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Hyper-spectral NIR and MIR data and optimal wavebands for detection of apple tree diseases

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arXiv 2020年

作者： Shadrin, Dmitrii Pukalchik, Mariia Uryasheva, Anastasia Tsykunov, Evgeny Yashin, Grigoriy Rodichenko, Nikita Tsetserukou, Dzmitry Center for Computational and Data-Intensive Science and Engineering Moscow Russia Moscow Russia

Plant diseases can lead to dramatic losses in yield and quality of food, becoming a problem of high priority for farmers. Apple scab, moniliasis, and powdery mildew are the most significant apple tree diseases worldwide and may cause between 50% and 60% in yield losses annually;they are controlled by fungicide use with huge financial and time expenses. This research proposes a modern approach for analyzing the spectral data in Near-Infrared and Mid-Infrared ranges of the apple tree diseases at different stages. Using the obtained spectra, we found optimal spectral bands for detecting particular disease and discriminating it from other diseases and healthy trees. The proposed instrument will provide farmers with accurate, real-time information on different stages of apple tree diseases, enabling more effective timing, and selecting the fungicide application, resulting in better control and increasing yield. The obtained dataset as well as scripts in Matlab for processing data and finding optimal spectral bands are available via the link: https://***/d/ZqfGaNlYVR3TUA. Copyright © 2020, The Authors. All rights reserved.

关键词： Infrared devices

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

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

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

A "String Art" Approach to the Design and Manufacturing of Optimal Composite Materials and Structures

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arXiv 2020年

作者： Ostanin, Igor Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow Russia

In this paper we report a new promising idea on the design and manufacturing of ply composite structures, tailored to exhibit maximum stiffness under given weight constraints and loading conditions. It is based on the idea behind an artistic technique known as "string art" - the representation of an image with a single thread, tensioned between pins on the flat frame. A discrete optimization algorithm has been employed recently to formalize the process of finding a configuration of thread windings that fuses into a given greyscale image. We demonstrate how this algorithm can be employed to approximate the two-dimensional distribution of isotropic material, computed by a conventional topology optimization algorithm. An optimal composite design is thus found as a result of the following two-stage process. At the first stage, topology optimization procedure produces regular grid of greyscale values of stiffness. At the second stage, this distribution is approximated with a polyline, representing the stiff reinforcement fiber in a soft matrix, according to "string art" optimization algorithm. The efficiency of the proposed approach is illustrated with few simple numerical examples. Our development opens a wide avenue for the industrial design of the new generation of fibrous composite structures. Copyright © 2020, The Authors. All rights reserved.

关键词： Manufacture

Optimal Multistage Group Testing Algorithm for 3 Defectives

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Optimal Multistage Group Testing Algorithm for 3 Defectives

IEEE International Symposium on Information Theory

作者： Ilya Vorobyev Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow Russia

The following topics are dealt with: channel coding; computational complexity; decoding; channel capacity; probability; optimisation; error correction codes; learning (artificial intelligence); graph theory; and data ...

ISBN: (数字)9781728164328

ISBN: (纸本)9781728164335

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Bayesian generative models for knowledge transfer in MRI semantic segmentation problems

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arXiv 2020年

作者： Kuzina, Anna Egorov, Evgenii Burnaev, Evgeny Skolkovo Institute of Science and Technology Center for Computational and Data-Intensive Science and Engineering Moscow Russia

Automatic segmentation methods based on deep learning have recently demonstrated state-of-the-art performance, outperforming the ordinary methods. Nevertheless, these methods are inapplicable for small datasets, which are very common in medical problems. To this end, we propose a knowledge transfer method between diseases via the Generative Bayesian Prior network. Our approach is compared to a pre-train approach and random initialization and obtains the best results in terms of Dice Similarity Coefficient metric for the small subsets of the Brain Tumor Segmentation 2018 database (BRATS2018). Copyright © 2020, The Authors. All rights reserved.

关键词： Tumors

A S I N G L E I M AG E D E E P L E A R N I N G A P P ROAC H TO R E S TO R AT I O N O F C O R RU P T E D R E M OT E S E N S I N G P RO D U C T S

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arXiv 2020年

作者： Petrovskaia, Anna Jana, Raghavendra B. Oseledets, Ivan V. Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

Remote sensing images are used for a variety of analyses, from agricultural monitoring, to disaster relief, to resource planning, among others. The images can be corrupted due to a number of reasons, including instrument errors and natural obstacles such as clouds. We present here a novel approach for reconstruction of missing information in such cases using only the corrupted image as the input. The Deep Image Prior methodology eliminates the need for a pre-trained network or an image database. It is shown that the approach easily beats the performance of traditional single-image methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Disaster prevention

Self-torqued harmonics and attosecond pulses driven by time-delayed relativistic vortex lasers

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Physical Review A 2022年第3期106卷 033515-033515页

作者： Jingwei Wang Matt Zepf Yuxin Leng Ruxin Li Sergey G. Rykovanov State Key Laboratory of High Field Laser Physics and Chinese Academy of Sciences Center for Excellence in Ultra-Intense Laser Science Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai 201800 China China-Russian Belt and Road Joint Laboratory on Laser Science Shanghai 201800 China Collaborative Innovation Center of IFSA Shanghai Jiao Tong University Shanghai 200240 China Helmholtz Institute Jena Fröbelstieg 3 07743 Jena Germany Faculty of Physics and Astronomy Friedrich-Schiller-Universität Jena 07743 Jena Germany High Performance Computing and Big Data Laboratory Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow 121205 Russia

Light carrying time-varying orbital angular momentum (OAM) is a recently discovered type of structured electromagnetic field compared with a typical vortex field whose OAM is static. Such so-called self-torqued light is employed for manipulating the fast magnetic, topological, and quantum excitations and increasing its intensity and having access to shorter pulse durations would be of great benefit. Here we theoretically and numerically demonstrate the generation of intense self-torqued harmonics and attosecond pulses in the relativistic regime, driven by two time-delayed relativistic vortex lasers with different OAMs l1 and l2. The OAM of the nth harmonic spans nl1 to nl2, and the OAM of the attosecond pulses changes from l1 to l2. Such intense self-torqued harmonics and attosecond pulses may offer alternative possibilities in ultrafast spectroscopy.

关键词： High intensity laser-plasma interactions High-energy-density plasmas Radiation & particle generation in plasmas Ultrafast phenomena Relativistic plasmas Particle-in-cell methods Relativistic hydrodynamics

Kalman Filtering for Accurate and Fast Plant Growth Dynamics Assessment

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

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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Average age of information of irregular repetition slotted ALOHA

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arXiv 2020年

作者： Munari, Andrea Frolov, Alexey Wessling82234 Germany Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology Moscow121205 Russia

Flanking traditional metrics such as throughput and reliability, age of information (AoI) is emerging as a fundamental tool to capture the performance of IoT systems. In this context, we focus on a setup in which a large number of nodes attempt delivery of time-stamped updates to a common destination over a shared channel, and investigate the ability of different grant-free access strategies to maintain fresh information at the receiver. Specifically, we derive for the first time an exact closed-form expression of the average AoI achieved by irregular repetition slotted ALOHA (IRSA), and compare its performance to that of a slotted ALOHA approach. Our analysis reveals the potential of modern random access schemes, and pinpoints some fundamental trade-offs, providing useful hints for proper system design. Copyright © 2020, The Authors. All rights reserved.

关键词： Economic and social effects