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4th International Conference on Internet of Things and Smart City, IoTSC 2024

作者： Li, Shuai Yao, Zhonghao Chen, Shengbo Schoool of Software Henan University Henan Kaifeng China School of Computer Science & Technology Beijing Institute of Technology Beijing China School of Computer and Information Engineering Henan University Henan Kaifeng China Henan Engineering Research Center of Intelligent Technology and Application Henan University Henan Kaifeng China

ISBN: (纸本)9781510681767

The solar energy harvesting communication system is the basic support layer that is associated with the Internet of Things (IoT). However, the inherent stochasticity of solar energy brings about extensive research on energy allocation in the system. In this paper, we propose an energy allocation algorithm for maximizing the data transfer (MDT) of a solar energy harvesting communication system while jointly considering the practical constraints of battery capacity and link capacity restrictions. We can solve it through the convex optimization problem, but the solution is extremely complicated. This complexity is the result of the coupling of energy allocation problems caused by restricted battery capacity and link capacity. To simplify the solution process, we propose a decoupled energy allocation (DEA) algorithm. Simulation experiments are conducted through real energy harvesting data sets, and the results show that DEA outperforms the other two heuristic schemes. © 2024 SPIE.

关键词： Convex optimization

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Clustering Dynamic Networks by Discriminating Roles of Vertices and Capturing Temporality with Subsequent Feature Projection

SSRN

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SSRN 2024年

作者： Ma, Yaxiong Gao, Yue Dou, Zengfa Huang, Guohua Ma, Xiaoke School of Computer Science and Technology Xidian University Shaanxi Xi’an710071 China School of Information Engineering Xian University Shaanxi Xi’an710065 China Schoool of Computer and Information Science Qinghai Institute of Technology Qinghai Xining810016 China School of Information Technology and Administration Hunan University of Finance and Economics Hunan Changsha410215 China

Clustering dynamic networks is becoming more and more popular since many complex systems in nature and society are dynamic which cannot be fully characterized by the traditional static ones. It is highly non-trivial in comparison to clustering static network since it requires simultaneously to balance clustering accuracy and clustering drift, where clustering accuracy measures how clustering reflects structure of graph at current time, and clustering drift quantifies how clustering smoothes historical snapshot(s). In this study, we propose an algorithm \underline{\textbf{c}}lustering \underline{\textbf{d}}ynamic \underline{\textbf{n}}etwork by \textbf{\underline{d}}iscriminating \textbf{\underline{r}}oles of vertices and \underline{\textbf{c}}apturing \underline{\textbf{t}}emporality with subsequent feature projection (\textbf{CDN-DRCT}). Specifically, clustering accuracy is achieved by factorizing high-order matrix of slice at current time, and vertices are divided into static and dynamic ones by the reconstruction errors. Finally, the proposed algorithm measures temporality of networks with a projection matrix, which connects subsequent features at the previous and current time, thereby enhancing clustering drift of clusters. In this case, temporality of dynamic networks is characterized from vertex and global level, providing a better way to balance clustering accuracy and clustering drift. Experimental results on 10 typical dynamic networks demonstrate the proposed algorithm is superior to baselines in terms of accuracy as well efficiency. © 2024, The Authors. All rights reserved.

关键词： Non-negative matrix factorization

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Vibration isolation system with a compact damping system for power recycling mirrors of KAGRA

arXiv

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arXiv 2019年

作者： Akiyama, Y. Akutsu, T. Ando, M. Arai, K. Arai, Y. Araki, S. Araya, A. Aritomi, N. Asada, H. Aso, Y. Bae, S. Baiotti, L. Barton, M.A. Cannon, K. Capocasa, E. Chen, C.-S. Chiu, T.-W. Cho, K. Chu, Y.-K. Craig, K. Dattilo, V. Doi, K. Enomoto, Y. Flaminio, R. Fujii, Y. Fujimoto, M.-K. Fukunaga, M. Fukushima, M. Furuhata, T. Haino, S. Hasegawa, K. Hashimoto, Y. Hashino, K. Hayama, K. Hirayama, T. Hirose, E. Hsieh, B.H. Huang, C.-Z. Ikenoue, B. Inoue, Y. Ioka, K. Itoh, Y. Izumi, K. Kaji, T. Kajita, T. Kakizaki, M. Kamiizumi, M. Kanbara, S. Kanda, N. Kanemura, S. Kang, G. Kasuya, J. Kawai, N. Kawasaki, T. Kim, C. Kim, W.S. Kim, J. Kim, J.C. Kimura, N. Kirii, S. Kitaoka, Y. Kitazawa, H. Kojima, Y. Kokeyama, K. Komori, K. Kong, A. Kotake, K. Kozu, R. Kumar, R. Kuo, H.-S. Kuroki, S. Kuroyanagi, S. Lee, H.K. Lee, H.M. Lee, H.W. Leonardi, M. Lin, C.-Y. Lin, F.-L. Liu, G.C. Marchio, M. Matsui, T. Michimura, Y. Mio, N. Miyakawa, O. Miyamoto, A. Miyoki, S. Morii, W. Morisaki, S. Moriwaki, Y. Musha, M. Nagano, S. Nagano, K. Nakamura, K. Nakamura, T. Nakano, H. Nakano, M. Narikawa, T. Quynh, L. Nguyen Ni, W.-T. Nishizawa, A. Obuchi, Y. Oh, J. Oh, S.H. Ohashi, M. Ohishi, N. Ohkawa, M. Okutomi, K. Ono, K. Oohara, K. Ooi, C.P. Pan, S.-S. Paoletti, F. Park, J. Passaquieti, R. Peña Arellano, F.E. Sago, N. Saito, S. Saito, Y. Sakai, K. Sakai, Y. Sasai, M. Sato, S. Sato, T. Sekiguchi, T. Sekiguchi, Y. Shibata, M. Shimoda, T. Shinkai, H. Shishido, T. Shoda, A. Someya, N. Somiya, K. Son, E.J. Suemasa, A. Suzuki, T. Suzuki, T. Tagoshi, H. Tahara, H. Takahashi, H. Takahashi, R. Takeda, H. Tanaka, H. Tanaka, K. Tanaka, T. Tanioka, S. San Martin, E.N. Tapia Tomaru, T. Tomura, T. Travasso, F. Tsubono, K. Tsuchida, S. Uchikata, N. Uchiyama, T. Uehara, T. Ueno, K. Uraguchi, F. Ushiba, T. van Putten, M.H.P.M. Vocca, H. Wakamatsu, T. Watanabe, Y. Xu, W.-R. Yamada, T. Yamamoto, K. Yamamoto, K. Yamamoto, S. Yamamoto, T. Yokogawa, K. Yokoyama, J. Yokozawa, T. Yoshioka, T. Yuzurihara, H. Zeidler, S. Zhu, Z.-H. Graduate School of Science and Engineering Hosei University TokyoKoganei184-8584 Japan National Astronomical Observatory of Japan TokyoMitaka181-8588 Japan Department of Physics University of Tokyo TokyoBunkyo113-0033 Japan University of Tokyo KashiwaChiba277-8582 Japan High Energy Accelerator Research Organization TsukubaIbaraki305-0801 Japan Earthquake Research Institute University of Tokyo TokyoBunkyo113-0032 Japan Department of Physics University of Tokyo TokyoBunkyo113-0033 Japan Department of Mathematics and Physics Hirosaki University AomoriHirosaki036-8561 Japan National Astronomical Observatory of Japan GifuHida506-1205 Japan Korea Institute of Science and Technology Information Yuseong Daejeon34141 Korea Republic of Department of Physics Osaka University ToyonakaOsaka560-0043 Japan University of Tokyo TokyoBunkyo113-0033 Japan Department of Physics National Taiwan Normal University Taipei116 Taiwan Department of Physics Sogang University Seoul121-742 Korea Republic of PisaCascinaI-56021 Italy Department of Physics University of Toyama ToyamaToyama930-8555 Japan Department of Astronomy University of Tokyo TokyoBunkyo113-0032 Japan Advanced Technology Center National Astronomical Observatory of Japan TokyoMitaka181-8588 Japan Institute of Physics Academia Sinica TaipeiNankang11529 Taiwan Department of Applied Physics Fukuoka University FukuokaJonan814-0180 Japan Yukawa Institute for Theoretical Physics Kyoto University KyotoSakyo606-8502 Japan Graduate School of Science Osaka City University OsakaSumiyosi558-8585 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency SagamiharaKanagawa252-5210 Japan University of Tokyo GifuHida506-1205 Japan Graduate Schoool of Science and Technology Tokyo Institute of Technology MeguroTokyo152-8551 Japan Department of Physics Ewha Womans University SeoulSeodaemun-gu03760 Korea Republic of National Institute for

A vibration isolation system called Type-Bp system used for power recycling mirrors has been developed for KAGRA, the interferometric gravitational-wave observatory in Japan. A suspension of the Type-Bp system passively isolates an optic from seismic vibration using three main pendulum stages equipped with two vertical vibration isolation systems. A compact reaction mass around each of the main stages allows for achieving sufficient damping performance with a simple feedback as well as vibration isolation ratio. Three Type-Bp systems were installed in KAGRA, and were proved to satisfy the requirements on the damping performance, and also on estimated residual displacement of the optics. Copyright © 2019, The Authors. All rights reserved.

关键词： Mirrors

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An OPC UA client development for monitoring and control applications

An OPC UA client development for monitoring and control appl...

引用

International Forum on Strategic technology, IFOST

作者： Son Mai Van Tan Vu Myeong-Jae Yi Schoool of Computer Engineering and Information Technology University of Ulsan Korea School of Information and Communication Technology Hanoi University of Science and Technology Vietnam Schoool of Computer Engineering and Information Technology University of Ulsan Ulsan Korea

Classic OPC, released by OPC Foundation, is well accepted and applied in industrial automation, which led to many OPC products on the market from a variety of companies. However, OPC technology was based on retiring Microsoft COM/DCOM. The OPC Unified Architecture was introduced as the new generation specification with the main goal of keeping all the functionality of Classic OPC and switching from COM/DCOM technology to state -of-the-art web services. The OPC Foundation has been also developing OPC UA Toolkit that provide a collection of libraries, classes, and interfaces which make developers and programmers easy to create and implement OPC UA components. However, this toolkit is insufficient for developers and programmers to implement real monitoring and control applications from industry due to the limitations of such a toolkit, the complexity of related decision tasks and information systems, etc. In this paper, an OPC UA (Unified Architecture) client framework is proposed and developed by using OPC UA specifications, Service Oriented Architecture (SOA), web services, XML, OPC UA SDK, etc. This framework minimizes the efforts of developers and programmers in learning new techniques and allows system arc hitects and designers to perform dependency analysis on the development of monitoring and control applications. The initial results from the system implemented by Visual Studio 2008 are also provided.

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