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5th International Conference on applied computing and Information Technology, 2017 4th International Conference on Computational science/Intelligence and applied Informatics and 2017 1st International Conference on Big Data, Cloud computing, Data science and Engineering, ACIT-CSII-BCD 2017

作者： Wu, Chien-Heng Chang, Wen-Yi Tsai, Whey-Fone Lin, Franco Lee, Ching-Fang Yang, Chao-Tung High Performance Computing and Applications National Center for High-Performance Computing National Applied Research Laboratories Hsinchu Science Park No. 7 R and D 6th Rd. Hsinchu30076 Taiwan Cloud Computing and System Integration National Center for High-Performance Computing National Applied Research Laboratories Hsinchu Science Park No. 7 R and D 6th Rd. Hsinchu30076 Taiwan Computer Science Department TungHai University Boulevard Xitun District Taichung40704 Taiwan

ISBN: (纸本)9781538633021

The present study utilizes VirtualBox virtual environment technology to develop the personal and compact size of multi-node big data VM platform with Spark and Hadoop cluster that can effectively replicate and provides an environment for developers to easily design and implement Spark and Hadoop Map/Reduce programming. By using the multi-node Hadoop VM system, developers can conduct Map/Reduce programing completely the same as that in the real multi-node Hadoop cluster. To demonstrate its capability and applicability, this study performs the benchmark by using the big data VM platform and a physical Multi-Node Hadoop Cluster. Based on the standard WordCount benchmarking, the computing time of the physical multi-node Hadoop cluster is 3.7 times faster than that of VM Hadoop cluster. The benchmark results show that the big data VM platform is an ideal platform for the portal and Map/Reduce programming, Spark programming and testing purposes, and the physical Hadoop cluster is the most appropriate for production runs. In addition, the big data VM platform contains a web portal development module designed to support applications that implement big data computing services for the engineering and science users. Such applications are inherently complex, potentially accessing data from a variety of sources and distributing applications to a variety of clients. This portal development module can act as multiple roles in many projects such as personal portals, small business portals, enterprise portals, educational portal, infrastructure portal, and other types of portals. Finally, the big data VM platform, in term of a big data development platform, is ready for users to download. The first author of this paper would like to give a demonstration for the proposed multi-node big data VM platform. © 2017 IEEE.

关键词： MapReduce

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Development and Application of Personal Hadoop-Based Big Data Platform

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Journal of the Chinese Institute of Civil and Hydraulic Engineering 2018年第2期30卷 107-120页

作者： Wu, Gary Lin, Franco Chang, Wen-Yi Tsai, Whey-Fone Lin, Shi-Ching Yang, Chao-Tung National Center for High-performance Computing National Applied Research Laboratories Hsinchu30076 Taiwan Department of Computer Science Tunghai University Taichung40704 Taiwan

Big data and data mining technology is getting much more popular in recent years. Many world-class corporations such as Intel, Google and Alibaba invest large amounts of financial and manpower resources to perform big data analysis and data mining in order to assist the decision making and business strategy. The demand for big data analytics associated with environmental monitoring and model simulation has grown rapidly. However, many developers lack a big data platform for programing and testing because a distributed Hadoop cluster is not easily built. Hence, the present study utilized virtual environment technology to establish the personal Hadoop-based big data platform, which can replicate virtual machines on a single machine and provide an environment for data management and computing programing. Regarding the performance benchmark, the standard WordCount case was employed to analyze the performance. The result shows that using the distributed 1 + 3 virtual machines could be an ideal platform of code programing and testing for beginners with civil engineering background. In the end, two application cases are given to illustrate the big data analytics techniques in the developed big data platform. One is the flow image recognition for river velocity measurement, which explains the storage characteristics in the special designed file system and the distributed computing concept in data management and computing programing. The other is the two-dimensional hydraulic model simulation, which introduces the way to use native Fortran code for data management and computing programing by the streaming technique. Thus, the proposed big data platform with virtual machine capability as well as two application cases could be powerful tools to facilitate fast solving civil and hydraulic engineering problems regarding big data issues. © 2018, Chinese Institute of Civil and Hydraulic Engineering. All right reserved.

关键词： MapReduce

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On reference solutions and the sensitivity of the 2D Kelvin–Helmholtz instability problem

arXiv

引用

arXiv 2018年

作者： Schroeder, Philipp W. John, Volker Lederer, Philip L. Lehrenfeld, Christoph Lube, Gert Schöberl, Joachim Institute for Numerical and Applied Mathematics Georg-August-Universität Göttingen Göttingen37083 Germany Weierstrass Institute for Applied Analysis and Stochastics Berlin10117 Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin14195 Germany Institute for Analysis and Scientific Computing TU Wien 1040 Wien Austria

Two-dimensional Kelvin–Helmholtz instability problems are popular examples for assessing discretizations for incompressible flows at high Reynolds number. Unfortunately, the results in the literature differ considerably. This paper presents computational studies of a Kelvin–Helmholtz instability problem with high order divergence-free finite element methods. Reference results in several quantities of interest are obtained for three different Reynolds numbers up to the beginning of the final vortex pairing. A mesh-independent prediction of the final pairing is not achieved due to the sensitivity of the considered problem with respect to small perturbations. A theoretical explanation of this sensitivity to small perturbations is provided based on the theory of self-organization of 2D turbulence. Possible sources of perturbations that arise in almost any numerical simulation are discussed. Copyright © 2018, The Authors. All rights reserved.

关键词： Numerical methods

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Corrigendum to “A Dynamic Neural Network Architecture with Immunology Inspired Optimization for Weather Data Forecasting” [Big Data Research 14 (2018) 81–92]

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Big Data Research 2019年 18卷

作者： Abir Jaafar Hussain Panos Liatsis Mohammed Khalaf Hissam Tawfik Haya Al-Asker Liverpool John Moores University Applied Computing Research Group Liverpool L3 3AF Merseyside England United Kingdom Khalifa University of Science & Technology Department of Computer Science Abu Dhabi United Arab Emirates Leeds Beckett University School of Computing Creative Technologies & Engineering Leeds LS1 3HE W Yorkshire England United Kingdom Prince Sattam Bin Abdulaziz University Department of Computer Science College of Computer Engineering and Sciences Al-Kharj 11942 Saudi Arabia

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A Novel New Idea of Data Hiding Using GEMD Technique

A Novel New Idea of Data Hiding Using GEMD Technique

引用

International Conference on applied System Innovation

作者： Yi-Chun Weng Wen-Chung Kuo Chun-Cheng Wang Yu-Chih Huang Department of Computer Science and Information Engineering National Yunlin University of Science & Technology Douliou Yunlin Taiwan R.O.C. National Center for High-performance Computing National Applied Research Laboratories Tainan Taiwan R.O.C Department of Information Management Tainan University of Technology Yongkang District Tainan City Taiwan R.O.C.

Data hiding is a technique about embedding secret message into multimedia, and transports information without causing any distrustful situation. In 2013, Kuo and Wang proposed GEMD (General Exploiting Modification direction). It can effectively achieve the balance of payload and image quality. However, the study of transmission security is slightly inadequate. In order to improve this shortcoming, we will propose a modified method which is used 1bit of pixel group to keep the channel safely or not in this paper. In other words, if it is an unsafe channel, the sender uses the encrypted key to encrypt secret message, in order to avoid other stealing or tampering message. The simulation results are effective about transmission security, moreover, payload and PSNR are 1bpp and 50 dB, respectively.

关键词： Data hiding EMD GEMD

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Morphology of proliferating epithelial cellular tissue

arXiv

引用

arXiv 2018年

作者： Madhikar, Pranav Åström, Jan Baumeier, Björn Karttunen, Mikko Department of Mathematics and Computer Science Institute for Complex Molecular Systems Eindhoven University of Technology Eindhoven5600 MB Netherlands CSC Scientific Computing Ltd Kägelstranden 14 Esbo02150 Finland Department of Chemistry Department of Applied Mathematics Western University 1151 Richmond Street LondonONN6A 5B7 Canada

We investigate morphologies of proliferating cellular tissue using a newly developed numerical simulation model for mechanical cell division. The model reproduces structures of simple multi-cellular organisms via simple rules for selective division and division plane orientation. The model is applied to a bimodal mixture of stiff cells with a low growth potential and soft cells with a high growth potential. In an even mixture, the soft cells develop into a tissue matrix and the stiff cells into a dendrite-like network structure. For soft cell inclusion in a stiff cellular matrix, the soft cells develop to a fast growing tumour like structure that gradually evacuates the stiff cell matrix. With increasing inter-cell friction, the tumour growth slows down and parts of it is driven to self-inflicted cell death. Copyright © 2018, The Authors. All rights reserved.

关键词： Mixtures

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Overview of KAGRA: Detector design and construction history

arXiv

引用

arXiv 2020年

作者： Akutsu, T. Ando, M. Arai, K. Arai, Y. Araki, S. Araya, A. Aritomi, N. Aso, Y. Bae, S. Bae, Y. Baiotti, L. Bajpai, R. Barton, M.A. Cannon, K. Capocasa, E. Chan, M. Chen, C. Chen, K. Chen, Y. Chu, H. Chu, Y.-K. Eguchi, S. Enomoto, Y. Flaminio, R. Fujii, Y. Fukunaga, M. Fukushima, M. Ge, G. Hagiwara, A. Haino, S. Hasegawa, K. Hayakawa, H. Hayama, K. Himemoto, Y. Hiranuma, Y. Hirata, N. Hirose, E. Hong, Z. Hsieh, B.H. Huang, C.-Z. Huang, P. Huang, Y. Ikenoue, B. Imam, S. Inayoshi, K. Inoue, Y. Ioka, K. Itoh, Y. Izumi, K. Jung, K. Jung, P. Kajita, T. Kamiizumi, M. Kanda, N. Kang, G. Kawaguchi, K. Kawai, N. Kawasaki, T. Kim, C. Kim, J.C. Kim, W.S. Kim, Y.-M. Kimura, N. Kita, N. Kitazawa, H. Kojima, Y. Kokeyama, K. Komori, K. Kong, A.K.H. Kotake, K. Kozakai, C. Kozu, R. Kumar, R. Kume, J. Kuo, C. Kuo, H.-S. Kuroyanagi, S. Kusayanagi, K. Kwak, K. Lee, H.K. Lee, H.W. Lee, R. Leonardi, M. Lin, C. Lin, C.-Y. Lin, F.-L. Liu, G.C. Luo, L. Marchio, M. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, A. Miyazaki, Y. Miyo, K. Miyoki, S. Morisaki, S. Moriwaki, Y. Nagano, K. Nagano, S. Nakamura, K. Nakano, H. Nakano, M. Nakashima, R. Narikawa, T. Negishi, R. Ni, W.-T. Nishizawa, A. Obuchi, Y. Ogaki, W. Oh, J.J. Oh, S.H. Ohashi, M. Ohishi, N. Ohkawa, M. Okutomi, K. Oohara, K. Ooi, C.P. Oshino, S. Pan, K. Pang, H. Park, J. Peña Arellano, F.E. Pinto, I. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sakuno, Y. Sato, S. Sato, T. Sawada, T. Sekiguchi, T. Sekiguchi, Y. Shibagaki, S. Shimizu, R. Shimoda, T. Shimode, K. Shinkai, H. Shishido, T. Shoda, A. Somiya, K. Son, E.J. Sotani, H. Sugimoto, R. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takamori, A. Takano, S. Takeda, H. Takeda, M. Tanaka, H. Tanaka, K. Tanaka, K. Tanaka, T. Tanaka, T. Tanioka, S. Tapia San Martin, E.N. Telada, S. Tomaru, T. Tomigami, Y. Tomura, T. Mitaka City Tokyo181-8588 Japan Japan Department of Physics University of Tokyo Bunkyo-ku Tokyo113-0033 Japan University of Tokyo Bunkyo-ku Tokyo113-0033 Japan KAGRA Observatory University of Tokyo Kashiwa City Chiba277-8582 Japan Tsukuba City Ibaraki305-0801 Japan Earthquake Research Institute University of Tokyo Bunkyo-ku Tokyo113-0032 Japan Kamioka-cho Hida City Gifu506-1205 Japan Mitaka City Tokyo181-8588 Japan Yuseong-gu Daejeon34141 Korea Republic of National Institute for Mathematical Sciences Daejeon34047 Korea Republic of Department of Earth and Space Science Graduate School of Science Osaka University Toyonaka City Osaka560-0043 Japan Tsukuba City Ibaraki305-0801 Japan Department of Applied Physics Fukuoka University Jonan Fukuoka City Fukuoka814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City25137 Taiwan Department of Physics and Institute of Astronomy National Tsing Hua University Hsinchu30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City32001 Taiwan Institute of Physics Academia Sinica Nankang Taipei11529 Taiwan Université Savoie Mont Blanc CNRS/IN2P3 AnnecyF-74941 France Department of Astronomy University of Tokyo Mitaka City Tokyo181-8588 Japan Chinese Academy of Sciences Xiaohongshan Wuhan430071 China Tsukuba City Ibaraki305-0801 Japan KAGRA Observatory University of Tokyo Kamioka-cho Hida City Gifu506-1205 Japan College of Industrial Technology Nihon University Narashino City Chiba275-8575 Japan Graduate School of Science and Technology Niigata University Nishi-ku Niigata City Niigata950-2181 Japan Department of Physics National Taiwan Normal University sec. 4 Taipei116 Taiwan University of Tokyo Kashiwa City Chiba277-8582 Japan Kavli Institute for Astronomy and Astrophysics Peking University China Kyoto University Sakyou-ku Kyot

KAGRA is a newly built gravitational-wave telescope, a laser interferometer comprising arms with a length of 3 km, located in Kamioka, Gifu, Japan. KAGRA was constructed under the ground and it is operated using cryogenic mirrors that help in reducing the seismic and thermal noise. Both technologies are expected to provide directions for the future of gravitational-wave telescopes. In 2019, KAGRA finished all installations with the designed configuration, which we call the baseline KAGRA. In this occasion, we present an overview of the baseline KAGRA from various viewpoints in a series of of articles. In this article, we introduce the design configurations of KAGRA with its historical background. Copyright © 2020, The Authors. All rights reserved.

关键词： Laser interferometry

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Overview of KAGRA : Data transfer and management

引用

Progress of Theoretical and Experimental Physics 2023年第10期2023卷

作者： Akutsu, T Ando, M Arai, K Arai, Y Araki, S Araya, A Aritomi, N Asada, H Aso, Y Bae, S Bae, Y Baiotti, L Bajpai, R Barton, M A Cannon, K Cao, Z Capocasa, E Chan, M Chen, C Chen, K Chen, Y Chiang, C-Y Chu, H Chu, Y-K Eguchi, S Enomoto, Y Flaminio, R Fujii, Y Fujikawa, Y Fukunaga, M Fukushima, M Gao, D Ge, G Ha, S Hagiwara, A Haino, S Han, W-B Hasegawa, K Hattori, K Hayakawa, H Hayama, K Himemoto, Y Hiranuma, Y Hirata, N Hirose, E Hong, Z Hsieh, B Huang, G-Z Huang, H-Y Huang, P Huang, Y-C Huang, Y Hui, D C Y Ide, S Ikenoue, B Imam, S Inayoshi, K Inoue, Y Ioka, K Ito, K Itoh, Y Izumi, K Jeon, C Jin, H-B Jung, K Jung, P Kaihotsu, K Kajita, T Kakizaki, M Kamiizumi, M Kanda, N Kang, G Kawaguchi, K Kawai, N Kawasaki, T Kim, C Kim, J Kim, J C Kim, W S Kim, Y-M Kimura, N Kita, N Kitazawa, H Kobayashi, Y Kojima, Y Kokeyama, K Komori, K Kong, A K H Kotake, K Kozakai, C Kozu, R Kumar, R Kume, J Kuo, C Kuo, H-S Kuromiya, Y Kuroyanagi, S Kusayanagi, K Kwak, K Lee, H K Lee, H W Lee, R Leonardi, M Li, K L Lin, L C-C Lin, C-Y Lin, F-K Lin, F-L Lin, H L Liu, G C Luo, L-W Majorana, E Marchio, M Michimura, Y Mio, N Miyakawa, O Miyamoto, A Miyazaki, Y Miyo, K Miyoki, S Mori, Y Morisaki, S Moriwaki, Y Nagano, K Nagano, S Nakamura, K Nakano, H Nakano, M Nakashima, R Nakayama, Y Narikawa, T Naticchioni, L Negishi, R Quynh, L Nguyen Ni, W-T Nishizawa, A Nozaki, S Obuchi, Y Ogaki, W Oh, J J Oh, K Oh, S H Ohashi, M Ohashi, T Ohishi, N Ohkawa, M Ohta, H Okutani, Y Okutomi, K Oohara, K Ooi, C Oshino, S Otabe, S Pan, K Pang, H Parisi, A Park, J Arellano, F E Peña Pinto, I Sago, N Saito, S Saito, Y Sakai, K Sakai, Y Sakuno, Y Sasaki, Y Sato, S Sato, T Sawada, T Sekiguchi, T Sekiguchi, Y Shao, L Shibagaki, S Shimizu, R Shimoda, T Shimode, K Shinkai, H Shishido, T Shoda, A Somiya, K Son, E J Sotani, H Sugimoto, R Suresh, J Suzuki, T Tagoshi, H Takahashi, H Takahashi, R Takamori, A Takano, S Takeda, H Takeda, M Tanaka, H Tanaka, K Tanaka, T Tanioka, S Martin, E N Tapia San Telada, S Tomaru, T Tomigami, Y Tomura, T Travasso, F Trozzo, L Tsang, T Ts Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research (ICRR) KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Hirosaki University 3 Bunkyo-cho Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) 245 Daehak-ro Yuseong-gu Daejeon 34141 Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University No. 19 Xinjiekou Street Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Rd. Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy Nation

KAGRA is a newly built gravitational wave observatory, a laser interferometer with a 3 km arm length, located in Kamioka, Gifu prefecture, Japan. In this article, we describe the KAGRA data management system, i.e., recording of data, transfer from the KAGRA experiment site to computing resources, as well as data distribution to tier sites, including international sites in Taiwan and Korea. The amount of KAGRA data exceeded 1.0 PiB and increased by about 1.5 TB per day during operation in 2020. Our system has succeeded in data management, and has achieved performance that can withstand observations after 2023, that is, a transfer rate of 20 MB s-1or more and file storage of sufficient capacity for petabyte class. We also discuss the sharing of data between the global gravitational-wave detector network with other experiments, namely LIGO and Virgo. The latency, which consists of calculation of calibrated strain data and transfer time within the global network, is very important from the view of multi-messenger astronomy using gravitational waves. Real-time calbrated data delivered from the KAGRA detector site and other detectors to our computing system arrive with about 4–15 seconds of latency. These latencies are sufficiently short compared to the time taken for gravitational wave event search computations. We also established a high-latency exchange of offline calibrated data that was aggregated with a better accuracy compared with real-time data.

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Benefits from using mixed precision computations in the ELPA-AEO and ESSEX-II eigensolver projects

arXiv

引用

arXiv 2018年

作者： Alvermann, Andreas Basermann, Achim Bungartz, Hans-Joachim Carbogno, Christian Ernst, Dominik Fehske, Holger Futamura, Yasunori Galgon, Martin Hager, Georg Huber, Sarah Huckle, Thomas Ida, Akihiro Imakura, Akira Kawai, Masatoshi Köcher, Simone Kreutzer, Moritz Kus, Pavel Lang, Bruno Lederer, Hermann Manin, Valeriy Marek, Andreas Nakajima, Kengo Nemec, Lydia Reuter, Karsten Rippl, Michael Röhrig-Zöllner, Melven Sakurai, Tetsuya Scheffler, Matthias Scheurer, Christoph Shahzad, Faisal Brambila, Danilo Simoes Thies, Jonas Wellein, Gerhard University of Greifswald Institute of Physics Köln Germany Technical University of Munich Department of Informatics Fritz Haber Institute of the Max Planck Society Berlin Germany University of Erlangen-Nuremberg High Performance Computing University of Tsukuba Applied Mathematics University of Wuppertal Mathematics and Natural Sciences University of Tokyo Computer Science Technical University of Munich Department of Theoretical Chemistry Max Planck Computing and Data Facility Garching Germany

We first briefly report on the status and recent achievements of the ELPA-AEO (Eigenvalue Solvers for Petaflop Applications - Algorithmic Extensions and Optimizations) and ESSEX II (Equipping Sparse Solvers for Exascale) projects. In both collaboratory efforts, scientists from the application areas, mathematicians, and computer scientists work together to develop and make available efficient highly parallel methods for the solution of eigenvalue problems. Then we focus on a topic addressed in both projects, the use of mixed precision computations to enhance efficiency. We give a more detailed description of our approaches for benefiting from either lower or higher precision in three selected contexts and of the results thus obtained. Copyright © 2018, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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Green wave-based virtual traffic light management scheme with VANETs

Green wave-based virtual traffic light management scheme wit...

引用

作者： Chou, Li-Der Shen, Tsung-Yi Tseng, Chia-Wei Chang, Yao-Jen Kuo, Yen-Wei Department of Computer Science and Information Engineering National Central University Taoyuan32001 Taiwan National Center for High-performance Computing National Applied Research Laboratories Hsinchu30076 Taiwan Department of Electronic Engineering Chung Yuan Christian University Taoyuan32023 Taiwan

Green intelligent transportation systems (GITS) have received significant attention in recent years. Traffic congestion, which is an important research topic on intelligent transportation systems (ITS), is rapidly becoming one of the most serious problems affecting urban areas. This study utilises the vehicular ad hoc networks (VANETs) technology to build a virtual traffic light (VTL) environment to reduce traffic congestion. The objective of this study is to adjust the traffic light signal time length on-demand to enable vehicles to pass through numerous intersections rapidly, thereby saving energy and reducing fuel consumption. The traffic phase combination algorithm and VTL operation mechanism are also addressed to improve the traffic congestion situation in urban areas. Simulation results indicate that the proposed scheme can increase the percentage of traffic flow and the average speed of all vehicles in all intersections, thereby saving energy. Copyright © 2017 Inderscience Enterprises Ltd.

关键词： Vehicular ad hoc networks

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