bluuebunny/crossref_metadata_2025 huggingface dataset:
Express method for analyzing the efficiency of endodontic files in dentistry
Authors: Avilov A V , Avilova N V , Tsybri I K
Published: August 2020

When treating root canals of teeth, deformations occur, changes in the geometric characteristics of the surface of endodontic files, which causes their breakages and problems when removing fragments of files from the root canals of the tooth. The article offers a method of express analysis of the preliminary assessment of the serviceable state of the endodontic file to exclude its damage in the root canal of the tooth. The method consists in studying the amplitude-frequency characteristics of endodontic files (natural frequencies) using the software of modern smartphones and sound spectrum analyzers for smartphones with the Android operating system. Research results are presented. It is proved that the natural oscillation frequency of new endodontic files ranges from 1260-1280 Hz, and the natural oscillation frequency of deformed endodontic files increases to 1520-1560 Hz or more.
Development and in Vivo Evaluation of a Biodegradable Vascular Graft Reinforced with a Fused PCL Filament
Authors: Krivkina E O , Klyshnikov K Y , Rezvova M A , Sevostyanova V V , Tkachenko V O , Glyshkova T V , Mironov A V , Antonova L V
Published: August 2020

Tissue-engineered vascular grafts developed for cardiovascular surgery must be fully functional after implantation, resistant to all types of kinks, compression and burst pressure. One of the approaches to improve mechanical properties includes the reinforcement with an outer polymeric sheath. This study was aimed at evaluating the mechanical properties of a tissue-engineered vascular graft reinforced with a fused PCL filament and in vivo testing in a carotid artery of sheep within one year.
Kidney stones analysis by ICP-OES
Authors: Tsygankova A , Lundovskaya O , Aleksandrova A , Korolkov I , Filatov E , Pechkovsky E , Yarin G , Safonov D , Vilgelmi I , Glushkova N , Gubanov A.
Published: August 2020

The elemental composition of 100 oxalate type (only whewellite, weddellite and their mixture) urinary stones was determined by ICP OES. The calcium content varies from 130 to 320 g/kg; phosphorus – from 1.6 to 28 g/kg; sodium – from 0.54 to 8.7 g/kg; Ba, Fe, K, Li, Mg, Sr and Zn – from 0.0002 to 2.0 g/kg. The correlation analysis (Spearman rank correlation) showed a very weak tightness of the relationship between the elements of Ca/Li; a weak bond tightness for the pairs of elements Ba/Ca, Ba/Mg, Ba/Sr; Ca/Fe, Ca/Na, Ca/Sr; Fe/Mg, Fe/P, Fe/Sr, Fe/Zn; Li/Mg; Mg/Sr, Mg/Zn; P/Zn; average bond tightness for pairs of elements Ca/Mg, K/Na, Mg/P. All these correlations are positive.
Creation of applied intelligent system for diagnostics of cognitive and emotional-volitional sphere of post-stroke patients at different stages of rehabilitation treatment
Authors: Yankovskaya A , Obukhovskaya V , Nazmetdinova D
Published: August 2020

In this paper, we describe the creation of the medical diagnostic intelligent system, which is used for the analysis of cognitive and emotional-volitional sphere of post-stroke patients at different stages of rehabilitation treatment (IS DICEV). The applied IS DICEV is constructed with the help of intelligent instrumental software IMSLOG and is based on test methods of the pattern recognition, fault-tolerant mixed diagnostic tests. The use of the applied IS DICEV will allow revealing various kinds of regularities in the cognitive and emotional-volitional sphere of post-stroke patients, as well as finding diagnostic decisions and justifying those using graphical tools. These goals are very important for tracking the dynamics of rehabilitation treatment.
Mathematical and information support of the program complex for planning of the harvesting of wild-growing products
Authors: Ivanyo Ya , Petrova S , Polkovskaya M
Published: August 2020

The paper presents the results of the development of information and software for a program complex of modeling the harvesting of wild-growing food resources. Linear programming models with interval parameters are proposed to optimize the harvesting of wild-growing food resources. In addition to models with interval parameters, a model of stochastic programming is developed under the condition of stationary state of the yield series of wild-growing crops. Models may contain dependent and independent coefficients for unknowns. The database includes information on the yield of wild crops, labor resources, product prices, questionnaire data filled in by procurement staff, results of field studies on a preliminary assessment of possible harvest, maps showing the territories of commercial resources for each species. The developed software package can be used to simulate the harvesting of wild food resources in any regions with commercial reserves of wild plants. The development results were tested for some municipal districts of the Irkutsk region and model clusters.
Analysis of Statistical Methods on Plurilinguistic Quantitative Data
Authors: Krasnopeeva T , Gromov M
Published: August 2020

This multidisciplinary study deals with a population cluster of migrant multilinguals as a complex phenomenon of Social Physics with the help of the mathematical-statistical tools. It enlightens two statistical methods used to analyse the quantitative data on the plurilingual competence of the university students: the Rasch analysis and the T-test. These methods are able to give a more profound picture of the individual migrants’ plurilingual ability in terms of migration as a sociophysical phenomenon. We consider the strengths that each method has as the physical values in order to understand the linguistic behavior of migrant flow as a complex matter and each migrant student as a part of this flow. Our multidisciplinary study empirically investigates whether the positive impact of the statistical methods is relevant by using recent dataset on the example of the multilinguals’ social cluster. The main conclusion of the study shows the positive impact of the Rasch model in measurement of complex sociophysical matters with respect to the ability of a migrant social cluster to the plurilingualism, and results in the statement that this tool is capable to decipher the empirical data in a qualitative manner, in particular, for its application to the group educational trajectories. However, T-test showed the statistical insignificance of the current data set if this data set is used to predict further development of plurilingual competence.
Using an ESP8266 Microcontroller to Develop a Learning Game
Authors: Chursin G , Semenov M
Published: August 2020

This article discusses the possibility of connecting an ESP8266 microcontroller to a learning game developed on the Unity3D game engine. The game is aimed at teaching and developing the skills of students, such as mathematics, physics, programming and the basics of robotics. The paper presents a diagram of the interaction of the microcontroller and the game, as well as a comparative analysis of the Arduino and ESP8266 platforms. Comparison of the Arduino firmware process via USB and ESP8266 over Wi-Fi is carried out. It was possible to establish that the firmware by air takes an average of 2 seconds more, which does not affect the gameplay.
Robust signal processing in nonparametric autoregression
Authors: Pchelintsev Evgeny , Povzun Maria
Published: August 2020

In this paper we consider the problem of a robust adaptive estimation of a periodic signal modeled by the nonparametric autoregression. We develop a new sequential model selection method, using improved estimation approach and the efficient sequential kernel estimators. This procedure is based on the sequential estimators. For robust quadratic risk of proposed estimate we obtain sharp oracle inequality that allows us to establish the efficiency property of this model selection procedure. We give the Monte Carlo simulation results for numerical comparing of the risks of proposed improved procedure and ordinary least squares estimates.
Applying a Principle Component Analysis to Search for Objects on Historical Territories by the Spectral Brightness of Vegetation
Authors: Zlobina A G , Zhurbin I V
Published: August 2020

An approach is proposed for analyzing multispectral aerial photography data to identify traces of human activity; this approach is based on the application of a principal component analysis. Its efficiency is illustrated by a case study of historical territory – the Pudemsky Ironworks (Udmurt Republic, Russia). About 67% of the arable land area abandoned in the latter half of the 19th century is revealed. Nowadays, this site is covered with forest vegetation and no longer has any striking visual or spectral differences from the environment.
Simulation of multiple supersonic jets impinging with obstacle
Authors: Kagenov A M , Kostyushin K V , Aligasanova K L , Kotonogov V A
Published: August 2020

In this paper the mathematical modeling of the interaction of a twin supersonic jet with a flat obstacle in Mars environment and Mach numbers at the nozzle exit 4.5 are considered. The effect of the distance between the nozzles on the shock-wave structure of the jets and their force on obstacle are investigated. The distance ranged from 0.1 to 4 nozzle exit diameters (L/D). It is found that the self-oscillating mode is observed only for the case L/D = 1.5, for the rest of the cases the stationary mode are implemented. With an increase in the distance between the nozzles, the maximum pressure on obstacle decreases from 33 kPa to 13 kPa. In the case when the plumes do not close L/D = 4, the force effect of the jets is 2.5 times less compared to L/D = 0.1.
Features of propagation of slow deformation perturbations in geomedia with faults
Authors: Kazakbaeva A A , Smolin I Yu , Makarov P V
Published: August 2020

Our work is performed in the framework of the mathematical model suggested by P.V. Makarov to describe the joint generation and propagation of ordinary stress waves (propagating with the sound speed) and slow deformation waves of the inelastic nature in loaded elastoplastic media. Structural models of block media with weakened regions (faults or deformation sites) are constructed for test calculations on generation and propagation of slow deformation waves in nonlinear dissipative media. The features of propagation of deformation waves are investigated for different fault orientations and implementations of the algorithm of cellular automata for transmitting slow perturbation. The zigzag and diamond nature of propagating fronts of slow deformation disturbances is revealed.
Algorithms for ranking and unranking the combinatorial set of closed questionnaire answers
Authors: Shcheglov P P , Filippov G A , Shablya Y V , Kruchinin D V
Published: August 2020

In this paper, we study the combinatorial set of closed questionnaire answers with a specified minimum number of correct answers. For this combinatorial set, we obtain an explicit formula for its cardinality function. Using the obtained cardinality function, we construct the corresponding AND/OR tree structure and determine the bijecion rules for this AND/OR tree and the considered combinatorial set. In addition, we develop ranking and unranking algorithms for the combinatorial set.
Designing high performance, power-efficient, reconfigurable compute structures for specialized applications
Authors: Shatravin V , Shashev D V
Published: August 2020

In this paper, a new approach to design high-performance and power-efficient computing structures are proposed for machine learning tasks. Such structures can be very useful in some specialized applications such as autonomous robots, mobile devices, smart sensors for the Internet of Things (IoT) and so on. This approach is based on the concept of reconfigurable homogeneous computing environments. Major advantages of this approach are discussed. The process of designing a set of elementary operations for such structures is described in detail using an example with a typical Feed-Forward Neural Network (FFNN) and its training module.
Reducing dimensions of the histogram of oriented gradients (HOG) feature vector
Authors: Shidlovskiy S V , Bondarchuk A S , Poslavsky S , Shikhman M V
Published: August 2020

The article discusses the basic principles of a HOG-descriptor. A method is proposed for reducing dimensions of the feature vector obtained using the HOG-descriptor by applying the convolution operation and converting the resulting values of gradients and their directions. After using new feature vectors for training, the Support Vector Machine (SVM) classifier showed a 37-fold increase in performance when processing an image with a resolution of 282×159 pixels.
VLSI architecture with a configurable data processing path based on serial distributed arithmetic
Authors: Tarasov I E , Potekhin D S
Published: August 2020

The article considers the VLSI architecture intended for streaming data processing using a configurable path based on sequential distributed arithmetic. The development of specialized VLSIs is advisable if there is a need for serial production of devices, and the domain of application of such VLSIs decreases as the capabilities of the CPU, GPU and FPGA expand. The alternative approach is to build configurable VLSIs that can efficiently perform computations in related applications. The solution under consideration is focused on performing stream operations, including FIR filters and other tasks based on the operation “multiplication and accumulation”, for example, neural networks and deep learning algorithms. The architecture provides for compliance with the GALS (Globally Asynchronous, Locally Synchronous) approach, which allows placing many independent computing nodes in the VLSI. The characteristics of VLSI were evaluated and the areas of preferred application of the considered architecture were considered.
Improving the performance of processing special computing tasks using an asynchronous actor model
Authors: Andrianova E G , Sachkov V E , Zhukov D O
Published: August 2020

The use of third-party ready-made solutions to perform special computing tasks (SCT): processing text arrays in a natural language, the use of cryptography methods in data transmission networks, machine learning in solving applied problems, scientific computations and many other ones is a common practice in modern development of software systems. However, the use of third-party ready-made software solutions often leads to their poor optimization for parallel and distributed operation and to the difficulty in vertical and horizontal scaling, impossibility of modifying a solution, e.g., due to its legal protection, etc. In order to solve these problems, an asynchronous actor model can be used that facilitates developing software for processing special computing tasks. In addition, an asynchronous actor model allows parallel processing of input tasks, provides asynchronous operation, and extends its functionality to third-party ready-made solutions, that it is impossible or forbidden to modify to meet user’s or optimization requirements. Methods, algorithms, and the entire logic of asynchronous actor operation involve transitions of actors from one state to another under the effect of input messages and returning the results of processed tasks to the frame system. This allows setting an automatic grammar and for using methods and approaches for developing software systems based on finite-state automata. The asynchronous actor operation scheme is represented by a directional state graph, which allows using the mathematical apparatus of the finite-state automaton theory (the Mealy model) to describe the same. The developed model is convenient for designing and organizing the SCT processing using computer systems. The use of the asynchronous actor model makes it possible, in special operation modes, to increase the performance of poorly optimized SCT without modifying the same, as compared to task processing without using the asynchronous actor model.
Diagnostics of aluminum alloys with friction stir welded joints based on multivariate analysis of acoustic emission signals
Authors: Dmitriev A A , Polyakov V V , Kolubaev E A
Published: August 2020

The acoustic emission method was applied to study aluminum-magnesium alloys produced by friction stir welding. Alloy specimens were tested under static tension with simultaneous recording of acoustic emission, applied load, and elongation. The recorded acoustic emission signals were processed using projection methods of multivariate data analysis; the informative features used were the coefficients of wavelet discrete decomposition which characterize the low-frequency form of the signal. It is shown that the proposed approach allows the partition of signals formed on different stages of plastic deformation and fracture. Strong differences in acoustic emission signals were revealed and described to be due to the formation of highly defect structure in the weld zones in different welding modes. The obtained results can be useful for acoustic emission diagnostics of welded joints in structures of metal alloys exposed to external loads.
Computations of cross-correlation functions on a single board Raspberry Pi computer
Authors: Faerman V A , Shvetsov M P , Tsavnin A V
Published: August 2020

The paper discusses the implementation of correlation algorithm for time delay estimation on a Raspberry Pi single-board computer. The implemented correlation algorithm is based on Fourier transform. In the course of the study, we applied two alternative solutions for the software implementation of discrete Fourier transform. The first solution stands on FFTW library and uses general-purpose quad-core ARM Cortex A53 processing unit. The alternative method uses VideoCore IV graphic processing unit and is implemented via firmware GPU_FFT library. We have performed a computational experiment on a Raspberry Pi 3B to determine which solution is more preferable for the implementation of correlator. After a comparative study we figured out that estimated processing time is highly dependent on computations parameters and input signals. For small FFT window sizes CPU is proved to be a preferable option. However, for large FFT windows GPU allows significantly accelerating the computations. At some point, you can achieve even better performance by using batching and GPU for direct FFT and CPU for inverse FFT. According with the results, we have concluded that both alternatives have their own potential advantages and particular drawback. We also establish, that Raspberry Pi 3 B computer with HiFiberry extension can be used as a real-time correlator for audio signals.
Use of trainable wavelet transform with adaptive threshold filtering for noise reduction of speech signals
Authors: Lependin A A , Ilyashenko I D , Nasretdinov R S
Published: August 2020

A method of noise reduction based on an adaptive threshold filtering over trainable wavelet transform was proposed. The restrictions on the trainable transform filter parameters were provided by a set of quadratic regularization terms. As an analog of the “hard” and “soft” threshold functions we used their smooth infinitely differentiable versions. The parameters of trainable wavelet transform, and threshold values were estimated by backpropagation and gradient-based optimization algorithm with an adaptive momentum estimation. Results of the proposed method were compared with an approach based on fixed discrete wavelet transform and non-adaptive global and level-depended threshold algorithms on the model problem. We used signal-to-noise ratio between suppressed and clean signals to numerically estimate the efficiency of noise reduction. We showed that the best results were obtained when the proposed trainable method with Daubechies 4 wavelet filters fine-tuning and adaptive level-dependent thresholding were applied.
Optimization method for non-cooperative iris recognition task using Daugman integro-differential operator
Authors: Petrov I , Minakova N
Published: August 2020

We considered the issues arising when Daugman’s integrodifferential operator is used to localize iris edges. Daugman’s integro-differential operator is a widely common method to localize the iris, however, problems of the operator optimization poorly presented in the literature. The article considers existing methods of optimization of the operator applied at the iris recognition step. Based on the provided research we proposed using Nelder-Mead and Differential Evolution methods to optimize the integro-differential operator. The problems of the iris localization and their solving methods were considered. The article focuses attention on non-cooperative iris recognition. The very general boundary conditions based on iris’s anatomy which are not dependent on captured image properties were defined. The results of the comparative analysis of the accuracy and performance of selected optimization methods of Daugman’s integrodifferential operator were presented at the experimental results chapter. It was found that the Differential evolution optimization method gives fine performance and correctness. It was concluded that the Differential evolution is expedient as Daugman’s integro-differential operator optimization method.
Automated analysis of x-ray images using transparency masks
Authors: Dabagov A R , Tomakova R A , Alekseev V A , Kondrashov D S
Published: August 2020

The method for classification of x-ray images, which is implemented in this article, improves the differential diagnosis of socially considerable diseases. The novelty of this method is that the input digital x-ray image is supplemented by a transparency mask which is found by image segmentation, and the classified sign vector is formed by pixels which aren’t masked by the transparency mask. The original x-ray image is divided into segments to classify morphological structures with pathological formings. The classification of the selected segment is implemented by a modified convolutional neural network which uses pooling layers and layers of a fully-connected neural network. The proposed classifier allows dividing patients into two groups: patients without found pathology and patients with disorders of health condition. The found morphological pathological formings help clinicians to find the most promising way for prevention of the disease development at the patients, saving money and time.
Use of the university’s enrolment campaign database for the development of a computer model to predict student expulsion
Authors: Zharikov A V , Zhuravlev E V , Zhurenkov O V , Kozlov D Yu
Published: August 2020

The article discusses the construction of a computer model to predict the problems occurrence in students in the educational process at the university. The following data sources of Altai State University were used for this purpose: “Admissions Office” (enrollees database) and “Dean’s office” (database of students) for 2013-2018. These data were combined using developed SQL scripts. While analyzing the obtained combined data set, we had to face the difficulties typical for solving data analysis problems. Thus, it turned out that there are incomplete and inconsistent data or cases when one and the same entity is named differently, etc. In order to solve these problems, we wrote a script in the R programming language using regular expressions, the data were unified and standardized, and the missing data were restored using the information from other fields of the data set. Then we discarded the variables with the near-zero dispersion, which could not make a significant contribution to the developed predictive model. After that, the data set under study was divided into 2 parts: the 2013-2017 data were taken to build a predictive model with the use of the logistic regression algorithm, while the data for 2018 were used, in fact, to predict whether a particular student would be expelled. It should be mentioned that the 2013-2017 data were divided into the training and test samples in the proportion of 90% and 10% correspondingly. The test result of the computer model built in the R programming language showed satisfactory accuracy; the most significant factors affecting student expulsion were also identified. The paper substantiates the economic feasibility of using the developed computer model at the university.
Diagnostics of diabetic polyneuropathy in children and adolescents using data mining methods
Authors: Krotova O S , Moskalev I V , Nazarkina O M , Khvorova L A
Published: August 2020

The article considers the application of data mining methods to develop a diagnostic model for one of the most common and dangerous diabetes mellitus complications – diabetic polyneuropathy characterized by damage to peripheral nerve fibers. The article explores the possibility of diagnosing diabetic polyneuropathy with the use of machine learning methods. The data base of the study includes 3204 anonymized medical records of children and adolescents with type 1 diabetes residing in the territory of Altai krai. 1100 records hold data on diabetic polyneuropathy. Medical records contain different information: patient complaints, medical case history, test results. The attribute space is represented by 40 different indicators. In the course of the study, we considered the differences between the attribute values in two groups, built the attribute space ensuring the best classification quality. The article presents the results of applying various methods to transform the source data, evaluates the quality of the resulting model. The implementation of all the study phases was carried out with the use of the Python high-level programming language.
Numerical methodology for the assessment of asymmetry coefficient of aerosol scattering in near IR region of spectrum
Authors: Pashnev V V , Pavlov V E , Matyuschenko Yu Ya
Published: August 2020

Based on the aerosol model of IAP RAS, a methodology has been developed for determining the aerosol coefficient of asymmetry of scattered radiation for natural particles. The source of information is the calculation data for the brightness of the cloudless sky in solar almucantarat with different spectral transparency of the atmosphere and the albedo of the underlying surface. By solving the radiation transfer equation by the Monte Carlo method, the asymmetry coefficients of diffuse fluxes were calculated, including the effects of single and multiple scattering, as well as light reflection from the earth’s surface. Tables of average values of the asymmetry coefficients are presented that assume the use of interpolation methods for calculating atmospheric parameters. A technique is proposed for determining the aerosol asymmetry coefficient from the results of observations of a similar integral coefficient, optical depth, and terrain albedo without using an apparatus of solving inverse problems. In this case, the brightness can be observed in any units, including directly the readings of the photometer. Software has been developed that implements this technique.
Reliability assessment of automatic process control systems for the production of concentrates of MD1 and MD2 nanostructures in terms of providing thermal vortex enrichment
Authors: Kolosov A D , Nebogin S A , Gorovoy V O , Govorkov A S , Kononenko R V
Published: August 2020

As part of the project to create a comprehensive resource-saving technology for the associated production of nanostructure concentrates, the reliability of the software package “Automated control system for the technological process of obtaining MD1 and MD2 nanostructure concentrates” was evaluated in terms of providing thermal vortex enrichment. The calculation of the reliability of the system was performed to assess the level of reliability and quantitatively determine the reliability indicators for the implementation of the functions of ACS TO 2.12. The object to be calculated was identified, the goals and objectives of the calculation at this stage, the nomenclature and the required values of the calculated reliability indicators were determined, the calculation method was selected that is adequate to the features of the object, the goals of the calculation, the availability of the necessary information about the object and the source data for the calculation. The initial data for the calculation were obtained and pre-processed; the values of the reliability indicators of the object were calculated. From a comparison of the calculation results with the reference values of the integral safety level (SIL) in accordance with IEC 61508, it follows that the maximum safety level of the ACS TO 2.12 SIL 2, the system availability is 98.97%, and the system uptime is 2 years. The probability of a dangerous failure of the PAZ system is 1.31·10−4, which corresponds to a high value of the integral safety level (SIL 4).
Computational technologies for the synthesis of decentralized control systems for multistage technological processes
Authors: Oskorbin N M
Published: August 2020

This article discusses the development of two-level hierarchical control systems for complex technological processes. This area of research relates to the problems of creating robotic complexes as part of automation systems for managing continuous multi-stage processes according to economic criteria. For the synthesis of decentralized systems of optimal control of processes with a sequential structure, it is recommended to use the dynamic programming method, which allows providing optimal coordinating solutions and justify the setting of local tasks for managing the stages of the technological process, provided that the current states of the input products of these stages are accurately or approximately observed. For an n-stage technological process in conditions of complete information, the problem of a coordinating subsystem is written, the solutions of which do not change for a set of values of input variables of the process and the time period of constancy of external and internal perturbations. It is shown that the implementation of algorithms for controlling individual stages of the process can be performed on the basis of microprocessor technology. Estimates of control error were obtained using a simulation model of a process control system with specified parameters. The article considers the possibility of applying the dynamic programming method in the management of multi-stage technological processes in conditions of incomplete information.
Clone detection in student programs based on lexical analysis of source codes
Authors: Polovikova O N , Ivanova V E
Published: August 2020

This article presents the development of automatic clone detection for verification students programs - the Detector of Clones. The Levenshtein Distance is used for the initial assessment of the similarity of the two token sequences which is calculated by the Wagner-Fisher algorithm. Verification of two programs is carried out by the fingerprint method and by the winnowing method. To improve the results of plagiarism assessment, an additional calculation was added to the implementation of the winnowing method: the detector compares not only the labels themselves, but also the sequences near the matching labels. The detector of clones is formed for the cycle of disciplines Object Oriented Programming, Object Oriented Analysis and Design on the Moodle platform. These tools support C-like languages (C++ and C#). In general, the work of the detector undoubtedly made it possible to increase the consistency in verification of student programs.
Analysis of seed quality indicators based on neural network
Authors: Barysheva N N , Guner M V , Baryshev D D , Pronin S P
Published: August 2020

The paper presents a neural network study of the data of wheat seed quality. It is established that the analysis of bioelectrical signals of wheat seeds based on a neural network can be used in practice for the solution of two problems - diagnostics of seed material quality and the evaluation of cleaning line quality (separation into fractions). The paper presents the results of initial data preparation, formation of a neural network, analysis of training data for two practical problems of classification. It was established using a neural network that there is a nonlinear dependence of the membrane potential maximum value and the signal rise time on the seed yield. The model makes it possible to predict yield in terms of the seed material quality. A nonlinear dependence of the maximum membrane potential, the signal rise time of wheat seeds and the seeds variety to one or another faction (speed of separation into the fractions in this example) was also established in this paper. Studies have shown that the seeds variety is an important informative feature for solving the problem of classifying seeds by fractions. Therefore, it is necessary to conduct additional studies with other wheat seeds varieties to apply this method in practice.
Description of the control system algorithm for the concurrent production of concentrates of MD1 and MD2 nanostructures in terms of providing thermal vortex enrichment
Authors: Gorovoy V O , Kolosov A D , Nebogin S A , Govorkov A S , Kononenko R V
Published: August 2020

As part of a series of works on the processing of aluminum and silicon waste products, including the project to create a comprehensive resource-saving technology for the production of nanostructure concentrates along the way, the algorithm of the automated system for controlling the technological process for producing concentrates of MD1 and MD2 nanostructures in part providing thermal vortex enrichment is described. Algorithms have been developed for the automated processing of incoming raw whole data into a real format in the parameter range, for controlling the three-position regulator (RO) with open/close commands with a built-in automatic step-by-step PI controller. The purpose and characteristics of the processes, the information used, the results of the solution, the decision algorithms, the requirements for the test example are described.
Registration and processing of experimental data in research of martensitic transformations in TiNi alloys by acoustic emission method
Authors: Gryaznov A S , Plotnikov V A , Makarov S V
Published: August 2020

The characteristics of the software and hardware system for recording acoustic emission in a wide frequency range are given. This system is used in studies of structural and phase transformations of metals and alloys under complex thermo-mechanical loading. The software and hardware system is the author’s development of the team and provides an affordable solution for recording and processing data in real time, which is a determining factor in the choice of technology for the study of structural-phase transformations of metals and alloys by method of acoustic emission. The requirements for acoustic emission technique differ slightly from the approaches common in the field of non-destructive testing. The hardware complex consists of a standard ADC with a sampling rate of at least 10 MHz, which provides spectrum registration in the range up to 1 MHz. The cascade of amplifiers are provides requirements for study by method of acoustic emission. The set includes a low-noise heater, an Arduino-based recording unit for related experimental parameters (temperature, mechanical stress, strain), and a personal computer. The software part of the system is a light scientific open source shell for conducting a physical experiment - the “dotScope”, developed by the author’s team. The program includes an extensible plugins system for working with various ADCs, plugins for real-time data processing, and plugins for post-processing.
Polyhedral programming and optimization of discrete control processes with polyhedral performance criterions
Authors: Filimonov A B , Filimonov N B , Matvienko V T
Published: August 2020

The elements of polyhedral programming theory considering the extreme tasks with polyhedral both goal and limiting functions are presented. The authors discuss the application of polyhedral programming device for optimal control tasks by discrete dynamic objects with polyhedral performance criterions. The decision of two optimization tasks of discrete control processes is reduced. They are the control task by finite state and the task of terminal stabilization.
Computational procedure for preparing the technical conditions for stowage and securing cargo in rail cars and containers
Authors: Olentsevich V A , Upyr’ R Yu , Gladkih A M
Published: August 2020

The transition of the railway industry from information management systems to systems with full management can be achieved by combining automated information systems integrated into production processes in the railway network. Russian Railways OAO acts as a driver for the development of modern technologies in the transport sector, aiming to increase efficiency in organizing the transportation process. Monitoring changes in customer needs, as well as focusing on increasing the value of services and products for consumers, including service quality improvement by digitalizing individual operations related to the cargo handling during loading, is becoming increasingly important. The introduction of the developed automated system for the preparation of technical specifications for the stowage and securing of cargo in rail cars and containers will increase production system organization quality in railway transport, as it will eliminate the incompetence, negligence and irresponsibility of workers associated with the handling, stowage and securing, reduce the time for preparing technical documentation, and improve the transport system operation quality. To achieve the stated goal, based on the studies, the author developed a computational decision-making procedure for the stowage and securing of cargo in the rail car, taking into account a possible two-coordinate shift. The procedure allows employees responsible for accepting cargo for transportation to assess the quality of the cargo securing according to the criterion of permissible shift at the initial stage of the transportation process. The developed automated system has many positive aspects. The security of the system significantly increases, the risk of errors is reduced, and the influence of the human factor is minimized. The complexity of the process of compiling a sketch of the stowage and securing of the cargo in the rail car loaded in accordance with the Technical Specifications is reduced. Most of the work is done by automated software, the cargo shipper has more time to control the loading process; time limits of various works and projects generally decrease.
Simulation of measuring transducers based on interconnected piezoresonators
Authors: Sedalishchev V N , Sergeeva Ia S
Published: August 2020

The article presents the results of simulation of the operating modes of measuring transducers based on interconnected piezoresonators. The article discusses modulation options as a function of the measured effects of the parameters of equivalent electrical equivalent circuits of piezoresonators and coupling elements between them. The article describes the features of using coupled oscillations in systems with two degrees of freedom for constructing differential-type sensors with a frequency and amplitude output. The article gave examples of the practical implementation of measuring devices based on coupled oscillations of piezoresonators.
Solution algorithms of an automated control system for a technological process of thermal vortex enrichment
Authors: Kondrat’ev V V , Gorovoy V O , Kolosov A D , Govorkov A S , Kononenko R V
Published: August 2020

As a part of the development of a comprehensive resource-saving technology and the organization of high-tech production of nanostructures based on carbon and silicon dioxide to improve the properties of building and structural materials, the algorithms for the software package Automated Control System for the Technological Process for Obtaining Concentrates of MD1 and MD2 Nanostructures are described in part providing thermal vortex enrichment. Algorithms have been developed for controlling an analog value according to the PID control law, stopping the production line in emergency mode, and regenerating bag filters as they become clogged. The purpose and characteristics of the processes, the information used, the results of the solution, the decision algorithms and the requirements for the test example are described.
Internal Control of Accounting Information System in Regional Chain Technology
Authors: Jia Xu
Published: August 2020

In the current enterprise development process, the accounting information system is widely used in the application of regional chain technology. The regional chain technology can effectively solve some problems in the accounting information system, and has certain positive significance for improving the level of solidified transactions and processing. However, there are still some limitations in the application of regional chain technology. Therefore, we need to study and analyze the application of regional chain technology in the current internal control process of accounting information system, so that we can further improve the application effect of regional chain technology
Street Lamp Intelligent Monitoring System Design Based on NB-IoT Technology
Authors: Tian Ye , Wang Yali
Published: August 2020

In view of the problems in the practical application of traditional urban Lighting systems, such as inconvenient centralized control of street lamps, untimely information monitoring, and low efficiency of human inspection methods, a design scheme for street lamp monitoring systems based on narrow-band Internet of Things (NB-IoT) technology is proposed. In this solution, the STM32L431 RCT6 chip is used as the main control chip, and the NB-IoT module is used as the communication module. It is connected to the Huawei Internet of Things management platform, and an application program is developed on the application side to remotely monitor the street lights in real time. The experimental results show that the system realizes real-time monitoring and intelligent control of street lamps.
ENMFM Algorithm Applicable for the Multi-Source Heterogeneous Data Source Model of Power Grid Regulatory Cloud Platform
Authors: Haibo Lan , Linpeng Xiao , Yongzheng Mu , Liangjing Cao , Huiyong Liu , Tianyue Lou
Published: August 2020

With the rapid development of the intelligent grid technology and the arrival of the informationalized big data era, the application of computing method to power grid specialty will be a key step for the value of power grid data. Grid data record is not standard, the confusion caused by a device with multiple recording, professional equipment for power grid name recognition and use of data and algorithm based on identification service work will gradually replace artificial recognition, this paper presents a ENMTM algorithm with the grid raw data, which can identify accurately the same equipment with different names.

The equipment name record is an important data of power grid business scenario, however, the same device is easy to describe in different situations or staff’s records, which causes data redundancy and equipment confusion caused by error identification of equipment name. The name recognition is to segment the device name string into a structured element unit which can be calculated by the computer, so as to realize the identification of multiple words with one meaning and devices with different names. In this paper, we study the recognition algorithm of recognition, the establishment of professional word library, segmentation and calculation of similarity recognition. The results show that the ENMFM result error rate is only 3.13%, on the basis of segmentation results and the confusion matrix of device name similarity can be seen that the positive samples has good prediction. In addition, in the experiment, the Top N items of higher similarity were given, which provided the staff with professional judgment to ensure the rigor of work.

The calculation method to solve the name recognition of power equipment can greatly reduce the human work of identifying equipment, improve the work efficiency of power professional business scenarios, and lay a solid foundation for the unified data environment of intelligent grid.
CIM/G graphics automatic generation in substation primary wiring diagram based on image recognition
Authors: Peng Zhang , Yan Geng , Zhongshan Qu , Huiyong Liu , Mouying Li , Shengnan Liu
Published: August 2020

With the further development of smart grids, people put forward more requirements for the intelligent level of the dispatching automation system, and the demands for unified substation standard, realization of unified association and sharing of models, data and graphics are gradually increasing. Relying on the CAD, PDF and other graphic format files of the substation, we use grid recognition technology based on image recognition and OCR to identify standard primitives, topological connections, device names and other information, and automatically draw standard CIM/G files. For the identified CIM/G file, we use related technologies of natural language to associate the primitives in the CIM/G file with the model data, and form the overall solution for a grid substation wiring diagram primitive recognition, text recognition, topology recognition, model association. We also construction substation graphic file recognition and construction system based on the image recognition to support the maintenance of the substation graphic inside the control center. Through the system deployment application, it is verified that the method can effectively reduce the workload of manual maintenance and improve work efficiency.
Refractive Index Sensing Based on Terahertz Spoof Surface Plasmon Polariton Structure
Authors: Chen Xinda , Xiao Huaibao , Lu Guizhen , Zhao Ruiqi
Published: August 2020

Surface plasmon resonance sensing technology has many advantages, such as high sensitivity, no interference to samples and real-time monitoring. It has been widely used in biomedical detection, food safety testing and environmental protection etc. How to increase the measurement sensitivity is a key technology in these applications. In this paper, a stepped surface plasmon resonance sensing structure is proposed, which is easy to be machined. The influence of its structure parameters on the sensing sensitivity is simulated and analyzed. The results show that the sensitivity can be increased to 2.44THz/RIU by optimizing the structure parameters when the refractive index of the liquid to be measured is between 1.33 and 1.36.
A new clustering and sorting algorithm for radar emitter signals
Authors: Li MingWei , He MingHao , Han Jun , Tang YuWen
Published: August 2020

The traditional k-means clustering algorithm needs to set parameters manually in radar signal sorting application, which is sensitive to isolated points and prone to “batch” phenomenon, and the selection of initial clustering center has a direct impact on clustering effect. In order to solve the above problems, a radar signal sorting algorithm based on data field and improved k-means clustering is proposed. Firstly, the potential values of all data samples are calculated according to the theory of data field. After the isolated points are removed, the maximum local potential values are found. The nearest sample data is selected as the initial clustering center, and the maximum number of local potential values is selected as the clustering number. Finally, the improved k-means clustering algorithm is used to complete the radar signal sorting. The algorithm can automatically obtain the initial clustering center and the number of clusters, and the clustering results have larger inter cluster distance and smaller intra cluster distance, so the clustering results are better. Simulation results verify the feasibility of the algorithm.