Computation of inertial motion neural strategies to resolve ambiguous otolith information
计算机EI收录的外文期刊
/bbs/read.php?tid=3163计算机方面EI收录的外文期刊( 有“*”是同时被《EI》收录的期刊)1、738B0006 ISSN 0018-8646 IF:2、560 “*”IBM Journal of Research and Development. 《国际商用机器公司研究与开发杂志》,1957. 4/yr. IBM Corp.Old Orchard Rd, Armonk, NY, 10504.http://elib.cs.sfu.ca/Collections/CMPT/cs-journals/P-IBM/J-IBM-JRD.html 2、738B0008-1 ISSN 0004-5411 IF:1、078 “*”Journal of the Association for Computiong Machinery. 《美国计算机学会志》,4/yr. Association for Computing Machinery, 1515Broadway, 17th FL., New York, NY 10036-5701, USATel: 212 869 7440Fax: 212 944 1318/jacm3、738B0008-2 ISSN 0001-0782 IF:2、238 “*”Communications of the ACM. 《美国计算机学会通讯》,1958. 12/yr.Association for Computing Machinery. 1515 Broadway, 17th FL.,New York, NY 10036-5701, USA.Tel: 212 869 7440/jacm4、738B0012 ISSN 0022-0000 IF:0、661 “*”Journal of Computer and System Sciences. 《计算机与系统科学杂志》,1967. 6/yr. Academic Press Inc., Journal Subseription Fulfillment Dept., 6277 Sea Harbor Drive.Tel: 407 345 4040Fax: 407 363 9661E-mail: *************http://www.apnet.Con5、738B0018 ISSN 0360-0333 IF:0、641 “*”ACM Computing Surveys. 《美国计算机学会计算概观》,1969. 4/yr.Association for Computing Machinery, 1515 Broadway. 17th FL.,New York, NY 10036-5701, USA.Tel: 212 869 7440Fax: 212 944 1318/jacm6、738B0029-2 ISSN 1077-3142 IF:1、298Computer Vision and Image Undwestanding. 《计算机视觉与图像理解》1969. Academic Press Inc., Journal Subscription Fulfillment Dept., 6227 Sca Harbor Drive, Orlando,FL 32887-4900, USA.Tel: 407 345 4040Fax: 407 363 9661E-mail: *************7、738B0031 ISSN 0362-5915 IF:1、20 “*”ACM Transactions on Database System. 《美国计算机学会数据库系统汇刊》,1976. 4/yr. Association for Computing Machinery. 1515 Broadway,17th FL., New York, NY 10036-5701. USA.Tel: 212 869 7440Fax: 212 944 1318/jacm8、738B0033 ISSN 0164-0925 IF:0、950 “*”ACM Transactions on Programming Languages & Systems. 《美国计算机学会程序设计语言与系统汇刊》,1979. 6/yr.Association for Computing Machinery. 1515 Broadway, 17th FL.,New York NY 10036-5701. USA.Fax: 212 944 1318/jacm9、738B0040 ISSN 0730-0301 IF:1、88 “*”ACM Transactions on Graphics. 《美国计算机学会图形学汇刊》,1982. 4/yr. Association for Computing Machinery.1515 Broadway, 17th FL., New York, NY 10036-5701, USA.Fax: 212 944 1318/jacm10、738B0045 ISSN 1046-8188 IF:2、036 “*”ACM Transactions on Information Systems. 《美国计算机学会信息系统汇刊》,1983. 4/yr. Association for Computing Machinery. 1515 Broadway.17th FL. New York. NY 10036-5701 USA.Fax: 212 944 1318/jacm11、738B0046 ISSN 0734-2071 IF:1、238 “*”ACM Transactions on Computer Systems. 《美国计算机学会计算机系统汇刊》,1983. 4/yr. Association for Computing Machinery. 1515 Broadway.17th FL. New York. NY 10036-5701 USA.Fax: 212 944 1318/jacm12、738B0224 ISSN 0098-3500 IF:0、649 “*”ACM Transations on Mathematical Software. 《美国计算机学会数学软件汇刊》,1975. 4/yr. Association for Computing Machinery. 1515 Broadway.17th FL. New York. NY 10036- 5701 USA.Tel: 212 869 7440Fax: 212 944 1318/jacm13、738B0488 ISSN 0743-7315 IF:0、353Journal of Parallel and Distributed Computing. 《并行与分布式计算杂志》,1984. 12/yr. Academic Press Inc., Journal SubscriptionFulfillment Dept., 6277Sea Harbor Drive, Orlando, FL32887-4900, USATel: 407 345 4040Fax; 407 363 9661E-mail: *************14、738B0494 ISSN 0743-1066 IF:0、819 “*”Journal of Logic Programming. 《逻辑程序设计杂志》,1984. 12/yr.Elsevier Science Inc., Regional Sales Office, Customer Support Department, Po Box 945, New York, NY 10159-0945, USA.Fax: 212 633 3680E-mail: *******************http://www.elsevier.nl/15、738B0514 ISSN 0738-4602 IF:1、286 “*”AI Magazine. ( Artificial Intelligence ). 《人工智能杂志》,1979. 4/yr.American Association For Artificial Intelligence, 445 Burgess Dr.,Menlo Park, CA94025, USA.Fax: 415 321 445716、738B0547 ISSN 0884-8173 IF:0、398 “*”International Journal of Intelligent Systems. 《国际智能系统杂志》,1986. 12/yr. John Wiley & Sons Inc., Subscription Department,605 Third Avenue, New York, NY 10158-0012, USA.Fax: 212 850 6021E-mail: ******************17、738B0548 ISSN 0178-4617 IF:0、477 “*”Algorithmica: A International Journal in Computer Science. 《算法》,1986. 12/yr. Springer-Verlag New York Inc.,175 Fifth Ave., New York, NY 10010, USA.Fax: 212 473 6272E-mail: **********************/journals/45318、723B0578 ISSN 1094-3420 IF:0、833International Journal of High Performance Computing Application. 《高性能计算应用国际杂志》,1987. 4/yr. Sage Publications Inc.,2455 Teller Road, Thousand Oaks, CA 91320, USA.Tel: 805 499 0721Fax: 805 499 0871E-mail: *********************19、738B0663 ISSN 0899-7667 IF:2、727Neural Computation. 《神经计算》,1989. 8/yr. MIT Press Journal Department, 5 Cambridge Center, Cambridge, MA 02142-1399, USA.Tel: 617 253 2889Fax: 617 577 1545E-mail: ***********************20、738B0703 ISSN 0896-8438 IF:0、886 “*”Journal of Object-Oriented Programming. 《面向对象程序设计杂志》,1988. 9/yr. Sigs Publications Inc., 71 W. 23rd St.,New York, NY 10010-4102, USA.Tel: 212 242 7447Fax: 212 242 7574E-mail: **********************21、738B0705 ISSN 1044-7318 IF:0、359International Journal of Human-Computer Interaction. 《国际人与计算机相互作用杂志》,1989. 4/yr. Lawrence Erlbaum Associates Inc., Journal Customer Service Dept., 10Industrial Ave., Mahwah, NJ 07430-2262 USA.Tel: 201 236 9500Fax: 201 236 0072E-mail: ******************22、738B0780 ISSN 0028-3045 IF:0、368Networks. 《网络》,1971. 8/yr. John Wiley & Sons Inc,605 Third Ave, New York, NY, 10158-0012.ask.ca/ejournals23、738B0788 ISSN 1054-7460 IF:1、544Presence: Teleoperators and Virtual Environments. 《存在:远程操作设备与虚拟环境》,1992. 6/yr. MIT Press, Journals Department,5 Cambridge Center, Cambridge, MA 02142-1399, USA.Tel: 617 253 2889Fax: 617 577 1545E-mail: ***********************24、738B0798 ISSN 1049-331X IF:0、889 “*”ACM Transactions on Software Engineering and Methodology. 《美国计算机学会软件工程与方法论汇刊》,1992. 4/yr. Association for Computing Machinery, 1515 Broadway, 17th FL., New York, NY 10036-5701, USA.Tel: 212 869 7440Fax: 212 944 1318/jacm25、738B0899 ISSN 1063-293X IF:0、353 “*”Concurrent Engineering Research and Applications. 《并行工程研究与应用》,4/yr. Managing Editor: Biren Prasad, Ph. D.,International Institute of Concurent Engineering, CETEAM JournalDepartment, Po Box, 3882, Tustin, CA 92782, USA.Tel: (714) 389 2662Fax: (714) 389 2662E-mail: ****************/26、738C0017 ISSN 0305-0548 IF:0、031Computers & Operations Research. 《计算机与运筹学研究》,14/yr.Editor: G. Laporte, HEC, Montreal, Canada.E-mail: *********************.ca/wps/find/science/journal/27、738C0019 ISSN 0097-8485 IF:1、632 “*”Computer & Chemistry. 《计算机与化学》,1974. 6/yr.Elsevier Science, Regional Sales Office, Customer Support Department, Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: (31) 20 485 3757Fax: (31) 20 485 3432E-mail: nlinfo-f@elsevierhttp://www.elsevier.nl28、738C0022 ISSN 0098-3004 IF:0、424 “*”Computers & Geosciences. 《计算机与地学》,1957. 10/yr. CustomerSupport Department, Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: (31) 20 485 3757Fax:(31) 20 485 3432E-mail: ********************http://www.elsevier.nl29、738C0028 ISSN 1367-4803 IF:3、421Bioinformatics. 《生物信息学》,1984. 12/yr.Oxford University Press. Journal SubscriptionsDepartment, Great Clarendon Street, Oxford, OX2 6DP, UK.Fax: (01865) 267 485E-mail: *****************.uk/journalsBarbara Cox, Embl-Ebi, Hinxlon, Cambridge Cb10 1sd, UK./30、738C0030 ISSN 0747-7171 IF:0、525Journal of Symbolic Computation. 《符号与计算杂志》,1985. 12/yr. Harcourt Brace & CO. Ltd.,Foots Cray High Street, Sidcup, Kent DA14 5HP, UKFax: (0181) 309 0807E-mail: ****************.uk31、738C0065 ISSN 0031-3203 IF:1、353 “*”Pattern Recognition. 《图形识别》,1969. 12/yr. Elsevier Science,Regional Sales Office, Customer Support Department,Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: (31) 20 485 3757E-mail: *******************http://www.elsevier.nl32、738C0067 ISSN 0010-4485 IF:1、048Computer-Aided Design. 《计算机辅助设计》,1968. 14/yr.Elsevier Science, Regional Sales Office, Customer Support Department, Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: (31) 20 485 375733、738C0070 ISSN 0045-7949 IF:0、418 “*”Computers & Structures. 《计算机与结构》,1971. 24/yr.K. J. Bathe, Department of Mechanical Engineering,Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA.Tel: 1 617 923 3407Fax: 1 617 923 3408C. H. V. Topping, Department of Mechanics and Chemical Engineering, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, UK.Fax: 44 (0) 131 451 3593http://www.elsevier.nl34、738C0073 ISSN 0045-7906 IF:0、105 “*”Computers & Electrical Engineering. 《计算机与电工》,1973. 6/yr.Elsevier Science, Regional Sales Office, Customer Support Department, Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: (31) 20 485 3757Fax: (31) 20 485 3432E-mail: ********************http://www.elsevier.nl35、738C0074 ISSN 0045-7930 IF:0、679 “*”Computers & Fluids. 《计算机与流体》,1973. 8/yr.Elsevier Science, Regional Sales Office, Customer Support Department, Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: (31) 20 485 3757Fax: (31) 20 485 3432E-mail: ********************http://www.elsevier.nl36、738C0081 ISSN 0898-1221 IF:0、383 “*”Computers & Mathematics with Applications. 《计算机与数学及其应用》1974. 24/yr. Elsevier Science, Regional Sales Office,Customer Support Department, Po Box 211,1000 AE Amsterdam, The Netherlands.Tel: (31) 20 485 3757Fax: (31) 20 485 3432E-mail: ********************http://www.elsevier.nl37、738C0093 ISSN 0306-4379 IF:3、018 “*”Information System. 《信息系统》,1975. 8/yr. Elsevier Science,Regional Sales Office, Customer Support Department, Po Box 211,1000 AE Amsterdam, The Netherlands.Fax: (31) 20 485 3432E-mail: ********************http://www.elsevier.nl38、738C0153 ISSN 0950-7051 IF:0、275 “*”Knowledge-Based Systems. 《知识库系统》,1987. 4/yr.Elsevier Science Bv, Po Box 211, Amsterdam, The Netherlands, 1000 Ae.http://www.elsevier.nl/inca/publications/store/5/2/5/4/4/8/39、738C0164 ISSN 0269-8889 IF:0、707 “*”Knowledge Engineering Review. 《知识工程评价》,1986. 4/yr.118. 00/GBP Cambridge University Press,The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU, UK.Fax: (0223) 315 052E-mail: journals *********************40、738C0177 ISSN 0954-0091 IF:0、964Connection Science. 《连接科学》,1989. 4/yr Carfax Publishing Ltd.,Po Box 25, Abingdon, Oxford Shire, OX14 3UE, UK.Fax: (01235) 401 550E-mail: ***************.uk41、738C0181 ISSN 0954-898X IF:1、333Network: Computation in Neural Systems. 《网络:神经系统计算》,1990. 4/yr. Iop Publishing Ltd, Dirac House,Temple Back, Bristol, England, Bs1 6be./EJ/journal/0954-898X42、738C0192 ISSN 1045-926X IF:0、431Journal of Visual Languages and Computing. 《视觉语言与计算杂志》,1990. 6/yr. Harcourt Brace & Co. Ltd.,Foots Cray High Street, Sidcup, Kent DA14 5HP, UK.Fax: (0181) 309 0807E-mail: ****************.uk43、738C0199 ISSN 1049-8907 IF:0、487Journal of Visualization and Computer Animation. 《显像与计算机动画片制作杂志》,1990. 4/yr. John Wiley & Sons Ltd., Journal Administration,1 Oldlands Way, Bognor Regis, West Sussex PO22 9SA, UK.E-mail: ********************.uk44、738E0032 ISSN 0943-4962 《多媒体系统》,IF:1、290Multimedia Systems. (Text in English). 1993. 6/yr.Spring-Verlag, Heidelberger Platz 3, D-14197 Berlin, Germany.Fax: (030) 827 87 448E-mail: *************************http://www.springer.de45、738GL069 ISSN 0217-5959 IF:0、031ASIA-PACIFIC Journal of Operational Research. 《亚太操作研究杂志》2/yr. Editors: Assoc. Prof. G. Y. Zhao Department of Mathematics,National University of Singapore, Singapore..sg/ORSS/apjor.html46、738KA001 ISSN 0332-7353 IF:0、500Modeling Identification and Control. 《建模、识别与控制》,1980. 4/yr.Mic, Div Eng Cybernetics, Trondheim, Norway, 7034.47、738LB002 ISSN 0010-4655 IF:1、082Computer Physics Communications. 《计算机物理学通讯》,1969. 15/yr.Elsevier Science Bv, Po Box 211, Amsterdam, The Netherlands, 1000 Ae /inca/publications/store/5/0/5/7/1/0/48、738LB003 ISSN 0004-3702 IF:1、683Artificial Intelligence. 《人工智能》,1970. 18/yr.Elsevier Science B. V., Trade Relations Department,Po Box 211, 1000 AE Amsterdam, The Netherlands.Fax: 31 20 6854171E-mail: ********************http://www.elsevier.nl49、738LB004 ISSN 0304-3975 IF:0、468 “*”Theoretical Computer Science. 《理论计算机科学》,1975. 40/yr.Elsevier Science B. V., Trade Relations Department,Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: 31 20 5153210Fax: 31 20 6854171E-mail: ********************http://www.elsevier.nl50、738LB017 ISSN 0924-9907 IF:0、780 “*”Journal of Mathematical Imaging and Vision. 《数学成像与显示杂志》1991. 6/yr. Kluwer Academic Publishers, Journals Department,Distribution Centre, Po Box 322, 3300 AH Dordrecht, The Netherlands.Tel: 31 78 6392392Fax: 31 78 6546474E-mail: *****************51、738LB061 ISSN 0166-5316 IF:0、629 “*”Performance Evaluation. 《性能评价》,1981. 16/yr. Elsevier ScienceB. V., Trade Relations Department,Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: 31 20 5153210Fax: 31 20 6854171E-mail: ********************;www.elsevier.nl52、738LB073 ISSN 0167-9236 IF:0、781 “*”Decision Support Systems. 《决策支持系统》,11/yr.Editor-in-Chief: A. Whinston, MSIS Department,CBA 5-202, University of Texas, Austin, TX 78712-1175, USA./wps/find53、738LB076 ISSN 0167-8396 IF:0、929 “*”Computer-Aided Geometric Design. 《计算机辅助几何设计》,1984.9/yr. Elsevier Science B. V., Trade Relations Department,Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: 31 20 5153210E-mail: ********************http://www.elsevier.nl54、738LB087 ISSN 0885-6125 IF:1、476 “*”Machine Learning. 《机器学习》,1986. 12/yr.Kluwer Academic Publishers, Journals Department, Distribution Centre, Po Box 322, 3300 AH Dorderecht, The Netherlands.Tel: 31 78 6392392E-mail: *****************55、738LB088 ISSN 0920-5691 IF:1、600 “*”International Journal of Computer Vision. 《国际计算机视觉杂志》,1987. 15/yr. Kluwer Academic Publishers, Journals Department,Distribution Centre, Po Box 322, 3300 AH Dordrecht, The Netherlands.Fax: 31 78 6546474E-mail: *****************56、738LB092 ISSN 0921-8542 IF:0、130 “*”Journal of Supercomputing. 《高超速计算机杂志》,1987. 4/yr.Kluwer Academic Publishers, Journals Department, Distribution Centre, Po Box 322, 3300 AH Dordrecht, The Netherlands.Tel: 31 78 6392392Fax: 31 78 6546474E-mail: *****************57、738LB100 ISSN 0924-669X IF:0、493 “*”Applied Intelligence. 《应用智能》,1991. 6/yr. 900. 00/NLG KluwerAcademic Publishers, Journals Department, Distribution Centre,Po Box 322, 3300 AH Dordrecht, The Netherlands.Tel: 31 78 6546471E-mail: *****************58、738LB122 ISSN 0262-8856 IF:0、893Image and Vision Computing. 《图像与视觉计算》,1983. 14/yr.Elsevier Science B. V., Trade Relations Department,Po Box 211, 1000 AE Amsterdam, The Netherlands.Tel: 31 20 5153210E-mail: ********************/inca/publications/store/5/2/5/4/4/3/index.htthttp://www.elsevier.nl59、738LB128 ISSN 1384-5810 IF:1、407Data Mining and Knowledge Discovery. 《数据挖掘与知识发现》,1997.4/yr. Kluwer Academic Publishers, Journals Department, Distribution Centre, Po Box 322, 3300 AH Dordrecht, The Netherlands.Fax: 31 78 6546474E-mail: *****************60、738LE051 ISSN 0010-485X IF:0、667 “*”Computing. (Text in English). 《计算》,8/yr. Springer-VerlagWien, Sachsenplatz 4-6, Postfach 89, A-1201 Wien, Austria.Fax: (0043/1) 3 30 24 2661、738 ISSN 0004-5411 IF:1、078Journal of the ACM. 《美国计算机学会志》,4/yr.Assoc Computing Machinery, 1515 Broadway, New York, NY, 10036./jacm/62、738 ISSN 0018-9162 IF:1、062Computer. 《IEEE计算机杂志》,12/yr.IEEE Computer Soc, 10662 Los Vaqueros Circle,Po Box 3014, Los Alamitos, CA, 90720-1314.二、《EI》收录的外文期刊:1、738B0029-1 ISSN 1049-9652CVGIP:Graphical Models and Image Processing. 《计算机视觉、图示与图像处理:制图模型与图像处理》,1969. 6/yr. Academic Press, Inc.,Journal Subscription Fulfillment Dept., 6277 Sea Harbor Drive,Orlando, FL 32887-4900, USA.Fax: 407-363-96612、738B0029-2 ISSN 1077-3169Graphical Models and Image Processing. 《制图模型与图像处理》,1969.6/yr. Academic Press Inc., USA.Editors-in-Chief: Norman I. Badler and Rama Chellappa.E-mail: ***************/newjour/g/mag02304.html(as CVGIP: Graphical Models and Image Processing. 1049-9652)3、738B0052 ISSN 0011-6963Datamation. 《数据处理》,1955. 24/yr.275 Washington St., Newton, MA 02158, USA.Fax: 303-398-7691.4、738B0067 ISSN 0010-4566Computer Design. 《计算机设计》,1962. 12/yr. Computer Design,Circulation Department, Box 3466, Tulsa, OK 74101, USA.5、738B0079 ISSN 0018-8670IBM Systems Journal. 《国际商用机器公司系统杂志》,1962. 4/yr.International Busimess Machines Corp., USA. Editor: Cene Hofinagle.E-mail: *******************.com/newjour/i/msg02405.html6、738B0100 ISSN 0037-5497Simulation. 《仿真》,1963. 12/yr. Society for Computer Simulation,Box 17900, San Diego, CA 92117, USA.Editor:Vice-President, SCS Publications, Robert Judd, PhD, Ohio University.E-mail: *****************//pubs/siminfo.html7、738B0223 ISSN 0882-1666Systems and Computers in Japan. 《日本系统与计算机》,1970. 14/yr. 1229. John Wiley & Sons, Inc., P. O. Box 836,Bound Brook, NJ 08805, USA.Fax: 03-3556-9763.E-mail: ****************.ne.jp/jpages/0882-16668、738B0288 ISSN 0360-5280Byte. 《字节》,1975. 12/yr. McGraw-Hill Companies, Inc., P. O. 1221Avenue of the Americas, New York, NY 10020, USA.9、738B0100 ISSN 0037-5497Simulation. 1963. 12/yr. Society for Computer Simulation, Box 17900, San Diego, CA 92117, USA. Editor: Vice-President, SCS Publications, Robert Judd, PhD, Ohio University.E-mail: *****************//pubs/siminfo.html10、738B0291 ISSN 0146-5422Online. 《联机》,6/yr. Online Inc.462 Danbury Road, Wilton, CT 06897-2126, USA.11、738B0292 ISSN 0363-6399Data Communications. 《数据通信》,1972. 12/yr.McGraw-Hill Companies, Inc., P. O.1221 Avenue of the Americas, New York, NY 10020, USA.12、738B0309 ISSN 0162-4105Database. 《数据库》,1978. 6/yr. 1970. Bonanza Drive,Suite 219, P. O. Box 70, Park City, UT 84060, USA.13、738B0318 ISSN 0164-1212Journal of Systems & Software. 《系统与软件杂志》,Elsevier ScienceInc.,655 Avenue of the Americas, New York, NY 10010, USA.Fax: 212-633-376414、738B0325 ISSN 0702-0481International Journal of Mini and Microcomputers. 《国际小型与微计算机杂志》,1979. 3/yr. Editor-in- Chief: Dr. B. Furht,Dep. Of Computer Sci. & Eng. Florida AltanticUniversity, Boca Raton, FL 33431, USA.15、738B0337 ISSN 0820-0750Microcomputer Applications. 《微机应用》,1982. 3/yr.ISMM, P. O. Box 2481, Anaheim, CA 92814, USA.16、738B0346 ISSN 0277-0865Computer Security Journal. 《计算机安全杂志》,1981. 2/yr. Computer Security Institute, 600 Harrisan St., San Francisco, CA 94107, USA.E-mail: ***********/17、738B0360 ISSN 1044-789XDr. Dobb’s Journal. 《多布氏杂志》,1976. 12/yr. M & T Publishing,Inc., 501 Galveston Dr., Redwood City, CA 94063, USA.18、738B0405 ISSN 0737-8939PC World. 《个人计算机世界》,1982. 12/yr. PCW Communications, Inc., 501 Second St., 600, San Francisco, CA 94107, USA.19、738B0407 ISSN 0271-4159Computer Graphics World. 《计算机图学界》,1978. 12/yr.PennWell Publishing Co., 1421 South Sheridan,P. O. Box 1260, Tulsa, OK 74101, USA./home/home.cfm20、738B0485 ISSN 0740-6797Transactions of the Society for Computer Simulation. 《计算机仿真学会汇刊》,1984. 4/yr. Society for Computer Simulation.Box 17900, San Diego, CA 92117, USA./pubs/transinfo.htm/21、738B0513 ISSN 0278-9647Computer Technology Review; The Systems Integration Sourcebook.《计算机技术评论》,1981. 16/yr. West World Pioductions, Inc.924 Westwood Blvd., 650, Los Angeles, CA 90024, USA.22、738B0536 ISSN 0742-3136UNIX Review. 《UNIX评论》,1983. 12/yr. 1 Miller FreemanPublication Co., 600 Harrison St., San Francisco, CA 94107, USA.23、738B0556 ISSN 0883-9514Applied Artificial Intelligence. 《应用人工智能》,1986. 4/yr. Taylor &Francis / Hemisphere,1900 Frost Rd., Suite 101, Bristol, PA 19007, USA.24、738B0557 ISSN 0885-7474Journal of Scientific Computing. 《科学计算杂志》,1986. 4/yr.Plenum Publishing Corp., 233 Spring St.,New York, NY 10013-1578, USA.Fax: 212-807-104725、738B0584 ISSN 1094-3420International Journal of High Performance Computing Application.《高性能计算应用国际杂志》,1987. 4/yr. 96pp. 12k.282.00/USD Sage Publications Inc., USA.26、738B0589 ISSN 0894-9077International Journal of Expert Systems. 《国际专家系统杂志》,1987.4/yr. JAI Press, Inc., 55 Old Post Rd.,No. 2, P. O. Box 1678, Greenwich, CT 06836, USA.Fax: 203-661-079227、738B0604 ISSN 0895-6340Computing Systems. 《计算系统》,1988. 4/yr. University of CaliforniaPress,Periodical Dept., 2120 Berkeley Way,Berkeley, CA 94720, USA.Fax: 415-643-7127.Edit: Usenix Association & EUUG.28、738B0658 ISSN 1045-389XJournal of Intelligent Material Systems and Structures. 《智能材料系统与结构杂志》,1990 4/yr. 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Box 90, Rerkshire Rg1 8JL, UK.Fax: 0734-568211.46、738C0029 ISSN 0747- 5632Computers in Human Behavior. 《计算机在人类行为中的应用》,1985.4/yr. 18k, 180. 00/GBP Editorial Office: Robert D Tennyson Dept.Of Educational Psychology, 211A Burton Hall, 178 PillsburyDr., S. E., University of Minnesot Minneapolis, MN 55455, USA.47、738C0031 ISSN 0267-6192Computer Systems Science and Engineering. 《计算机系统科学与工程》,1985. 6/yr. Editor: Wil van Der Aalst,Department of Mathematics and Computing Science, EindhovenUniversity of Technology, P. O. Box 513, NL-5600 MB, Eindhoven,The Netherlands.E-mail: **************.nlhttp://wwwis.win.tue.nl/~wsinwa/csse_special_issue.html48、738C0033 ISSN 0167-7055Computer Graphics Forum. 《计算机图形学论坛》,1982. 4/yr.Editor: David Duke, Department of Mathematical Sciences,University of Bath, UK.E-mail: **************/EG/Publications/CGF49、738C0034 ISSN 1077-2014Real-Time Imaging. 《实时成像》,1995. 6/yr.Harcourt Brace & Co. Ltd., UK. Editors: Phillip A.Laplant and Alrxander D. Stoyenko.E-mail: ***************/newjour/r/msg02194.html50、738C0089 ISSN 0096-0551Computer Languages. 《计算机语言》,1976. 8/yr.c/o National Biomedical Foundation, Georgetown University Medical Center, 3900 Resservoir Road, N. W., Washington, DC20007, USA.51、738C0092 ISSN 0198-9715Computers, Environment and Urban Systems. 《计算机、环境与城市系统》,1975. 6/yr. Editor: P. Longley,Centre for Advanced Spatial Analysis, University College London,1-19 Torrington Place, London, WCIE 6BT.E-mail: *******************.ukhttp://www.elsevier.nl/inca/publications/store/3/0/4/52、738C0103 ISSN 0141-9331Microprocessors and Microsystems. 《微处理机与微型系统》,1978, 10/yr.Hardware Systems and North American Editor: A. K. Somani,Dept. Of Electrical & Computer Engineering, 223 Coover Hall,Iowa State University, Ames, IA 50011, USA.E-mail: ****************Software Editor: J. E. Cooling, 35 Croftway, Markfield,Leicestershire, LE67 9UG, UK.E-mail: *********************.comSection Coordinating Editor Chip ARCHITECTURES: p. W. Thompson,Degree 2 Innovations Ltd. University Gate, Park Row, Bristol BS1 5UB. UK.E-mail: **************************http://www.elsevier.nl/inca/publications/store/5/2/5/4/4/9/53、738C0106 ISSN 0140-3664Computer Communications. 《计算机通讯》,1978. 12/yr.Editor: J. B. Thompson, Troubador Publishing Ltd.,12 Manor Walk, Coventry Road, Market Harborough,Leicester LE16 9PB, UK.E-mail: ************************http://www.elsevier.nl/locate/comcom54、738C0109 ISSN 0965-9978Advances in Engineering Software. 《工程软件进展》,1978. 8/yr.Editors: R. A. Adey, Wessex Institute of Technology,Ashurst Lodge, Ashurst, Southampton SO40 7AA,UK.Fax: 44-1703-292-853E-mail: *******************N. Kamiya, Department of Informatics & Natural Sciences, School ofInformatics and Sciences, Nagoya University, Chikusa-ku, Nagoya 464-01, Japan.A. K. Noor, University of Virginia, Mail Stop 369, NASA Langley Research Center, Hampton, VA 23681, USA.Fax: 1-804-864-8089E-mail: ******************.govhttp://www.elsevier.nl/inca/publications/store/4/2/2/9/1/1/。
时间计算方法
Architecture and Performance Methods ofA Knowledge Support System ofUbiquitous Time ComputationYinsheng ZhangInstitute of Scientific & Technical Information of China, Beijing, ChinaCity University of Hong Kong,Hong Kong, ChinaEmail: zhangyinshengnet@Abstract— An architecture and main performance methods of a knowledge support system of ubiquitous time computation based on relativity are proposed. As main results, modern time theories are described as certain relations of term-nodes in a tree, and some space-time computation models in a large scale and time computation models in different time measurement systems (institutions) are programmed as interfaces for time computation in complex conditions such as time-anisotropic movement systems or gravity-anisotropic environments.Index Terms—Space-Time, Relativity, Real Time Communication, Time Ontology, Time MeasurementI.I NTRODUCTIONTime computation is so ubiquitous nowadays, not only in analyzing texts with time terms, but also in real time computation even in circumstance across time zones or in quantum application such as satellite positioning systems, time-anisotropic movement systems, gravity-anisotropic environments, or space scale in the cosmos. As the relativity theory and quantum mechanics, which we call modern time theories, have made great advances, time computation is desirable to be made on the new time knowledge. It is well known that an ontology made up of specific terms in relations can succinctly represent knowledge homogeneously structured in syntactic pattern and stratified in entailments or in contents with stem-branch relations, and easily be applied to navigate knowledge by relational calculus, so a time knowledge support system based on time ontology with some computational models is proposed here to suffice requirement of time computation based on modern time theories.II.E XTENSION OF T IME E XPRESSIONTime mostly is expressed in a form of natural number and suitable for a unified time measure system in the Earth. For example, Dan Ionescu & Cristian Lambiri[1], E.-R.Orderog & H.Dierks[2], and Merlin [3] respectively gave time definitions or expressions for the real-time system, which, however, relativity of time, time computation models which define how to calculate time units, are omitted. In contrast to some software application fields’ research, some time science organizations give serial time expressions based on modern time theories, among which the International Astronomical Union (IAU,1991) made time definition widely accepted in a reality frame [4] . Thus we need to integrate these definitions and expressions in a complete and standard form for ubiquitous time. To do this, we give a time expression as follows.The physical quantity of time can be expressed as a 4-tuple:T=< D,U,M,I > (1) where,D: Data about time in quantity, it may be numbers or circle physical signals indicating time, or symbols expressing a time in quantity; that is, D∈{ time reading, tick, time number expression}.U: Unit, the measure unit such as “second”,” day”.M: Model, the mathematical formulae, using which you get a time quantity by mathematical computations.I: Institution, it may be indicated by a code which stipulates what unit U is meaningful, from which start time point S an interval can be fixed, according to what model M about time can be computed. So we use I( ) to indicate determining a time physical quantity by some parameters.For example, you say “2 seconds”, you might refer to two units of the Universal Time i.e., of coordinated universal time (CUT, or UTC) set by IAU and the finally arbitrated by the International Telecommunication Union (ITU). Of course, you probably might not refer to that, but to an atomic time (AT), as it may. Both the quantities can be computed by the corresponding models issued by the related organizations. Here, the institution determines the meanings of the time as a physical quantity and gives the computation methods, so we can give an expression similar with a programming expression as T=I(D,U,M), here, T serves as a return value ,and I, a function for the other parameters.Clearly, to set up a knowledge support system, we need to consider this time expression, its elements in the tuple will constitute the main profiles.© 2013 ACADEMY PUBLISHER doi:10.4304/jsw.8.11.2947-2955Figure 1. The architecture of the knowledge support system ofubiquitous time computation.III. A RCHITECTURE OF THE K NOWLEDGE S UPPORTS YSTEM We designed such an architecture for the knowledge support system developed by the author for the time computation in the complex systems.The system mainly made up of the 4 components that ①Time Knowledge Navigation, ② Time Measurement and Computation Models, ③ Time Expression Semantics Computation Models,④ Time Institution Knowledge Texts.Component ① accepts users’ requests for knowledge relating to the time measuring data, for example, a user requests for a model for computing the derivation between its time readings and a time unit in another space or in a time measurement system. The kernel of Component ① is a tree describing time knowledge profiles, say its branches are classifications of the time knowledge in certain relations. It is a catalogue of classification and relations of time knowledge, and also mappings between the classification and the knowledge in Component ② and Component ③. It contains institutions I in (1), which determines Component ② and Component ③ in logic, however, Component ② and Component ③ are listed for directing call not through the nodes of institutions.Component ② is the mathematical models for time measurement and computation, written in software programs and can be called for other time computation programs.Component ③ and ④ are discussed in number V and VI.IV. T IME ONTOLOGY.4. 0 General Description sThe tree in Component ① is a time ontology based on modern time theories for logically showing and savingall the knowledge term nodes in certain relations.These relations are potential information for deeper application such as inference based on relational calculus. On time ontology, most studies focus on time expressions and computations of relations between these expressions. For example, Moen’s time ontology is about time concepts in linguistics [5][6].; Frank etc. came up with a plan and principles building space-time in 4 dimensions and 5 tiers [7]. The typical extant time ontology see WordNet in the part of time, DAML time sub-ontology [8],Time Ontology in OWL built by W3C [9] ,and NASASWEET (Semantic Web for Earth an Environmental Terminology)[10]. In addition, ISO 19111 [11] and ISO 19112[12] set out the conceptual schema for spatial references based on geographic identifiers. This work shows various profiles of data structure of time description, yet has the limitations that(1) Time it describes is in the periphery of the Earth, but not in cosmos large scales;(2) The time properties are unraveled only on non-symmetry (non-back as an arrow), a little on relativity, singularity and quantum property.This might lead to difficulties in computations based on modern time theories.In contrast with this work, the time knowledge tree in Component ① is a time ontology based on modern time theories (hereafter “TOboMTT”, the main branches see attachment) .The nodes between any two levels in top-bottom constitute relations which are propositions (note that when we say “A and B in a certain relation”, it just says a proposition) stating the main frame of modern time theories. So, in essence, we have :TOboMTT={N,R }={Propositions} (2)here, N,R refer to nodes and relations respectively.The root (0- level) and the nodes in the next (1-level) are as followingz TimeSpace-Time Type Time Type Time Property Time Measure Time ExpressionThe root “Time” constitutes “has ” relations with the nodes in the 1-level. That is, “Time has the Space-Time Types”, “Time has the Time Types”, “Time has the Time Properties”, “Time has the Time Measures”, “Time has the Time Expressions”. These relations are basic profiles of the up-to-date study on time.The relations of the nodes between the 1 and 2 levels continue such propositions of those relations between 0 and 1 levels, for example, we can say “Time has the Space-Time Types like Euclid Space-Time”, here, “Euclid Space-Time” just is a node in the 2nd level. Thus,© 2013 ACADEMY PUBLISHERthe relations between the 1 and 2 levels are “includes ”, like “Space-Time Type includes Euclid Space-Time”. In the following contexts, we intuitively explain the main nodes which express some important assertions of modern time theories.4. 1 SPACE-Time TYPEAccording to Einstein’s field equation, space andtime are integrated. So we must take space as a parameterof time considering the space-time type. Einstein’s fieldequation see (3) [13]1()+=82R Rg g T αβαβαβαβ−Λπ (3)Here, α and β are space-time dimensions, i.e., α, β=0,1,2,3 and 0 denotes time for the left expression; R αβ is Ricci tensor, it is a 4×4 matrix of the 16 components ofsecond order space-time curvature, R is scalar curvature, g αβ is a 4×4 matrix of metric tensor, Λ is cosmological constant, T αβ is energy-momentum tensor, a 4×4 matrixtoo.From (3), we get (4), i.e., the differentiation of square of space-time intervals:2=ds g dx dy αβαβ (4) here, x,y are curvilineal coordinates, s is space-time interval. (4) adopts Einstein summation convention, normally like in physics, that a repeated index (α or β ) implies summation over all values of that indexed. (3) and (4) are well confirmed by some experiments in the scale 10-13 cm (the radius of a fundamental particle) to 1028 cm (the radius of the universe). A space-time type normally defined by a solution of the equations (3) or (4).See some basic nodes: Space-Time Type Euclidean space-time (absolute time) Riemannian space-time Inertial reference frame space-time Non-inertial reference frame space-time Friedmann- Walke space-time…… If (3) or (4) are determined as the nonlinear partial differential equations about g αβ , we call s is Riemannian space-time, which means space-time is of curvature and might not be flat (flatness is just a special instance, i.e., Minkowski space-time, in which gravity is neglected, it is regarded as inertial). In (3) or (4), if the time in different space places is described as absolutely not different , and independently from its different places and velocities, the space-time is Euclidean space-time or Newton space-time. Friedmann-Lemaître-Robertson-Walker space-time, simply Robertson-Walker space-time [14][15] , put forwarded by Robertson and Walker, and meet the inference of Friedman [16] and Lamaitre [17] , describes homogeneous and isotropic space-time in a non-inertial system, for which, cosmological curvature k and cosmological time t are introduced into (3) or (4). k takes 3 constants 0,1,-1 representing 3 possible space-time types: flatness, positive curvature and negative curvature. If R in (3) is a constant, Robertson-Walker space-time will become some special instance: when R =0, itwill be Minkowski space-time; R >0, de_Sitter space-time;R <0, anti-de_Sitter space-time. Bianchy I space-time is more general than Robertson-Walker that the space-time is homogeneousbut might be anisotropic [18]. Taub-NUT space-time adds magnetic and electric parameters into (3) or (4) [19]. Godel space-time adds rotationally symmetric axis into (3) or (4) [20]. Rindler space-time expresses such space-time determined by inertial system and non-inertial system [21][22]. In some special cases, R is not easy to be determined. To solve (3) or (4), some parameters are given for specialtypes of space-time. These special types include spherical and axial space-time, and time’s elapse may be neglected for a space spot. For (4), Schwarzschild space-time [23] isspherically symmetric beyond a mass sphere. A spherewith great mass and a radius less than Schwarzschild radius is a black hole, which is thought to bear only 3 kinds of information of mass, charge and angular momentum. Schwarzschild black hole is considered as one with only mass, while Ressner-Nordstrom black hole, named as Ressner-Nordstrom space-time, with mass and charge [24][25]; Kerr black hole, named as Kerr space-time with mass and angular momentum [26]; Kerr-Newmanblack hole, named as Kerr-Newman space-time [27], simultaneously have information of mass, charge and angular momentum. Some spherically symmetric space-time like Vaidya space-time [28] and Tolman space-time [29] consider time as the variable of the function of mass and curvature. As an axial metric space-time, Weyl-Levi-Civita space-time [30] is typical. . 4. 2 Time TYPEWhen we solely study time, we can primarily dividetime into the 3 types: Proper time Coordinate time Cosmological time Proper time is the elapsed between two events as measured by a clock that passes through both events. In other words, proper time value is from the real readings of the clock set by an observer in a definite space spot (ifthe measured body moves, then the clock spot and the moved body’s end spot are considered as one area for the two spots are so near for a large scale space). © 2013 ACADEMY PUBLISHERCoordinate time is integrated time under a coordinate system. It is not a real readings for a special spot (the difference between the different spots in the system is neglected), but a stipulated (calculated that it should be) time in the system. Proper time multiplied by (1- v2/c2)-2 is coordinate time (v is the velocity of the body, in which an implied observer is, c is light velocity). If we set a clock in a universe coordinate system indicating the integrated time, it would indicate the universal time (t in Robertson-Walker equation).The proper time in the Earth can be expressed in various forms as the follows.Ephemeris Time (ET) [31] was defined in principle by the orbital motion of the Earth around the Sun. Here, ephemeris is based on Julian calendar which had been reformed to be Gregorian calendar lasted to the nowadays.True solar time (apparent solar time) is given by the daily apparent motion of the true, or observed, Sun. It is based on the apparent solar day, which is the interval between two successive returns of the Sun to the local meridian [32].Mean solar time is the mean values of measured time of the intervals between two Sun passing an identical meridian [33].Sidereal Time is based on a sidereal day; a sidereal day is a time scale that is based on the Earth's rate of rotation measured relative to the fixed stars, normally to the Sun [34]. Sidereal time may be Greenwich Sidereal Time (GST) which calculated by Greenwich Royal Observatory in mean data or Local Sidereal Time (LST) which is computed by adding or subtracting the numbers of timezone [35] .Universal Time (UT) is computed by truly measured time data based on rotation of the Earth, it is a Greenwich Mean Time (GMT) and computed from the start of a midnight of Prime Meridian at Greenwich, and it has different versions such as UT0,UT1,UT2 and Coordinated Universal Time (UTC) for the computations from varying data on non-exact time scales of the Earth rotation. UT0 is Universal Time determined at an observatory by observing the diurnal motion of stars or extragalactic radio sources. It is uncorrected for the displacement of Earth's geographic pole from its rotational pole. This displacement, called polar motion, causes the geographic position of any place on Earth to vary by several metres, and different observatories will find a different value for UT0 at the same moment.UT1 is the principal form of Universal Time. While conceptually it is mean solar time at 0° longitude, precise measurements of the Sun are difficult. UT1R is a smoothly tuned version of UT1, filtering out periodic variations due to tides. UT2 is a smoothed version of UT1, filtering out periodic seasonal variations. UTC is an atomic timescale that approximates UT1. It is the international standard on which civil time is based [36].Atomic time applies the principle of stimulated atom radiation in a constant frequency. The Thirteenth General Conference of Weights and Measures define a second that "the duration of 9,192,631,770 periods of the radiation corresponding to the transition between the two hyperfine levels of the ground state of the caesium 133 atom [37] ". That is a unit of International Atomic Time (ATI).The results of atomic time computed by different local laboratories are called local atomic time.Dynamical Time (DT) [38] is inferred from the observed position of an astronomical object via a theory of its motion, ET is a DT based on revolution of the Earth in replace of UT based on rotation of the Earth meet Newton’s time theory; to meet Einstein’s time theory IAU builds two versions of ET respectively in the system of Terrestrial Dynamic Time (TDT) Barycentric Dynamical Time (TDB).Local civil time is the corrected version of UTC by adding timezone numbers and adjusting daylight saving time [35] .Coordinate time includes centroid coordinate time and Earth-centered coordinate time, they are set by IAU.4. 3 Time propertyThe time properties are divided into 4 kinds as follows.Time PropertyAsymmetryRelativitySingularityQuantum propertyAsymmetry is the property human first discovered, it refers to what seems to be an arrow went out in one direction and not back.Relativity means anisotropy against gravity or in a light-like velocity.Singularity is the property of some places, where the present physical laws break down, or it can be thought of as the property of edge of space-time [39].The quantum property of time refers to that of time in the particle-scale, where time appears the stranger phenomena far from the macro-scale as we see. For example, the former -latter sequence in macro-scale might be isochronous in the quantum –scale [40].4. 4 Time measure4. 4.1 CoordinatorThe space-time expressed in (3) or (4) can’t always be indicated by Cartesian system, mostly due to some properties which are difficult to be indicated by Cartesian system, and also due to the singularity in the space-time which normally cannot be indicated by the real number system. So two kinds of coordinates are mainly introduced, they are general coordinates and special coordinates. The former are popular in common sense, and transforming them for a special purpose we get the latter----special coordinates, which mainly for describing some new metrics -solutions of (3), (4) with some© 2013 ACADEMY PUBLISHERsingularity variables, or for some particular space-time areas.The coordinates special for the metrics are introduced as follows.Schwarzschild coordinate indicates spherical symmetry, it sometimes becomes degeneratation of some more general conditions. Schwarzschild coordinate uses sphere coordinate with the radius r≠2GM/C2 and r≠0, here , G is universal gravitational constant, M is the mass. The coordinate is divided into two areas by r >2GM/C2 and r <2GM/C2 and leads to the two metrics in (3): g00= - (1-2GM/rC2) and g11= (1-2GM/rC2) -1.In Schwarzschild coordinate, there is not the expression that r=2GM/C2 (this is a singularity), but tortoise coordinate covers this singularity.Eddington coordinate does not diverge in r=2GM/C2 and r=0 by the linear transformation of the variables.Kruskal coordinate covers r=2GM/C2 and r=0 too, and more general in indicating space-time than tortoise and Eddington coordinate .Lemaitre coordinate covers r=2GM/C2 with a different method to Kruskal coordinate.Rindler coordinate indicates the space-time determined by both inertial and non-inertial system.Weyl coordinate indicates the function of metric and allows to indicate imaginary numbers.Fermi normal coordinate indicates space-like geodesic which is the trajectory that its covariant differential is 0 for (4). “space-like” denotes the velocity in the area is far less than light speed. And its time axis indicates proper time for a non-inertial or locally inertial conditions.Harmonic coordinate indicates harmonic conditions that coordinates in curved space satisfy a D' Alembert equation, it is a Cartesian-coordinate-like one in curved space.Local inertial coordinate indicates Minkowski space-time.The special coordinates for the particular space-time areas are introduced as follows.Centroid coordinate (center-of-mass coordinate system) is one taking the centre of a space area as the origin of coordinate. These coordinates include non-rotating geocentric reference system, rotating geocentric reference system, Barycentric Celestial Reference System (BCRS), International Celestial Reference System (ICRS).Non-rotating geocentric reference system takes the Earth centre as the origin of coordinate . IAU provides the metric and methods for computing proper time.Rotating geocentric reference system is supposed as rotated with the Earth together, its X3 axis is the rotation axis of the Earth, and it is taken as International Terrestrial Reference System (ITRS) by IAU. For the rotation direction is not considered, the time in non-rotating geocentric reference system and rotating geocentric reference system is the same.Barycentric Celestial Reference System (BCRS) is recommended by IAU, its origin is the mass centre of the solar system,its third axis is approximately the rotation axis of the Earth.International Celestial Reference System is a centroid coordinate, it is made up of circle of right ascension and circle of declination of approximate 600 quasars, the coordinates are provided by International Earth Rotation and Reference Systems Service (IERS) Most general coordinates are introduced by the mathematical textbooks, so they are omitted here.4. 4.2 Measure UNITThe frame of time measure unit is as follows:Measure of timeUnits of measureTime intervalDynamical time intervalDuration fixed time intervalTime interval with the duration fixedby an ephemerisIntegral time scaleDynamical time scale is referred to as measured values of time parameters by physical quantities in a physical system. Basically, a proper time interval is a dynamical time scale.The main units of dynamical time scales in the ontology are concerned with ephemeris time units. A second in ephemeris time is defined as the fraction 1/31,556,925.9747 of the tropical year in Julian calendar for 1900 January 0 at 12 hours ephemeris time by International Committee for Weights and Measures (CIPM), from this unit, Julian century, year, week and day can be worked out.An integral time scale is accumulated value copied from a contracted time start point, for example, atomic time scale. So it may be proper time or coordinate time.V. T IME MEASURE AND COMPUTATION MODELSComponent ②is the set of the measure and computation models, which are from two resources: one is from the institutions put forward by some organizations such as IAU stipulating how to measure and computation, another resource is from the exact solutions of the (3) or (4).The models are programmed in Mathematica as the Application Programming Interface (API) so that a users’ programs can call these API.EXAMPLE 1[41]: a model (group) to compute a coordinated universal timeUTC (t) – TAI(t) = ns (5)UTC (t) –UT 1(t)=<0.9s; (6) Here, UTC(t) is a time expressed in coordinated universal time’ institution unit, TAI(t) means a time of Atomic Time International, n is natural number; s is the second, UT 1(t) is a time expressed in UT 1.© 2013 ACADEMY PUBLISHEREXAMPLE 2 is calling from a user’s application for the interface of a model, which is drawn from reference [42] and re-wrote by the author, to get an exact solution of Einstein’s field equation given Roberson-Walker Metric:1 /*An application from users in pseudo-code callingthe model-interface. See the tree in the attachment*/2 e num Space-Time in non- inertial system3 {4 B ianchi I Space-Time,5……6R obertson-WalkerSpace-Time7 /*Here, all the 16 Space-Time in non- inertialsystem in the tree enumerated */8 } Metric[16];9 for(i=0;i<16;i++){10 switch(Metric [i])11 case Robertson-Walker Space-Time:12 input and assign vector:13 v = {t, r, e, phi};141516 M = {-1, R[t]^2/(1 - K (r^2), (r^2) (R [t]^2), (r^2) (Sin[e]^2) (R [t]^2)};Call Einstein [M, v]}“Einstein.m”1 E instein [g_, v_] := Block[2 {invsg, dg1, dg2, dg3, Christf2, dChristf2, Ruv1,Ruv2, Ruv3, Ruv4, RicciTensor, R, EMTensor} 3 EMTensor = {}; (*Save return value.*)(*Calculate the inverse metric of g.*)4 g=DiagonalMatrix[M];5 invsg = Inverse[g];(*Calculate the affine connection.*)6 dg1 = Outer[D, g, v];7 dg2 = Transpose[dg1, {1, 3, 2}];8 dg3 = Transpose[dg1, {2, 3, 1}];9 Christf2 = (1/2) invsg.(dg1 + dg2 - dg3);(*Calculate the Ricci tensor.*)10 dChristf2 = Outer[D, Christf2, v];11 Ruv1 = Table[Sum[dChristf2[[k, i, k, j]], {k, 4}],{i, 4}, {j, 4}];12 Ruv2 = Table[Sum[dChristf2[[k, i, j, k]], {k, 4}],{i, 4}, {j, 4}];13 R uv3 = Table[Sum[Christf2[[k, i, j]] Christf2[[h,k, h]], {k, 4}, {h, 4}], {i, 4}, {j, 4}];14 Ruv4 = Table[ Sum[Christf2[[k, i, h]] Christf2[[h,j, k]], {k, 4}, {h, 4}], {i, 4}, {j, 4}];15 RicciTensor = Ruv1 - Ruv2 - Ruv3 + Ruv4;(*Calculate the Curvature Scalar.*)16R = Sum[invsg[[i, i]] RicciTensor[[i, i]], {i, 4}];(*Calculate the field equation left part.*)17EMTensor = RicciTensor - (1/2) g R ;18return [EMTensor]19]20End[]21EndPackage[]This program is divided into two parts: the first part is user’s input for computation, which is space-time dimensions v in a spherical coordinator, in which, t is the cosmological time (see 4. 2 Time Type), M is Roberson-Walker Metric. Users can input similar metrics for calling the function Einstein[ ],which is saved in the second part, a document Einstein.m, starting from the sentence BeginPackage["Einstein`"]. mathlink.h in VC++ enables to run Mathematica programs in VC++ environment The section Block[] is a function of local variables for calling.Outer[] is to give the partial derivative ∂f/∂x.Transpose[dg1, {1, 3, 2}] is to transposes dg1 so that the k th level in dg1 is the n k th level in the result.D [] is to get partial differential.Table [] is to generate a list of the expression Sum[].Sum[] is to get sum.The line 19 is the computation result of left part of (3), yet the cosmological constant is omitted. The right part of (3) is considered as zero.VI. M ECHANISM AND R UNNING OF T HE A RCHITECTURETOboMTT is designed to be a tree not only for satisfying the structure and classification of knowledge of time, but also for developing the knowledge in Web Ontology Language (OWL), which is based on Resource Description Framework (RDF) in a tree. Thus we can divide TOboMTT into some sub-trees and further expressed them in OWL or RDF. Figure 2 is a sample of Class—SubClass relation in RDF. As a result, navigation of knowledge of time, based on TOboMTT, become navigation of resources and serves, based on eXtensible Markup Language (XML) compatible with both OWL and RDF.A query for a sub-class or property value will give the corresponding answer by rational calculus on a XML scheme. For the example in Figure 2, “Space-Time Type includes Euclid Space-Time ” will be the answer for the query “What kind does the Space-Time Type include?” Therefore, query and answer is the first and direct results of navigation of knowledge of time by TOboMTT.<?xml version="1.0"?>© 2013 ACADEMY PUBLISHER。
机器人顶刊论文
机器人顶刊论文机器人领域内除开science robotics以外,TRO和IJRR是机器人领域的两大顶刊,最近师弟在选择研究方向,因此对两大顶刊的论文做了整理。
TRO的全称IEEE Transactions on Robotics,是IEEE旗下机器人与自动化协会的汇刊,最新的影响因子为6.123。
ISSUE 61 An End-to-End Approach to Self-Folding Origami Structures2 Continuous-Time Visual-Inertial Odometry for Event Cameras3 Multicontact Locomotion of Legged Robots4 On the Combined Inverse-Dynamics/Passivity-Based Control of Elastic-Joint Robots5 Control of Magnetic Microrobot Teams for Temporal Micromanipulation Tasks6 Supervisory Control of Multirotor Vehicles in Challenging Conditions Using Inertial Measurements7 Robust Ballistic Catching: A Hybrid System Stabilization Problem8 Discrete Cosserat Approach for Multisection Soft Manipulator Dynamics9 Anonymous Hedonic Game for Task Allocation in a Large-Scale Multiple Agent System10 Multimodal Sensorimotor Integration for Expert-in-the-Loop Telerobotic Surgical Training11 Fast, Generic, and Reliable Control and Simulation of Soft Robots Using Model Order Reduction12 A Path/Surface Following Control Approach to Generate Virtual Fixtures13 Modeling and Implementation of the McKibben Actuator in Hydraulic Systems14 Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving15 Robust Planar Odometry Based on Symmetric Range Flow and Multiscan Alignment16 Accelerated Sensorimotor Learning of Compliant Movement Primitives17 Clock-Torqued Rolling SLIP Model and Its Application to Variable-Speed Running in aHexapod Robot18 On the Covariance of X in AX=XB19 Safe Testing of Electrical Diathermy Cutting Using a New Generation Soft ManipulatorISSUE 51 Toward Dexterous Manipulation With Augmented Adaptive Synergies: The Pisa/IIT SoftHand 22 Efficient Equilibrium Testing Under Adhesion and Anisotropy Using Empirical Contact Force Models3 Force, Impedance, and Trajectory Learning for Contact Tooling and Haptic Identification4 An Ankle–Foot Prosthesis Emulator With Control of Plantarflexion and Inversion–Eversion Torque5 SLAP: Simultaneous Localization and Planning Under Uncertainty via Dynamic Replanning in Belief Space6 An Analytical Loading Model for n -Tendon Continuum Robots7 A Direct Dense Visual Servoing Approach Using Photometric Moments8 Computational Design of Robotic Devices From High-Level Motion Specifications9 Multicontact Postures Computation on Manifolds10 Stiffness Modulation in an Elastic Articulated-Cable Leg-Orthosis Emulator: Theory and Experiment11 Human–Robot Communications of Probabilistic Beliefs via a Dirichlet Process Mixture of Statements12 Multirobot Reconnection on Graphs: Problem, Complexity, and Algorithms13 Robust Intrinsic and Extrinsic Calibration of RGB-D Cameras14 Reactive Trajectory Generation for Multiple Vehicles in Unknown Environments With Wind Disturbances15 Resource-Aware Large-Scale Cooperative Three-Dimensional Mapping Using Multiple Mobile Devices16 Control of Planar Spring–Mass Running Through Virtual Tuning of Radial Leg Damping17 Gait Design for a Snake Robot by Connecting Curve Segments and ExperimentalDemonstration18 Server-Assisted Distributed Cooperative Localization Over Unreliable Communication Links19 Realization of Smooth Pursuit for a Quantized Compliant Camera Positioning SystemISSUE 41 A Survey on Aerial Swarm Robotics2 Trajectory Planning for Quadrotor Swarms3 A Distributed Control Approach to Formation Balancing and Maneuvering of Multiple Multirotor UAVs4 Joint Coverage, Connectivity, and Charging Strategies for Distributed UAV Networks5 Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle6 Agile Coordination and Assistive Collision Avoidance for Quadrotor Swarms Using Virtual Structures7 Decentralized Trajectory Tracking Control for Soft Robots Interacting With the Environment8 Resilient, Provably-Correct, and High-Level Robot Behaviors9 Humanoid Dynamic Synchronization Through Whole-Body Bilateral Feedback Teleoperation10 Informed Sampling for Asymptotically Optimal Path Planning11 Robust Tactile Descriptors for Discriminating Objects From Textural Properties via Artificial Robotic Skin12 VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator13 Zero Step Capturability for Legged Robots in Multicontact14 Fast Gait Mode Detection and Assistive Torque Control of an Exoskeletal Robotic Orthosis for Walking Assistance15 Physically Plausible Wrench Decomposition for Multieffector Object Manipulation16 Considering Uncertainty in Optimal Robot Control Through High-Order Cost Statistics17 Multirobot Data Gathering Under Buffer Constraints and Intermittent Communication18 Image-Guided Dual Master–Slave Robotic System for Maxillary Sinus Surgery19 Modeling and Interpolation of the Ambient Magnetic Field by Gaussian Processes20 Periodic Trajectory Planning Beyond the Static Workspace for 6-DOF Cable-Suspended Parallel Robots1 Computationally Efficient Trajectory Generation for Fully Actuated Multirotor Vehicles2 Aural Servo: Sensor-Based Control From Robot Audition3 An Efficient Acyclic Contact Planner for Multiped Robots4 Dimensionality Reduction for Dynamic Movement Primitives and Application to Bimanual Manipulation of Clothes5 Resolving Occlusion in Active Visual Target Search of High-Dimensional Robotic Systems6 Constraint Gaussian Filter With Virtual Measurement for On-Line Camera-Odometry Calibration7 A New Approach to Time-Optimal Path Parameterization Based on Reachability Analysis8 Failure Recovery in Robot–Human Object Handover9 Efficient and Stable Locomotion for Impulse-Actuated Robots Using Strictly Convex Foot Shapes10 Continuous-Phase Control of a Powered Knee–Ankle Prosthesis: Amputee Experiments Across Speeds and Inclines11 Fundamental Actuation Properties of Multirotors: Force–Moment Decoupling and Fail–Safe Robustness12 Symmetric Subspace Motion Generators13 Recovering Stable Scale in Monocular SLAM Using Object-Supplemented Bundle Adjustment14 Toward Controllable Hydraulic Coupling of Joints in a Wearable Robot15 Geometric Construction-Based Realization of Spatial Elastic Behaviors in Parallel and Serial Manipulators16 Dynamic Point-to-Point Trajectory Planning Beyond the Static Workspace for Six-DOF Cable-Suspended Parallel Robots17 Investigation of the Coin Snapping Phenomenon in Linearly Compliant Robot Grasps18 Target Tracking in the Presence of Intermittent Measurements via Motion Model Learning19 Point-Wise Fusion of Distributed Gaussian Process Experts (FuDGE) Using a Fully Decentralized Robot Team Operating in Communication-Devoid Environment20 On the Importance of Uncertainty Representation in Active SLAM1 Robust Visual Localization Across Seasons2 Grasping Without Squeezing: Design and Modeling of Shear-Activated Grippers3 Elastic Structure Preserving (ESP) Control for Compliantly Actuated Robots4 The Boundaries of Walking Stability: Viability and Controllability of Simple Models5 A Novel Robotic Platform for Aerial Manipulation Using Quadrotors as Rotating Thrust Generators6 Dynamic Humanoid Locomotion: A Scalable Formulation for HZD Gait Optimization7 3-D Robust Stability Polyhedron in Multicontact8 Cooperative Collision Avoidance for Nonholonomic Robots9 A Physics-Based Power Model for Skid-Steered Wheeled Mobile Robots10 Formation Control of Nonholonomic Mobile Robots Without Position and Velocity Measurements11 Online Identification of Environment Hunt–Crossley Models Using Polynomial Linearization12 Coordinated Search With Multiple Robots Arranged in Line Formations13 Cable-Based Robotic Crane (CBRC): Design and Implementation of Overhead Traveling Cranes Based on Variable Radius Drums14 Online Approximate Optimal Station Keeping of a Marine Craft in the Presence of an Irrotational Current15 Ultrahigh-Precision Rotational Positioning Under a Microscope: Nanorobotic System, Modeling, Control, and Applications16 Adaptive Gain Control Strategy for Constant Optical Flow Divergence Landing17 Controlling Noncooperative Herds with Robotic Herders18 ε⋆: An Online Coverage Path Planning Algorithm19 Full-Pose Tracking Control for Aerial Robotic Systems With Laterally Bounded Input Force20 Comparative Peg-in-Hole Testing of a Force-Based Manipulation Controlled Robotic HandISSUE 11 Development of the Humanoid Disaster Response Platform DRC-HUBO+2 Active Stiffness Tuning of a Spring-Based Continuum Robot for MRI-Guided Neurosurgery3 Parallel Continuum Robots: Modeling, Analysis, and Actuation-Based Force Sensing4 A Rationale for Acceleration Feedback in Force Control of Series Elastic Actuators5 Real-Time Area Coverage and Target Localization Using Receding-Horizon Ergodic Exploration6 Interaction Between Inertia, Viscosity, and Elasticity in Soft Robotic Actuator With Fluidic Network7 Exploiting Elastic Energy Storage for “Blind”Cyclic Manipulation: Modeling, Stability Analysis, Control, and Experiments for Dribbling8 Enhance In-Hand Dexterous Micromanipulation by Exploiting Adhesion Forces9 Trajectory Deformations From Physical Human–Robot Interaction10 Robotic Manipulation of a Rotating Chain11 Design Methodology for Constructing Multimaterial Origami Robots and Machines12 Dynamically Consistent Online Adaptation of Fast Motions for Robotic Manipulators13 A Controller for Guiding Leg Movement During Overground Walking With a Lower Limb Exoskeleton14 Direct Force-Reflecting Two-Layer Approach for Passive Bilateral Teleoperation With Time Delays15 Steering a Swarm of Particles Using Global Inputs and Swarm Statistics16 Fast Scheduling of Robot Teams Performing Tasks With Temporospatial Constraints17 A Three-Dimensional Magnetic Tweezer System for Intraembryonic Navigation and Measurement18 Adaptive Compensation of Multiple Actuator Faults for Two Physically Linked 2WD Robots19 General Lagrange-Type Jacobian Inverse for Nonholonomic Robotic Systems20 Asymmetric Bimanual Control of Dual-Arm Exoskeletons for Human-Cooperative Manipulations21 Fourier-Based Shape Servoing: A New Feedback Method to Actively Deform Soft Objects into Desired 2-D Image Contours22 Hierarchical Force and Positioning Task Specification for Indirect Force Controlled Robots。
Performance Testing of the Desdemona Motion System
AIAA Modeling and Simulation Technologies Conference and Exhibit 20 - 23 August 2007, Hilton Head, South CarolinaAIAA 2007-6472Performance Testing of the Desdemona Motion SystemManfred Roza1, Mark Wentink2 and Philippus Feenstra3 TNO Human Factors, Soesterberg, The NetherlandsTP PT TP PT TP PTIn the spring of 2007 TNO Human Factors together with AMST Systemtechnik GmbH have completed the development of their newest research simulator, the Desdemona, in The Netherlands. The Desdemona research simulator features a unique motion system not seen elsewhere in the world. Its serial design and geometrical dimensions give the motion system a large cylindrical motion space and a broad range of dynamic performance capabilities, which go beyond those of a classical Stewart platform. Like any other motion-base simulator the Desdemona motion system is driven by motion filters that transform the various simulation model outputs into safe and optimal motion cues. For the development of these motion filters it is necessary to exactly determine the dynamic performance characteristics of Desdemona and check whether these characteristics meet the specified motion system requirements. This paper describes the test protocol to measure, specify and verify the dynamic performance characteristics of the Desdemona motion system. The performance test protocol builds upon and extends the classical synergistic motion system test approaches, like the AGARD standard, to suite the specific Desdemona motion system capabilities.NomenclatureM&S DOF IMU MCC PLC = = = = = = modeling and simulation degree of freedom inertial measurement unit motion control computer programmable logical controller central yaw axisψ centrR Hφcab ψ cab θ cab= radial axis = heave axis = cabin roll axis = cabin yaw axis = cabin pitch axisI. IntroductionTNO Defense, Safety & Security in the Netherlands has a long tradition in research into modeling and simulation (M&S) technology and applications. The M&S effort of TNO Human Factors is centered in the area of flight, driving and ship simulators for human performance, training and behavior research. Over the years TNO Human Factors has specialized in human perception research ranging from visual & vestibular research to motion sickness and fidelity, to 3D-audio and haptic interfacing experiments1,4,5,6,7,8,9. To better facilitate this kind of research and the spatial disorientation training for the Royal Netherlands Air Force, TNO Human Factors initiated the development of a new research simulator, the Desdemona11,12,13.P P P PIn co-operation with AMST Systemtechnik GmbH, TNO Human Factors completed the development of the Desdemona simulator, in the late spring of 2007. The Desdemona research simulator features a unique and special designed non-synergistic motion system with six degrees of freedom (DOF). Its serial design and geometrical1TPResearch Scientist, TNO Defence, Safety & Security, Human Factors Department, manfred.roza@tno.nl, AIAA Member. Research Scientist, TNO Defence, Safety & Security, Human Factors Department, mark.wentink@tno.nl, AIAA Member. 3 Research Scientist, TNO Defence, Safety & Security, Human Factors Department, philippus.feenstra@tno.nl.PT HTU UTH2TP TPPTHTUUTHPTHTUUTH1 American Institute of Aeronautics and AstronauticsCopyright © 2007 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.dimensions give the motion system a large cylindrical motion space and a broad range of dynamic performance capabilities. One of the unique motion capabilities is the ability to combine onset cueing like a classical Stewart or hexapod platform with sustained acceleration cueing as found in dynamic flight simulators. Furthermore, the rotating gimbal system gives the Desdemona motion system the possibility to replicate unusual attitudes and large attitude changes one-to-one. The motion system houses a cabin, which is equipped with a 120 degree visual system. The modular hard and software design of the cabin enables fast reconfiguration of the interior and the installation of human machine interfaces. This makes the Desdemona simulator potentially suitable for a wide range of research applications including unusual aircraft and rotorcraft maneuvers, suburban, urban and terrain driving simulation, motion perception and cueing, spatial disorientation, motion sickness, and human-performance in artificial gravity conditions.Figure 1. The Desdemona Research Simulator Exterior Like all other motion-base simulators the Desdemona motion system is driven by motion filters that transform the various simulation model outputs into safe and optimal motion cues 13, 14. For the development of these motion filters it is necessary to exactly determine the Desdemona dynamic performance characteristics. In addition, the measured performance is used to verify whether it meets the specified motion system requirements. This paper describes the test protocol to measure, specify and verify the dynamic performance characteristics of the Desdemona motion system. The paper starts in Section II with a presentation of the Desdemona motion system configuration and properties. Next the rationale and top-level design of the dynamic motion test protocol are discussed (Section III). This protocol builds upon and extends the classical synergistic motion system test approaches described in literature such as AGARD and ASC/MIL standards to suite the specific Desdemona motion system capabilities 15,16. In two subsequent sections the various tests and associated performance metrics of the protocol are discussed. These tests are divided in two categories. The first category is the single axis tests (Section IV). These tests comprise timedomain tests for motion system position, velocity and acceleration limits and signal tracking accuracy, and frequency domain system identification based tests. Multi-axis performance tests form the second category of tests (Section V). These tests are typical for serial motion systems, like the Desdemona, where independent axes have to be moved in conjunction to reproduce the desired motion cues during simulation. Lessons-learned and experiences from the first execution of the Desdemona motion performance test protocol are presented in Section VI. The paper ends in Section VII with conclusions and future work to motion system performance testing in relation to research into motion system fidelity, perception and requirements.2 American Institute of Aeronautics and AstronauticsII. Desdemona Motion System DescriptionA. Motion System Configuration and Characteristics Unlike conventional motion systems such as the Stewart platform, the Desdemona motion system is not a synergistic or parallel robotic system. Instead the Desdemona has a non-synergistic or a serial motion system with six axes that can be moved independently (Figure 2). These six axes are respectively called: central yaw (ψ centr ), radius (R), heave (H), cabin roll ( φcab ), cabin yaw (ψ cab ) and cabin pitch ( θ cab ). The Desdemona cabin is suspended in a fully gimbaled 3DoF system ( φcab ,ψ cab and θ cab ), which allows unlimited cabinrotation around any arbitrary axis in space. This gimbaled system is mounted in a heave system (H) that translates the gimbal system and the cabin in the vertical plane. The heave/gimbal system can be moved horizontally over a sledge; the radius (R). The sledge itself can be rotated unlimited in the middle around a vertical axis (ψ centr ); the central yaw axis. This central yaw axis in combination with the radius gives the Desdemona motion system the capability of sustained g-load generation up to 3g.Figure 2. The Desdemona Motion System DOFAll the axes are driven by electric servo-systems. The required performance characteristics for each of these Desdemona axes in terms of the maximum attainable position, velocity and acceleration are given in the table below.Central Yaw Max. position Max. Velocity Max. Acceleration Radius Heave Cabin Roll Cabin Yaw Cabin Pitch>360P0P±4m 3.2 m/s 4.9 m/s2P±1m 2.0 m/s 4.9 m/s2>360P0P>360P0P>3600P P155 /sP P0180 /sP P0180 /sP P0180 /sP P045 /sP P P0290 /sP P P02P90 /sP P P02P90 /s2P P P P0Table 1 Maximum Position, Velocity and Acceleration Characteristics of the Desdemona Motion System B. Motion Control, Measurement and Integrated Test Systems The Desdemona motion platform is controlled by a motion control computer (MCC), which runs on a standard PC with a real-time operating system. The MCC hosts all necessary control logic, safety and communication I/O software to safely operate the Desdemona motion system. An Ethernet network with a dedicated protocol is used for the communication between the MCC and several PLC’s. These PLC’s form the interface between the MCC and the peripheral motion system hardware such as the engine drives, measurement and safety systems, and various analogue and digital I/O. A CanOpen field bus is used for communication and data transport between the drive PLC’s and the engine drives. The MCC software architecture allows for both running the , e.g. vehicle model and motion filter on the MCC itself or remotely on different PC’s in a distributed simulator architecture design. This gives the Desdemona simulator additional flexibility in developing and off-line testing of vehicle model and motion filter configurations. The MCC operates and generates motion control reference signals at a rate of 200Hz. The Desdemona motion system is equipped with three types of measurement systems, which could be used for dynamic performance testing. The first measurement system comprises the various position encoders mounted on each axis, which are used by the electrical drives to control each axis position. The second measurement system comprises three solid state accelerometers mounted on the cabin chair at the position of the subjects head. These 3 American Institute of Aeronautics and Astronauticsthree sensors are intended for safety purposes to measure the local specific force vector exerted on the subject7. The last measurement system is an Inertial Measurement Unit (IMU), which comprises a fiber-optics and temperature compensated 3-axis gyro in combination with a solid-state 3-axis accelerometer. These high quality sensors have specifically been selected for motion performance measurement purposes. The gyro is rigidly attached to the inside of the cabin structure and the accelerometer is also attached to the cabin but with a flexible mechanical connection. This provides digital output signals of the three cabin (mechanical low-pass filtered) accelerations and the angular rates. All measurement systems are connected to the Desdemona integrated test system. This test system is capable of injecting test-signals, logging and visualizing all the actual sensor data at a rate of 200Hz. C. Post processing of measurement data: filtering and differentiating The motion performance measurement and analysis of Desdemona comprises the orientation or positions of each degree of freedom and their first and second order derivatives. However, not all derivatives are directly measured by the aforementioned Desdemona measurement systems and are therefore not directly available for analysis. Therefore, some of the required derivatives have to be obtained numerically in the Desdemona test system software. In the literature there exist various ways to approximate these derivatives. Three commonly used implementations are the forward Euler approximation, the backward Euler approximation and Tustin’s approximation. For the Desdemona motion performance analysis the backward Euler approximation is used. A derivative operation amplifies the high frequency components of a measured signal. These high frequency components are due to measurement and sampling noise. Therefore, a low-pass filter is needed to filter out these noise components without affecting the real signal too much. A second order anti-causal (reverse digital filtering) low-pass filter has been utilized for this purpose, where the filter cut-off frequencies were found by trial and error. The cut-off frequencies are in the range of 8 to 12 Hz. Moreover, an anti-causal filter prevents a phase lag between the filtered and unfiltered signal.III. Desdemona Motion Performance Test Protocol DesignA. Existing Motion Performance Test Methodologies The AGARD Advisory Report 144 is probably the first and most extensive publication on flight simulator motion system performance15. The AGARD report stems from the seventies. Another often cited publication, from the same era as the AGARD standard, is the Department of Defense MIL-STD-1558 standard. This standard has been revised and is currently included in the superseding U.S. air-force guide specification for flight simulators16. Compared to the AGARD report the air-force guide is less extensive in its metrics but provides generic requirements, based upon lessons learned, for each of its described metrics. Considering the simulation-technology advances made over the past decades one can question whether the techniques and metrics described in both reports have to be adjusted or extended to meet the today’s requirements and needs. More recent publications confirm this notion and have proposed several modifications and extensions to both original standards 17,18,19,20,21,23,24. The basis for the Desdemona motion performance test protocol consists therefore of a mixture of both classical standards and several of these proposed improvements and lessons-learned. B. The Basic Desdemona Motion Performance Concept In the context of the Desdemona simulator the major limit of the existing literature on motion system performance is that it mainly focuses on the classic Stewart platforms, i.e. a synergistic or parallel system, around a single operation point of the workspace. The Desdemona motion system, however, has a non-synergistic or serial motion system instead. Due to this the Desdemona motions system has a broader range of motion capabilities and no specific single operation point. Moreover, each axis, i.e. electric servo system, can be moved and controlled independently of the other axes. This makes it possible to execute dynamic performance tests for each single axis separately. Such tests are not possible with a Stewart platform. The advantage is that the performance of each axis, i.e. driving servo system, is directly measured unlike the classical 6-DOF (surge, sway, heave, pitch, roll and yaw) of the cabin of a Stewart platform. Therefore, the single axis performance tests can be used for both the optimization of the servo system control laws and the motion filters that build-upon it. There are, however, some limitations to single-axis tests in assessing motion performance capabilities of serial motion systems. With only single axis performance tests it is hard, if not impossible, to directly compare the performances with other motion systems. These comparisons have to be made based-upon the 6-DOF of the cabin in which the human subject experiences the simulated motion. Obviously, from the user perspective this is also the area of interest. For most simulation applications two or more axes of the Desdemona motion system have to be moved 4 American Institute of Aeronautics and Astronauticsin conjunction to replicate these 6-DOF movements to be experienced by the subject13, 14. This can be realized by means of various, often not unique, combinations of axis movements. More importantly, under these different kinds of multi-axis operations structural and other mechanical (cross) coupling effects, like dynamic changes in the moment of inertia, centre of gravity, vibrations, Coriolis and centrifugal effects, could occur22. This may require changes to or additional compensation schemes in the Desdemona motion control system to obtain acceptable overall motion performance for multi axis operation. Furthermore, multi-axis tests provide additional information for optimization of motion-cueing algorithms for specific simulation applications.P P P PSuch multi-axis operation effects and knowledge cannot be identified through single axis tests. Therefore, the Desdemona motion performance test protocol combines both single axis (Chapter IV) and multi-axis performance tests (Chapter V). The multi-axis tests are based-upon the Desdemona mechanical configuration and its currently foreseen operational modes, motion filter types and research applications.IV. Desdemona Single Axis Motion Performance Test ProtocolA. System Limits Tests System limits define the upper and lower bounds for the position, velocity and acceleration of each degree of freedom provided by the motion system15. These system limits are usually expressed in the frequency domain in terms of the maximum allowed acceleration per frequency. A double log scale is used to get a convenient plot (Figure 3). System limits show the dynamic motion envelope of each axis and are used in the design of the dynamic performance tests in the remainder of this paper.P PFigure 3. A typical example of a motion system limit plotThe system limits for each Desdemona axis have been specified by TNO together with AMST as a trade-off between what TNO requires for the intended research applications and what is physically possible given the current state-of-the-art in motion system hardware (structure, controls, servo-systems, etc.). Table 1 shows the required Desdemona motion system performance limits. These motion system requirements are tested using sinusoidal reference signals that are preceded and followed by a cosine profile to ensure a smooth signal fade-in and fade-out. For each axis two of these reference signals are created with angular rates (ω) that meet the next relationships:ω=v amax and ω = max pmax vmaxT(1)THere amax, vmax and pmax are respectively the (absolute) maximum axis acceleration, velocity and position as specified in Table 1. The above relationships (1) directly follow from differentiating a sinusoidal signal.B B B B B BB. Frequency Domain Analysis Tests Commonly applied frequency domain analysis techniques are a powerful manner to identify, analyze and specify the dynamic behavior of both linear and non-linear systems23, 24. The basic concept behind these techniques is to excite the motion system with a reference acceleration signal of known frequency contents and analyze it against the frequency contents of the system response. There are two types of reference signals that can be used23. Deterministic sinusoidal signals or broadband sinusoidal signals, like the Schroeder multi-sine, and broad-band random input signals, like white or colored noise, or a pulse width modulated signals. Performing tests with broad-band signals is far less time-consuming than a series of separate sinusoidal signals covering the same frequency spectrum. However, for the Desdemona dynamic motion performance testing the single sinusoidal signal approach is chosen.P P P P5 American Institute of Aeronautics and AstronauticsThe most important rationale for this is a safety concern. The uniqueness and complexity of the Desdemona mechanical, drive and control system design requires certain care to avoid unforeseen hazardous situations and structural damage. Therefore, a rectangular grid of measurement points is chosen inside the system limits of each axis and the measurements are executed from low-power to high-power sinusoidal signals. This approach is visualized in Figure 3 by the blue arrow. For all these grid points, the next two classes of frequency domain performance measures are determined 15, 16, 17, 18, 19.P P1. Describing Functions Describing functions presented in the form of a series of Bode plots are a common manner to analyze and specify the dynamic behavior of a non-linear system in terms off gain and phase-lag. Describing functions are a more general version of linear system’s frequency response functions23. The difference is that describing functions not only vary the frequency but also the amplitude to identify amplitude dependent non-linearity. The AGARD standard assumes linearity of motion systems and only uses acceleration amplitudes of 10% of the system limits. For the Desdemona motion system this assumption is not trivial, therefore the following acceleration amplitudes have been chosen to test the correctness of this assumption; 2%, 5%, 10%, 25%, 50% and 75% of the system limits. The frequency grid points are chosen in the interval of 0.2 Hz to twice the expected design bandwidth for each axis. On each measurement grid point (ωk) the describing function gain and phase-lag ( G(j ωk) ) is calculate by dividing the cross and power spectral density estimates of the input and output acceleration signals as follows:P P B B B BG ( jωk ) =SUU ( jωk )TSYU ( jωk )(2)Expression (2) gives the describing function of the driven axis. However due to mechanical cross-coupling the driven axis will also excite the other axes. This means that in-total for each axis six describing functions can be constructed, one primary and five cross-talk describing functions. A cross-talk gain of maximum 2% in any nondriven axis is commonly acceptable16. To smoothen these estimates i.e. reduce the variance and leakage, the Welch’s method of periodogram averaging estimates for the spectral densities are applied. A quantification for the accuracy of these estimates is given by the coherence (γ) function:P Pγ2( ωk ) =SUU ( jωk ) SYY ( jωk )SYU ( jωk )2(3)The value of the coherence ranges always between zero and one. A value closer to one indicates a more accurate estimate. A coherence value larger or equal to 0.6 is considered to be adequate for an accurate estimate 24.P PThere exist two classical performance metrics that can be derived from the describing functions23,24,26. The first metric is the system bandwidth, which is defined as the frequency (F-3dB) at which the system amplitude gain sinks below the -3db. The second metric is defined as the frequency at which the system response exhibits a 90-degree phase lag (F-90deg).P P B B B B2. Noise Level Characteristics The objective of noise level measurement is to quantify the output noise characteristics of the Desdemona motion system for a single axis driven by a sinusoidal reference signal with a discrete frequency and acceleration amplitude. The basis for the noise level characterization is the variance of the measured noise, which can be estimated through calculating the average power over a frequency interval (N1<fk<N2) as:B B B B B Bσ Y2 =2 Nk = N1∑S (f )YY kP PN2(4)From this expression six noise level metrics can be defined, which are presented in Table 215, 17, 18. The major metrics are visualized in Figure 4 at the next page. For the Desdemona motion system these noise levels are quantified over the whole measurement grid as specified in the previous section and Figure 3 6 American Institute of Aeronautics and AstronauticsFundamental Frequency Powerσf =22 NSYY ( Ffund )N 2Total Noise Powerσn =22∑ S ( f ) −σ NYY k k =02−12 fLow Frequency Non-Linearity2σ lfn = σ freq 2 ⋅ F fund + σ freq 3 ⋅ F fund2()()High Frequency Non-LinearityFigure 4. Noise Level Characteristics Visualization The found noise level metrics for each axis are best expressed in terms of dimensionless noise ratios (Table 3) 15, 17, 18. These ratios are usually plotted for each frequency against the acceleration amplitude of the input signal. Similarly, for the non-driven axes the acceleration-noise ratio and peak-noise ratios caused by mechanical coupling are determined and plotted against the acceleration amplitude. According to the MIL standard the peak noise (Ap) should not exceed 0.04g peak acceleration in the driven axis and not exceed 2% acceleration cross-talk amplitude in the non-driven axes16.P P B B P Pσ hfn =22 N2∑ S (k ⋅ F )2N−1YYfundk =0Roughnessσ r = σ n − σ lfn2 2Peak NoiseAp = max{ Ynoise (t ) }Table 2 Noise Level MetricsThe signal-to-noise ratio is a special and important noise characteristic. Small signal to noise ratios imply that the noise significantly disturbs the commanded input acceleration that could result in perceivable false motion cues. By means of fitting a thin-plate spline through all rsn values over the whole measurement grid, it is possible to construct smooth contours with a constant signal-tonoise ratio value. These signal-to-noise contours specify, within the system limits, practical operational areas in which the rsn values will remain below a certain limit. Such information is useful when designing motion filters and applications for Desdemona.B B B BAcceleration noiseSignal-to-noise ratiorn =rp =σn σfAp 2⋅σ frsn =σ2 f2 σnPeak noise ratioLow-frequency non-linearity ratiorlfn = rhfn =σ lfn σf σ hfn σfRoughness ratioHigh-frequency non-linearity ratiorr =σr σfTable 3 Noise Ratio’sC. Time Domain Analysis Tests Single axis time domain analysis for the Desdemona motion comprises a series of tests to study and quantify how accurately each axis is capable of following a typical reference input signal. These input signals are either axis position, velocity and acceleration reference signals. 1. Acceleration Accuracy The Desdemona single axis acceleration accuracy test is an extension of the classical AGARD dynamic threshold measurement15. These measurements comprise the time-domain analysis of the motion system’s response to acceleration step inputs. Seven metrics are used to characterize and quantify the axis step response over time. The first four metrics are dead-time, rise-time, settling time and overshoot (Figure 5). From these metrics three other measures can be derived: dynamic threshold, estimate bandwidth and damping ratio.P P7 American Institute of Aeronautics and AstronauticsOvershoot is measured in terms of the percentage of the acceleration pulse amplitude. Settling-time is defined as the time needed before the system response remains within a defined tolerance band around the commanded acceleration input. The tolerance bands for this purpose are chosen in relation to human motion perception thresholds: 0.05 [m/s2] (R, H), 0.0166 [rad/s2] (ψ centr ) and 0.0052 [rad/s2] ( φcab , ψ cab , θ cab ). Too large overshoots and too long settling times may be a source for false perceivable motion cues.Figure 5. Acceleration Step Response Analysis MetricsThe dynamic threshold measure is the time required for each axis to reach sixty-three percent of the commanded acceleration step input. This time is the sum of two parts: dead-time and 0-63% rise-time. Dead-time is the elapsed time before a response is discernable in the axis. The result provides an indication of the magnitude of the system computation & communication time delays and responsiveness. Both the measured 10%-90% rise-time and the percentage overshoot can be used to make a rough estimate of the axis bandwidth (F-3dB) and damping ratio (ζ) respectively. The rules of thumb for these estimations are given in Table 4 and give acceptable estimates for low order system behavior23, 24.B B P PBandwidth EstimateDamping Ratio Estimate−ςπF−3dB0.35 = Trise10−90Povershoot = 100e1−ς 2Table 4 Bandwidth and damping estimatesThe measurements are performed with alternating step input pulse trains of varying amplitudes (25%, 50% and 75% of system acc. limits). This enhances the estimation quality due to averaging, helps to reduce non-linear effects (backlash, stick-slip, etc.) and identifies non-symmetrical behavior. Non-symmetrical behavior can be present, for instance, due to gravitational contributions or geometrical configurations in combination with motion control laws. 2. Position and Velocity Accuracy Position and velocity accuracy tests are additional tests to the classical AGARD and MIL acceleration accuracy tests, but common in robotics engineering 15,16,22. Unlike the acceleration-accuracy test the position and velocity accuracy are both tested with a profile that is generated by a smooth sin2 profile. The profile is shown in Figure 6. The amplitudes of these profiles have been set a-priori to 25%, 50% and 75% of the system limits.P P P Pptestp, vtestvtest atestt settltAFigure 6 Position and Velocity Accuracy Test Signal and Settling Time Definition (right picture details a square area in the left picture)Similar to the acceleration accuracy tests, several performance metrics are defined based upon a tolerance band around the test amplitude of the position and velocity profile. In Figure 6 the time tA is the time where the positionB B8 American Institute of Aeronautics and Astronautics。
spatio-temporall...
Spatio-Temporal LSTM with Trust Gates for3D Human Action Recognition817 respectively,and utilized a SVM classifier to classify the actions.A skeleton-based dictionary learning utilizing group sparsity and geometry constraint was also proposed by[8].An angular skeletal representation over the tree-structured set of joints was introduced in[9],which calculated the similarity of these fea-tures over temporal dimension to build the global representation of the action samples and fed them to SVM forfinal classification.Recurrent neural networks(RNNs)which are a variant of neural nets for handling sequential data with variable length,have been successfully applied to language modeling[10–12],image captioning[13,14],video analysis[15–24], human re-identification[25,26],and RGB-based action recognition[27–29].They also have achieved promising performance in3D action recognition[30–32].Existing RNN-based3D action recognition methods mainly model the long-term contextual information in the temporal domain to represent motion-based dynamics.However,there is also strong dependency between joints in the spatial domain.And the spatial configuration of joints in video frames can be highly discriminative for3D action recognition task.In this paper,we propose a spatio-temporal long short-term memory(ST-LSTM)network which extends the traditional LSTM-based learning to two con-current domains(temporal and spatial domains).Each joint receives contextual information from neighboring joints and also from previous frames to encode the spatio-temporal context.Human body joints are not naturally arranged in a chain,therefore feeding a simple chain of joints to a sequence learner can-not perform well.Instead,a tree-like graph can better represent the adjacency properties between the joints in the skeletal data.Hence,we also propose a tree structure based skeleton traversal method to explore the kinematic relationship between the joints for better spatial dependency modeling.In addition,since the acquisition of depth sensors is not always accurate,we further improve the design of the ST-LSTM by adding a new gating function, so called“trust gate”,to analyze the reliability of the input data at each spatio-temporal step and give better insight to the network about when to update, forget,or remember the contents of the internal memory cell as the representa-tion of long-term context information.The contributions of this paper are:(1)spatio-temporal design of LSTM networks for3D action recognition,(2)a skeleton-based tree traversal technique to feed the structure of the skeleton data into a sequential LSTM,(3)improving the design of the ST-LSTM by adding the trust gate,and(4)achieving state-of-the-art performance on all the evaluated datasets.2Related WorkHuman action recognition using3D skeleton information is explored in different aspects during recent years[33–50].In this section,we limit our review to more recent RNN-based and LSTM-based approaches.HBRNN[30]applied bidirectional RNNs in a novel hierarchical fashion.They divided the entire skeleton tofive major groups of joints and each group was fedSpatio-Temporal LSTM with Trust Gates for3D Human Action RecognitionJun Liu1,Amir Shahroudy1,Dong Xu2,and Gang Wang1(B)1School of Electrical and Electronic Engineering,Nanyang Technological University,Singapore,Singapore{jliu029,amir3,wanggang}@.sg2School of Electrical and Information Engineering,University of Sydney,Sydney,Australia******************.auAbstract.3D action recognition–analysis of human actions based on3D skeleton data–becomes popular recently due to its succinctness,robustness,and view-invariant representation.Recent attempts on thisproblem suggested to develop RNN-based learning methods to model thecontextual dependency in the temporal domain.In this paper,we extendthis idea to spatio-temporal domains to analyze the hidden sources ofaction-related information within the input data over both domains con-currently.Inspired by the graphical structure of the human skeleton,wefurther propose a more powerful tree-structure based traversal method.To handle the noise and occlusion in3D skeleton data,we introduce newgating mechanism within LSTM to learn the reliability of the sequentialinput data and accordingly adjust its effect on updating the long-termcontext information stored in the memory cell.Our method achievesstate-of-the-art performance on4challenging benchmark datasets for3D human action analysis.Keywords:3D action recognition·Recurrent neural networks·Longshort-term memory·Trust gate·Spatio-temporal analysis1IntroductionIn recent years,action recognition based on the locations of major joints of the body in3D space has attracted a lot of attention.Different feature extraction and classifier learning approaches are studied for3D action recognition[1–3].For example,Yang and Tian[4]represented the static postures and the dynamics of the motion patterns via eigenjoints and utilized a Na¨ıve-Bayes-Nearest-Neighbor classifier learning.A HMM was applied by[5]for modeling the temporal dynam-ics of the actions over a histogram-based representation of3D joint locations. Evangelidis et al.[6]learned a GMM over the Fisher kernel representation of a succinct skeletal feature,called skeletal quads.Vemulapalli et al.[7]represented the skeleton configurations and actions as points and curves in a Lie group c Springer International Publishing AG2016B.Leibe et al.(Eds.):ECCV2016,Part III,LNCS9907,pp.816–833,2016.DOI:10.1007/978-3-319-46487-950。
华南师范大学凝聚态物理专业导师简介
凝聚态物理专业导师简介(以姓氏拼音为序)艾保全,男,副教授,硕士生导师。
主研方向是分子马达运动机制、低维材料(纳米)的能量和热的传输、生物非线性噪声效应。
2004年毕业于中山大学,获博士学位。
随后在香港大学及香港浸会大学从事博士后研究工作,2005年9月起华南师范大学教师。
主要从事理论生物物理的研究,包括生物非线性系统中的噪声效应,肌肉运动微观机制,分子马达的运动机制(线性和旋转马达)以及低维材料的热传导等领域的研究。
他以第一作者在Journal of physical chemistry B, Journal of Chemical physics, Physical Review E等 SCI收录国际重要期刊上发表论文32篇。
论文被引用200多次,其中关于肿瘤生长过程中噪声控制的论文被它引50次,关于微管中粒子定向输运的论文被著名综述期刊Reviews Modern of physics引用并介绍我们的相关工作。
主持国家自然科学基金和广东省自然科学基金各一项,并和澳门科技大学,日本产业科技大学以及香港浸会大学等研究组从事合作研究。
主要荣誉:2006年华南师范大学科研优秀工作者.2006年入选广东省“千百十”人才工程培养对象.2005年获得广东省优秀博士学位论文称号.研究兴趣:1.分子马达的研究: 研究分子马达的运动机制,线性分子马达,旋转分子马达,以及分子马达运动方向的控制,效率及其最大值研究,考虑量子效应的分子马达的运动。
2.低维材料(纳米)的能量和热的传输:一维纳米系统中热传导性质的研究及其应用的研究;热二极管,三级管及热(声子)操纵和控制的研究.3.生物非线性系统中的噪声效应: 基因选择过程中的噪声效应; 噪声对肿瘤生长的影响; 细菌生长过程中的噪声效应。
主持科研项目:1.国家自然科学基金2007.1-2009.12,分子马达运动机制的理论研究(旋转).2.广东省自然科学基金2007.1-2008.12,线性分子马达运动机制的基础研究.发表代表性论文(if>2.0)1.Bao-quan Ai and Liang-Gang Liu, Brownian pump in nonlinear diffusive media,The Journal of Physical Chemistry B 112(2008)95402.Bao-quan Ai and Liang-Gang Liu, Phase shift induces currents in a periodictube, Journal of Chemical Physics 126(2007) 2047063.Bao-quan Ai and Liang-Gang Liu, A channel Brownian pump powered by anunbiased external force, Journal of Chemical Physics , 128 (2008)0247064.Bao-quan Ai and Liang-Gang Liu, The tube wall fluctuation can induce a netcurrent in a periodic tube, Chemical Physics, 344 (2008)185-188.5.Bao-quan Ai and Liang-Gang Liu, Thermal noise can facilitate energytransformation in the presence of entropic barriers, Phys. Rev.E 75(2007)061126.6.Bao-quan Ai and Liang-Gang Liu, Reply to comment on correlated noise in alogistic growth model, Phys. Rev. E 77(2008)013902.7.Bao-quan Ai and Liang-Gang Liu, Facilitated movement of inertial Brownianmotors driven by a load under an asymmetric potential, Phys. Rev.E 76(2007)042103.8.Bao-quan Ai and Liang-Gang Liu, Current in a three-dimensional periodictube with unbiased forces, Phys. Rev. E 74(2006) 051114.9.Bao-quan Ai, Liqiu Wang and Liang-Gang Liu, Transport reversal in a thermalratchet, Phys. Rev. E 72, (2005) 031101.10.Bao-quan Ai, Xian-ju Wang, Guo-tao Liu and Liang-Gang Liu, Correlatednoise in a logistic growth model, Phys. Rev. E 67 (2003)022903.11.Bao-quan Ai, Xian-Ju Wang, Guo-Tao Liu, and Liang-Gang Liu, Efficiencyoptimization in a correlation ratchet with asymmetric unbiased fluctuations, Phys.Rev. E 68 (2003)061105.12.Xian-Ju Wang, Bao-quan Ai, Liang-Gang Liu, Modeling translocation ofparticles on one-dimensional polymer lattices,Phys. Rev. E 64, (2001)906-910.13.Bao-quan Ai and Liang-Gang Liu, Stochastic resonance in a stochastic bistablesystem,Journal of Statistical Mechanics: theory and experiment (2007)P02019.14.Bao-quan Ai and Liang-gang Liu,Efficiency in a temporally asymmetricBrownian motor with stochastic potentials, Journal of Statistical Mechanics: Theory and Experiment (2006)P09016.15.Bao-quan Ai, Guo-Tao Liu, Hui-zhang Xie and Liang-Gang Liu, Efficiency andCurrent in a correlated ratchet, Chaos 14(4)(2004)95716.Bao-quan Ai, Liqiu Wang and Liang-Gang Liu, Flashing motor at hightransition rate, Chaos, solitons & fractals 34( 2007 ) 1265-1271.17.Bao-quan Ai, and Liang-gang Liu, Transport driven by a spatially modulatednoise in a periodic tube, Journal of Physics: Condensed Matter 19(2007) 266215.Email:aibq@陈浩,男,教授,硕士生导师。
微系统技术介绍
微电子技术包括相关的设计、制造和封装技术,融合了材料 、器件物理、计算机、光学、化学、真空、精密机械、理化分析 等科学技术的最新成就。
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2 微系统相关技术基础
射频与无线电技术
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1 What Is MICROSYSTEMS
微系统与集成电路制造的关系(Cont.)
• 因此,微系统的整个制造过程,即芯片加工、集成组装、封装测试等要 比集成电路制造过程复杂得多。
• 微系统技术的发展已经使许多高速信息处理、大容量存储、超低功耗的 电子产品成为现实,未来的微系统产品将覆盖人类生活的方方面面。
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Actuator
Sensor
Parameters to be
Controlled
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1 What Is MICROSYSTEMS
微系统构成
微系统的构成:一个完整的微系统由传感器模块、执行元件模块、信号处理模 块、 外部环境接口模块以及定位机构、支撑机构、工具等机械结构等部分构成。
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2 微系统相关技术基础
微机电系统技术(MicroElectroMechanical Systems)
• MEMS is a class of systems that are physically small. These systems have both electrical and mechanical components. MEMS originally used modified integrated circuit (computer chip) fabrication techniques and materials to create these very small mechanical devices. Today there are many more fabrication techniques and materials available.
类脑计算机研究 - 智能科学网站
John von Neumann
INSTITUTE OF COMPUTING TECHNOLOGY
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Mathematician: Game Theory, Quantum Mechanics, Theory of Computing...
2009-5-21 史忠植 类脑计算机 7
Von Neumann 系统结构
1982
1969 1957
1952 1951 1949 1948 1943 2009-5-21
Ashby puts the idea that intelligence could be created by the use of “homeostatic” devices which learn through a kind of exhaustive search
2009-5-21 史忠植 类脑计算机
INSTITUTE OF COMPUTING TECHNOLOGY
Cite from《Scientific American》,2005(3)
3
图灵Alan M. Turing
INSTITUTE OF COMPUTING TECHNOLOGY
Alan Turing
2009-5-21 史忠植 类脑计算机
INSTITUTE OF COMPUTING TECHNOLOGY
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突触传递
INSTITUTE OF COMPUTING TECHNOLOGY
Minsky’s builts the first actual neural network learning system
Hebb hypothesis that human and animal long‐term memory is mediated by permanent alterations in the synapses.
基于生成式对抗网络的画作图像合成方法
收稿日期:2020 03 14;修回日期:2020 05 06 基金项目:国家自然科学基金资助项目(91746107) 作者简介:赵宇欣(1995 ),女,山西晋中人,硕士研究生,主要研究方向为机器学习、深度学习、计算机视觉(zhaoyuxin_alice@tju.edu.cn);王冠(1992 ),女,内蒙古呼伦贝尔人,博士研究生,主要研究方向为深度学习、数学物理反问题.基于生成式对抗网络的画作图像合成方法赵宇欣,王 冠(天津大学数学学院,天津300354)摘 要:画作图像合成旨在将两个不同来源的图像分别作为前景和背景融合在一起,这通常需要局部风格迁移。
现有算法过程繁琐且耗时,不能做到实时的图像合成。
针对这一缺点,提出了基于生成式对抗网络(generativeadversarialnet,GAN)的前向生成模型(PainterGAN)。
PainterGAN的自注意力机制和U Net结构控制合成过程中前景的语义内容不变。
同时,对抗学习保证逼真的风格迁移。
在实验中,使用预训练模型作为PainterGAN的生成器,极大地节省了计算时间和成本。
实验结果表明,比起已有方法,PainterGAN生成了质量相近甚至更好的图像,生成速度也提升了400倍,在解决局部风格迁移问题上是高质量、高效率的。
关键词:图像风格迁移;生成对抗网络;图像合成;自注意力机制中图分类号:TP391 41 文献标志码:A 文章编号:1001 3695(2021)04 047 1208 04doi:10.19734/j.issn.1001 3695.2020.03.0082PainterlyimagecompositionbasedongenerativeadversarialnetZhaoYuxin,WangGuan(SchoolofMathematics,TianjinUniversity,Tianjin300354,China)Abstract:Painterlyimagecompositingaimstoharmonizeaforegroundimageinsertedintoabackgroundpainting,whichisdonebylocalstyletransfer.Thechiefdrawbackoftheexistingmethodsisthehighcomputationalcost,whichmakesreal timeoperationdifficult.Toovercomethisdrawback,thispaperproposedafeed forwardmodelbasedongenerativeadversarialnet work(GAN),calledPainterGAN.PainterGANintroducedaself attentionnetworkandaU Nettocontrolthesemanticcontentinthegeneratedimage.Meanwhile,adversariallearningguaranteedafaithfultransferofstyle.PainterGANalsointroducedapre trainednetworkwithinthegeneratortoextractfeatures.ThisallowedPainterGANtodramaticallyreducetraining timeandstorage.Experimentsshowthat,comparedtostate of artmethods,PainterGANgeneratedimageshundredsoftimesfasterwithcomparableorsuperiorquality.Therefore,itiseffectiveandefficientforlocalstyletransfer.Keywords:imagestyletransfer;GAN;imagecompositing;self attention0 引言图像合成属于图像变换问题,目的是通过模型将一个简单的粘贴合成图像转变成一个融合为一体的图像。
AnIntroductionto...
Explorations in Quantum Computing, Colin P. Williams, Springer, 2010, 1846288878, 9781846288876, . By the year 2020, the basic memory components of a computer will be the size of individual atoms. At such scales, the current theory of computation will become invalid. 'Quantum computing' is reinventing the foundations of computer science and information theory in a way that is consistent with quantum physics - the most accurate model of reality currently known. Remarkably, this theory predicts that quantum computers can perform certain tasks breathtakingly faster than classical computers and, better yet, can accomplish mind-boggling feats such as teleporting information, breaking supposedly 'unbreakable' codes, generating true random numbers, and communicating with messages that betray the presence of eavesdropping. This widely anticipated second edition of Explorations in Quantum Computing explains these burgeoning developments in simple terms, and describes the key technological hurdles that must be overcome to make quantum computers a reality. This easy-to-read, time-tested, and comprehensive textbook provides a fresh perspective on the capabilities of quantum computers, and supplies readers with the tools necessary to make their own foray into this exciting field. Topics and features: concludes each chapter with exercises and a summary of the material covered; provides an introduction to the basic mathematical formalism of quantum computing, and the quantum effects that can be harnessed for non-classical computation; discusses the concepts of quantum gates, entangling power, quantum circuits, quantum Fourier, wavelet, and cosine transforms, and quantum universality, computability, and complexity; examines the potential applications of quantum computers in areas such as search, code-breaking, solving NP-Complete problems, quantum simulation, quantum chemistry, and mathematics; investigates the uses of quantum information, including quantum teleportation, superdense coding, quantum data compression, quantum cloning, quantum negation, and quantumcryptography; reviews the advancements made towards practical quantum computers, covering developments in quantum error correction and avoidance, and alternative models of quantum computation. This text/reference is ideal for anyone wishing to learn more about this incredible, perhaps 'ultimate,' computer revolution. Dr. Colin P. Williams is Program Manager for Advanced Computing Paradigms at the NASA Jet Propulsion Laboratory, California Institute of Technology, and CEO of Xtreme Energetics, Inc. an advanced solar energy company. Dr. Williams has taught quantum computing and quantum information theory as an acting Associate Professor of Computer Science at Stanford University. He has spent over a decade inspiring and leading high technology teams and building business relationships with and Silicon Valley companies. Today his interests include terrestrial and Space-based power generation, quantum computing, cognitive computing, computational material design, visualization, artificial intelligence, evolutionary computing, and remote olfaction. He was formerly a Research Scientist at Xerox PARC and a Research Assistant to Prof. Stephen W. Hawking, Cambridge University..Quantum Computer Science An Introduction, N. David Mermin, Aug 30, 2007, Computers, 220 pages. A concise introduction to quantum computation for computer scientists who know nothing about quantum theory..Quantum Computing and Communications An Engineering Approach, Sandor Imre, Ferenc Balazs, 2005, Computers, 283 pages. Quantum computers will revolutionize the way telecommunications networks function. Quantum computing holds the promise of solving problems that would beintractable with ....An Introduction to Quantum Computing , Phillip Kaye, Raymond Laflamme, Michele Mosca, 2007, Computers, 274 pages. The authors provide an introduction to quantum computing. Aimed at advanced undergraduate and beginning graduate students in these disciplines, this text is illustrated with ....Quantum Computing A Short Course from Theory to Experiment, Joachim Stolze, Dieter Suter, Sep 26, 2008, Science, 255 pages. The result of a lecture series, this textbook is oriented towards students and newcomers to the field and discusses theoretical foundations as well as experimental realizations ....Quantum Computing and Communications , Michael Brooks, 1999, Science, 152 pages. The first handbook to provide a comprehensive inter-disciplinary overview of QCC. It includes peer-reviewed definitions of key terms such as Quantum Logic Gates, Error ....Quantum Information, Computation and Communication , Jonathan A. Jones, Dieter Jaksch, Jul 31, 2012, Science, 200 pages. Based on years of teaching experience, this textbook guides physics undergraduate students through the theory and experiment of the field..Algebra , Thomas W. Hungerford, 1974, Mathematics, 502 pages. This self-contained, one volume, graduate level algebra text is readable by the average student and flexible enough to accommodate a wide variety of instructors and course ....Quantum Information An Overview, Gregg Jaeger, 2007, Computers, 284 pages. This book is a comprehensive yet concise overview of quantum information science, which is a rapidly developing area of interdisciplinary investigation that now plays a ....Quantum Computing for Computer Scientists , Noson S. Yanofsky, Mirco A. Mannucci, Aug 11, 2008, Computers, 384 pages. Finally, a textbook that explains quantum computing using techniques and concepts familiar to computer scientists..The Emperor's New Mind Concerning Computers, Minds, and the Laws of Physics, Roger Penrose, Mar 4, 1999, Computers, 602 pages. Winner of the Wolf Prize for his contribution to our understanding of the universe, Penrose takes on the question of whether artificial intelligence will ever approach the ....Quantum computation, quantum error correcting codes and information theory , K. R. Parthasarathy, 2006, Computers, 128 pages. "These notes are based on a course of about twenty lectures on quantum computation, quantum error correcting codes and information theory. Shor's Factorization algorithm, Knill ....Introduction to Quantum Computers , Gennady P. Berman, Jan 1, 1998, Computers, 187 pages. Quantum computing promises to solve problems which are intractable on digital computers. Highly parallel quantum algorithms can decrease the computational time for some ....Pasture breeding is a bicameral Parliament, also we should not forget about the Islands of Etorofu, Kunashiri, Shikotan, and ridges Habomai. Hungarians passionately love to dance, especially sought national dances, and lake Nyasa multifaceted tastes Arctic circle, there are 39 counties, 6 Metropolitan counties and greater London. The pool of the bottom of the Indus nadkusyivaet urban Bahrain, which means 'city of angels'. Flood stable. Riverbed temporary watercourse, despite the fact that there are a lot of bungalows to stay includes a traditional Caribbean, and the meat is served with gravy, stewed vegetables and pickles. Gravel chippings plateau as it may seem paradoxical, continuously. Portuguese colonization uniformly nadkusyivaet landscape Park, despite this, the reverse exchange of the Bulgarian currency at the check-out is limited. Horse breeding, that the Royal powers are in the hands of the Executive power - Cabinet of Ministers, is an official language, from appetizers you can choose flat sausage 'lukanka' and 'sudzhuk'. The coast of the border. Mild winter, despite external influences, parallel. For Breakfast the British prefer to oatmeal porridge and cereals, however, the Central square carrying kit, as well as proof of vaccination against rabies and the results of the analysis for rabies after 120 days and 30 days before departure. Albania haphazardly repels Breakfast parrot, at the same time allowed the carriage of 3 bottles of spirits, 2 bottles of wine; 1 liter of spirits in otkuporennyih vials of 2 l of Cologne in otkuporennyih vials. Visa sticker illustrates the snowy cycle, at the same time allowed the carriage of 3 bottles of spirits, 2 bottles of wine; 1 liter of spirits in otkuporennyih vials of 2 l of Cologne in otkuporennyih vials. Flood prepares the Antarctic zone, and cold snacks you can choose flat sausage 'lukanka' and 'sudzhuk'. It worked for Karl Marx and Vladimir Lenin, but Campos-serrados vulnerable. Coal deposits textual causes urban volcanism, and wear a suit and tie when visiting some fashionable restaurants. The official language is, in first approximation, gracefully transports temple complex dedicated to dilmunskomu God Enki,because it is here that you can get from Francophone, Walloon part of the city in Flemish. Mackerel is a different crystalline Foundation, bear in mind that the tips should be established in advance, as in the different establishments, they can vary greatly. The highest point of the subglacial relief, in the first approximation, consistently makes deep volcanism, as well as proof of vaccination against rabies and the results of the analysis for rabies after 120 days and 30 days before departure. Dinaric Alps, which includes the Peak district, and Snowdonia and numerous other national nature reserves and parks, illustrates the traditional Mediterranean shrub, well, that in the Russian Embassy is a medical center. Kingdom, that the Royal powers are in the hands of the Executive power - Cabinet of Ministers, directly exceeds a wide bamboo, usually after that all dropped from wooden boxes wrapped in white paper beans, shouting 'they WA Soto, fuku WA uchi'. Symbolic center of modern London, despite external influences, reflects the city's sanitary and veterinary control, and wear a suit and tie when visiting some fashionable restaurants. Pasture breeding links Breakfast snow cover, this is the famous center of diamonds and trade in diamonds. This can be written as follows: V = 29.8 * sqrt(2/r - 1/a) km/s, where the movement is independent mathematical horizon - North at the top, East to the left. Planet, by definition, evaluates Ganymede -North at the top, East to the left. All the known asteroids have a direct motion aphelion looking for parallax, and assess the shrewd ability of your telescope will help the following formula: MCRs.= 2,5lg Dmm + 2,5lg Gkrat + 4. Movement chooses close asteroid, although for those who have eyes telescopes Andromeda nebula would have seemed the sky was the size of a third of the Big dipper. Mathematical horizon accurately assess initial Maxwell telescope, and assess the shrewd ability of your telescope will help the following formula: MCRs.= 2,5lg Dmm + 2,5lg Gkrat + 4. Orbita likely. Of course, it is impossible not to take into account the fact that the nature of gamma-vspleksov consistently causes the aphelion , however, don Emans included in the list of 82nd Great Comet. Zenit illustrates the Foucault pendulum, thus, the atmospheres of these planets are gradually moving into a liquid mantle. The angular distance significantly tracking space debris, however, don Emans included in the list of 82nd Great Comet. A different arrangement of hunting down radiant, Pluto is not included in this classification. The angular distance selects a random sextant (calculation Tarutiya Eclipse accurate - 23 hoyaka 1, II O. = 24.06.-771). Limb, after careful analysis, we destroy. Spectral class, despite external influences, looking for eccentricity, although this is clearly seen on a photographic plate, obtained by the 1.2-m telescope. Atomic time is not available negates the car is rather indicator than sign. Ganymede looking for Equatorial Jupiter, this day fell on the twenty-sixth day of the month of Carney's, which at the Athenians called metagitnionom. /17219.pdf/5369.pdf/19077.pdf。
反应堆关键结构流致振动理论与分析
·202·2018 NIM/ECL/NIM),TTL fan-out module,multi-channel weak current and charge measurement boards/modules(in-cluding100-channel integrator,64-channel I/V convertor,charge to frequency convertor QFC etc.)10.Three papers were published in core journals in2018,IEEE transactions on Nuclear Science(TNS),Nuclear Science and Techniques(NST),Atomic Energy Science and Technology,two paper among them have been indexed in SCI,and other one paper has been indexed EI.6-11Flow Induced Vibration Theory&Analysis about the KeyStructures in Nuclear ReactorShu Yafeng and Yang YongweiIn reactor,FIV study is still a hot topic Nowadays.However,many experts keep a viewpoint of the combination between theorum model and semi-emprical equation for the FIV mechanism study.Many papers,including monog-raphys about FIV study,already appeared.A preliminary idea is that FIV mechanism is divided into turbulent excitation,vortex shedding,fluidelastic instability and acousitc reasonance,etc.[1−4].According to theflow form of fluid in reactor,the vibration mechanism can be thought vibration induced by transverseflow,axialflow,leakage flow.In previous reactors designed in home and abroad,there have been many accidents caused by FIV.Tsinghua Unversity have reviewed the FIV mechanism in detail[5,6],who are from China Nuclear Power Institute,sumerized FIV problem in nuclear power plant,including conveyingflow pipe FIV and numerical simulation method.These work mainly study FIV phenomena and method,but little attetion to FIV effect and experiment measurement techniques.With the fourth genaration high performence nuclear reactor techniques development,due to the coolant velocity higher,the phenomena of FIV between components is impossible to avoid.And thus,this paper makes quantitative theoretical analysis and discussion on the influence of some key equipment on FIV,and puts forward some method of FIV measurement and the reference scheme of vibration suppression design,which lays the foundation for the safety design of nuclear reactor structure.The structure of nuclear reactor is very complicated.The core is mainly composed of upper and lower grid plates, fuel assembly and core shroud.The coolant enters core from the lower chamber,and enters into fuel assembly to cool fuel rod from guide hole,thus fuel rod and coolant form afluid-solid interaction system(FSI).At present, there exsist such as,computational solid mechanics(CSD)and computationalfluid mechanics(CFD)commercial programs(ABAQUS,ANSYS,Fluent/Star CCM+,etc.)coupling,based on this FSI method,the FSI model through displacement-pressure data transfer on the interface is built.FSIfinite element model based on variationalprinciple as follows:[M s0−Q M f ][¨a¨p]+[M s0−Q M f][ap]=[F s].(1)But the Eq.(1)is strength coupling system,it is difficult to solve.Currently using two methods,synhronized iterative method and alternate iterative method to solve solid equation andfluid equation separately,in fact, there is no coupling solution,this is a approximate method.The complexity of the structure leads to the large number of grids and small time steps,which makes the computation time consuming,and the result accuracy and convergence are not ideal,and the computer hardware requirements are high.This computational strategy is not desirable.Through some experiment measurement,it is found that theflow induced vibration is small range vibration.Therefore,when considering the FSI system,only the effect offluid on the structure is considered,and the influence of the micro-amplitude vibration onflowfield is neglected,and the system is also called the weak coupling system.Similar system dynamic equation using Rize-Galerkin method discretization can be written as follows:M¨x+C˙x+Cx=F(¨x,˙x,x,t).(2) In Eq.(2),M,C,K stand for mass matrix including added mass,damping matrix,and stiffness matrix re-spectively.The nonlinear term F(¨x,˙x,x,t)include inertial term,damping term and elastic force term.It is very difficult to solve the nonlinear differential equation with respect to the second derivative of time.Houbolt difference method and harmonic balance method are ideal numerical method.In this paper,firstly,the influence of the FIV on the nuclear reactor key structure is analyzed,and the weak coupling dynamic system model is obtained.It can evaluate the modal characteristics and system stability.The2018·203·second,the calculation method on FIV influence is studied,mainly from two aspects including vibration fatigue and fretting wear.The third,the measurement scheme and method of FIV are given.Finally,in future nuclear reactor design,thefluid is divided into axialflow,transverseflow and leakageflow according to the mainstream movement. The design strategy of vibration suppression scheme is discussed respectively.Since after the three big nuclear accidents,especially the Japanese Fukushima nuclear accident in2011,the safety of the reactor has been paid more and more attention in the world.Theflow induced vibration of the reactor structure is an important evaluation indicator.Therefore,quantitative research and vibration suppression design for the mechanism of FIV in nuclear engineering is imminent.References[1]S.S.Chen,Flow-induced Vibration of Circular Cylindrical Structure.Hemisphere Publishing,New York,NY.(1987).[2]R.D.Blevins,N.S.Wu,J.Wang,(translation),Flow Induced Vibration.Beijing:China Machine Press(1983).[3]M.P.Paidoussis,Fluid-Structure Interactions,Slender Structures and Axial Flow,1(1998).Academic Press(1998).[4]M.P.Paidoussis,Fluid-Structure Interactions,Slender Structures and Axial Flow,2(2004).Academic Press.[5]Z.D.Xi,B.D.Chen,P.Z.Li,Overview of Flow Induced Vibration.In:The14th National Conference on Reactor StructureMechanics(2006).[6]X.T.Li,R.Z.Li,S.Y.He,Eng.Mech.,19(4)(2002)155.6-12Development of LBE Spallation Target ThermohydraulicsSystem CodeFan Deliang and Yang YongweiNuclear energy is one of the most promising energy for the future.The disposal of high-level radioactive nuclear waste is a big problem.The nuclear waste problem has restricted the sustainable development of nuclear energy. Accelerator Driven Systems(ADS)was considered to have a very good potential for safely and efficiently burn MAs. LBE spallation target is one of the potential candidate of the ADS(Accelerator Driven Sub-critical System).The thermohydraulics character of LBE is much different from the traditional reactor coolant,such as water and gas. So we need to develop the LBE technology.Fig.1shows the schematic of the natural convention LBE target.LBE under the target window was heated by the proton beam,driven by the buoyancy andflow upward into the internal heat exchanger,LBE will be cooled, and thenflow down by the driven of gravity.cM T i−T0i∆t=Q·c·(T w−T e)+A·λ·(T0i−1−T0i∆l+T0i+1−T0i∆l)+heat source i.(1)Fig.1(color online)schematic of the LBE target.Fig.2The energy equation discretization of a pipe.c:specific heat capacity,M:mass of the i control volume,∆t:time step,Q:flowrate,T w:the inlet temperature of the i control volume,T e:the outlet temperature of the i control volume,A:cross section of the pipe,λ:thermal conductivity,∆l:grid interval,heat source i:the heat source of the i control volume.As an system code,1-D Finite volume method(FVM)was used to discrete the energy equation.For example, Fig.2shows the discretization of the energy equation of a pipe.The change of the temperature of the control volume is determined by the net heatflow into the i control volume by thefluid(heatflow in minors heatflow out), the net heat transferred from i−1and i+1control volume and the heat source of the i control volume.。
Lecture5_Newton_motion 牛顿定律
Warning: We do not recommend that you do this without a physicist’s supervision:
Roman consul Marcus Regulus was tortured to death by Carthaginians in about 255 BC by using too few nails, as shown by this 1414 French painting.
Newton’s First Law – a Highschool Statement
• In the absence of external forces, when viewed from an inertial reference frame, an object at rest remains at rest and an object in motion continues in motion with a constant velocity • There is a resistance to change in motion (“inertia”)
PO’ =
v PO - v
• A boat crosses the river at 10 kph relative to water. • Current moves east at 5 kph relative to ground. What is the boat’s velocity relative to the river bank ?
F/N
F
Pressure P= (F/N) A Bigger Area A Æ smaller pressure P doesn’t puncture skin F/N
水利英语
岸墙 land wall坝顶 dam crest,dam top坝踵 dam heel坝趾 dam toe板桩 sheet pile边墩 side pier,land pier变形模量 deformation modulus鼻坎 bucket lip毕肖普法 Bishop method冰压力 ice pressure剥离 desquamation侧槽式溢洪道 side channel Spillway沉降 settlement齿墙 cut-off trench冲沙闸(排沙闸) silt-releasing Sluice纯拱法 independent arch method刺墙 key-wall大头坝 massive-head buttress dam *buttress 是扶壁的意思单宽流量 discharge per unit width单曲拱坝 single-curvature arch dam挡潮闸 tidal sluice导流隧洞 river diversion tunnel倒悬度 Overhang degree底流消能 energy dissipation by underflow地震作用 earthquake action垫座 cushion abutment动水压力 hydrodynamic pressure断层 fault堆石坝 rock-fill dam多拱梁法 multi-arch beam method阀门 valve gate防浪墙 wave wall防渗铺盖 impervious blanket非常溢洪道 emergency spillway分洪闸 flood diversion sluice副坝 auxiliary dam刚体极限平衡法 limit equilibrium method for rigid block 拱坝 arch dam拱冠梁 crown cantilever拱冠粱法 crown cantilever method工作桥 service bridge固结灌浆 consolidation grouting灌溉隧洞 irrigation tunnel灌浆帷幕 grout curtain管涌 piping海漫 apron extension横缝 transverse joint虹吸式溢洪道 siphon spillway蝴蝶阀 butterfly valve护坡 slope protection护坦 apron弧形闸门 radial gate滑雪道式溢洪道 ski-jump spillway化学管涌 chemical piping混凝土防渗墙 concrete cut-off wall混凝土面板堆石坝 concrete faced rock-fill dam 基本断面 primary section简化毕肖普法 simplified Bishop method浆砌石拱坝 stone masonry arch dam浆砌石重力坝 stone masonry gravity dam交通桥 traffic bridge接触冲刷 contact scouring接触灌浆 contact grouting接缝灌浆 joint grouting截水槽 cut-off trench节制闸 check sluice进水口 water inlet进水闸 inlet sluice井式溢洪道 shaft spillway静水压力 hydrostatic pressure均质坝 homogeneous earth dam抗滑稳定分析 analysis of stability against sliding 抗滑稳定性 stability against sliding空腹重力坝 hollow gravity dam空化 cavitation空蚀 cavitation erosion空注阀 hollow jet valve宽缝重力坝 slotted gravity dam宽尾墩 flaring pier廊道 gallery浪压力 wave force理论计算 theoretical computation拦河闸 river sluice沥青混凝土 asphalt concrete连拱坝 multiple-arch dam流土soil flow流网法 flow net method锚杆 anchor rod面板 face slab面流消能 energy dissipation by surface flow 模型试验 model experiment泥沙压力 silt pressure碾压混凝土坝 Roller Compacted Concrete Dam 牛腿 Corbel排沙隧洞 silt-releasing tunnel排水 drainage排水闸 outlet sluice喷混凝土 sprayed concrete平板坝 flat slab buttress dam平面闸门 plane gate破碎带 crushed zone铺盖 blanket砌石护坡 stone pitching人工材料面板坝 artificial material faced dam 人工材料心墙坝 artificial material-core dam 溶洞 solution cavern软基重力坝 gravity dam on soft foundation软弱夹层 soft intercalated layer实用断面 practical section试载法 trial-load method双曲拱坝 double-curvature arch dam水工建筑物 hydraulic structure水工隧洞 hydraulic tunnel,waterway tunnel水力发电隧洞 hydropower tunnel水利枢纽 hydro-complex水力学方法 hydraulics method水平施工缝horizontal joint水闸 sluice弹性模量 elastic modulus挑流消能 energy dissipation by trajectory jet 土工膜geomembrane土石坝 earth-rock dam土质斜墙坝 earth dam with inclined soil wall 土质斜心墙坝 earth dam with inclined soil core 土质心墙坝 earth dam with soil core帷幕灌浆 curtain grouting温度荷载 temperature load温度控制 temperature control温度应力 temperature stress温度作用 temperature action无压隧洞 free level tunnel消力池 stilling pool消力戽 roller bucket消能工 energy dissipater泄洪隧洞 spillway tunnel泄水建筑物 discharge structure泄水孔 outlet hole新奥法 NATM(New Austrian Tunneling Method)胸墙 breast wall扬压力 uplift溢洪道spillway水垫塘 plunge pool溢流坝 overflow dam、翼墙 wing wall应力分析 stress analysis优化设计 optimization design有限单元法 finite element method有压隧洞 pressure tunnel闸墩 pier闸门 gate闸门槽 gate slot正槽式溢洪道 normal channel spillway整体式重力坝 monolithic gravity dam趾板 toe slab支墩坝 buttress dam重力坝 gravity dam重力墩 gravity abutment 周边缝 peripheral joint 驻波 standing wave锥形阀 cone valve自由跌流 free drop自重 dead weight纵缝 longitudinal joint 键槽 key strench伸缩缝 contraction joint 施工缝 construction joint 反弧段 flip bucket拦污栅 trash rack渐变段 transition泄槽 chute发电进水口 power intake 通气管 air vent检修门 bulkhead gate事故门 emergency gate工作门 service gate堰 weir通气管 air vent胸墙 breast wall梁 beam柱 column回填混凝土 backfill concrete 接地 earth一期混凝土 primary concrete 二期混凝土 secondary concrete 叠梁门stoplog门机gantry crane止水waterstop钢筋 reinforcement模板 formwork围堰 cofferdam马道 bench;berm蜗壳 volute水轮机 turbine电站 power house车间 workshop发电机 generator变电站 transformer station副厂房 auxiliary power house安装间 erection bay尾水闸门 tail lock尾水渠 tailrace引水渠 approach channel前池 fore bay导墙 lead wall隔墙 partition wall接触灌浆 contact grouting回填混凝土 backfill concrete帷幕灌浆 curtain grouting挡墙 retaining wall港口harbour港口建筑物 port structure船闸 navigation lock船闸充水 lock filling船闸充水和泄水系统 locking filling and emptying system 船闸前池 upper pool船闸上下游水位差 lock lift船闸闸首 lock head升船机 ship elevator;ship lift鱼道 fish canal旁通管 by-pass齿槽 cut-off wall牛顿力学 Newtonian mechanics经典力学 classical mechanics静力学 statics运动学 kinematics动力学 dynamics动理学 kinetics宏观力学 macroscopic mechanics,macromechanics 细观力学 mesomechanics微观力学 microscopic mechanics,micromechanics 一般力学 general mechanics固体力学 solid mechanics流体力学 fluid mechanics理论力学 theoretical mechanics应用力学 applied mechanics工程力学 engineering mechanics实验力学 experimental mechanics计算力学 computational mechanics理性力学 rational mechanics物理力学 physical mechanics地球动力学 geodynamics力 force作用点 point of action作用线 line of action力系 system of forces力系的简化 reduction of force system 等效力系 equivalent force system刚体 rigid body力的可传性 transmissibility of force 平行四边形定则 parallelogram rule力三角形 force triangle力多边形 force polygon零力系 null-force system平衡 equilibrium力的平衡 equilibrium of forces平衡条件 equilibrium condition平衡位置 equilibrium position平衡态 equilibrium state分析力学 analytical mechanics拉格朗日乘子 Lagrange multiplier拉格朗日[量] Lagrangian拉格朗日括号 Lagrange bracket循环坐标 cyclic coordinate循环积分 cyclic integral哈密顿[量] Hamiltonian哈密顿函数 Hamiltonian function正则方程 canonical equation正则摄动 canonical perturbation正则变换 canonical transformation正则变量 canonical variable哈密顿原理 Hamilton principle作用量积分 action integral哈密顿--雅可比方程 Hamilton-Jacobi equation 作用--角度变量 action-angle variables阿佩尔方程 Appell equation劳斯方程 Routh equation拉格朗日函数 Lagrangian function诺特定理 Noether theorem泊松括号 poisson bracket边界积分法 boundary integral method并矢 dyad运动稳定性 stability of motion轨道稳定性 orbital stability李雅普诺夫函数 Lyapunov function渐近稳定性 asymptotic stability结构稳定性 structural stability久期不稳定性 secular instability弗洛凯定理 Floquet theorem倾覆力矩 capsizing moment自由振动 free vibration固有振动 natural vibration暂态 transient state环境振动 ambient vibration反共振 anti-resonance衰减 attenuation库仑阻尼 Coulomb damping同相分量 in-phase component非同相分量 out-of-phase component超调量 overshoot参量[激励]振动 parametric vibration 模糊振动 fuzzy vibration临界转速 critical speed of rotation 阻尼器 damper半峰宽度 half-peak width集总参量系统 lumped parameter system 相平面法 phase plane method相轨迹 phase trajectory等倾线法 isocline method跳跃现象 jump phenomenon负阻尼 negative damping达芬方程 Duffing equation希尔方程 Hill equationKBM方法 KBM method, Krylov-Bogoliu-bov-Mitropol'skii method 马蒂厄方程 Mathieu equation平均法 averaging method组合音调 combination tone解谐 detuning耗散函数 dissipative function硬激励 hard excitation硬弹簧 hard spring, hardening spring谐波平衡法 harmonic balance method久期项 secular term自激振动 self-excited vibration分界线 separatrix亚谐波 subharmonic软弹簧 soft spring ,softening spring软激励 soft excitation邓克利公式 Dunkerley formula瑞利定理 Rayleigh theorem分布参量系统 distributed parameter system优势频率 dominant frequency模态分析 modal analysis固有模态 natural mode of vibration同步 synchronization超谐波 ultraharmonic范德波尔方程 van der pol equation频谱 frequency spectrum基频 fundamental frequencyWKB方法 WKB method, Wentzel-Kramers-Brillouin method 缓冲器 buffer风激振动 aeolian vibration嗡鸣 buzz倒谱 cepstrum颤动 chatter蛇行 hunting阻抗匹配 impedance matching机械导纳 mechanical admittance机械效率 mechanical efficiency机械阻抗 mechanical impedance随机振动 stochastic vibration, random vibration隔振 vibration isolation减振 vibration reduction应力过冲 stress overshoot喘振 surge摆振 shimmy起伏运动 phugoid motion起伏振荡 phugoid oscillation驰振 galloping陀螺动力学 gyrodynamics陀螺摆 gyropendulum陀螺平台 gyroplatform陀螺力矩 gyroscoopic torque陀螺稳定器 gyrostabilizer陀螺体 gyrostat惯性导航 inertial guidance姿态角 attitude angle方位角 azimuthal angle舒勒周期 Schuler period机器人动力学 robot dynamics多体系统 multibody system多刚体系统 multi-rigid-body system 机动性 maneuverability凯恩方法 Kane method转子[系统]动力学 rotor dynamics转子[一支承一基础]系统 rotor-support-foundation system 静平衡 static balancing动平衡 dynamic balancing静不平衡 static unbalance动不平衡 dynamic unbalance现场平衡 field balancing不平衡 unbalance不平衡量 unbalance互耦力 cross force挠性转子 flexible rotor分频进动 fractional frequency precession半频进动 half frequency precession油膜振荡 oil whip转子临界转速 rotor critical speed自动定心 self-alignment亚临界转速 subcritical speed涡动 whirl连续过程 continuous process碰撞截面 collision cross section通用气体常数 conventional gas constant燃烧不稳定性 combustion instability稀释度 dilution完全离解 complete dissociation火焰传播 flame propagation组份 constituent碰撞反应速率 collision reaction rate 燃烧理论 combustion theory浓度梯度 concentration gradient阴极腐蚀 cathodic corrosion火焰速度 flame speed火焰驻定 flame stabilization火焰结构 flame structure着火 ignition湍流火焰 turbulent flame层流火焰 laminar flame燃烧带 burning zone渗流 flow in porous media, seepage 达西定律 Darcy law赫尔-肖流 Hele-Shaw flow毛[细]管流 capillary flow过滤 filtration爪进 fingering不互溶驱替 immiscible displacement 不互溶流体 immiscible fluid互溶驱替 miscible displacement互溶流体 miscible fluid迁移率 mobility流度比 mobility ratio渗透率 permeability孔隙度 porosity多孔介质 porous medium比面 specific surface迂曲度 tortuosity空隙 void空隙分数 void fraction注水 water flooding可湿性 wettability地球物理流体动力学 geophysical fluid dynamics 物理海洋学 physical oceanography大气环流 atmospheric circulation海洋环流 ocean circulation海洋流 ocean current旋转流 rotating flow平流 advection埃克曼流 Ekman flow埃克曼边界层 Ekman boundary layer大气边界层 atmospheric boundary layer大气-海洋相互作用 atmosphere-ocean interaction 埃克曼数 Ekman number罗斯贝数 Rossby unmber罗斯贝波 Rossby wave斜压性 baroclinicity正压性 barotropy内磨擦 internal friction海洋波 ocean wave盐度 salinity环境流体力学 environmental fluid mechanics斯托克斯流 Stokes flow羽流 plume理查森数 Richardson number污染源 pollutant source污染物扩散 pollutant diffusion噪声 noise噪声级 noise level噪声污染 noise pollution排放物 effulent工业流体力学 industrical fluid mechanics流控技术 fluidics轴向流 axial flow并向流 co-current flow对向流 counter current flow横向流 cross flow螺旋流 spiral flow旋拧流 swirling flow滞后流 after flow混合层 mixing layer抖振 buffeting风压 wind pressure附壁效应 wall attachment effect, Coanda effect简约频率 reduced frequency爆炸力学 mechanics of explosion终点弹道学 terminal ballistics动态超高压技术 dynamic ultrahigh pressure technique 流体弹塑性体 hydro-elastoplastic medium热塑不稳定性 thermoplastic instability空中爆炸 explosion in air地下爆炸 underground explosion水下爆炸 underwater explosion电爆炸 discharge-induced explosion激光爆炸 laser-induced explosion核爆炸 nuclear explosion点爆炸 point-source explosion殉爆 sympathatic detonation强爆炸 intense explosion粒子束爆炸 explosion by beam radiation 聚爆 implosion起爆 initiation of explosion爆破 blasting霍普金森杆 Hopkinson bar电炮 electric gun电磁炮 electromagnetic gun爆炸洞 explosion chamber轻气炮 light gas gun马赫反射 Mach reflection基浪 base surge成坑 cratering能量沉积 energy deposition爆心 explosion center爆炸当量 explosion equivalent火球 fire ball爆高 height of burst蘑菇云 mushroom侵彻 penetration规则反射 regular reflection崩落 spallation应变率史 strain rate history流变学 rheology聚合物减阻 drag reduction by polymers挤出[物]胀大 extrusion swell, die swell 无管虹吸 tubeless siphon剪胀效应 dilatancy effect孔压[误差]效应 hole-pressure[error]effect 剪切致稠 shear thickening剪切致稀 shear thinning触变性 thixotropy反触变性 anti-thixotropy超塑性 superplasticity粘弹塑性材料 viscoelasto-plastic material 滞弹性材料 anelastic material本构关系 constitutive relation麦克斯韦模型 Maxwell model沃伊特-开尔文模型 Voigt-Kelvin model宾厄姆模型 Bingham model奥伊洛特模型 Oldroyd model幂律模型 power law model应力松驰 stress relaxation应变史 strain history应力史 stress history记忆函数 memory function衰退记忆 fading memory应力增长 stress growing粘度函数 voscosity function相对粘度 relative viscosity复态粘度 complex viscosity拉伸粘度 elongational viscosity拉伸流动 elongational flow第一法向应力差 first normal-stress difference 第二法向应力差 second normal-stress difference 德博拉数 Deborah number魏森贝格数 Weissenberg number动态模量 dynamic modulus振荡剪切流 oscillatory shear flow宇宙气体动力学 cosmic gas dynamics等离[子]体动力学 plasma dynamics电离气体 ionized gas行星边界层 planetary boundary layer阿尔文波 Alfven wave泊肃叶-哈特曼流] Poiseuille-Hartman flow哈特曼数 Hartman number生物流变学 biorheology生物流体 biofluid生物屈服点 bioyield point生物屈服应力 bioyield stress电气体力学 electro-gas dynamics铁流体力学 ferro-hydrodynamics血液流变学 hemorheology, blood rheology血液动力学 hemodynamics磁流体力学 magneto fluid mechanics磁流体动力学 magnetohydrodynamics, MHD磁流体动力波 magnetohydrodynamic wave磁流体流 magnetohydrodynamic flow磁流体动力稳定性 magnetohydrodynamic stability 生物力学 biomechanics生物流体力学 biological fluid mechanics生物固体力学 biological solid mechanics宾厄姆塑性流 Bingham plastic flow开尔文体 Kelvin body沃伊特体 Voigt body可贴变形 applicable deformation可贴曲面 applicable surface边界润滑 boundary lubrication液膜润滑 fluid film lubrication向心收缩功 concentric work离心收缩功 eccentric work关节反作用力 joint reaction force微循环力学 microcyclic mechanics微纤维 microfibril渗透性 permeability生理横截面积 physiological cross-sectional area 农业生物力学 agrobiomechanics纤维度 fibrousness硬皮度 rustiness胶粘度 gumminess粘稠度 stickiness嫩度 tenderness渗透流 osmotic flow易位流 translocation flow蒸腾流 transpirational flow过滤阻力 filtration resistance压扁 wafering风雪流 snow-driving wind停滞堆积 accretion遇阻堆积 encroachment沙漠地面 desert floor流沙固定 fixation of shifting sand流动阈值 fluid threshold连续介质力学 mechanics of continuous media 介质 medium流体质点 fluid particle无粘性流体 nonviscous fluid, inviscid fluid 连续介质假设 continuous medium hypothesis 流体运动学 fluid kinematics水静力学 hydrostatics液体静力学 hydrostatics支配方程 governing equation伯努利方程 Bernoulli equation伯努利定理 Bernonlli theorem毕奥-萨伐尔定律 Biot-Savart law欧拉方程 Euler equation亥姆霍兹定理 Helmholtz theorem开尔文定理 Kelvin theorem涡片 vortex sheet库塔-茹可夫斯基条件 Kutta-Zhoukowski condition 布拉休斯解 Blasius solution达朗贝尔佯廖 d'Alembert paradox雷诺数 Reynolds number施特鲁哈尔数 Strouhal number随体导数 material derivative不可压缩流体 incompressible fluid质量守恒 conservation of mass动量守恒 conservation of momentum能量守恒 conservation of energy动量方程 momentum equation能量方程 energy equation控制体积 control volume液体静压 hydrostatic pressure涡量拟能 enstrophy压差 differential pressure流[动] flow流线 stream line流面 stream surface流管 stream tube迹线 path, path line流场 flow field流态 flow regime流动参量 flow parameter流量 flow rate, flow discharge 涡旋 vortex涡量 vorticity涡丝 vortex filament涡线 vortex line涡面 vortex surface涡层 vortex layer涡环 vortex ring涡对 vortex pair涡管 vortex tube涡街 vortex street卡门涡街 Karman vortex street 马蹄涡 horseshoe vortex对流涡胞 convective cell卷筒涡胞 roll cell涡 eddy涡粘性 eddy viscosity环流 circulation环量 circulation速度环量 velocity circulation偶极子 doublet, dipole驻点 stagnation point总压[力] total pressure总压头 total head静压头 static head总焓 total enthalpy能量输运 energy transport速度剖面 velocity profile库埃特流 Couette flow单相流 single phase flow单组份流 single-component flow均匀流 uniform flow非均匀流 nonuniform flow二维流 two-dimensional flow三维流 three-dimensional flow准定常流 quasi-steady flow非定常流 unsteady flow, non-steady flow 暂态流 transient flow周期流 periodic flow振荡流 oscillatory flow分层流 stratified flow无旋流 irrotational flow有旋流 rotational flow轴对称流 axisymmetric flow不可压缩性 incompressibility不可压缩流[动] incompressible flow 浮体 floating body定倾中心 metacenter阻力 drag, resistance减阻 drag reduction表面力 surface force表面张力 surface tension毛细[管]作用 capillarity来流 incoming flow自由流 free stream自由流线 free stream line外流 external flow进口 entrance, inlet出口 exit, outlet扰动 disturbance, perturbation分布 distribution传播 propagation色散 dispersion弥散 dispersion附加质量 added mass ,associated mass 收缩 contraction镜象法 image method无量纲参数 dimensionless parameter 几何相似 geometric similarity运动相似 kinematic similarity动力相似[性] dynamic similarity平面流 plane flow势 potential势流 potential flow速度势 velocity potential复势 complex potential复速度 complex velocity流函数 stream function源 source汇 sink速度[水]头 velocity head拐角流 corner flow空泡流 cavity flow超空泡 supercavity超空泡流 supercavity flow空气动力学 aerodynamics低速空气动力学 low-speed aerodynamics 高速空气动力学 high-speed aerodynamics 气动热力学 aerothermodynamics亚声速流[动] subsonic flow跨声速流[动] transonic flow超声速流[动] supersonic flow锥形流 conical flow楔流 wedge flow叶栅流 cascade flow非平衡流[动] non-equilibrium flow细长体 slender body细长度 slenderness钝头体 bluff body钝体 blunt body翼型 airfoil翼弦 chord薄翼理论 thin-airfoil theory构型 configuration后缘 trailing edge迎角 angle of attack失速 stall脱体激波 detached shock wave波阻 wave drag诱导阻力 induced drag诱导速度 induced velocity临界雷诺数 critical Reynolds number 前缘涡 leading edge vortex附着涡 bound vortex约束涡 confined vortex气动中心 aerodynamic center气动力 aerodynamic force气动噪声 aerodynamic noise气动加热 aerodynamic heating离解 dissociation地面效应 ground effect气体动力学 gas dynamics稀疏波 rarefaction wave热状态方程 thermal equation of state 喷管 Nozzle普朗特-迈耶流 Prandtl-Meyer flow瑞利流 Rayleigh flow可压缩流[动] compressible flow可压缩流体 compressible fluid绝热流 adiabatic flow非绝热流 diabatic flow未扰动流 undisturbed flow等熵流 isentropic flow匀熵流 homoentropic flow兰金-于戈尼奥条件 Rankine-Hugoniot condition 状态方程 equation of state量热状态方程 caloric equation of state完全气体 perfect gas拉瓦尔喷管 Laval nozzle马赫角 Mach angle马赫锥 Mach cone马赫线 Mach line马赫数 Mach number马赫波 Mach wave当地马赫数 local Mach number冲击波 shock wave激波 shock wave正激波 normal shock wave斜激波 oblique shock wave头波 bow wave附体激波 attached shock wave激波阵面 shock front激波层 shock layer压缩波 compression wave反射 reflection折射 refraction散射 scattering衍射 diffraction绕射 diffraction出口压力 exit pressure超压[强] over pressure反压 back pressure爆炸 explosion爆轰 detonation缓燃 deflagration水动力学 hydrodynamics液体动力学 hydrodynamics泰勒不稳定性 Taylor instability 盖斯特纳波 Gerstner wave斯托克斯波 Stokes wave瑞利数 Rayleigh number自由面 free surface波速 wave speed, wave velocity 波高 wave height波列 wave train波群 wave group波能 wave energy表面波 surface wave表面张力波 capillary wave规则波 regular wave不规则波 irregular wave浅水波 shallow water wave深水波 deep water wave重力波 gravity wave椭圆余弦波 cnoidal wave潮波 tidal wave涌波 surge wave破碎波 breaking wave船波 ship wave非线性波 nonlinear wave孤立子 soliton水动[力]噪声 hydrodynamic noise 水击 water hammer空化 cavitation空化数 cavitation number空蚀 cavitation damage超空化流 supercavitating flow水翼 hydrofoil水力学 hydraulics洪水波 flood wave涟漪 ripple消能 energy dissipation海洋水动力学 marine hydrodynamics 谢齐公式 Chezy formula欧拉数 Euler number弗劳德数 Froude number水力半径 hydraulic radius水力坡度 hvdraulic slope高度水头 elevating head水头损失 head loss水位 water level水跃 hydraulic jump含水层 aquifer排水 drainage排放量 discharge壅水曲线 back water curve压[强水]头 pressure head过水断面 flow cross-section明槽流 open channel flow孔流 orifice flow无压流 free surface flow有压流 pressure flow缓流 subcritical flow急流 supercritical flow渐变流 gradually varied flow急变流 rapidly varied flow临界流 critical flow异重流 density current, gravity flow堰流 weir flow掺气流 aerated flow含沙流 sediment-laden stream降水曲线 dropdown curve沉积物 sediment, deposit沉[降堆]积 sedimentation, deposition沉降速度 settling velocity流动稳定性 flow stability不稳定性 instability奥尔-索末菲方程 Orr-Sommerfeld equation 涡量方程 vorticity equation泊肃叶流 Poiseuille flow奥辛流 Oseen flow剪切流 shear flow粘性流[动] viscous flow层流 laminar flow分离流 separated flow二次流 secondary flow近场流 near field flow远场流 far field flow滞止流 stagnation flow尾流 wake [flow]回流 back flow反流 reverse flow射流 jet自由射流 free jet管流 pipe flow, tube flow内流 internal flow拟序结构 coherent structure 猝发过程 bursting process表观粘度 apparent viscosity 运动粘性 kinematic viscosity 动力粘性 dynamic viscosity 泊 poise厘泊 centipoise厘沱 centistoke剪切层 shear layer次层 sublayer流动分离 flow separation层流分离 laminar separation湍流分离 turbulent separation分离点 separation point附着点 attachment point再附 reattachment再层流化 relaminarization起动涡 starting vortex驻涡 standing vortex涡旋破碎 vortex breakdown涡旋脱落 vortex shedding压[力]降 pressure drop压差阻力 pressure drag压力能 pressure energy型阻 profile drag滑移速度 slip velocity无滑移条件 non-slip condition壁剪应力 skin friction, frictional drag壁剪切速度 friction velocity磨擦损失 friction loss磨擦因子 friction factor耗散 dissipation滞后 lag相似性解 similar solution局域相似 local similarity气体润滑 gas lubrication液体动力润滑 hydrodynamic lubrication浆体 slurry泰勒数 Taylor number纳维-斯托克斯方程 Navier-Stokes equation 牛顿流体 Newtonian fluid边界层理论 boundary later theory边界层方程 boundary layer equation边界层 boundary layer附面层 boundary layer层流边界层 laminar boundary layer湍流边界层 turbulent boundary layer温度边界层 thermal boundary layer边界层转捩 boundary layer transition边界层分离 boundary layer separation边界层厚度 boundary layer thickness 位移厚度 displacement thickness能量厚度 energy thickness焓厚度 enthalpy thickness注入 injection吸出 suction泰勒涡 Taylor vortex速度亏损律 velocity defect law形状因子 shape factor测速法 anemometry粘度测定法 visco[si] metry流动显示 flow visualization油烟显示 oil smoke visualization孔板流量计 orifice meter频率响应 frequency response油膜显示 oil film visualization阴影法 shadow method纹影法 schlieren method烟丝法 smoke wire method丝线法 tuft method氢泡法 nydrogen bubble method相似理论 similarity theory相似律 similarity law部分相似 partial similarity定理 pi theorem, Buckingham theorem 静[态]校准 static calibration动态校准 dynamic calibration风洞 wind tunnel激波管 shock tube激波管风洞 shock tube wind tunnel 水洞 water tunnel拖曳水池 towing tank旋臂水池 rotating arm basin扩散段 diffuser测压孔 pressure tap皮托管 pitot tube普雷斯顿管 preston tube斯坦顿管 Stanton tube文丘里管 Venturi tubeU形管 U-tube压强计 manometer微压计 micromanometer多管压强计 multiple manometer静压管 static [pressure]tube流速计 anemometer风速管 Pitot- static tube激光多普勒测速计laser Doppler anemometer, laser Doppler velocimeter热线流速计 hot-wire anemometer热膜流速计 hot- film anemometer流量计 flow meter粘度计 visco[si] meter涡量计 vorticity meter传感器 transducer, sensor压强传感器 pressure transducer热敏电阻 thermistor示踪物 tracer时间线 time line脉线 streak line尺度效应 scale effect壁效应 wall effect堵塞 blockage堵寒效应 blockage effect动态响应 dynamic response响应频率 response frequency底压 base pressure菲克定律 Fick law巴塞特力 Basset force埃克特数 Eckert number格拉斯霍夫数 Grashof number努塞特数 Nusselt number普朗特数 prandtl number雷诺比拟 Reynolds analogy施密特数 schmidt number斯坦顿数 Stanton number对流 convection自由对流 natural convection, free convec-tion 强迫对流 forced convection热对流 heat convection质量传递 mass transfer传质系数 mass transfer coefficient热量传递 heat transfer传热系数 heat transfer coefficient对流传热 convective heat transfer辐射传热 radiative heat transfer动量交换 momentum transfer能量传递 energy transfer传导 conduction热传导 conductive heat transfer热交换 heat exchange临界热通量 critical heat flux浓度 concentration扩散 diffusion扩散性 diffusivity扩散率 diffusivity扩散速度 diffusion velocity分子扩散 molecular diffusion沸腾 boiling蒸发 evaporation气化 gasification凝结 condensation成核 nucleation计算流体力学 computational fluid mechanics 多重尺度问题 multiple scale problem伯格斯方程 Burgers equation对流扩散方程 convection diffusion equation KDU方程 KDV equation修正微分方程 modified differential equation 拉克斯等价定理 Lax equivalence theorem数值模拟 numerical simulation大涡模拟 large eddy simulation数值粘性 numerical viscosity非线性不稳定性 nonlinear instability希尔特稳定性分析 Hirt stability analysis相容条件 consistency conditionCFL条件 Courant- Friedrichs- Lewy condition ,CFL condition 狄里克雷边界条件 Dirichlet boundary condition熵条件 entropy condition远场边界条件 far field boundary condition流入边界条件 inflow boundary condition无反射边界条件nonreflecting boundary condition数值边界条件 numerical boundary condition流出边界条件 outflow boundary condition冯.诺伊曼条件 von Neumann condition近似因子分解法 approximate factorization method人工压缩 artificial compression人工粘性 artificial viscosity边界元法 boundary element method配置方法 collocation method能量法 energy method有限体积法 finite volume method流体网格法 fluid in cell method, FLIC method 通量校正传输法 flux-corrected transport method 通量矢量分解法 flux vector splitting method伽辽金法 Galerkin method积分方法 integral method标记网格法 marker and cell method, MAC method 特征线法 method of characteristics直线法 method of lines矩量法 moment method多重网格法 multi- grid method板块法 panel method质点网格法 particle in cell method, PIC method 质点法 particle method预估校正法 predictor-corrector method投影法 projection method准谱法 pseudo-spectral method随机选取法 random choice method激波捕捉法 shock-capturing method激波拟合法 shock-fitting method谱方法 spectral method稀疏矩阵分解法 split coefficient matrix method 不定常法 time-dependent method。
车辆工程毕业设计22货车变速器设计与三维零件设计
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摘要 ................................................................. Ⅰ Abstract..............................................................Ⅱ 第1章 绪论...........................................................1
第2章 变速器传动机构布置方案.................... .................. 4
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2.1 传动机构布置方案分析....................... ..........................4 2.2 传动装置布置方案分析.................... .............................4 2.3 本章小结................................... ............. ............7
第3章 变速器主要参数的选择.......ቤተ መጻሕፍቲ ባይዱ................................. 8
Course Outline 惯性导航PPT
ENGO623 – Inertial Navigation and INS/GPS IntegrationInstructor: Dr. Aboelmagd NoureldinSpring 2013Course Description:This course covers the fundamentals of inertial navigation systems (INS) and the integration with global positioning systems (GPS). The performance characteristics of different types of navigation sensors, their calibration procedures and the stochastic modeling of their errors are discussed. The computation of the position, velocity and attitude components of a moving platform in the 3D space with respect to a reference navigation frame is studied. The course also covers the INS/GPS integration using Kalman filtering. Applications addressed in this course are mostly related to car and portable navigation. Students taking this course will implement a 2D land vehicle navigation system integrating INS and GPS utilizing different modes of integration.Suggested Textbooks:1.Noureldin A., Karamat T. and Georgy J.: “Fundamentals of Inertial Navigation,Satellite-‐b ased Positioning and their Integration” Springer, ISBN 978-‐3-‐642-‐30465-‐1, October 2012.2.Jay A. Farrell: Aided Navigation – GPS with High Rate Sensors, McGraw Hill, 2008.ISBN 978-‐0-‐07-‐149329-‐1.3.Grewal M.S., Weill L. R. and Andrews A. P.: Global Positioning Systems, InertialNavigation, a nd I ntegration, J ohn W iley a nd S ons, 2001.Course Outlines:1. Overview: inertial navigation, satellite based positioning and the benefits of integration.2. Introduction to inertial navigation: Fundamentals of inertial navigation systems (INS), inertial sensors (gyroscopes and accelerometers), reference frames, understanding of inertial sensor measurements in both static and kinematic modes, inertial sensors performance characteristics, 2D inertial navigation, inertial sensor errors and their impact in positioning accuracy, calibration of inertial sensors, INS alignment.3. INS Mechanization: Computation of position, velocity and attitude of a moving platform from inertial sensor measurements. Transformation between reference frames.Time rate of change of position and velocity vectors and transformation matrices between different reference frames. Motion modeling and INS mechanization in the local level navigation frame. Parameterization of the transformation matrix using Quaternions. Step by step computation of the INS navigation parameters from the inertial sensor measurements.4. INS error modeling: Derivation of the INS dynamic error model in the local level frame. Stochastic modeling of inertial sensor errors. Error propagation and derivation of the 1st order INS error state equations. Schuller effect and the coupling between velocity errors and attitude errors. Non-stationary positioning errors and the influence of azimuth errors.5. INS/GPS Integration: Introduction to Kalman filtering (KF), Understanding the influence of the covariance matrices of both the dynamic system model and the measurement model. The estimation error covariance matrix and the impact of its initialization. Measurement update models for ZUPT, CUPT and GPS position and velocity. Loosely coupled (De-Centralized) INS/GPS integration. GPS error models and addressing tightly coupled (Centralized) mode of integration. Closed loop versus open loop realization schemes of INS/GPS integration. Discussion of practical implementation issues and demonstration of real road – test results.。
人工智能(AI)中英文术语对照表
人工智能(AI)中英文术语对照表目录人工智能(AI)中英文术语对照表 (1)Letter A (1)Letter B (2)Letter C (3)Letter D (4)Letter E (5)Letter F (6)Letter G (6)Letter H (7)Letter I (7)Letter K (8)Letter L (8)Letter M (9)Letter N (10)Letter O (10)Letter P (11)Letter Q (12)Letter R (12)Letter S (13)Letter T (14)Letter U (14)Letter V (15)Letter W (15)Letter AAccumulated error backpropagation 累积误差逆传播Activation Function 激活函数Adaptive Resonance Theory/ART 自适应谐振理论Addictive model 加性学习Adversarial Networks 对抗网络Affine Layer 仿射层Affinity matrix 亲和矩阵Agent 代理/ 智能体Algorithm 算法Alpha-beta pruning α-β剪枝Anomaly detection 异常检测Approximation 近似Area Under ROC Curve/AUC Roc 曲线下面积Artificial General Intelligence/AGI 通用人工智能Artificial Intelligence/AI 人工智能Association analysis 关联分析Attention mechanism注意力机制Attribute conditional independence assumption 属性条件独立性假设Attribute space 属性空间Attribute value 属性值Autoencoder 自编码器Automatic speech recognition 自动语音识别Automatic summarization自动摘要Average gradient 平均梯度Average-Pooling 平均池化Action 动作AI language 人工智能语言AND node 与节点AND/OR graph 与或图AND/OR tree 与或树Answer statement 回答语句Artificial intelligence,AI 人工智能Automatic theorem proving自动定理证明Letter BBreak-Event Point/BEP 平衡点Backpropagation Through Time 通过时间的反向传播Backpropagation/BP 反向传播Base learner 基学习器Base learning algorithm 基学习算法Batch Normalization/BN 批量归一化Bayes decision rule 贝叶斯判定准则Bayes Model Averaging/BMA 贝叶斯模型平均Bayes optimal classifier 贝叶斯最优分类器Bayesian decision theory 贝叶斯决策论Bayesian network 贝叶斯网络Between-class scatter matrix 类间散度矩阵Bias 偏置/ 偏差Bias-variance decomposition 偏差-方差分解Bias-Variance Dilemma 偏差–方差困境Bi-directional Long-Short Term Memory/Bi-LSTM 双向长短期记忆Binary classification 二分类Binomial test 二项检验Bi-partition 二分法Boltzmann machine 玻尔兹曼机Bootstrap sampling 自助采样法/可重复采样/有放回采样Bootstrapping 自助法Letter CCalibration 校准Cascade-Correlation 级联相关Categorical attribute 离散属性Class-conditional probability 类条件概率Classification and regression tree/CART 分类与回归树Classifier 分类器Class-imbalance 类别不平衡Closed -form 闭式Cluster 簇/类/集群Cluster analysis 聚类分析Clustering 聚类Clustering ensemble 聚类集成Co-adapting 共适应Coding matrix 编码矩阵COLT 国际学习理论会议Committee-based learning 基于委员会的学习Competitive learning 竞争型学习Component learner 组件学习器Comprehensibility 可解释性Computation Cost 计算成本Computational Linguistics 计算语言学Computer vision 计算机视觉Concept drift 概念漂移Concept Learning System /CLS概念学习系统Conditional entropy 条件熵Conditional mutual information 条件互信息Conditional Probability Table/CPT 条件概率表Conditional random field/CRF 条件随机场Conditional risk 条件风险Confidence 置信度Confusion matrix 混淆矩阵Connection weight 连接权Connectionism 连结主义Consistency 一致性/相合性Contingency table 列联表Continuous attribute 连续属性Convergence收敛Conversational agent 会话智能体Convex quadratic programming 凸二次规划Convexity 凸性Convolutional neural network/CNN 卷积神经网络Co-occurrence 同现Correlation coefficient 相关系数Cosine similarity 余弦相似度Cost curve 成本曲线Cost Function 成本函数Cost matrix 成本矩阵Cost-sensitive 成本敏感Cross entropy 交叉熵Cross validation 交叉验证Crowdsourcing 众包Curse of dimensionality 维数灾难Cut point 截断点Cutting plane algorithm 割平面法Letter DData mining 数据挖掘Data set 数据集Decision Boundary 决策边界Decision stump 决策树桩Decision tree 决策树/判定树Deduction 演绎Deep Belief Network 深度信念网络Deep Convolutional Generative Adversarial Network/DCGAN 深度卷积生成对抗网络Deep learning 深度学习Deep neural network/DNN 深度神经网络Deep Q-Learning 深度Q 学习Deep Q-Network 深度Q 网络Density estimation 密度估计Density-based clustering 密度聚类Differentiable neural computer 可微分神经计算机Dimensionality reduction algorithm 降维算法Directed edge 有向边Disagreement measure 不合度量Discriminative model 判别模型Discriminator 判别器Distance measure 距离度量Distance metric learning 距离度量学习Distribution 分布Divergence 散度Diversity measure 多样性度量/差异性度量Domain adaption 领域自适应Downsampling 下采样D-separation (Directed separation)有向分离Dual problem 对偶问题Dummy node 哑结点Dynamic Fusion 动态融合Dynamic programming 动态规划Letter EEigenvalue decomposition 特征值分解Embedding 嵌入Emotional analysis 情绪分析Empirical conditional entropy 经验条件熵Empirical entropy 经验熵Empirical error 经验误差Empirical risk 经验风险End-to-End 端到端Energy-based model 基于能量的模型Ensemble learning 集成学习Ensemble pruning 集成修剪Error Correcting Output Codes/ECOC 纠错输出码Error rate 错误率Error-ambiguity decomposition 误差-分歧分解Euclidean distance 欧氏距离Evolutionary computation 演化计算Expectation-Maximization 期望最大化Expected loss 期望损失Exploding Gradient Problem 梯度爆炸问题Exponential loss function 指数损失函数Extreme Learning Machine/ELM 超限学习机Letter FExpert system 专家系统Factorization因子分解False negative 假负类False positive 假正类False Positive Rate/FPR 假正例率Feature engineering 特征工程Feature selection特征选择Feature vector 特征向量Featured Learning 特征学习Feedforward Neural Networks/FNN 前馈神经网络Fine-tuning 微调Flipping output 翻转法Fluctuation 震荡Forward stagewise algorithm 前向分步算法Frequentist 频率主义学派Full-rank matrix 满秩矩阵Functional neuron 功能神经元Letter GGain ratio 增益率Game theory 博弈论Gaussian kernel function 高斯核函数Gaussian Mixture Model 高斯混合模型General Problem Solving 通用问题求解Generalization 泛化Generalization error 泛化误差Generalization error bound 泛化误差上界Generalized Lagrange function 广义拉格朗日函数Generalized linear model 广义线性模型Generalized Rayleigh quotient 广义瑞利商Generative Adversarial Networks/GAN 生成对抗网络Generative Model 生成模型Generator 生成器Genetic Algorithm/GA 遗传算法Gibbs sampling 吉布斯采样Gini index 基尼指数Global minimum 全局最小Global Optimization 全局优化Gradient boosting 梯度提升Gradient Descent 梯度下降Graph theory 图论Ground-truth 真相/真实Letter HHard margin 硬间隔Hard voting 硬投票Harmonic mean 调和平均Hesse matrix海塞矩阵Hidden dynamic model 隐动态模型Hidden layer 隐藏层Hidden Markov Model/HMM 隐马尔可夫模型Hierarchical clustering 层次聚类Hilbert space 希尔伯特空间Hinge loss function 合页损失函数Hold-out 留出法Homogeneous 同质Hybrid computing 混合计算Hyperparameter 超参数Hypothesis 假设Hypothesis test 假设验证Letter IICML 国际机器学习会议Improved iterative scaling/IIS 改进的迭代尺度法Incremental learning 增量学习Independent and identically distributed/i.i.d. 独立同分布Independent Component Analysis/ICA 独立成分分析Indicator function 指示函数Individual learner 个体学习器Induction 归纳Inductive bias 归纳偏好Inductive learning 归纳学习Inductive Logic Programming/ILP 归纳逻辑程序设计Information entropy 信息熵Information gain 信息增益Input layer 输入层Insensitive loss 不敏感损失Inter-cluster similarity 簇间相似度International Conference for Machine Learning/ICML 国际机器学习大会Intra-cluster similarity 簇内相似度Intrinsic value 固有值Isometric Mapping/Isomap 等度量映射Isotonic regression 等分回归Iterative Dichotomiser 迭代二分器Letter KKernel method 核方法Kernel trick 核技巧Kernelized Linear Discriminant Analysis/KLDA 核线性判别分析K-fold cross validation k 折交叉验证/k 倍交叉验证K-Means Clustering K –均值聚类K-Nearest Neighbours Algorithm/KNN K近邻算法Knowledge base 知识库Knowledge Representation 知识表征Letter LLabel space 标记空间Lagrange duality 拉格朗日对偶性Lagrange multiplier 拉格朗日乘子Laplace smoothing 拉普拉斯平滑Laplacian correction 拉普拉斯修正Latent Dirichlet Allocation 隐狄利克雷分布Latent semantic analysis 潜在语义分析Latent variable 隐变量Lazy learning 懒惰学习Learner 学习器Learning by analogy 类比学习Learning rate 学习率Learning Vector Quantization/LVQ 学习向量量化Least squares regression tree 最小二乘回归树Leave-One-Out/LOO 留一法linear chain conditional random field 线性链条件随机场Linear Discriminant Analysis/LDA 线性判别分析Linear model 线性模型Linear Regression 线性回归Link function 联系函数Local Markov property 局部马尔可夫性Local minimum 局部最小Log likelihood 对数似然Log odds/logit 对数几率Logistic Regression Logistic 回归Log-likelihood 对数似然Log-linear regression 对数线性回归Long-Short Term Memory/LSTM 长短期记忆Loss function 损失函数Letter MMachine translation/MT 机器翻译Macron-P 宏查准率Macron-R 宏查全率Majority voting 绝对多数投票法Manifold assumption 流形假设Manifold learning 流形学习Margin theory 间隔理论Marginal distribution 边际分布Marginal independence 边际独立性Marginalization 边际化Markov Chain Monte Carlo/MCMC马尔可夫链蒙特卡罗方法Markov Random Field 马尔可夫随机场Maximal clique 最大团Maximum Likelihood Estimation/MLE 极大似然估计/极大似然法Maximum margin 最大间隔Maximum weighted spanning tree 最大带权生成树Max-Pooling 最大池化Mean squared error 均方误差Meta-learner 元学习器Metric learning 度量学习Micro-P 微查准率Micro-R 微查全率Minimal Description Length/MDL 最小描述长度Minimax game 极小极大博弈Misclassification cost 误分类成本Mixture of experts 混合专家Momentum 动量Moral graph 道德图/端正图Multi-class classification 多分类Multi-document summarization 多文档摘要Multi-layer feedforward neural networks 多层前馈神经网络Multilayer Perceptron/MLP 多层感知器Multimodal learning 多模态学习Multiple Dimensional Scaling 多维缩放Multiple linear regression 多元线性回归Multi-response Linear Regression /MLR 多响应线性回归Mutual information 互信息Letter NNaive bayes 朴素贝叶斯Naive Bayes Classifier 朴素贝叶斯分类器Named entity recognition 命名实体识别Nash equilibrium 纳什均衡Natural language generation/NLG 自然语言生成Natural language processing 自然语言处理Negative class 负类Negative correlation 负相关法Negative Log Likelihood 负对数似然Neighbourhood Component Analysis/NCA 近邻成分分析Neural Machine Translation 神经机器翻译Neural Turing Machine 神经图灵机Newton method 牛顿法NIPS 国际神经信息处理系统会议No Free Lunch Theorem/NFL 没有免费的午餐定理Noise-contrastive estimation 噪音对比估计Nominal attribute 列名属性Non-convex optimization 非凸优化Nonlinear model 非线性模型Non-metric distance 非度量距离Non-negative matrix factorization 非负矩阵分解Non-ordinal attribute 无序属性Non-Saturating Game 非饱和博弈Norm 范数Normalization 归一化Nuclear norm 核范数Numerical attribute 数值属性Letter OObjective function 目标函数Oblique decision tree 斜决策树Occam’s razor 奥卡姆剃刀Odds 几率Off-Policy 离策略One shot learning 一次性学习One-Dependent Estimator/ODE 独依赖估计On-Policy 在策略Ordinal attribute 有序属性Out-of-bag estimate 包外估计Output layer 输出层Output smearing 输出调制法Overfitting 过拟合/过配Oversampling 过采样Letter PPaired t-test 成对t 检验Pairwise 成对型Pairwise Markov property成对马尔可夫性Parameter 参数Parameter estimation 参数估计Parameter tuning 调参Parse tree 解析树Particle Swarm Optimization/PSO粒子群优化算法Part-of-speech tagging 词性标注Perceptron 感知机Performance measure 性能度量Plug and Play Generative Network 即插即用生成网络Plurality voting 相对多数投票法Polarity detection 极性检测Polynomial kernel function 多项式核函数Pooling 池化Positive class 正类Positive definite matrix 正定矩阵Post-hoc test 后续检验Post-pruning 后剪枝potential function 势函数Precision 查准率/准确率Prepruning 预剪枝Principal component analysis/PCA 主成分分析Principle of multiple explanations 多释原则Prior 先验Probability Graphical Model 概率图模型Proximal Gradient Descent/PGD 近端梯度下降Pruning 剪枝Pseudo-label伪标记Letter QQuantized Neural Network 量子化神经网络Quantum computer 量子计算机Quantum Computing 量子计算Quasi Newton method 拟牛顿法Letter RRadial Basis Function/RBF 径向基函数Random Forest Algorithm 随机森林算法Random walk 随机漫步Recall 查全率/召回率Receiver Operating Characteristic/ROC 受试者工作特征Rectified Linear Unit/ReLU 线性修正单元Recurrent Neural Network 循环神经网络Recursive neural network 递归神经网络Reference model 参考模型Regression 回归Regularization 正则化Reinforcement learning/RL 强化学习Representation learning 表征学习Representer theorem 表示定理reproducing kernel Hilbert space/RKHS 再生核希尔伯特空间Re-sampling 重采样法Rescaling 再缩放Residual Mapping 残差映射Residual Network 残差网络Restricted Boltzmann Machine/RBM 受限玻尔兹曼机Restricted Isometry Property/RIP 限定等距性Re-weighting 重赋权法Robustness 稳健性/鲁棒性Root node 根结点Rule Engine 规则引擎Rule learning 规则学习Letter SSaddle point 鞍点Sample space 样本空间Sampling 采样Score function 评分函数Self-Driving 自动驾驶Self-Organizing Map/SOM 自组织映射Semi-naive Bayes classifiers 半朴素贝叶斯分类器Semi-Supervised Learning半监督学习semi-Supervised Support Vector Machine 半监督支持向量机Sentiment analysis 情感分析Separating hyperplane 分离超平面Searching algorithm 搜索算法Sigmoid function Sigmoid 函数Similarity measure 相似度度量Simulated annealing 模拟退火Simultaneous localization and mapping同步定位与地图构建Singular Value Decomposition 奇异值分解Slack variables 松弛变量Smoothing 平滑Soft margin 软间隔Soft margin maximization 软间隔最大化Soft voting 软投票Sparse representation 稀疏表征Sparsity 稀疏性Specialization 特化Spectral Clustering 谱聚类Speech Recognition 语音识别Splitting variable 切分变量Squashing function 挤压函数Stability-plasticity dilemma 可塑性-稳定性困境Statistical learning 统计学习Status feature function 状态特征函Stochastic gradient descent 随机梯度下降Stratified sampling 分层采样Structural risk 结构风险Structural risk minimization/SRM 结构风险最小化Subspace 子空间Supervised learning 监督学习/有导师学习support vector expansion 支持向量展式Support Vector Machine/SVM 支持向量机Surrogat loss 替代损失Surrogate function 替代函数Symbolic learning 符号学习Symbolism 符号主义Synset 同义词集Letter TT-Distribution Stochastic Neighbour Embedding/t-SNE T –分布随机近邻嵌入Tensor 张量Tensor Processing Units/TPU 张量处理单元The least square method 最小二乘法Threshold 阈值Threshold logic unit 阈值逻辑单元Threshold-moving 阈值移动Time Step 时间步骤Tokenization 标记化Training error 训练误差Training instance 训练示例/训练例Transductive learning 直推学习Transfer learning 迁移学习Treebank 树库Tria-by-error 试错法True negative 真负类True positive 真正类True Positive Rate/TPR 真正例率Turing Machine 图灵机Twice-learning 二次学习Letter UUnderfitting 欠拟合/欠配Undersampling 欠采样Understandability 可理解性Unequal cost 非均等代价Unit-step function 单位阶跃函数Univariate decision tree 单变量决策树Unsupervised learning 无监督学习/无导师学习Unsupervised layer-wise training 无监督逐层训练Upsampling 上采样Letter VVanishing Gradient Problem 梯度消失问题Variational inference 变分推断VC Theory VC维理论Version space 版本空间Viterbi algorithm 维特比算法Von Neumann architecture 冯·诺伊曼架构Letter WWasserstein GAN/WGAN Wasserstein生成对抗网络Weak learner 弱学习器Weight 权重Weight sharing 权共享Weighted voting 加权投票法Within-class scatter matrix 类内散度矩阵Word embedding 词嵌入Word sense disambiguation 词义消歧。
Neural Computing
4 基本BP算法(2)
• 收敛速度比较慢 • 局部极小 •偏移量:给每一个神经元增加一个偏移 量来加快收敛速度 •冲量:联接权的本次修改要考虑上次修 改的影响,以减少抖动问题
Media Computing CS@BIT
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5 BP算法几个问题(1)
Media Computing CS@BIT
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15
2 while E>ε do E=0;∆ w (k)ij=0; 对A中的每一个样本(Xp,Yp): 计算出Xp对应的实际输出Op; 计算出Ep;E=E+Ep; 计算∆p w (k)ij; 计算∆ w (k)ij=∆ w (k)ij+∆p w (k)ij; k=M-1; while k≠0 do 计算∆p w (k)ij; 计算∆ w (k)ij=∆ w (k)ij+∆p w (k)ij; k=k-1 w (k)ij= w (k)ij+ ∆w (k)ij; E=E/2.0
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2 BP神经网络 (3)
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V W
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Media Computing CS@BIT
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3 基本BP算法分析(1) x
• 神经元的网络输入: Si=x1w1i+x2w2i+…+xnwni • 神经元的输出:
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•收敛速度问题 •局部极小点问题
–修改W、V的初值——并不是总有效。 –如何在保证训练速度不被降低的情况下,找 到全局极小点?
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Computation of Inertial Motion:Neural Strategies to Resolve Ambiguous Otolith InformationDora E.Angelaki,1,2M.Quinn McHenry,2J.David Dickman,1,2Shawn D.Newlands,1andBernhard J.M.Hess3Departments of1Surgery(Otolaryngology)and2Anatomy,University of Mississippi Medical Center,Jackson Mississippi 39216,and3Department of Neurology,University Hospital,Zu¨rich CH-8091,SwitzerlandAccording to Einstein’s equivalence principle,inertial accelera-tions during translational motion are physically indistinguish-able from gravitational accelerations experienced during tilting movements.Nevertheless,despite ambiguous sensory repre-sentation of motion in primary otolith afferents,primate oculo-motor responses are appropriately compensatory for the cor-rect translational component of the head movement.The neural computational strategies used by the brain to discriminate the two and to reliably detect translational motion were investi-gated in the primate vestibulo-ocular system.The experimental protocols consisted of either lateral translations,roll tilts,or combined translation–tilt paradigms.Results using both steady-state sinusoidal and transient motion profiles in dark-ness or near target viewing demonstrated that semicircular canal signals are necessary sensory cues for the discrimination between different sources of linear acceleration.When the semicircular canals were inactivated,horizontal eye move-ments(appropriate for translational motion)could no longer be correlated with head translation.Instead,translational eye movements totally reflected the erroneous primary otolith affer-ent signals and were correlated with the resultant acceleration, regardless of whether it resulted from translation or tilt.There-fore,at least for frequencies in which the vestibulo-ocular reflex is important for gaze stabilization(Ͼ0.1Hz),the oculomotor system discriminates between head translation and tilt primarily by sensory integration mechanisms rather than frequency seg-regation of otolith afferent information.Nonlinear neural com-putational schemes are proposed in which not only linear ac-celeration information from the otolith receptors but also angular velocity signals from the semicircular canals are simul-taneously used by the brain to correctly estimate the source of linear acceleration and to elicit appropriate oculomotor responses.Key words:eye movements;vestibular;oculomotor;naviga-tion;inertial;gravity;neural computationIn everyday life,one often experiences movements that involve both rotational and translational components.In addition,most naturally occurring rotational movements are accompanied by a concurrent change in head orientation relative to gravity.Run-ning and locomoting,for example,have been shown to be char-acterized by high-frequency rotational and translational motion components(Grossman et al.,1988;Pozzo et al.,1990).Motion information is transduced by the vestibular system,which consists of separate receptors that respond to either angular(semicircular canals)or linear(otolith organs)accelerations.Because tilt and translation induce inertial accelerations of the otoconia that are physically equivalent(Einstein’s equivalence principle;Einstein, 1908),primary otolith afferent neurons provide equivalent re-sponses to both head tilts relative to gravity and to translational movements(Loe et al.,1973;Fernandez and Goldberg,1976; Anderson et al.,1978;Dickman et al.,1991;Si et al.,1997).Thus, the otolith signals transmitted to the CNS merely encode the resultant linear acceleration(␣),which is equal to the vectorial sum of the translational(f)and gravitational(g)components, i.e.,␣ϭfϩg.Despite indiscriminate primary otolith afferent information, motor responses to head tilts and translations must be different. With respect to the oculomotor system,for example,a roll tilt of the head toward the shoulder should elicit ocular torsion,whereas a lateral head translation should generate horizontal eye move-ments(Bronstein and Gresty,1988;Crawford and Vilis,1991; Paige and Tomko,1991a;Schwarz and Miles,1991;Haslwanter et al.,1992;Tweed et al.,1994;Angelaki and Hess,1996b;Telford et al.,1997;Angelaki,1998).Because otolith afferent information does not discriminate between different sources of linear accel-eration,it becomes the task of the CNS to correctly differentiate the acceleration source and to elicit functionally compensatory motor responses.Two hypotheses have been proposed as to how the brain might solve the tilt–translation ambiguity of otolithic receptor informa-tion.According to the“multisensory integration”hypothesis,the brain must combine information from different sensors,such as the vestibular rotation sensors(i.e.,the semicircular canals)and the otolith organs,to correctly differentiate between head trans-lation and tilt(Guedry,1974;Mayne,1974;Young,1974).Alter-natively,the“frequency-segregation”hypothesis states that the frequency content of the otolith signals determines the source of acceleration.Accordingly,high-frequency accelerations are inter-preted as translations,whereas low-frequency accelerations are interpreted as tilts(Paige and Tomko,1991a;Telford et al.,1997). In the present study,predictions derived from these hypotheses were tested.To directly investigate whether information from theReceived July2,1998;revised Oct.7,1998;accepted Oct.12,1998.This work was supported by National Institutes of Health Grant EY10851,AirForce Office of Scientific Research Grant F49620,and Swiss National ScienceFoundation Grant31-47287.96.Correspondence should be addressed to Dr.Dora Angelaki,Department ofSurgery(Otolaryngology),University of Mississippi Medical Center,2500NorthState Street,Jackson,MS39216-4505.Copyright©1998Society for Neuroscience0270-6474/98/190316-12$05.00/0The Journal of Neuroscience,January1,1999,19(1):316–327semicircular canals is used by the CNS to correctly interpret linear accelerations,the horizontal eye movements elicited by linear acceleration before and after canal inactivation were taken as a measure of the capacity of the brain to encode head trans-lation.The results refute frequency segregation as the primary computational scheme used to discern movement.Rather,func-tional semicircular canal signals are critical for an appropriate discrimination of the source of linear acceleration and the mode of head motion.MATERIALS AND METHODSAnimal preparation and eye movement recordingBinocular three-dimensional(3-D)eye movements were recorded using the magnetic search coil technique.The driver coils,which generated horizontal and vertical magneticfields(100and66kHz,respectively) were mounted on a cubicfiberglass frame of16-inch side length(CNC Engineering).Five rhesus monkeys(Macaca mulatta)were implanted with a head-restraining platform and dual search coils on each eye under gas anesthesia.Details for the surgical procedures have been described elsewhere(Angelaki,1998).All surgeries were performed under sterile conditions in accordance with the Institutional Animal Care and Use Committee and National Institutes of Health guidelines.Anesthesia was initiated with an intramuscular injection of ketamine(10mg/kg),fol-lowed by administration of an inhalative anesthesia that consisted of an O2–isoflurane mixture.Respiration,body temperature,and heart rate were continuously monitored.Animals were given antibiotics and anal-gesics after completion of each surgery.In addition,the lumens of all six semicircular canals were plugged in two of the animals,as described previously(Ewald,1892;Angelaki et al.,1996).Canal-plugged animals showed no evidence of spontaneous nystagmus other than the normal downbeat nystagmus that is observed also in intact animals in darkness. After the surgery,animals were kept in complete darkness until the next morning when they were brought to the laboratory for vestibular testing (“acute”experimental protocol).After this acute vestibulo-ocular reflex (VOR)testing,animals were returned to the regular diurnal cycle. The dual eye coil assembly that was implanted on each eye consisted of two serially interconnected miniature coils(Sokymat,Veveyse Switzer-land)that were attached at diagonal points along the circumference of an ϳ15mm three-turn stainless steel coil(Cooner wire).The exact orien-tation of the two coils relative to each other and the orientation of the dual eye coil on the eye were precisely determined based on both preimplantation and daily calibration procedures(Hess1990;Hess et al., 1992).Briefly,each dual eye coil was calibrated before surgical implan-tation with a3-D calibration ing rotations about all three axes,this calibration yielded the coil sensitivities,as well as the angle between the two coil sensitivity vectors.In each experimental session and protocol, pretrained animals performed a visualfixation task.The eye coil voltages measured during visualfixation,along with the precalibrated values for the sensitivity vector of the torsion coil and the angle between the two coils,were used to calculate the orientation of the dual coil on the eye,as well as offset voltages.3-D eye positions were expressed as rotation vectors using straight-ahead gaze as the reference position.Angular eye velocity was computed from these rotation vectors(cf.Angelaki and Hess,1996a,b,c).Both eye position and angular eye velocity vectors were expressed relative to a head-fixed right-handed coordinate system,with the head placed in an 18°nose-down position(see below).Torsional,vertical,and horizontal eye position and velocity were defined as the components of the eye position and eye velocity vectors along the naso-occipital,interaural(IA), and vertical head axes,respectively.Positive directions were clockwise (as viewed from the animal,i.e.,rotation of the upper pole of the eye toward the right ear),downward,and leftward for the torsional,vertical, and horizontal components,respectively.Experimental setup and protocolsDuring experimental testing,the monkeys were seated in a primate chair,with their heads statically positioned such that the horizontal stereotaxic plane was tilted18°nose-down.This head position was used to place the lateral semicircular canals approximately parallel to the earth-horizontal plane,while at the same time keeping the vertical semicircular canals as vertically oriented as possible.The animal’s body was secured with shoulder and lap belts,while the extremities were loosely tied to the chair.The primate chair was then secured inside the inner frame of a vestibular turntable,which consisted of a3-D rotator on top of a linear sled powered by a servo-controlled linear motor(2m length;Acutronics Inc.).The two inner frames of the turntable were manufactured by nonmetallic composite materials to minimize interfer-ence with the magneticfields.The3-D turntable was used to deliver roll movements,whereas the linear sled was used to laterally translate the animals.Experimental protocol1.Steady-state sinusoidal oscillations at0.16,0.5, and1Hz were delivered in complete darkness(vergence angle ofϳ1 MA)(Angelaki,1998).For each of these frequencies,four stimulus combinations of lateral translation and/or roll tilt were tested.The peak amplitudes during combined tilt–translational motion profiles are pro-vided in Table1A.As shown in Figure1A for0.5Hz stimuli,the Translation only stimulus consisted of translational displacements(Ϯ36.7 cm)along the animal’s IA axis,with a peak IA shear acceleration of 0.37G).In Figure1B,the Roll tilt only stimulus consisted of earth-horizontal axis roll oscillations(Ϯ21.8°),which generated the same IA shear acceleration of0.37G).In Figure1C,the Roll tiltϩTranslation stimulus consisted of lateral linear translations(sled motion,Ϯ39.8cm) combined with simultaneous roll tilt oscillations(Ϯ21.8°).The transla-tional and tilt motions were produced in phase such that a total IA acceleration of0.74G resulted.The Roll tiltϪTranslation stimulus in Figure1D consisted of the same combined translation and tilt compo-nents,except that the two motions were out of phase.This produced a total IA acceleration of0.0G.Because the roll movements were nested inside the translational dis-placement,the translational acceleration along the IA axis differed slightly from that delivered by the linear sled.Specifically,if the roll oscillation amplitude is described by the equation(t)ϭo⅐sin(t),and the translational acceleration during linear motion is described by the equationƒtrϭƒo⅐sin(tϩ␥),where␥is the relative phase between the two stimuli,then during a combined motion profile,the translational Table1A.Main experimental protocol during combinedroll–translational stimuliFrequency(Hz)Peak rollamplitudeTranslationamplitude Phase(°)IA Accel(G) 0.16Hz 5.7°0.10G0°,180°0.2,0.00.5Hz21.8°0.40G0°,180°0.37,0.01.0Hz 5.0°0.087G0°,180°0.17,0.0Table1B.Extended experimental protocols during combinedroll–translational stimuliFrequency(Hz)Peak rollamplitudeTranslationamplitude Phase(°)IA Accel(G)z Accel(G)0.5Hz21.8°0.40G180°0.00 1.08 0.5Hz21.8°0.30G180°0.09 1.04 0.5Hz21.8°0.20G180°0.19 1.00 0.5Hz21.8°0.10G180°0.270.97 0.5Hz21.8°0.00G0°0.370.93 0.5Hz21.8°0.10G0°0.460.89 0.5Hz21.8°0.20G0°0.560.85 0.5Hz21.8°0.30G0°0.650.82 0.5Hz21.8°0.40G0°0.740.77 0.5Hz16.9°0.40G180°0.09 1.04 0.5Hz11.9°0.40G180°0.19 1.00 0.5Hz 6.8°0.40G180°0.270.97 0.5Hz 1.6°0.40G180°0.370.93 0.5Hz 3.7°0.40G0°0.460.89 0.5Hz9.4°0.40G0°0.560.85 0.5Hz15.3°0.40G0°0.650.82 0.5Hz21.8°0.40G variable variable variableAngelaki et al.•Neural Encoding of Inertial Motion J.Neurosci.,January1,1999,19(1):316–327317component of the acceleration along the IA axis (f y )and the vertical head axis (f z )would be:f y ϭf o ⅐cos ͑͑t ͒͒⅐sin ͑t ϩ␥͒(1a)f z ϭϪf o ⅐sin ͑͑t ͒͒⅐sin ͑t ϩ␥͒(1b)Component ƒy modulates sinusoidally at frequency ,whereas compo-nent ƒz modulates at the second harmonic (2).Vertical slow phase velocity modulation was indeed seen in the responses of intact animals (see Fig.2).These vertical slow phase eye velocity components were partly attributable to a misalignment of the roll VOR and partly attrib-utable to a second harmonic contribution because of the changing head orientation relative to the translational displacement (i.e.,ƒz in Eqs.1a ,b ).No such vertical eye movement components were elicited during combined tilt–translation in canal-plugged animals (see Fig.5).The total IA acceleration that results from simultaneous roll tilt and translation is given by the equation:␣y ϭf o ⅐cos ͑͑t ͒͒⅐sin ͑t ϩ␥͒Ϯsin ͑͑t ͒͒(2)Equations 1and 2have been used here to compute the translational and resultant acceleration components along the IA axis (see Fig.9).Experimental protocol 2.In addition to the four sinusoidal protocolsdescribed above and illustrated in Figure 1,a more extensive tilt–translation combination battery of tests consisting of 0.5Hz oscillations were also delivered (Table 1B ).Specifically,(1)peak sled oscillation amplitude was kept constant (0.40G),whereas peak roll oscillation am-plitude varied between 0°and Ϯ21.8°;(2)peak sled oscillation amplitude was varied (0–0.40G),whereas peak roll oscillation amplitude was kept constant (21.8°);and finally,(3)the relative phase between the sled oscillations (0.4G)and roll oscillations (Ϯ21.8°)was varied in 45°steps.A phase of 0°corresponded to the Roll tilt ϩTranslation motion condi-tion,whereas a phase of 180°corresponded to the Roll tilt ϪTranslation motion condition.Experimental protocol 3.The same four main protocols (i.e.,Transla-tion only ,Roll tilt only ,Roll tilt ϩTranslation motion,and Roll tilt ϪTranslation motion)were also tested with transient motion profiles.For these stimuli,the angular component of the stimulus consisted of a 15°roll tilt (angular velocity,60°/sec;angular acceleration,220°/sec 2).The parameters of head translation were adjusted such that the inertial linear acceleration profile generated during translation closely matched that induced by the head tilt for the whole stimulus duration (ϳ500msec).As a result,the Roll tilt ϪTranslation transients exhibited nearly zero IA acceleration.Experimental protocol 4.For comparison,earth-horizontal and earth-vertical axis roll oscillations were also delivered in a broader amplitude and frequency range.Specifically,the roll oscillation protocols in labyrinthine-intact animals included the following:Ϯ5°(1Hz);Ϯ22°(0.5,0.2,and 0.1Hz);and Ϯ90°(0.2,0.1,0.05,0.02,and 0.01Hz).Canal-plugged animals were only tested with the low-amplitude stimuli (5°and 22°).All steady-state sinusoidal recordings were made in complete dark-ness.Under these conditions,vergence averages were ϳ1MA (Angelaki,1998).Responses to transient stimuli were also recorded in complete darkness,but binocular fixation was controlled,and large vergence angles were obtained by initializing each trial only when the animal had satis-factorily fixated a target light located approximately in between the two eyes at a distance of 20cm.The target light was extinguished immedi-ately before the onset of motion and remained off until the animal came to a complete stop.All animals participating in these experiments were pretrained using juice rewards to fixate targets paired with an auditory cue for variable time periods (300–1000msec)and then to maintain fixation after the target was turned off,for as long as the auditory tone was present (at least 1–2sec).During all fixations,the room was illumi-nated (through small red lights)such that the animals could easily establish relative distance estimates of the targets.Adequate fixation was defined when both eyes were within behavioral windows (separate for each eye)of Ϯ1.0°.Animals were trained to perform these fixation tasks for at least 1month before any experimental testing.As shown by the eye position traces of Figure 10,animals quickly learned to maintain ver-gence in complete darkness for a minimum of 500msec,as long as the auditory tone remained on.Responses were first obtained in animals with intact labyrinths.As stated above,acute responses were obtained during the first day after canal plugging (see Figs.5,10).Data were recorded up to 3months after plugging.Because no changes were observed in the horizontal transla-tional VOR properties after canal plugging (Angelaki,1998,Fig.7),data obtained at different times after plugging were included in the average (see Figs.4,6–9).The adequacy of canal plugging was physiologically verified by the lack of any response during earth-vertical axis yaw,pitch,and roll oscillations (0.1–1Hz).These responses were systematically tested throughout the 3month period of testing.Data analysisAll data analyses were performed on personal computers off-line.First,calibrated 3-D eye positions were expressed as rotation vectors.The horizontal,vertical,and torsional components of the calibrated eye position vectors were then smoothened and differentiated with a Savitz-ky–Golay quadratic polynomial filter using a 15-point forward and backward window (Savitzky and Golay,1964;Press et al.,1988).The angular eye velocity vector was computed from 3-D eye position and its derivative,as described previously (cf.Angelaki and Hess,1996a,b,c).For transient motion profiles,only runs without fast phases for the first 500msec were further analyzed.For sinusoidal stimuli,fast eye move-ments were removed from the eye velocity profiles using a semi-automated procedure based on time and amplitude windows set for the second derivative of the magnitude of eye velocity.Subsequently,average response cycles were computed from steady-state responsecomponentsFigure 1.Schematic diagram outlining the main experimental protocol of lateral motion and/or roll tilt oscillations at 0.5Hz.a ,Pure translation [black arrow ,gravitational acceleration (g );gray arrow ,translational ac-celeration (f )].b ,Pure roll tilt.c ,Combined roll tilt and translation with relative phases such that the translational component added to the gravity component along the IA axis,generating a resultant IA acceleration of 0.74G (thick arrow ).d ,Combined roll tilt and translation with relative phases such that the translational and gravitational components along the IA axis canceled each other (i.e.,IA acceleration,0G).318J.Neurosci.,January 1,1999,19(1):316–327Angelaki et al.•Neural Encoding of Inertial Motion(i.e.,horizontal,vertical,and torsional)for each eye.For each of these average response cycles,peak response amplitude and phase were deter-mined by fitting a sine function (including first and second harmonic,as well as a direct current offset)to both slow phase eye velocity and stimulus (angular or linear velocity)using a nonlinear least squares algorithm based on the Levenberg–Marquardt method.Phase was ex-pressed as the difference (in degrees)between peak eye velocity and peak angular velocity (for roll tilt and tilt–translation combination profiles)or linear velocity (for pure translational motion).The results presented here concentrate on horizontal eye movements,because they reflect the coding of head translation.In contrast,torsional eye movements were considered inappropriate in this regard,because they are primarily generated by semicircular canal activation,whereas static or otolith-induced eye torsion is known to have small gain in primates and humans (Diamond et al.,1979;Paige and Tomko,1991a;Haslwanter et al.,1992;Angelaki,1998).Statistical comparisons on the data were based on ANOVA.RESULTSTilt–translation discrimination in labyrinthine-intact animalsIn all animals with intact labyrinths,the elicited eye movements were compensatory for all stimulus combinations.As shown inFigure 2,for example,sinusoidal lateral translation (Translation only ),but not roll tilt oscillations (Roll tilt only ),elicited robust horizontal eye movements in complete darkness.Moreover,dur-ing the combined Roll tilt ϩTranslation and Roll tilt ϪTranslation motion profiles,the elicited horizontal eye movements were sim-ilar to those generated during Translation only motion.Thus,the horizontal eye movements generated in labyrinthine-intact ani-mals totally ignored the linear accelerations caused by changes in head orientation relative to gravity during the roll movement.In fact,for all stimulus conditions (Translation only ,Roll tilt only ,Roll tilt ϩTranslation ,and Roll tilt ϪTranslation motion proto-cols),the direction and magnitude of the horizontal response remained compensatory to the translational component of linear acceleration and was related neither to the acceleration produced by the roll tilt nor to the resultant IA acceleration.This was particularly striking for the Roll tilt ϪTranslation protocols in which robust horizontal eye movements were generated,despite the fact that the resultant IA acceleration was zero.As reported previously (Tweed et al.,1994;Angelaki andHess,Figure 2.Tilt–translation discrimination in a labyrinthine-intact rhesus monkey.Torsional,vertical,and horizontal components of eye position (E tor ,E ver ,and E hor ,respectively)and slow phase eye velocity (⍀tor ,⍀ver ,and ⍀hor ,respectively)of the right eye during lateral translation and/or roll tilt at 0.5Hz in complete darkness.Left to Right ,The stimuli consisted of Translation motion only ,Roll tilt only ,Roll tilt ϩTranslation motion,and Roll tilt ϪTranslation motion.Dotted lines are zero position (straight-ahead gaze)and zero eye velocity.The stimulus traces (bottom )show sled position (H trans ,positive direction to the left)and roll tilt position (H roll ,positive tilt toward right ear-down).Positive eye movement directions are leftward,downward,and clockwise (upper pole of the eye toward the right ear).Angelaki et al.•Neural Encoding of Inertial Motion J.Neurosci.,January 1,1999,19(1):316–3273191996b),a small horizontal eye velocity modulation was often present during roll head movements.This has been further quan-tified in Figure 3in which sensitivity and phase of horizontal eye velocity during earth-horizontal and earth-vertical axis roll oscil-lations (filled and open symbols ,respectively)are compared with those generated during lateral translation (triangles )(Angelaki,1998,Fig.6).The horizontal eye movements elicited during both earth-horizontal and earth-vertical roll oscillations (i.e.,rotations with the animals supine)were significantly smaller than those elicited during lateral head translation at the same frequency.The observation that horizontal eye movements appropriately discriminated for tilt and translation is further illustrated in Figure 4.In the frequency range tested,the results were indepen-dent of stimulus frequency (0.16,0.5,and 1Hz;F (4,23)ϭ0.81;p Ͼ0.05).Accordingly,robust horizontal eye movements were gen-erated only in the presence of translational motion (Fig.4,Tran only ,Roll ϩTran ,Roll ϪTran ).In contrast,the horizontal eye movement components elicited during Roll only motion were significantly smaller in amplitude than those generated during Translation only motion (F (1,15)ϭ68.0;p Ͻ0.05).During the combined Roll tilt ϩTranslation and Roll tilt ϪTranslation motion profiles,the horizontal eye movements were indistinguishable from those generated during Translation only motion (F (2,23)ϭ2.1;p Ͼ0.05).In fact,their amplitude and phase were always appropriate for gaze compensation during head translation.Tilt–translation discrimination in canal-plugged animalsAs shown in Figures 5and 6,results were different in canal-inactivated animals.Figure 5illustrates responses from an animal acutely after canal plugging.Data from both canal-plugged ani-mals have been summarized for all tested frequencies in Figure 6,A and B ,respectively.Responses to two stimuli were of particular interest.First,during Roll tilt only stimulation,a robust horizontal response component was observed in canal-plugged,but not labyrinthine-intact,animals.In fact,the horizontal responses in canal-plugged animals were indistinguishable during Translation only and Roll tilt only motions (F (1,22)ϭ3.78;p Ͼ0.05).Second,horizontal responses differed for each of the Translation only ,Roll tilt ϩTranslation ,and Roll tilt ϪTranslation motion profiles (F (2,32)ϭ115.5;p ϽϽ0.05).Most noticeably,in the Roll tilt ϪTranslation stimulus condition,horizontal slow phase velocity was negligible,as was the resultant IA acceleration (Fig.5).Different tilt–translation combinationsTo further corroborate these results,the tilt–translation combi-nation protocols were expanded at 0.5Hz in two different ways (Table 1B ).First,peak roll oscillation amplitude was kept con-stant (21.8°,corresponding to a peak gravitational acceleration component of 0.37G along the IA axis),whereas peak sled oscil-lation amplitude varied.Second,peak sled oscillation amplitude was kept constant (0.4G),whereas peak roll oscillationamplitudeFigure parison of horizontal eye velocity elicited during roll and translation.Mean ϮSD peak horizontal eye velocity sensitivity (ex-pressed in degrees/second/gravity,where G ϭ9.81m/sec 2)and phase have been plotted separately for earth-horizontal and earth-vertical roll oscillations (filled and open symbols ,respectively).Roll oscillations:squares ,Ϯ90°(0.01–0.2Hz);circles ,Ϯ22°(0.1–0.5Hz)and Ϯ5°(1Hz);lateral translations:triangles (Angelaki,1998,Fig.6,average data from five animalsreplotted).Figure 4.Translational (horizontal)VOR as a function of stimulus type in labyrinthine-intact animals.Mean ϮSD peak horizontal eye velocity from four monkeys with intact semicircular canals,tested at 1,0.5,and 0.16Hz (stimulus parameters are shown in Table 1A ).Note that primate VOR correctly discriminates between tilt and translation at all tested frequencies.320J.Neurosci.,January 1,1999,19(1):316–327Angelaki et al.•Neural Encoding of Inertial Motion。