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Integration of IOT and control systems for industry 4.0 applications

AIP Conference Proceedings 2023年第1期2477卷

作者： Mohan Sundar Rajan Tilahun Weldcherkos Sher Afghan Khan Maughal Ahmed Ali Baig Chamakura Abhinav Reddy Department of Industrial Control and Instrumentation Faculty of Electrical and Computer Engineering Arbaminch Institute of Technology PO No:21 Arbaminch University Arbaminch Ethiopia Department of Mechanical Faculty of Engineering International Islamic UniversityMalaysia 50728 Kuala Lumpur Department of Mechanical Engineering CMR TechnicalCampus Hyderabad Telangana India Department of Computer Science and Engineering CMR College of Engineering and Technology Hyderabad Telangana India

Modern manufacturing applications such as Industry 4.0 focus on integrated industrial automation and IoT to improve efficiency, quality, and productivity. To establish and implement this new approach, new technologies like IoT, wireless networking control systems (WNCS), and cloud computing are necessary. This paper explains different techniques adopted in control systems applied via IoT, i.e., SCADA, HIL, and explained the PID Plus filter architecture. The Internet of Things (IoT), which enables independent devices to use the internet for data exchange, is a significant recent interest in the communication between machines. The Internet and the WWW have made people’s connections revolutionized. They came from the need to share science amongst industries. Human communications are similar to IoT subjects such as codes, representations, and tools. Various organizations, including start-ups, are currently testing them. The smart city term is also used to define IoT applications such as intelligent parking, jamming, and waste management. There is already a lot of expertise in control systems for extensive testing facilities for connecting thousands of devices, which more and more have a TCP/IP link. This paper examines the potential integration of IoT and control Systems.

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Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses

arXiv

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arXiv 2022年

作者： Majumder, Swarnadeep Yale, Christopher G. Morris, Titus Lobser, Daniel S. Burch, Ashlyn D. Chow, Matthew N.H. Revelle, Melissa C. Clark, Susan M. Pooser, Raphael C. Duke Quantum Center Duke University DurhamNC27701 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Sandia National Laboratories AlbuquerqueNM87123 United States Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Physics and Astronomy University of New Mexico AlbuquerqueNM87131 United States Center for Quantum Information and Control University of New Mexico AlbuquerqueNM87131 United States

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that near term algorithms can be performed with proximate accuracy (like chemical accuracy for quantum chemistry problems). While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware code-sign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations. © 2022, CC BY.

关键词： Testbeds

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Artificial intelligence enabled radio propagation for communications-Part II: Scenario identification and channel modeling

arXiv

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arXiv 2021年

作者： Huang, Chen He, Ruisi Ai, Bo Molisch, Andreas F. Lau, Buon Kiong Haneda, Katsuyuki Liu, Bo Wang, Cheng-Xiang Yang, Mi Oestges, Claude Zhong, Zhangdui The Purple Mountain Laboratories Nanjing211111 China The National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China The State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Key Laboratory of Railway Industry of Broadband Mobile Information Communications Beijing Jiaotong University Beijing100044 China The School of Information Engineering Zhengzhou University Zhengzhou450001 China Peng Cheng Laboratory Shenzhen518055 China The Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States The Department of Electrical and Information Technology Lund University Lund22100 Sweden The Department of Radio Science and Engineering Aalto University Aalto00076 Finland The School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom The Institute of Information and Communication Technologies Electronics and Applied Mathematics Universite Catholique de Louvain Louvain-la-Neuve 1348 Belgium

This two-part paper investigates the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. In Part I, we introduced AI and ML as well as provided a comprehensive survey on ML enabled channel characterization and antenna-channel optimization, and in this part (Part II) we review state-of-the-art literature on scenario identification and channel modeling here. In particular, the key ideas of ML for scenario identification and channel modeling/prediction are presented, and the widely used ML methods for propagation scenario identification and channel modeling and prediction are analyzed and compared. Based on the state-of-art, the future challenges of AI/ML-based channel data processing techniques are given as well. © 2021, CC BY-NC-ND.

关键词： Machine learning

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Modelling 3D magnetic networks in a realistic solar atmosphere

arXiv

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arXiv 2019年

作者： Gent, Frederick A. Snow, Ben Fedun, Viktor Erdélyi, Robertus Academy of Finland ReSoLVE Centre of Excellence Department of Computer Science Aalto University FI-02150 Finland College of Engineering Mathematics and Physical Sciences University of Exeter EX4 4QF United Kingdom School of Mathematics Statistics and Physics Newcastle University NE1 7RU United Kingdom School of Mathematics and Statistics University of Sheffield S3 7RH United Kingdom Plasma Dynamics Group Department of Automatic Control and Systems Engineering University of Sheffield S1 3JD United Kingdom Department of Astronomy Eötvös Loránd University Pázmány Péter sétány 1/A Budapest H-1117 Hungary

The magnetic network extending from the photosphere (solar radius ' R) to lower corona (R + 10 Mm) plays an important role in the heating mechanisms of the solar atmosphere. Here we further develop the models with realistic open magnetic flux tubes of the authors in order to model more complicated configurations. Closed magnetic loops, and combinations of closed and open magnetic flux tubes are modelled. These are embedded within a stratified atmosphere, derived from observationally motivated semi-empirical and data-driven models subject to solar gravity and capable of spanning from the photosphere up into the chromosphere and lower corona. Constructing a magnetic field comprising self-similar magnetic flux tubes, an analytic solution for the kinetic pressure and plasma density is derived. Combining flux tubes of opposite polarity it is possible to create a steady background magnetic field configuration modelling a solar atmosphere exhibiting realistic stratification. The result can be applied to SOHO/MDI and SDO/HMI and other magnetograms from the solar surface, upon which photospheric motions can be simulated to explore the mechanism of energy transport. We demonstrate this powerful and versatile method with an application to Helioseismic and Magnetic Imager data. Copyright © 2019, The Authors. All rights reserved.

关键词： 3D modeling

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Modeling the effects of a lightbridge on oscillations in a solar pore

arXiv

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arXiv 2024年

作者： Schiavo, Luiz A.C.A. Gordovskyy, Mykola Browning, Philippa Silva, Suzana S.A. Verth, Gary Ballai, Istvan Shelyag, Sergiy Ruzheinikov, Sergey N. McLaughlin, James A. Fedun, Viktor Department of Mathematics Physics and Electrical Engineering Northumbria University NewcastleNE1 8ST United Kingdom Centre for Astrophysics Research Department of Physics Astronomy & Mathematics University of Hertfordshire HatfieldAL10 9AB United Kingdom Jodrell Bank Centre for Astrophysics University of Manchester ManchesterM13 9PL United Kingdom Plasma Dynamics Group Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom Plasma Dynamics Group School of Mathematics and Statistics University of Sheffield Hounsfield Road SheffieldS3 7RH United Kingdom College of Science and Engineering Flinders University TonsleySA5042 Australia

Solar pores are ideal magnetic structures for wave propagation and transport of energy radially-outwards across the upper layers of the solar atmosphere. We aim to model the excitation and propagation of magnetohydrodynamic waves in a pore with a lightbridge modelled as two interacting magnetic flux tubes separated by a thin, weaker field, layer. We solve the three-dimensional MHD equations numerically and calculate the circulation as a measure of net torsional motion. We find that the interaction between flux tubes results in the natural excitation of propagating torsional Alfvén waves, but find no torsional waves in the model with a single flux tube. The torsional Alfvén waves propagate with wave speeds matching the local Alfvén speed where wave amplitude peaks. Copyright © 2024, The Authors. All rights reserved.

关键词： Plasma magnetohydrodynamic waves

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Magnetic Tracking: A Facile Magnetic System for Tracking of Medical Devices (Adv. Mater. Technol. 6/2021)

引用

Advanced Materials Technologies 2021年第6期6卷

作者： Liam Swanepoel Nouf Alsharif Alexander Przybysz Pieter Fourie Pierre Goussard Mohammad Asadullah Khan Abdullah Almansouri Jurgen Kosel Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Thuwal Makkah 23955-6900 Saudi Arabia Department of Paediatrics and Child Health Stellenbosch University Stellenbosch Western Cape 7600 South Africa Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield S1 3JD UK Department of Electrical and Electronic Engineering University of Jeddah Jeddah Makkah 21959 Saudi Arabia Department of Sensor Systems Silicon Austria Labs Villach 9524 Austria

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Observation of Integer and Fractional Quantum Anomalous Hall Effects in Twisted Bilayer MoTe2

引用

Physical Review X 2023年第3期13卷 031037-031037页

作者： Fan Xu Zheng Sun Tongtong Jia Chang Liu Cheng Xu Chushan Li Yu Gu Kenji Watanabe Takashi Taniguchi Bingbing Tong Jinfeng Jia Zhiwen Shi Shengwei Jiang Yang Zhang Xiaoxue Liu Tingxin Li Key Laboratory of Artificial Structures and Quantum Control (Ministry of Education) Shenyang National Laboratory for Materials Science School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai 201210 China Department of Physics and Astronomy University of Tennessee Knoxville Tennessee 37996 USA State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics Tsinghua University 100084 Beijing China Research Center for Electronic and Optical Materials National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan Beijing National Laboratory for Condensed Matter Physics and Institute of Physics Chinese Academy of Sciences Beijing 100190 China Hefei National Laboratory Hefei 230088 China Min H. Kao Department of Electrical Engineering and Computer Science University of Tennessee Knoxville Tennessee 37996 USA

The interplay between strong correlations and topology can lead to the emergence of intriguing quantum states of matter. One well-known example is the fractional quantum Hall effect, where exotic electron fluids with fractionally charged excitations form in partially filled Landau levels. The emergence of topological moiré flat bands provides exciting opportunities to realize the lattice analogs of both the integer and fractional quantum Hall effects without the need for an external magnetic field. These effects are known as the integer and fractional quantum anomalous Hall (IQAH and FQAH) effects. Here, we present direct transport evidence of the existence of both IQAH and FQAH effects in small-angle-twisted bilayer MoTe2. At zero magnetic field, we observe well-quantized Hall resistance of h/e2 around moiré filling factor ν=−1 (corresponding to one hole per moiré unit cell), and nearly quantized Hall resistance of 3h/2e2 around ν=−2/3, respectively. Concomitantly, the longitudinal resistance exhibits distinct minima around ν=−1 and −2/3. The application of an electric field induces topological quantum phase transition from the IQAH state to a charge transfer insulator at ν=−1, and from the FQAH state to a topologically trivial correlated insulator, further transitioning to a metallic state at ν=−2/3. Our study paves the way for the investigation of fractionally charged excitations and anyonic statistics at zero magnetic field based on semiconductor moiré materials.

关键词： Magnetism Phase transitions Topological materials

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One-Dimensional EEG Artifact Removal Network Based on Convolutional Neural Networks

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第1期9卷 142-159页

作者： Xiong, Jun Meng, Xiang-Long Chen, Zhao-Qi Wang, Chuan-Sheng Zhang, Fu-Quan Grau, Antoni Chen, Yang Huang, Jing-Wei School of Computer and Data Science Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China College of Electronic Engineering Shandong University of Science and Technology No. 579 Qianwangang Road Huangdao District Qingdao China College of Computer and Big Data Fuzhou University Fuzhou University Town No. 2 Wulongjiang North Road Fuzhou China Department of Automatic Control Technical Polytechnic University of Catalonia Autonomous Region of Catalonia Barcelona Spain Digital Media Art Key Laboratory of Sichuan Province Sichuan Conservatory of Music Fuzhou Technology Innovation Center of intelligent Manufacturing information System Minjiang University Fuzhou University Town No. 200 Xiyuangong Road Fuzhou China Fujian Province University No. 1 Campus New Village Longjiang Street Fuqing China School of Mechanical and Automotive Engineering Fujian University of Technology No. 33 Xuefu South Road University New District Fuzhou China

The electroencephalogram (EEG) serves as a significant tool in the realms of clinical medicine, cerebral investigation, and neurological disorders research. However, the EEG records we obtain are often easily contaminated by various artifacts, which can blur or distort the underlying EEG signals and make data interpretation difficult. Generally speaking, removing EEG artifacts is considered an essential step in brain signal analysis. Therefore, removing artifacts is crucial for obtaining accurate and reliable EEG signals for subsequent analysis. Recently, deep learning techniques have found widespread application across various domains for denoising tasks, including image denoising and EEG denoising. Many advanced algorithms have been developed in image denoising, which has achieved good results in enhancing low-quality images. Moreover, it has shown superior performance in EEG denoising. In contrast, few people have devoted themselves to studying EEG denoising, and existing convolutional neural network EEG denoising methods still have problems of overfitting and poor denoising effect in Electromyograph(EMG) and ElectroOculoGram(EOG) artifact removal. Therefore, this paper proposes a method called DWINet (De-artifacting with Image-based Network for EEG Signals) based on an image dehazing network DRHNet for removing artifacts from EEG signals. Specifically, our approach DWINet, addresses the de-artifacting issue in EEG signals by converting it as an image dehazing problem and utilizes the image dehazing capability of DRHNet to enhance the denoising performance of EEG signals. Experimental results demonstrate that the proposed method outperforms the compared algorithms in removing the ocular artifact in EEG signals and exhibits higher accuracy and robustness. © 2024, J. Network Intell. All rights reserved.

关键词： Image enhancement

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Preface

Lecture Notes in Electrical Engineering

引用

Lecture Notes in electrical engineering 2022年 820卷 v页

作者： Chanda, Chandan Kumar Szymanski, Jerzy R. Sikander, Afzal Mondal, Pranab Kumar Acharjee, Dulal Department of Electrical Engineering Indian Institute of Engineering Science and Technology West Bengal Shibpur India Department of Electrical Drives Kazimierz Pulaski University of Technology and Humanity Radom Poland Instrumentation and Control Engineering Dr. B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Mechanical Engineering Indian Institute of Technology Guwahati Guwahati India Computer Science Applied Computer Technology West Bengal Kolkata India

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The status of KAGRA underground cryogenic gravitational wave telescope 15

The status of KAGRA underground cryogenic gravitational wave...

引用

15th International Conference on Topics in Astroparticle and Underground Physics, TAUP 2017

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, A.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. Quynh, L.Nguyen Ni, W.-T. Ochi, T. Oh, J. Oh, S. Ohashi, M. Ohishi, N. Ohkawa, M. Okutomi, K. Oohara, K. Alleano, F.E.P. 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 Aomori Hirosaki036-8561 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 Chiba Kashiwa277-8582 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 Osaka Toyonaka560-0043 Japan Korea Institute of Science and Technology Information Yuseong Daejeon 34141 Korea Republic of Yuseong Daejeon34055 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 Ibaraki Tsukuba305-0801 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 Chiba Kashiwa277-8582 Japan Istituto Nazionale di Fisica Nucleare Sapienza University Roma00185 Italy Department o

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. © Published under licence by IOP Publishing Ltd.

关键词： Interferometers

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