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International Workshop on Advanced Image technology (IWAIT)

作者： Supawadee Ekkasan Theekapun Charoenpong Kosin Chamnongthai Supiya Charoensiriwath Department of Biomedical Engineering Srinakharinwijot University Nakhonnayok Thailand Department of Electrical and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Thailand Biomedical Signal Processing Laboratory National Electronics and Computer Technology Center Pathumthani Thailand

ISBN: (纸本)9781538626160

Due to a problem of current research occurring when reading the nutrition facts label with Thai font. In this paper, we proposed a method to read the amount of the nutrition numbers on nutrition facts label with Thai font by using integrated image processing technique. This method consists of three steps: label extraction, number segmentation, and number classification. Nutrition facts label image is used as input of algorithm. First, the label is extracted by using a local adaptive threshold. Four sides of a label box are detected from histogram in horizontal and vertical axis. Second, numbers are segmented based on blob region analysis. Blob of number can be defined according to blob sequence in a line. A number in blob of number is then separated. Third, a number is divided into 5×7 regions. A number vector defined from 35 regions is used to classify the number by the support vector machine. To test the performance of the proposed method, number of the amount of the nutrition is extracted from twenty Thai labels. In such labels, there are 180 numbers. A number is classified into number 0-9. By using support vector machine for classification, the accuracy is 81.11%. The experimental result shows the satisfactory results. This is the first method for reading number in Thai nutrition facts label.

关键词： Erbium Data acquisition Data mining Graphics Tools

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END TO END SIMULATION STUDY OF GEOSTAIONARY PASSIVE MICROWAVE ATMOSPHERIC SOUNDING

END TO END SIMULATION STUDY OF GEOSTAIONARY PASSIVE MICROWAV...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Ke Chen Al. Gasiewski Kun Zhang Liang Lang Liangqi Gui Qingxia Li Ye He Science and Technology on Multi-spectral Information Processing Laboratory Wuhan China Department of Electrical Computer and Energy Engineering University of Colorado at Boulder School of Electronic Information and Communications Huazhong University of Science and Technology

A numerical simulator for analysis of the geostationary orbit multispectral passive microwave (Geo-MW) mapping and sounding is described, which mainly includes upwelling brightness temperatures forward, microwave radiometer payload simulation and atmospheric profile retrieval. This simulator allows evaluation and optimization of the ability of microwave sensors to retrieve atmospheric temperature and humidity profile. In this paper, end to end simulation study of a Geo-MW radiometer observation at selected frequencies from 50 to 425 GHz with a real-aperture antenna is performed and the accuracy of the brightness temperature measurement and the atmospheric temperature and humidity profile sounding are quantitatively analyzed and evaluated.

关键词： Atmospheric modeling Microwave radiometry Brightness temperature Microwave imaging Microwave antennas Computational modeling Microwave communication

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On Capacity-Based Codebook Design and Advanced Decoding for Sparse Code Multiple Access Systems

On Capacity-Based Codebook Design and Advanced Decoding for ...

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作者： Xiao, Kexin Xia, Bin Chen, Zhiyong Xiao, Baicen Chen, Dageng Ma, Shaodan Shanghai Institute for Advanced Communication and Data Science Institute of Wireless Communication Technologies Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Institute of Wireless Communication Technologies Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Electrical Engineering University of Washington SeattleWA98105 United States Cooperative Medianent Innovation Center Shanghai Jiao Tong University Shanghai200240 China Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai200240 China Communications Technology Laboratory Huawei Technologies Co. Ltd. Shanghai201206 China Department of Electrical and Computer Engineering University of Macau C-Macau999078 China

Sparse code multiple access (SCMA) is a promising non-orthogonal air-interface technology for its ability to support massive connections. In this paper, we design the multiuser codebook and the advanced decoding from the perspective of the theoretical capacity and the system feasibility. First, different from the lattice-based constellation in point-to-point channels, we propose a novel codebook for maximizing the constellation constrained capacity. We optimize a series of 1-D superimposed constellations to construct multi-dimensional codewords. An effective dimensional permutation switching algorithm is proposed to further obtain the capacity gain. Consequently, it shows that the performance of the proposed codebook approaches the Shannon limit and achieves significant gains over the other existing ones. Furthermore, we provide a symbol-based extrinsic information transfer tool to analyze the convergence of SCMA iterative detection, where the complex codewords are considered in modeling the a priori probabilities instead of assuming the binary inputs in previous literature. Finally, to approach the capacity, we develop a low-density parity-check code-based SCMA receiver. Most importantly, by utilizing the EXIT charts, we propose an iterative joint detection and decoding scheme with only partial inner iterations, which exhibits significant performance gain over the traditional one with separate detection and decoding. © 2002-2012 IEEE.

关键词： Iterative decoding

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Corrigendum: Ethanol-controlled peroxidation in liquid-anode discharges (2019 J. Phys. D: Appl. Phys. 52 425205)

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Journal of Physics D: Applied Physics 2021年第22期54卷

作者： Qiang Chen Jiao Lin Xinyi He Hailong Hu Junshuai Li Qing Xiong Bingyan Chen Zhengyong Song Hai Liu Qing Huo Liu Kostya (Ken) Ostrikov Institute of Electromagnetics and Acoustics Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Department of Electronic Science Xiamen University Xiamen 361005 People's Republic of China College of Physics and Information Engineering Fuzhou University Fuzhou 350116 People's Republic of China Key Laboratory of Special Function Materials and Structure Design of the Ministry of Education and School of Physical Science and Technology Lanzhou University Lanzhou 730000 People's Republic of China State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing University Chongqing 400044 People's Republic of China Department of Mathematics and Physics Hohai University Changzhou 213022 People's Republic of China School of Civil Engineering Guangzhou University Guangzhou 510006 People's Republic of China Department of Electrical and Computer Engineering Duke University Durham NC 27708 United States of America Institute for Future Environments and School of Chemistry Physics and Mechanical Engineering Queensland University of Technology Brisbane QLD 4000 Australia CSIRO-QUT Joint Sustainable Processes and Devices Laboratory Commonwealth Scientific and Industrial Research Organization PO Box 218 Lindfield NSW 2070 Australia

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Machine discovery of partial differential equations from spatiotemporal data

arXiv

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arXiv 2019年

作者： Yuan, Ye Li, Junlin Li, Liang Jiang, Frank Tang, Xiuchuan Zhang, Fumin Liu, Sheng Goncalves, Jorge Voss, Henning U. Li, Xiuting Kurths, Jürgen Ding, Han School of Artificial Intelligence and Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta30332 United States School of Power and Mechanical Engineering Wuhan University Wuhan430074 China Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom Luxembourg Centre for Systems Biomedicine University of Luxembourg BelvauxL-4367 Luxembourg Citigroup Biomedical Imaging Center Weill Cornell Medical College New York10021 United States Research Domain IV - Transdisciplinary Concepts & Methods Potsdam Institute for Climate Impact Research Potsdam14473 Germany School of Mechanical Science and Engineering State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China

The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data. The method, called Sparse Spatiotemporal System Discovery (S3d), decides which physical terms are necessary and which can be removed (because they are physically negligible in the sense that they do not affect the dynamics too much) from a pool of candidate functions. The method is built on the recent development of Sparse Bayesian Learning;which enforces the sparsity in the to-be-identified PDEs, and therefore can balance the model complexity and fitting error with theoretical guarantees. Without leveraging prior knowledge or assumptions in the discovery process, we use an automated approach to discover ten types of PDEs, including the famous Navier-Stokes and sine-Gordon equations, from simulation data alone. Moreover, we demonstrate our data-driven discovery process with the Complex Ginzburg-Landau Equation (CGLE) using data measured from a traveling-wave convection experiment. Our machine discovery approach presents solutions that has the potential to inspire, support and assist physicists for the establishment of physical laws from measured spatiotemporal data, especially in notorious fields that are often too complex to allow a straightforward establishment of physical law, such as biophysics, fluid dynamics, neuroscience or nonlinear optics. Copyright © 2019, The Authors. All rights reserved.

关键词： Nonlinear optics

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Tensor representation in high-frequency financial data for price change prediction

Tensor representation in high-frequency financial data for p...

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2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017

作者： Tran, Dat Thanh Magris, Martin Kanniainen, Juho Gabbouj, Moncef Iosifidis, Alexandros Laboratory of Signal Processing Tampere University of Technology Tampere Finland Laboratory of Industrial and Information Management Tampere University of Technology Tampere Finland Department of Engineering Electrical and Computer Engineering Aarhus University Aarhus Denmark

ISBN: (纸本)9781538627259

Nowadays, with the availability of massive amount of trade data collected, the dynamics of the financial markets pose both a challenge and an opportunity for high frequency traders. In order to take advantage of the rapid, subtle movement of assets in High Frequency Trading (HFT), an automatic algorithm to analyze and detect patterns of price change based on transaction records must be available. The multichannel, time-series representation of financial data naturally suggests tensor-based learning algorithms. In this work, we investigate the effectiveness of two multilinear methods for the mid-price prediction problem against other existing methods. The experiments in a large scale dataset which contains more than 4 millions limit orders show that by utilizing tensor representation, multilinear models outperform vector-based approaches and other competing ones. © 2017 IEEE.

关键词： Tensors

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Conceptual design of the three-dimensional magnetic field configuration relevant to the magnetopause reconnection in the SPERF

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plasma Science and technology 2017年第3期19卷 27-33页

作者： Aohua MAO Yang REN Hantao JI Peng E Ke HAN Zhibin WANG Qingmei XlAO Laboratory for Space Environment and Physical Sciences Harbin Institute of Technology Harbin 150001 People's Republic of China Princeton Plasma Playsics Laboratory Princeton University Princeton New Jersey 08543 USA School of computer & information engineering Harbin University of Commerce Harbin 150028 people's Republic of China Department of electrical engineering Harbin Institute of Technology Harbin 150001 People's Republicof China

A new ground-based expenmental device,the Space plasma Environment Research Facility（SPERF）,is being designed at Harbin Institute of technology in China,with Asymmetric REconnection eXperiment-3 Dimensional（AREX-3D） as one of the experimental components to study the asymmetric reconnection dynamics relevant to the interaction between the interplanetary and magnetospheric *** asymmetry in the designed magnetic reconnection process not only refers to the distinct plasma parameters designed for the two upstream regions across the current sheet,but also refers to the inhomogeneity in the direction along the current sheet resulting from the designed 3D magnetic field *** two asymmetries are fundamental features of the reconnection process at the Earth＇s *** experiment,the reconnection process is driven by a set of flux cores through coil-currentramp-up from the ＇magnetosheath-side＇ to interact with a dipole magnetic field generated by the Dipole Research Experiment（DREX） coil on the ＇magnetosphere-side＇.The AREX-3D will be able to investigate a range of important reconnection issues in 3D magnetic field geometry that is relevant to the Earth＇s magnetopause.A wide range of plasma parameters can be achieved through inductive plasma generation with flux cores on the ＇magnetosheath-side＇ and electron cyclotron resonance（ECR） with microwave sources on the ＇magnetosphere-side＇,***（low）plasma density at experimental magnetosheath（dipole） *** reconnection regimes and geometries can be produced by adjusting plasma parameters and coil setups as well as coil current *** three-dimensional magnetic field configurations in the SPERF relevant to the dayside magnetopause reconnection are discussed in detail.

关键词： AREX-3D SPERF magnetosphere reconnection experiment asymmetric magneticreconnection

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Modelling of synchronisation and energy performance of FBE- and LBE-based standalone LTE-U networks

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Journal of engineering 2017年第7期2017卷 292-299页

作者： Li, Jiamin Shan, Hangguan Huang, Aiping Yuan, Jiantao Cai, Lin X. Zhejiang Provincial Key Laboratory of Information Processing and Communication Networks Hangzhou China College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Department of Electrical and Computer Engineering Illinois Institute of Technology Chicago United States

Without the aid of licensed channel, deploying long-term evolution (LTE) networks over unlicensed spectrum (named standalone LTE-U networks) faces the difficulty of establishing and maintaining synchronisation between user equipments and base stations. In this work, considering the two modes of listen-before-talk-based channel access scheme, frame-based equipment (FBE) and load-based equipment (LBE), the authors propose analytical frameworks to study the successful probability of synchronisation and the energy consumption of synchronisation in a standalone LTE-U network. Specifically, for the LBE mode, the authors also propose a Lattice-Poisson algorithmbased approach to derive the distribution of the channel non-occupancy period of a standalone LTE-U network. Furthermore, the authors explore the impact of diverse protocol parameters of both FBE and LBE modes on the two studied performance metrics. Simulation results demonstrate the accuracy of the analysis, and shed some light on the selection of FBE and LBE for standalone LTE-U networks, in terms of synchronisation, energy consumption, and throughput of standalone LTE-U and Wi-Fi networks.

关键词： Synchronization

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Deep learning enabled fast optical characterization of two-dimensional materials

arXiv

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arXiv 2019年

作者： Han, Bingnan Lin, Yuxuan Yang, Yafang Mao, Nannan Li, Wenyue Wang, Haozhe Fatemi, Valla Zhou, Lin Wang, Joel I-Jan Ma, Qiong Cao, Yuan Rodan-Legrain, Daniel Bie, Ya-Qing Navarro-Moratalla, Efrén Klein, Dahlia MacNeill, David Wu, Sanfeng Leong, Wei Sun Kitadai, Hikari Ling, Xi Jarillo-Herrero, Pablo Palacios, Tomás Yin, Jihao Kong, Jing Image Processing Center School of Astronautics Beihang University Beijing100191 China Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Chemistry Boston University BostonMA02215 United States Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Instituto de Ciencia Molecular Universidad de Valencia c/Catedrático José Beltrán 2 Paterna46980 Spain Division of Materials Science and Engineering Boston University BostonMA02215 United States

Characterization of nanomaterial morphologies with advanced microscopy and/or spectroscopy tools plays an indispensable role in nanoscience and nanotechnology research 1 2, 3, 4, 5, as rich information about the chemical compositions, crystallography, other physical and chemical properties, as well as the growth mechanism can be extracted from morphology analysis. However, the interpretation of imaging data heavily relies on the "intuition" of experienced researchers. As a result, many of the deep graphical features are often unused because of difficulties in processing the data and finding the correlations. Such difficulties can be well addressed by deep learning 6 7, 8, 9. In this work, we use the optical characterization of two-dimensional (2D) materials as a case study, and demonstrate a neural network based algorithm for the material and thickness identification of exfoliated 2D materials with high prediction accuracy and real-time processing capability. Further analysis shows that the trained network can be used to predict physical properties of the materials. Finally, a transfer learning technique is applied to adapt the pretrained network to more optical characterization applications such as identifying layer numbers of chemically synthesized graphene domains. Copyright © 2019, The Authors. All rights reserved.

关键词： Data handling

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Whistler waves observed by Solar Orbiter / RPW between 0.5 AU and 1 AU

arXiv

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arXiv 2021年

作者： Kretzschmar, Matthieu Chust, T. Krasnoselskikh, V. Graham, D. Colomban, L. Maksimovic, M. Khotyaintsev, Yu V. Soucek, J. Steinvall, K. Santolík, O. Jannet, G. Brochot, J.-Y. Le Contel, O. Vecchio, A. Bonnin, X. Bale, S.D. Froment, C. Larosa, A. Bergerard-Timofeeva, M. Fergeau, P. Lorfevre, E. Plettemeier, D. Steller, M. Štverák, Š. Trávníček, P. Vaivads, A. Horbury, T.S. O’Brien, H. Evans, V. Angelini, V. Owen, C. Louarn, P. LPC2E UMR7328 CNRS University of Orléans 3A avenue de la recherche scientifique Orléans France LPP CNRS Ecole Polytechnique Sorbonne Université Observatoire de Paris Université Paris-Saclay Palaiseau Paris France Uppsala Sweden LESIA Observatoire de Paris Université PSL CNRS Sorbonne Université Université de Paris Meudon France Institute of Atmospheric Physics Czech Academy of Sciences Prague Czech Republic CNES 18 Avenue Edouard Belin Toulouse31400 France Technische Universität Dresden Würzburger Str. 35 DresdenD-01187 Germany Space Research Institute Austrian Academy of Sciences Graz Austria Astronomical Institute of the Czech Academy of Sciences Prague Czech Republic Radboud Radio Lab Department of Astrophysics Radboud University Nijmegen Netherlands Space Sciences Laboratory University of California BerkeleyCA United States Physics Department University of California CA United States Stellar Scientific BerkeleyCA United States Department of Space and Plasma Physics School of Electrical Engineering and Computer Science Royal Institute of Technology Stockholm Sweden Department of Physics Imperial College LondonSW7 2AZ United Kingdom Mullard Space Science Laboratory University College London Holmbury St. Mary Dorking SurreyRH5 6NT United Kingdom Institut de Recherche en Astrophysique et Planétologie 9 Avenue du Colonel ROCHE BP 4346 Toulouse Cedex 431028 France

Context. The solar wind evolution differs from a simple radial expansion and wave-particle interactions are supposed to be the major cause for the observed dynamics of the electron distribution function. In particular, whistler waves are thought to inhibit the electron heat flux and ensure the diffusion of the field aligned energetic electrons (Strahl) to replenish the halo population. Aims. The goal of our study is to detect and characterize the electromagnetic waves that can modify the electron distribution functions, with a special attention to whistler waves. Methods. We analyse in details the electric and magnetic field fluctuations observed by the Solar Orbiter spacecraft during its first orbit around the Sun between 0.5 and 1 AU. Using data of the Search Coil Magnetometer and electric antenna, both parts of the Radio and plasma Waves (RPW) instrumental suite, we detect the electromagnetic waves with frequencies above 3 Hz and determine the statistical distribution of their amplitudes, frequencies, polarization and k-vector as a function of distance. We also discuss relevant instrumental issues regarding the phase between the electric and magnetic measurements and the effective length of the electric antenna. Results. An overwhelming majority of the observed waves are right hand circularly polarized in the solar wind frame and identified as outward propagating and quasi parallel whistler waves. Their occurrence rate increases by a least a factor two from 1 AU to 0.5 AU. These results are consistent with the regulation of the heat flux by the whistler heat flux instability. Near 0.5 AU, whistler waves are found to be more field-aligned and to have smaller normalized frequency (f/ fce), larger amplitude, and larger bandwidth than at 1 AU. © 2021, CC BY-NC-ND.

关键词： Electromagnetic waves

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