Pavel Kharyuk, Dmitry Nazarenko, Ivan Oseledets, И. А. Родин, О. А. Шпигун, Andrey Tsitsilin, Mikhail Lavrentyev,
Abstract A dataset of liquid chromatography-mass spectrometry measurements of medicinal plant extracts from 74 species was generated and used for training and validating plant species identification algorithms. Various strategies for data handling and feature space extraction were tested. Constrained Tucker decomposition, large-scale (more than 1500 variables) discrete Bayesian Networks and autoencoder based dimensionality reduction coupled with continuous Bayes classifier and logistic regression ...
Tópico(s): Traditional Chinese Medicine Studies
2018 - Nature Portfolio | Scientific Reports
Roman S. Bugaev, Mikhail O. Piskunov, Timofey Rakov,
... level. Second, the evolution of the ideas of Mikhail Lavrentyev, the founder of Akademgorodok, who upon arrival in ...
Tópico(s): Landscape and Cultural Studies
2021 - Brill | The Soviet and Post-Soviet Review
Andrey V. Basko, Т. Н. Лебедева, Mikhail Yurov, Anna N. Ilyasova, G. K. Elyashevich, V. K. Lavrentyev, Denis Kalmykov, А. В. Волков, K. V. Pochivalov,
A new interpretation of the mechanism of the polyvinylidene fluoride (PVDF) membrane formation using the nonsolvent-induced phase separation (NIPS) method based on an analysis of the complete experimental phase diagram for the three-component mixture PVDF–dimethyl acetamide (DMAc)–water is proposed. The effects of the precipitation bath’s harshness and thermodynamic affinity of the polymer’s solvent on the morphology, crystalline structure, transport and physical–mechanical properties of the membranes ...
Tópico(s): Surface Modification and Superhydrophobicity
2023 - Multidisciplinary Digital Publishing Institute | Polymers
K. V. Pochivalov, Andrey V. Basko, Mikhail Yurov, T. N. Lebedeva, M. G. Shalygin, V. K. Lavrentyev, A. A. Yushkin, Tatyana Anokhina, А. В. Волков,
The goal of this work was to investigate the effect of non-solvent nature on the formation of porous membranes via non-solvent/thermally induced phase separation (N-TIPS). The hot solution of polypropylene (PP) in a mixture of dioctyl phthalate (DOP) and dibutyl phthalate (DBP) at 210°C was placed as a thin film on a polyethylene terephthalate (PET) substrate, and then precipitated by immersion in the non-solvent (water, iso-propanol, 1-hexanol, or 1-decanol) at room temperature. It was found that the ...
Tópico(s): Membrane-based Ion Separation Techniques
2024 - Elsevier BV | Journal of Membrane Science
Denis Baramiya, M. S. D’yakov, S. A. Kuzikovskii, Mikhail Lavrentyev,
Tópico(s): Advanced Research in Systems and Signal Processing
2017 - Pleiades Publishing | Optoelectronics Instrumentation and Data Processing
Natalia A. Kupershtokh, Alexander Apolonskiy,
... be located in Siberia was proposed by academicians Mikhail Lavrentyev, Sergei Sobolev, and Sergei Khristianovich (figure 6). The ...
Tópico(s): Computational Physics and Python Applications
2014 - Birkhäuser | Physics in Perspective
... the 120 th anniversary of birth of Academician Mikhail Alekseevich Lavrentyev. The Conference was held at Novosibirsk Akademgorodok, Russia, ...
Tópico(s): Geological Studies and Exploration
2020 - IOP Publishing | Journal of Physics Conference Series
Pavel Kharyuk, Dmitry Nazarenko, Ivan Oseledets, И. А. Родин, О. А. Шпигун, Andrey Tsitsilin, Mikhail Lavrentyev,
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Tópico(s): Traditional Chinese Medicine Studies
2020 - Nature Portfolio | Scientific Reports
Mikhail Kiselev, Alexander Ivanitsky, Andrey Lavrentyev,
Working memory is a crucial property of spiking neural networks (SNN) recognizing long complex spatio-temporal patterns since the features characterizing onset of the pattern should be stored until its end. Many different ways to implement memory mechanism in SNN have been proposed. Here, we compare two of them – one is based on the variable threshold potential while the other – on the short-term synaptic plasticity (STP). The methodology for objective quantitative memory quality measurement using a special ...
Tópico(s): Neural Networks and Reservoir Computing
2021 - Springer Nature | Studies in computational intelligence
Mikhail Kiselev, Andrey Lavrentyev,
The crucial feature of liquid state machines (LSM) is memory which is necessary to the convert spatio-temporal input patterns and their sequences scattered in time into multidimensional representation in the form of instant neuronal activity. In this work, we utilize a methodology for exact estimation of LSM memory ability and to find parameters of the LSM “liquid” (the chaotic spiking neural network) optimal from viewpoint of memory depth using genetic algorithm. We applied this technique to chaotic ...
Tópico(s): Neural dynamics and brain function
2022 - Springer Nature | Studies in computational intelligence
Mikhail Stolbov, Alexander Lavrentyev,
This paper presents a new speech enhancement method with microphone array for the joint suppression of coherent and diffuse noise. The proposed method is based on combined technique: target and noise steering beamforming and adaptive noise suppression. The microphone array forms two beams steered in the directions of target speaker and of noise source. The signal of reference beam is used to suppress the noise in primary channel. The proposed algorithm of Adaptive Noise Suppressor (ANS) is based ...
Tópico(s): Acoustic Wave Phenomena Research
2016 - Springer Science+Business Media | Lecture notes in computer science
Rizal Mohd Nor, Mikhail Nesterenko, Peter J. Lavrentyev,
Tópico(s): Water Quality Monitoring Technologies
2010 - Elsevier BV | Ad Hoc Networks
V. M. Kopeikin, В. П. Шевченко, G. V. Malafeev, А. N. Novigatsky, Natalia Pankratova, T. Ya. Ponomareva, А. И. Скороход, Yu. A. Shtabkin, Irina Makhotina, Mikhail Makhotin, E. Yu. Churakova,
... R/V), “Acad. Mstislav Keldysh”, “Acad. M. A. Lavrentyev” and “Prof. Molchanov” in 2011–2018. They were ...
Tópico(s): Atmospheric and Environmental Gas Dynamics
2020 - IOP Publishing | IOP Conference Series Earth and Environmental Science