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First light demonstration of the integrated superconducting spectrometer

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arXiv 2019年

作者： Endo, Akira Karatsu, Kenichi Tamura, Yoichi Oshima, Tai Taniguchi, Akio Takekoshi, Tatsuya Asayama, Shinichiro Bakx, Tom J. L. C. Bosma, Sjoerd Bueno, Juan Chin, Kah Wuy Fujii, Yasunori Fujita, Kazuyuki Huiting, Robert Ikarashi, Soh Ishida, Tsuyoshi Ishii, Shun Kawabe, Ryohei Klapwijk, T.M. Kohno, Kotaro Kouchi, Akira Llombart, Nuria Maekawa, Jun Murugesan, Vignesh Nakatsubo, Shunichi Naruse, Masato Ohtawara, Kazushige Laguna, Alejandro Pascual Suzuki, Junya Suzuki, Koyo Thoen, David J. Tsukagoshi, Takashi Ueda, Tetsutaro Visser, Pieter J. De Werf, Paul P. Vander Yates, Stephen J. C. Yoshimura, Yuki Yurduseven, Ozan Baselmans, Jochem J. A. Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 Netherlands Kavli Institute of NanoScience Faculty of Applied Sciences Delft University of Technology Lorentzweg 1 Delft2628 Netherlands SRON|Netherlands Institute for Space Research Sorbonnelaan 2 Utrecht3584 Netherlands Division of Particle and Astrophysical Science Graduate School of Science Nagoya University Aichi464-8602 Japan National Astronomical Observatory of Japan Mitaka Tokyo181-8588 Japan Graduate University for Advanced Studies 2-21-1 Osawa Mitaka Tokyo181-0015 Japan Institute of Astronomy Graduate School of Science University of Tokyo 2-21-1 Osawa Mitaka Tokyo181-0015 Japan Graduate School of Informatics and Engineering University of Electro-Communications Cho-fu Tokyo182-8585 Japan School of Physics and Astronomy Cardi University Parade CardiCF243AA United Kingdom Department of Astronomy School of Science University of Tokyo Bunkyo Tokyo113-0033 Japan Institute of Low Temperature Science Hokkaido University Sapporo060-0819 Japan Joint ALMA Observatory Alonso de Cordova Vitacura Santiago3107 Physics Department Moscow State Pedagogical University Moscow119991 Russia Research Center for the Early Universe Graduate School of Science University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-0033 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency Sagamihara252-5210 Japan Graduate School of Science and Engineering Saitama University 255 Shimo-okubo Sakura Saitama338-8570 Japan High Energy Accelerator Research Organization 1-1 Oho Tsukuba Ibaraki305-0801 Japan Leiden Observatory Leiden University PO Box 9513 LeidenNL-2300 Netherlands SRON Netherlands Institute for Space Research Landleven 12 Groningen9747 Netherlands

Ultra-wideband 3D imaging spectrometry in the millimeter-submillimeter (mm-submm) band is an essential tool for uncovering the dust-enshrouded portion of the cosmic history of star formation and galaxy evolution1{3. However, t is challenging to scale up conventional coherent heterodyne receivers4 or free-space diffraction techniques5 to suficient bandwidths (≥1 octave) and numbers of spatial pixels2,3 (>102). Here we present the design and first astronomical spectra of an intrinsically scalable, ntegrated superconducting spectrometer6, which covers 332{377 GHz with a spectral resolution of F/ΔF ∼ 380. It combines the multiplexing advantage of microwave kinetic inductance detectors (MKIDs7) with planar superconducting filters for dispersing the signal in a single, small superconducting integrated circuit. We demonstrate the two key applications for an instrument of this type: As an eficient redshift machine, and as a fast multi-line spectral mapper of extended areas. The line detection sensitivity is in excellent agreement with the instrument design and laboratory performance, reaching the atmospheric foreground photon noise limit on sky. The design can be scaled to bandwidths in excess of an octave, spectral resolution up to a few thousand and frequencies up to ∼1.1 THz. The miniature chip footprint of a few cm2 allows for compact multi-pixel spectral imagers, which would enable spectroscopic direct imaging and large volume spectroscopic surveys that are several orders of magnitude faster than what is currently possible1{3. Copyright © 2019, The Authors. All rights reserved.

关键词： Bandwidth

Joint pilot allocation and robust transmission design for ultra-dense user-centric tdd C-ran with imperfect CSI

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arXiv 2017年

作者： Pan, Cunhua Mehrpouyan, Hani Liu, Yuanwei Elkashlan, Maged Nallanathan, Arumugam Queen Mary University of London LondonE1 4NS United Kingdom Department of Electrical and Computer Engineering Boise State University BoiseID83725 United States Department of Informatics Kings College London LondonWC2R 2LS United Kingdom

This paper considers the unavailability of complete channel state information (CSI) in ultra-dense cloud radio access networks (C-RANs). The user-centric cluster is adopted to reduce the computational complexity, while the incomplete CSI is considered to reduce the heavy channel training overhead, where only large-scale inter-cluster CSI is available. Channel estimation for intra-cluster CSI is also considered, where we formulate a joint pilot allocation and user equipment (UE) selection problem to maximize the number of admitted UEs with fixed number of pilots. A novel pilot allocation algorithm is proposed by considering the multi-UE pilot interference. Then, we consider robust beam-vector optimization problem subject to UEs' data rate requirements and fronthaul capacity constraints, where the channel estimation error and incomplete inter-cluster CSI are considered. The exact data rate is difficult to obtain in closed form, and instead we conservatively replace it with its lower-bound. The resulting problem is nonconvex, combinatorial, and even infeasible. A practical algorithm, based on UE selection, successive convex approximation (SCA) and semi-definite relaxation approach, is proposed to solve this problem with guaranteed convergence. We strictly prove that semidefinite relaxation is tight with probability 1. Finally, extensive simulation results are presented to show the fast convergence of our proposed algorithm and demonstrate its superiority over the existing algorithms. Copyright © 2017, The Authors. All rights reserved.

关键词： Channel state information

Sea wind parameters retrieval using Y-configured Doppler navigation system data. Performance and accuracy

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Journal of Physics: Conference Series 2018年第3期1015卷

作者： A B Khachaturian A V Nekrasov M I Bogachev Saint Petersburg Electrotechnical University Professora Popova 5 Saint Petersburg 197376 Russia Institute for Computer Technologies and Information Security Southern Federal University Chekhova 2 Taganrog 347922 Russia Faculty of Electrical Engineering and Informatics Technical University of Košice Letná 9 Košice 042 00 Slovakia

The authors report the results of the computer simulations of the performance and accuracy of the sea wind speed and direction retrieval. The analyzed measurements over the sea surface are made by the airborne microwave Doppler navigation system (DNS) with three Y-configured beams operated as a scatterometer enhancing its functionality. Single- and double-stage wind measurement procedures are proposed and recommendations for their implementation are described.

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Scalable photonic reinforcement learning by time-division multiplexing of laser chaos

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arXiv 2018年

作者： Naruse, Makoto Mihana, Takatomo Hori, Hirokazu Saigo, Hayato Okamura, Kazuya Hasegawa, Mikio Uchida, Atsushi Network System Research Institute National Institute of Information and Communications Technology 4-2-1 Nukui-kita Koganei Tokyo184-8795 Japan Department of Information and Computer Sciences Saitama University 255 Shimo-Okubo Sakura-ku Saitama Saitama338-8570 Japan Interdisciplinary Graduate School University of Yamanashi Takeda Kofu Yamanashi400-8510 Japan Nagahama Institute of Bio-Science and Technology 1266 Tamura Nagahama Shiga526-0829 Japan Graduate School of Informatics Nagoya University Furo Chikusa Nagoya Aichi464-8601 Japan Department of Electrical Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika Tokyo125-8585 Japan

Reinforcement learning involves decision making in dynamic and uncertain environments and constitutes a crucial element of artificial intelligence. In our previous work, we experimentally demonstrated that the ultrafast chaotic oscillatory dynamics of lasers can be used to solve the two-armed bandit problem efficiently, which requires decision making concerning a class of difficult trade-offs called the exploration?exploitation dilemma. However, only two selections were employed in that research;thus, the scalability of the laser-chaos-based reinforcement learning should be clarified. In this study, we demonstrated a scalable, pipelined principle of resolving the multi-armed bandit problem by introducing time-division multiplexing of chaotically oscillated ultrafast time-series. The experimental demonstrations in which bandit problems with up to 64 arms were successfully solved are presented in this report. Detailed analyses are also provided that include performance comparisons among laser chaos signals generated in different physical conditions, which coincide with the diffusivity inherent in the time series. This study paves the way for ultrafast reinforcement learning by taking advantage of the ultrahigh bandwidths of light wave and practical enabling technologies. Copyright © 2018, The Authors. All rights reserved.

关键词： Time series

Network slicing based 5G and future mobile networks: Mobility, resource management, and challenges

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arXiv 2017年

作者： Zhang, Haijun Liu, Na Chu, Xiaoli Long, Keping Aghvami, Abdol-Hamid Leung, Victor C.M. Beijing Engineering and Technology Research Center Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing100083 Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada College of Information Science and Technology Beijing University of Chemical Technology Beijing100029 China Department of Electronic and Electrical Engineering University of Sheffield SheffieldS1 3JD United Kingdom Department of Informatics King's College London LondonWC2R 2LS United Kingdom

The fifth-generation (5G) networks are expected to be able to satisfy users' different quality-of-service (QoS) requirements. Network slicing is a promising technology for 5G networks to provide services tailored for users' specific QoS demands. Driven by the increased massive wireless data traffic from different application scenarios, efficient resource allocation schemes should be exploited to improve the flexibility of network resource allocation and capacity of 5G networks based on network slicing. Due to the diversity of 5G application scenarios, new mobility management schemes are greatly needed to guarantee seamless handover in network slicing based 5G systems. In this article, we introduce a logical architecture for network slicing based 5G systems, and present a scheme for managing mobility between different access networks, as well as a joint power and subchannel allocation scheme in spectrum-sharing two-tier systems based on network slicing, where both the co-tier interference and cross-tier interference are taken into account. Simulation results demonstrate that the proposed resource allocation scheme can flexibly allocate network resources between different slices in 5G systems. Finally, several open issues and challenges in network slicing based 5G networks are discussed, including network reconstruction, network slicing management and cooperation with other 5G technologies. Copyright © 2017, The Authors. All rights reserved.

关键词： 5G mobile communication systems

Erratum to: Search for resonant and nonresonant production of pairs of dijet resonances in proton-proton collisions at = 13 TeV

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Journal of High Energy Physics 2025年第5期2025卷 1-23页

作者： Tumasyan, A. Adam, W. Andrejkovic, J. W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P. S. Jeitler, M. Krammer, N. Lechner, L. Liko, D. Mikulec, I. Paulitsch, P. Pitters, F. M. Schieck, J. Schöfbeck, R. Schwarz, D. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M. R. Janssen, T. Kello, T. Rejeb Sfar, H. Van Mechelen, P. Bols, E. S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Moortgat, S. Morton, A. Müller, D. Sahasransu, A. R. Tavernier, S. Van Doninck, W. Vannerom, D. Clerbaux, B. De Lentdecker, G. Favart, L. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Makarenko, I. Malara, A. Paredes, S. Pétré, L. Postiau, N. Starling, E. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. Dobur, D. Knolle, J. Lambrecht, L. Mestdach, G. Niedziela, M. Rendón, C. Roskas, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den Bossche, N. Vermassen, B. Wezenbeek, L. Benecke, A. Bethani, A. Bruno, G. Bury, F. Caputo, C. David, P. Delaere, C. Donertas, I. S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Mondal, K. Prisciandaro, J. Taliercio, A. Tran, T. T. Vischia, P. Wertz, S. Alves, G. A. Coelho, E. Hensel, C. Moraes, A. Rebello Teles, P. Aldá Júnior, W. L. Alves Gallo Pereira, M. Barroso Ferreira Filho, M. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Da Costa, E. M. Da Silveira, G. G. De Jesus Damiao, D. Dos Santos Sousa, V. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S. M. Sznajder, A. Thiel, M. Torres Da Silva De Araujo, F. Vilela Pereira, A. Bernardes, C. A. Calligaris, L. Fernandez Perez Tomei, T. R. Gregores, E. M. Mercadante, P. G. Novaes, S. F. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Rodozov, M. Shopova, M. Sultanov, G. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Cheng, T. Javaid, T. Mittal, M. Yuan, L. Ahmad, M. Bauer, G. Hu, Z. Lezki, S. Yi, K. Chen, G. M. Chen, H. S. Chen, M. Iemmi, F. Jiang, C. H. Kapo Yerevan Physics Institute Yerevan Armenia Yerevan State University Yerevan Armenia Institut für Hochenergiephysik Vienna Austria TU Wien Vienna Austria Universiteit Antwerpen Antwerpen Belgium Institute of Basic and Applied Sciences Faculty of Engineering Arab Academy for Science Technology and Maritime Transport Alexandria Egypt Université Libre de Bruxelles Bruxelles Belgium Vrije Universiteit Brussel Brussel Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual de Campinas Campinas Brazil Federal University of Rio Grande do Sul Porto Alegre Brazil UFMS Nova Andradina Brazil The University of the State of Amazonas Manaus Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China University of Chinese Academy of Sciences Beijing China Department of Physics Tsinghua University Beijing China Nanjing Normal University Department of Physics Nanjing China The University of Iowa Iowa City USA Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) - Fudan University Shanghai China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prag

Mapping the Human Body at Cellular Resolution -- The NIH Common Fund Human BioMolecular Atlas Program

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arXiv 2019年

作者： Snyder, Michael P. Lin, Shin Posgai, Amanda Atkinson, Mark Regev, Aviv Rood, Jennifer Rozenblatt-Rosen, Orit Gaffney, Leslie Hupalowska, Anna Satija, Rahul Gehlenborg, Nils Shendure, Jay Laskin, Julia Harbury, Pehr Nystrom, Nicholas A. Bar-Joseph, Ziv Zhang, Kun Börner, Katy Lin, Yiing Conroy, Richard Procaccini, Dena Roy, Ananda L. Pillai, Ajay Brown, Marishka Galis, Zorina S. Cai, Long Shendure, Jay Trapnell, Cole Lin, Shin Jackson, Dana Snyder, Michael P. Nolan, Garry Greenleaf, William James Lin, Yiing Plevritis, Sylvia Ahadi, Sara Lee, Hayan Nevins, Stephanie Esplin, Ed Horning, Aaron Bahmani, Amir Zhang, Kun Sun, Xin Jain, Sanjay Hagood, James Kharchenko, Peter Atkinson, Mark Bodenmiller, Bernd Brusko, Todd Clare-Salzler, Michael Nick, Harry Otto, Kevin Posgai, Amanda Wasserfall, Clive Maffioletti, Sergio Caprioli, Richard M. Spraggins, Jeffrey M. Gutierrez, Danielle Patterson, Nathan Heath Neumann, Elizabeth K. Harris, Raymond deCaestecker, Mark de Plas, Raf Van Lau, Ken Cai, Long Yuan, Guo-Cheng Zhu, Qian Dries, Ruben Yin, Peng Saka, Sinem K. Kishi, Jocelyn Y. Wang, Yu Goldaracena, Isabel Laskin, Julia Ye, DongHye Burnum-Johnson, Kristin E. Piehowski, Paul D. Ansong, Charles Zhu, Ying Harbury, Pehr Desai, Tushar Mulye, Jay Chou, Peter Nagendran, Monica Bar-Joseph, Ziv Teichmann, Sarah A. Paten, Benedict Murphy, Robert F. Ma, Jian Kiselev, Vladimir Yu Kingsford, Carl Ricarte, Allyson Ruffalo, Matthew Gehlenborg, Nils Kharchenko, Peter Vella, Margaret McCallum, Chuck Börner, Katy Cross, Leonard E. Friedman, Samuel H. Heiland, Randy Herr, Bruce Macklin, Paul Quardokus, Ellen M. Record, Lisel Sluka, James P. Weber, Griffin M. Nystrom, Nicholas A. Silverstein, Jonathan C. Blood, Philip D. Ropelewski, Alexander J. Shirey, William E. Mabee, Paula Lenhardt, W. Christopher Robasky, Kimberly Michailidis, Stavros Satija, Rahul Marioni, John Regev, Aviv Butler, Andrew Stuart, Tim Fisher, Eyal Ghazanfar, Shila Rood, Jennifer Gaffney, Leslie Ersalan, Gokcen Biancalani, Tommaso Conroy, Richard Procaccini, Dena Roy, Anan School of Medicine Stanford University 300 Pasteur Drive United States Department of Genetics Stanford School of Medicine StanfordCA94305 United States Department of Medicine University of Washington SeattleWA98195 United States Department of Pathology University of Florida Diabetes Institute GainesvilleFL32610 United States Klarman Cell Observatory Broad Institute of MIT and Harvard CambridgeMA02142 United States Howard Hughes Medical Institute Koch Institute of Integrative Cancer Research Department of Biology Massachusetts Institute of Technology CambridgeMA02140 United States New York Genome Center New York CityNY10013 United States New York University New YorkNY10012 United States Department of Biomedical Informatics Harvard Medical School BostonMA02115 United States Department of Genome Sciences University of Washington SeattleWA98105 United States Department of Chemistry Purdue University West LafayetteIN47907 United States Department of Biochemistry Stanford University School of Medicine StanfordCA94305 United States Pittsburgh Supercomputing Center Carnegie Mellon University PittsburghPA15213 United States Department of Computational Biology School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Department of Bioengineering University of California San Diego La JollaCA92093 United States Department of Intelligent Systems Engineering School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Department of Surgery Washington University School of Medicine St LouisMO63110 United States Division of Program Coordination Planning and Strategic Initiatives National Institutes of Health BethesdaMD20892 United States National Human Genome Research Institute National Institutes of Health BethesdaMD20892 United States National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Caltech-UW TMC Departmen

Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible 3D molecular and cellular atlas of the human body, in health and various disease settings. Copyright © 2019, The Authors. All rights reserved.

关键词： Mapping

Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Muhammad Iqbal Dahlan Abdullah H Hartono Cut Ita Erliana S Sriadhi Nurmawati M Adhi Prasnowo Abdurrozzaq Hasibuan Akbar Iskandar Kundharu Saddhono Abdussakir Hastuti Musa Muhammad Ikhsan Setiawan Youmeni Sagala Rumiris Siahaan Eka Mayastika Sinaga Anggraini Syahputri Feby Milanie Henry Aspan Muammar Khaddafi Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan-Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making System of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods.

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Retraction: Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method (J. Phys.: Conf. Ser. 1114 012082)

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Journal of Physics: Conference Series 2018年第1期1114卷

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

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