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Self-Awareness for Autonomous Systems

PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems computational modeling

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Devising an integrated procedure for assessing fragmentation effects

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IOP Conference Series: Materials Science and engineering 2020年第4期962卷

作者： A N Yasyreva L V Poluyan E S Guryev Department of Computer-Aided Design of Construction Facilities Ural Federal University named after the first President of Russia B.N.Yeltsin Mira 19 Yekaterinburg 620002 Russia Science and Engineering Centre 'Reliability and Safety of Large Systems and Machines' Ural Branch Russian Academy of Sciences Studencheskaya 54-A Yekaterinburg 620049 Russia

The paper presents a comparative analysis of Russian and foreign investigations in fragmentation effects and methods for assessing parameters of fragments formed by explosions of the equipment used for storing hazardous substances. Based on the results of the analysis, a conclusion was made as to the necessity of developing an integrated procedure for assessing fragmentation effects. The procedure is to be implemented as an ordered systematized algorithm comprising the analyzed methods for calculating individual parameters of fragments. The procedure devised was tested during the accident at the «Cosmo Oil» petroleum refinery in Japan, on March 11, 2011. Practical relevance of the procedure proposed is justified by the calculation results agreeing with the accident events.

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Author Correction: Mapping global lake dynamics reveals the emerging roles of small lakes

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Nature communications 2022年第1期13卷 6337页

作者： Xuehui Pi Qiuqi Luo Lian Feng Yang Xu Jing Tang Xiuyu Liang Enze Ma Ran Cheng Rasmus Fensholt Martin Brandt Xiaobin Cai Luke Gibson Junguo Liu Chunmiao Zheng Weifeng Li Brett A Bryan School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen China. Department of Urban Planning and Design The University of Hong Kong Hong Kong SAR China. Urban Systems Institute The University of Hong Kong Hong Kong SAR China. School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen China. fengl@***. Department of Geosciences and Natural Resource Management University of Copenhagen Copenhagen Denmark. Department of Biology University of Copenhagen Copenhagen Denmark. Department of Physical Geography and Ecosystem Science Lund University Lund Sweden. Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China. Institute of Geodesy and Geophysics Chinese Academy of Sciences Wuhan China. School of Water Conservancy North China University of Water Resources and Electric Power 450046 Zhengzhou China. EIT Institute for Advanced Study Ningbo China. Institute for Climate and Carbon Neutrality The University of Hong Kong Hong Kong SAR China. Centre for Integrative Ecology School of Life and Environmental Sciences Deakin University Burwood Victoria Australia.

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Features of the synthesis of information and measurement systems using machine learning for conducting of environmental monitoring

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Journal of Physics: Conference Series 2021年第3期1889卷

作者： Yu M Avdeev A I Pakhomova A L Zolkin V D Munister V M Kalyakina Department of Urban Cadastre and Geodesy of the Engineering and Construction Institute Vologda State University Lenin Street 15 Vologda 160000 Russia Department of Economics and management Institute of service and entrepreneurship (branch) of DSTU in Shakhty Shevchenko Street 147 Shahti Rostov region 346500 Russia Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics L.Tolstogo Street 23 Samara 443010 Russia Department of Mathematical Methods and Computer-Aided Design Private educational institution 'Donetsk Academy of Transport' Dzerzhinsky Street 7 Donetsk 83086 Ukraine Department of health safety and environmental engineering protection Don State technical University Gagarin square 1 Rostov-on-Don 344002 Russia Natural Sciences Department Private institution of higher education 'Medical University' Reaviz Chapaevskaya Street 227 Samara 443001 Russia Department of Enterprise Economics State educational institution of higher professional education 'Donetsk National Technical University' Shibankova Street 2 Pokrovsk Donetsk region 85300 Ukraine

The article is dedicated to the consideration of new methods for the synthesis of digital environmental monitoring systems, inclusive to the analysis through the methodology of machine learning. The role of circuit components proposed for implementation is considered. Attention is paid to the specifics of the analysis of already measured data and to the memory device of information-measuring systems. The importance of using MS-triggers and logistic regression in analysis of the stability of sensors is justified.

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CEPC Technical design Report

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Radiation Detection Technology and Methods 2024年第1期8卷 I0003-I0016,1-1091页

作者： Waleed Abdallah Tiago Carlos Adorno de Freitas Konstantin Afanaciev Shakeel Ahmad Ijaz Ahmed Xiaocong Ai Abid Aleem Wolfgang Altmannshofer Fabio Alves Weiming An Rui An Daniele Paolo Anderle Stefan Antusch Yasuo Arai Andrej Arbuzov Abdesslam Arhrib Mustafa Ashry Sha Bai Yu Bai Yang Bai Vipul Bairathi Csaba Balazs Philip Bambade Yong Ban Tripamo Bandyopadhyay Shou-Shan Bao Desmond P.Barber Ayse Bat Varvara Batozskaya Subash Chandra Behera Alexander Belyaev Michele Bertucci Xiao-Jun Bi Yuanjie Bi Tianjian Bian Fabrizio Bianchi Thomas Biekotter Michela Biglietti Shalva Bilanishvili Deng Binglin Denis Bodrov Anton Bogomyagkov Serge Bondarenko Stewart Boogert Maarten Boonekamp Marcello Borri Angelo Bosotti Vincent Boudry Mohammed Boukidi Igor Boyko Ivanka Bozovic Giuseppe Bozzi Jean-Claude Brient Anastasiia Budzinskaya Masroor Bukhari Vladimir Bytev Giacomo Cacciapaglia Hua Cai Wenyong Cai Wujun Cai Yijian Cai Yizhou Cai Yuchen Cai Haiying Cai Huacheng Cai Lorenzo Calibbi Junsong Cang Guofu Cao Jianshe Cao Antoine Chance Xuejun Chang Yue Chang Zhe Chang Xinyuan Chang Wei Chao Auttakit Chatrabhuti Yimin Che Yuzhi Che Bin Chen Danping Chen Fuqing Chen Fusan Chen Gang Chen Guoming Chen Hua-Xing Chen Huirun Chen Jinhui Chen Ji-Yuan Chen Kai Chen Mali Chen Mingjun Chen Mingshui Chen Ning Chen Shanhong Chen Shanzhen Chen Shao-Long Chen Shaomin Chen Shiqiang Chen Tianlu Chen Wei Chen Xiang Chen Xiaoyu Chen Xin Chen Xun Chen Xurong Chen Ye Chen Ying Chen Yukai Chen Zelin Chen Zilin Chen Gang Chen Boping Chen Chunhui Chen Hok Chuen Cheng Huajie Cheng Shan Cheng Tongguang Cheng Yunlong Chi Pietro Chimenti Wen Han Chiu Guk Cho Ming-Chung Chu Xiaotong Chu Ziliang Chu Guglielmo Coloretti Andreas Crivellin Hanhua Cui Xiaohao Cui Zhaoyuan Cui Brunella D'Anzi Ling-Yun Dai Xinchen Dai Xuwen Dai Antonio De Maria Nicola De Filippis Christophe De La Taille Francesca De Mori Chiara De Sio Elisa Del Core Shuangxue Deng Wei-Tian Deng Zhi Deng Ziyan Deng Bhupal Dev Tang Dewen Biagio Di Micco Ran Ding Siqin Dingl Yadong Ding Haiyi Dong Jianin AGH University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakow Anhui University HefeiAnhui Applied Physics Department Federal Urdu University of ArtsScience and TechnologyIslamabad Banaras Hindu University Institute of ScienceVaranasi Bandirma Onyedi Eylul University Bandirma Beihang University Beijing Beijing Computational Science Research Center Beijing Beijing Conveyi LTD Beijing Beijing Glass Research Institute Co. LtdBeijing Beijing Institute of Technology Beijing Beijing Normal University Beijing Brown University ProvidenceRI Budker Institute of Nuclear Physics Novosibirsk Cadi Ayyad University Laboratory of Fundamental and Applied PhysicsPolydisciplinary FacultyMarrakech Cairo University Giza Center for Theory and Computation National Tsing Hua UniversityHsinchu Central China Normal University WuhanHubei Central South University ChangshaHunan Centro de Fisica Teorica de Particulas Universidade Tecnica de LisboaLisboa Chengdu KaitengSifang Digital Radio&TV Equipment Co. LtdChengduSichuan China academy of engineering physics MianyangSichuan China building materials academy Beijing China Center of Advanced Science and Technology Beijing China Institute of Atomic Energy Beijing China Jiliang University HangzhouZhejiang China Nuclear Instrument CO. LTDBeijing China University of Geosciences Beijing China University of Geosciences WuhanHubei China University of Mining and Technology XuzhouJiangsu China West Normal University NanchongSichuan Chongqing University Department of PhysicsChongqing Chulalongkorn University Bangkok City University of Hong Kong Department of PhysicsHong Kong Cockcroft Institute Daresbury Cornell University IthacaNY CPPM(AMU/IPhU&CNRS/INP) Marseille Dalian Minzu University DalianLiaoning Dalian University of Technology Department of PhysicsDalian Deutsches Elektronen-Synchrotron DESY Hamburg Dzhelepov Laboratory of Nuclear Problems of Joint Institute for Nuclear Research(DLNP JINR) Dubna East China University Of Science And Technol

The Circular Electron Positron Collider(CEPC)is a large scientific project initiated and hosted by China,fostered through extensive collaboration with international *** complex comprises four accelerators:a 30 GeV Linac,a 1.1 GeV Damping Ring,a Booster capable of achieving energies up to 180 GeV,and a Collider operating at varying energy modes(Z,W,H,and tt).The Linac and Damping Ring are situated on the surface,while the subterranean Booster and Collider are housed in a 100 km circumference underground tunnel,strategically accommodating future expansion with provisions for a potential Super Proton Proton Collider(SPPC).The CEPC primarily serves as a Higgs *** its baseline design with synchrotron radiation(SR)power of 30 MW per beam,it can achieve a luminosity of 5×10^(34)cm^(-2)s^(-1)per interaction point(IP),resulting in an integrated luminosity of 13 ab^(-1)for two IPs over a decade,producing 2.6 million Higgs *** the SR power to 50 MW per beam expands the CEPC's capability to generate 4.3 million Higgs bosons,facilitating precise measurements of Higgs coupling at sub-percent levels,exceeding the precision expected from the HL-LHC by an order of *** Technical design Report(TDR)follows the Preliminary Conceptual design Report(Pre-CDR,2015)and the Conceptual design Report(CDR,2018),comprehensively detailing the machine's layout,performance metrics,physical design and analysis,technical systems design,R&D and prototyping efforts,and associated civil engineering ***,it includes a cost estimate and a preliminary construction timeline,establishing a framework for forthcoming engineering design phase and site selection *** is anticipated to begin around 2027-2028,pending government approval,with an estimated duration of 8 *** commencement of experiments and data collection could potentially be initiated in the mid-2030s.

关键词： initiated exceeding precise

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Multiscale spectral subtraction method and support vector machine for clustering heavy background noise classification 24

Multiscale spectral subtraction method and support vector ma...

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24th International Congress on Sound and Vibration, ICSV 2017

作者： Tsai, Yu-Ting Huang, Jin H. Feng Chia University Bachelor's Program in Precision System Design Taichung Taiwan Feng Chia University Department of Mechanical and Computer-Aided Engineering Taichung Taiwan

For measuring the rotation engine vibration signals, the mechanical or acoustical sensors are dif-ficult to get the clean signals from the heavy background noise of the machinery environment. The noise reduction algorithm may anticipate to decrease the background noise without disturbing the unpolluted signal. The spectral subtraction methods for noise attenuation case are reached for many years due to its simple and effectively. In this paper, the proposed algorithm incorporates the multiscale spectral subtraction method (MSS) with voice activity detector (VAD) and sup-ports vector machine (SVM) for removing the background noise, since SVM can be required for distinguishing a multivariate signal into separated subcomponents. From the analysis case for the rotating machinery, MSS shows that the low frequency with their harmonics frequencies can be tracked through the clustering of the data from SVM. The present method is helpful in background noise and signal compartmentalization as its application can significantly lower the requirement for labelled training cases in both the inductive noise and wanted signals.

关键词： Support vector machines

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A model of the development of an accident situation involving construction scaffolding

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AIP Conference Proceedings 2019年第1期2116卷

作者： Bożena Hoła Anna Hoła Mariusz Szóstak 1Wroclaw University of Science and Technology Faculty of Civil Engineering Department of Construction Technology and Management Wroclaw Poland 2Wroclaw University of Science and Technology Faculty of Civil Engineering Department of Building Physics and Computer Aided Design Wroclaw Poland

On the basis of conducted research and the analysis of occupational accidents that involved scaffolding, a model of the development of an accident situation in the form of a directed graph was developed. The model was used to analyse 187 accidents that occurred in 5 Polish voivodeships in the years from 2010 to 2017. Based on the analysis of the set of accidents, the critical path in the graph was determined and the most dangerous events related to work on scaffolding were specified.

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Knowledge-based material selection for injection-molded, thermoplastic parts

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AIP Conference Proceedings 2019年第1期2055卷

作者： Alexander Porsch René Andrae Johannes Wortberg Peter Köhler 1University of Duisburg-Essen Institute of Product Engineering Department of Engineering Design and Plastics Machinery Lotharstraße 1 47057 Duisburg Germany 2University of Duisburg-Essen Institute of Product Engineering Department of Computer Aided Engineering Lotharstraße 1 47057 Duisburg Germany

Material selection is an important but often an arbitrary process at the beginning of the development of injection-molded parts. Due to the absence of a sufficient documentation, it cannot be retraced and optimized by other engineers. The use of expert systems, which apply a comprehensive knowledge base, is a possibility to reduce mistakes and make decisions more transparent. In this paper, a knowledge-based method for material selection is presented. Basis of the method is a knowledge base containing information about the properties of thermoplastics. This includes for example single- and multi-point-data, or facts like chemical resistances. Moreover, additional information concerning the modification of the properties, correlations, or the exact definitions are stored in the knowledge base. It also contains knowledge about production processes like standard injection molding, MuCell, or injection-compression molding restricting the number of suitable materials. Additional knowledge about the influence of part design for material selection completes the knowledge base. Considering the vast amount of available thermoplastics, the presented knowledge base includes selected examples. Based on this knowledge, a multistage method is developed using questionnaires to refine requirements and to exchange information between engineer and expert system. During the selection process, additional information, as it has been mentioned before, is given. At the end of the process, the user gets a ranking of possible materials. In addition, more detailed knowledge about their properties, advantages, and disadvantages are provided. For the development and the visualization of the method, System Modeling Language diagrams are used. These allow different views to the material selection method, the stages, and links between knowledge base and selection process. Finally, the results are discussed, and an outlook for development potential is given.

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Application of artificial intelligence and digital technologies in the organization of the educational process of specialists in the field of physics, engineering and metrology

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Journal of Physics: Conference Series 2021年第2期1889卷

作者： S V Shamina V D Munister A L Zolkin R A Verbitskiy V V Dragulenko Department Natural science disciplines South Ural state agrarian University Gagarin street 13 Troitsk 457100 Chelyabinsk region Russia Department of Mathematical Methods and Computer-Aided Design Private educational institution 'Donetsk Academy of Transport' Dzerzhinsky Street 7 Donetsk 83086 Ukraine Department of Enterprise Economics State educational institution of higher professional education 'Donetsk National Technical University' Shibankova Street 2 Pokrovsk Donetsk region 85300 Ukraine Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics L.Tolstogo Street 23 Samara 443010 Russia Natural Sciences Department Private institution of higher education 'Medical University' Reaviz Chapaevskaya Street 227 Samara 443001 Russia Engineering drawing department MIREA - Russian Technological University Vernadsky Avenue 178 Moscow 119454 Russia Department of tractors automobiles and technical mechanics Federal State Budgetary Educational Institution of Higher Education 'Kuban State Agrarian University named after I.T. Trubilin' Kalinina Street 13 Krasnodar 350044 Russia

The article deals with the problems and the importance of modern advanced learning. A model of teaching for students mastering programs of secondary and higher vocational education, based on the terminal-matrix approach, which includes the integration of several related disciplines, is proposed. The importance of artificial intelligence methods in engineering, physical, engineering education is substantiated by the example of checking of research results.

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Digital heuristic paradigm of research and development work in the conditions of university

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Journal of Physics: Conference Series 2021年第2期1889卷

作者： O V Kosnikova V D Munister A L Zolkin P M Yudanov V E Ozhiganov Department of Economic Cybernetics Federal State Budgetary Educational Institution of Higher Education «Kuban State Agrarian University named after I.T. Trubilin» KalininaStreet 13 Krasnodar 350044 Russia Department of Mathematical Methods and Computer-Aided Design Private educational institution 'Donetsk Academy of Transport' Dzerzhinsky Street 7 Donetsk 83086 Ukraine Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics L.Tolstogo Street 23 Samara 443010 Russia Chemistry and material sciences department Civil Defence Academy of EMERCOM of Russia Novogorskdstr. Khimki Moscow region 141435 Russia Engineering department 2 RUSSIAN FEDERAL NUCLEAR CENTERAll-Russian Research Institute of Experimental PhysicsFSUE RFNC – VNIIEF Mira Ave 37 Sarov Nizhny Novgorod region607188 Russia Department of Enterprise Economics State educational institution of higher professional education 'Donetsk National Technical University' Shibankova Street 2 Pokrovsk Donetsk region 85300 Ukraine Natural Sciences Department Private institution of higher education 'Medical University' Reaviz Chapaevskaya Street 227 Samara 443001 Russia

The article discusses the model of a digital university. The author's paradigm of research and design work, based on the student social network model, is researched, the scientometric and heuristic aspects of the proposed system functioning are determined. The role and general significance of the proposed methodology is indicated. A schematic diagram of the reduction to the proposed digital paradigm is given. The application of the model and its transparency are substantiated.

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