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Approximating and Predicting Energy Consumption of Portable Devices
P. 1–7.
Алкзир Н., Yarykina n., Nikolaev D. et al., Neuroscience and Behavioral Physiology 2024
Added: April 28, 2025
Hlib Nekrasov, Aleksandr Belov, , in: International IoT, Electronics and Mechatronics Conference, Volume 2. Proceedings of IEMTRONICS 2024. LNEE, volume 1228Vol. 1228.: Springer Publishing Company, 2025. P. 379–395.
Added: January 26, 2025
Yasnitsky L., Plotnikova E. G., Прикладная информатика 2024 Т. 19 № 5 С. 88–100
Outliers in statistical data, which are the result of erroneously collected information, are often an obstacle to the successful application of machine learning methods in many subject areas. The presence of outliers in training data sets reduces the accuracy of machine learning models, and in some cases, makes the application of these methods impossible. Currently ...
Added: November 29, 2024
Vurganov M., Псковский регионологический журнал 2023 Т. 19 № 4 С. 32–48
Diversification of energy exports in favor of the countries of the Asia-Pacific region in a tense geopolitical situation is one of the most important tasks for Russia. The characteristics of the current state of the oil and gas markets in the Asia-Pacific region are presented. The analysis made it possible to estimate the shares of ...
Added: May 13, 2024
Milovidov S., Artnodes 2024 No. 33 P. 1–9
This article employs a case‐study method to investigate the artivism neural network community concentrated on Twitter (since renamed X), which has been ideologically influenced by the content policy and limitations of OpenAI. Today, many young artists using machine learning technologies in their artworks (Midjourney, Stable Diffusion, Kandinsky) note that despite significant progress in the field ...
Added: February 1, 2024
Kosmachev A., Задорожникова А. А., Perov A., В кн.: БОЛЬШИЕ ДАННЫЕ Материалы I Международного форума (Новосибирск, 16–18 ноября 2022 года).: Новосибирск: Новосибирский государственный университет экономики и управления «НИНХ», 2023.
The article discusses the basic concepts and terms used in steganography, substantiates the relevance of the problem of steganalysis, discusses the use of deep neural networks in the tasks of steganalysis on digital images. A comparative analysis and description of the most effective convolutional network architectures for solving the task is performed. ...
Added: January 26, 2024
I. K. Kusakin, Fedorets O. V., A. Y. Romanov, Scientific and Technical Information Processing 2023 Vol. 50 No. 3 P. 176–183
This paper discusses modern approaches to natural language processing and the application of machine learning models to the task of classifying short scientific texts in Russian. This study is devoted to the analysis of methods for vectorization of textual information, selection of a model for scientific paper clas- sification, and training of linguistic model BERT ...
Added: November 4, 2023
Искандеров Ю. М., Катарушкин Б. Е., Ершов А. А., Информатизация и связь 2020 № 2 С. 46–51
Aim. Currently, when creating intelligent information systems in various fields of practical activity, machine learning methods are used. The article shows the possibilities of using these methods in automating the detection of obstacles in the interest of improving safety and reducing the number of emergencies at level crossings. Materials and methods. The article discusses advanced ...
Added: September 15, 2023
Fabrykant M., Социодиггер 2023 Т. 4 № 5-6
Обсуждаются возможные причины доверия к ChatGPT. Делается вывод, что основная приична в том, что ChatGPT представляют собой наиболее точный из доступных эквивалентов коммуникации с обществом в целом. ...
Added: August 23, 2023
[б.и.], 2023.
Addressing problems in different science and engineering disciplines often requires solving optimization problems, including via machine learning from large training data. One class of methods has recently gained significant attention for problems in computer vision and visual computing: coordinate-based neural networks parameterizing a field, such as a neural network that maps a 3D spatial coordinate ...
Added: July 18, 2023
Pantiukhin D., Информатика и образование 2023 Т. 38 № 1 С. 55–63
The problem of neural network vulnerability has been the subject of scientific research and experiments for several years. Adversarial attacks are one of the ways to “trick” a neural network, to force it to make incorrect classification decisions. The very possibility of adversarial attack lies in the peculiarities of machine learning of neural networks. The ...
Added: April 14, 2023
Vladimir V. Klinshov, Kirillov S., Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2022 Vol. 106 No. 6 Article L062302
Neural mass models is a general name for various models describing the collective dynamics of large neural
populations in terms of averaged macroscopic variables. Recently, the so-called next-generation neural mass
models have attracted a lot of attention due to their ability to account for the degree of synchrony. Being exact
in the limit of infinitely large number of ...
Added: January 24, 2023
Vladimir V. Klinshov, Kovalchuk A., Franović I. et al., Chaos, Solitons and Fractals 2022 Vol. 158 Article 112011
Rate chaos is a collective state of a neural network characterized by slow irregular fluctuations of firing rates of
individual neurons.We study a sparsely connected network of spiking neuronswhich demonstrates three different
scenarios for the emergence of rate chaos, based either on increasing the synaptic strength, increasing the
synaptic integration time, or clustering of the excitatory synaptic connections. ...
Added: January 24, 2023
Muratova A., Ignatov D. I., Mitrofanova E., , in: Recent Trends in Analysis of Images, Social Networks and Texts. 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020 Revised Supplementary ProceedingsVol. 12602.: Springer, 2021. P. 297–299.
This is the extended abstract of a case study on demographic sequences analysis by machine learning and data mining methods. ...
Added: November 1, 2022
Karakaya E., Sedat Alataş, Yılmaz B., Energy Efficiency 2020 Vol. 13 No. 7 P. 1457–1472
Recent studies investigating convergence in energy consumption at the sectoral level within a country suggest that aggregate energy consumption could mask considerable differential impacts that might be observed at the sectoral level. This study aims to contribute and complement the existing convergence literature with an attempt to analyze sectoral convergence in energy consumption from the ...
Added: September 23, 2022
Pantiukhin D., Речевые технологии 2021 № 3-4 С. 3–16
Added: June 17, 2022
Belov A. V., Sapozhnikov A., Semichasnov I., , in: Proceedings of the 2021 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies" (IT&QM&IS).: IEEE, 2021. P. 485–490.
The purpose of this work is to develop algorithms and game mechanics for controlling the car driving along a track using a genetic algorithm for training a neural network with the ability to save and load the obtained weights during training. A genetic algorithm and a neural network were developed using the C ++ programming ...
Added: January 14, 2022
Markvirer V., Sakhipova M., В кн.: Математика и междисциплинарные исследования – 2021.: Пермь: Пермский государственный национальный исследовательский университет, 2021. С. 152–157.
Added: December 19, 2021
Kuskova V., Zaytsev D., Sokol A. et al., , in: Proceedings of the 26th ISSAT Conference on Reliability and Quality in Design.: International Society of Science and Applied Technologies, 2021. P. 122–126.
Added: October 29, 2021
Berezutskii A., Beketov M., Yudin D. et al., Journal of Physics: Complexity 2020 Vol. 1 No. 3 Article 03LT01
The numerical emulation of quantum systems often requires an exponential number of degrees of freedom which translates to a computational bottleneck. Methods of machine learning have been used in adjacent fields for effective feature extraction and dimensionality reduction of high-dimensional datasets. Recent studies have revealed that neural networks are further suitable for the determination of ...
Added: October 5, 2021
Rohrmanstorfer S., Komarov M. M., Mödritscher F., Mathematics 2021 No. 9 Article 624
With the always increasing amount of image data, it has become a necessity to automatically look for and process information in these images. As fashion is captured in images, the fashion sector provides the perfect foundation to be supported by the integration of a service or application that is built on an image classification model. ...
Added: September 14, 2021