Journal Scientific and Technical 158 Научно-технический вестник информационных технологий, механики и оптикиScientific and Technical Journal of Information Technologies, Mechanics and Optics Journal Scientific and Technical Of Information Technologies, Mechanics and Optics

2024 , VOLUME 24, NUMBER 6 ( november-december )

ISSN 2226-1494 (print), ISSN 2500-0373 (online)

Publications

2025

Editor-in-Chief

Nikiforov
Vladimir O.
D.Sc., Prof.

Partners

Сontents

OPTICAL ENGINEERING

Zhidik Y. S., Sheinberger A. A., Stepanenko M. V., Troyan P. E.

Design and fabrication of collimating ball lensed fiber for the system of optical radiation output from radiophotonic components

871

Zyubin A. Y., Kundalevich A. A., Zozulya A. S., Bahdasarau M. A., Demishkevich E. A., Samusev I. G.

From Triassic to moderinity: Raman spectroscopy for differentiation of fossil resins age by age

880

Elanskaia K. G., Sidorov A. I.

Optimization of geometry of two-dimensional photonic crystal waveguide for telecommunications and sensorics

892

Volkov A. V., Malmakin A. P., Ushanov S. A.

Development and investigation of the suppressing additive noises methods in fiber-optic interferometric sensors

899

Sandrovskii A. A., Sharkov I. A., Plotnikov M. Y., Ushanov S. A., Goncharov D. B., Karpov E. E.

Method for compensating the constant component of noise in the reflectogram of a fiber-optic communication line under conditions of insufficient dynamic range of an optical backscatter reflectometer in the time domain

907

Moor I. D., Kozlova A. I., Korobkova U. R., Varzhel S. V., Kulikov A. V.

Investigation of the method of moving object weight measurement based onquasidistributed fiber Bragg gratings with temperature compensation

913

Chertov N. A., Khokhlov D. D.

Modern optical methods of non-contact geometric measurements and reconstruction of object 3D surface shape: a review

923

MATERIAL SCIENCE AND NANOTECHNOLOGIES

Pesnyakov V. V., Marasanov D. V., Evstropiev S. K., Nikonorov N. V.

Spectral-luminescent properties of silver clusters Ag_1–5 in the ion-exchange layer of silicate glass

936

Ivanov A. Y., Sharofidinov S. S., Panov D. I., Kremleva A. V., Bauman D. A., Romanov A. E.

Forming a thick layer of ε-Ga₂O₃ on the GaN sublayer with V-defects at the interface

943

COMPUTER SCIENCE

Le V.H. et al.
A model for ensuring the continuity of the safe functioning of the product quality traceability system in conditions of unstable communication

949

Usoltsev D.A. et al.
Application of Markov chain Monte Carlo and machine learning for identifying active modules in biological graphs

962

Novgorodcev N.P. et al.
Surface defect detection with limited data based on SSD detector and Siamese networks

972

Benabdallah A., Abderrahim M.A., Mokri M.
Sentiment analysis of Arabic tweets using supervised machine learning (in English)

982

Grashchenkov P.V., Pasko L.I., Studenikina K.A., Tikhomirov M.M.
Russian parametric corpus RuParam

991

Khokhlova M.V., Koryshev M.V.
Comparative analysis of AI-generated and original abstracts of academic articles on philology

999

Darwesh G. et al.
Enhancing Kubernetes security with machine learning: а proactive approach to anomaly detection

1007

Masliukhin S.M., Posokhov P.A., Skrylnikov S.S. et al.
Prompt-based multi-task learning for robust text retrieval

1016

Gorbatovski A.V.
Improving question answering in programming domain with pretrained language model finetuning using structured diverse online forum data

1024

Novikov F.A., Afanasieva I.V., Fedorchenko L.N., Kharisova T.A.
Specification language for automatа-based objects cooperation

1035

Isakov A.O. et al.
Aspects of organizing game interactions among asymmetric agents using graph neural networks

1044

MODELING AND SIMULATION

Rogalev N.D. et al.
Development and modeling of technological scheme of steam methane reforming with oxy-fuel combustion and carbon capture

1049

Bondarev A.V. et al.
Stability study of hybrid MOS memristor memory using modified particle swarm optimization method

1059

BRIEF PAPERS

Teterev N.V., Trifonov V.E., Levina A.B.
Analysis of the vulnerability of YOLO neural network models to the Fast Sign Gradient Method attack

1066