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6th International Conference on Communication, Image and Signal Processings, CCISP 2021

作者： Okunev, Alexey Burnaev, Evgeny Wang, Jun Center for Computational and Data-Intensive Science and Engineering Skoltech Moscow Russia

ISBN: (纸本)9781665432795

Sparse Bayesian learning based on collaborative neurodynamic optimization (CNO-SBL) is a novel neural network approach proposed recently for sparse regression. In this paper, we demonstrate how well CNO-SBL performs for ordinary differential equation identification. It is shown that the approach is capable of recovering ordinary differential equations and outperforms the sequentially thresholded least square (STLS) algorithm in terms of accuracy for small size of dictionaries. © 2021 IEEE.

关键词： Ordinary differential equations

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CONDUCTIVITY AND ELECTRODE PLACEMENT VARIABILITY: EVALUATING THE CRAMER-RAO LOWER BOUND IN 2D ELECTRICAL IMPEDANCE TOMOGRAPHY

arXiv

引用

arXiv 2024年

作者： Kormakov, Georgii Koshev, Nikolay Department of Computational Data Science and Engineering Skoltech Moscow Russia Vladimir Zelman Center for Neurobiology and Brain Rehabilitation Skoltech Moscow Russia

Electrical Impedance Tomography (EIT) is a non-invasive imaging modality that has earned significant attention for its potential in real-time monitoring of various physiological parameters. Despite its promise, the sensitivity and resolution of EIT remain areas of active research. This article presents a new way to analyse the sensitivity of EIT systems using the Cramer-Rao Lower Bound (CRLB). This statistical tool provides a theoretical lower bound on the variance of unbiased estimators. To simulate the EIT full cycle, we compared two forward models: standard Dirichlet-to-Neumann (DtN) and restricted DtN. By taking the CRLB over modelled with Finite Elements Method (FEM) 2D circular area with various conductivity patterns, we showed the influence of electrode configuration on each basic FEM element sensitivity. Also, the sensitivity on small perturbations for different conductivity patterns was offered. This article aims to bridge the gap between the research of widely used hardware implementations standard forward DtN model and theoretically approved restricted DtN. We conclude with a discussion on the motivation behind this research and the objectives our work introduces for the inverse restricted DtN model in practice. © 2024, CC BY-NC-ND.

关键词： Physiological models

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Logging Multi-Component Supply Chain Production in Blockchain 2021

Logging Multi-Component Supply Chain Production in Blockchai...

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4th International Conference on Computers in Management and Business, ICCMB 2021

作者： Madhwal, Yash Chistiakov, Ivan Yanovich, Yury Faculty of Computer Science National Research University Higher School of Economics Russia Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Russia Center for Computational and Data-Intensive Science and Engineering Skolkovo Inst. of Sci. and Technol. and Lab. of Data Mining and Predictive Modelling Inst. for Info. Transmiss. Prob. Russia

ISBN: (纸本)9781450388610

The supply chain is a thriving industry where numerous parties have different interests. Subsequently, the immense volume of data produced is difficult to audit. Some information can be lost or intentionally distorted in the process. Blockchain as an open, public, borderless, neutral, and censorship-resistant architecture can significantly complement supply chains. A new supply chain architecture is proposed in this work, where the tokenized directed acyclic hypergraph (DAG) represents real-world production processes. An anti-aerosol respirator manufacturing is used as an illustration example. By tokenizing all parts of multi-component products, supply chain data is automatically timestamped and secured. Moreover, the DAG design allows one to trace-back all the elements of the final product to their origin. Blockchain can formally audit the entire supply chain without the need to go from place to place. A single incorruptible operations log creates an enabling environment for an unbiased reputation system to emerge. © 2021 ACM.

关键词： Smart contract

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Conceptual Method of Temperature Sensation in Bionic Hand by Extraordinary Perceptual Phenomenon

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Journal of Bionic engineering 2021年第6期18卷 1344-1357页

作者： Saeed Bahrami Moqadam Ahamd Saleh Asheghabadi Farzaneh Norouzi Hamed Jafarzadeh Ali Khosroabadi AfshinAlagheband Ghazal Bangash Negar Morovatdar Jing Xu State Key Laboratory of Tribology Department of Mechanical EngineeringTsinghua UniversityBeijing100084China Medical University of Mashhad 13131–99137MashhadIran Center for Computational and Data Intensive Science and Engineering(CDISE) Skolkovo Institute of Science and Technology(Skoltech)Moscow121205Russia Department of Mechanical Engineering Ferdowsi UniversityMashhad***Iran Department of Electrical Engineering Ferdowsi UniversityMashhad***Iran Department of Computer Engineering Ferdowsi UniversityMashhad***Iran Clinical Research Unit Imam Reza HospitalMashhad University of Medical Sciences13131–99137MashhadIran

Lack of temperature sensation of myoelectric prosthetic hand limits the daily activities of *** this end,a noninvasive temperature sensation method is proposed to train amputees to sense temperature with psychophysical sensory *** this study,22 healthy participants took part besides 5 amputee *** duration time of the study was 31 days with five test steps according to the Leitner *** adjustable temperature mug and a Peltier were used to change the temperature of the water/phantom digits to induce temperature to ***,to isolate the surroundings and show colors,a Virtual Reality(VR)glass was *** statistical results conducted are based on the response of participants with questionnaire *** Chi-square tests,it is concluded that participants answer the experiment significantly correctly using the Leitner technique(P value<0.05).Also,by applying the“Repeated Measures ANOVA”,it is noticed that the time of numbness felt by participants had significant(P value<0.001)*** could remember lowest and highest temperatures significantly better than other temperatures(P value<0.001);furthermore,the well-trained amputee participant practically using the prosthesis with 72.58%could identify object’s temperature with only once time experimenting the color temperature.

关键词： Temperature perceptions Leitner learning technique Classical conditioning Psychophysical sensory substitution Extraordinary perceptual phenomenon Bionic hand prosthesis

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High-Performance computational Approach for Inverse Design of Passive Photonic Components

High-Performance Computational Approach for Inverse Design o...

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2022 Laser Applications Conference, LAC 2022

作者： Minin, Iurii Matveev, Sergey Skoltech Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 bld.1 Moscow121205 Russia Fryazino Branch of Kotel’nikov Institute of Radio-Engineering and Electronics of RAS Vvedenskiy sq. 1 Moscow Region Fryazino141190 Russia Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Leninskie Gory 1-52 2nd educational building 6th floor room 663 Moscow119991 Russia Marchuk Institute of Numerical Mathematics RAS Moscow Russia

We propose novel approach for high-performance computations of electric field distributions which uses Green’s Function Integral Equation Method, memcopy-free GMRES, fast (FFT-based) matvecs and can work 10 times fas... 详细信息

ISBN: (纸本)9781957171203

关键词： Integral equations

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Topology Optimizer for Inverse Design and Fabrication of Passive Photonic Integrated Components UsingWeighted Target

Topology Optimizer for Inverse Design and Fabrication of Pas...

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Advanced Solid State Lasers, ASSL 2021 - Part of Laser Congress, LAC 2021

作者： Minin, Iurii Kazakov, Ivan Kontorov, Sergey Shipulin, Arkady Matveev, Sergey Fedorov, Maxim Skoltech Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 bld.1 Moscow Russia Skoltech Center for Photonics and Quantum Materials Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 building 1 Moscow Russia Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Leninskie Gory 1-52 2nd educational building 6th floor room 663 Moscow Russia

We propose a novel approach optimizing passive photonic integrated component topology computations. It is based on Green's Function Integral Equation method, utilizes weighted optimization methods and fast Toeplit... 详细信息

ISBN: (纸本)9781557528209

关键词： Integral equations

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Benchmarks of Cuda-Based GMRES Solver for Toeplitz and Hankel Matrices and Applications to Topology Optimization of Photonic Components

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computational Mathematics and Modeling 2021年第4期32卷 438-452页

作者： Minin, Iu. B. Matveev, S.A. Fedorov, M.V. Zacharov, I.E. Rykovanov, S.G. Skoltech Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow Russian Federation Fryazino Branch of Kotel’nikov Institute of Radio-Engineering and Electronics of Russian Academy of Sciences Moscow Fryazino Russian Federation Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russian Federation Marchuk Institute of Numerical Mathematics Russian Academy of Sciences Moscow Russian Federation Sirius University of Science and Technology Krasnodar Krai Sochi Russian Federation

Generalized Minimal Residual Method (GMRES) was benchmarked on many types of GPUs for solving linear systems based on dense and sparse matrices. However, there are still no GMRES implementation benchmarks on Tesla V100 compared to GTX 1080 Ti ones or even for Toeplitz-like matrices. The introduced software consists of a Python module and a C++ library which enable to manage streams for concurrent computations of separated linear systems on a GPU (and GPUs). The GMRES solver is parallelized for running on a NVIDIA GPGPU accelerator. The parallelization efficiency is explored when GMRES is applied to solve (Helmholtz equation) linear systems based on the use of Green’s Function Integral Equation Method (GFIEM) for computing electric field distribution in the design domain. The proposed implementation shew the maximal speedup of 55 (t¯=0.017s) and of 125 (t¯=0.77s) for 1024 × 1024 (on GTX 1080 Ti) and 8192 × 8192 (on Tesla V100) dense Toeplitz matrices generated from GFIEM. 1024 × 1024 resolution provides accuracy 6.1% that can be acceptable according to testing and demonstrating on gradient computations and topology optimization. We open up possibilities for robust topology optimization of passive photonic integrated components. That has the advantage, e. g., of faster and more accurate designing photonic components on a PC without a supercomputer. © 2022, Springer science+Business Media, LLC, part of Springer Nature.

关键词： CUDA C++ GMRES GPU Helmholtz equation parallelization performance Python module Toeplitz-like matrix topology optimization

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Topology Optimizer for Inverse Design and Fabrication of Passive Photonic Integrated Components Using Weighted Target

Topology Optimizer for Inverse Design and Fabrication of Pas...

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Laser Applications Conference, LAC 2021 - Part of Laser Congress 2021

作者： Minin, Iurii Kazakov, Ivan Kontorov, Sergey Shipulin, Arkady Matveev, Sergey Fedorov, Maxim Skoltech Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 bld.1 Moscow121205 Russia Skoltech Center for Photonics and Quantum Materials Skolkovo Institute of Science and Technology Bolshoy Boulevard 30 building 1 Moscow121205 Russia Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Leninskie Gory 1-52 2nd educational building 6th floor room 663 Moscow119991 Russia

We propose a novel approach optimizing passive photonic integrated component topology computations. It is based on Green’s Function Integral Equation method, utilizes weighted optimization methods and fast Toeplitz-l... 详细信息

ISBN: (纸本)9781557528209

关键词： Integral equations

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A study of first-passage time minimization via Q-learning in heated gridworlds

arXiv

引用

arXiv 2021年

作者： Larchenko, Maria A. Osinenko, P. Yaremenko, G. Palyulin, V.V. Center for Computational and Data-intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

Optimization of first-passage times is required in applications ranging from nanobots navigation to market trading. In such settings, one often encounters unevenly distributed noise levels across the environment. We extensively study how a learning agent fares in 1- and 2- dimensional heated gridworlds with an uneven temperature distribution. The results show certain bias effects in agents trained via simple tabular Q-learning, SARSA, Expected SARSA and Double Q-learning. While high learning rate prevents exploration of regions with higher temperature, low enough rate increases the presence of agents in such regions. The discovered peculiarities and biases of temporal-difference-based reinforcement learning methods should be taken into account in real-world physical applications and agent design. Copyright © 2021, The Authors. All rights reserved.

关键词： Reinforcement learning

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Kalman Filtering for Accurate and Fast Plant Growth Dynamics Assessment

Kalman Filtering for Accurate and Fast Plant Growth Dynamics...

引用

IEEE Instrumentation and Measurement Technology Conference

作者： Dmitrii Shadrin Tatiana Podladchikova George Ovchinnikov Artem Pavlov Mariia Pukalchik Andrey Somov Center for Computational and Data-Intensive Science and Engineering (CDISE) Space Center Skolkovo Institute of Science and Technology (SkolTech) Moscow Russia

ISBN: (数字)9781728144603

ISBN: (纸本)9781728144610

Artificial growth systems are the essential part of the precision agriculture. It allows solving many problems associated with the growing demand in the environmental friendly food production in the context of increasing world population. Accurate and reliable assessment of plant growth dynamics parameters is crucial for the future success of the whole growing system parameters optimization. In this research, we report on the implementation of the extended Kalman filtering method for insitu evaluation of plant growth dynamics parameters. We show the reliability and benefits of the proposed approach on the simulated and experimental data obtained from the IoT-based testbed. We demonstrate that our method serves as a robust and computationally cost-effective tool for the accurate assessment of the growing dynamics that, in turn, could be used for the further optimization of the whole plant cultivation process in artificial conditions.

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