bluuebunny/crossref_metadata_2025 huggingface dataset:
Epic novel “War and Peace” by L. Tolstoy as a polyphonic structure
Authors:   Peoples’ Friendship University of Russia, Kovalenko Alexander G. , Lumpova Lidiya N.
Published: November 2022

The article is devoted to the revealing of the phenomenon of polyphony in the Tolstoy’s works. The article explores the phenomenon of polyphony in a general sense: thepolyphony is as the equality of mutually exclusive elements within the same semantic context / image / concept as to in the synchrony and in the diachrony. The relevance of the problem is due to the fact that the phenomenon of polyphony in the Tolstoy’s works was previously considered from the standpoint of literary criticism, but almost never analyzed in the context of text linguistics. The purpose of this work is the analyzing of the phenomenon of polyphony from the standpoint of text linguistics in the epic novel “War and Peace”. For this purpose the main task of the study is to combine two approaches in the analysis of a literary text: linguistic and literary approaches. In the semantic structure of the analyzed work, the phenomenon of polyphony will be expressed in the existence of mutually exclusive meanings within the same semantic context, object (image), within the same concept, therefore the semantic structure of the image and the conceptually significant concepts of the epic novel will be endowed with a system of opposed to each other meanings, which will lead to polyphony of the entire semantic structure of the text as a whole.
Functions of plot associations from classical literature in B. Akunin’s game projects about Fandorin and Pelagia
Authors:   Linguistic Gymnasium No. 3 (Ulan-Ude), Bobkova Natalia G.
Published: November 2022

The article is devoted to novels by B. Akunin who uses the quotations, reminiscences and subjects of classical authos for the realization of his detective projects. The scientific novelty of the article lies in the fact that an attempt is made to investigate the role of quotations and reminiscences, plot, figurative and stylistic associations borrowed from Russian and foreign classical literature in B. Akunin’s detective novels about Fandorin and Pelagia. In the intertextual space of the writer’s novels, themes and motives from the novels of F.M. Dostoevsky, N.V. Gogol, M.A. Bulgakov, M.Yu. Lermontov and other writers. The writer skillfully combines foreign classics with detective intrigue. The image of detective Erast Fandorin is a fusion of features of Sherlock Holmes, William of Baskerville, Prince Florizel: the image of the nun Pelagia — Miss Marple and Father Brown. The motives, style, language of the classics of Russian literature determine the stylistic originality of the modern writer. The stylization of the writer’s novels not only makes it possible to strike up a literary game with a reader — a connoisseur of classical literature, at the same time, counting on a detective lover, but also makes it possible to overcome the difference between two cultural fields: elite literature and mass literature.
“My poetry… is full of movement and heat, characteristic of life”: The theme of love in the lyrics Forugh Farrokhzad
Authors:   University of Tehran, Yahyapour Marzieh , Karimi-Motahhar Janolah , Farmani Fahrahnaz , Maltseva Tatiana V. ,   Pushkin Leningrad State University
Published: November 2022

The article deals with forms of representation of love theme in lyrics by F. Farrokhzad. It considers the fact that interpretation of love in Farrokhzad’s lyrics differs from traditional perception of love in oriental poetry. Hence the authors prove that F. Farrokhzad has broken the traditional circle of associations in oriental love lyrics and has rethought it by adding new “bodily” signs of love. Love in Farrokhzad’s lyrics is shown through the prism of everyday, natural and existential patterns. Love as an event serves as a core for the poetess’ lyrics and displaces the generic features of the lyrics itself. Love lyrics by F. Farrokhzad demonstrates the features of the narrative text combining lyrical and epic pictures of the world in poem’s structure, so narrativeness is one of the key parameters of F. Farrokhzad’s poetics. The authors conclude that poetess tends to concentration of everyday details and to eventful measure of the reality.
ADMINISTRATIVE PERSONNEL SELECTION OF KAMBANGAN VILLAGE IN BRUNO DISTRICT, PURWOREJO REGENCY
Authors: Atmoko Agus Dwi , Ayuningtyas Pratika , Mauludin Lutfi Ashar
Published: November 2022

Background: As an independent institution, Politeknik Sawunggalih Aji is trusted to hold one of the three requirements of administrative personnel selection, which is a Computer skill test. Objective: The aim is to conduct a computer skill test as one of three requirements of organizational personnel selection Method: Computer Skill test includes the mastery of Ms. Word, Ms. Excel, and Ms. PowerPoint. Results: The total score of the participants' test is qualified. Conclusion: The test is well run. The computer test is valued at 30% of the total score of the three requirements.
Implementasi Trade Facilitation Agreement Sebagai Reformasi Perekonomian Di Indonesia
Authors: Hakim Luqman
Published: November 2022

The most crucial barriers to international trade take the form of administrative barriers. Therefore, the presence of the Trade Facilitation Agreement (TFA) aims to remove these administrative barriers, thereby facilitating international trade. This study analyzez the implementation of TFA as a reform of the Indonesian economy. The research method used is normative legal research, by examining legal data sourced from literature as the secondary legal materials or literature related to the topic of this research. The results of this study concluded that after Indonesia’s ratification of the TFA, it was able to increase exports and reduce trade costs. This is due to the nature of TFA as a multilateral agreement among WTO member countries and affects the increase and optimization of trade procedures. Thus providing access for MSMEs to contribute to international trade and reducing trade costs incurred by business actors. After the ratification of TFA through Law Number 17 of 2017 on Ratification of the Protocol to Amend the Marrakesh Agreement on the Establishment of World Trade. The policies issued by Indonesia include one single submission (OSS), reduced container storage period (dwelling time), simplification of licensing, NLE, Digital Bank.
Improving Visual SLAM by Combining SVO and ORB-SLAM2 with a Complimentary Filter to Enhance Indoor Mini-Drone Localization Under Varying Conditions
Authors: Basiri Amin , Mariani Valerio , Neyestani Arman , Glielmo Luigi
Published: November 2022

Mini-drones can be used for a variety of tasks, such as weather monitoring, package delivery, search and rescue, and recreation. Their uses are mostly restricted to outside locations with access to the Global Positioning System (GPS) and/or similar systems since their usefulness, safety, and performance substantially rely on ubiquitously accurate positioning and navigation. Indoor localization is getting better, thanks to technologies like Visual Simultaneous Localization and Mapping (V-SLAM). However, more advancements are still required for mini-drone navigation applications with greater safety standards. In this research, a novel method for enhancing indoor mini-drone localization performance is proposed. By merging Oriented Rotated Brief SLAM (ORB-SLAM2), Semi-Direct Monocular Visual Odometry (SVO), and an Adaptive Complementary Filter, the suggested strategy improves V-SLAM approaches (ACF). The findings demonstrate that, when compared to other widely-used indoor localization algorithms, the suggested methodology performs better at estimating location under various situations (low light, low texture, and dynamic environments).
Effect of Different Tillage Practices in Sunflower (Helianthus annuus) Cultivation in a Crop Rotation System with Intercropping Triticosecale -Pisum sativum
Authors: Molla Aikaterini , Charvalas Georgios , Dereka Maria , Skoufogianni Elpiniki
Published: November 2022

The objective of this work was to investigate the effect of different soil tillage practices in sunflower cultivation in a rotation system with intercropping Triticosecale x Pisum sativum. For this purpose a two year experimental field of 5% slope was established in central Greece. There were four treatments with three replications each. The treatments were: (a) no tillage - planting parallel to the contour (NTC-PAC), (b) conventional tillage - planting parallel to the contour (CTC-PAC), (c) no tillage - planting perpendicular to the contour (NTC-PEC), (d) conventional tillage - planting perpendicular to the contour (CTC-PEC). During the experiment plant height, leaf area index, specific leaf area, plants’ total nitrogen and plants’ proteins were measured. According to the results plant height ranged from 64.9 (CTC-PAC) to 85.2 cm (NTC-PEC) the 1st year and between 66.5 – 86.5 cm in CTC-PAC and NTC-PEC treatments in the 2nd year. Furthermore, LAI and SLA, plant’s total nitrogen and protein content and N-uptake were affected positively by the no tillage practice. To conclude, sunflower is a promising crop in a rotation system with intercropping Triticosecale x Pisum sativum, cultivating under rainfed sloping conditions.
Current Status of Tungiasis in Endemic Areas. Prevalence, Risk Factors, Prevention
Authors: Velev Valeri
Published: November 2022

Tungiasis is a neglected parasitic skin disease caused by the permanent penetration of the female sand flea (Tunga penetrans) in the skin of the host, mainly the lower extremities.This gradually, it can lead to severe limb deformities.To date it is a health issue mainly in sub-Saharan Africa, the Caribbean, Latin and South America. It occurs mainly in poor rural populations and a major problem for children and the elderly. In diurnal zones, the incidence can reach over 73%. Over the past 20 years, studies in endemic areas on tungiasis have clarified to some extent the scientific community's knowledge for some problems of the disease. In this review, the current data on epidemiology, risk factors and prevention options are examinedof Tungiasis, as well as the expected steps of the international medical community to combat the disease.
Providing Decision Support in Career Guidance Through the use of Machine Vision
Authors: Tarasova Iuliia Sergeevna , Andreev Vyacheslav Viktorovich , Chechin Andrey Vyacheslavovich , Toskin Denis V.
Published: November 2022

This paper is devoted to the review of the results of the development and implementation of the ColorUnique Pro career guidance software package in the career guidance activities of higher educational institutions. The review begins with the initial formulation of the problem, justification of the use of neural networks as the basis of one of the classifiers, consideration of the results of experiments and then – the introduction of a software package. At the end of the article, prospects for further research are described, such as the creation of a three-dimensional map of types and subtypes and the further identification of new subtypes. The possibility of using additional methods of analysis, detection and classification is also being considered in order to study the influence on the definition of ISA of such features of the images obtained as «demonstrative» and «true» structures, as well as the presence of a «background» that does not contain characteristic elements. In addition to neural networks, the authors also used the «sliding» window image processing method, as a result, the software package includes two classifiers that analyze images separately, however, in the future, the results of the analysis of both classifiers are compared by an expert, since some subtypes can only be determined by joint interpretation.
Development of a Neural Network Model for Semantic Segmentation of Point Clouds
Authors: Leshin O.D. , Grigoriev D.S.
Published: November 2022

Processing point clouds using neural network models is a relatively new approach. The first significant works in this direction date back to 2017. Point clouds are a set of vertices in threedimensional space and characterize the external surface of an object. Due to the peculiarities of such data, typical fully connected convolutional networks cannot be applied. This is due to the fact that such data should take into account not only the color component but also the entire geometric shape of the object. This paper presents a neural network model for semantic segmentation of point clouds, which are remote sensing data of the earth. The proposed model is a modification of the original DGCNN model, which is based on the graph representation of point clouds, and atrous convolution layers were used to improve the result. The training and testing of the model was carried out on the Hessigheim 3D dataset, which was obtained by scanning a suburban area. As a result of numerical experiments on model development and data set preprocessing, acceptable results were obtained for the F1 and overall accuracy metrics.
Comparison of G-Means Algorithms and Kohonen Network in Solving Clustering Problems
Authors: Sudakov O.V. , Dmitriev D.V.
Published: November 2022

Purpose: In this paper, the question of how to improve a self-organizing neural network consisting of a bundle of clustering algorithm and a multilayer perceptron for data verification tasks in the absence of training pairs is considered. Design/methodology/approach: The most popular clustering algorithm is the Kohonen network, but today it is not the only algorithm capable of performing the task quickly and accurately. The paper compares the Kohonen network and the G-Means algorithm. The principle of operation of these two algorithms is briefly analyzed. The accuracy of these algorithms and the speed of their learning are compared. Findings: By conducting experiments, conclusions were drawn about the speed and accuracy of the algorithms. Originality/value: The relevance of this work lies in the fact that the preparation of training pairs for intelligent systems and the process of learning with a teacher is a resource-intensive task. The systems of self-learning algorithms under consideration will significantly increase the learning rate, as well as eliminate the need for manual classification of data and the creation of training pairs for the perceptron, which in turn will allow you to create a self-learning system with the ability to generalize and predict.
Competency-based Approach in Expert-heuristic Evaluation of Graphical User Interfaces
Authors: Khaleeva U.I.
Published: November 2022

This paper is a continuation of a cycle of research aimed at forming a new method for evaluating graphical user interfaces (GUI) using an expert-heuristic method. A combination of expert and heuristic approach is proposed, to detect a wide range of UI/UX problems, ensure the competence of the evaluation and reduce the level of incredulity to the expert. This paper illustrates the possibility of implementing a competency-based approach to form heuristic criteria. The key idea behind the application of such a method, the principle of scoring and the experiments conducted to confirm this hypothesis are described in detail. A practical implementation of the competency-based assessment technique for expert-heuristic assessment of UI/UX is presented. The analysis of the experiment is performed, the key advantages and disadvantages of the considered approach are revealed. Conclusions are made about the applicability of the method for evaluating interfaces of different types.
Аutomatic Constructing the NURBS Surface of a Ship's Hull
Authors: Popov E.V. , Shorkina I.N.
Published: November 2022

The article describes an automated algorithm for the formation of a geometric model of the ship's hull surface according to an electronic theoretical drawing. An analysis of the traditional technology for the formation of ship surfaces based on the Russian CAD system (Sea Solution) is presented. The main disadvantages of traditional technology are determined. The automated algorithm for generating a geometric surface model is designed to reduce the complexity of manual design. The mathematical apparatus for constructing NURBS curves and surfaces serves as the instrumental basis of the algorithm, which provides a simple user control of forms. On the basis of a theoretical drawing generated by the CAD system, a cloud of approximation points was created to build the surface of the ship's hull from them. A general scheme of automatic construction of elements of the surface model in the initial approximation is given. To solve this problem, a software product based on HTML5, JavaScript and Three JS and Verb libraries was created. The use of the JavaScript language is due to its versatility, a large amount of information in the public domain. WebGL is used to implement 3D graphics rendering pipeline. Functions from the Three JS libraries made it possible to implement methods used in analytical geometry. The operability of the developed algorithm is demonstrated on the example of building a 3D model of the hull surface of a fishing trawler.
Semantic 3D Reconstruction of a Scene and Its Effective Visualisation
Authors: Kniaz Vladimir Vladimirovich , Moshkantsev Petr V. , Bordodymov Artem N. , Mizginov Vladimir A. , Novikov Daniil I.
Published: November 2022

Single-image 3D scene reconstruction is required in multiple challenging tasks including mobile robotics, industrial monitoring and reconstruction of lost cultural heritage. While modern models demonstrate robust resolution of scene in real time with resolution up to 128 x 128 x 128 voxels, visualization of such detailed of a such detailed voxel model is challenging. A model with 1283 voxels contains 2097152 simple cubes 16M vertices. It is unfeasible for modern hardware to perform visualization of such voxel models in real-time. Hence a voxel model simplification technique is required to demonstrate reconstruction results in real-time. In this paper, we propose a new algorithm for voxel model simplification using predefined camera views. The algorithm reduces a rigid-body voxel model to a shell voxel model. It keeps only the voxels that are visible from the required view. We demonstrate the effectiveness of the proposed algorithm using a case study with a mobile robot and a state-of-the-art SSZ single-photo 3D reconstruction neural network. We generated a real and a virtual scene with various objects including a statue. We use a mobile robot equipped with a single camera to collect real and synthetic data. We train the SSZ model using the collected data. We developed a dedicated visualization software that implements our algorithm. The comparison of the visualization performance for the full model and its reduced version demonstrates that our algorithm allows to increase the performance by 420 times.
Visualization of Supersonic Flow in a Channel with an Obstacle by High-speed Shadow Imaging, Pulsed Discharge and Numerical Simulation
Authors: Znamenskaya Irina Aleksandrovna , Lutsky Alexander Evgenievich , Dolbnya D.I.
Published: November 2022

In a supersonic flow in a shock tube chamber, a pulsed volume discharge with preionization by ultraviolet radiation from plasma sheets is realized. An obstacle with dimensions of 2 mm ? 48 mm ? 6 mm, installed on the lower plasma sheet across the flow in the discharge chamber, leads to structural changes in the flow and, accordingly, the discharge localization. As a result of the localization of the discharge energy, a complex unsteady gas-dynamic flow is formed, containing discontinuities and inhomogeneities of various types. To visualize the flow, registration of the glow field of a submicrosecond discharge in the flow is used; high-speed shadow shooting with a frequency of 150 thousand frames per second for 14 ms after the initiation of a discharge in an inhomogeneous flow behind the shock wave. Additional information about the flow under study was obtained by numerical simulation based on the Navier-Stokes equations. Numerical data are presented in the form of gas-dynamic quantities distributions, including the modulus of the density gradient, at various stages of the process. A comparison is made between the calculated and experimental shadow images of the flow formed as a result of the discharge energy input; the energy input in the numerical calculation was carried out in accordance with the density field.
Visualization of Mental Map Representation Patterns
Authors: Chumakov Roman , Ryabinin Konstantin Valentinovich , Belousov Konstantin Igorevich
Published: November 2022

The paper is devoted to the automation of visual analytics of digital mental map representation sets. Digital mental map representations are digital drawings of some certain spaces made by humans, reflecting their spatial experience and distinctive thoughts they have about the considered spatial places. The subjectivity behind mental maps fundamentally distinguishes them from the geographical maps and makes them a very fruitful material for Digital Humanities research. To unveil the potential of this research, in the previous works we developed the Creative Maps Studio vector graphics editor to enable informants intuitively draw their mental maps. In the present work, we enrich Creative Maps Studio with ontology-driven analytical subsystem to enable in-place handling of mental map representations. The proposed subsystem provides visual tools to describe the processing pipeline of mental map representations using a data flow programming paradigm wherein each processing step is described by ontology. This approach proved its flexibility and efficiency in solving different visual analytics tasks. The implemented analytical modules allow automatically render a set of mental maps representations in the graphical form and to view statistical characteristics of individual objects from these representations. The process of data preparation and visualization is described. The suggestions are proposed on the interpretation of the result. The pros and cons of using the proposed method are discussed along with the possible directions for its further development.
Visualization of the Evolutionary Trajectory: Application of Reduced Amino Acid Alphabets and Word2Vec Embedding
Authors: Forghani Majid Ali , Firstkov Artyom L. , Vasev Pavel Alexandrovich , Ramsay Edward S.
Published: November 2022

Analysis of viral evolution is a key element of epidemiological surveillance and control. One of the fundamental tools which is widely used to illustrate evolutionary history is the phylogenetic tree. Recently, we have proposed an alternative visualization for the phylogenetic tree using the evolutionary trajectory of its taxa. An evolutionary trajectory is a path starting from a taxon and ending at the root of the tree. In this paper, we propose an embedding of tree nodes by encoding their genetic sequence using a reduced amino acid alphabet and employing the Word2Vec framework. The suggested visualization maintains the phylogenetic relationship between nodes, while their proximity in 3D space depends on three factors: the type of reduced amino acid alphabet; fixed-length genetic patterns used in Word2Vec; and the neighbor effect of adjacent signatures. The results of our experiments showed that the majority of evolutionary history can be described in the embedded space. Moreover, they suggest potential application of our approach as an explanatory tool in studying various aspects: evolutionary dynamics; evolutionary deviation of viral variants; and phylogenetic characteristics, such as formation of new clades. Besides the usual local analysis of point mutations, the developed framework enables studying these aspects based on a more comprehensive global context, including neighboring effects, genetic signatures.
On the Visualization of Multidimensional Functions Using Canonical Decomposition
Authors: Alexeev Alexey Kirillovich , Bondarev Alexander Evgenyevich , Pyatakova Yu.S.
Published: November 2022

The approximation of the multidimensional function using the high order tensor and canonical decomposition is considered for the purpose of visualization. Formally, from the standpoint of computational resources (operational memory volume and the time of computation) the canonical decomposition is beyond comparison. However, at present, the main algorithm that calculates the canonical decomposition is based on the Khatri-Rao product, which implies matrization. This circumstance restricts the domain of applicability by tensors of the relatively small order. In order to overcome this drawback, the algorithm of the computation for the canonical decomposition formmatrices is described that is composed by combination of alternating least squares and stochastic gradient descent. This algorithm has no restrictions from the standpoint of the order of the tensor under the consideration. The numerical tests are presented for the approximation of functions in six-dimensional space that demonstrate the high computational efficiency and high quality of results. The instabilities arising at the estimation of the rank of the decomposition are another trouble of the canonical decomposition. The results of the numerical tests are presented that illustrate the search for the optimal rank providing the minimum of the discrepancy of the exact solution and its approximation.
Application of Volumetric Stereoanimation in Maxillofacial Surgery
Authors: Kobets K.R. , Andreev Sergey Valeryevich , Bondarev Alexander Evgenyevich , Bondarenko A.V.
Published: November 2022

The work is devoted to the application of previously developed algorithms and methods of stereo imaging in the field of maxillofacial surgery. Construction of stereo images can be useful for solving the problem of visual aids in medicine. The work is based on the developed algorithms and software tools for presenting 3D objects in stereo mode on modern autostereoscopic monitors. Test examples of 3D volumetric animations of the results of real CT scans of patients are constructed and presented as illustrations. A similar approach can be used for virtual volumetric 3D visualization of human organs in various fields of medicine. Practical cooperation of medical workers and developers of methods of stereo animation on autostereoscopic monitors on example of practical tasks allows to develop new approaches, necessary for specialists. For medical workers creation of stereopresentation base helps to identify patients' pathologies, to establish communication with the patient by means of visual volumetric representations, to establish communication between medical specialists. The dissemination of such stereoscopic images in various fields is extremely important. Such visual representations help to move the processes of patient analysis, data processing to a new, higher level.
Subjective Interpretation in Visualization
Authors: Zakharova A.A. , Shklyar A.V. , Vekhter E.V.
Published: November 2022

The paper considers the problem of the influence of subjective factors on the effectiveness of the use of visualization tools in the tasks of interpretation and practical analysis of unformalized data. Subjectivity is the starting point in the cognitive search, analysis of new information and proposing new hypotheses. In the methods of studying unformalized data, including the use of modern intelligent methods, the emergence of the stage of interactive communication between the researcher and the data, allowing to combine the data and their possible subjective interpretation in one information space, can give new tools for scientific research and methods of their application Based on the developed semiotic model of visualization, the system of initiating factors that have a significant impact on the performance of the tools is proposed It is shown that visualization tools, their perceived characteristics and control subsystems can form the necessary emotional factors in the user to control his activity. A controllability hypothesis has been formulated to explain the limitations of some visualization systems and to avoid errors in the design of new visual analytics tools. Thus, the design of visualization tools is considered as a complex parameter for managing their purpose and effectiveness. Examples are given to illustrate the validity of the assumptions made and their practical relevance.
Real-Time Implementation of Modified YOLO Object Detector on FPGA
Authors: Levkin Timophey , Skonnikov Petr Nikolaevich , Trofimov Dmitriy V.
Published: November 2022

Some operating principles of the YOLO object detector are considered. The functions of processing the array elements coming from the last convolutional layer are analyzed. It is shown that three different types of functions are used to process various parameters. For example, the logistic sigmoid is used to predict the positioning accuracy and the bounding boxes vertical and horizontal offsets. The exponent is used to predict the height and width of boxes, and the SoftMax function is used to predict class probabilities. Formulas for the derivatives of these functions, which are required when training the network, are given. The replacement of these functions with simpler ones for implementation in hardware is proposed. The logistic function is replaced by a rational sigmoid, the exponent is replaced by a shifted fourth-order parabolic curve. The modified SoftMax function also uses a shifted parabola. The derivatives of proposed functions are presented to calculate the error backpropagation. Using the obtained formulas, a YOLO detector based on a modified neural network was trained. The modified YOLO detector with the proposed functions is implemented on a specially designed Xilinx FPGA board. Experimental studies of the board showed the high speed of the detector (more than 60 frames per second) and the high quality of object detection and classification.
Analysis of Parking Space Using Computer Vision
Authors: Laptev V.V. , Laptev N.V. , Ozdiev A.H. , Gerget O.M.
Published: November 2022

The article deals with the system of parking space analysis, based on the processing of video monitoring through image segmentation, performed with the help of an artificial neural network (ANN). Two key algorithms included into the parking space analysis system are described in detail: 1) the algorithm of the image quality analysis; 2) the algorithm of the adaptive image analysis. The main purpose of the development and implementation of the first algorithm is to evaluate the feasibility of ANN image analysis, based on the recognition of object boundaries. The idea of the second algorithm-adaptive image analysis is as follows: to analyze images of different size and approximation (scale), by bringing the input image to a single dimensional format, followed by the approach of splitting into patch. After ANN analyzing the resulting parts of the image, the algorithm again combines them into a whole picture, identical to the input format. The final stage of the system proposed by the authors is an algorithm for the classification of multiple parking spaces, based on the combined analysis of the segmentation mask obtained from the ANN and a pre-prepared polygonal grid of parking spaces in the image. The paper describes the data used to achieve the obtained results and the characteristics of the training of the semantic segmentation model, giving the statistics of the performance.
Recurrent Neural Network for Recognition of Gestures of the Russian Language, Taking into Account the Language Dialect of the Siberian Region
Authors: Zhukovskaya V.A. , Pyataeva A.V.
Published: November 2022

Sign recognition is an important task, in particular for the communication of the deaf and hard of hearing population with people who do not know sign language. Russian sign language is poorly studied, Russian sign language of the Siberian region has significant differences from others within the Russian language group. There is no generally accepted data set for Russian Sign Language. The paper presents a gesture recognition algorithm based on video data. The gesture recognition algorithm is based on the identification of key features of the hands and posture of a person. Gestures were classified using the LSTM recurrent neural network. To train and test the results of gesture recognition, we independently developed a data set consisting of 10 sign words. The selection of words for the data set was made among the most popular words of the Russian language, as well as taking into account the maximum difference in the pronunciation of gestures of the language dialect of the Siberian region. The implementation of the gesture recognition algorithm was carried out using Keras neural network design and deep learning technologies, the OpenCV computer vision library, the MediaPipe machine learning framework, and other auxiliary libraries. Experimental studies conducted on 300 video sequences confirm the effectiveness of the proposed algorithm.
Optical-information Method of Detection of Unmanned Aircraft by a Robotic Optical-electronic System
Authors: Smolin V.A. , Yakimenko I.V. , Rasskaza D.S.
Published: November 2022

The informativeness of the operating spectral ranges of optoelectronic detection systems for unmanned aircraft is considered. The conducted studies have shown that the spectral range of 3 – 5 microns, due to the absence of powerful radiation sources in unmanned aircraft, has significantly lower radiation power compared to the spectral range of 8 – 13 microns. As an alternative to the range of 3 – 5 microns, a range of 1.2 - 1.7 microns is proposed. The proposed near–infrared range can complement the use of a range of 8 - 13 microns in daytime conditions, which, along with the development of new detection methods based on the background principle, will increase the detection efficiency of unmanned aircraft. A contrast method has been developed based on the background detection principle. A distinctive feature of the contrast method is the splitting of the frame into segments. The segment size corresponds to the size of the inhomogeneities of the atmosphere. A contrast algorithm for detecting unmanned aircraft is considered. The probability of detecting small-sized objects was calculated using the developed method. The developed contrast method is compared with existing methods. The advantage of the developed contrast method in comparison with the investigated ones is revealed. The detection range of unmanned aircraft has increased by 10%.
Usage of Scenario Based Modeling Automation in Optics CAD Systems
Authors: Kopylov Mikhail Sergeevich
Published: November 2022

This article describes approaches to the use of scenarios in the automation of applied tasks within the framework of working with a software complex of optical modeling and photorealistic computer graphics. Optical modeling complex should include support for scripting, since conventional tools, such as those provided using a graphical user interface, are usually not enough to perform a variety of tasks that arise in practice. A brief overview of existing solutions is made. Methods are proposed that ensure effective bringing of scenario support into an existing optical modeling system. These methods provide full access from scripts to system modules, including computational modules, various simulator modules, etc. Both trivial scripts containing ordinary command sequences and more complex ones using the capabilities of high-level scripting languages such as Python are supported. Separately, a special high-level API is considered which is used for the interaction between of scripts written in the Python language and the optical modeling system. This API can also be used to extend the capabilities of the system with new parametric objects. The specialized software modules integrated into the optical modeling system, such as the batch interpreter, script interpreter and editor, extension class editor, are considered in detail. Examples of scenario-based modeling automation are given.
Bio-inspired Neuron Model for Motion Detection on Base Signal Accumulation
Authors: Kugaevskikh A.V. , Mangarakov A.D.
Published: November 2022

The article presents a new model of the MT neuron (neuron of the middle temporal region), which allows motion detecting and determining its direction and speed without the use of recurrent communication. The model is based on signal accumulation and is organized using a space-time vector that sets the weighting coefficients. The space-time vector is formed using the product of the Gaussian, which defines the spatial component, and the "Mexican hat" wavelet, which sets the time vector of the change in the receptive field. This configuration allows not only to motion detect, but also to make the model not sensitive to uniform or textural fill. The model is presented in variants for determining linear and rotational motion. Motion, in this case, is the sequential activation of several edge selection neurons located in the same direction in a certain neighborhood over time i.e. with a change of frame. To assess the motion, the models were tested on the MPI Sintel dataset. The model developed by us shows results better than Spatio-Temporal Gabor. The best accuracy of determining the direction of movement can be obtained with the size of the space-time vector (7*7, 7).
Generation and Study of the Synthetic Brain Electron Microscopy Dataset for Segmentation Purpose
Authors: Sokolov N.A. , Vasiliev E.P. , Getmanskaya A.A.
Published: November 2022

Advanced microscopy technologies such as electron microscopy have opened up a new field of vision for biomedical researchers. The use of artificial intelligence methods for processing EM data is largely difficult due to the small amount of annotated data at the training stage. Therefore, we add synthetic images to an annotated real EM dataset or use a fully synthetic training dataset. In this work, we present an algorithm for the synthesis of 6 types of organelles. Based on the EPFL dataset, a training set of 860 real fragments 256x256 (ORG) and 6000 synthetic ones (SYN), as well as their combination (MIX), were generated. An experiment of training models for segmentation into 5 and 6 classes showed that, despite the imperfection of synthetic data, for an axon poorly represented in the training data set, the use of a synthetic data set improves the Dice metric from 0.3 on the original dataset to 0.8 on the mixed and synthetic datasets. The synthetic data strategy gives annotations for free, but shifts the effort to producing sufficiently realistic images.
Estimation of Geometric Model data Loss under Import Substitution Conditions
Authors: Filinskikh A.D. , Merzlyakov I.N. , Kurushin E.A.
Published: November 2022

The formats of the geometric model translation are analyzed and investigated using the example of using professional software for creating three-dimensional computer graphics Autodesk 3ds Max and Blender. In the context of import substitution, there is a need to switch to using other software, and therefore, when transferring geometric models from one system to another, data loss may occur. So, during the evaluation, the transfer of the model took place through the formats of translation of geometric models. The results of the work done have shown that each format successfully conveys the geometry of the model, while complementary information about this model is lost, such as color, materials, names of constituent elements. Moreover, the evaluation will depend on the priority parameters for successful transmission.
Automated Calculation of the Parametric Index of a Flat Contour According to Its Electronic Drawing
Authors: Tyurina Valeria Alexandrovna , Smychek M.M. , Romensky Sergey Aleksandrovich , Lagunova M.V.
Published: November 2022

The article describes an algorithm for automatic calculation of the parametric number of a flat contour created electronically in vector format. Since the parametric number of the contour corresponds to the number of dimensions in the drawing necessary for its unambiguous reproduction, the described algorithm can be used as the basis for the process of solving the difficultly formalized problem of automated drawing dimensions on the drawing. This task is relevant primarily for automating design tasks associated with the problem of automatic "reading" of the drawing, which is still far from its final solution. In addition, this algorithm can be used to expand the capabilities of training simulators that contribute to the formation of geometric and graphic competencies in the training of specialists in various areas of training. This article describes the process of selecting non-derivative figures that make up a flat contour, and identifying geometric conditions between them, allowing you to replace the shape and position parameters in the contour drawing in order to optimize the number of dimensions applied to the drawing. The general algorithm for solving the problem posed requires solving a large number of related problems, many of which involve the use of a heuristic approach. Therefore, testing the developed algorithm is a separate, multifactorial task that requires a large number of iterations.
A Study on the In-depth Teaching of English Reading in Senior High School Aiming at Core Literacy
Authors: Jiay Li , Ran Ran , Jianjie Yang , Junwei Lu , Juan Wang
Published: November 2022

This study uses methods like a questionnaire survey, teacher interviews, micro-lectures teaching, etc. to ask questions like: What is the current situation of teachers' cultivation of students' core literacy in the teaching of English reading? How can in-depth teaching of high school English reading help to cultivate core literacy? Making good use of micro-lectures teaching, applying diversified reading teaching methods, taking students as the main body to improve students' participation and experience in reading classrooms, and maximising teaching evaluation methods are some of the teaching inspiration drawn from the study.
Örgüt Kültürü ile Personel Motivasyonu Arasındaki İlişkiye Yönelik Karşılaştırmalı Bir Araştırma: Türkiye ve Afganistan Örneği
Authors: ROOZİ Mohammad Aref , TETİK Semra
Published: November 2022

Organizational culture is the common values, beliefs and norms that employees share in the organization. Organizational culture guides employees to have the right attitudes and behaviors. Organizational culture leads to solidarity, belonging and integration for employees. Creating a strong organizational culture with this dimension can increase personnel motivation. Personnel motivation is the process of taking the desired behavior and encouraging the individual in line with the goals of the organization. In terms of the effectiveness and efficiency of the organizations, the motivation of the employees should be kept alive. In this context, it is thought that the creation of a strong organizational culture by the managers would positively affect the motivation of the personnel. The aim of the study is to comparatively examine the relationship between organizational culture and personnel motivation in public institutions in Turkey and Afghanistan, and to analyze whether the organizational culture perceptions of the employees' organizations affect their motivation. As a result, it is understood that organizational culture is effective on the level of motivation. On the other hand, it is determined that there is no significant difference between countries in terms of organizational culture and motivation level.
360 Derece Performans Değerlendirme Sistemi Hakkında Kavramsal Bir İnceleme
Authors: EKŞİ Gül
Published: November 2022

Bu çalışmada her işletme için önemli bir yer teşkil eden performans, performans ölçme ve değerlendirme kavramları incelenmiştir. Öncelikle Web of Science veri tabanında bir literatür taraması yapılmış, ardından performans, performans ölçümü ve değerlendirmesi kavramları teorik olarak incelenmiş; performans değerlendirme yaklaşımları ele alınmıştır. Literatür taraması sonucunda işletme literatüründe çok fazla yer bulmadığı tespit edilen, performans değerlendirme yöntemleri içinde modern yöntemlerden biri olan 360 derece performans değerlendirme sistemi ayrıntılı olarak incelenmiş ve bu konu hakkında genel bir çerçeve oluşturulmaya çalışılmıştır. Sonuç olarak; 360 derece performans değerlendirme sisteminin performans sorunlarına tek başına ve doğrudan bir çözüm getiremeyeceği saptanmıştır. Ancak bu sistem özenle hazırlanıp doğru bir şekilde uygulandığında klasik performans değerlendirme yöntemlerinin neden olduğu, işletmelerin bireyi mekanik bir üretim materyali gibi görme eğiliminden uzaklaştırarak, “insan” olarak görme eğilimine yönelttiği bir gerçektir.
A comparative study on compost preparation using lab prepared eco-enzyme and its effect on growth of plant species Phaseolus vulgaris
Authors: Narang Nitika , Hussain Athar , Madan Sangeeta
Published: November 2022

The augmented rise in population in the last few decades has resulted in gigantic increase in the solid waste production in India and around the Globe. The conventional composting methods are slow and sluggish process that has resulted in the advancement techniques for the emergence in new rapid composting processes. Use of eco-enzyme is such a rapid technique that helps to degrade the solid waste in a very accelerative manner. The present study has been carried out by preparing eco-enzyme using the kitchen waste and with the objective to utilize it for degradation of agricultural wastes and preparing compost for its utilization for different plant species as soil conditioner and fertilizer. The prepared eco-enzyme was added during the composting process in each batch with concentration variation of 10%, 15% and 20% (V/V) once every week. The pH value of the final prepared compost was found to be within neutral rage of 6.51 ± 0.03–7.88 ± 0.50 in all the samples. The maximum organic nitrogen concentration of 1.02 ± 0.04% has been observed in prepared sawdust compost with 10% eco-enzyme. The maximum vigor index value of 587 cm has been assessed in the compost produced using sawdust with 10% eco-enzyme when used for plant species Phaseolus vulgaris. The present study will be having two-fold advantage as the environment will get rid of such wastes as the same can be utilized as resource and it will also be helpful for the farmers from economical point of view.
Detecting Use of Patient Dietary Supplements in Free Text Clinical Notes
Authors: Redd Douglas , Workman T. Elizabeth , Shao Yijun , Cheng Yan , Garvin Jennifer H. , Brandt Cynthia , Zeng-Treitler Qing
Published: November 2022

Background: There is widespread use of dietary supplements, some prescribed but many taken without a physician’s guidance. There are many potential interactions of supplements with both over the counter and prescription medications. Many of these are not known to the patient. Documentation of supplement use is incomplete in structured medical records, however additional information about supplements is often found in unstructured clinical notes. Natural language processing (NLP) techniques can be used to detect supplement use in these notes.
Methods: We study a group of 377 patients from three healthcare systems and develop an NLP system to detect supplement use. We then use surveys of these patients to investigate correlation between self-reported supplement use and NLP predictions from the clinical notes.
Results: We attain an F1 score of 0.914 on creation of the model for all supplements. Individual supplement detection had variable correlation with survey responses, ranging from and F1 of 0.83 for calcium, to F1 of 0.39 for folic acid.
Conclusions: We demonstrate the ability to capture the use of dietary supplements from free text clinical notes, enabling clinical studies including drug interactions and outcomes research. Generalizability is demonstrated due to the use of notes from a nationwide electronic health record system. We also show that patients from three healthcare systems self-reported supplement use that often contradicted what was recorded in the clinical record.