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The status of KAGRA underground cryogenic gravitational wave telescope

Journal of Physics: Conference Series 2019年第1期1342卷

作者： T. Akutsu M. Ando A. Araya N. Aritomi H. Asada Y. Aso S. Atsuta K. Awai M. A. Barton K. Cannon K. Craig W. Creus K. Doi K. Eda Y. Enomoto R. Flaminio Y. Fujii M.-K. Fujimoto T. Furuhata S. Haino K. Hasegawa K. Hashino K. Hayama S. Hirobayashi E. Hirose A. H. Hsieh Y. Inoue K. Ioka Y. Itoh T. Kaji T. Kajita M. Kakizaki M. Kamiizumi S. Kambara N. Kanda S. Kanemura M. Kaneyama G. Kang J. Kasuya Y. Kataoka N. Kawai S. Kawamura C. Kim H. Kim J. Kim Y. Kim N. Kimura T. Kinugawa S. Kirii Y. Kitaoka Y. Kojima K. Kokeyama K. Komori K. Kotake R. Kumar H. Lee Y. Liu N. Luca E. Majorana S. Mano M. Marchio T. Matsui F. Matsushima Y. Michimura O. Miyakawa T. Miyamoto A. Miyamoto K. Miyo S. Miyoki W. Morii S. Morisaki Y. Moriwaki T. Morozumi M. Musha S. Nagano K. Nagano K. Nakamura T. Nakamura H. Nakano M. Nakano K. Nakao T. Narikawa L.Nguyen Quynh W.-T. Ni T. Ochi J. Oh S. Oh M. Ohashi N. Ohishi M. Ohkawa K. Okutomi K. Oohara F. E.Peña Alleano I. Pinto N. Sago M. Saijo Y. Saito K. Sakai Y. Sakai Y. Sasaki M. Sasaki S. Sato T. Sato Y. Sekiguchi N. Seto M. Shibata T. Shimoda H. Shinkai A. Shoda K. Somiya E. Son A. Suemasa T. Suzuki H. Tagoshi H. Takahashi R. Takahashi A. Takamori H. Takeda H. Tanaka K. Tanaka T. Tanaka D. Tatsumi T. Tomaru T. Tomura F. Travasso K. Tsubono S. Tsuchida N. Uchikata T. Uchiyama T. Uehara S. Ueki K. Ueno T. Ushiba M. H. P. M. van Putten H. Vocca S. Wada T. Wakamatsu T. Yamada S. Yamamoto T. Yamamoto K. Yamamoto A. Yamamoto J. Yokoyama T. Yokozawa T. H. Yoon H. Yuzurihara S. Zeidler Z.-H. Zhu KAGRA Collaboration National Astronomical Observatory of Japan Mitaka Tokyo 181-8588 Japan Department of Physics University of Tokyo Bunkyo Tokyo 113-0033 Japan Earthquake Research Institute University of Tokyo Bunkyo Tokyo 113-0032 Japan Department of Advanced Physics Hirosaki University Hirosaki Aomori 036-8561 Japan National Astronomical Observatory of Japan Hida Gifu 506-1205 Japan Department of Physics Tokyo Institute of Technology Meguro Tokyo 152-8551 Japan Institute for Cosmic Ray Research University of Tokyo Hida Gifu 506-1205 Japan Research Center for the Early Universe University of Tokyo Bunkyo Tokyo 113-0033 Japan Institute for Cosmic Ray Research University of Tokyo Kashiwa Chiba 277-8582 Japan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Department of Physics University of Toyama Toyama Toyama 930-8555 Japan Faculty of Engineering University of Toyama Toyama Toyama 930-8555 Japan Yukawa Institute for Theoretical Physics Kyoto University Sakyo Kyoto 606-8502 Japan Department of Physics Osaka City University Sumiyosi Osaka 558-8585 Japan Department of Physics Osaka University Toyonaka Osaka 560-0043 Japan Korea Institute of Science and Technology Information Yuseong Daejeon 34141 Korea Korea Astronomy and Space Science Institute (KASI) Yuseong Daejeon 34055 Korea National Institute for Mathematical Sciences Daejeon 34047 Korea Department of Computer Simulation Inje University Gimhae Gyeongsangnam 50834 Korea Department of Physics and Astronomy Seoul National University Seoul 151-742 Korea High Energy Accelerator Research Organization Tsukuba Ibaraki 305-0801 Japan Department of Physical Science Hiroshima University Higashihiroshima Hiroshima 903-0213 Japan Department of Applied Physics Fukuoka University Jonan Fukuoka 814-0180 Japan Department of Advanced Materials Science University of Tokyo Kashiwa Chiba 277-8582 Japan Istituto Nazionale di Fisica Nucleare Sapienza University Roma 00185 Italy Department of Ma

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.

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Cloud Service - Cyber Social Democracy and Smart University

Cloud Service - Cyber Social Democracy and Smart University

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IEEE East-West Design & Test Symposium

作者： Vugar Abdullayev Vladimir Hahanov Eugenia Litvinova Dahiri Farid Anton Arefiev Yulia Hahanova Azerbaijan State Oil Academy Azerbaijan National Academy of Sciences Institute of Control Systems Baku Azerbaijan Computer Engineering Faculty National University of Radioelectronics Kharkov Ukraine

ISBN: (纸本)9781467377775

The system of cloud services CyUni for active monitoring and management of digitized scientific and educational processes, primary and secondary departments of the university is proposed. CyUni is based on the technological culture IoT, having the hierarchy structure Cloud - Fog Networks - Mobile [1-4], which excludes the paper carriers, and dependence on subjectivism of academic officials. Socially significant model for human-free cyber monitoring the state structures is created;it allows depriving an authoritarian leader from the functionality of subjective managing resources and processes. The models of the harmonious interaction of the democratic voting rules and cyber monitoring for decision-making in public universities and organizations are developed [5-8]. Market feasibility of the CyUni-service is defined;it is determined by the trend of global enter of cyber services in the state scientific and educational structures focused on initiating of activity of the teaching staff that can improve productivity of scientists, at least twice.

关键词： initiating activity teaching

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Loop Closure Detection by Compressed Sensing for Exploration of Mobile Robots in Outdoor Environments

Loop Closure Detection by Compressed Sensing for Exploration...

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RSI/ISM International Conference on Robotics and Mechatronics

作者： Alireza Norouzzadeh Ravari Hamid D. Taghirad Advanced Robotics and Automated Systems (ARAS) Industrial Control Center of Excellence (ICCE) Faculty of Electrical and Computer Engineering K.N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781467372350

In the problem of simultaneously localization and mapping (SLAM) for a mobile robot, it is required to detect previously visited locations so the estimation error shall be reduced. Sensor observations are compared by a similarity metric to detect loops. In long term navigation or exploration, the number of observations increases and so the complexity of the loop closure detection. Several techniques are proposed in order to reduce the complexity of loop closure detection. Few algorithms have considered the loop closure detection from a subset of sensor observations. In this paper, the compressed sensing approach is exploited to detect loops from few sensor measurements. In the basic compressed sensing it is assumed that a signal has a sparse representation is a basis which means that only a few elements of the signal are non-zero. Based on the compressed sensing approach a sparse signal can be recovered from few linear noisy projections by l_1 minimization. The difference matrix which is widely used for loop detection has a sparse structure, where similar observations are shown by zero distance and different locations are indicated by ones. Based on the multiple measurement vector technique which is an extension of the basic compressed sensing, the loop closure detection is performed by comparison of few sensor observations. The applicability of the proposed algorithm is investigated in some outdoor environments through some publicly available data sets. It has been shown by some experiments that the proposed method can detect loops effectively.

关键词： Loop Closure Detection Compressed Sensing Mobile Robots

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Device-Free Human Presence Detection Using Frequency Domain

Device-Free Human Presence Detection Using Frequency Domain

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IEEE International Workshop on Consumer Electronics

作者： Bojan Mrazovac Branislav M. Todorovic Dragan Kukolj Miodrag Temerinac Department for Computing and Control Engineering Faculty of Technical Sciences Novi Sad Serbia RT-RK Institute for Computer Based Systems Narodnog fronta 23a Novi Sad Serbia

ISBN: (纸本)9781509042692

Device-free human presence (DFHP) detection is a novel technique, mainly applicable to wireless sensor networks in which a human does not need to carry a wireless transceiver to be detected. Irregularities in the radio signal propagation pattern, expressed in a form of received signal strength indicator's (RSSI) variations can indicate possible presence of a human within the existing radio network. In this paper we propose DFHP detection method based on frequency analysis of RSSI variations. The main advantage of the proposed method compared to human detection method based on information entropy is the possibility to determine human presence from furniture layout change. The main drawback is a disability to recognize the absence from the presence of a motionless person in an environment. However, the combination of these two approaches defines a robust and cost-effective DFHP detection method that can be used in various smart home systems without the need for specific hardware installation and exploitation procedures.

关键词： fast Fourier transform human presence detection information entropy rssi

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Estimates, trends, and drivers of the global burden of type 2 diabetes attributable to PM_2·5 air pollution, 1990–2019: an analysis of data from the Global Burden of Disease Study 2019

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The Lancet Planetary Health 2022年第7期6卷 e586-e600页

作者： Burkart, Katrin Causey, Kate Cohen, Aaron J Wozniak, Sarah S Salvi, Devashri Digvijay Abbafati, Cristiana Adekanmbi, Victor Adsuar, Jose C Ahmadi, Keivan Alahdab, Fares Al-Aly, Ziyad Alipour, Vahid Alvis-Guzman, Nelson Amegah, Adeladza Kofi Andrei, Catalina Liliana Andrei, Tudorel Ansari, Fereshteh Arabloo, Jalal Aremu, Olatunde Aripov, Timur Babaee, Ebrahim Banach, MacIej Barnett, Anthony Bärnighausen, Till Winfried Bedi, Neeraj Behzadifar, Masoud Béjot, Yannick Bennett, Derrick A Bensenor, Isabela M Bernstein, Robert S Bhattacharyya, Krittika Bijani, Ali Biondi, Antonio Bohlouli, Somayeh Breitner, Susanne Brenner, Hermann Butt, Zahid A Cámera, Luis Alberto Cantu-Brito, Carlos Carvalho, Felix Cerin, Ester Chattu, Vijay Kumar Chauhan, Bal Govind Choi, Jee-Young Jasmine Chu, Dinh-Toi Dai, Xiaochen Dandona, Lalit Dandona, Rakhi Daryani, Ahmad Davletov, Kairat De Courten, Barbora Demeke, Feleke Mekonnen Denova-Gutiérrez, Edgar Dharmaratne, Samath Dhamminda Dhimal, Meghnath Diaz, Daniel Djalalinia, Shirin Duncan, Bruce B El Sayed Zaki, Maysaa Eskandarieh, Sharareh Fareed, Mohammad Farzadfar, Farshad Fattahi, Nazir Fazlzadeh, Mehdi Fernandes, Eduarda Filip, Irina Fischer, Florian Foigt, Nataliya A Freitas, Marisa Ghashghaee, Ahmad Gill, Paramjit Singh Ginawi, Ibrahim Abdelmageed Gopalani, Sameer Vali Guo, Yuming Gupta, Rajat Das Habtewold, Tesfa Dejenie Hamadeh, Randah R Hamidi, Samer Hankey, Graeme J Hasanpoor, Edris Hassen, Hamid Yimam Hay, Simon I Heibati, Behzad Hole, Michael K Hossain, Naznin Househ, Mowafa Irvani, Seyed Sina Naghibi Jaafari, Jalil Jakovljevic, Mihajlo Jha, Ravi Prakash Jonas, Jost B Jozwiak, Jacek Jerzy Kasaeian, Amir Kaydi, Neda Khader, Yousef Saleh Khafaie, Morteza Abdullatif Khan, Ejaz Ahmad Khan, Junaid Khan, Md Nuruzzaman Khatab, Khaled Khater, Amir M Kim, Yun Jin Kimokoti, Ruth W Kisa, Adnan Kivimäki, Mika Knibbs, Luke D Kosen, Soewarta Koul, Parvaiz A Koyanagi, Ai Defo, Barthelemy Kuate Kugbey, Nuworza Lauriola, Paolo Lee, Paul H Leili, Mostafa Lewycka, Sonia Li, Shanshan Lim, Lee-Ling Li Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Plastic and Reconstructive Surgery University of Washington Seattle WA United States Research Insights and Innovation Seattle WA United States Health Effects Institute Boston MA United States School of Public Health Boston University Boston MA United States Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Population Medicine Cardiff University Cardiff United Kingdom Sport Science Department University of Extremadura Badajoz Spain School of Public Health Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom Mayo Evidence-based Practice Center Mayo Clinic Foundation for Medical Education and Research Rochester MN United States John T. Milliken Department of Internal Medicine Washington University in St. Louis St. Louis MO United States Clinical Epidemiology Center US Department of Veterans Affairs (VA) St Louis MO United States Health Management and Economics Research Center Iran University of Medical Sciences Tehran Iran Department of Health Economics Iran University of Medical Sciences Tehran Iran Preventive Medicine and Public Health Research Center Iran University of Medical Sciences Tehran Iran Pars Advanced and Minimally Invasive Medical Manners Research Center Iran University of Medical Sciences Tehran Iran Department of Community and Family Medicine Iran University of Medical Sciences Tehran Iran Research Group in Hospital Management and Health Policies Universidad de la Costa (University of the Coast) Barranquilla Colombia Research Group in Health Economics University of Cartagena Cartagena Colombia Department of Biomedical Science University of Cape Coast Cape Coast Ghana Cardiology Department Ca

Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM_2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM_2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM_2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM_2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM_2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am

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Stabilization of type-2 fuzzy Takagi-Sugeno-Kang identifier using Lyapunov functions

Stabilization of type-2 fuzzy Takagi-Sugeno-Kang identifier ...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Erdal Kayacan Mojtaba Ahmadieh Khanesar Erkan Kayacan School of Mechanical & Aerospace Engineering Nanyang Technological University Singapore Faculty of Electrical and Computer Engineering Semnan University Semnan Iran Delft Center for Systems and Control Delft University of Technology The Netherlands

Differing from previous studies, where sliding mode control theory-based rules are proposed for only the consequent part of the network, the developed algorithm in this paper applies fully sliding mode parameter update rules for both the premise and consequent parts of the interval type-2 fuzzy neural networks. The stability of the proposed learning algorithm has been proved by using an appropriate Lyapunov function. Then, the performance of the proposed learning algorithm is tested on the identification of wing flutter data set available online as a benchmark system and the prediction of Mackey-Glass chaotic system. The simulation results indicate that the proposed algorithm is significantly faster than the gradient-based methods as well as providing a slightly better identification performance. The reason for the fast convergence is that the proposed parameter update rules do not have any matrix manipulations which makes them simple to be implemented in real-time systems. In addition, the responsible parameter for sharing the contributions of the lower and upper parts of the type-2 fuzzy membership functions is also tuned. Another prominent feature of the proposed learning algorithm is to have a closed form which makes it easier to implement than the other existing learning methods, e.g. gradient-based methods.

关键词： Fuzzy neural networks Data models Prediction algorithms Chaos Adaptation models Uncertainty Heuristic algorithms

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Cooperative control in production and logistics

Cooperative control in production and logistics

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作者： Monostori, László Valckenaers, Paul Dolgui, Alexandre Panetto, Hervé Brdys, Mietek Csáji, Balázs Csanád Institute for Computer Science and Control Hungarian Academy of Sciences Kende u. 13-17 BudapestH-1111 Hungary Faculty of Mechanical Engineering Budapest University of Technology and Economics Hungary Department of Health Care and Technology KHLeuven Belgium LIMOS UMR 6158 CNRS Ecole Nationale Supérieure des Mines de Saint-Etienne France CNRS CRAN UMR 7039 France Université de Lorraine CRAN UMR 7039 France School of Electronic Electrical and Computer Engineering University of Birmingham United Kingdom Department of Control Systems Engineering Gdansk University of Technology Gdansk Poland

Classical applications of control engineering and information and communication technology (ICT) in production and logistics are often done in a rigid, centralized and hierarchical way. These inflexible approaches are typically not able to cope with the complexities of the manufacturing environment, such as the instabilities, uncertainties and abrupt changes caused by internal and external disturbances, or a large number and variety of interacting, interdependent elements. A paradigm shift, e.g., novel organizing principles and methods, is needed for supporting the interoperability of dynamic alliances of agile and networked systems. Several solution proposals argue that the future of manufacturing and logistics lies in network-like, dynamic, open and reconfigurable systems of cooperative autonomous entities. The paper overviews various distributed approaches and technologies of control engineering and ICT that can support the realization of cooperative structures from the resource level to the level of networked enterprises. Standard results as well as recent advances from control theory, through cooperative game theory, distributed machine learning to holonic systems, cooperative enterprise modeling, system integration, and autonomous logistics processes are surveyed. A special emphasis is put on the theoretical developments and industrial applications of Robustly Feasible Model Predictive control (RFMPC). Two case studies are also discussed: (i) a holonic, PROSA-based approach to generate short-term forecasts for an additive manufacturing system by means of a delegate multi-agent system (D-MAS);and (ii) an application of distributed RFMPC to a drinking water distribution system. © 2015 Elsevier Ltd.

关键词： Model predictive control

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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

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Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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GROUP CONSENSUS FOR MULTIPLE NETWORKED EULER-LAGRANGE systems WITH PARAMETRIC UNCERTAINTIES

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Journal of systems Science & Complexity 2014年第4期27卷 632-649页

作者： HU Hongxiang ZHANG Zhe YU Li YU Wenwu XIE Guangming Department of Mathematics Hangzhou Dianzi University Zhejiang Provincial United Key Laboratory of Embedded Systems Department of AutomationZhejiang University of Technology Department of Mathematics Southeast University School of Electrical and Computer Engineering RMIT University Faculty of Engineering King Abdulaziz University Center for Systems and Control State Key Laboratory of Turbulence and Complex SystemsCollege of EngineeringPeking University

In this paper,a group consensus problem is investigated for multiple networked agents with parametric uncertainties where all the agents are governed by the Euler-Lagrange system with uncertain *** the group consensus problem,the agents asymptotically reach several different states rather than one consistent state.A novel group consensus protocol and a time-varying estimator of the uncertain parameters are proposed for each agent in order to solve the couple-group consensus *** is shown that the group consensus is reachable even when the system contains the uncertain ***,the multi-group consensus is discussed as an extension of the couple-group consensus,and then the group consensus with switching topology is *** results are finally provided to validate the effectiveness of the theoretical analysis.

关键词： Euler-Lagrange system group consensus multi-agent systems switching topologies.

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Radiative parameters of steel slag for FeO content estimation using multispectral thermography system

Radiative parameters of steel slag for FeO content estimatio...

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作者： Strąkowski, Robert Pacholski, Krzysztof Więcek, Boguslaw Olbrycht, Robert Wittchen, Waclaw Borecki, Mariusz Institute of Electronics Faculty of Electrical Electronic Computer and Control Engineering Lodz University of Technology Lodz Poland Institute of Electrical Engineering Systems Faculty of Electrical Electronic Computer and Control Engineering Lodz University of Technology Lodz Poland Institute for Ferrous Metallurgy Gliwice Poland

The paper deals with the application of multispectral imaging to estimate steel quality directly after it is produced in the steelworks. In particular, thermal and visual cameras are used to estimate FeO content in the slag. This is done by analysis of the steel stream images that are acquired during discharge from an oxygenic converter. The analysis involves statistical analysis for determined primary and secondary radiative parameters of steel and slag. © 2014 Taylor & Francis.

关键词： Slags

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