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Author Index, 2024, Volume 11
S. S. Adyshkin, see A. V. Yudin
Comp. nanotechnol., 2024, Volume 11:1, 25–35
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D. G. Andryushenkov, see N. M. Hadi
Comp. nanotechnol., 2024, Volume 11:3, 64–80
|
V. S. Artemyev, A. S. Maksimov
Implementation of Simoyu method for modeling of transients of control object
Comp. nanotechnol., 2024, Volume 11:3, 43–51
|
V. S. Artemyev, N. V. Mokrova
Method first approximation stability analysis of electrical control systems
Comp. nanotechnol., 2024, Volume 11:3, 52–56
|
M. A. Belov, see A. V. Zhivetyev
Comp. nanotechnol., 2024, Volume 11:3, 81–88
|
D. N. Bogomolov, S. B. Plotnikov
The possibilities of using Big Data technologies in solving problems of processing data on atmospheric air pollution
Comp. nanotechnol., 2024, Volume 11:1, 162–170
|
A. A. Breev, see D. V. Kornienko
Comp. nanotechnol., 2024, Volume 11:1, 57–67
|
E. S. Budaev
Development of a web application for intelligent analysis of customer reviews using a modified seq2seq model with an attention mechanism
Comp. nanotechnol., 2024, Volume 11:1, 151–161
|
A. N. Chesalin, see N. M. Hadi
Comp. nanotechnol., 2024, Volume 11:3, 64–80
|
S. D. Danilova
Development of a visual odometry model based on sensors and video stream analysis
Comp. nanotechnol., 2024, Volume 11:1, 36–47
|
L. A. Demidova, see V. V. Maslennikov
Comp. nanotechnol., 2024, Volume 11:2, 58–85
|
A. A. Dyda, see A. M. Shevchenko
Comp. nanotechnol., 2024, Volume 11:1, 127–134
|
A. N. Fedorets, see D. D. Sileshi
Comp. nanotechnol., 2024, Volume 11:1, 104–111
|
A. N. Fedorets, see D. D. Sileshi
Comp. nanotechnol., 2024, Volume 11:1, 112–120
|
A. M. Frolov, see D. D. Sileshi
Comp. nanotechnol., 2024, Volume 11:1, 112–120
|
L. G. Gagarina, see K. S. Nikolaev
Comp. nanotechnol., 2024, Volume 11:2, 43–50
|
S. O. Golovanov, see R. V. Shamin
Comp. nanotechnol., 2024, Volume 11:1, 48–56
|
O. A. Gorkusha, see V. G. Zavodinskó
Comp. nanotechnol., 2024, Volume 11:1, 121–126
|
N. V. Grineva, see N. V. Grineva
Comp. nanotechnol., 2024, Volume 11:1, 135–150
|
N. V. Grineva, see A. M. Moiseenko
Comp. nanotechnol., 2024, Volume 11:1, 68–77
|
N. V. Grineva, N. V. Grineva
Neural networks in the task of genre classification of musical compositions
Comp. nanotechnol., 2024, Volume 11:1, 135–150
|
P. Yu. Grosheva, see A. V. Yudin
Comp. nanotechnol., 2024, Volume 11:1, 25–35
|
P. Yu. Grosheva, see R. V. Shamin
Comp. nanotechnol., 2024, Volume 11:1, 48–56
|
N. M. Hadi, D. G. Andryushenkov, A. N. Chesalin
Algorithm for identifying abnormal actions
Comp. nanotechnol., 2024, Volume 11:3, 64–80
|
N. S. Kireychenkov, see A. V. Medvedev
Comp. nanotechnol., 2024, Volume 11:2, 35–42
|
P. V. Komarov, D. Potekhin
Architecture of a device for monitoring the health of the human body based on ultrasonic measurements
Comp. nanotechnol., 2024, Volume 11:2, 51–57
|
P. V. Komarov, D. Potekhin
Investigation of a dynamically changing signal using wavelet transformations
Comp. nanotechnol., 2024, Volume 11:3, 34–42
|
D. V. Kornienko, A. A. Breev
Modeling the processes of interaction between team members during the implementation of complex software products
Comp. nanotechnol., 2024, Volume 11:1, 57–67
|
D. V. Kornienko, A. V. Nikulin
Visualization of microservices-based information system architectures using opentelemetry data
Comp. nanotechnol., 2024, Volume 11:1, 94–103
|
I. V. Kuchumov
Algebraic models for data and knowledge representation in modern database management systems
Comp. nanotechnol., 2024, Volume 11:1, 78–84
|
A. A. Kulikov
Using genetic algorithm in clustering problem for weighted oriented graph
Comp. nanotechnol., 2024, Volume 11:2, 93–101
|
A. A. Kulikov
Improvement of neural network model topology for object segmentation in digital images based on convolutional neural networks
Comp. nanotechnol., 2024, Volume 11:3, 57–63
|
V. A. Londikov, S. Yu. Lukanov, O. Yu. Timoshevskaya
Development of an intelligent control algorithm for a group of unmanned aerial vehicles
Comp. nanotechnol., 2024, Volume 11:2, 86–92
|
S. Yu. Lukanov, see V. A. Londikov
Comp. nanotechnol., 2024, Volume 11:2, 86–92
|
L. V. Makhnach, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:1, 224–234
|
S. E. Makievskiy, see A. V. Yudin
Comp. nanotechnol., 2024, Volume 11:1, 25–35
|
A. S. Maksimov, see V. S. Artemyev
Comp. nanotechnol., 2024, Volume 11:3, 43–51
|
D. S. Malygin
Trends and perspective directions in the development of software programming
Comp. nanotechnol., 2024, Volume 11:1, 184–192
|
V. V. Maslennikov, L. A. Demidova
Modification of a quantum-inspired genetic algorithm for numerical optimization using qudit under conditions of simulating quantum decoherence
Comp. nanotechnol., 2024, Volume 11:2, 58–85
|
M. A. Maslova
An automated approach to selecting sentences for test case generation
Comp. nanotechnol., 2024, Volume 11:2, 29–34
|
A. V. Medvedev, A. A. Medvedev, M. D. Shuchkov
The concept of food management using rfid technology: minimizing losses and increasing consumer awareness
Comp. nanotechnol., 2024, Volume 11:1, 85–93
|
A. V. Medvedev, A. A. Medvedev, N. S. Kireychenkov
Implementation of rpa bots in cold supply chain logistics
Comp. nanotechnol., 2024, Volume 11:2, 35–42
|
A. A. Medvedev, see A. V. Medvedev
Comp. nanotechnol., 2024, Volume 11:1, 85–93
|
A. A. Medvedev, see A. V. Medvedev
Comp. nanotechnol., 2024, Volume 11:2, 35–42
|
S. S. Mikhaylova
Research and development of algorithms and methods for constructing three-dimensional computer models of real objects
Comp. nanotechnol., 2024, Volume 11:1, 13–24
|
S. S. Mikhaylova, S. A. Sabirova
Development of a cryptocurrency trading strategy using machine learning methods
Comp. nanotechnol., 2024, Volume 11:2, 11–21
|
A. M. Moiseenko, N. V. Grineva
The effectiveness of the A2C algorithm in relation to classical models of the theory of economic growth
Comp. nanotechnol., 2024, Volume 11:1, 68–77
|
N. V. Mokrova, see V. S. Artemyev
Comp. nanotechnol., 2024, Volume 11:3, 52–56
|
K. S. Nikolaev, L. G. Gagarina
Model for data objects selection by search image for intelligent recommender systems
Comp. nanotechnol., 2024, Volume 11:2, 43–50
|
A. V. Nikulin, see D. V. Kornienko
Comp. nanotechnol., 2024, Volume 11:1, 94–103
|
V. V. Pan'kov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:1, 224–234
|
V. V. Pan'kov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 145–156
|
V. V. Pan'kov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 174–190
|
D. A. Petrosov
Application of the theory of Petri nets in the development of simulation models of business processes based on the IDEF3 methodology
Comp. nanotechnol., 2024, Volume 11:3, 89–97
|
S. B. Plotnikov, see D. N. Bogomolov
Comp. nanotechnol., 2024, Volume 11:1, 162–170
|
N. I. Plusnin, see V. G. Zavodinskó
Comp. nanotechnol., 2024, Volume 11:1, 121–126
|
Z. A. Ponimash, M. V. Potanin
Non-iterative calculation of parameters of a linear classifier with a threshold activation function
Comp. nanotechnol., 2024, Volume 11:1, 171–183
|
M. V. Potanin, see Z. A. Ponimash
Comp. nanotechnol., 2024, Volume 11:1, 171–183
|
D. Potekhin, see P. V. Komarov
Comp. nanotechnol., 2024, Volume 11:2, 51–57
|
D. Potekhin, see P. V. Komarov
Comp. nanotechnol., 2024, Volume 11:3, 34–42
|
E. V. Pustovalov, see D. D. Sileshi
Comp. nanotechnol., 2024, Volume 11:1, 104–111
|
E. V. Pustovalov, see D. D. Sileshi
Comp. nanotechnol., 2024, Volume 11:1, 112–120
|
M. R. Rakhimov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 174–190
|
R. Kh. Rakhimov
Pulse tunnel effect: fundamentals and prospects for application
Comp. nanotechnol., 2024, Volume 11:1, 193–213
|
R. Kh. Rakhimov, V. P. Yermakov
New approaches to the synthesis of functional materials with specified properties under the influence of concentrated radiation and pulse tunnel effect
Comp. nanotechnol., 2024, Volume 11:1, 214–223
|
R. Kh. Rakhimov, V. V. Pan'kov, V. P. Yermakov, L. V. Makhnach
Productive methods for increasing the efficiency of intermediate reactions in the synthesis of functional ceramics
Comp. nanotechnol., 2024, Volume 11:1, 224–234
|
R. Kh. Rakhimov, V. P. Yermakov
Pulse tunneling effect. Features interaction with substance
Comp. nanotechnol., 2024, Volume 11:2, 115–144
|
R. Kh. Rakhimov, V. V. Pan'kov, T. S. Saidvaliev
Investigation of the influence of pulsed radiation generated by functional ceramics based on the principle of PTE on the characteristics of the Cr$_{2}$O$_{3}$-SiO$_{2}$-Fe$_{2}$O$_{3}$-CaO-Al$_{2}$O$_{3}$-MgO-CuO system
Comp. nanotechnol., 2024, Volume 11:2, 145–156
|
R. Kh. Rakhimov, V. P. Yermakov
Features of the ITE-based polymerization process
Comp. nanotechnol., 2024, Volume 11:2, 157–173
|
R. Kh. Rakhimov, V. V. Pan'kov, V. P. Yermakov, T. S. Saidvaliev, J. Kh. Rashidov, M. R. Rakhimov, Kh. K. Rashidov
Pulse tunnel effect: prospects for scaling photocatalysts
Comp. nanotechnol., 2024, Volume 11:2, 174–190
|
R. Kh. Rakhimov
Potential of pulsed tunnel effect (PTE) to overcome technical barriers of quantum computers
Comp. nanotechnol., 2024, Volume 11:3, 11–33
|
R. Kh. Rakhimov
Fractals in quantum mechanics: from theory to practical applications
Comp. nanotechnol., 2024, Volume 11:3, 125–160
|
R. Kh. Rakhimov
Pulsed tunnel effect: new perspectives for controlling superconducting devices
Comp. nanotechnol., 2024, Volume 11:3, 161–176
|
R. Kh. Rakhimov
Interrelation and interpretation of effects in quantum mechanics and classical physics
Comp. nanotechnol., 2024, Volume 11:3, 98–124
|
J. Kh. Rashidov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 174–190
|
Kh. K. Rashidov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 174–190
|
S. A. Sabirova, see S. S. Mikhaylova
Comp. nanotechnol., 2024, Volume 11:2, 11–21
|
T. S. Saidvaliev, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 145–156
|
T. S. Saidvaliev, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 174–190
|
I. Yu. Sakash, see V. A. Terskov
Comp. nanotechnol., 2024, Volume 11:2, 22–28
|
R. V. Shamin, P. Yu. Grosheva, S. O. Golovanov
Mathematical model of economic information
Comp. nanotechnol., 2024, Volume 11:1, 48–56
|
A. M. Shevchenko, A. A. Dyda
An overview of the simulation capabilities for optimizing the operation of the seaport in the AnyLogic environment
Comp. nanotechnol., 2024, Volume 11:1, 127–134
|
M. D. Shuchkov, see A. V. Medvedev
Comp. nanotechnol., 2024, Volume 11:1, 85–93
|
D. S. Dilla, E. V. Pustovalov, A. N. Fedorets
Advanced electron microscopy image processing for analyzing amorphous alloys: Electron Microscopy Image Cluster Analyzer (EMICA). Tool and results
Comp. nanotechnol., 2024, Volume 11:1, 104–111
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D. S. Dilla, E. V. Pustovalov, A. N. Fedorets, A. M. Frolov
Exploring amorphous alloys: advanced electron microscopy and cluster analysis
Comp. nanotechnol., 2024, Volume 11:1, 112–120
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V. A. Terskov, I. Yu. Sakash
The mathematical model for assessing the reliability of multiprocessor computing systems functioning
Comp. nanotechnol., 2024, Volume 11:2, 22–28
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O. Yu. Timoshevskaya, see V. A. Londikov
Comp. nanotechnol., 2024, Volume 11:2, 86–92
|
A. A. Volkov, see A. E. Volkov
Comp. nanotechnol., 2024, Volume 11:2, 102–114
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A. E. Volkov, A. A. Volkov
Waste processing by plasma arc electrolytic centrifugal conversion
Comp. nanotechnol., 2024, Volume 11:2, 102–114
|
V. P. Yermakov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:1, 214–223
|
V. P. Yermakov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:1, 224–234
|
V. P. Yermakov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 115–144
|
V. P. Yermakov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 157–173
|
V. P. Yermakov, see R. Kh. Rakhimov
Comp. nanotechnol., 2024, Volume 11:2, 174–190
|
A. V. Yudin, S. E. Makievskiy, S. S. Adyshkin, P. Yu. Grosheva
Analysis of performance and features of the functioning of microfrontends
Comp. nanotechnol., 2024, Volume 11:1, 25–35
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V. G. Zavodinskó, O. A. Gorkusha, N. I. Plusnin
Computer simulation of li and be wetting layers on the Si (100) surface
Comp. nanotechnol., 2024, Volume 11:1, 121–126
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A. V. Zhivetyev, M. A. Belov
Adaptive delivery of educational and methodological materials based on neurolinguistic programming models based on the results of assessing the student's posture at the computer or in the classroom using machine learning
Comp. nanotechnol., 2024, Volume 11:3, 81–88
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