times. The anatomical points were based on previously published 3D models used for radial inclination and dorsopalmar tilt measurements. The repeatability and reproducibility of the measurements derived using this manual landmarking were calculated using different measurement methods based on the identified points. An error of ≤2° was considered clinically acceptable.

Results:

This study of intraobserver and interobserver variability of the anatomic points allowed us to determine the least variable and most accurately defined points. The middle of the ulnar border of the radius, the radial styloid, and the midpoint of the ulnar incisura of the radius were the least variable. The palmar and dorsal ends of the ridge delineating the scaphoid and lunate facets were the most variable. Only 1 of the radial inclination measurement methods was clinically acceptable; the others had a repeatability and reproducibility limit of >2°, making those measurements clinically unacceptable.

Conclusions:

The use of isolated points seems insufficient for the development of a wrist reference frame, especially for the purpose of measuring dorsopalmar tilt. If one concurs that an error of 2° is unacceptable for all distal radial measurements, then clinicians should avoid using 3D landmarked points, due to their unreliability, except for radial inclination measured using the radial styloid and the midpoint of the ulnar edge of the radius. A characterization of the wrist using 3D shapes that fit the articular surface of the radius should be considered.

Level of Evidence:

Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Evaluation of genetic purity on Bambara groundnut lines (Vigna subterranean L. Verdcourt) based on qualitative and quantitative characters
Authors: Khoirani Ratria Resti , Nurholis Nurholis , Fatimah Siti
Published: November 2023

Evaluation of genetic purity Bambara groundnut hope line is very important to maintain genetic purity before being released into new varieties. The purpose of this research to examine 12 lines of local Bambara groundnuts. The experiment consisted of 12 unit, each containing 30 plants. The data results are analysed of cluster test for variables qualitative, quantitative variables by counting the mean, variance, standard deviation and coefficient of diversity. The results showed that the 7 populations lines of hope were uniform because they had a similarity matrix value above 0.80 and the remaining 5 populations of lines of hope were not uniform because they had a similarity matrix value below 0.80. The results of data analysis on quantitative characters showed that age of germination, flowering, and harvest. Terminal leaf length and width, number of internodes, and number of branches had low diversity. Character number of leaves and, diameter of thecrown at the age of 3, 4, 5, 6, 7 and 10 WAP, petiole length, internode length, weight of wetstover, weight of dry stover, lengt hand width of seeds had moderatediversity. Characters of wetpod weight, pod weightdryness, skin thickness ,number of seeds and seed weight varied from high to very high.
The Adsorption Ability of Cibacron Red Dye from Aqueous Solution Using Copper Oxide Nanoparticles
Authors: Khanjar Aya Qasim , Farhan Ahlam Mohammed , Rheima Ahmed Mahdi
Published: November 2023

يصف هذا البحث الإنتاج الصديق للبيئة لجسيمات النحاس النانوية باستخدام مستخلص نبات الجرجير والحرق عند درجة حرارة 400 درجة مئوية لمدة 3 ساعات. تم استخدام SEM و TEM لتحليل  حجم الجسيمات النانوية المحضرة. تم استخدام حيود الأشعة السينية  لتحديد الهيكل البلوري. كشف التحليل الطيفي للأشعة السينية المشتتة للطاقة لهيكل المنتج الذي تم إنشاؤه عن مكونات النحاس والأكسجين فقط ، مما يدل على نقاء المادة المحضرة. استخدمت المادة النانوية المحضرة  CuO NPs  في امتزاز صبغة Cibacron الحمراء. في 35 دقيقة من زمن الاتزان ، لوحظ امتزاز أسرع لصبغة Cibacron الحمراء على الجسيمات النانوية CuO . كان نموذجا    Freundlich و pseudo-second ذات قيم R2 أكثر من 0.9785 و 0.999 على التوالي ، الأكثر فاعلية في وصف عملية الامتزاز. تم حساب المعلمات  ΔG, ΔH, ΔS. يمكن الاستنتاج أن CuO NPs هي سطح ممتز فعال لصبغة Cibacron الحمراء.
A Dislocated Quasi-Normed Space and Its Completeness for A Fixed Point Theorem
Authors: Al-Delfi Jawad Kadhim K.
Published: November 2023

تم تقديم مفهوم الفضاء شبه المعياري المشتت في هذا البحث وهو حالة خاصة لمفهوم الفضاء شبه المعياري ومرتبط بمفهوم الفضاء شبه المتري المشتت. العلاقة بين هذا المفهوم والمفاهيم الأخرى أعطيت من خلال أمثلة توضيحية. مفهوم شبه بناخ المشتت هو شبه المعياري المشتت الكامل   والتي يعتبر مهم لنتائجنا فيما يتعلق بنظرية النقطة الصامدة. أيضًا، يتم تقديم التقابل شبه انكماشي، الذي فيه   ثابت ليبتشيتز يعتمد على ثابت الفضاء شبه المعياري المشتت، ثم ندرس نظرية بناخ الانكماشية في شبه بناخ المشتت مع بعض النتائج المهمة.