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A Decade of Soft Computing Approaches in Power System Investment Planning

Journal of Physics: Conference Series 2021年第1期1878卷

作者： S B Yaakob A S F Rahman N M Mukhtar M N Yaakob N Arbaiy P-C Lin Control System Group (CSG) Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Kampus Alam UniMAP Pauh Putra 02600 Arau Perlis Malaysia Institut Pendidikan Guru Malaysia Kampus Darul Aman Bandar Darul Aman Kedah 06000 Jitra Kedah Malaysia Faculty of Computer Science and Information Technology University Tun Hussein Onn Malaysia 86400 Batu Pahat Johor Malaysia Department of Information Engineering and Computer Science Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan

This paper opens up an issue regarding to power system investment planning. In order to obtain a sustainable electricity supply, the power outage should be minimized. Maintenance cost plays as an essential element in investment planning, therefore misdirect investment should be avoided. Since soft computing can solved this problem, this paper offers a review in solving investment planning problem through such approaches. The main objective of this paper is to examine the concept and findings by the researchers in power system investment planning problem. Besides, this paper will highlight the most relevant contributions and limitations that can be improve in the other research. Finally, this paper will be pointed out some trends in power system investment planning problem.

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Quantum repeaters: From quantum networks to the quantum internet

arXiv

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arXiv 2022年

作者： Azuma, Koji Economou, Sophia E. Elkouss, David Hilaire, Paul Jiang, Liang Lo, Hoi-Kwong Tzitrin, Ilan NTT Basic Research Laboratories NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan NTT Research Center for Theoretical Quantum Physics NTT Corporation 3-1 Morinosato-Wakamiya Kanagawa Atsugi243-0198 Japan Department of Physics Virginia Tech BlacksburgVA24061 United States QuTech Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands Networked Quantum Devices Unit Okinawa Institute of Science and Technology Graduate University Okinawa Japan Quandela SAS 10 Boulevard Thomas Gobert Palaiseau91120 France Pritzker School of Molecular Engineering The University of Chicago ChicagoIL60637 United States Quantum Bridge Technologies Inc. 100 College Street TorontoONM5G 1L5 Canada Department of Physics University of Hong Kong Pokfulam Hong Kong Center for Quantum Information and Quantum Control Department of Physics Department of Electrical & Computer Engineering University of Toronto TorontoM5S 3G4 Canada Department of Physics University of Toronto Toronto Canada

A quantum internet is the holy grail of quantum information processing, enabling the deployment of a broad range of quantum technologies and protocols on a global scale. However, numerous challenges exist before the quantum internet can become a reality. Perhaps the most crucial of these is the realization of a quantum repeater, an essential component in the long-distance transmission of quantum information. As the analog of a classical repeater, extender, or booster, the quantum repeater works to overcome loss and noise in the quantum channels comprising a quantum network. Here, we review the conceptual frameworks and architectures for quantum repeaters, as well as the experimental progress towards their realization. We also discuss the various near-term proposals to overcome the limits to the communication rates set by point-to-point quantum communication. Finally, we overview how quantum repeaters fit within the broader challenge of designing and implementing a quantum internet. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum optics

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A data-driven approach to predict daily risk of Clostridium difficile infection at two large academic health centers

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Open Forum Infectious Diseases 2017年第SUPPL_1期4卷 S403-S404页

作者： Makar, Maggie Oh, Jeeheh Fusco, Christopher Marchesani, Joseph McCaffrey, Robert Rao, Krishna Ryan, Erin E Washer, Laraine West, Lauren R Young, Vincent B Guttag, John Hooper, David C Shenoy, Erica S Wiens, Jenna Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge Massachusetts Computer Science and Engineering University of Michigan Ann Arbor Michigan Information Systems Partners HealthCare Boston Massachusetts Department of Internal Medicine Division of Infectious Diseases University of Michigan Medical School Ann Arbor Michigan Division of Infectious Diseases Massachusetts General Hospital Boston Massachusetts Infection Control Unit Massachusetts General Hospital Boston Massachusetts Harvard Medical School Boston Massachusetts Department of Medicine Division of Infectious Diseases Massachusetts General Hospital Boston Massachusetts Medical Practice Evaluation Center Department of Medicine Massachusetts General Hospital Boston Massachusetts

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Asymmetric P300 features in Alzheimer's disease may be related to cognitive decline – An EEG study

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IBRO Reports 2019年 6卷 S435-S435页

作者： Eunpyo Kim Sehyeon Jang Jeonghwan Gwak Kyu Yeong Choi Byeong C. Kim Jong-In Song Kun Ho Lee Sung Chan Jun School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju Republic of Korea Biomedical Research Institute & Department of Radiology Seoul National University Hospital (SNUH) Seoul Republic of Korea National Research Center for Dementia Chosun University Gwangju Republic of Korea Department of Biomedical Science Chosun University Gwangju Republic of Korea Department of Neurology Chonnam National University Medical School Gwangju Republic of Korea BK21-plus Research Team for Bioactive Control Technology Chosun University Gwangju Republic of Korea

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Correction to: Development and clinical validation of inertial sensor-based gait-clustering methods in Parkinson's disease

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Journal of neuroengineering and rehabilitation 2019年第1期16卷 98页

作者： An Nguyen Nils Roth Nooshin Haji Ghassemi Julius Hannink Thomas Seel Jochen Klucken Heiko Gassner Bjoern M Eskofier Machine Learning and Data Analytics Lab Department of Computer Science Friedrich-Alexander-University Erlangen-Nürnberg (FAU) Carl-Thiersch-Straße 2b 91052 Erlangen Germany. an.nguyen@fau.de. Machine Learning and Data Analytics Lab Department of Computer Science Friedrich-Alexander-University Erlangen-Nürnberg (FAU) Carl-Thiersch-Straße 2b 91052 Erlangen Germany. Control Systems Group Department of Electrical Engineering and Computer Science Technische Universität Berlin (TUB) Einsteinufer 17 10587 Berlin Germany. Department of Molecular Neurology University Hospital Erlangen Friedrich-Alexander University Erlangen-Nürnberg (FAU) Schwabachanlage 6 91054 Erlangen Germany.

The original article [1] contained an error whereby Fig. 6 contained a minor shading glitch affecting its presentation. This has now been corrected.

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THE NAVAL SHIP RESEARCH AND DEVELOPMENT CENTER ADVANCED STRUCTURE FACILITYxs

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Naval Engineers Journal 1973年第1期85卷 43-49页

作者： BECKER, LOUIS A. SIEGRIST, FRANKLIN I. Louis A. Becker was born in New Rochelle N.Y. in 1930 receiving his earlier education in the New Rochelle Public Schools. He completed his undergraduate studies at Manhattan College in 1952 receiving his BCE degree during which time he was also engaged in land surveying. Following this he did postgraduate study at Virginia Polytechnic Institute obtaining his MS in 1954. He joined Naval Ship Research and Development Center in 1953 as a Junior Engineer and is currently the Head of the Engineering & Facilities Division Structures Department. His field of specialization is Structural Research and Development. Franklin I. Siegrist was born in Knoxville Tenn. in 1937 receiving his earlier education in the Public Schools of Erie Pa. He attended Pennsylvania State University graduating in 1962 with a Bachelor of Science degree in Electrical Engineering having prior to that time served four years in the U. S. Navy. He was a Junior Engineer in the AC Spark Plug Division of General Motors from 1962 until 1964 at which time he came to the David Taylor Model Basin as an Electrical Engineer in the Industrial Department. He is currently Supervisory Engineer for Electrical and Electronics Engineering Structures Department Naval Ship Research and Development Center. His field of specialization is Electrical Engineering Control Systems Data Collection Systems Computer Applications to Structural Research and Hydraulic System Design. In the last of these he holds Patent Rights on a “Hydraulic Supercharge and Cooling Circuit” granted in 1970.

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Properties of carbide electro-spark coatings after laser processing

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AIP Conference Proceedings 2018年第1期2017卷

作者： Norbert Radek Izabela Pliszka Aneta Gądek-Moszczak Jarosław Rolek Jana Petru 1Kielce University of Technology Faculty of Mechatronics and Mechanical Engineering Al. 1000-lecia Państwa Polskiego 7 25-314 Kielce Poland 2Cracow University of Technology Institute of Applied Informatics Faculty of Mechanical Engineering Al. Jana Pawła II 37 31-864 Cracow Poland 3Kielce University of Technology Faculty of Electrical Engineering Automatic Control and Computer Science Al. 1000-lecia Państwa Polskiego 7 25-314 Kielce Poland 4VSB-TU Ostrava Faculty of Mechanical Engineering Department of Machining Assembly and Engineering Metrology 17. listopadu 15/2172 70833 Ostrava-Poruba Czech Republic

The aim of the study was to determine the influence of the laser processing on the properties of electro-spark coatings. The properties were assessed by analyzing the coating microstructure, X-ray radiation, microhardness, corrosion resistance, porosity and tribological tests. In addition, the paper presents the results of measurements and analysis of electrical pulse during ESD. The tests were carried out on WC-Cu coating (the anode) obtained by electro spark deposition over carbon steel C45 (the cathode) and molten with a laser beam. The coatings were deposited by means of the EIL-8A and they were laser treated with the Nd:YAG. The tests show that the laser-treated electro-spark deposited WC-Cu coatings are characterized by lower hardness and friction force, higher seizure resistance, roughness. The laser treatment process causes the homogenization of the chemical composition, the structure refinement and the healing of microcracks and pores of the electro-spark deposited coatings. Laser treated electro-spark deposited coatings are likely to be applied in sliding friction pairs and as protective coatings.

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3D Mesostructures: Fabrication and Deformation of 3D Multilayered Kirigami Microstructures (Small 11/2018)

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Small 2018年第11期14卷

作者： Mohammad Humood Yan Shi Mengdi Han Joseph Lefebvre Zheng Yan Matt Pharr Yihui Zhang Yonggang Huang John A. Rogers Andreas A. Polycarpou Department of Mechanical Engineering College of Engineering Texas A&M University College Station TX 77843-3123 USA State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Nanjing 210016 P. R. China Center for Mechanics and Materials and Center for Flexible Electronics Technology AML Department of Engineering Mechanics Tsinghua University Beijing 100084 P. R. China Department of Materials Science and Engineering Fredrick Seitz Materials Research Laboratory University of Illinois at Urbana-Champaign Urbana IL 61801 USA Bruker Nano Surfaces Eden Prairie MN 55344 USA Department of Chemical Engineering and Department of Mechanical and Aerospace Engineering University of Missouri Columbia MI 65211 USA Departments of Mechanical Engineering and Civil and Environmental Engineering Northwestern University Evanston IL 60208 USA Department of Biomedical Engineering Department of Chemistry Department of Mechanical Engineering Department of Electrical Engineering and Department of Computer Science Center for Bio-Integrated Electronics Simpson Querrey Institute for Nano/Biotechnology Northwestern University Evanston IL 60208 USA

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The status of KAGRA underground cryogenic gravitational wave telescope

arXiv

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arXiv 2017年

作者： Akutsu, T. Ando, M. Araya, A. Aritomi, N. Asada, H. Aso, Y. Atsuta, S. Awai, K. Barton, M.A. Cannon, K. Craig, K. Creus, W. Doi, K. Eda, K. Enomoto, Y. Flaminio, R. Fujii, Y. Fujimoto, M.-K. Furuhata, T. Haino, S. Hasegawa, K. Hashino, K. Hayama, K. Hirobayashi, S. Hirose, E. Hsieh, B.H. Inoue, Y. Ioka, K. Itoh, Y. Kaji, T. Kajita, T. Kakizaki, M. Kamiizumi, M. Kambara, S. Kanda, N. Kanemura, S. Kaneyama, M. Kang, G. Kasuya, J. Kataoka, Y. Kawai, N. Kawamura, S. Kim, C. Kim, H. Kim, J. Kim, Y. Kimura, N. Kinugawa, T. Kirii, S. Kitaoka, Y. Kojima, Y. Kokeyama, K. Komori, K. Kotake, K. Kumar, R. Lee, H. Lee, H. Liu, Y. Luca, N. Majorana, E. Mano, S. Marchio, M. Matsui, T. Matsushima, F. Michimura, Y. Miyakawa, O. Miyamoto, T. Miyamoto, A. Miyo, K. Miyoki, S. Morii, W. Morisaki, S. Moriwaki, Y. Morozumi, T. Musha, M. Nagano, S. Nagano, K. Nakamura, K. Nakamura, T. Nakano, H. Nakano, M. Nakao, K. Narikawa, T. Nguyen Quynh, L. Ni, W.-T. Ochi, T. Oh, J. Oh, S. Ohashi, M. Ohishi, N. Ohkawa, M. Okutomi, K. Oohara, K. Peña Alleano, F.E. Pinto, I. Sago, N. Saijo, M. Saito, Y. Sakai, K. Sakai, Y. Sasaki, Y. Sasaki, M. Sato, S. Sato, T. Sekiguchi, Y. Seto, N. Shibata, M. Shimoda, T. Shinkai, H. Shoda, A. Somiya, K. Son, E. Suemasa, A. Suzuki, T. Suzuki, T. Tagoshi, H. Takahashi, H. Takahashi, R. Takamori, A. Takeda, H. Tanaka, H. Tanaka, K. Tanaka, T. Tatsumi, D. Tomaru, T. Tomura, T. Travasso, F. Tsubono, K. Tsuchida, S. Uchikata, N. Uchiyama, T. Uehara, T. Ueki, S. Ueno, K. Ushiba, T. van Putten, M.H.P.M. Vocca, H. Wada, S. Wakamatsu, T. Yamada, T. Yamamoto, S. Yamamoto, T. Yamamoto, K. Yamamoto, A. Yokoyama, J. Yokozawa, T. Yoon, T.H. Yuzurihara, H. Zeidler, S. Zhu, Z.-H. National Astronomical Observatory of Japan Mitaka Tokyo181-8588 Japan Department of Physics University of Tokyo Bunkyo Tokyo113-0033 Japan Earthquake Research Institute University of Tokyo Bunkyo Tokyo113-0032 Japan Department of Advanced Physics Hirosaki University Hirosaki Aomori036-8561 Japan National Astronomical Observatory of Japan Hida Gifu506-1205 Japan Department of Physics Tokyo Institute of Technology Meguro Tokyo152-8551 Japan Institute for Cosmic Ray Research University of Tokyo Hida Gifu506-1205 Japan Research Center for the Early Universe University of Tokyo Bunkyo Tokyo113-0033 Japan Institute for Cosmic Ray Research University of Tokyo Kashiwa Chiba277-8582 Japan Institute of Physics Academia Sinica Nankang Taipei11529 Taiwan Department of Physics University of Toyama Toyama Toyama930-8555 Japan Faculty of Engineering University of Toyama Toyama Toyama930-8555 Japan Yukawa Institute for Theoretical Physics Kyoto University Sakyo Kyoto606-8502 Japan Department of Physics Osaka City University Sumiyosi Osaka558-8585 Japan Department of Physics Osaka University Toyonaka Osaka560-0043 Japan Korea Institute of Science and Technology Information Yuseong Daejeon34141 Korea Republic of Daejeon Yuseong34055 Korea Republic of National Institute for Mathematical Sciences Daejeon34047 Korea Republic of Department of Computer Simulation Inje University Gimhae Gyeongsangnam50834 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul151-742 Korea Republic of High Energy Accelerator Research Organization Tsukuba Ibaraki305-0801 Japan Department of Physical Science Hiroshima University Higashihiroshima Hiroshima903-0213 Japan Department of Applied Physics Fukuoka University Jonan Fukuoka814-0180 Japan Department of Advanced Materials Science University of Tokyo Kashiwa Chiba277-8582 Japan Istituto Nazionale di Fisica Nucleare Sapienza University Roma00185 Italy D

KAGRA is a 3-km interferometric gravitational wave telescope located in the Kamioka mine in Japan. It is the first km-class gravitational wave telescope constructed underground to reduce seismic noise, and the first km-class telescope to use cryogenic cooling of test masses to reduce thermal noise. The construction of the infrastructure to house the interferometer in the tunnel, and the initial phase operation of the interferometer with a simple 3-km Michelson configuration have been completed. The first cryogenic operation is expected in 2018, and the observing runs with a full interferometer are expected in 2020s. The basic interferometer configuration and the current status of KAGRA are described. Copyright © 2017, The Authors. All rights reserved.

关键词： Interferometers

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End to End Multitask Joint Learning Model for Osteoporosis Classification in CT Images

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Computational intelligence and neuroscience 2023年第1期2023卷 3018320页

作者： Kun Zhang Pengcheng Lin Jing Pan Peixia Xu Xuechen Qiu Danny Crookes Liang Hua Lin Wang School of Electrical Engineering Nantong University Nantong Jiangsu 226001 China. Nantong Key Laboratory of Intelligent Control and Intelligent Computing Nantong Jiangsu 226001 China. Nantong Key Laboratory of Intelligent Medicine Innovation and Transformation Nantong Jiangsu 226001 China. Department of Radiology Affiliated Hospital 2 of Nantong University Nantong Jiangsu 226001 China. College of Mechanical Engineering Donghua University Shanghai 201620 China. School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast BT7 1NN UK.

Osteoporosis is a significant global health concern that can be difficult to detect early due to a lack of symptoms. At present, the examination of osteoporosis depends mainly on methods containing dual-energyX-ray, quantitative CT, etc., which are high costs in terms of equipment and human time. Therefore, a more efficient and economical method is urgently needed for diagnosing osteoporosis. With the development of deep learning, automatic diagnosis models for various diseases have been proposed. However, the establishment of these models generally requires images with only lesion areas, and annotating the lesion areas is time-consuming. To address this challenge, we propose a joint learning framework for osteoporosis diagnosis that combines localization, segmentation, and classification to enhance diagnostic accuracy. Our method includes a boundary heat map regression branch for thinning segmentation and a gated convolution module for adjusting context features in the classification module. We also integrate segmentation and classification features and propose a feature fusion module to adjust the weight of different levels of vertebrae. We trained our model on a self-built dataset and achieved an overall accuracy rate of 93.3% for the three label categories (normal, osteopenia, and osteoporosis) in the testing datasets. The area under the curve for the normal category is 0.973; for the osteopenia category, it is 0.965; and for the osteoporosis category, it is 0.985. Our method provides a promising alternative for the diagnosis of osteoporosis at present.

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