A model for worldwide tracking of distributed objects
AModelforWorldwideTrackingofDistributedObjectsMaartenvanSteen,FranzJ.Hauck,AndrewS.TanenbaumVrijeUniversiteit,Amsterdam
AbstractWedescribeaserviceforlocatingdistributedobjectsidentifiedbylocation-independentobjectidentifiers.Anobjectinourmodelisphysicallydistributed,withmultipleactivecopiesondifferentmachines.Pro-cessesmustbindtoanobjectinordertoinvokeitsmethods.Partofthebindingprotocolisconcernedwithcontactingtheobject,whichoffersoneormorecontactpoints.Anobjectcanchangeitscontactpointsinthecourseoftime,thusexhibitingmigrationbehavior.Wepresentasolutiontofindinganobject’scon-tactpointswhichisbasedonaworldwidedistributedsearchtreethatadaptsdynamicallytoindividualmigrationpatterns.
1IntroductionTheintroductionoftheWorldWideWebandtheeaseofaccesstotheInternetisradicallychang-ingourperceptionofworldwidedistributedsystems.Suchsystemsshouldallowustoeasilyshareandexchangeinformation.Thisalsomeansthatitshouldbeeasytotracksourcesofin-formation,evenifthesesourcesmovebetweendifferentlocations.(Wedonotaddresstheprob-lemoffindingrelevantsourcesofinformationasisdoneby,forexample,resourcediscoveryservices[11].)Akeyroleintrackingsourcesofinformationisplayedbynamingsystems.Animportantproblemwithcurrentnamingsystemsforwideareanetworksisthatnamesarelocation-dependent:anameistightlycoupledtothelocationoftheobjectitrefersto.Forexam-ple,aURLsuchashttp://www.ripn.net/nic/rfc/rfc1737.txtisthenameofaWebpagecontainingthetextofRFC1737.Thenamereflectsexactlywherethepageisstored.Ifthepageismovedorreplicated,thenamewillhavetochangeaswell.Whatisneededisanamingandidentifica-tionfacilitythathidesallaspectsofanobject’slocation.Usersshouldnotbeconcernedwhereanobjectislocated,whetheritcanmove,whetheritisreplicated,andifitisreplicated,howconsistencybetweenreplicasismaintained.Thismechanismshouldbeavailabletoallapplica-tionsasastandardfacility.Aboveall,itshouldscaletotheentireworld,andbeabletohandletrillionsofobjects.Inthispaper,weoutlineasolutionforlocatingobjectsusinglocation-independentidenti-fiers.Ourapproachisbasedonamodelinwhichprocessesinteractandcommunicatethroughdistributedsharedobjects[5].Eachobjectoffersoneormoreinterfaces,eachconsistingofasetofmethods.Objectsarepassive;clientthreadsuseobjectsbyexecutingthecodefortheirmethods.Inorderforaprocesstoinvokeanobject’smethod,itmustfirstbindtothatobject.Thismeansthataninterfacebelongingtotheobject,aswellasanimplementationofthatin-terfacemustbeplacedintheprocess’addressspace.Tothisend,adistributedobjecthasoneormorecontactpoints.Acontactpointspecifiesthenetworkaddressandprotocolwithwhichinitialcommunicationwiththeobjectcantakeplace.Anobject’scontactpointsmaychangeinthecourseoftime.Forexample,anobjectcanbesaidtoexpandinto,orwithdrawfromaregionwhencontactpointsinthatregionareestablishedorremoved,respectively.Weproposeatwo-levelnaminghierarchyforfindingcontactpoints.Thefirstleveldealswithhierarchicallyorganized,user-definednamespaces.Thesenamespacesarehandledbyadistributednamingservice.However,wheretraditionalnameserviceimplementationsmain-tainname-to-addressbindings,namesinourapproacharemappedtoobjecthandles.Anobjecthandleisagloballyunique,andlocation-independentobjectidentifier.(Theyhavealsobeencoinedpurenamesin[10].)Objecthandlesformthesecondlevelinthenaminghierarchy.Eachobjecthandleismappedtoanobject’scontactaddresses.Acontactaddressisadescriptionofacontactpoint,suchasanIPaddressortheaddressofthecurrentcellinthecaseofmobiletele-phones.Itisthetaskofalocationservicetomaintainthemappingbetweenobjecthandlesandcontactaddresses.Thedesignofapossiblelocationserveristhesubjectofthispaper.Oursolutioncomprisesasearchtreeinwhichanobject’scontactaddressesarestoredatrel-ativelystablelocations,neartotheplaceswheretheobjectcanbereached.Weshowhowthesestablelocationsareidentifieddynamically,andthattheymaychangeasthemigrationbehav-ioroftheobjectchangesovertime.Storingcontactaddressesatstablelocationspermitsustoeffectivelycachelocationpointers.Thecombinationofdynamicallyidentifyingstablestoragelocationsforcontactaddresses,andcachingpointerstothoselocations,isnew.Theresultisalocationservicethatishighlyefficientbyexploitinglocalityinlookupandupdateoperations.Locationservicesarenotnewandhaveshowntoberelativelyeasytoimplementinlocaldis-tributedsystems.However,theybecomemuchmorecomplicatedwhenscalabilityistakenintoaccount.WefirstpresentthelogicalorganizationofourlocationserviceinSection2,andsomeimportantoptimizationsinSection3.ThescalabilityofourapproachisdiscussedinSection4.WeconcludewithacomparisontorelatedworkinSection5.
Matlab GPU计算解决方案
M = ceil((numel(x)-W)/stride);%iterations needed o = cell(M, 1); % preallocate output for i = 1:M % What are the start points thisSP = (i-1)*stride:step: … (min(numel(x)-W, i*stride)-1); % Move the data efficiently into a matrix X = copyAndWindowInput(x, window, thisSP); % Take lots of fft's down the colmuns
+
谢谢！
+
Matlab 集群推荐配置
集群 AMAX Xn-1113G， Xn-4002G Tesla卡 • Tesla C2070 (6 GB) • Tesla C2075 (6GB) 新系统: • CPU: 2 x 4core Xeon E5645 • Memory: 48GB • Disk: 500 GB • GPU: 1~2 Tesla C2070/C2075 • 40Gb Infiniband
z = gather(x); % Bring back into MATLAB
+100 Functions support GPU Arrays
fft, fft2, ifft, ifft2
Matrix multiplication (A*B) Matrix left division (A\b)
LU factorization ‘ .’ abs, acos, …, minus, …, plus, …, sin, …
Panasonic GP-US932 3CCD HD摄像头系统说明书
Broadening the possibilities of video expression 1920 x 1080 True HD 3CCD cameraPanasonic ,s 3CCD camera with true 16 x 9 multi format high definition delivers sharp, pure color images. The camera is an ideal solution for microscopy, industrial endoscopy, special effects, and many other applications.Conventional imageGP-US932 imageT r u e m u l t i -f o r m a t H D I n a d d i t i o n t o t h e 1080i (1920 x 1080) t r u e H D m o d e , 720p (1280 x 720), 480p a n d 480i (720x 480) m o d e s a r e se l e c t a b l ef o r s h ar p , h i g h r e s o l u t i o n f l i c k e r -f r e e i m a g e s .*The images are samples.E x p a n d e d d y n a m i c r a n g e D e t a i l i n t h e b r i g h t a r e a s a n d c o n t r as ti n t h e d a r k a r e a s a r e r e p r o d u c e da s a w e l l -b a l a nc ed i m a ge .(T h e t w o i m a ge s t o t he r i g h ta r e a c tua l p i c t u r e s u s i n gt he e x p a n d e d d y n a mi c r a n g e fu n c t i o n.)T r u e -t o -l i f e c o l o r s T w e l v e i n d e p e nd e n t l y a d j u s t a b l e a x i s I n p a r t i c u l a r , t h ee x c el l e n t r e d -c o l o rr e p r o d u c i b i l i t yi s s u i t e d f o r b i o l o g i c a l a n d m ed i ca l a p p l i c a t i o n s .*Recommended lenses are optionally available.The new 1/3-type progressive CCD features exceptionally high sensitivity with a large light-receiving area for each pixel. Balanced high resolution and S/N ratio is achieved from the combination of high-performance image processing technology implemented by a new digital signal processor (DSP).New high-sensitivity progressive CCDProgressive capture is followed by 14-bit A/D conversion and newly developed DSP for 19-bit internal processing. The result is extraordinary high-precision 1920 x 1080 true HD image output.Newly developed DSP with 14-bit A/D conversionand 19-bit processing functionsHigh-sensitivity 3CCDFujinon* HD lensFujinon* SD lensSpecifications of Recommend LensesRecommend LensesHAF4.8DA-1XA4x7.5DA-1TF2.8DA-8TF4DA-8TF8DA-8TF15DA-8Model No.Manufacturer Focal Length (mm)Zoom RatioMaximum Aperture RatioAngle of View (˚)HorizontalVerticalMinimum Object Distance (m / ft)Filter Thread Mount FocusIrisLength (from focal plane)(mm / inch)Full Aperture (mm / inch)Weight (g / lbs)HAF4.8DA-1Fujinon*4.8 2.2 57.07˚34.05˚0.1 / 0.33M55C Manual Manual 53.126 / 2.092(in air)ø42 / ø1.65495 / 0.21XA4x7.5DA-1Fujinon*7.5 – 304 2.8 38.38˚ – 9.94˚22.18˚ – 5.61˚0.45 / 1.48M52C Manual Manual 178.926 / 7.044(in air)ø54 / ø2.126500 / 1.1TF2.8DA-8 Fujinon*2.8 2.2 85.98˚55.40˚0.1 / 0.33 N/A C Manual Manual 64.025 / 2.521(in air)ø34 / ø1.33975 / 0.17TF4DA-8 Fujinon*4 2.2 66.25˚40.36˚0.1 / 0.33 M27 x 0.5C Manual Manual 63.025 / 2.481(in air)ø29 / ø1.14270 / 0.15TF8DA-8 Fujinon*8 2.2 36.14˚20.82˚0.1 / 0.33M25.5 x 0.5C Manual Manual 56.526 / 2.225(in air)ø29 / ø1.14260 / 0.13TF15DA-8 Fujinon*15 2.2 19.74˚11.19˚0.1 / 0.33M25.5 x 0.5C Manual Manual 56.526 / 2.225(in air)ø29 / ø1.14260 / 0.13HD LensesSD Lenses* Fujinon Lenses: Please contact to your distributorPanasonic technology enables high definition image quality covering a wide range of applicationsThe lineup includes HDMI output and HD-SDI/SD-SDI output models for different applications and purposes.HDMI output model lineupHDMI, HDMI logo, and High-Definition Multimedia Interface are trademarks orregistered trademarks of HDMI Licensing LLC.Beautiful, true-to-life colors are reproduced. Each of the 12 axis can be independently adjusted without affecting the adjacent color vector. The excellent red-color reproduction is ideal for biological and medical applications.Excellent color performanceA higher-level vertical resolution is obtained from P/I conversion, line conversion, and down conversion of native images with high vertical resolution from full-frame 59.94 fps progressive scanning. High image quality unparalleled by electronically interpolated interlace scanning is obtained.High-resolution native progressive scanConventional imageGP-US932 image*The images are samples.Simply select the appropriate functions from the list of camera functions displayed on the monitor screen to complete the setting.Images can be adjusted easily and efficiently while observing the images.Easy set-up menuThe functions provide high-precision true HD outputs.14-bit A/D conversion and 19-bit processing DSPThe new proprietary expanded dynamic range function expands the contrast of the dark areas while maintaining detail in the bright areas. Objects with high contrast can be represented as natural images.Proprietary expanded dynamic range functionConventional imageExpanded dynamic range image*Actual camera images<Parameters>Each of the three independent scene files has twelve parameters that can be customized to suit any applications.Three scene filesDetail Red detail Gamma KneeBlack stretch Dynamic range White clipFlare compensationDigital noise reduction Color matrix Chroma gain Total pedestalElectronic zoom up to 2.5xFreeze function White balanceElectronic shutter Gain control Electronic zoom up to 2.5x allows checking finer detail.Motionless video images can be displayed while capturing video.ATW (auto-tracking white balance) mode,AWC (automatic white balance) mode, or manual white balancemode can be selected according to the illumination of the scene.ELC mode (automatic shutter speed control accordingto the object`s amount of light), STEP mode (selection from 1/100, 1/250, 1/500, 1/1000, 1/2000, 1/4000, or 1/10000 to obtain the optimal setting), or select MANU mode.AUTO (automatic gain control) will provide automatic adjustment of sensitivity. Manual adjustment of sensitivity is also available.Other features。
外文翻译---视频监控系统
A System for Video Surveillance andMonitoringThe thrust of CMU research under the DARPA Video Surveillance and Monitoring (VSAM) project is cooperative multi-sensor surveillance to support battlefield awareness. Under our VSAM Integrated Feasibility Demonstration (IFD) contract, we have developed automated video understanding technology that enables a single human operator to monitor activities over a complex area using a distributed network of active video sensors. The goal is to automatically collect and disseminate real-time information from the battlefield to improve the situational awareness of commanders and staff. Other military and federal law enforcement applications include providing perimeter security for troops, monitoring peace treaties or refugee movements from unmanned air vehicles, providing security for embassies or airports, and staking out suspected drug or terrorist hide-outs by collecting time-stamped pictures of everyone entering and exiting the building.Automated video surveillance is an important research area in the commercial sector as well. Technology has reached a stage where mounting cameras to capture video imagery is cheap, but finding available human resources to sit and watch that imagery is expensive. Surveillance cameras are already prevalent in commercial establishments, with camera output being recorded to tapes that are either rewritten periodically or stored in video archives. After a crime occurs – a store is robbed or a car is stolen – investigators can go back after the fact to see what happened, but of course by then it is too late. What is needed is continuous 24-hour monitoring and analysis of video surveillance data to alert security officers to a burglary in progress, or to a suspicious individual loitering in the parking lot, while options are still open for avoiding the crime.Keeping track of people, vehicles, and their interactions in an urban or battlefield environment is a difficult task. The role of VSAM video understanding technology in achieving this goa l is to automatically “parse” people and vehicles from raw video, determine their geolocations, and insert them into dynamic scene visualization. We have developed robust routines for detecting and tracking moving objects. Detected objects are classified into semantic categories such as human, human group, car, and truck using shape and color analysis, and these labels are used to improve tracking using temporal consistency constraints. Further classification of human activity, suchas walking and running, has also been achieved. Geolocations of labeled entities are determined from their image coordinates using either wide-baseline stereo from two or more overlapping camera views, or intersection of viewing rays with a terrain model from monocular views. These computed locations feed into a higher level tracking module that tasks multiple sensors with variable pan, tilt and zoom to cooperatively and continuously track an object through the scene. All resulting object hypotheses from all sensors are transmitted as symbolic data packets back to a central operator control unit, where they are displayed on a graphical user interface to give a broad overview of scene activities. These technologies have been demonstrated through a series of yearly demos, using a testbed system developed on the urban campus of CMU.Detection of moving objects in video streams is known to be a significant, and difficult, research problem. Aside from the intrinsic usefulness of being able to segment video streams into moving and background components, detecting moving blobs provides a focus of attention for recognition, classification, and activity analysis, making these later processes more efficient since only “moving” pixels need be considered.There are three conventional approaches to moving object detection: temporal differencing ; background subtraction; and optical flow. Temporal differencing is very adaptive to dynamic environments, but generally does a poor job of extracting all relevant feature pixels. Background subtraction provides the most complete feature data, but is extremely sensitive to dynamic scene changes due to lighting and extraneous events. Optical flow can be used to detect independently moving objects in the presence of camera motion; however, most optical flow computation methods are computationally complex, and cannot be applied to full-frame video streams in real-time without specialized hardware.Under the VSAM program, CMU has developed and implemented three methods for moving object detection on the VSAM testbed. The first is a combination of adaptive background subtraction and three-frame differencing . This hybrid algorithm is very fast, and surprisingly effective – indeed, it is the primary algorithm used by the majority of the SPUs in the VSAM system. In addition, two new prototype algorithms have been developed to address shortcomings of this standard approach. First, a mechanism for maintaining temporal object layers is developed to allow greater disambiguation of moving objects that stop for a while, are occluded by other objects,and that then resume motion. One limitation that affects both this method and the standard algorithm is that they only work for static cameras, or in a ”stepand stare” mode for pan-tilt cameras. To overcome this limitation, a second extension has beendeveloped to allow background subtraction from a continuously panning and tilting camera . Through clever accumulation of image evidence, this algorithm can be implemented in real-time on a conventional PC platform. A fourth approach to moving object detection from a moving airborne platform has also been developed, under a subcontract to the Sarnoff Corporation. This approach is based on image stabilization using special video processing hardware.The current VSAM IFD testbed system and suite of video understanding technologies are the end result of a three-year, evolutionary process. Impetus for this evolution was provided by a series of yearly demonstrations. The following tables provide a succinct synopsis of the progress made during the last three years in the areas of video understanding technology, VSAM testbed architecture, sensor control algorithms, and degree of user interaction. Although the program is over now, the VSAM IFD testbed continues to provide a valuable resource for the development and testing of new video understanding capabilities. Future work will be directed towards achieving the following goals:l better understanding of human motion, including segmentation and tracking of articulated body parts;l improved data logging and retrieval mechanisms to support 24/7 system operations;l bootstrapping functional site models through passive observation of scene activities;l better detection and classification of multi-agent events and activities;l better camera control to enable smooth object tracking at high zoom; andl acquisition and selection of “best views” with the eventual goal of recognizing individuals in the scene.视频监控系统在美国国防部高级研究计划局，视频监控系统项目下进行的一系列监控装置研究是一项合作性的多层传感监控，用以支持战场决策。
多智能体系统自适应跟踪控制
多智能体系统自适应跟踪控制赵蕊;朱美玲;徐勇【摘要】The leader-follower tracking problems of second-order multi-agent systems with intrinsic nonlinear dynamics are studied. It assumes that each following agent can access the relative position and velocity information with its neigh-bors, the position and velocity information of the leader is only accessed by a subset of the following agents, and the leader's non-zero reference input cannot be available by any following agents. To track the active leader, a distributed adaptive consensus protocol is proposed for each following agent in the case that the interaction relationship among agents is undi-rected connected graph. The protocol effectively avoids the uncertainty of global information. The consensus tracking problem can be transformed into the stability problem of error system. Based on the theory of Lyapunov stability and matrix theory, it gets the sufficient conditions which guarantee the system to reach a leader-follower tracking consensus. Finally, a simulation example is given to verify the effectiveness of the obtained.%基于带有非线性动态的二阶多智能体系统,研究了在有动态领导者条件下的跟踪一致性问题.假设跟随者只能获取邻居智能体的相对状态信息,只有一部分跟随者可以获得领导者的位置和速度信息,领导者的控制输入非零且不被任何一个跟随者可知.在通信拓扑为无向连通图的条件下,为了避免全局信息的不确定性,设计了分布式自适应控制协议.将系统的一致性问题转化为误差系统的一致性问题,通过Lyapunov稳定性理论和矩阵理论分析得到了该协议使系统达到一致的充分条件.最后用仿真例子证明了设计方法的有效性.【期刊名称】《计算机工程与应用》【年(卷),期】2017(053)018【总页数】5页(P39-43)【关键词】多智能体系统;一致性;分布式控制;自适应控制;领导者【作者】赵蕊;朱美玲;徐勇【作者单位】河北工业大学理学院,天津 300401;河北工业大学理学院,天津300401;河北工业大学理学院,天津 300401【正文语种】中文【中图分类】TP13一致性，是智能体组成的网络系统的一类集体行为，近年来由于它广泛应用在生物系统、传感器网络、无人机编队控制等领域，引起了许多学者的关注，得到了大量研究成果[1-5]。
卫星定位理论与方法-第15次课-卫星定位误差源
1.10 0.91 0.91 1.14
0.48 0.42 0.4 0.5
0.59 0.5 0.48 0.59
1 0.83 0.83 1.04
1.2 1 0.91 1.18
1.2 1.1 1 1.27
0.96 0.85 0.79 1
Ex) 100m(2DRMS) accuracy ⇒ 42m(CEP)
Now has roughly the same accuracy as PPS Used by military receivers before Y-code lock is established
Scatter plot of horizontal accuracy 2 May 2000
Processing Algorithms, Operational Mode and Other Enhancements
1、Whether the user is moving or stationary. Clearly repeat observations at a stationary station would permit an improvement in precision due to the effect of averaging over time. A moving GPS receiver does not offer this possibility. 2、Whether the results are required in real-time, or if post-processing of the data is possible. Real-time positioning requires a “robust” but less precise technique to be used. The luxury of post-processing the data permits more sophisticated modelling and processing of GPS data to minimise the magnitude of residual biases and errors. 3、The level of measurement noise has a considerable influence on the precision attainable with GPS. Low measurement noise would be expected to result in comparatively high accuracy. Hence carrier phase measurements are the basis for high accuracy techniques, while pseudo-range measurements are used for low accuracy applications.
2021年北京市丰台区高三一模英语试题[附答案]
![2021年北京市丰台区高三一模英语试题[附答案]](https://360docs-1393072327.cos.ap-beijing.myqcloud.com/648b051b0c22590103029d61.webp)
丰台区2021年高三年级第二学期综合练习（一）英语2021.03本试卷满分共100分考试时间90分钟注意事项：1.答题前，考生务必先将答题卡上的学校、年级、班级、姓名、准考证号用黑色字迹签字笔填写清楚，并认真核对条形码上的准考证号、姓名，在答题卡的“条形码粘贴区”贴好条形码。
2.本次考试所有答题均在答题卡上完成。
选择题必须使用2B铅笔以正确填涂方式将各小题对应选项涂黑，如需改动，用橡皮擦除干净后再选涂其它选项。
非选择题必须使用标准黑色字迹签字笔书写，要求字体工整、字迹清楚3.请严格按照答题卡上题号在相应答题区内作答，超出答题区域书写的答案无效，在试卷、草稿纸上答题无效。
4.请保持答题卡卡面清洁，不要装订、不要折叠、不要破损。
第一部分：知识运用(共两节，30分)第一节完形填空(共10小题；每小题1.5分，共15分)阅读下面短文，掌握其大意，从每题所给的A、B、C、D四个选项中，选出最佳选项，并在答题卡上将该项涂黑。
This was the fifth time I’d been to the National Annual Competition. Reporters had been saying that I looked unbeatable. Everyone expected me to __1__. But I knew something was __2__ because I couldn’t get this one picture out of my head; a picture of me, falling. “Go away,” I’d say, But the image wouldn’t __3__.It was time to skate. The music started, slowly, and I told myself, “Have fun, Michael! It’s just a(n) __4__.”Once the music picked up, I started skating faster, I’d practiced the routine so manytimes, and I didn’t have to think about __5__ came next. But when I came down from thejump, my foot slipped from under me. I put a hand on the ice to __6__ myself, but it didn’tdo any good.Things kept getting __7__. On a triple flip(三周跳) I spun through the air, and justas I landed, my whole body went down again. There I was, flat on the ice, with the whole world __8__.I didn’t think I’d be able to pull myself together. But as I got up, I heard an amazing __9__. People were clapping in time to the music. They were trying to give me courage.I wasn’t surprised by my scores. However, the audience’s clapping woke me up! I was so busy trying not to __10__ that I forgot to feel what was in my heart—the love for skating.1. A. win B. enjoy C. share D. relax2. A. challenging B. missing C. wrong D. dangerous3. A. return B. leave C. appear D. stay4. A. sport B. activity C. picture D. accident5. A. when B. why C. who D. what6. A. prepare B. catch C. comfort D. measure7. A. clearer B. easier C. heavier D. worse8. A. watching B. expecting C. ignoring D. changing9. A. voice B. story C. sound D. idea10. A. collapse B. resist C. fall D. escape第二节语法填空(共10小题；每小题1.5分，共15分)阅读下列短文，根据短文内容填空，在未给提示词的空白处仅填写1个适当的单词，在给出提示词的空白处用括号内所给词的正确形式填空。
外文文献常用句式
Useful expressions for paper-writing Notice:All of the following sentences are derived from papers and the internet.目录一、研究方法表述类： (2)二、摘要总结类： (9)三、公式表述类： (10)四、其他表达： (11)一、研究方法表述类：A great number of research results have been reported , for example[1]—[5]★A neural network based dynamics compensation method has been proposed for trajectory control of a robot system[11].A combined approach of neural network and sliding mode technology for both feedback linearization and control error compesation has been presented[12].1、研究目的的表示方法The purpose of this investigation is to ...The main focus of this study is ...The objective of the present work is to ...The aim of the present study is to ...The present study is aimed at ...The present study is designed to ...The present study is an attempt to ...We have embarked on research attempting to ...This study is undertaken with the intent of ...The present investigation is conducted to ...This study was undertaken to ...To gain a better understanding of ...The investigation concentrated on efforts to ...The present study is performed in an effort to ...2、研究动机的表示方法Since the early literature contained a few reports of ...Because of the potential importance of ..., we have investigaed ... Because of the economic potential of ..., we decided to study ... Current work in this laboratory ..., stimulated interest in determining some of ...Prompted by ..., we initiated an examination of ...In view of ..., this study was conducted to examine ...The finding of ..., led us to reinvestigate ...A recent report ..., encouraged us to ...Little attention/effort has been given to ...... are poorly understood ...... have been poorly characterized ...The question have been raised as to whether or not ...... the question arose...3、研究内容的表示方法This article examines ...This research assessed ...This study documents ...The present work has shown ...This report describes ...The paper presents ...Work presented here introduces ...Our forthcoming studies will establish ...In this report, we report ...Here we describe ...In this report we examine ...In this reprot we describe ...We report here ...... this is the first report of ...This is the first report ...This report contains the first ...Our results are the first report on ...We report here for the first time ...This ..., is the first to ..., reported for ...,This report documents the first ...... this is the first time that ,,,The novelty of this research lies in ...Of particular interest and novelty is ...The evidence presented in this communication demonstrtes ... The data presented in this report represent ...The major idea addressed in this studies ...The emphasis of this study is ...This study is an attempt to ...4、研究报告的数量表示方法..., much efforts has gone into the study of ...Many research groups have recently been involved with ... ... have received fairly intensive study... have done a considerable amount of work on ...Many studies have addressed ...There have been many investigations into ...There have been numerous studies ...A substantial amount of ... information is available on ... There are only a few reprots of ...Only a few studies have dealt with ...Only a few studies have bean performed on...... there are very few studies ...Few studies have involved ...Few studies have centered on ...Investigations ... are extremely few ...A surprisingly limited amount of information exists on ... Reports on ... are extremely scarce.... has been the subject of only a limited number of studies.Information ... is limited.We found no reprots of ...We know of no report concerning ......, no studies ... have been reported ...There are no reports on ...no ... have been documented ...... no information is available concerning ...No data have been published ...To date, no reports have appeared concerning ... no ... is reported ...None have been reported for ...... information ... is ... lacking ...Virtually nothing is known about ...Little is known of ...very little actually is known about ...There is little known about ...5、注意、兴趣的表示方法... has not received as much attention ...Less attention has been paid ...Relatively little attention has been directed ... ... have received very little attention ...Little attention has been given to ...Attention was focused on ...... has recently received increased attention.There is currently great interest in ...... has been the focus of intense research interest. ... has been become a subject of considerable interest.6、研究正在进行的表示方法Studies are under way to ...... are currently under study.Further work is in progress ...Further experiments are in progress to ...Further investigations are in progress to ...Attempts to ... are currently in progress.Efforts continue ...We are presently attempting to determine ...Further studies ... are being conducted ...Our laboratory presently is involved with ...... is being investigated.7、将来工作的建议的表示方法Further work is needed ...Further work is required ...... is worthy of further study.Much more research is needed ...... has to be elucidated.... have to be determined.... requires further testing ...... makes ... worthy of further study.Further studies are contemplated to ...Further research is planned to ...continuing studies will yield further insight into ... Further research ... may yield...Further research should explore ...Further studies should clarify ...... remains to be determined.... remain to be investigated, and ... remains to be tested. ... remains to be established.What remains to be resolved ...... remains to be shown.... remains unexplained...., it remains unknown.... remain unanswered ...8、结论的表示方法In conclusion, ...This conclusion is supported ... by ... finding that ... ... leads to the conclusion that ...二、摘要总结类：★Simulations and experiments are carried out on AdeptOne robot.★From the simulation and experimental results,the effectiveness and usefulness of the proposed control sysytem are confirmed.★This paper addresses the issue of trajectory tracking control based on a neural network controller for industrial manipulators.In this paper,we present a new and simple control system consisting of a traditional controller for trajectory tracking control of industrial robot manipulators.★This paper describes a vision-based navigation method in an indoor environment for an autonomous mobile robot which can avoid obstacles.★★In this method, the self-localiation of the robot is done with a model-based vision system,and a non-stop navigation is realized by a retroactive position correction system.We present a robust and automatic method for evaluating the accurancy of weed discrimination algorithms. The proposed method is based onsimualated agronomic images and a crop weed discrimination algorithm can be dividided into the two following steps. Firstly,……. Afterwards,….In this research ,we aim at high precision trajectory tracking control of the industrial robot manipulators using simple and applicable contrl method.三、公式表述类：The dynamic model can be easily derived and expressed systematically with the formulation as follows:Formulation (1)The detail mathematical description of the network is given byFormulaion (2)四、其他表达：An industrial manipulator AdepOne is adopted as an experimental test bed.★Trajectory tracking control simulations and experiments are carried out. The results demonstrate effectiveness and usefulness of the proposed control system.★For this reason,we design the neural network controller such that it takes the important part on which the linear controller has shown its limitation and/or powerlessness.Other advantages of the neural networks often cited are parallel distributed structure,and learning ability.Theoretically speaking,System implementation,however,is difficult to perform because of the existence of the uncertainties of….。
四大安全会议论文题目
2009and2010Papers:Big-4Security ConferencespvoOctober13,2010NDSS20091.Document Structure Integrity:A Robust Basis for Cross-site Scripting Defense.Y.Nadji,P.Saxena,D.Song2.An Efficient Black-box Technique for Defeating Web Application Attacks.R.Sekar3.Noncespaces:Using Randomization to Enforce Information Flow Tracking and Thwart Cross-Site Scripting Attacks.M.Van Gundy,H.Chen4.The Blind Stone Tablet:Outsourcing Durability to Untrusted Parties.P.Williams,R.Sion,D.Shasha5.Two-Party Computation Model for Privacy-Preserving Queries over Distributed Databases.S.S.M.Chow,J.-H.Lee,L.Subramanian6.SybilInfer:Detecting Sybil Nodes using Social Networks.G.Danezis,P.Mittal7.Spectrogram:A Mixture-of-Markov-Chains Model for Anomaly Detection in Web Traffic.Yingbo Song,Angelos D.Keromytis,Salvatore J.Stolfo8.Detecting Forged TCP Reset Packets.Nicholas Weaver,Robin Sommer,Vern Paxson9.Coordinated Scan Detection.Carrie Gates10.RB-Seeker:Auto-detection of Redirection Botnets.Xin Hu,Matthew Knysz,Kang G.Shin11.Scalable,Behavior-Based Malware Clustering.Ulrich Bayer,Paolo Milani Comparetti,Clemens Hlauschek,Christopher Kruegel,Engin Kirda12.K-Tracer:A System for Extracting Kernel Malware Behavior.Andrea Lanzi,Monirul I.Sharif,Wenke Lee13.RAINBOW:A Robust And Invisible Non-Blind Watermark for Network Flows.Amir Houmansadr,Negar Kiyavash,Nikita Borisov14.Traffic Morphing:An Efficient Defense Against Statistical Traffic Analysis.Charles V.Wright,Scott E.Coull,Fabian Monrose15.Recursive DNS Architectures and Vulnerability Implications.David Dagon,Manos Antonakakis,Kevin Day,Xiapu Luo,Christopher P.Lee,Wenke Lee16.Analyzing and Comparing the Protection Quality of Security Enhanced Operating Systems.Hong Chen,Ninghui Li,Ziqing Mao17.IntScope:Automatically Detecting Integer Overflow Vulnerability in X86Binary Using Symbolic Execution.Tielei Wang,Tao Wei,Zhiqiang Lin,Wei Zou18.Safe Passage for Passwords and Other Sensitive Data.Jonathan M.McCune,Adrian Perrig,Michael K.Reiter19.Conditioned-safe Ceremonies and a User Study of an Application to Web Authentication.Chris Karlof,J.Doug Tygar,David Wagner20.CSAR:A Practical and Provable Technique to Make Randomized Systems Accountable.Michael Backes,Peter Druschel,Andreas Haeberlen,Dominique UnruhOakland20091.Wirelessly Pickpocketing a Mifare Classic Card.(Best Practical Paper Award)Flavio D.Garcia,Peter van Rossum,Roel Verdult,Ronny Wichers Schreur2.Plaintext Recovery Attacks Against SSH.Martin R.Albrecht,Kenneth G.Paterson,Gaven J.Watson3.Exploiting Unix File-System Races via Algorithmic Complexity Attacks.Xiang Cai,Yuwei Gui,Rob Johnson4.Practical Mitigations for Timing-Based Side-Channel Attacks on Modern x86Processors.Bart Coppens,Ingrid Verbauwhede,Bjorn De Sutter,Koen De Bosschere5.Non-Interference for a Practical DIFC-Based Operating System.Maxwell Krohn,Eran Tromer6.Native Client:A Sandbox for Portable,Untrusted x86Native Code.(Best Paper Award)B.Yee,D.Sehr,G.Dardyk,B.Chen,R.Muth,T.Ormandy,S.Okasaka,N.Narula,N.Fullagar7.Automatic Reverse Engineering of Malware Emulators.(Best Student Paper Award)Monirul Sharif,Andrea Lanzi,Jonathon Giffin,Wenke Lee8.Prospex:Protocol Specification Extraction.Paolo Milani Comparetti,Gilbert Wondracek,Christopher Kruegel,Engin Kirda9.Quantifying Information Leaks in Outbound Web Traffic.Kevin Borders,Atul Prakash10.Automatic Discovery and Quantification of Information Leaks.Michael Backes,Boris Kopf,Andrey Rybalchenko11.CLAMP:Practical Prevention of Large-Scale Data Leaks.Bryan Parno,Jonathan M.McCune,Dan Wendlandt,David G.Andersen,Adrian Perrig12.De-anonymizing Social Networks.Arvind Narayanan,Vitaly Shmatikov13.Privacy Weaknesses in Biometric Sketches.Koen Simoens,Pim Tuyls,Bart Preneel14.The Mastermind Attack on Genomic Data.Michael T.Goodrich15.A Logic of Secure Systems and its Application to Trusted Computing.Anupam Datta,Jason Franklin,Deepak Garg,Dilsun Kaynar16.Formally Certifying the Security of Digital Signature Schemes.Santiago Zanella-Beguelin,Gilles Barthe,Benjamin Gregoire,Federico Olmedo17.An Epistemic Approach to Coercion-Resistance for Electronic Voting Protocols.Ralf Kuesters,Tomasz Truderung18.Sphinx:A Compact and Provably Secure Mix Format.George Danezis,Ian Goldberg19.DSybil:Optimal Sybil-Resistance for Recommendation Systems.Haifeng Yu,Chenwei Shi,Michael Kaminsky,Phillip B.Gibbons,Feng Xiao20.Fingerprinting Blank Paper Using Commodity Scanners.William Clarkson,Tim Weyrich,Adam Finkelstein,Nadia Heninger,Alex Halderman,Ed Felten 21.Tempest in a Teapot:Compromising Reflections Revisited.Michael Backes,Tongbo Chen,Markus Duermuth,Hendrik P.A.Lensch,Martin Welk22.Blueprint:Robust Prevention of Cross-site Scripting Attacks for Existing Browsers.Mike Ter Louw,V.N.Venkatakrishnan23.Pretty-Bad-Proxy:An Overlooked Adversary in Browsers’HTTPS Deployments.Shuo Chen,Ziqing Mao,Yi-Min Wang,Ming Zhang24.Secure Content Sniffing for Web Browsers,or How to Stop Papers from Reviewing Themselves.Adam Barth,Juan Caballero,Dawn Song25.It’s No Secret:Measuring the Security and Reliability of Authentication via’Secret’Questions.Stuart Schechter,A.J.Bernheim Brush,Serge Egelman26.Password Cracking Using Probabilistic Context-Free Grammars.Matt Weir,Sudhir Aggarwal,Bill Glodek,Breno de MedeirosUSENIX Security2009promising Electromagnetic Emanations of Wired and Wireless Keyboards.(Outstanding Student Paper)Martin Vuagnoux,Sylvain Pasini2.Peeping Tom in the Neighborhood:Keystroke Eavesdropping on Multi-User Systems.Kehuan Zhang,XiaoFeng Wang3.A Practical Congestion Attack on Tor Using Long Paths,Nathan S.Evans,Roger Dingledine,Christian Grothoff4.Baggy Bounds Checking:An Efficient and Backwards-Compatible Defense against Out-of-Bounds Errors.Periklis Akritidis,Manuel Costa,Miguel Castro,Steven Hand5.Dynamic Test Generation to Find Integer Bugs in x86Binary Linux Programs.David Molnar,Xue Cong Li,David A.Wagner6.NOZZLE:A Defense Against Heap-spraying Code Injection Attacks.Paruj Ratanaworabhan,Benjamin Livshits,Benjamin Zorn7.Detecting Spammers with SNARE:Spatio-temporal Network-level Automatic Reputation Engine.Shuang Hao,Nadeem Ahmed Syed,Nick Feamster,Alexander G.Gray,Sven Krasser8.Improving Tor using a TCP-over-DTLS Tunnel.Joel Reardon,Ian Goldberg9.Locating Prefix Hijackers using LOCK.Tongqing Qiu,Lusheng Ji,Dan Pei,Jia Wang,Jun(Jim)Xu,Hitesh Ballani10.GATEKEEPER:Mostly Static Enforcement of Security and Reliability Policies for JavaScript Code.Salvatore Guarnieri,Benjamin Livshits11.Cross-Origin JavaScript Capability Leaks:Detection,Exploitation,and Defense.Adam Barth,Joel Weinberger,Dawn Song12.Memory Safety for Low-Level Software/Hardware Interactions.John Criswell,Nicolas Geoffray,Vikram Adve13.Physical-layer Identification of RFID Devices.Boris Danev,Thomas S.Heydt-Benjamin,Srdjan CapkunCP:Secure Remote Storage for Computational RFIDs.Mastooreh Salajegheh,Shane Clark,Benjamin Ransford,Kevin Fu,Ari Juels15.Jamming-resistant Broadcast Communication without Shared Keys.Christina Popper,Mario Strasser,Srdjan Capkun16.xBook:Redesigning Privacy Control in Social Networking Platforms.Kapil Singh,Sumeer Bhola,Wenke Lee17.Nemesis:Preventing Authentication and Access Control Vulnerabilities in Web Applications.Michael Dalton,Christos Kozyrakis,Nickolai Zeldovich18.Static Enforcement of Web Application Integrity Through Strong Typing.William Robertson,Giovanni Vigna19.Vanish:Increasing Data Privacy with Self-Destructing Data.(Outstanding Student Paper)Roxana Geambasu,Tadayoshi Kohno,Amit A.Levy,Henry M.Levy20.Efficient Data Structures for Tamper-Evident Logging.Scott A.Crosby,Dan S.Wallach21.VPriv:Protecting Privacy in Location-Based Vehicular Services.Raluca Ada Popa,Hari Balakrishnan,Andrew J.Blumberg22.Effective and Efficient Malware Detection at the End Host.Clemens Kolbitsch,Paolo Milani Comparetti,Christopher Kruegel,Engin Kirda,Xiaoyong Zhou,XiaoFeng Wang 23.Protecting Confidential Data on Personal Computers with Storage Capsules.Kevin Borders,Eric Vander Weele,Billy Lau,Atul Prakash24.Return-Oriented Rootkits:Bypassing Kernel Code Integrity Protection Mechanisms.Ralf Hund,Thorsten Holz,Felix C.Freiling25.Crying Wolf:An Empirical Study of SSL Warning Effectiveness.Joshua Sunshine,Serge Egelman,Hazim Almuhimedi,Neha Atri,Lorrie Faith Cranor26.The Multi-Principal OS Construction of the Gazelle Web Browser.Helen J.Wang,Chris Grier,Alex Moshchuk,Samuel T.King,Piali Choudhury,Herman VenterACM CCS20091.Attacking cryptographic schemes based on”perturbation polynomials”.Martin Albrecht,Craig Gentry,Shai Halevi,Jonathan Katz2.Filter-resistant code injection on ARM.Yves Younan,Pieter Philippaerts,Frank Piessens,Wouter Joosen,Sven Lachmund,Thomas Walter3.False data injection attacks against state estimation in electric power grids.Yao Liu,Michael K.Reiter,Peng Ning4.EPC RFID tag security weaknesses and defenses:passport cards,enhanced drivers licenses,and beyond.Karl Koscher,Ari Juels,Vjekoslav Brajkovic,Tadayoshi Kohno5.An efficient forward private RFID protocol.Come Berbain,Olivier Billet,Jonathan Etrog,Henri Gilbert6.RFID privacy:relation between two notions,minimal condition,and efficient construction.Changshe Ma,Yingjiu Li,Robert H.Deng,Tieyan Li7.CoSP:a general framework for computational soundness proofs.Michael Backes,Dennis Hofheinz,Dominique Unruh8.Reactive noninterference.Aaron Bohannon,Benjamin C.Pierce,Vilhelm Sjoberg,Stephanie Weirich,Steve Zdancewicputational soundness for key exchange protocols with symmetric encryption.Ralf Kusters,Max Tuengerthal10.A probabilistic approach to hybrid role mining.Mario Frank,Andreas P.Streich,David A.Basin,Joachim M.Buhmann11.Efficient pseudorandom functions from the decisional linear assumption and weaker variants.Allison B.Lewko,Brent Waters12.Improving privacy and security in multi-authority attribute-based encryption.Melissa Chase,Sherman S.M.Chow13.Oblivious transfer with access control.Jan Camenisch,Maria Dubovitskaya,Gregory Neven14.NISAN:network information service for anonymization networks.Andriy Panchenko,Stefan Richter,Arne Rache15.Certificateless onion routing.Dario Catalano,Dario Fiore,Rosario Gennaro16.ShadowWalker:peer-to-peer anonymous communication using redundant structured topologies.Prateek Mittal,Nikita Borisov17.Ripley:automatically securing web2.0applications through replicated execution.K.Vikram,Abhishek Prateek,V.Benjamin Livshits18.HAIL:a high-availability and integrity layer for cloud storage.Kevin D.Bowers,Ari Juels,Alina Oprea19.Hey,you,get offof my cloud:exploring information leakage in third-party compute clouds.Thomas Ristenpart,Eran Tromer,Hovav Shacham,Stefan Savage20.Dynamic provable data possession.C.Christopher Erway,Alptekin Kupcu,Charalampos Papamanthou,Roberto Tamassia21.On cellular botnets:measuring the impact of malicious devices on a cellular network core.Patrick Traynor,Michael Lin,Machigar Ongtang,Vikhyath Rao,Trent Jaeger,Patrick Drew McDaniel,Thomas Porta 22.On lightweight mobile phone application certification.William Enck,Machigar Ongtang,Patrick Drew McDaniel23.SMILE:encounter-based trust for mobile social services.Justin Manweiler,Ryan Scudellari,Landon P.Cox24.Battle of Botcraft:fighting bots in online games with human observational proofs.Steven Gianvecchio,Zhenyu Wu,Mengjun Xie,Haining Wang25.Fides:remote anomaly-based cheat detection using client emulation.Edward C.Kaiser,Wu-chang Feng,Travis Schluessler26.Behavior based software theft detection.Xinran Wang,Yoon-chan Jhi,Sencun Zhu,Peng Liu27.The fable of the bees:incentivizing robust revocation decision making in ad hoc networks.Steffen Reidt,Mudhakar Srivatsa,Shane Balfe28.Effective implementation of the cell broadband engineTM isolation loader.Masana Murase,Kanna Shimizu,Wilfred Plouffe,Masaharu Sakamoto29.On achieving good operating points on an ROC plane using stochastic anomaly score prediction.Muhammad Qasim Ali,Hassan Khan,Ali Sajjad,Syed Ali Khayam30.On non-cooperative location privacy:a game-theoretic analysis.Julien Freudiger,Mohammad Hossein Manshaei,Jean-Pierre Hubaux,David C.Parkes31.Privacy-preserving genomic computation through program specialization.Rui Wang,XiaoFeng Wang,Zhou Li,Haixu Tang,Michael K.Reiter,Zheng Dong32.Feeling-based location privacy protection for location-based services.Toby Xu,Ying Cai33.Multi-party off-the-record messaging.Ian Goldberg,Berkant Ustaoglu,Matthew Van Gundy,Hao Chen34.The bayesian traffic analysis of mix networks.Carmela Troncoso,George Danezis35.As-awareness in Tor path selection.Matthew Edman,Paul F.Syverson36.Membership-concealing overlay networks.Eugene Y.Vasserman,Rob Jansen,James Tyra,Nicholas Hopper,Yongdae Kim37.On the difficulty of software-based attestation of embedded devices.Claude Castelluccia,Aurelien Francillon,Daniele Perito,Claudio Soriente38.Proximity-based access control for implantable medical devices.Kasper Bonne Rasmussen,Claude Castelluccia,Thomas S.Heydt-Benjamin,Srdjan Capkun39.XCS:cross channel scripting and its impact on web applications.Hristo Bojinov,Elie Bursztein,Dan Boneh40.A security-preserving compiler for distributed programs:from information-flow policies to cryptographic mechanisms.Cedric Fournet,Gurvan Le Guernic,Tamara Rezk41.Finding bugs in exceptional situations of JNI programs.Siliang Li,Gang Tan42.Secure open source collaboration:an empirical study of Linus’law.Andrew Meneely,Laurie A.Williams43.On voting machine design for verification and testability.Cynthia Sturton,Susmit Jha,Sanjit A.Seshia,David Wagner44.Secure in-VM monitoring using hardware virtualization.Monirul I.Sharif,Wenke Lee,Weidong Cui,Andrea Lanzi45.A metadata calculus for secure information sharing.Mudhakar Srivatsa,Dakshi Agrawal,Steffen Reidt46.Multiple password interference in text passwords and click-based graphical passwords.Sonia Chiasson,Alain Forget,Elizabeth Stobert,Paul C.van Oorschot,Robert Biddle47.Can they hear me now?:a security analysis of law enforcement wiretaps.Micah Sherr,Gaurav Shah,Eric Cronin,Sandy Clark,Matt Blaze48.English shellcode.Joshua Mason,Sam Small,Fabian Monrose,Greg MacManus49.Learning your identity and disease from research papers:information leaks in genome wide association study.Rui Wang,Yong Fuga Li,XiaoFeng Wang,Haixu Tang,Xiao-yong Zhou50.Countering kernel rootkits with lightweight hook protection.Zhi Wang,Xuxian Jiang,Weidong Cui,Peng Ning51.Mapping kernel objects to enable systematic integrity checking.Martim Carbone,Weidong Cui,Long Lu,Wenke Lee,Marcus Peinado,Xuxian Jiang52.Robust signatures for kernel data structures.Brendan Dolan-Gavitt,Abhinav Srivastava,Patrick Traynor,Jonathon T.Giffin53.A new cell counter based attack against tor.Zhen Ling,Junzhou Luo,Wei Yu,Xinwen Fu,Dong Xuan,Weijia Jia54.Scalable onion routing with torsk.Jon McLachlan,Andrew Tran,Nicholas Hopper,Yongdae Kim55.Anonymous credentials on a standard java card.Patrik Bichsel,Jan Camenisch,Thomas Gros,Victor Shouprge-scale malware indexing using function-call graphs.Xin Hu,Tzi-cker Chiueh,Kang G.Shin57.Dispatcher:enabling active botnet infiltration using automatic protocol reverse-engineering.Juan Caballero,Pongsin Poosankam,Christian Kreibich,Dawn Xiaodong Song58.Your botnet is my botnet:analysis of a botnet takeover.Brett Stone-Gross,Marco Cova,Lorenzo Cavallaro,Bob Gilbert,MartinSzydlowski,Richard A.Kemmerer,Christopher Kruegel,Giovanni VignaNDSS20101.Server-side Verification of Client Behavior in Online Games.Darrell Bethea,Robert Cochran and Michael Reiter2.Defeating Vanish with Low-Cost Sybil Attacks Against Large DHTs.S.Wolchok,O.S.Hofmann,N.Heninger,E.W.Felten,J.A.Halderman,C.J.Rossbach,B.Waters,E.Witchel3.Stealth DoS Attacks on Secure Channels.Amir Herzberg and Haya Shulman4.Protecting Browsers from Extension Vulnerabilities.Adam Barth,Adrienne Porter Felt,Prateek Saxena,and Aaron Boodman5.Adnostic:Privacy Preserving Targeted Advertising.Vincent Toubiana,Arvind Narayanan,Dan Boneh,Helen Nissenbaum and Solon Barocas6.FLAX:Systematic Discovery of Client-side Validation Vulnerabilities in Rich Web Applications.Prateek Saxena,Steve Hanna,Pongsin Poosankam and Dawn Song7.Effective Anomaly Detection with Scarce Training Data.William Robertson,Federico Maggi,Christopher Kruegel and Giovanni Vignarge-Scale Automatic Classification of Phishing Pages.Colin Whittaker,Brian Ryner and Marria Nazif9.A Systematic Characterization of IM Threats using Honeypots.Iasonas Polakis,Thanasis Petsas,Evangelos P.Markatos and Spiros Antonatos10.On Network-level Clusters for Spam Detection.Zhiyun Qian,Zhuoqing Mao,Yinglian Xie and Fang Yu11.Improving Spam Blacklisting Through Dynamic Thresholding and Speculative Aggregation.Sushant Sinha,Michael Bailey and Farnam Jahanian12.Botnet Judo:Fighting Spam with Itself.A.Pitsillidis,K.Levchenko,C.Kreibich,C.Kanich,G.M.Voelker,V.Paxson,N.Weaver,S.Savage13.Contractual Anonymity.Edward J.Schwartz,David Brumley and Jonathan M.McCune14.A3:An Extensible Platform for Application-Aware Anonymity.Micah Sherr,Andrew Mao,William R.Marczak,Wenchao Zhou,Boon Thau Loo,and Matt Blaze15.When Good Randomness Goes Bad:Virtual Machine Reset Vulnerabilities and Hedging Deployed Cryptography.Thomas Ristenpart and Scott Yilek16.InvisiType:Object-Oriented Security Policies.Jiwon Seo and Monica m17.A Security Evaluation of DNSSEC with NSEC3.Jason Bau and John Mitchell18.On the Safety of Enterprise Policy Deployment.Yudong Gao,Ni Pan,Xu Chen and Z.Morley Mao19.Where Do You Want to Go Today?Escalating Privileges by Pathname Manipulation.Suresh Chari,Shai Halevi and Wietse Venema20.Joe-E:A Security-Oriented Subset of Java.Adrian Mettler,David Wagner and Tyler Close21.Preventing Capability Leaks in Secure JavaScript Subsets.Matthew Finifter,Joel Weinberger and Adam Barth22.Binary Code Extraction and Interface Identification for Security Applications.Juan Caballero,Noah M.Johnson,Stephen McCamant,and Dawn Song23.Automatic Reverse Engineering of Data Structures from Binary Execution.Zhiqiang Lin,Xiangyu Zhang and Dongyan Xu24.Efficient Detection of Split Personalities in Malware.Davide Balzarotti,Marco Cova,Christoph Karlberger,Engin Kirda,Christopher Kruegel and Giovanni VignaOakland20101.Inspector Gadget:Automated Extraction of Proprietary Gadgets from Malware Binaries.Clemens Kolbitsch Thorsten Holz,Christopher Kruegel,Engin Kirda2.Synthesizing Near-Optimal Malware Specifications from Suspicious Behaviors.Matt Fredrikson,Mihai Christodorescu,Somesh Jha,Reiner Sailer,Xifeng Yan3.Identifying Dormant Functionality in Malware Programs.Paolo Milani Comparetti,Guido Salvaneschi,Clemens Kolbitsch,Engin Kirda,Christopher Kruegel,Stefano Zanero4.Reconciling Belief and Vulnerability in Information Flow.Sardaouna Hamadou,Vladimiro Sassone,Palamidessi5.Towards Static Flow-Based Declassification for Legacy and Untrusted Programs.Bruno P.S.Rocha,Sruthi Bandhakavi,Jerry I.den Hartog,William H.Winsborough,Sandro Etalle6.Non-Interference Through Secure Multi-Execution.Dominique Devriese,Frank Piessens7.Object Capabilities and Isolation of Untrusted Web Applications.Sergio Maffeis,John C.Mitchell,Ankur Taly8.TrustVisor:Efficient TCB Reduction and Attestation.Jonathan McCune,Yanlin Li,Ning Qu,Zongwei Zhou,Anupam Datta,Virgil Gligor,Adrian Perrig9.Overcoming an Untrusted Computing Base:Detecting and Removing Malicious Hardware Automatically.Matthew Hicks,Murph Finnicum,Samuel T.King,Milo M.K.Martin,Jonathan M.Smith10.Tamper Evident Microprocessors.Adam Waksman,Simha Sethumadhavan11.Side-Channel Leaks in Web Applications:a Reality Today,a Challenge Tomorrow.Shuo Chen,Rui Wang,XiaoFeng Wang Kehuan Zhang12.Investigation of Triangular Spamming:a Stealthy and Efficient Spamming Technique.Zhiyun Qian,Z.Morley Mao,Yinglian Xie,Fang Yu13.A Practical Attack to De-Anonymize Social Network Users.Gilbert Wondracek,Thorsten Holz,Engin Kirda,Christopher Kruegel14.SCiFI-A System for Secure Face Identification.(Best Paper)Margarita Osadchy,Benny Pinkas,Ayman Jarrous,Boaz Moskovich15.Round-Efficient Broadcast Authentication Protocols for Fixed Topology Classes.Haowen Chan,Adrian Perrig16.Revocation Systems with Very Small Private Keys.Allison Lewko,Amit Sahai,Brent Waters17.Authenticating Primary Users’Signals in Cognitive Radio Networks via Integrated Cryptographic and Wireless Link Signatures.Yao Liu,Peng Ning,Huaiyu Dai18.Outside the Closed World:On Using Machine Learning For Network Intrusion Detection.Robin Sommer,Vern Paxson19.All You Ever Wanted to Know about Dynamic Taint Analysis and Forward Symbolic Execution(but might have been afraid to ask).Thanassis Avgerinos,Edward Schwartz,David Brumley20.State of the Art:Automated Black-Box Web Application Vulnerability Testing.Jason Bau,Elie Bursztein,Divij Gupta,John Mitchell21.A Proof-Carrying File System.Deepak Garg,Frank Pfenning22.Scalable Parametric Verification of Secure Systems:How to Verify Ref.Monitors without Worrying about Data Structure Size.Jason Franklin,Sagar Chaki,Anupam Datta,Arvind Seshadri23.HyperSafe:A Lightweight Approach to Provide Lifetime Hypervisor Control-Flow Integrity.Zhi Wang,Xuxian Jiang24.How Good are Humans at Solving CAPTCHAs?A Large Scale Evaluation.Elie Bursztein,Steven Bethard,John C.Mitchell,Dan Jurafsky,Celine Fabry25.Bootstrapping Trust in Commodity Computers.Bryan Parno,Jonathan M.McCune,Adrian Perrig26.Chip and PIN is Broken.(Best Practical Paper)Steven J.Murdoch,Saar Drimer,Ross Anderson,Mike Bond27.Experimental Security Analysis of a Modern Automobile.K.Koscher,A.Czeskis,F.Roesner,S.Patel,T.Kohno,S.Checkoway,D.McCoy,B.Kantor,D.Anderson,H.Shacham,S.Savage 28.On the Incoherencies in Web Browser Access Control Policies.Kapil Singh,Alexander Moshchuk,Helen J.Wang,Wenke Lee29.ConScript:Specifying and Enforcing Fine-Grained Security Policies for JavaScript in the Browser.Leo Meyerovich,Benjamin Livshits30.TaintScope:A Checksum-Aware Directed Fuzzing Tool for Automatic Software Vulnerability Detection.(Best Student Paper)Tielei Wang,Tao Wei,Guofei Gu,Wei Zou31.A Symbolic Execution Framework for JavaScript.Prateek Saxena,Devdatta Akhawe,Steve Hanna,Stephen McCamant,Dawn Song,Feng MaoUSENIX Security20101.Adapting Software Fault Isolation to Contemporary CPU Architectures.David Sehr,Robert Muth,CliffBiffle,Victor Khimenko,Egor Pasko,Karl Schimpf,Bennet Yee,Brad Chen2.Making Linux Protection Mechanisms Egalitarian with UserFS.Taesoo Kim and Nickolai Zeldovich3.Capsicum:Practical Capabilities for UNIX.(Best Student Paper)Robert N.M.Watson,Jonathan Anderson,Ben Laurie,Kris Kennaway4.Structuring Protocol Implementations to Protect Sensitive Data.Petr Marchenko,Brad Karp5.PrETP:Privacy-Preserving Electronic Toll Pricing.Josep Balasch,Alfredo Rial,Carmela Troncoso,Bart Preneel,Ingrid Verbauwhede,Christophe Geuens6.An Analysis of Private Browsing Modes in Modern Browsers.Gaurav Aggarwal,Elie Bursztein,Collin Jackson,Dan Boneh7.BotGrep:Finding P2P Bots with Structured Graph Analysis.Shishir Nagaraja,Prateek Mittal,Chi-Yao Hong,Matthew Caesar,Nikita Borisov8.Fast Regular Expression Matching Using Small TCAMs for Network Intrusion Detection and Prevention Systems.Chad R.Meiners,Jignesh Patel,Eric Norige,Eric Torng,Alex X.Liu9.Searching the Searchers with SearchAudit.John P.John,Fang Yu,Yinglian Xie,Martin Abadi,Arvind Krishnamurthy10.Toward Automated Detection of Logic Vulnerabilities in Web Applications.Viktoria Felmetsger,Ludovico Cavedon,Christopher Kruegel,Giovanni Vigna11.Baaz:A System for Detecting Access Control Misconfigurations.Tathagata Das,Ranjita Bhagwan,Prasad Naldurg12.Cling:A Memory Allocator to Mitigate Dangling Pointers.Periklis Akritidis13.ZKPDL:A Language-Based System for Efficient Zero-Knowledge Proofs and Electronic Cash.Sarah Meiklejohn,C.Chris Erway,Alptekin Kupcu,Theodora Hinkle,Anna Lysyanskaya14.P4P:Practical Large-Scale Privacy-Preserving Distributed Computation Robust against Malicious Users.Yitao Duan,John Canny,Justin Zhan,15.SEPIA:Privacy-Preserving Aggregation of Multi-Domain Network Events and Statistics.Martin Burkhart,Mario Strasser,Dilip Many,Xenofontas Dimitropoulos16.Dude,Where’s That IP?Circumventing Measurement-based IP Geolocation.Phillipa Gill,Yashar Ganjali,Bernard Wong,David Lie17.Idle Port Scanning and Non-interference Analysis of Network Protocol Stacks Using Model Checking.Roya Ensafi,Jong Chun Park,Deepak Kapur,Jedidiah R.Crandall18.Building a Dynamic Reputation System for DNS.Manos Antonakakis,Roberto Perdisci,David Dagon,Wenke Lee,Nick Feamster19.Scantegrity II Municipal Election at Takoma Park:The First E2E Binding Governmental Election with Ballot Privacy.R.Carback,D.Chaum,J.Clark,J.Conway,A.Essex,P.S.Herrnson,T.Mayberry,S.Popoveniuc,R.L.Rivest,E.Shen,A.T.Sherman,P.L.Vora20.Acoustic Side-Channel Attacks on Printers.Michael Backes,Markus Durmuth,Sebastian Gerling,Manfred Pinkal,Caroline Sporleder21.Security and Privacy Vulnerabilities of In-Car Wireless Networks:A Tire Pressure Monitoring System Case Study.Ishtiaq Rouf,Rob Miller,Hossen Mustafa,Travis Taylor,Sangho Oh,Wenyuan Xu,Marco Gruteser,Wade Trappe,Ivan Seskar 22.VEX:Vetting Browser Extensions for Security Vulnerabilities.(Best Paper)Sruthi Bandhakavi,Samuel T.King,P.Madhusudan,Marianne Winslett23.Securing Script-Based Extensibility in Web Browsers.Vladan Djeric,Ashvin Goel24.AdJail:Practical Enforcement of Confidentiality and Integrity Policies on Web Advertisements.Mike Ter Louw,Karthik Thotta Ganesh,V.N.Venkatakrishnan25.Realization of RF Distance Bounding.Kasper Bonne Rasmussen,Srdjan Capkun26.The Case for Ubiquitous Transport-Level Encryption.Andrea Bittau,Michael Hamburg,Mark Handley,David Mazieres,Dan Boneh27.Automatic Generation of Remediation Procedures for Malware Infections.Roberto Paleari,Lorenzo Martignoni,Emanuele Passerini,Drew Davidson,Matt Fredrikson,Jon Giffin,Somesh Jha28.Re:CAPTCHAs-Understanding CAPTCHA-Solving Services in an Economic Context.Marti Motoyama,Kirill Levchenko,Chris Kanich,Damon McCoy,Geoffrey M.Voelker,Stefan Savage29.Chipping Away at Censorship Firewalls with User-Generated Content.Sam Burnett,Nick Feamster,Santosh Vempala30.Fighting Coercion Attacks in Key Generation using Skin Conductance.Payas Gupta,Debin GaoACM CCS20101.Security Analysis of India’s Electronic Voting Machines.Scott Wolchok,Erik Wustrow,J.Alex Halderman,Hari Prasad,Rop Gonggrijp2.Dissecting One Click Frauds.Nicolas Christin,Sally S.Yanagihara,Keisuke Kamataki3.@spam:The Underground on140Characters or Less.Chris Grier,Kurt Thomas,Vern Paxson,Michael Zhang4.HyperSentry:Enabling Stealthy In-context Measurement of Hypervisor Integrity.Ahmed M.Azab,Peng Ning,Zhi Wang,Xuxian Jiang,Xiaolan Zhang,Nathan C.Skalsky5.Trail of Bytes:Efficient Support for Forensic Analysis.Srinivas Krishnan,Kevin Z.Snow,Fabian Monrose6.Survivable Key Compromise in Software Update Systems.Justin Samuel,Nick Mathewson,Justin Cappos,Roger Dingledine7.A Methodology for Empirical Analysis of the Permission-Based Security Models and its Application to Android.David Barrera,H.Gunes Kayacik,Paul C.van Oorschot,Anil Somayaji8.Mobile Location Tracking in Metropolitan Areas:malnets and others.Nathanial Husted,Steve Myers9.On Pairing Constrained Wireless Devices Based on Secrecy of Auxiliary Channels:The Case of Acoustic Eavesdropping.Tzipora Halevi,Nitesh Saxena10.PinDr0p:Using Single-Ended Audio Features to Determine Call Provenance.Vijay A.Balasubramaniyan,Aamir Poonawalla,Mustaque Ahamad,Michael T.Hunter,Patrick Traynor11.Building Efficient Fully Collusion-Resilient Traitor Tracing and Revocation Schemes.Sanjam Garg,Abishek Kumarasubramanian,Amit Sahai,Brent Waters12.Algebraic Pseudorandom Functions with Improved Efficiency from the Augmented Cascade.Dan Boneh,Hart Montgomery,Ananth Raghunathan13.Practical Leakage-Resilient Pseudorandom Generators.Yu Yu,Francois-Xavier Standaert,Olivier Pereira,Moti Yung14.Practical Leakage-Resilient Identity-Based Encryption from Simple Assumptions.Sherman S.M.Chow,Yevgeniy Dodis,Yannis Rouselakis,Brent Waters15.Testing Metrics for Password Creation Policies by Attacking Large Sets of Revealed Passwords.Matt Weir,Sudhir Aggarwal,Michael Collins,Henry Stern16.The Security of Modern Password Expiration:An Algorithmic Framework and Empirical Analysis.Yinqian Zhang,Fabian Monrose,Michael K.Reiter17.Attacks and Design of Image Recognition CAPTCHAs.Bin Zhu,JeffYan,Chao Yang,Qiujie Li,Jiu Liu,Ning Xu,Meng Yi18.Robusta:Taming the Native Beast of the JVM.Joseph Siefers,Gang Tan,Greg Morrisett19.Retaining Sandbox Containment Despite Bugs in Privileged Memory-Safe Code.Justin Cappos,Armon Dadgar,JeffRasley,Justin Samuel,Ivan Beschastnikh,Cosmin Barsan,Arvind Krishnamurthy,Thomas Anderson20.A Control Point for Reducing Root Abuse of File-System Privileges.Glenn Wurster,Paul C.van Oorschot21.Modeling Attacks on Physical Unclonable Functions.Ulrich Ruehrmair,Frank Sehnke,Jan Soelter,Gideon Dror,Srinivas Devadas,Juergen Schmidhuber22.Dismantling SecureMemory,CryptoMemory and CryptoRF.Flavio D.Garcia,Peter van Rossum,Roel Verdult,Ronny Wichers Schreur23.Attacking and Fixing PKCS#11Security Tokens.Matteo Bortolozzo,Matteo Centenaro,Riccardo Focardi,Graham Steel24.An Empirical Study of Privacy-Violating Information Flows in JavaScript Web Applications.Dongseok Jang,Ranjit Jhala,Sorin Lerner,Hovav Shacham25.DIFC Programs by Automatic Instrumentation.William Harris,Somesh Jha,Thomas Reps26.Predictive Black-box Mitigation of Timing Channels.Aslan Askarov,Danfeng Zhang,Andrew Myers27.In Search of an Anonymous and Secure Lookup:Attacks on Structured Peer-to-peer Anonymous Communication Systems.Qiyan Wang,Prateek Mittal,Nikita Borisov28.Recruiting New Tor Relays with BRAIDS.Rob Jansen,Nicholas Hopper,Yongdae Kim29.An Improved Algorithm for Tor Circuit Scheduling.Can Tang,Ian Goldberg30.Dissent:Accountable Anonymous Group Messaging.Henry Corrigan-Gibbs,Bryan Ford31.Abstraction by Set-Membership—Verifying Security Protocols and Web Services with Databases.Sebastian Moedersheim。
基于径向基神经网络的列车速度跟踪控制研究
基于径向基神经网络的列车速度跟踪控制研究黄娟;魏宗寿【摘要】针对高速列车运行过程的非线性和运行环境复杂性,提出一种基于径向基(Radial Basis Function,RBF)神经网络模型的广义预测控制方法.采用数据驱动建模方法建立高速列车运行过程径向基神经网络模型,利用广义预测控制算法对列车速度进行跟踪.将神经网络所建模型作为广义预测控制的预测模型,进而推导出RBF 广义预测控制律的灵敏度公式.将该方法与PID、固定模型广义预测控制方法(Fixed Structure Generalized Predictive Control,FGPC)进行仿真对比,该方法体现出较高的精确度和鲁棒性.【期刊名称】《兰州工业学院学报》【年(卷),期】2019(026)002【总页数】5页(P74-78)【关键词】高速列车;径向基神经网络;广义预测控制;跟踪控制【作者】黄娟;魏宗寿【作者单位】[1]兰州交通大学自动控制研究所,甘肃兰州730070;[2]甘肃省高原交通信息工程及控制重点实验室,甘肃兰州730070;[1]兰州交通大学自动控制研究所,甘肃兰州730070;[2]甘肃省高原交通信息工程及控制重点实验室,甘肃兰州730070;【正文语种】中文【中图分类】TP273从近年来城市轨道交通无人自动驾驶技术的发展来看，自动驾驶(ATO)技术也必然会成为高速列车运行控制系统的趋势之一[1].列车自动驾驶需要解决的主要问题是自动调整列车运行速度，使列车安全、可靠、准时、高效地运行.因此，针对高速列车运行工况复杂、环境多变、非线性问题对高速列车运行过程进行精确建模与有效的速度跟踪控制方法进行研究具有重要的现实意义[2].在高速列车建模方面：文献[3]用T-S模型描述高速列车模型的非线性和时变性，但受线路条件的限制；文献[4]利用聚类算法建立多模型来描述高速列车的非线性与不确定性，但不能有效地处理模型间的平滑切换；文献[5]建立高速列车自动驾驶Hammerstein模型，但速度以设定值为中心波动较为明显.在控制方面：广义预测控制在处理复杂的非线性系统方面有明显优势[6]，也开始应用于高速列车速度追踪控制中，如文献[7～9]通过广义预测控制对高速列车速度位移进行跟踪控制，取得了较好的控制效果.径向基神经网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，文献[10]中提出径向基神经网络广义预测控制方法，应用到大型锌湿法炼铁厂除铁工艺控制过程中，工业实验证明了所提方法具有较好的跟踪控制性能和鲁棒性.文献[11]将基于径向基神经网络的模型预测方法用于废水处理过程的溶解氧浓度控制中，提供了一个结构动态变化的预测模型，并分析了闭环系统的稳定性和收敛性，提高了控制性能；故本文通过径向基神经网络描述高速列车运行过程，将径向基神经网络与广义预测控制结合，来实现对高速列车高精度和高鲁棒性的速度跟踪控制.1 基于RBF的多步预测模型设非线性系统由非线性离散时间(NARMAX)模型表示，即y(k)=F[y(t-1),…,y(t-ny);u(t-d),…,u(t-d-nu)]，式中:u(·)和y(·)分别为系统的输入和输出；F(·)为一个未知的连续非线性函数；d为非线性的时滞；ny和nu分别是系统的输出输入阶次.为了建立上述非线性系统模型，将RBF神经网络也选为NARMAX模型，即径向基神经网络结构如图1所示，网络输入为x(t)=[y(t-1),…,y(t-ny),u(t-d),…,u(t-d-nu)]T.包含1个输入层，1个输出层，和1个隐藏层，K个隐藏层节点的输出可以描述为(1)式中：ωk为第k个隐藏神经元和输出神经元的连接权重；k是隐藏神经元的数目；θk是第k个隐藏神经元的输出.且(2)式中：μk是第k个隐藏节点高斯核函数的中心向量，且μk=[μk1,μk2,…,μkn]T；σk是第k个隐藏节点高斯核函数的宽度；‖x(t)-μk‖是x和μk的欧氏距离.图1 RBF神经网络结构RBF神经网络采用梯度下降法调整连接权重ωk(t)、高斯核函数中心μk(t)和宽度σk(t)，来获得参数较优的神经网络模型.首先，定义一个目标函数(3)式中：y为系统实际输出；为神经网络输出，此过程的目标是使期望目标函数E最小.参数更新公式为(4)(5)式中：η为参数学习率；α为动量项因子(α∈[0,1)).2 速度跟踪广义预测控制广义预测控制是自校正控制与预测控制相结合的产物，是一类性能稳定且鲁棒性较强的控制系统.因此，本文通过设计广义预测控制器来对高速列车期望速度进行追踪.基于RBF模型的高速列车速度跟踪预测控制框图如图2所示.图2 基于RBF模型的速度跟踪控制框图定义如下广义预测性能指标(6)受限于(7)式中:分别为未来参考轨迹和预测输出；N1、N2、Nu分别为最小输出长度、预测长度和控制长度；λj为控制加权序列；Δu(t+j-1)为控制增量.将性能指标表示为如下矩阵形式，即(8)其中，Yr=[yr(t+N1)，yr(t+N1+1)，…,yr(t+N2)]TΔU=[Δu(t),Δu(t+1),…,Δu(k+Nu-1)]T,R=diag(λ1,λ2,…,λNu).(9)梯度下降法的基本观点是通过最小化性能指标来求得未来控制时域内的控制量，控制输入序列通过如下梯度更新，即(10)这里η>0是控制输入序列的优化步长，并且(11)其中(12)由式(6)～(9)可得(13)则(14)实现上述广义预测控制律，需计算雅可比矩阵中的灵敏度导数.本文采用较大的预测长度N2，保留广义预测控制中多步预测优势，同时考虑列车速度跟踪控制的实时性，取Nu=1，则雅可比矩阵简化为一个行向量.利用求导法则推导出灵敏度导数为(15)式中：i=0,…,N2-d.3 系统仿真3.1 RBF神经网络模型本文用多输入单输出RBF神经网络来描述高速列车这一非线性系统，模型定义如下(16)式中：y为系统实际输出；为神经网络输出.采集京沪铁路CRH380AL型高速列车某区间的实际运行数据，1 150组运行速度和控制力数据，选择900组数据样本训练RBF神经网络模型，剩余250组数据作为测试数据.RBF初始网络结构为5-6-1，参数学习率η=0.5，动量项因子为α=0.01，时滞d=3，训练过程中加入噪声，RBF测试数据误差曲线如图3所示，可以看出，高速列车测试输出与实际模型的输出误差为[-0.127 6, 0.102 3]km/h,在允许范围内.图3 RBF数据输出误差曲线3.2 速度跟踪控制列车按“牵引-恒速-惰行-恒速-牵引-恒速-惰行-制动”方式运行，基于上述所建立的RBF模型，采用广义预测控制对京沪高铁运营的CRH380AL列车进行速度跟踪控制，控制器参数N1=3，N2=3，Nu=1，R=0.3I.将仿真结果与PID、固定模型广义预测控制方法FGPC进行对比.速度跟踪曲线与误差曲线如图4～5所示.由图4可知，PID控制与FGPC在高速列车追踪控制启动过程中速度曲线偏离较大，在恒速和降速过程中发生振荡现象，从仿真结果中看出径向基广义预测控制(Radial Basis Function Generalized Predictive Control, RBF-GPC)跟踪精度高，控制效果好，对列车运行的复杂工况具有很好的适应性.图5通过速度追踪误差的对比，进一步说明RBF-GPC控制器速度误差小，满足CTCS-3列控系统的误差要求[12].图6为高速列车位移曲线，由图可看出，PID与FGPC两种控制方法与目标曲线偏差较大，RBF-GPC几乎能完全追踪目标参考曲线，体现了该方法较好的控制性能.图4 速度跟踪曲线对比图5 速度跟踪误差对比图6 位移曲线对比4 结语针对高速列车建模难和控制复杂的难题，提出了RBF-GPC方法，基于径向基神经网络建立高速列车运行过程的预测模型，仿真表明建模准确性高，所提出的控制方法能够有效追踪速度曲线，与PID和FGPC相比，本文方法控制性能好，鲁棒性更高.参考文献：【相关文献】[1] DONG H, NING B, CAI B, et al. Automatic Train Control System Development and Simulation for High-Speed Railways[J]. Circuits &Systems Magazine IEEE, 2010, 10(2):6-18.[2] LI Zhongqi, YANG Hui, ZHANG Kunpeng, et al. Distributed Model Predictive Control Based on Multi-agent Model for Electric Multiple Units[J]. Acta Automatic Sinica, 2014,40(11): 2625-2631.[3] YANG H, FU Y T, ZHANG K P. Generalized predictive control based on neurofuzzy model for electric multiple unit[C]// Proceedings of the Third International Conference on Digital Manufacturing and Automation, Guilin:IEEE,2012. 422-445.[4] 杨辉, 张坤鹏, 王昕, 等. 高速列车多模型广义预测控制方法[J]. 铁道学报. 2011, 34(8): 16-21.[5] 郭红弋, 孙志毅, 张春美. 动车组列车制动系统Hammerstein模型的广义预测控制研究[J]. 铁道学报, 2014, 36(6): 47-54.[6] WU M, WANG C, CAO W, et al. Design and application of generalized predictive control strategy with closed-loop identification for burn-through point in sintering process[J].Control Engineering Practice, 2012, 20(10): 1065-1074.[7] 李中奇, 杨振村, 杨辉, 等. 高速列车双自适应广义预测控制方法[J]. 中国铁道科学, 2015, 36(6): 120-126.[8] 杨辉, 刘盼, 李中奇. 基于Elman模型的高速列车速度跟踪控制[J]. 控制理论与应用, 2017, 34(1): 125-130.[9] 李中奇, 杨辉, 刘明杰, 等. 高速动车组制动过程的建模及跟踪控制[J].中国铁道科学, 2016,37(5):80-85.[10] XIE Shiwen, XIE Yongfang, HUANG Tingwen Huang et al. Generalized predictive control for industrial processes based on neuron adaptive splitting and merging RBF neural network[J]. IEEE Trans. Indus. Electric，2018,11(09):1-10.[11] HAN Hong-Gui, ZHANG Lu, HOU Ying, et al. Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network[J]. IEEE Transactions on Neural Networks and Learning Systems，2016,27(2):402-415.[12] FU Yating, YANG Hui, WANG Dianhui. Real-time optimal control of tracking running for high-speed electric multiple unit[J]. Information Sciences, 2017, 376:202-215.。
完整个人简历英语版通用7篇
完整个人简历英语版通用7篇简历是有针对性的自我介绍的一种规范化、逻辑化的书面表达。
对应聘者来说，简历是求职的"敲门砖"。
这次漂亮的小编为亲带来了7篇完整个人简历英语版，在大家参考的同时，也可以分享一下牛牛范文给您的好友哦。
优秀英文简历篇一Chinese Name:linyuanEnglish Name: Eddy ZhangSex: FEMaleBorn: 6/12/86University: zhongshan UniversityMajor: MarketingAddress: 388#, zhongshan UniversityTelephone: 一叁68****451Email:Job Objective:A Position offering challenge and responsibility in the realm of consumer affairs or marketing.Education:20xx-2019 Bejing University, College Of CommerceGraduating in July with a B. S. degree in Marketing.Fields of study include: economics, marketing, business law, statistics, calculus,psychology, sociology, social and managerial concepts in marketing, consumer behavior, sales force management, product policy, marketing research and forecast,marketing strategies.1994-20xx The No.2 Middle School of Xi"an.Social Activities:20xx-2019 Secretary of the Class League Branch.1994-20xx Class monitor.Summer Jobs:20xx Administrative Assistant in Sales Department of Xi"an Nokia Factory. Responsible for public relations, correspondence, expense reports, record keeping, inventory catalog.20xx Provisional employee of Sales Department of Xi"an Lijun Medical Instruments Equipment (Holdings) Company. Responsible for sorting orders, shipping arrangemeents, deliveries.Hobbies:Internet-surfing, tennis, travel.English Proficiency:College English Test-Band Six.Computer Skills:Microsoft office, Adobe Photoshop, etc.英文简历篇二Personal informationxxxxxGender: maleNationality: han nationalityAge: 30Marital status: marriedProfessional name: civil engineeringMajor in: civil engineeringPolitical appearance: league memberGraduate school: fujian engineering collegeGraduation time: July 2006Highest degree: bachelor degreeComputer level: proficientWork experience: over 10 yearsHeight: 一⑦2 cmWeight: 65 kgLocation: xinluo districtCensus register: xinluo districtobjectiveExpected career: bid, management classExpected salary: 4,000 to 5000Expected work area: xinluo districtExpected job quality: full timeThe quickest time to be on duty: be on dutyHousing: no needEducation/trainingEducation background:School name: university of chongqing (September 2012 to February 20壹伍) Professional name: municipal engineering education: bachelor degree Location: xiamen certificate:School name: fujian institute of engineering (September 2003 to June 2006)Professional name: secretarial education: junior collegeLocation: fuzhou certificate:Trained experience:Training institute: xiamen (May 2011 - October 2011)Class name: car driving licence certificate: C1Lesson description: driver#39;s licenseWork experienceCompany name: taihua construction company (July 20壹伍to January 20一⑦)Industry: real estate development, construction and engineering services (intermediary property supervision design) company nature: private enterpriseCompany size: 10 people below: longyanJob title: managementJob description: bidding, qualification, engineering managementCompany name: China jianli tian group co.，LTD. (June 2014 - May 20壹伍)Industry: real estate development, construction and engineering services (intermediary property supervision design) company nature: private enterpriseCompany size: 500 ~ 1000 people work place: longyanJob title: noJob description: responsible for the operation of longyan areaName of the company: longyan branch of the sixth engineering bureau of zhongcheng (October 20一叁to February 2014)Industry: real estate development, construction and engineering services (intermediary property, supervision and design) company nature: state-owned enterprisesCompany size: 50 ~ 200 people working place: longyanJob title: clerkJob description: qualification and biddingCompany name: xiamen tonganjie municipal engineering co.，LTD. (August 2009 to May 20一叁)Industry: real estate development, construction and engineering services (intermediary property, supervision and design) company nature: joint-stock enterprisesCompany size: 50 ~ 200 people working place: xiamen cityTitle: officerJob description: responsible for bidding and qualification and personnel management of engineersCompany name: fujian development and construction group co.，LTD. (feb 2006 - May 2009)Industry: real estate development, construction and engineering services (intermediary property supervision design) company nature: private enterpriseCompany size: 200 ~ 500 people working place: fuzhouJob title: clerkJob description: be responsible for bidding and qualification management. The company will distinguish the company from the recordSelf assessmentSelf-evaluation: work hardLanguage abilityLanguage name mastery degreeGood EnglishMandarin good大学生英文版个人简历篇三DorothyC.Thomas1473GoldleafLaneNewark,NJ07102Phone:201-564-2411EmailID:dorothy.c.thomas@OBJECTIVE:Toobtainanentry-levelpositioninanorganizationwheremywork-relatedskillsareutilizedtotheirmaxi mumpotential.EXPERIENCE:CastleIslandEngineeringWorks,SouthBoston,MAMay–Sept2001SummerPlacementPerformedtimestudiesoneachprocessinalargemanufacturingarea.Plannedthefloorlayoutforanewautomatedproductionline.CompletedAuto-CADdrawingsfortheSeniorEngineeronlinelayoutandergonomicspace-savingconce pts.Identifiedpotentialbottleneckstoproduction,anddevelopedmethodstoreduceandpreventtheseimp edimentstoefficiency.Completedchangerequestsonproductionproceduresanddrawings.DouglasEngineeringCo.Ltd.,Cambridge,MAJune–Sept2000SummerPlacementCompletedAuto-CADdrawingsofproposedlayoutsforalargeproductionfacilityinBoston.Reviewedproductionproceduresandengineeringspecsincludingmachinedrawingspriortosubmittalf orreviewinthechangeprocess.Developedandmaintainedadatabasefortrackingtechfiles,equipmentspecs,equipmentinstallationch ecklistsetc.EDUCATION:BostonUniversity,Boston,MA2000-PresentBSinMechanicalEngineering,GraduatedwithHonours.BostonCollege,Boston,MA1999–2001BSinComputerScienceRELEVANTINFORMATION:ProficientinMicrosoftWord,Excel,Access,PowerPoint,Auto-CADandJava.Participatedinatwo-weekcourseinMachineDesign,Christmas2000.OtherinterestsincludeAircraftModelmakinganddesign,carpentryandtoolmaking.HobbiesincludeFootball,Hockey,SwimmingandReading.英文简历制作篇四英文简历范例模板制作2则英文简历范例模板制作2则1、Position Sought: Computer Programmer with a foreign enterprise in Dalian2、Qualifications: Four years' work experience operating computers extensively, coupledwith educational preparation.3、Professional Experience: Computer Programmer, Sough China Computer Company, Guangzhou, from 1990 to date. Operate flow-charts, collect business infromation fro management, update methods of operation. Adept at operating IBM-PC and Compact computers.4、Educational Background: South China University of Technology. B.S. in Computer Science, July 1990.5、Courses included: Computer Science, Systems Design and Analysis, PASCAL Programming, Operating Systems, COBOL Programming, D-BASE Programming, FORTRAN Programming, Systems Management Dalian No.34 Middle School, 1981-19866、English Proficiency: Fluent in speaking, reading and writing.7、Hobbies: Bridge, computer games, boating, swimming.8、Personal Data:Born: November 29, 1970 in Dalian;Health: Excellent;Marital Status: Single;Height: 一⑦5cm; Weight: 68kg9、References: will be supplied upon request.英文简历（二）Personal Information:Family Name: XXXX Name: XXXDate of Birth: July 12, 1986 Birth Place: ChinaSex: Male Marital Status: UnmarriedTelephone: XXXXX E-mail:Work Experience:Nov. -present CCIDE Inc, as a director of software development and webpublishing .Organized and attended trade shows (Comdex 99) .Summer of BIT Company as a technician ,designed various web sites . Designed and maintained the web site of our division independently from s electing suitable materials, content editing to designing web page by FrontPage, Photoshop and Java as well ;Education:1991 - August Dept.of Automation, Tsinghua University, B.E.Achievements Activities:President and Founder of the Costumer CommitteeEstablished the organization as a member of BITPresident of Communications for the Marketing AssociationRepresentative in the Student AssociationComputer Abilities:Skilled in use of MS Frontpage, Win 95/NT, Sun, JavaBeans, HTML, CGI, JavaScript, Perl, Visual Interdev, Distributed Objects, CORBA, C, C++, Project 98, Office 97, Rational RequisitePro, Process, Pascal, PL/I and SQL softwareEnglish Skills:Have a good command of both spoken and written English .Past CET-6, TOEFL: 623; GRE: 22一叁Others:Aggressive, independent and be able to work under a dynamic environment. Have coordination skills, teamwork spirit. Studious nature and dedication are my greatest strengths.英文简历篇五Sex: Female National: Han Date of birth: July 1986 Marital status: unmarried Height: 壹伍3cmWeight: 53kg Residence: Fujian Longyan Is the location: Tongan District Xiamen, Fujian Graduated from the school: Vocational and Technical Institute of the East China Sea, XiamenEducation: specialist Professional Name: E-commerce Year of Graduation: 2007 Work experience: more than one year Contact Tel: 一叁888888888 Job intentions The nature of jobs: full-time Post Category: E-commerce / sales / B2C/C2C / Logistics Job Title: clerks, procurement, customer service, warehouse, etc.；Work areas: Xiamen Jimei District; Xiamen Tongan District; Treatment requirements: 1000-2000 Yuan / month do not need to provide housing Reported for duty time:may at any time Skills expertise Language skills: English; Putonghua standard Computer level: computer proficiency, OFFICE office automation software Educational Background: Time school qualifications September 2004 -July 2007 Xiamen, East China Sea Vocational and Technical College Work experience Company: Xiamen Shun-Qing Automation Technology Co.，Ltd.Time frame: December 2007 - January 2009 Company nature: private / private companies Their respective industries: trade, commerce, import and export To hold office: sales staff Job Description: Network marketing, as well as warehouse management, data, etc.Company: Xiamen Sky Express Logistics Time frame: March 2007 - December 2007 Company nature: private / private companies Industry: transportation, logistics, express delivery Post as: logistics / warehousing Job Description: 07-03 to 07-08 is responsible for customer service and express shipping operations 07-08 to 07-11 is responsible for freight service and billing Self-evaluation: I have a strong team spirit among colleagues, have good interpersonal relationships; good at coordination.During University I studied computer networks have some knowledge about computers, I seriously can bear hardships and stand hard work, self-motivated. After engaging in the service industry so I have learned patience, tolerance and self-control. What a year of sales experience I learned how to communicate with people, as well as self-learning. I am a person of honor and promised to do certain things other people do. Into action to appreciate the language of the people, hate the language into action.英文个人简历模板篇六Hello every one, First let me introduce myself. My name is , years old. i am from ,a beautiful city in henan province.it is famous as the capital of and enjoy yhe honer that l peony is the best in the world. played a very important role in chinese history. so it has a profound cultural background and many great heritagesites have been well reverved. such as longmen grotto, one of the three grottoes in china ang white horse temple, being regarded as the cradle of chnese buddhism. peony is world-famous. every year, many tourists travel to to see the beauty of peony .the people in my hometown are friendly, they welcome the travellers from all over the world.i like my hometown very much. I am very glad to be here for this interview. I graduated from College in July, and major in finance. Then, I was a teacher in abc, When I was a senior school student, I am interested in thought and began to read a certain classic work of Marxism, especially I finishedreading “the florilegium of Mao ZeDong”。