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Musical Synthesis for Certain Music Styles based on Machine Learning Algorithms
P. 543–562.
Dmitry V. Alexandrov, Evgeney V. Mistyukov
The machine learning sphere is one of the most important and growing science spheres nowadays. Many algorithms dealing with images exist, but attention to music is growing as well. Some algorithms classify music by genre while others developed recently deal with music synthesis. The goal of this paper is to present an algorithm, which syntheses a music audio file on the basis of two certain fragments of different music compositions. This paper provides a theoretical basis of neural networks and convolutional neural networks in particular, describing how to construct a working model to create an audio output from two inputs, and shows how the network parameters can be evaluated and changed to fit the model better and generate better results.
Krasnov L., Malikov D., Kiseleva M. et al., Journal of Medicinal Chemistry 2026 Vol. 69 No. 8 P. 8838–8851
In this work, we developed a straightforward data-driven approach to predict the cytotoxicity of metal complexes based entirely on their (metal + ligands) composition. To this end, we have manually curated MetalCytoToxDB─a comprehensive experimental database comprising 26,500 IC50 values for 7050 metal complexes against 754 cell lines from 1921 articles. Based on these, machine learning ...
Added: April 23, 2026
Plesovskikh A. E., Journal of Applied Economic Research 2023 Т. 22 № 2 С. 323–354
Modern studies widely discuss the role of special economic zones in stimulating the economic growth and development of Russia, generating the necessary investment flows and increasing the country's innovative potential by expanding production in high-tech sectors of the economy with high added value. The purpose of the study is to model the process of generating ...
Added: April 13, 2026
Pakshin P., Legal Issues in the Digital Age 2026 Vol. 7 No. 1 P. 32–48
Artificial intelligence plays a significant role in automation, minimizing human intervention in fields such as medicine, art, and law. Despite the historically close relationship between art and technology, generative AI has expanded the potential for creative activity. A significant catalyst for this process has been the proliferation of pre-trained AI systems, which have accelerated the ...
Added: March 31, 2026
Gabdrahmanov R., Tsoy T., Martinez-Garcia E. et al., , in: Proceedings of the 21st International Conference on Informatics in Control, Automation and Robotics - (Volume 1) ICINCO 2024.: SciTePress, 2024. P. 511–518.
Computer simulations are growing in popularity in robotics research due to their near-zero cost of error and lower labor intensity. One of necessary components of a simulation, in addition to a robot model, is a model of a world in which the robot operates. While it is always possible to construct a world model manually, ...
Added: March 17, 2026
Semenikhin T., Kornilov M., Pruzhinskaya M. et al., , in: 26th International Conference, DAMDID/RCDL 2024, Nizhny Novgorod, Russia, October 23–25, 2024, Revised Selected Papers. Data Analytics and Management in Data Intensive Domains. (CCIS, volume 2641).: Springer, 2026. P. 211–219.
We considered two fundamentally different approaches to real-bogus classification within the Zwicky Transient Facility survey data. The first approach is based on neural networks that take sequences of object images as input. The second approach uses features extracted from light curves and classical machine learning methods. Several models for both approaches were tested. Quality metrics ...
Added: March 11, 2026
Maltseva S. V., Бериков В. Б., Кладов Д. Е. et al., В кн.: Информатика и прикладная математика: Материалы X Международной научно-практической конференции (08.10 - 11.10.2025 г.)Т. 1: Сборник материалов часть 1.: Алматы: Институт информационных и вычислительных технологий КН МНВО РК, 2025. С. 227–232.
This paper examines the problem of clustering consumption patterns for a private household. An ensemble algorithm based on the Wasserstein metric was developed and applied to cluster daily load profiles. The proposed approach allows for identifying typical energy consumption scenarios and interpreting consumer behavior. Results from computational experiments using real data are presented. ...
Added: March 3, 2026
Arinin O. V., Bakhmach D. M., Katsnelson A. et al., , in: 2025 Systems of Signals Generating and Processing in the Field of on Board Communications.: IEEE, 2025. P. 1–5.
This research discusses the method of dataset collection automatization for microwave filter synthesis by integrating machine learning techniques, thus reducing development time. Utilizing the 3D electromagnetic analysis software package, the study involves simulation and collecting geometric parameters and amplitude-frequency characteristics from three variants of passband highly selective microstrip tworesonator combined filters with stepped impedance resonators. ...
Added: December 6, 2025
Индаков Г. С., Казначеев П. А., Майбук З. Я. et al., Геофизические исследования 2025 Т. 26 № 2 С. 99–124
The paper studies the clusterability of acoustic emission pulses during high-temperature heating of sandstone sample preliminarily subjected to mechanical loading. Mechanical loading was applied in uniaxial mode up to load close to destructive with appearance of signs of large cracks on the surface. After that, samples were subjected to thermal treatment up to 650 °C ...
Added: September 19, 2025
Chepikov I., Karpov I., , in: 26th International Conference, AIED 2025, Palermo, Italy, July 22–26, 2025, Proceedings, Part I. Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED.: Springer, 2025. P. 352 – 358.
Modern LLM models such as BERT, ChatGPT, DeepSeek have shown great potential in solving various tasks, including text classification, text generation, analysis and summary of documents. In this paper, we show that these models close to classical ML approaches based on decision trees not only in text processing, but also in processing classical tabular data ...
Added: September 4, 2025
Wien: Association for Computational Linguistics, 2025.
Added: August 26, 2025
Delev A., Semakov S., , in: 2025 8th International Conference on Artificial Intelligence and Big Data (ICAIBD).: IEEE, 2025. P. 318–322.
Profit is one of the most important economic indicators of a company’s performance, and for every company it is necessary to allocate resources in such a way as to obtain the maximum possible profit. The profit maximization problem is usually a dynamic optimization problem. This article discusses an approach to solving the production expansion problem ...
Added: August 25, 2025
Podchufarov A., Galkina A. N., Ванина С. С. et al., Экономика и управление: проблемы, решения 2025 Т. 5 № 4 С. 61–74
Under modern conditions, the introduction of artificial intelligence technologies is becoming a significant factor in the development of high-tech industries. The article presents the results of a study of the prospects for the use of intelligent analytical systems in nuclear energy. The experience of foreign countries is analyzed and the features of successful projects using ...
Added: June 5, 2025
Vakulenko E., Gorskiy D., Kondrateva V. et al., Demographic Research 2025 Vol. 52 P. 939–970
BACKGROUND
We study fertility intentions change in Russia, during the period of socio-economic shocks in 2022-2023, in response to the Russia-Ukraine armed conflict.
OBJECTIVE
Our objective is to identify factors that influence decision-making in a low fertility context during the crisis, including both objective characteristics and subjective assessment of the current situation.
METHODS
This paper is based on unique survey ...
Added: May 6, 2025
Loginova I., Grozovskiy F., Aksenova A., Automatic Documentation and Mathematical Linguistics 2025 Vol. 59 No. 3 P. 145–153
The paper analyzes the limitations of conventional methods for assessing the maturity of technology, such as the S-curve, technology readiness level (TRL), Gartner’s hype cycle and their dependence on experts’ opinions. Current approaches to this task based on big text data analysis and machine learning algorithms are reviewed, and their advantages are demonstrated. As a ...
Added: April 28, 2025
Derkach D., Efremenko D., Чупров И. А. et al., / Series Computer Science "arxiv.org". 2025. No. 2503.18849.
Added: March 25, 2025
Derkach D., Anderlini L., Capelli S. et al., Proceedings of Science 2025 Vol. 476 P. 1032
Simulating detector and reconstruction effects on physics quantities is crucial for data analysis, but it is coming unsustainably costly for the upcoming HEP experiments. The most radical approach to speed-up detector simulation is Flash Simulation, as proposed by the LHCb collaboration in Lamarr, a software package implementing a novel simulation paradigm relying on Deep Generative ...
Added: March 13, 2025
Semenikhin T. A., Kornilov M., Pruzhinskaya M. et al., Astronomy and Computing 2025 Vol. 51 Article 100919
In the task of anomaly detection in modern time-domain photometric surveys, the primary goal is to identify astrophysically interesting, rare, and unusual objects among a large volume of data. Unfortunately, artifacts — such as plane or satellite tracks, bad columns on CCDs, and ghosts — often constitute significant contaminants in results from anomaly detection analysis. ...
Added: March 3, 2025
Volnova A., Aleo P., Lavrukhina A. et al., Communications in Computer and Information Science 2024 Vol. 2086 P. 195–208
SNAD is an international project with a primary focus on detecting astronomical anomalies within large-scale surveys, using active learning and other machine learning algorithms. The work carried out by SNAD not only contributes to the discovery and classification of various astronomical phenomena but also enhances our understanding and implementation of machine learning techniques within the ...
Added: March 3, 2025
Voloshina A., Lavrukhina A., Pruzhinskaya M. et al., Monthly Notices of the Royal Astronomical Society 2024 Vol. 533 No. 4 P. 4309–4323
Most of the stars in the Universe are M spectral class dwarfs, which are known to be the source of bright and frequent stellar flares. In this paper, we propose new approaches to discover M-dwarf flares in ground-based photometric surveys. We employ two approaches: a modification of a traditional method of parametric fit search and ...
Added: March 3, 2025
Габов М. А., Bukina T. V., Kashin D., Журнал Новой экономической ассоциации 2025 № 4(69) С. 87–117
The study aims to compare approaches to forecasting the monthly level of consumer price index (CPI y/y) in the regions of the Volga Federal District using time series models and machine learning methods. This study attempts to select the most appropriate and efficient models for predicting the regional general price level index. The paper also ...
Added: February 22, 2025
Al-Maeeni A. R., Temirkhanov A., Ryzhikov A. et al., IEEE Access 2025 Vol. 13 P. 49643–49658
High-precision systems modeling is one of the main areas of industrial data analysis. Models of systems, their digital twins, are used to predict their behavior under various conditions. In this study, we developed several models of a storage system using machine learning-based generative models to predict performance metrics such as IOPS and latency. The models ...
Added: February 20, 2025
Mozgunov G., Pozanenko A. S., Minaev P. Y. et al., , in: Data Analytics and Management in Data Intensive Domains: 25th International Conference, DAMDID/RCDL 2023, Moscow, Russia, October 24–27, 2023, Revised Selected PapersVol. 2086: Communications in Computer and Information Science.: Springer, 2024. P. 215–224.
Added: January 31, 2025