Digital Object Identifier (DOI) 10.1007s00220-006-0053-x Mathematical Physics A Microscopic
oid对象标识符 -回复
oid对象标识符-回复OID(Object Identifier)对象标识符是用于标识网络中的对象的一种标准方法。
它是一个由数字和点组成的全球唯一标识符,可以用于识别和定位对象,如设备、协议、服务以及其它网络资源。
OID在信息技术领域广泛应用,可以用于管理、监控、配置和故障诊断等方面。
本文将逐步介绍OID的概念、应用场景、结构和实际应用。
第一部分:OID的概念和作用(500字)OID是Object Identifier的缩写,它是一种全球唯一标识符,用于标识网络中的对象。
在网络领域,有许多不同的设备、协议、服务和资源,而OID提供了一种统一的方式来标识和定位这些对象。
使用OID,可以轻松地识别和管理网络中的各种组件。
OID在网络管理中的应用非常广泛。
它可以用于监控网络设备的状态和性能,比如路由器、交换机和服务器等。
另外,OID还可以用于配置网络设备,比如修改设备的参数和设置。
此外,OID还可以用于诊断网络故障,快速定位问题并采取相应的措施。
总之,OID是网络管理中不可或缺的一部分,它为网络管理员提供了强大的工具来管理和维护网络。
第二部分:OID的结构和表示方法(500字)OID由一系列的数字和点组成,每个数字都被称为一个子标识。
OID的结构和表示方法如下:1. 第一个子标识(称为节点标识)代表一个对象树(或者称为MIB树)的根节点,它是一个预定义的值,比如1.3.6.1。
2. 之后的子标识表示树状结构中的分支和叶子节点。
每个子标识的取值范围是0到39之间,其中0到2乘以39是保留值,表示私有或特定用途。
3. 用点分隔的数字序列表示一个完整的OID,比如1.3.6.1.2.1.2.2.1.1表示一个特定的对象。
OID的结构大大简化了对象的标识和定位过程。
通过将对象组织成层次结构,OID可以快速而准确地找到所需的对象。
此外,OID还具有全局唯一性,确保在整个网络中不存在重复的标识符。
这使得网络管理更加简单和高效。
GSMR接口需求规范
ERTMS/ETCS – Class 1GSM-R InterfacesClass 1 RequirementsREF : SUBSET-093ISSUE : 2.3.0DATE : 10-Oct-2005Company Technical Approval Management approval ALCATELALSTOMANSALDO SIGNALBOMBARDIERINVENSYS RAILSIEMENS1. M ODIFICATION H ISTORYIssue NumberDateSection Number Modification / Description Author0.1.0 (8-Aug-02) Creation based on subset052LK0.1.1 (8-Aug-02) All Minor editorial changes LK0.1.1ec All englishcheck JH0.2.0 (9-Sep-02) 3., 4.2, 4.1, 6.3, 7.2,8.2 Updated after email discussionLK0.3.0 (24-Oct-02) All Updated after FlorencemeetingLK+TS0.4.0 (14-Nov-02) All Updated after LondonmeetingLK0.5.0 (5-Dec-02) 4.2, 5.6.1, 6.2, 7.1,7.3, 9.2 Updated after Berlin meetingLK0.6.0 (12-Dec-02) 3., 6.3., 10.4.3 Email comments included TS+LK2.0.0 (12-Dec-02) Erroneous versionnumber 2.2.0correctedFinal issue LK2.1.0 (28-March-03)3.1.1.1, 6.3.1.3,7.1.1.1, 8.1.1.1 Update acc. to super group commentsLK2.2.0 (28-March-03) - Final version LK2.2.2.31-03-03 Versionnumberchangedfor release to the usersGroupWLH2.2.3 (12-June-03) All Update after Brussels mtg.and GSM-R Op. grp.commentsLK2.2.4 (26-June-03) editorial Draft release to UsersGroupJH2.2.5 - FormalreleaseJH 2.2.5.1 4.2, 6.2, 6.3, new 6.4 Update after Paris mtg. andGSM-R Op. grp. commentsLK2.2.5.2 Various update after further GSM-ROp grp reviewJH2.2.5.3 cleanversion JH 2.2.5.4 6.4 Updated after further GSM-R Op grp requestRB2.2.6 CleanversionRB2.2.6 revA (31-Jan-05) 4.2, 6.3, 6.4, Annex A Proposal for QoS parametervaluesLK2.2.6 revB (14-Feb-05) 6.3, 6.4, Annex A Updated after QoSmeeting#6 BrusselsLK2.2.6 revC (24-Feb-05) 6.3, 6.4, Annex A,Annex B added Updated during BerlinmeetingLK2.2.6 revD (25-Feb-05) 6.2, 6.3.5, 10.3, 10.5.2 Email comments inserted LK2.2.6 revE (6-Apr-05)3.1., 3.2,4.1,5.1,6.3,10.1, 10.3, 10.5, 10.7 Updated after QoSmeeting#7 BrusselsLK2.2.6 revF (25-Apr-05)3.1,4.1,5.1,6.3, 6.4,10.1, 10.3, 10.5, 10.6,10.7Edinburgh meeting TS+LK2.2.6revG (20-May-05)3.1, 5.1, 6.3, 6.4, 8.2 Changes according toBrussels meetingLK2.2.6revH (1-Sep-05) 4.1, 5.1, 6.3, 6.4, 7.2,10.3, 10.4, 10.5 Comments from SG andEEIGLK2.2.6revI (8-Sep-05) 5.1, 6.3, 6.4, 10.4 Zürich meeting PL+LK 2.3.0 (10-Oct-05) update for issue JH2. T ABLE OF C ONTENTS1.M ODIFICATION H ISTORY (2)2.T ABLE OF C ONTENTS (4)3.R EFERENCES (6)3.1Normative Documents (6)3.2Informative Documents (7)4.T ERMS AND DEFINITIONS (8)4.1Abbreviations (8)4.2Definitions (9)5.G ENERAL (10)5.1Scope of this document (10)5.2Introduction (10)6.E ND-TO-END SERVICE REQUIREMENTS TO GSM-R NETWORKS (12)6.1Data bearer service requirements (12)6.2Additional services (12)6.3Quality of Service requirements (13)6.3.1General (13)6.3.2Connection establishment delay (14)6.3.3Connection establishment error ratio (14)6.3.4Transfer delay (15)6.3.5Connection loss rate (15)6.3.6Transmission interference (15)6.3.7GSM-R network registration delay (16)6.4Summary of QoS requirements (16)7.R EQUIREMENTS TO FIXED NETWORK INTERFACE (17)7.1Foreword (17)7.2Interface definition (17)7.3Communication signalling procedures (17)8.R EQUIREMENTS TO MOBILE NETWORK INTERFACE (18)8.1Foreword (18)8.2Interface definition (18)9.A NNEX A(I NFORMATIVE) TRANSMISSION INTERFERENCE AND RECOVERY (19)9.1General (19)9.2Transmission interference in relation to HDLC (19)10.A NNEX B(INFORMATIVE)J USTIFICATION OF Q O S PARAMETER VALUES (22)10.1General (22)10.2Connection establishment delay (22)10.3Connection establishment error ratio (22)10.4Transfer delay (23)10.5Connection loss rate (23)10.5.1QoS targets (23)10.5.2Conclusions (24)10.6Transmission interference (24)10.7Network registration delay (26)3. R EFERENCESDocuments3.1 Normative3.1.1.1 This document list incorporates by dated or undated references, provisions from otherpublications. These normative references are cited at the appropriate place in the textand the publications are listed hereafter. For dated references, subsequentamendments to or revisions of any of these publications apply to this document onlywhen incorporated in it by amendment or revision. For undated references the latestedition of the publication referred to apply.Reference DateTitleU-SRS 02.02 ERTMS/ETCS Class 1; Subset 026; Unisig SRS, version 2.2.2 Subset 037 07.03 ERTMS/ETCS Class 1; Subset 037; EuroRadio FIS; Class1requirements, version 2.2.5EIRENE FRS 10.03 UIC Project EIRENE; Functional Requirements Specification.Version 6.0, CLA111D003EIRENE SRS 10.03 UIC Project EIRENE; System Requirements Specification.Version 14.0, CLA111D004ETS 300011 1992 ISDN; Primary rate user-network interface; Layer 1 specificationand test principlesETS 300102-1 1990 ISDN; User-network interface layer 3; Specification for basiccall controlETS 300125 1991 ISDN; User-network interface data link layer specificationsGSM04.21 12.00 Rate Adaptation on the MS-BSS Interface, v.8.3.0GSM 07.0711.98 ETSI TS 100916; Digital cellular telecommunications system(Phase 2+); AT command set for GSM Mobile Equipment (ME),GSM TS 07.07 version 6.5.0 Release 1997ITU-T V.24 02.00 List of definitions for interchange circuits between data terminalequipment (DTE) and data circuit-terminating equipment (DCE)ITU-T V.25ter 07/97 Serial asynchronous dialling and controlITU-T V.110 02.00 Support of data terminal equipments (DTEs) with V-series typeinterfaces by an integrated services digital network (ISDN) EuroRadio FFFIS 09.03 UIC ERTMS/GSM-R Unisig; Euroradio Interface Group; RadioTransmission FFFIS for Euroradio; A11T6001; version 12O-2475 09.03 UIC ERTMS/GSM-R Operators Group; ERTMS/GSM-R Qualityof Service Test Specification; O-2475; version 1.0Documents3.2 InformativeTitleReference DateEEIG 04E117 12.04 ETCS/GSM-R Quality of Service - Operational Analysis, v0.q(draft)ERQoS 08.04 GSM-R QoS Impact on EuroRadio and ETCS application,Unisig_ALS_ERQoS, v.0104. T ERMS AND DEFINITIONS4.1 AbbreviationsAT ATtention command setATD AT command DialB channel User channel of ISDNB m channel User channel of GSM PLMN on the air interfaceBRI Basic Rate InterfaceByte 1 start bit + 8 data bits + 1 stop bitDCE Data Circuit EquipmentDCD Data Carrier DetectD channel Control channel of ISDND m channel Control channel of GSM PLMN on the air interfaceDTE Data Terminal EquipmenteMLPP enhanced Multi-Level Precedence and Pre-emptionFIS Functional Interface SpecificationGPRS General Packet Radio Service (a phase 2+ GSM service) GSM-R Global System for Mobile communication/RailwayHDLC High level Data Link ControlISDN Integrated Services Digital NetworkMLPP Multi-Level Precedence and Pre-emption (ISDN service) MOC Mobile Originated CallMS Mobile Station (a GSM entity)Termination/Terminated MT MobileMTC Mobile Terminated CallMTBD Mean Time Between DisturbanceUnitOBU On-BoardPLMN Public Land Mobile NetworkPRI Primary Rate InterfaceQoS Quality of ServicesRBC Radio Block CentreT TI Duration of Transmission Interference periodT REC Duration of Recovery periodUDI Unrestricted Digital4.2 Definitions4.2.1.1 Definitions for the purpose of this specification are inserted in the respective sections.5. G ENERAL5.1 Scope of this document5.1.1.1 The scope of this document is to specify the Radio Communication Systemrequirements to the GSM-R network services (including fixed side access) andinterfaces and also the pre-requisites to be fulfilled by GSM-R networks and ETCSinfrastructures. Presently the requirements for high-speed lines are covered,requirements for conventional lines may be included in future versions of thisdocument.5.1.1.2 The data transmission part of the communication protocols is fully described in theEuroRadio FIS [Subset 037].5.1.1.3 The Radio Transmission FFFIS for EuroRadio [EuroRadio FFFIS] specifies thephysical, electrical and functional details related to the interfaces.5.1.1.4 All requirements apply to GSM-R unless indicated otherwise .5.2 Introduction5.2.1.1 The definition of the GSM services and associated physical and communicationsignalling protocols on the air interface are fully standardised in the specificationsproduced by the ETSI GSM Technical Committee for the public GSM implementationas well as for the GSM-R. Additionally, some railway specific services are alsospecified in the EIRENE SRS. However, in both cases, not all are required for ERTMSclass 1 system definition.5.2.1.2 The following ETSI GSM phases 1/2/2+ services are required:a) Transparent data bearer serviceb) Enhanced multi-level precedence and pre-emption (eMLPP).5.2.1.3 Other ETSI GSM phases 1/2/2+ services are not required for Class 1. These are thefollowing :a) GSM supplementary services:• Call forwardingb) General packet radio service (GPRS)5.2.1.4 Other ETSI GSM phases 1/2/2+ services are not required. Examples of these are thefollowing :a) Non-transparent data bearer serviceb) GSM supplementary services:• Line identification•Call waiting and hold• Multiparty•Closed User Group•Advice of charge• Call Barringc) Short message service point to point or cell broadcastd) Voice broadcast servicee) Voice group call service5.2.1.5 The following EIRENE railway specific service [EIRENE SRS] is required:a) Location dependent addressing5.2.1.6 The following EIRENE specific services [EIRENE SRS] are not required :a) Functional addressingb) Enhanced location dependent addressingc) Calling and connected line presentation of functional identitiesd) Emergency callse) Shunting modef) Multiple driver communications6. E ND-TO-END SERVICE REQUIREMENTS TO GSM-RNETWORKS6.1 Data bearer service requirements6.1.1.1 For the transmission of information between OBU and RBC, the EuroRadio protocoluses the bearer services of a GSM-R network. The service provider makes these databearer services available at defined interfaces.6.1.1.2 The data bearer services are described as data access and transfer in the GSMnetwork from Terminal Equipment (TE) on the mobile side (i.e. OBU) to a networkgateway interworking with Public Switched Telephonic Network (PSTN) or IntegratedServices Digital Network (ISDN) on the fixed side (i.e. RBC).6.1.1.3 The following features and attributes of the required bearer service shall be provided:a) Data transfer in circuit switched modeb) Data transfer allowing multiple rate data streams which are rate-adapted[GSM04.21] and [ITU-T V.110]c) Unrestricted Digital Information (UDI) – only supported through ISDN interworking(no analogue modem in the transmission path)d) Radio channel in full ratee) Transfer of data only (no alternate speech/data)f) Transfer in asynchronous transparent modeg) The required data rates are listed in the following table:Bearer service Requirement24. Asynchronous 2.4 kbps T O25. Asynchronous 4.8 kbps T M26. Asynchronous 9.6 kbps T MT: Transparent; M: Mandatory; O: OptionalTable1 GSM-R bearer servicesservices6.2 Additional6.2.1.1 The following supplementary services shall be provided:a) Enhanced multi-level precedence and pre-emption.b) The selection of a particular mobile network shall be possible on-demand.6.2.1.2 The priority value for command control (safety) shall be assigned to according to[EIRENE FRS §10.2] and [EIRENE SRS §10.2].6.2.1.3 The following railway specific service shall be provided by GSM-R networks:a) Location dependent addressing based on the use of short dialling codes inconjunction with cell dependent routing.6.3 Quality of Service requirements6.3.1 General6.3.1.1 As an end-to-end bearer service is used, a restriction of requirements on the servicequality placed on the air interface is not sufficient.6.3.1.2 End-to-end quality of service has to be considered at the service access points.6.3.1.3 The service access points are:•the service access points to the signalling stack for the establishment or release of a physical connection,•the service access points to the data channel.6.3.1.4 The network shall be able to support transparent train-to-trackside and trackside-to-train data communications at speeds up to 500 km/h e.g. in tunnels, cuttings, onelevated structures, at gradients, on bridges and stations.6.3.1.5 The network shall provide a Quality of Service for ETCS data transfer that is at least asgood as listed below1. The parameters are valid for one end-to-end connection for onetrain running under all operational conditions.6.3.1.6 The required QoS parameters shall not depend on network load.6.3.1.7 These performance figures reflect railway operational targets [EEIG 04E117].6.3.1.8 Note: A justification of the performance figures is given by Annex B.6.3.1.9 QoS requirements are specified independently of the method of measurement (refer to[O-2475] for specification of testing).6.3.1.10 Conventional line quality of service requirements may be included in future versions ofthis document. Also the values may not be applied at all locations and times (e.g.discontinuous radio coverage at some locations).6.3.1.11 Given the performance constraints of GSM-R, pre-conditions may be necessary tomeet the railway operational targets of [EEIG 04E117]. If different operational QoStargets are required, then other pre-conditions on ETCS application may be necessary.1 Early experience suggests that GSM-R performance can be better than these parameters suggest, after network optimisation and tuning.Such a case is not covered by this specification and this aspect of ETCS SystemPerformance becomes the responsibility of whoever specifies different operationaltargets.6.3.2 Connection establishment delay6.3.2.1 Connection establishment delay is defined as:Value of elapsed time between the connection establishment request and theindication of successful connection establishment.6.3.2.2 In case of mobile originated calls, the delay is defined between the request bycommand ATD and indication by the later of the two events response CONNECT ortransition of DCD to ON.6.3.2.3 The connection establishment delay of mobile originated calls shall be <8.5s (95%),≤10s (100%).6.3.2.4 Delays>10s shall be evaluated as connection establishment errors.6.3.2.5 The required connection establishment delay shall not depend on user data rate of theasynchronous bearer service.6.3.2.6 The required connection establishment delay is not valid for location dependentaddressing.6.3.3 Connection establishment error ratio6.3.3.1 The Connection establishment error ratio is defined as:Ratio of the number of unsuccessful connection establishment attempts to the totalnumber of connection establishment attempts.6.3.3.2 “Unsuccessful connection establishment attempt” covers all possible types ofconnection establishment errors caused by end-to-end bearer service.6.3.3.3 Connection establishment delays >10s shall be evaluated as connection establishmenterrors.6.3.3.4 The GSM-R networks should be designed in such a way, that at least two consecutiveconnection establishment attempts will be possible (pre-condition on GSM-Rnetworks), e.g. regarding GSM-R radio coverage related to maximal possible trainspeed.6.3.3.5 If the operational QoS targets of [EEIG 04E117] are wanted, then the ETCSinfrastructure should be designed in such a way, that at least two consecutiveconnection establishment attempts will be possible (Recommended pre-condition forETCS infrastructure).6.3.3.6 The connection establishment error ratio of mobile originated calls shall be <10-2 foreach attempt .6.3.3.7 Note: entry into Level 2 is of particular importance; commonly, a time of 40s may berequired in the case the GSM-R mobile station is already registered with the GSM-Rnetwork (see [ERQoS]).6.3.4 Transfer delay6.3.4.1 The end-to-end transfer delay of a user data block is defined as:Value of elapsed time between the request for transfer of a user data block and theindication of successfully transferred end-to-end user data block6.3.4.2 The delay is defined between the delivery of the first bit of the user data block at theservice access point of transmitting side and the receiving of the last bit of the sameuser data block at the service access point of the receiving side.6.3.4.3 The end-to-end transfer delay of a user data block of 30 bytes shall be ≤0.5s (99%).6.3.5 Connection loss rate6.3.5.1 The Connection loss rate is defined as:Number of connections released unintentionally per accumulated connection time.6.3.5.2 The requirements for connection loss rate varies depending on ETCS system variablessuch as T_NVCONTACT and the possible train reactions after connection loss (seesection 10.5).6.3.5.3 If the operational QoS-targets of [EEIG 04E117] are wanted, then the ETCSinfrastructure should be designed in such a way, that at least the following conditionsare fulfilled (Recommended pre-condition for ETCS infrastructure):• T_NVCONTACT ≥ 41s and• M_NVCONTACT different to train trip and• a new MA reach the OBU before standstill.6.3.5.4 If the connection establishment error ratio is <10-2, then the connection loss rate shallbe <10-2/h.6.3.6 Transmission interference6.3.6.1 A transmission interference period T TI is the period during the data transmission phaseof an existing connection in which, caused by the bearer service, no error-freetransmission of user data units of 30 bytes is possible.6.3.6.2 A transmission interference happens, if the received data units of 30 bytes deviatepartially or completely from the associated transmitted data units.6.3.6.3 The transmission interference period shall be < 0.8s (95%), <1s (99%).6.3.6.4 An error-free period T Rec shall follow every transmission interference period to re-transmit user data units in error (e.g. wrong or lost) and user data units waiting to beserved.6.3.6.5 The error-free period shall be >20s (95%), >7s(99%).6.3.7 GSM-R network registration delay6.3.7.1 The GSM-R network registration delay is defined as:Value of elapsed time from the request for registration to indication of successfulregistration by +CREG response.6.3.7.2 The GSM-R network registration delay shall be ≤30s (95%), ≤35s (99%).6.3.7.3 GSM-R network registration delays > 40 s are evaluated as registration errors.6.4 Summary of QoS requirements6.4.1.1 Table 2 contains the summary of QoS requirements at GSM-R interface.QoS Parameter Value (see 6.3) Connection establishment delay of mobile< 8.5s (95%), ≤10s (100%) originated callsConnection establishment error ratio <10-2≤ 0.5s (99%)Maximum end-to-end transfer delay (of 30 bytedata block)Connection loss rate ≤ 10-2 /hTransmission interference period < 0.8s (95%), <1s (99%)Error-free period >20s (95%), >7s(99%)Network registration delay ≤30s (95%), ≤35s (99%), ≤40s (100%)Table 2 Summary of QoS requirements7. R EQUIREMENTS TO FIXED NETWORK INTERFACE7.1 Foreword7.1.1.1 This part of the specification does not define mandatory requirements forinteroperability. It is a preferred solution, in case interchangeability between tracksideRBC and access point to the fixed network is required for a given implementation.7.1.1.2 This section gives only limited information. [EuroRadio FFFIS] must be used for fullcompliance.7.1.1.3 Note: The requirements to fixed network interface refer to a set of ETSI specifications[ETS 300011, ETS 300125, ETS 300102-1]. This set is the basis of conformancerequirements for network terminations. Instead of these specifications updatedspecifications can be referred, if they state that they are compatible with the followingrequirements.7.2 Interfacedefinition7.2.1.1 The ISDN Primary Rate Interface (PRI) shall be provided as specified by [ETS300011].7.2.1.2 The service access point on the fixed network side corresponds with the S2M interfaceat the T-reference point.7.2.1.3 The Basic Rate interface might also be used as an option in some particular cases likeradio infill unit.7.2.1.4 In addition to these interfaces, the V.110 rate adaptation scheme shall be applied tothe user data channel. The RA2, RA1 and RA0 steps are mandatory.7.2.1.5 End-to-end flow control in layer 1 shall not be used.7.3 Communication signalling procedures7.3.1.1 The signalling protocols shall be provided as specified by:a) Link Access Procedure on the D channel [ETS 300125]b) User-network interface layer 3 using Digital Subscriber Signalling [ETS 300102-1]7.3.1.2 ISDN multi-level precedence and pre-emption (MLPP) supplementary service shall beprovided according to the EIRENE specification [EIRENE SRS].7.3.1.3 The SETUP message contains Information Elements including the bearer capabilityand the low layer compatibility (refer to [EuroRadio FFFIS] specifying the Euroradiodata bearer service requirements.8. R EQUIREMENTS TO MOBILE NETWORK INTERFACE8.1 Foreword8.1.1.1 This part of the specification does not define mandatory requirements forinteroperability. It is a preferred solution, in case interchangeability between OBU andMobile Terminal is required for a given implementation.8.1.1.2 This section gives only limited information. [EuroRadio FFFIS] must be used for fullcompliance.definition8.2 Interface8.2.1.1 If an MT2 interface is used at the mobile side, the service access point at the mobilestation corresponds with the R-reference point of the MT2.8.2.1.2 [GSM 07.07] specifies a profile of AT commands and recommends that this profile beused for controlling Mobile Equipment functions and GSM network services through aTerminal Adapter.8.2.1.3 For the mobile termination type MT2 the signalling over the V interface has to be inaccordance with [GSM 07.07], using the V.25ter command set.8.2.1.4 The online command state shall not be used to guarantee interoperability. To avoiddifferent behaviour, it is recommended to enable/disable this escape sequence usingthe appropriate AT command usually referred as ATS2=<manufacturer defined value>.This particular command shall be sent to the mobile terminal as part of its initialisationstring.8.2.1.5 State control using physical circuits is mandatory.8.2.1.6 The V-interface shall conform to recommendation ITU-T V.24. The signals required arespecified in [EuroRadio FFFIS].8.2.1.7 Note that in the case of class 1 mobile originated calls, it is allowed to set the priorityvalue “command control (safety)” at subscription time.8.2.1.8 The call control commands, interface control commands and responses used on the V-interface at the R reference point are specified in [EuroRadio FFFIS].9. A NNEX A(I NFORMATIVE) TRANSMISSION INTERFERENCEAND RECOVERY9.1 General9.1.1.1 The usual QoS parameter used as measure of accuracy of data transmission viatransparent B/B m channels is the bit error rate.9.1.1.2 The QoS parameter relevant for layer 2 accuracy is the HDLC frame error rate.9.1.1.3 It is not possible to define relationships between both rates. The channel behaviour isnot known: error bursts and interruptions of data transmission during radio cellhandover can happen.9.1.1.4 Additionally, statistical distributions of values such as error rates do not accurately mapthe requirements from the ETCS point of view. Transfer of user data is requested inbursts; the transfer delay can be critical for the application. It has to be guaranteed forsome application messages that data can be transferred to the train in a defined timeinterval.9.1.1.5 A model of service behaviour is necessary reflecting all relevant features of GSM-Rnetworks.9.1.1.6 This model can be used as a normative reference for acceptance tests and for networkmaintenance during ETCS operation. It enables the ETCS supplier to demonstrate thecorrect operation of ETCS constituents during conformance testing without thevariations of real world GSM-R networks.9.1.1.7 Transmission interference and recovery is a first approximation of such a servicebehaviour model.9.2 Transmission interference in relation to HDLC9.2.1.1 Transmission interference is characterised by a period in the received data streamduring which the received data units deviate partially or completely from those of thetransmitted data stream. The service user cannot see the causes of transmissioninterference.9.2.1.2 The user data units erroneously transmitted or omitted during the transmissioninterference must be corrected by re-transmission. These re-transmissions result in atime delay and in higher load in the B/B m channel. Therefore, after transmissioninterference a period of error-free transmission, called the recovery period, must follow.9.2.1.3 In the normal data transfer phase after recovery, user data units are transmitted toprovide the data throughput requested by application messages.9.2.1.4 Figure 1 shows a simplified relationship of B/B m channel and HDLC errors: because ofthe selected options for the HDLC protocol (e.g. multi selective reject) the recoveryperiod and the normal data transfer phase are not strictly separated.error-free frameHDLC statecorrupted frameerror-freeChannel stateerroneousFigure 1 B/B m channel and HDLC errors9.2.1.5 Some special cases exist in Figure 1:A Beginning of HDLC frame (corrupted by transmission) is earlier than beginning oftransmission interferenceB Error-free time is not sufficient for transfer of HDLC frameC No HDLC frame is ready for transferD End of corrupted HDLC frame is later than end of transmission interference9.2.1.6 Figure 2 shows as an example the HDLC behaviour in case of transmissioninterference.Figure 2 Event "Transmission interference"9.2.1.7 The sender does not receive an acknowledgement in the case of a corrupted last Iframe of a sequence of I frames. The timer T1 expires and a RR (poll bit set) frame willbe sent.9.2.1.8 After receiving an RR frame with an indication of successful transmission of thepreceding I frame, the lost I frame will be re-transmitted.9.2.1.9 Again the sender does not receive an acknowledgement and requests for thesequence number. Eventually, the transmission is successful but the delivery of userdata will be delayed towards the receiver.9.2.1.10 The occurrence of the above defined event represents a QoS event “Transmissioninterference” at the sender side. The beginning and the end of the transmissioninterference are not exactly known. But the second repetition clearly indicates an event“Transmission interference”:a) The transmission interference time was too long orb) The recovery time was too short.。
ARTISAN TECHNOLOGY GROUP 商业说明书
OverviewThe National Instruments Educational Laboratory Virtual Instrumentation Suite (NI ELVIS) is a LabVIEW-based design and prototyping environment or university science and engineering laboratories.NI ELVIS consists o f LabVIEW-based virtual instruments,a multifunction data acquisition device and a custom-designed benchtop workstation and prototyping board.This combination provides a ready-to-use suite of instruments found in all educational laboratories.Because it is based on LabVIEW and provides complete data acquisition and prototyping capabilities,the system is ideal for academic coursework from lower-division classes to advanced project-based curriculum.Applications•Circuit design and analysis for learning analog and digital electronics•Measurements in mechanical,electrical,biomedical, and physics laboratories•Teaching data acquisition and signal conditioning •Live demonstration of concepts in a lecture hall •Communications and control applications for Electrical and Mechanical Engineering•Hands-on LabVIEW trainingIntegrated Tools for University Laboratories•Offers integrated,multi-instrument functionality •Combines instrumentation,data acquisition and prototyping station •Virtual Instrument Suite •Oscilloscope,DMM,FunctionGenerator,Variable PowerSupply,Bode Analyzer,ArbitraryWaveform Generator,DSA,Voltage/Current Analyzer •LabVIEW source code provided •Completely open and customizable in the LabVIEW environment •Data storage in Excel or HTML Workstation•Short-circuit andhigh-voltage protection •Variable power supplies •Manual or programmatic control •Function generator•Manual or programmatic control •±15 and +5 V supply available •BNC inputs for DMM and scope •Detachable,customizable prototyping board•Affordable for student ownership •Designed to fit in a2 or 3-ring binderNI Educational Laboratory Virtual Instrumentation Suite (NI ELVIS)LabVIEW VIs• Oscilloscope• DMM• Function Generator • Arbitrary WaveformGenerator• Bode Analyzer• Dynamic Signal Analyzer • Power SupplyInstrumentationCircuit DesignSignal ProcessingCommunicationControlsMechatronics Prototyping Board WorkstationLabVIEW ApplicationNI Data Acquisition BoardCurriculum ApplicationsNI Educational Laboratory Virtual Instrumentation Suite (NI ELVIS)AnalyzersOscilloscopeTwo channelsData storage, cursors, auto scalingMax input bandwidth.......................................50 kHz 1Max sampling rate...........................................500 kHz / channel 1Range................................................................±10 VInput resolution................................................12 or 16 bits1Specification depends on Data Acquisition device functionality.Bode AnalyzerFrequency and phase plotsFrequency range and step controlLogarithmic or linear frequency spacing Data storage, cursors, auto scalingFrequency range............................................... 5 Hz to 35 kHz 11Specification depends on Data Acquisition device functionality.Dynamic Signal AnalyzerInput range.......................................................±10 VInput resolution................................................12 or 16 bitsImpedance AnalyzerMeasurement frequency range........................ 5 Hz to 35 kHz2-Wire Current Voltage AnalyzerVoltage range...................................................±10 V Current range...................................................±10 mA3-Wire Current Voltage AnalyzerNPN BJT transistor onlyData storage, cursors, auto scalingMaximum Collector Voltage.............................10 V Minimum base increment................................15 µADigital MultimeterResistanceAccuracy...........................................................1%Range................................................................ 5 Ωto 3 M ΩDC VoltageAccuracy...........................................................0.3%Range................................................................±20 V Input impedance...............................................1M ΩAC VoltageAccuracy...........................................................0.3%Range................................................................±14 V mrsCurrentDC accuracy......................................................0.25% ±3 mA 1AC accuracy......................................................0.25% ±3 mA 1Range................................................................±250 mA Shunt resistance..............................................0.5 ΩMaximum common mode voltage....................±20 V Common mode rejection..................................70 dB1Proper null correction at the common mode voltage can reduce ±3 mA error to 200 µA noise.CapacitanceAccuracy...........................................................2%Range................................................................50 pF to 500 µF Test voltage range............................................1V ppContinuityResistance threshold........................................15 ΩmaxInductanceAccuracy...........................................................1%Range................................................................100 µH to 100 mH Test frequency..................................................950 Hz Test frequency voltage.....................................1 V ppDigital I/ODigital input resolution....................................8 bits Digital output resolution..................................8 bits Digital addressing............................................ 4 bitsSourceFunction GeneratorManual or software controlSine, triangle, square waveforms Frequency sweep TTL sync pulse out AM, FM modulationFrequency range............................................... 5 Hz to 250 kHz Frequency accuracy..........................................3%Output amplitude.............................................±2.5 V Software amplitude resolution........................8 bits Offset range.....................................................±5 V AM voltage.......................................................10 V max Amplitude modulation......................................Up to 100%FM Voltage.......................................................10 V max Amplitude flatnessTo 50 kHz...................................................0.5 dB To 250 kHz.................................................3 dBArbitrary Waveform GeneratorTwo channelsOne-shot or continuous generation Waveform editorAmplitude.........................................................±10 VFrequency range...............................................DC to 100 kHz 1Output drive current.........................................25 mA max Output impedance.. (1)Slew rate..........................................................1.5 V/µs1Specification depends on Data Acquisition device functionality.Power Supplies±15 V SupplyOutput current...........................................Fused at 500 mA Ripple and noise........................................1%Line regulation...........................................0.5% max 5 V SupplyOutput current...........................................Fused at 2 A Ripple and noise........................................1%Line regulation...........................................0.5% maxVariable power supplies 0 to +12 V and -12 VRipple and noise........................................0.25% Software resolution...................................7 bitsCurrent limiting..........................................0.5 V at 130 mA, 5 V at 275 mA, 12 V at 450 mASpecificationsIntegrated Tools for University Laboratories2National Instruments •Tel: (800) 433-3488•***********•For Desktop ComputersNI ELVIS/PCI-6251 Bundle ........................................778748-02Qty 1-4:$1995 each Qty 5+:$1495 each For Laptop ComputersNI ELVIS/DAQCard-6062E Bundle ............................779064-01Qty 1-4:$2260 each Qty 5+:$1695 eachIncludes NI ELVIS workstation,DAQ device,cable,and LabVIEW drivers.For individual unit pricing please visit /academic .BUY NOW!For complete product specifications,pricing,and accessoryinformation,call (800) 813-3693 (U.S.only) or go to /academic .Ordering InformationNI Services and Supportapplication lif e cycle – f rom planningand development through deploymentand ongoing maintenance.We of erservices and service levels to meetcustomer requirements in research,design,validation,and manuVisit /services.Training and CertificationNI training is the fastest,most certain route to productivity with our products.NI training can shorten your learning curve,save development time,and reduce maintenance costs over the application lif e cycle.We schedule instructor-led courses in cities worldwide,or we can hold a course at your facility.We also offer a prof essional certif ication program that identif ies individuals who have high levels of skill and knowledge on using NI products. Visit /training.Professional ServicesOur Prof essional Services Team is comprised of NI applications engineers,NI Consulting Services,and a worldwide NI Alliance Partner Program of more than 600 independent consultants andintegrators.Services rangerom start-up assistance toturnkey system integration.Visit /alliance.OEM SupportWe of er design-in consulting and product integration assistance if you want to use our products or OEM applications.For information about special pricing and services for OEM customers, visit /oem.Local Sales and Technical SupportIn of f ices worldwide,our staf f is local to the country,giving you access to engineers who speak your language.NI delivers industry-leading technical support through online knowledge bases,our applications engineers,and access to 14,000 measurement andautomation prof essionals within NI Developer Exchange f orums.Find immediate answers to your questions at /support.We also offer service programs that provide automatic upgrades toyour application development environment and higher levels oftechnical support.Visit /ssp.Hardware ServicesNI Factory Installation ServicesNI Factory Installation Services (FIS) is the fastest and easiest way touse your PXI or PXI/SCXI combination systems right out of the box.Trained NI technicians install the so tware and hardware andconfigure the system to your specifications.NI extends the standardwarranty by one year on hardware components (controllers,chassis,modules) purchased with FIS.To use FIS,simply conf igure yoursystem online with /pxiadvisor.Calibration ServicesNI recognizes the need to maintain properly calibrated devices forhigh-accuracy measurements.We provide manual calibrationprocedures,services to recalibrate your products,and automatedcalibration so tware speci ically designed or use by metrologylaboratories.Visit /calibration.Repair and Extended WarrantyNI provides complete repair services for our products.Express repairand advance replacement services are also available.We o erextended warranties to help you meet project life-cycle requirements.Visit /services.© 2005 National Instruments Corporation. All rights reserved. LabVIEW, National Instruments Alliance Partner, NI, , and SCXI aretrademarks of National Instruments. Other product and company names listed are trademarks or trade names of their respective companies.A National Instruments Alliance Partner is a business entity independent from NI and has no agency, partnership, or joint-venture relationship with NI.National Instruments • Tel: (512) 683-0100 • ***********• (800) 433-348825_4929_35_11_D。
NORMA 4000 5000 Power Analyzer 用户说明手册说明书
Since some countries or states do not allow limitation of the term of an implied warranty, or exclusion or limitation of incidental or consequential damages, the limitations and exclusions of this warranty may not apply to every buyer. If any provision of this Warranty is held invalid or unenforceable by a court or other decision-maker of competent jurisdiction, such holding will not affect the validity or enforceability of any other provision.
BEGRENZTE GEWÄHRLEISTUNG UND HAFTUNGSBESCHRÄNKUNG
Fluke gewährleistet, daß jedes Fluke-Produkt unter normalem Gebrauch und Service frei von Material- und Fertigungsdefekten ist. Die Garantiedauer beträgt 2 Jahre ab Versanddatum. Die Garantiedauer für Teile, Produktreparaturen und Service beträgt 90 Tage. Diese Garantie wird ausschließlich dem Erster
纹理物体缺陷的视觉检测算法研究--优秀毕业论文
摘 要
在竞争激烈的工业自动化生产过程中,机器视觉对产品质量的把关起着举足 轻重的作用,机器视觉在缺陷检测技术方面的应用也逐渐普遍起来。与常规的检 测技术相比,自动化的视觉检测系统更加经济、快捷、高效与 安全。纹理物体在 工业生产中广泛存在,像用于半导体装配和封装底板和发光二极管,现代 化电子 系统中的印制电路板,以及纺织行业中的布匹和织物等都可认为是含有纹理特征 的物体。本论文主要致力于纹理物体的缺陷检测技术研究,为纹理物体的自动化 检测提供高效而可靠的检测算法。 纹理是描述图像内容的重要特征,纹理分析也已经被成功的应用与纹理分割 和纹理分类当中。本研究提出了一种基于纹理分析技术和参考比较方式的缺陷检 测算法。这种算法能容忍物体变形引起的图像配准误差,对纹理的影响也具有鲁 棒性。本算法旨在为检测出的缺陷区域提供丰富而重要的物理意义,如缺陷区域 的大小、形状、亮度对比度及空间分布等。同时,在参考图像可行的情况下,本 算法可用于同质纹理物体和非同质纹理物体的检测,对非纹理物体 的检测也可取 得不错的效果。 在整个检测过程中,我们采用了可调控金字塔的纹理分析和重构技术。与传 统的小波纹理分析技术不同,我们在小波域中加入处理物体变形和纹理影响的容 忍度控制算法,来实现容忍物体变形和对纹理影响鲁棒的目的。最后可调控金字 塔的重构保证了缺陷区域物理意义恢复的准确性。实验阶段,我们检测了一系列 具有实际应用价值的图像。实验结果表明 本文提出的纹理物体缺陷检测算法具有 高效性和易于实现性。 关键字: 缺陷检测;纹理;物体变形;可调控金字塔;重构
Keywords: defect detection, texture, object distortion, steerable pyramid, reconstruction
II
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JOURNAL OF ENVIRONMENTAL MANAGEMENT投稿说明
JOURNAL OF ENVIRONMENTAL MANAGEMENTAUTHOR INFORMATION PACK TABLE OF CONTENTS• Description• Impact Factor• Abstracting and Indexing • Editorial Board• Guide for Authors p.1p.1p.2p.2p.3ISSN: 0301-4797DESCRIPTIONThe Journal of Environmental Management is a journal for the publication of peer reviewed, original research for all aspects of management and the managed use of the environment, both natural and man-made. Critical review articles are also welcome; submission of these is strongly encouraged. As governments and the general public become more keenly aware of the critical issues arising from how humans use their environment, this journal provides a forum for the discussion of environmental problems around the world and for the presentation of management results. It is aimed not only at the environmental manager, but at anyone concerned with the sustainable use of environmental resources.Research Areas Include, but are not exclusive to:• Resource quality, quantity and sustainability• Economics of environmental management• Transport and fate of pollutants in the environment• Spill prevention and management• Remediation of contaminated sites• Process modification for pollution prevention• Improved energy efficiency• Waste treatment and disposalPapers submitted should address environmental management issues using a range of techniques e.g. case studies, observational and theoretical analyses, the application of science, engineering and technology to questions of environmental concern or mathematical and computer modeling techniques with the aim of informing both the researcher and practitioner.IMPACT FACTOR2014: 2.723 © Thomson Reuters Journal Citation Reports 2015ABSTRACTING AND INDEXINGAGRICOLAAgriculture, Biological and Environmental SciencesEMBASEGEOBASEPascalPeriodical Abstracts PlusTextScience Citation IndexBiological AbstractsCAB AbstractsBIOSIS PreviewsScopusScience Citation Index ExpandedEnvironmental SciencesEDITORIAL BOARDCo-Editor-in-ChiefR. Dewil, KU Leuven, Heverlee, BelgiumJ.M. Evans, Stetson University, DeLand, Florida, USAB. Tansel, Florida International University, Miami, Florida, USAAssociate Editors:J.C. Bollinger, Université de LimogesW.J. de Lange, Council for Scientific and Industrial Research (CSIR), Stellenbosch, South Africa P. Gikas, Technical University of Crete, Chania - Crete, GreeceP. Hooda, Kingston University, Kingston upon Thames, England, UKJ.L. Innes, University of British Columbia, Vancouver, British Columbia, CanadaC. Lin, University of Salford, Manchester, UKS.K. Ouki, University of Surrey, Guildford, England, UKR. Saravanane, Pondicherry Engineering College, Puducherry, IndiaKrishna Prasad Vadrevu, University of Maryland, College Park, USAEditorial Board:C. Allan, University of North Carolina School of Medicine, Charlotte, North Carolina, USAN-B. Chang, University of Central Florida, Orlando, Florida, USAB. Chen, Beijing Normal University, Beijing, ChinaL.G. Firbank, Institute of Grasslands and Environmental Research, Okehampton, UKA. Gilbert, IVM/VU, Amsterdam, NetherlandsG. Huang, University of Regina, Regina, Saskatchewan, CanadaJ. Marion, United States Geological Survey (USGS), Blacksburg, Virginia, USAR.K. Morgan, University of Otago, Dunedin, New ZealandR.A. Preston-Whyte, School of Psychology, Durban, South AfricaJ.P. Richards, Plymouth University, Plymouth, UKM. Ruth, Northeastern University, Boston, Massachusetts, USAH. Saarenmaa, University of Helsinki, Helsinki, FinlandD. Schaad, Duke University, Durham, North Carolina, USAGUIDE FOR AUTHORSYour Paper Your WayWe now differentiate between the requirements for new and revised submissions. You may choose to submit your manuscript as a single Word or PDF file to be used in the refereeing process. Only when your paper is at the revision stage, will you be requested to put your paper in to a 'correct format' for acceptance and provide the items required for the publication of your article.To find out more, please visit the Preparation section below.INTRODUCTIONAims and Scope:The Journal of Environmental Management is a journal for the publication of peer reviewed, original research for all aspects of management and the managed use of the environment, both natural and man-made. Critical review articles are also welcome; submission of these is strongly encouraged. As governments and the general public become more keenly aware of the critical issues arising from man's use of his environment, this journal provides a forum for the discussion of environmental problems around the world and for the presentation of management results. It is aimed not only at the environmental manager, but at anyone concerned with the sustainable use of environmental resources.Research Areas Include, but are not exclusive to: •resource quality, quantity and sustainability •economics of environmental management•transport and fate of pollutants in the environment•spill prevention and management•remediation of contaminated sites•process modification for pollution prevention•improved energy efficiency•waste treatment and disposalPapers submitted should address environmental management issues using a range of techniques e.g. case studies, observational and theoretical analyses, the application of science, engineering and technology to questions of environmental concern or mathematical and computer modeling techniques with the aim of informing both the researcher and practitioner.Contact details for submissionSpecial Issues: If you are submitting a manuscript for publication in a special issue, please contact the Editor or Guest Editor for submission instructions. Please do not submit it through the online EES unless you are specifically instructed to do so.BEFORE YOU BEGINEthics in publishingFor information on Ethics in publishing and Ethical guidelines for journal publication see https:///publishingethics and https:///journal-authors/ethics. Conflict of interestAll authors are requested to disclose any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations within three years of beginning the submitted work that could inappropriately influence, or be perceived to influence, their work. See also https:///conflictsofinterest. 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To verify originality, your article may be checked by the originality detection service CrossCheck https:///editors/plagdetect.Changes to authorshipAuthors are expected to consider carefully the list and order of authors before submitting their manuscript and provide the definitive list of authors at the time of the original submission. Any addition, deletion or rearrangement of author names in the authorship list should be made only before the manuscript has been accepted and only if approved by the journal Editor. To request such a change, the Editor must receive the following from the corresponding author: (a) the reason for the change in author list and (b) written confirmation (e-mail, letter) from all authors that they agree with the addition, removal or rearrangement. 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TD信息元素详解
信息元素功能性定义作者:李欣目录目录 (1)信息元素功能性定义 (11)1 核心网信息元素 (11)1.1 CN Information elements (11)1.2 CN Domain System Information (11)1.3 CN Information info (11)1.4 IMEI (11)1.5 IMSI (GSM-MAP) (11)1.6 Intra Domain NAS Node Selector (11)1.7 Location Area Identification (12)1.8 NAS message (12)1.9 NAS system information (GSM-MAP) (12)1.10 Paging record type identifier (12)1.11 PLMN identity (12)1.12 PLMN Type (12)1.13 P-TMSI (GSM-MAP) (12)1.14 RAB identity (12)1.15 Routing Area Code (12)1.16 Routing Area Identification (13)1.17 TMSI (GSM-MAP) (13)2 UTRAN 移动信息元素 (13)2.1 Cell Access Restriction (13)2.2 Cell identity (13)2.3 Cell selection and re-selection info for SIB3/4 (13)2.4 Cell selection and re-selection info for SIB11/12 (13)2.5 Mapping Info (14)2.6 URA identity (14)3 UE 信息元素 (14)3.1 Activation time (14)3.2 Capability Update Requirement (14)3.3 Cell update cause (15)3.4 Ciphering Algorithm (15)3.5 Ciphering mode info (15)3.6 CN domain specific DRX cycle length coefficient (15)3.7 CPCH Parameters (15)3.8 C-RNTI (15)3.9 DRAC system information (15)3.10 Void (16)3.11 Establishment cause (16)3.12 Expiration Time Factor (16)3.13 Failure cause (16)3.14 Failure cause and error information (16)3.15 Initial UE identity (16)3.16 Integrity check info (16)3.17 Integrity protection activation info (17)3.18 Integrity protection Algorithm (17)3.19 Integrity protection mode info (17)3.20 Maximum bit rate (17)3.21 Measurement capability (17)3.22 Paging cause (17)3.23 Paging record (17)3.24 PDCP capability (17)3.25 Physical channel capability (18)3.26 Protocol error cause (18)3.27 Protocol error indicator (18)3.28 RB timer indicator (18)3.29 Redirection info (18)3.30 Re-establishment timer (18)3.31 Rejection cause (18)3.32 Release cause (18)3.33 RF capability FDD (19)3.34 RLC capability (19)3.35 RLC re-establish indicator (19)3.36 RRC transaction identifier (19)3.37 Security capability (19)3.38 START (19)3.39 Transmission probability (19)3.40 Transport channel capability (20)3.41 UE multi-mode/multi-RAT capability (20)3.42 UE radio access capability (20)3.43 UE Timers and Constants in connected mode (21)3.44 UE Timers and Constants in idle mode (21)3.45 UE positioning capability (21)3.46 URA update cause (21)3.47 U-RNTI (21)3.48 U-RNTI Short (21)3.49 UTRAN DRX cycle length coefficient (21)3.50 Wait time (21)3.51 UE Specific Behavior Information 1 idle (21)3.52 UE Specific Behavior Information 1 interRAT (22)4 无线承载信息元素 (22)4.0 Default configuration identity (22)4.1 Downlink RLC STATUS info (22)4.2 PDCP info (22)4.3 PDCP SN info (22)4.4 Polling info (22)4.5 Predefined configuration identity (23)4.6 Predefined configuration value tag (23)4.7 Predefined RB configuration (23)4.8 RAB info (23)4.9 RAB info Post (23)4.10 RAB information for setup (23)4.11 RAB information to reconfigure (24)4.12 NAS Synchronization indicator (24)4.13 RB activation time info (24)4.14 RB COUNT-C MSB information (24)4.15 RB COUNT-C information (24)4.16 RB identity (24)4.17 RB information to be affected (24)4.18 RB information to reconfigure (25)4.19 RB information to release (25)4.20 RB information to setup (25)4.21 RB mapping info (25)4.22 RB with PDCP information (25)4.23 RLC info (25)4.24 Signaling RB information to setup (26)4.25 Transmission RLC Discard (26)5 传输信道信息元素 (26)5.1 Added or Reconfigured DL TrCH information (26)5.2 Added or Reconfigured UL TrCH information (27)5.3 CPCH set ID (27)5.4 Deleted DL TrCH information (27)5.5 Deleted UL TrCH information (27)5.6 DL Transport channel information common for all transport channels (27)5.7 DRAC Static Information (27)5.8 Power Offset Information (28)5.9 Predefined TrCH configuration (28)5.10 Quality Target (28)5.11 Semi-static Transport Format Information (28)5.12 TFCI Field 2 Information (28)5.13 TFCS Explicit Configuration (28)5.14 TFCS Information for DSCH (TFCI range method) (29)5.15 TFCS Reconfiguration/Addition Information (29)5.16 TFCS Removal Information (29)5.17 Void (29)5.18 Transport channel identity (29)5.19 Transport Format Combination (TFC) (29)5.20 Transport Format Combination Set (29)5.21 Transport Format Combination Set Identity (29)5.22 Transport Format Combination Subset (29)5.23 Transport Format Set (29)5.24 UL Transport channel information common for all transport channels (30)6 物理信道信息元素 (30)6.1 AC-to-ASC mapping (30)6.2 AICH Info (30)6.3 AICH Power offset (30)6.4 Allocation period info (30)6.5 Alpha (30)6.6 ASC Setting (30)6.7 Void (31)6.8 CCTrCH power control info (31)6.9 Cell parameters Id (31)6.10 Common timeslot info (31)6.11 Constant value (31)6.12 CPCH persistence levels (31)6.13 CPCH set info (31)6.14 CPCH Status Indication mode (31)6.15 CSICH Power offset (32)6.16 Default DPCH Offset Value (32)6.17 Downlink channelisation codes (32)6.18 Downlink DPCH info common for all RL (32)6.19 Downlink DPCH info common for all RL Post (32)6.20 Downlink DPCH info common for all RL Pre (32)6.21 Downlink DPCH info for each RL (32)6.22 Downlink DPCH info for each RL Post (33)6.23 Downlink DPCH power control information (33)6.24 Downlink information common for all radio links (33)6.25 Downlink information common for all radio links Post (33)6.26 Downlink information common for all radio links Pre (33)6.27 Downlink information for each radio link (33)6.28 Downlink information for each radio link Post (33)6.29 Void (33)6.30 Downlink PDSCH information (33)6.31 Downlink rate matching restriction information (34)6.32 Downlink Timeslots and Codes (34)6.33 DPCH compressed mode info (34)6.34 DPCH Compressed Mode Status Info (34)6.35 Dynamic persistence level (34)6.36 Frequency info (34)6.37 Individual timeslot info (35)6.38 Individual Timeslot interference (35)6.39 Maximum allowed UL TX power (35)6.40 Void (35)6.41 Midamble shift and burst type (35)6.42 PDSCH Capacity Allocation info (35)6.43 PDSCH code mapping (36)6.44 PDSCH info (36)6.45 PDSCH Power Control info (36)6.46 PDSCH system information (36)6.47 PDSCH with SHO DCH Info (36)6.48 Persistence scaling factors (36)6.49 PICH Info (36)6.50 PICH Power offset (37)6.51 PRACH Channelisation Code List (37)6.52 PRACH info (for RACH) (37)6.53 PRACH partitioning (37)6.54 PRACH power offset (37)6.55 PRACH system information list (37)6.56 Predefined PhyCH configuration (38)6.57 Primary CCPCH info (38)6.58 Primary CCPCH info post (38)6.59 Primary CCPCH TX Power (38)6.60 Primary CPICH info (38)6.61 Primary CPICH Tx power (38)6.62 Primary CPICH usage for channel estimation (38)6.63 PUSCH info (38)6.64 PUSCH Capacity Allocation info (38)6.65 PUSCH power control info (39)6.66 PUSCH system information (39)6.67 RACH transmission parameters (39)6.68 Radio link addition information (39)6.69 Radio link removal information (39)6.70 SCCPCH Information for FACH (39)6.71 Secondary CCPCH info (39)6.72 Secondary CCPCH system information (40)6.73 Secondary CPICH info (40)6.74 Secondary scrambling code (40)6.75 SFN Time info (40)6.76 SSDT cell identity (40)6.77 SSDT information (40)6.78 STTD indicator (40)6.79 TDD open loop power control (41)6.80 TFC Control duration (41)6.81 TFCI Combining Indicator (41)6.82 TGPSI (41)6.83 Time info (41)6.84 Timeslot number (41)6.85 TPC combination index (41)6.86 TSTD indicator (41)6.87 TX Diversity Mode (41)6.88 Uplink DPCH info (41)6.89 Uplink DPCH info Post (42)6.90 Uplink DPCH info Pre (42)6.91 Uplink DPCH power control info (42)6.92 Uplink DPCH power control info Post (42)6.93 Uplink DPCH power control info Pre (42)6.94 Uplink Timeslots and Codes (42)6.95 Uplink Timing Advance (42)6.96 Uplink Timing Advance Control (43)7 测量信息元素 (43)7.1 Additional measurements list (43)7.2 Cell info (43)7.3 Cell measured results (43)7.4 Cell measurement event results (44)7.5 Cell reporting quantities (44)7.6 Cell synchronization information (44)7.7 Event results (44)7.8 FACH measurement occasion info (45)7.9 Filter coefficient (45)7.10 HCS Cell re-selection information (45)7.11 HCS neighboring cell information (45)7.12 HCS Serving cell information (45)7.13 Inter-frequency cell info list (46)7.14 Inter-frequency event identity (46)7.15 Inter-frequency measured results list (46)7.16 Inter-frequency measurement (46)7.17 Inter-frequency measurement event results (47)7.18 Inter-frequency measurement quantity (47)7.19 Inter-frequency measurement reporting criteria (47)7.20 Inter-frequency measurement system information (47)7.21 Inter-frequency reporting quantity (47)7.22 Inter-frequency SET UPDATE (48)7.23 Inter-RAT cell info list (48)7.24 Inter-RAT event identity (48)7.25 Inter-RAT info (48)7.26 Inter-RAT measured results list (48)7.27 Inter-RAT measurement (49)7.28 Inter-RAT measurement event results (49)7.29 Inter-RAT measurement quantity (49)7.30 Inter-RAT measurement reporting criteria (49)7.31 Inter-RAT measurement system information (50)7.32 Inter-RAT reporting quantity (50)7.33 Intra-frequency cell info list (50)7.34 Intra-frequency event identity (50)7.35 Intra-frequency measured results list (50)7.36 Intra-frequency measurement (50)7.37 Intra-frequency measurement event results (51)7.38 Intra-frequency measurement quantity (51)7.39 Intra-frequency measurement reporting criteria (51)7.40 Intra-frequency measurement system information (51)7.41 Intra-frequency reporting quantity (52)7.42 Intra-frequency reporting quantity for RACH reporting (52)7.43 Maximum number of reported cells on RACH (52)7.44 Measured results (52)7.45 Measured results on RACH (52)7.46 Measurement Command (52)7.47 Measurement control system information (53)7.48 Measurement Identity (53)7.49 Measurement reporting mode (53)7.50 Measurement Type (53)7.51 Measurement validity (53)7.52 Observed time difference to GSM cell (53)7.53 Periodical reporting criteria (53)7.54 Primary CCPCH RSCP info (54)7.55 Quality measured results list (54)7.56 Quality measurement (54)7.57 Quality measurement event results (54)7.58 Quality measurement reporting criteria (54)7.59 Quality reporting quantity (54)7.60 Reference time difference to cell (54)7.61 Reporting Cell Status (55)7.62 Reporting information for state CELL_DCH (55)7.63 SFN-SFN observed time difference (55)7.64 Time to trigger (55)7.65 Timeslot ISCP info (55)7.66 Traffic volume event identity (55)7.67 Traffic volume measured results list (55)7.68 Traffic volume measurement (55)7.69 Traffic volume measurement event results (56)7.70 Traffic volume measurement object (56)7.71 Traffic volume measurement quantity (56)7.72 Traffic volume measurement reporting criteria (56)7.73 Traffic volume measurement system information (56)7.74 Traffic volume reporting quantity (56)7.75 UE internal event identity (56)7.76 UE internal measured results (57)7.77 UE internal measurement (57)7.78 UE internal measurement event results (57)7.79 UE internal measurement quantity (57)7.80 UE internal measurement reporting criteria (57)7.81 Void (58)7.82 UE Internal reporting quantity (58)7.83 UE Rx-Tx time difference type 1 (58)7.84 UE Rx-Tx time difference type 2 (58)7.85 UE Transmitted Power info (58)7.86 UE positioning Ciphering info (58)7.87 UE positioning Error (58)7.88 UE positioning GPS acquisition assistance (59)7.89 UE positioning GPS almanac (59)7.90 UE positioning GPS assistance data (59)7.91 UE positioning GPS DGPS corrections (59)7.92 UE positioning GPS ionospheric model (59)7.93 UE positioning GPS measured results (59)7.94 UE positioning GPS navigation model (60)7.95 UE positioning GPS real-time integrity (60)7.96 UE positioning GPS reference time (60)7.97 UE positioning GPS UTC model (61)7.98 UE positioning IPDL parameters (61)7.99 UE positioning measured results (61)7.100 UE positioning measurement (61)7.101 UE positioning measurement event results (61)7.102 Void (62)7.103 UE positioning OTDOA assistance data for UE-assisted (62)7.104 Void (62)7.105 UE positioning OTDOA measured results (62)7.106 UE positioning OTDOA neighbor cell info (62)7.107 UE positioning OTDOA quality (63)7.108 UE positioning OTDOA reference cell info (63)7.109 UE positioning position estimate info (64)7.110 UE positioning reporting criteria (64)7.111 UE positioning reporting quantity (64)7.112 T ADV info (65)8 其它信息元素 (65)8.1 BCCH modification info (65)8.2 BSIC (65)8.3 CBS DRX Level 1 information (65)8.4 Cell Value tag (65)8.5 Inter-RAT change failure (65)8.6 Inter-RAT handover failure (66)8.7 Inter-RAT UE radio access capability (66)8.8 Void (66)8.9 MIB Value tag (66)8.10 PLMN Value tag (66)8.11 Predefined configuration identity and value tag (66)8.12 Protocol error information (66)8.13 References to other system information blocks (66)8.14 References to other system information blocks and scheduling blocks (67)8.15 Rplmn information (67)8.16 Scheduling information (67)8.17 SEG COUNT (67)8.18 Segment index (67)8.19 SIB data fixed (67)8.20 SIB data variable (67)8.21 SIB type (67)8.22 SIB type SIBs only (67)9 ANSI-41 Information elements (68)10 Multiplicity values and type constraint values (68)信息元素功能性定义消息是由多个信息元素组合而成,信息元素根据其功能的不同划分为:核心网域信息元素、UTRAN 移动信息元素、UE 信息元素、无线承载信息元素、传输信道信息元素、物理信道信息元素和测量信息元素。
Digital Object Identifier (DOI) 10.1007s002050100158 An Eulerian Description of Fluids Cont
An Eulerian Description of Fluids Containing Visco-Elastic Particles
230
Chun Liu & Noel J. Walkington
to develop a reasonable existence theory. This approximation corresponds to an appropriate description of visco-hyperelasticity for the solid particles for which the strains but not the rotations are small. This simplified system should provide a good model problem for the analysis and comparison of various numerical algorithms. Elastic materials are typically described in Lagrangian coordinates since the stress depends upon the deformation gradient F from a fixed configuration, and F is not immediately available in an Eulerian description. We circumvented this by writing an evolution equation for F , our equation (5). Our description also utilizes a “phase” variable φ equal to ±1 in the fluid/solid regions. This approach has been used in the past for the simulation of the flow of immiscible fluids [5,16, 17,24, 23], and essentially circumvents the “mapping” problem encountered by the numerical analysts described in the first paragraph. The interaction of Eulerian and Lagrangian descriptions is ubiquitous in the plasticity literature [1, 2]. Classically, numerical computations are based upon a Lagrangian mesh [1], and the large plastic deformations can result in tangled meshes and ill-conditioned systems of equations. The computations in [10] utilize an Eulerian description which contains a free-boundary problem to determine the surface of the solid. Since the problem in [10] was one-dimensional it was relatively easy to track the motion of the free surface through the mesh; however, this would seem a difficult task in multiple dimensions where, for example, topological changes could occur due to contact. This problem of determining the location of the particles (and their surfaces) is circumvented here by exploiting a phase variable to track them. 1.1. Notation We adopt the standard notation of continuum mechanics [13]: X ∈ Rd is the material description; x = χ (X, t) is the position of particle X at time t ; and the velocity is given by v = x ˙ , where the dot indicates the partial derivative with respect to time with X fixed (the material or convective derivative). In the Eulerian description (x, t) the chain rule gives g ˙ = gt + v.∇ g where ∇ is the gradient in the x variables. Classical mechanics assumes that χ : Rd → Rd is a diffeomorphism and the deformation gradient F = [∂xi /∂Xα ] is the Jacobian of this mapping and has J = det (F ) > 0. Below we will consider incompressible materials for which J = 1. If the elastic part of the stress of a solid particle depends only upon the deformation gradient F , it must take the form (1/J )DW (F )F T where W : Rd ×d → R is the strain-energy function and (DW )iα = ∂ W /∂Fiα is the Piola Kirchhoff stress tensor. The strain-energy function must satisfy W (RU ) = W (U ) for all proper orthogonal matrices (i.e., RR T = I , det (R) > 0) and hence DW (RU ) = R DW (U ). If F = RU with U = U T represents the polar decomposition of the deformation gradient, it follows that the stress becomes (1/J )R DW (U )U R T . When the Piola Kirchhoff stress tensor is the gradient of a strain-energy function, as above, the material is called hyperelastic. Classical linear elasticity assumes that the displacement u = x − X is small so that F = I + H , where H = ∇X u is small. In this situation the polar decomposition is, to first order, F (I + Hskew )(I + Hsym ) where Hskew and Hsym are the skew and symmetric parts of H . If the “residual stress” DW (I ) vanishes, then, to first order,
Distributed_Adaptive_Asymptotic_Tracking_of_2-D_Ve
LetterDistributed Adaptive Asymptotic Tracking of 2-D Vehicular Platoon Systems With ActuatorFaults and Spacing ConstraintsJiayi Lei, Yuan-Xin Li, and Shaocheng TongDear Editor,This letter investigates the adaptive asymptotic tracking sliding-mode control for nonlinear 2-D vehicular platoon systems subject to actuator faults. Firstly, by using the Nussbaum function, the disad-vantageous factors brought by the unknown direction actuator faults can be attenuated. Then, a new neural network (NN) asymptotic tracking control method is presented based on the sliding-mode con-trol and bounded estimation approach. By constructing a barrier Lya-punov function, it can be guaranteed that all signals of the corre-sponding closed-loop systems are bounded, and constraints are not violated. Finally, a numerical simulation is given to verify the obtained results.In the past few decades, the research on the vehicular platoon sys-tems has received growing interests due to its great anti-interference characteristics and string stability. A plenty of representative control algorithms in this area have been developed in [1]–[4]. Although the aforementioned studies can achieve the string stability, the issue of spacing constraints was not considered. To circumvent this problem, an interesting control scheme was proposed in [5], which can guaran-tee not only the safe distance but also communication connectivity. Besides, it is desirable for vehicles to guarantee the collision avoid-ance in some chaotic environments. The distributed tracking control method was proposed for vehicle systems to deal with the problem of obstacle avoidance in [6] by means of the NN. On the basis of exist-ing researches, a vehicle model on a two-dimensional (2-D) plane was first considered in [7], which can simulate the more realistic driving scene. Besides, there were many related results on asymp-totic tracking control problem, which provided asymptotic stable tracking error systems with zero errors in [8]–[10].It is worth noting that, the aforementioned results do not consider the issue of actuator faults, which will lead to deteriorative and insta-ble performance of the system. To ensure the controlled systems’security and dependability, various advanced methods on fault-toler-ant control have been reported in [11]–[13]. Recently, the authors have turned the research direction to the fault-tolerant control of the vehicular platoon systems since various types of actuator faults trig-ger risks to vehicle mechanism. In [14]–[16], the sliding-mode con-trol method and adaptive control technique were used to eliminate the impact of faults for platoon systems. Although lots of significant progress on adaptive fault-tolerant control for vehicular platoon sys-tems have been proposed, the following defects are inevitable in the existing control strategies. 1) The disadvantageous factors brought by the unknown direction actuator faults should be considered, which widely exist in practice and can not be ignored in controller designed.2) There is no work focusing on the asymptotic tracking control for vehicular platoon systems with unknown direction actuator faults to provide tracking performance with zero-error tracking.d i(t)Motivated by the above considerations, this letter addresses the adaptive asymptotic tracking sliding-mode control problem for non-linear 2-D vehicular platoon systems subject to actuator faults with unknown directions. The main contributions lie in the following: 1) Different from the traditional control methods [1]–[6], where the pro-posed control method do not obey principle owing to the existence of unknown direction actuator faults. To solve this problem, we design a Nussbaum function to eliminate disadvantageous factors brought by the unknown direction actuator faults. 2) An asymptotic tracking control for nonlinear 2-D vehicular platoon systems with unknown direction actuator faults is first proposed in this work. Based on the sliding-mode control, we design a novel asymptotic tracking con-troller to ensure that the practical distance tracks the desired dis-tance d asymptotically.Problem formulation:Consider a nonlinear i th follower system expressed as the following form:i iψi(t)v i(t)a i(t)u Fi(t)g i(x i,y i,v i,t)r i(t)ωi(t)ϵi(t)position respectively; is the angle between the speed direction and the X-axis direction; and , respectively, the vehicle’s velocity and acceleration; denotes the actuator faults;is uncertainty under nonlinear unmodeled dynamic; represents external disturbance; is the angular rate and is the acceleration of the velocity direction deflection angle.The actuator faults in our research are modeled as follows:iγ,i i n,itγ,i t n,iwhere denote the fault factors and are the bias faults. and are unknown fault time instants.r i(t)|r i(t)|≤¯r i,i=1,2,...,nAssumption 1: The external disturbances are unknown and bounded satisfying.γi(t,tγ,i)n i(t,t n,i)0<γi≤|γi(t,tγ,i)|≤γi<∞|n i(t,t n,i)|≤¯n i,i=1,2,...,nAssumption 2: The unknown parameters and referring to (3) satisfy the following conditions:and .min max i i are respectively the distance and the velocity direction deflection0<∆min<d i(t)<∆max∆min∆maxthe spacing restrictions are given as: , where is the minimum distance to ensure safety, while is the maximum distance to maintain effective communication.In addition,to guarantee the distance restrictions, the followinga minb maxChoose the following sliding surfaces:s i(t)=˙e i(t)+ρ1e i(t)+ρ2|e i(t)|a b sgn(e i(t))(8)12ρ3where a and b are positive constants satisfying , and and are positive constants.u i(t)Then, the controller is established asCorresponding author: Yuan-Xin Li.Citation: J. Y. Lei, Y.-X. Li, and S. C. Tong, “Distributed adaptiveasymptotic tracking of 2-D vehicular platoon systems with actuator faults andspacing constraints,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 5, pp.1352–1354, May 2023.The authors are with the College of Science, Liaoning University of Techno-logy, Jinzhou 121001, China (e-mail: yxinly@126.Color versions of one or more of the figures in this paper are availableonline at .Digital Object Identifier 10.1109/JAS.2023.1231501352 IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 10, NO. 5, MAY 2023D i (t )=ρ1˙ei (t )+ρ2ab |e i (t )|ab −1˙e i (t )+i i d i (t ),G i (t )=s i (t )×(ˆθi ζT 1,i (X i )ζ1,i (X i )√s 2i ζT 1,i (X i )ζ1,i (X i )+σ2i +ˆφi ζT 2,i (X i )ζ2,i (X i )√s 2i ζT 2,i (X i )ζ2,i (X i )+σ2i +ηi √s 2i +σ2i)H i (t )=1−sgn(e i (t ))νi ×e i (t )k a 2−e 2i (t )+1+sgn(e i (t ))νi e i (t )k b 2−e 2i (t )where , and the adaptive update laws are pro-i i σi (t )σi (t )>0,lim t →∞ tt 0σi (ϵ)d ϵ≤σi <+∞,σi Here, , and l are positive parameters. The Nussbaum function can be chosen as [7] to attenuate the disadvantageous factors brought by unknown direction actuator faults. In addition, is any uni-form boundedness continuous function expressed as: with being an unknown positive constant.Theorem 1: Consider the 2-D vehicular platoon systems (1) satisfy-ing Assumptions 1 and 2. The controller (10) and the adaptive laws (11) can ensure that the tracking errors converge to zero asymptoti-cally, and all the signals of closed-loop system are bounded.Then, by considering (1), (4) and (8), we can obtainV (t )From (12) and Lemma in [7], the derivative of givesi i i i ˜θi (t )=θ∗i−ˆθi (t )˜φi (t )=φ∗i −ˆφi (t )where and represent the estimation of and . Defineand .W ∗Tj ,i ζj ,i (X i ),j =1,2,Referring to [12], the NN are employed to 1,i 2,i 1,i ε1,i |ε2,i (t )|≤ε2,i W ∗1,i W ∗2,i and , and are the given optimal weight vectors.µ=14θi +14φi +θi +φi +ηi where .0µσi with .V (0)∑N i =1 t0[(ςN +1)˙ξi ]d τ[0,+∞)V (t )e i ,˜θi ,˜φi ˆθi ˆφ[0,+∞)This together with Lemma in [17], it can be shown that and are bounded on . In view of the defini-tion of , the boundedness of can be achieved. Besides,we can obtain that and are bounded. Therefore, we can conclude that all the signals of the controlled system are bounded on .Next, we prove the asymptotic tracking performance of the sliding t →∞i lim t →∞e i (t )=0From that, we know . Together with (8), we canget . Therefore, the asymptotic convergence is achieved. In addition, to prove the stability of sliding surfaces, the ψi ˙Vψ(t )<0, which implies that the object of this letter is ensured that sliding surfaces are asymptotically stable.d =15m ∆min =7m ∆max =22m a 0(t )=0.6t m /s 2,2.3m /s 2,−5m /s 20s ≤t <5s ,5s ≤t <9s ,14s ≤t <15s Numerical example: A platoon of vehicles with 1 leader vehicle and 4 follower vehicles are taken into account. The desired vehicle distances are set as , and , . The ex-pected acceleration of leader is while , respectively.To verify the above results, the system parameters used for simula-LEI et al .: DISTRIBUTED ADAPTIVE ASYMPTOTIC TRACKING OF 2-D VEHICULAR PLATOON SYSTEMS 1353αi =10βi =0.0009σi =10e −5t ˆθi (t )=1ˆφi (t )=1ρ1=1.5ρ2=0.3ρ3=6a =6b =4l =170g i (x i ,y i ,v i ,t )=−a 0,i −a 1,i v i (t )−a 2,i v 2i (t )a 0,i =0.01176a 1,i =0.00077616a 2,i =0.000016n i (t ,t n ,i )=sin(it +i π)γi (t ,t γ,i )n i (t ,t n ,i )γ1(t ,t γ,1)=1.2−0.2cos(t )γ2(t ,t γ,2)=0.5−0.2cos(t )γ3(t ,t γ,3)=−0.9−0.2cos(t )γ4(t ,t γ,4)=−0.4+0.2sin(0.01t )n i (t ,t n ,i )=0.3+0.2cos(t )m =3n =0.001tions are given as: , , , ,, , , , , , . In the simu-lation, is used with , , . In addition, the distur-bance enters into the system at the beginning.Consider the fault efficiency factors and bias fault as: , , , , . For the Nussbaum function, we select , .d i (t )ψi −1(t )ψi u i Simulation results under the proposed scheme are depicted in Figs. 1(a)−1(d), Figs. 1(a) and 1(b) show the performance of output variable and and the desired reference d and , respec-tively. It can be observed from these two figures that the tracking errors converge to zero asymptotically despite of unknown direction faults occurring on the actuators, which means that the proposed con-trol scheme can completely compensate for the influence by the fault to the system. Fig. 1(c) shows the practical positions of four vehicles,which can be seen that all followers move to the line, and 2-D driv-ing scene is achieved. Fig. 1(d) shows the curve of control input .Generally, according to the simulation results, it is obvious that the tracking errors converge to zero asymptotically while the whole sig-nals of closed-loop systems are bounded.To better exhibit the effectiveness of the presented scheme, we make a comparison on convergence results between the presented scheme in this letter and existing control scheme in [7]. From the comparison in Fig. 2, it is very clear that the tracking errors in this letter are much more satisfactory than those in [7].Conclusion: In this letter, 2-D vehicular platoon asymptotic track-ing sliding-mode control under unknown directions actuator faults has been investigated. By using the Nussbaum function, the disad-vantageous factors brought by the unknown direction actuator faults can be attenuated effectively. Based on the sliding-mode control and bounded estimation approach, a new asymptotic tracking controlmethod is presented to realize the asymptotic convergence of track-ing errors. Simulations verify the performance of the proposed approach.Acknowledgment: This work was supported in part by the Funds of National Science of China (61973146, 62173172), the Distin-guished Young Scientific Research Talents Plan in Liaoning Province (XLYC1907077, JQL201915402), and the Applied Basic Research Program in Liaoning Province (2022JH2/101300276)ReferencesY. Li, C. Tang, S. Peeta, and Y. Wang, “Nonlinear consensus-basedconnected vehicle platoon control incorporating car-following interactions and heterogeneous time delays,” IEEE Trans. Intelligent Transportation Syst., vol. 20, no. 6, pp. 2209–2219, Jun. 2019.[1]G. Guo and D. Li, “Adaptive sliding mode control of vehicular platoonswith prescribed tracking performance,” IEEE Trans. Vehicular Techno -logy , vol. 68, no. 8, pp. 7511–7520, Aug. 2019.[2]X. Ge, S. Xiao, Q.-L. Han, X. M. Zhang, and D. Ding, “Dynamic event-triggered scheduling and platooning control co-design for automated vehicles over vehicular ad-hoc networks,” IEEE/CAA J. Autom. Sinica ,vol. 9, no. 1, pp. 31–46, Jan. 2022.[3]Z. Zuo, C. Liu, Q.-L. Han, and J. Song, “Unmanned aerial vehicles:Control methods and future challenges,” IEEE/CAA J. Autom. Sinica ,vol. 9, no. 4, pp. 601–614, Apr. 2022.[4]J. Wang, X. Luo, W. Wong, and X. Guan, “Specified-time vehicularplatoon control with flexible safe distance constraint,” IEEE Trans.Vehicular Technology , vol. 68, no. 11, pp. 10489–10503, Nov. 2019.[5]X. Ge, Q.-L. Han, J. Wang, and X. M. Zhang, “A scalable adaptiveapproach to multi-vehicle formation control with obstacle avoidance,”IEEE/CAA J. Autom. Sinica , vol. 9, no. 6, pp. 990–1004, Jun. 2022.[6]X. G. Guo, W. D. Xu, J. L. Wang, and J. H. Park, “Distributedneuroadaptive fault-tolerant sliding-mode control for 2-D plane vehicular platoon systems with spacing constraints and unknown direction faults,” Automatica , vol. 129, p. 109675, 2021.[7]Z. Zhang, S. Xu, and B. Zhang, “Asymptotic tracking control ofuncertain nonlinear systems with unknown actuator nonlinearity,” IEEE Trans. Autom. Control , vol. 59, no. 5, pp. 1336–1341, May 2014.[8]Z. Zhang, S. Xu, and B. Zhang, “Exact tracking control of nonlinearsystems with time delays and dead-zone input,” Automatica , vol. 52,pp. 272–276, 2015.[9]W. Wang, J. Huang, C. Wen, and H. Fan, “Distributed adaptive controlfor consensus tracking with application to formation control of nonholonomic mobile robots,” Automatica , vol. 4, no. 50, pp. 1254–1263, 2014.[10]S. Y. Xiao and J. X. Dong, “Distributed fault-tolerant containmentcontrol for nonlinear multi-agent systems under directed network topology via hierarchical approach,” IEEE/CAA J. Autom. Sinica , vol. 8,no. 4, pp. 806–816, Apr. 2021.[11]X. Jin, X. Zhao, J. Yu, X. Wu, and J. Chi, “Adaptive fault-tolerantconsensus for a class of leader-following systems using neural network learning strategy,” Neural Networks , vol. 121, pp. 474–483, 2020.[12]H. Wang, W. Bai, and P. X. Liu, “Finite-time adaptive fault-tolerantcontrol for nonlinear systems with multiple faults,” IEEE/CAA J.Autom. Sinica , vol. 6, no. 6, pp. 1417–1427, Nov. 2019.[13]G. Guo, P. Li, and L. Y. Hao, “Adaptive fault-tolerant control ofplatoons with guaranteed traffic flow stability,” IEEE Trans. Vehicular Technology , vol. 69, no. 7, pp. 6916–6927, Jul. 2020.[14]C. Pan, Y. Chen, and I. Ali, “Adaptive fault-tolerant control forautonomous vehicle platoon against fault,” in Proc. CAA Symp. Fault Detection, Supervision, Safety Technical Processes , 2021, pp. 1–5.[15]L. Y. Hao, H. Zhang, H. Li, and T. S. Li, “Sliding mode fault-tolerantcontrol for unmanned marine vehicles with signal quantization and time-delay,” Ocean Engineering , vol. 215, p. 107882, 2020.[16]Z. T. Ding, “Adaptive consensus output regulation of a class ofnonlinear systems with unknown high-frequency gain,” Automatica ,vol. 51, no. 7, pp. 348–355, 2015.[17]J. J. Slotine and W. Li. “Applied nonlinear control,” in EnglewoodCliffs , New Jersey, USA: Prentice Hall, 1991, vol. 199, no. 1, pp.1–461.[18]1050−5−10e (t ),i = 1, 2, 3, 45L 0F F F F t (s)(a) Spacing errors e i (t )1015Δ−Δ−e (t )e (t )e (t )e (t )0.20−0.2−0.4e (t ),i = 1, 2, 3, 4t (s)(b) Deflection angle errors e ψi (t )33323130292827y (t ),i = 1, 2, 3, 450100150200250300350400x (t ), i = 1, 2, 3, 4(c) 2-D driving scene 450500400020000−2000−4000u (t ),i = 1, 2, 3, 45t (s)(d) Control input u i (t )1015u (t )u (t )u (t )u (t )Fig. 1. Simulation results of this letter.1050−5−10e (t ),i = 1, 2, 3, 41050−5−10e (t ),i = 1, 2, 3, 41050−5−10e (t ),i = 1, 2, 3, 4t1050−5−10e (t ),i = 1, 2, 3, 45t (s)(a) e 1(t )10155t (s)(b) e 2(t )1015(c) e 3(t )5t (s)(d) e 4(t )10155t (s)1015e (t ) in this letter e (t ) in [7]e (t ) in this letter e (t ) in [7]e (t ) in this letter e (t ) in [7]e (t ) in this letter e (t ) in [7]e i (t )Fig. 2. Comparison results of .1354IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 10, NO. 5, MAY 2023。
数字对象唯一标识符CDOI探析
△通 信 作 者 :谢 丽 佳 ,513407720@qq.tom
058
信 息管 理 与信 息学
48—2012数字对象 唯一标识符规范》。l8 本文对 CDOI 结构及具体 的编码规则进行分析讨 论并提 出 自己的设 想 ,希 望 能 抛 砖 引 玉 ,吸 引 学 者 们 从 更 多 的 角 度 对 CDOI的 标识 符 系 统方 案 进 行研 究 与 推广 。
popularity of early DOI systems.This article introduces the genera l situation of DOI,Chines DOI and CDOI,ana lyzes the syntax of CDOI in detail,and discusses the naming rules of CDOI pref ix,extension of suffix and the feasibility of applying two—dimen— sional code.
Keywords:Unique Identifier of Digital Object;DOI;Chinese DOI;CDOI
1 引 言 随着 互 联 网的 普 及 ,数 字 对 象 的 内容 、生 成 方 式
和 格 式 越来 越 多 。数 字 对 象 唯一 标识 字 对 象 的 一种 内容 识 别 符 系 统 ,… 具 有 唯 一 性 、永 久 性 、多重 链 接 等 特 点 ,能在 网络 环 境 下对 数 字 对 象 进 行 标识 、定 位 及管 理 。E 2 3数 字对 象 唯 一 标 识 符 分 为 静 态 和 动 态 两 种 类 型 , 如 ISBN、 ISSN、ISRC 等 是 静 态 唯 一 标 识 符 ,而 URL、DOI、 CIDF等 属 于 动 态 标 识 符 。两 种 标 识 符 都 有 特 定 的构 成 规 则 和 专 门 的管 理 机 构 ,区别 在 于 静 态标 识 符 缺 乏 基 于 网络 的解 析 ,而 动 态 标识 符 具 有 网络 环境 下分 布 式 解 析 与 管 理 的 机 制 ,是 可 产 生行 为 的 、可 解 析 的 、 可 链 接 的标 识 符 。
数字对象唯一标识符
谢谢观看
数字对象唯一标识符
互联信息在内的数字信息进行标识的一种工具
01 概念
03 行政组织 05 国内情况
目录
02 命名规则 04 国外情况 06 优点
07 形式
09 库存天数
目录
08 意义 010 解释域
doi的全称是digital object unique identifier,是指数字对象唯一标识符,是云计算背景下最佳的 “大数据”样本存储和应用技术,用于IKE进行协商SA协议统一分配。
形式
编码方案
DOI的编码方案(即美国标准ANSI/NISO Z39.84-2000)规定,一个DOI由两部分组成:前缀和后缀,中间用 “/”分割。对前缀与后缀的字符长度没有任何限制,因此理论上,DOI编码体系的容量是无限的。
前缀组成
DOI前缀由两部分组成,一个是目录代码,所有DOI的目录都是“10.”,即所有DOI代码都以“10.”开头。 另一个是登记机构代码,任何想登记DOI的组织或单位都可以向IDF申请登记机构代码。登记机构代码的分配也是 非常灵活的,如一个出版商可以为其所有的信息资源只申请一个前缀,也可以为其数字图书、音像制品各申请一 个前缀。
优点
唯一性 DOI标识符作为数字化对象的识别符,对所标识的数字对象而言,相当于人的,具有唯一性。这种特性保证 了在络环境下对数字化对象的准确提取,有效地避免重复。 持久性 一个数字化对象的DOI标识符一经产生就永久不变,不随其所标识的数字化对象的版权所有者或存储等属性 的变更而改变。 兼容性 DOI标识符的兼容性体现在DOI号码的后缀中可以包含任何已有的标识符,例如国际标准书号ISBN,国际标准 刊号ISSN,国际标准文本代码ISTC,出版物件标识符PII等。 互操作性 DOI的处理系统可以与任何因特上不同的计算机操作系统在处理同一数据时能保持一致,能与不同时期的技 术系统兼容。
digitalio用法 -回复
digitalio用法-回复digitalio用法指的是在编程中使用digitalio库来控制数字输入输出(digital input/output)的操作。
这篇文章将一步一步地介绍digitalio 的用法和示例,帮助读者理解如何使用digitalio库来控制数字输入输出。
第一步:导入digitalio库在使用digitalio库之前,我们需要先导入该库。
可以在代码的开头添加以下代码:import digitalio第二步:初始化引脚在开始使用digitalio库之前,我们需要先初始化引脚。
引脚的初始化包括指定引脚的模式(输入或输出)和设置引脚的初始状态(高电平或低电平)。
以下是初始化引脚的示例代码:import boardimport digitalio# 初始化引脚为输出模式led = digitalio.DigitalInOut(board.LED)led.direction = digitalio.Direction.OUTPUT# 初始化引脚为输入模式button = digitalio.DigitalInOut(board.BUTTON)button.direction = digitalio.Direction.INPUTbutton.pull = digitalio.Pull.UP在上述示例代码中,我们使用了`board`库来指定引脚。
`board.LED`和`board.BUTTON`是一些常见开发板上的引脚定义,可以根据具体开发板的引脚定义进行修改。
第三步:控制输出引脚一旦引脚被初始化为输出模式,我们可以使用digitalio库提供的方法来控制输出引脚的状态。
以下是几个常用的控制输出引脚的方法:- `value`属性:用于读取或设置引脚的状态。
`True`表示高电平,`False`表示低电平。
- `toggle()`方法:用于切换引脚的状态,如果当前状态是高电平,则切换为低电平;如果当前状态是低电平,则切换为高电平。
我刊加入中国知网数据DOI注册、解析及链接服务
河南科技大学学报(社会科学版)第33卷櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢櫢毟毟毟毟·简讯·我刊加入中国知网数据DOI 注册、解析及链接服务根据我刊编辑部与同方知网(北京)技术有限公司“国际DOI 中国注册与服务中心”签订的DOI 授权协议,该中心为我刊提供论文的DOI 注册、DOI 解析及链接服务。
我刊将从2015年第3期开始为发表的每篇稿件标注DOI 注册码。
DOI (Digital Object Identifier )的中文含义为“数字对象唯一标识符”,是一种针对数字资源的全球唯一永久性标识符,主要是针对因特网环境下如何对知识产权进行有效保护和管理而产生的,具有对资源进行永久命名标识、动态解析链接的特性,被称为互联网上的条形码。
目前美国、欧洲、澳洲、日本等国家的重要学术资源都已经使用DOI 标识。
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本刊编辑部2015年5月[8]罗迪江.论语言适应论的生成观[J ].西安外国语大学学报,2014,(3):62-66.[9]罗迪江,兰晶.语言适应论的本体论意蕴[J ].南华大学学报:社会科学版,2014,(2):116-120.[10]约翰·霍兰.隐秩序:适应性造就复杂性[M ].周晓牧,韩晖,译.陈禹,方美琪,校.上海:上海科技教育出版社,2000.[11]陈禹.复杂适应系统(CAS )理论及其应用———由来、内容与启示[J ].系统辩证学报,2001,(4):35-39.[12]罗迪江.基于CAS 的语言迁移的生成过程探析[J ].外国语文,2013,(5):75-79,118.[13]约翰·霍兰.涌现———从混沌到有序[M ].陈禹,方美琪,译校.上海:上海科学技术出版社,2006:127.[14]罗迪江,兰晶.论维索尔论“综观论转向”的实质[J ].柳州师专学报,2014,(3):39-42.[15]罗迪江,董保华.语言适应论的意义诠释[J ].牡丹江大学学报,2013,(8):86-89.[16]钱冠连.汉语文化语用学:人文网络言语学[M ].北京:清华大学出版社,2002:10.[17]桂起权.再论量子场的实在论和生成辩证法[J ].自然辩证法研究,2009,(3):19-23.[18]罗迪江.以CAS 理论为视角解读自私基因理论的核心思想[J ].科学技术哲学研究,2014,(5):60-64.Linguistic Adaptation Theory Explored from the Perspectiveof CAS TheoryLUO Di-jiang a ,LAN Jing b(Guangxi University of Science and Technologya.Foreign Languages School ,b.Lushan College ,Liuzhou 545006,China )Abstract :Verschueren extended Darwin ’s Natural Selection Theory into the field of pragmatics and constructed Linguistic Adaptation Theory on the basis of making linguistic choices and adaptation.Based on the perspectiveof complexity adaptive system (CAS ),Linguistic Adaptation Theory places the making choice-adaptation mechanism of language-context interaction at the key point and reveals that its inner structure is based on theinteractional mechanism of causation and contingency with basic feature that adaptability making the complexity of language application.Key words :CAS ;Linguistic Adaptation Theory ;choice-adaptation mechanism·07·。
电子文件元数规范
电子文件元数据规范1 范围本规范适用于九省区各级国家档案馆、各级党政机关、社会团体、企事业单位对电子文件进行以保证凭证性为目的的管理活动。
其他社会组织可参照执行在电子文件管理过程中使用元数据可实现以下目的:——确保并证明归档电子文件的真实性、完整性与有效性,从而保证其凭证价值;——有利于归档电子文件的保护,实现长期保存;——在异构的信息系统中对归档电子文件进行规范、有效的管理,保证归档电子文件的可捕获、可收集、查长期利用;——对归档电子文件及馆(室)藏档案数字化资源进行集成管理,实现有效、方便地查询、检索与利用。
2 规范性引用文件下列文件中的条款通过本规范的引用而成为本规范的条款。
凡是注明日期的引用文件,其随后所有的修改单(不包括勘误的内容)或修订版均不适用于本规范,然而,鼓励根据本规范达成协议的各方研究是否可使用这些文件的最新版本。
GB 2312-1980 信息交换用汉字编码字符集基本集GB/T 3760-1995 文献叙词标引规则GB/T 3792.1-1983 文献著录总则GB/T 7156-2003 文献保密等级代码GB/T 7408-2005 数据元和交换格式信息交换日期和时间表示法GB/T 9704-1999 国家行政机关公文格式GB/T 11714-1997 全国组织机构代码编制规则GB/T 11821-2002 照片档案管理规范GB/T 13959-1992 文件格式与代码编制方法GB/T 13967-1992 全宗单GB/T 15418-1994 档案分类标引规则GB 18030-2000 信息技术信息交换用汉字编码字符集基本集的扩充GB/T 18894-2002 电子文件归档与管理规范DA/T 1-2000 档案工作基本术语DA/T 12-1994 全宗卷规范DA/T 13-1994 档号编制规则DA/T 18-1999 档案著录规则DA/T 19-1999 档案主题标引规则DA/T 22-2000 归档文件整理规则DA/T 31-2005 纸质档案数字化技术规范《中华人民共和国电子签名法》中办发[1996]14号中国共产党机关公文处理条例国发﹝2000﹞23号关于发布《国家行政机关公文处理办法》的通知国档发[1987]4号关于颁发《编制全国档案馆名称代码实施细则》的通知国家档案局第6号令《电子公文归档管理暂行办法》,2003年7月28日国家档案局第8号令《机关文件材料归档范围和文书档案保管期限规定》,2006年12月19日ISO 15489 Information and documentation—Records managementISO 23081-1 Information and documentation – Records Management Processes – Metadata for Records—Part 1: PrinciplesISO 14721 Open archives information system (OAIS)ISO/IEC 11179-3 :2004 INFORMATION TECHNOLOGY - SPECIFICATION AND STANDARDIZATION OF DATAELEMENTS - PART 3: BASIC ATTRIBUTES OF DATA ELEMENTSGUIDE FOR MANAGING ELECTRONIC RECORDS FROM AN ARCHIVAL PERSPECTIVE, COMMITTEE ON ELECTRONIC RECORDS,ICA(国际档案理事会电子文件管理委员会《电子文件管理指南》),1997 W3C Namespaces in XML XML的命名空间(Namespaces)3 术语与定义3.1电子文件(Electronic Records)电子文件是指在数字设备及环境中生成,以数码形式存储于磁带、磁盘、光盘等载体,依赖计算机等数字设备阅读、处理,并可在通信网络上传送的文件。
A_Novel_Sensor_Scheduling_Algorithm_Based_on_Deep_
LetterA Novel Sensor Scheduling Algorithm Based on DeepReinforcement Learning for Bearing-Only TargetTracking in UWSNsLinyao Zheng, Meiqin Liu, Senior Member, IEEE, Senlin Zhang, Member, IEEE, and Jian Lan, Senior Member, IEEEDear Editor,This letter is concerned with the energy-aware multiple sensor co-scheduling for bearing-only target tracking in the underwater wire-less sensor networks (UWSNs). Considering the traditional methods facing with the problems of strong environment dependence and lack flexibility, a novel sensor scheduling algorithm based on the deep reinforcement learning is proposed. Firstly, the sensors’ co-schedul-ing strategy in UWSNs is formulated as Markov decision process (MDP). Then, a dueling double deep Q network (D3QN) is devel-oped to solve the MDP in a scalable and model free manner. Besides, the prioritized experience replay (PER) method is utilized to acceler-ate network convergence. Finally, the effectiveness and superiority of the proposed algorithm are confirmed by experimental results.With the advantages of self-organization structure, low cost and strong concealment, UWSNs show a promising ability in underwater target passive tracking [1]. However, the battery-powered sensors in the UWSNs are hardly to be recharged in the depths of the ocean, severely limiting the lifetime of UWSNs. Therefore, it is essential to study an energy-efficient sensor co-scheduling strategy to make a tradeoff between tracking accuracy and energy consumption. In [2], a wake-up/sleep and valid measurement selecting method was pro-posed to increase the energy efficiency of the sensors in UWSNs. In [3], an adaptive sensor scheduling scheme was introduced, and energy can be saved by changing the sampling intervals according to tracking accuracy threshold at each time step. In [4], a novel under-water passive tracking framework in UWSNs based on dynamic clus-tering was proposed, scheduling the sensors by selecting cluster head and cluster members adaptively based on dynamic programming (DP) method. Although the above studies have already made good progress, the proposed methods greatly depend on environment and prior information, and lack flexibility in complex and dynamic underwater environments.Compared with the traditional method, deep reinforcement learn-ing (DRL) has no need for exactly prior knowledge of environment and has a strong ability to adapt the dynamic changes of the environ-ment [5], which makes it more suitable for underwater environment. Besides, as demonstrated in [6], the DRL techniques can be effec-tively deployed in UWSNs.Motivated by the above discussions, in this letter, we aim to obtain an energy-efficient sensor scheduling policy for underwater passive tracking in UWSNs. To this end, following the underwater passive tracking framework in [4] and considering the characteristics of underwater passive tracking in UWSNs, we formulate the sensors’co-scheduling protocol as MDP. Then, the D3QN algorithm with PER is applied to obtain better learning performance. The main con-tributions of this letter are stated as follows: 1) The sensor co-scheduling strategy in UWSNs is formulated as MDP. 2) A mock data method is introduced to construct the reward function in the DRL environment to avoid the abuse of ground truth of target. 3) The D3QN algorithm with PER is introduced to solve the MDP to find a suitable schedule policy in a scalable and model-free manner.N kFC kR c R s.E kF k E k F kProblem statement:1) Underwater passive tracking framework: In this letter, the target motion model is assumed as constant velocity model (CVM) [7]. Referring to the underwater passive tracking framework in [4], there are cluster members (CM) and a cluster head to construct a dynamic cluster to participate in tracking at time k. Fig. 1 shows the basic idea of this framework. Furthermore, assuming the sensors in the UWSNs have the same communication range and the same sensing range Moreover, we define that all activated sensors make up the candidate cluster member set and the candidate cluster head set at time k. and satisfy the fol-I P_th I FC_thE PthE FCth where and are acoustic intensity thresholds of candidate cluster members and cluster heads respectively. and are energy thresholds of candidate cluster members and cluster heads respectively.Target trajectoryTarget radiated signalCommunication between CHsCommunication between CH and CMFig. 1. The passive target tracking framework based on dynamic cluster.E k2) Energy-efficient sensors’ co-scheduling protocol: The objective of the co-scheduling in the above framework is to choose the suit-able cluster members from the set by cluster heads to make an optimal tradeoff between tracking accuracy and energy consumption. The above objective is equivalent to maximize the objective func-tion as follows:JψPkNkλφutility(·)where is the sub set composed of cluster members which are chosen at time k, is the joint factor which is used to balance the energy consumption and tracking accuracy, and is the util-ity function representing the tracking performance, which is given byCorresponding author: Meiqin Liu.Citation: L. Y. Zheng, M. Q. Liu, S. L. Zhang, and J. Lan, “A novel sensor scheduling algorithm based on deep reinforcement learning for bearing-only target tracking in UWSNs,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 4, pp. 1077–1079, Apr. 2023.L. Y. Zheng and J. Lan are with the Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an 710049, China (e-mail: zhengLY@M. Q. Liu is with the Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an 710049, and also with the State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027,S. L. Zhang is with the College of Electrical Engineering, ZhejiangColor versions of one or more of the figures in this paper are available online at .Digital Object Identifier 10.1109/JAS.2023.123159J k P ∗k φcos t (·)here is the fisher information matrix according to the positions of members in [4]. is the cost function representing theE initial i ,ki -th E pi ,k i -th where is the initial energy of the cluster member at time k ,and is the energy consumption of the cluster member.Proposed methods: In this section, we shall introduce the detail of the proposed method from two aspects:<S ,A ,R ><S ,A ,R >1) Formulation of MDP: Equation (4)can be formulated as an MDP, which is defined by a tuple . Each element is defined as follows:S a) State space : From the discussion above, the state of the MDP S where the state is directly related to the objection function at timek , giving faster convergence for the algorithm [8].A N k !N ∗k!(N k −N ∗k )!b) Action space : The action space corresponding to different ways of choosing the suitable cluster member from the set R r c kr s .c) Reward function : The reward function includes the followingtwo items: the current rewardand the settlement reward The r s T d ¯d i The settlement reward is the huge reward representing each training result which can be reflected by tracking performance and system energy efficiency. However, the most of tracking perfor-mance evaluation methods assume exact knowledge of the ground truth, which is hard to be obtained in the practical underwater pas-sive tracking.To solve this problem, we introduce the mock data method [9], which can evaluate the tracking performance by measur-ing the deviation between mock data generated by the estimate and the real measurement. Therefore, assuming that the time of a track-ing is , the tracking performance of each training can be repre-m k m k d x whereis the mock data and is the real measurement, is theMahalanobis distance between the mock data and real measurement.N e d goal E goal κµwhere is the number of training,and are the goal of tracking accuracy and energy consumption respectively, which are determined by the task requirements. and are weighting factors,which are set for the tradeoff between the tracking performance and system energy consumption.Q (s k ,a k )2) Solution by D3QN: In DRL, the key point of solving MDP is to obtain the expected return by maximizing state-action value which is approximated by the deep Q network. For better learning performance, we introduce the D3QN to solve the above MDP.D3QN is composed of current network and target network which are deep Q networks with different parameters but the same structure,Here, current network and target network are composed of one inputθθ′layer, two 128-layer full connection (FC) layers and one output layer.The parameter of current network is while the parameter of target network is . D3QN solves the MDP by updating the current net-work with loss function. The current network of D3QN at time k , is composed of value function and advantage function, which isa k V k (·)A (·)N A p q where is all actions that can be taken at time k , is the value function, is the advantage function, is the number of actions, and are network parameters of value function and advantage function respectively.To further improve the samplingefficiency and convergence speed, PER is employed to update the network parameter [10]. Then,kr tor gradually increasing to 1.In summary, the proposed D3QN-PER based sensor scheduling method is shown in Fig. 2.Fig. 2. The D3QN-PER based sensor scheduling method.Experiments: A numerical example is provided to evaluate the performance of the proposed method in the underwater passive track-ing scenario compared with some existing sensor schedule methods.We consider the following existing methods:1) The sensor schedule method based on DP in [4].2)The sensor schedule method based on genetic algorithm (GA),which utilizes the GA method to solve the schedule problem in (6).30N ∗k |E k|=10,λThe initial settings of UWSNs and target are the same as those in [4]. The total observation time of system is s. The number of clus-ter member is set as 3 and meanwhile, the joint factor of the objection function is set as 0.6. Overall, the simulation envi-ronment is shown in Fig. 3. The D3QN parameter setting is shown in Table 1, which is set by the rule in [5]. The training process of the proposed method is shown in Fig. 4. The GA method is imple-mented by the GA tools in Python [11].Our experiment uses an AMD Core 5800X CPU @ 3.80 GHz,NVIDIA GeForce RTX3080 GPU, and Windows 1064 bit. We use Python 3.8 and Pytorch 1.11.0 to realize the proposed method.To access the target passive tracking accuracy, the root mean square error (RMSE) is adopted to evaluate the performance of our algorithm. The RMSE data of these compared methods in 100 Monte Carlo tests is shown in Fig. 5. Furthermore, to evaluate the energy consumption, we record the energy consumption in Fig. 5.As shown in Fig. 4, After around the 130th episode, the reward keeps stable high scores, which illustrates the convergence of the proposed algorithm. In Fig. 5, the RMSE result illustrates that the tracking accuracy of D3QN-PER based method is better than that ofDP based method and GA based method. Besides, Fig. 5 also shows that the D3QN-PER based method has lower energy consumption compared with other methods. It is seen from Fig. 5 that the pro-posed method performs better than the methods compared.Conclusions: This letter has proposed a new DRL-based sensor schedule method for underwater passive tracking in UWSNs. The schedule problem is formulated as MDP and a mock data method is introduced to construct the reward function to avoid the abuse of ground truth of target. Furthermore, the D3QN-PER algorithm is introduced to solve the MDP to find a suitable schedule policy in a scalable and model-free manner. Finally, the simulation results con-firm the effectiveness and the superiority of the proposed method.Acknowledgments: This work was supported by the National Nat-ural Science Foundation of China (62173299, U1809202), the Joint Fund of Ministry of Education for Pre-Research of Equipment (8091B022147), and the Fundamental Research Funds for the Cen-tral Universities (072022001).ReferencesJ. Luo, H. Ying, and L. Fan, “Underwater acoustic target tracking: Areview,” Sensors , vol. 18, no. 1, p. 112, 2018.[1]C. H. Yu, J. C. Lee, J. W. Choi, M.-K. Park, and D. J. Kang, “Energyefficient distributed interacting multiple model filter in UWSNs,” in Proc. 12th Int. Conf. Control, Automation and Syst., 2012, pp.1093–1098.[2]S. Zhang, H. Chen, and M. Liu, “Adaptive sensor scheduling for targettracking in underwater wireless sensor networks,” in Proc. Int. Conf.Mechatronics Control , 2014, pp. 55–60.[3]X. Han, M. Liu, S. Zhang, and Q. Zhang, “A multi-node cooperativebearing-only target passive tracking algorithm via UWSNs,” IEEE Sensors J., vol. 19, no. 22, pp. 10609–10623, 2019.[4]A. Feriani and E. Hossain, “Single and multi-agent deep reinforcementlearning for AI-enabled wireless networks: A tutorial,” IEEE Commu.Surveys & Tutorials , vol. 23, no. 2, pp. 1226–1252, 2021[5]R. Su, Z. Gong, D. Zhang, C. Li, Y. Chen, and R. Venkatesan, “Anadaptive asynchronous wake-up scheme for underwater acoustic sensor networks using deep reinforcement learning,” IEEE Trans. Vehicular Technology , vol. 70, no. 2, pp. 1851–1865, 2021.[6]X. R. Li and V. P. Jilkov, “Survey of maneuvering target tracking. PartI. Dynamic models,” IEEE Trans. Aerospace and Electronic Syst., vol.39, no. 4, pp. 1333–1364, 2003.[7]X. Leong, A. S. Ramaswamy, A. Quevedo, and D. E. Karl, “Deepreinforcement learning for wireless sensor scheduling in cyber–physical systems,” Automatica , vol. 113, p. 108759, 2020.[8]W. Cao, J. Lan, and X. R. Li, “Joint tracking and classification based onrecursive joint decision and estimation using multi-sensor data,” in Proc. 17th Intern. Conf. Information Fusion , 2014, pp. 1–8.[9]H. Song, Y. Liu, J. Zhao, J. Liu, and G. Wu, “Prioritized replay duelingDDQN based grid-edge control of community energy storage system,”IEEE Trans. Smart Grid , vol. 12, no. 6, pp. 4950–4961, 2021.[10]W. Lee and H. Y. Kim, “Genetic algorithm implementation in python,”in Proc. 4th Annual ACIS International Conf. Computer and Infor.Science , 2005, pp. 8–11.[11]Table 1. D3QN Parameter SettingParameter Value κ/µWeighting factor 1500/2000d goal /E goal0.8/0.23N mMinibatch 128N rReplay buffer capacity 105N e Training episode 200f uNetwork update frequency 30βPER parameter 0.4Learning rate 0.000 25γDiscount factor 0.93Activation function ReLU εExploration probability 0.017500Z (m )1000Fig. 3. The simulation environment.Episode−400−2000200400600800R e w a r dFig. 4. The training process.7654m 3210t (s)16141210j8642t (s)−3Fig. 5. RMSE and energy consumption.ZHENG et al .: A NOVEL SENSOR SCHEDULING ALGORITHM BASED ON DRL FOR BEARING-ONLY TARGET TRACKING IN UWSNS1079。
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Digital Object Identifier (DOI)10.1007/s00220-006-0053-x Commun.Math.Phys.(2006)Communications in Mathematical Physics A Microscopic Derivation of the Quantum Mechanical Formal Scattering Cross SectionD.Dürr 1,S.Goldstein 2,T.Moser 1,N.Zanghì31Mathematisches Institut der Universität München,Theresienstr.39,80333München,Germany.E-mail:duerr@mathematik.uni-muenchen.de;moser@mathematik.uni-muenchen.de2Department of Mathematics,Rutgers University,New Brunswick,NJ 08903,USA.E-mail:oldstein@3Dipartimento di Fisica,Universitàdi Genova,Sezione INFN Genova,Via Dodescanesco 33,16146Genova,Italy.E-mail:zanghi@ge.infn.it Received:1September 2005/Accepted:14March 2006©Springer-Verlag 2006Abstract:We prove that the empirical distribution of crossings of a “detector”surface by scattered particles converges in appropriate limits to the scattering cross section com-puted by stationary scattering theory.Our result,which is based on Bohmian mechanics and the flux-across-surfaces theorem,is the first derivation of the cross section starting from first microscopic principles.1.IntroductionThe central quantity in a scattering experiment is the empirical cross section,which reflects the number of particles that are scattered in a given solid angle per unit time.In this paper we shall derive the theoretical prediction for the cross section starting from a microscopic model describing a realistic scattering situation.We confine ourselves to the case of potential scattering of a nonrelativistic,(spinless)quantum particle and leave the many-particle case for future research.This paper is in fact a technical elaboration and continuation of our article “Scattering theory from microscopic first principles”[9].The common approaches to the foundations of scattering theory take for granted that “an experimentalist generally prepares a state …at t →−∞,and then measures what this state looks like at t →+∞”(cf.[25],p.113),meaning that the asymptotic expressions are “all there is,”as if they are not the asymptotic expressions of some other formula,however complicated,describing the scattering situation as it really is,namely happening at finite distances and at finite times.Thus a truly microscopic derivation starting from first principles must provide firstly a formula for the empirical cross sec-tion,which by the law of large numbers approximates its expectation value,and which is computed from the underlying theory.Secondly,that formula should apply to the real-istic finite-times and finite-distances situation,from which eventually the usual Born formula should emerge by taking appropriate limits.11For a detailed discussion of the scattering regime see [8].D.Dürr,S.Goldstein,T.Moser,N.ZanghìWe shall present a Bohmian analysis of the scattering cross section.With a particletrajectory we can ask for example whether or not that trajectory eventually crosses adistant spherical surface and if it does when and where itfirst crosses that surface.Sim-ilarly,for a beam of particles we can ask for the number of particles in the beam thatfirst crosses the surface in a given solid angle .From a Bohmian perspective it appearsreasonable to identify this number with detection events in a scattering experiment.Wethus model in this paper the measured cross section using the number N ( )offirst crossings of .This will of course depend on many parameters encoding the experi-mental setup,e.g.the distances R and L of the detector and the particle source from thescattering center,the details of the beam including its profile A and the wave functionsof the particles in the beam,as well as on the length of the time intervalτduring whichthe particles are emitted.We shall show in this paper that when these parameters aresuitably scaled,N ( )τis well approximated by the usual Born formula for the scattering cross section in terms of the T-matrix,i.e.,lim N ( )τ=16π4|T(k0ω,k0)|2d ,(1)where k0is the initial momentum of the particles.The paper is organized as follows:We collectfirst some mathematical notions and facts as well as recent results of scattering theory.In Sect.3we define the relevant random variables associated with the surface-crossings of a single particle and relate their distribution to the quantum probability current density.In Sect.4we model the beam by a suitable point process and in Sect.5we define N ( )in terms of this point process.A precise description of the limit procedure will be presented in Sect.6.Our main results,Theorem1and2,are stated in Sect.7and are proven in Sect.8.2.The Mathematical Framework of Potential ScatteringWe list those results of scattering theory(e.g.[2,7,11,14,16,18–20,22])which are essential for the proof of Theorem1and Theorem2in Sect.8.We use the usual description of a nonrelativistic spinless one-particle system by the Hamiltonian H(we use natural units =m=1),H:=−12+V(x)=:H0+V(x),with the real-valued potential V∈(V)n,defined as follows:Definition1.V is in(V)n,n=2,3,4, (i)(i)V∈L2(R3),(ii)V is locally Hölder continuous except,perhaps,at afinite number of singularities, (iii)there exist positive numbersδ,C,R0such that|V(x)|≤C x −n−δfor x≥R0,where · :=(1+(·)2)12.A Microscopic Derivation of the Quantum Mechanical Formal Scattering Cross SectionUnder these conditions (see e.g.[16])H is self-adjoint on the domain D(H )=D(H 0)={f ∈L 2(R 3): |k 2 f (k )|2d 3k <∞}(k =|k |),where f :=F f is the Fourier transform f (k ):=(2π)−32 e −i k ·x f (x )d 3x .(2)Let U (t )=e −i Ht .Since H is self-adjoint on the domain D(H ),U (t )is a strongly contin-uous one-parameter unitary group on L 2(R 3).Let φ∈D(H ).Then φt ≡U (t )φ∈D(H )and satisfies the Schrödinger equationi ∂∂tφt (x )=H φt .In a typical scattering experiment the scattered particles move almost freely far away from the scattering center.“Far away”in position space can also be phrased as “long before”and “long after”the scattering event takes place.So for the “scattering states”ψthere are asymptotes ψin ,ψout defined bylim t →−∞e −i H 0t ψin (x )−e −i Ht ψ(x ) =0,lim t →∞ e −i H 0t ψout (x )−e −i Ht ψ(x ) =0.(3)From this it is natural to define the wave operators ±:L 2(R 3)→Ran ( ±)by the strong limits±:=s-lim t →±∞e i Ht e −i H 0t .(4)These wave operators map the incoming and outgoing asymptotes to their corresponding scattering states.Ikebe [14]proved that for a potential V ∈(V )n the wave operators exist and have the rangeRan ( ±)=H cont (H )=H a.c.(H ).(This property is called asymptotic completeness.)Hence,the scattering states consist of states with absolutely continuous spectrum and the singular continuous spectrum of H is empty.In addition Ikebe [14]showed that the Hamiltonian has no positive eigenvalues.Then we have for every ψ∈H a.c.(H )asymptotes ψin ,ψout ∈L 2(R 3)with−ψin =ψ= +ψout .(5)On D(H 0)the wave operators satisfy the so-called intertwining propertyH ±= ±H 0,while on H a.c.(H )∩D(H )we have thatH 0 −1±= −1±H .(6)The scattering operator S :L 2(R 3)→L 2(R 3)is given byS := −1+ −,D.Dürr,S.Goldstein,T.Moser,N.Zanghìwhile using the identity I ,the T -operator is given byT :=S −I .(7)If the system is asymptotically complete,the ranges of the wave operators are equal and thus S is unitary.Since the wave operator maps a scattering state onto its asymptotic state,the scattering operator maps the incoming asymptote ψin onto the corresponding out state ψout .The formula for the T -matrix,which holds in the L 2-sense,is given by (see e.g.,Theorem XI.42in [19]) T g (k )=−2πik =kT (k ,k ) g (k )k d ,(8)for g ∈S (R 3)(Schwartz space)such that g has support in a spherical shell.2T (k ,k )is given by (see e.g.,[19]):T (k ,k )=(2π)−3 e −i k ·x V (x )ϕ−(x ,k )d 3x ,(9)where ϕ−(as well as ϕ+)are eigenfunctions of H defined by Lemma 1below.Since the eigenfunctions ϕ±are bounded and continuous (cf.Lemma 2),we can conclude that T (k ,k )is bounded and continuous on R 3×R 3,if the potential is in (V )3.Then the formula (8)can be proved for g ∈S (R 3)without any restriction on the momentum support by the same method as in [19].We will need the time evolution of a state ψ∈H a.c.(H )with the Hamiltonian H .Its diagonalization on H a.c.(H )is given by the eigenfunctions ϕ±:(−12 +V (x ))ϕ±(x ,k )=k 22ϕ±(x ,k ).(10)Inverting (−12 −k 22)one obtains the Lippmann-Schwinger equation.We recall the main parts of a result on this due to Ikebe in [14]which is collected in the present formin [22].Proposition 1.Let V ∈(V )2.Then for any k ∈R 3\{0}there are unique solutions ϕ±(·,k ):R 3→C of the Lippmann-Schwinger equationsϕ±(x ,k )=e i k ·x −12π e ∓ik |x −x ||x −x |V (x )ϕ±(x ,k )d 3x ,(11)which satisfy the boundary conditions lim |x |→∞(ϕ±(x ,k )−e i k ·x )=0,which are also classical solutions of the stationary Schrödinger equation (10),and are such that:(i)For any f ∈L 2(R 3)the generalized Fourier transforms 3(F ±f )(k )=1(2π)32l .i .m . ϕ∗±(x ,k )f (x )d 3x exist in L 2(R 3).2In [19]Equation (8)was proven outside an “exceptional set”.For our class of potentials the “exceptional set”is empty.The additional factor 12in [19]comes from the different definition of H 0.3l .i .m . is a shorthand notation for s-lim R →∞ B R,where s-lim denotes the limit in the L 2-norm and B R a ball with radius R around the origin.A Microscopic Derivation of the Quantum Mechanical Formal Scattering Cross Section(ii)Ran(F ±)=L 2(R 3).Moreover F ±:H a.c.(H )→L 2(R 3)are unitary and the inverses of these unitaries are given by (F −1±f )(x )=1(2π)32l .i .m . ϕ±(x ,k )f (k )d 3k .(iii)For any f ∈L 2(R 3)the relations ±f =F −1±F f hold,where F is the ordinary Fourier transform given by (2).(iv)For any f ∈D (H )∩H a.c.(H )we have:H f (x )= F −1±k 22F ±f (x ),and therefore for any f ∈H a.c.(H ),e −i Ht f (x )= F −1±e −i k 22t F ±f (x ).In order to apply stationary phase methods we will need estimates on the derivatives of the generalized eigenfunctions:Proposition 2.Let V ∈(V )n for some n ≥3.Then:(i)ϕ±(x ,·)∈C n −2(R 3\{0})for all x ∈R 3and the partial derivatives 4∂αk ϕ±(x ,k ),|α|≤n −2,are continuous with respect to x and k .If,in addition,zero is neither an eigenvalue nor a resonance of H,then(ii)supx ∈R 3,k ∈R 3|ϕ±(x ,k )|<∞,for any αwith |α|≤n −2there is a c α<∞such that(iii)supk ∈R 3\{0}|κ|α|−1∂αk ϕ±(x ,k )|<c α x |α|,with κ:=k k ,and for any l ∈{1,...,n −2}there is a c l <∞such that (iv)sup k ∈R 3\{0}∂l ∂k l ϕ±(x ,k ) <c l x l ,where ∂∂k is the radial partial derivative in k -space.Remark 1.This proposition,except the assertion (iii),was proved in [22],Theorem 3.1.Assertion (iii)repairs a false statement in Theorem 3.1which did not include the nec-essary κ|α|−1factor,which we have in (iii).For |α|=1,which was the important case in that paper,there is however no difference.We have commented on the proof of this corrected version in [11].Remark 2.Zero is a resonance of H if there exists a solution f of H f =0such that x −γf ∈L 2(R 3)for any γ>12but not for γ=0.5The appearance of a zero eigenvalue or resonance can be regarded as an exceptional event:For a Hamiltonian H =H 0+cV ,c ∈R ,this can only happen for c in a discrete subset of R ,see [1],p.20and [15],p.589.As a simple consequence of Proposition 2we obtain4We use the usual multi-index notation:α=(α1,α2,α3),αi ∈N 0,∂αk f (k ):∂α1k 1∂α2k 2∂α3k 3f (k )and |α|:=α1+α2+α3.5There are various definitions,see e.g.[26],p.552,[1],p.20and [15],p.584.D.Dürr,S.Goldstein,T.Moser,N.ZanghìCorollary 1.Let V ∈(V )3and let zero be neither an eigenvalue nor a resonance of H.Then the T -matrix defined by (9)is a bounded and continuous function on R 3×R 3.Moreover,if V ∈(V )n ,for some n ≥3we have for all multi-indices αwith |α|≤n −3a constant c α>0such thatsup k ∈R 3,k ∈R 3\{0}κ|α|−1|∂αk T (k ,k )|≤c α.(12)With the regularity of the generalized eigenfunctions one can prove the flux-across-surfaces theorem.The quantum probability current density (=quantum flux density)is given byj ψt (x ):=−i 2(ψ∗t (x )∇ψt (x )−ψt (x )∇ψ∗t (x )).(13)For ψt (x )a solution of the Schrödinger equation we have the identity∂|ψt (x )|2∂t+div j ψt (x )=0,which has the form of a continuity equation.The flux-across-surfaces theorem can be naturally proven for the following class of wave functions (in the following definition we have the Fourier transform of ψout , ψout (k )= ϕ+(x ,k )ψ(x )d 3x (cf.Proposition1),in mind):Definition 2.A function f :R 3\{0}→C is in G +if there is a constant C ∈R +with:|f (k )|≤C k −15, ∂αk f (k ) ≤C k −6,|α|=1, κ∂αk f (k ) ≤C k −5,|α|=2,κ=k k , ∂2∂k 2f (k ) ≤C k −3.With this definition we haveProposition 3.(Flux-across-surfaces theorem (FAST)).Suppose V ∈(V )4and that zero is neither a resonance nor an eigenvalue of H.Suppose ψout (k )∈G +and let ψ= +ψout .Then ψt (x )=e −i Ht ψ(x )is continuously differentiable except at the singularities of V ,for any measurable set ⊆S 2and any T ∈R j ψt (x )·d σdt is absolutely integrable on R ×[T ,∞)for R sufficiently large andlim R →∞∞ TR j ψt (x )·d σdt =lim R →∞∞ T R j ψt (x )·d σ dt = C| ψout (k )|2d 3k ,(14)where R :={x ∈R 3:x =R ω,ω∈ },C :={k ∈R 3:k k ∈ }is the cone given by and d σis the outward-directed surface element on RS 2.The proof can be found in [11].The FAST plays a crucial role in the proof of our main results,Theorem 1and Theorem 2.Its importance for scattering theory was first pointed out in [6].A Microscopic Derivation of the Quantum Mechanical Formal Scattering Cross Section3.The Quantum Flux,Crossing Statistics and Bohmian MechanicsIn Bohmian mechanics,see [5],the particle has a position Q t that evolves via the equations d dt Q t =v ψt (Q t )=Im ∇ψt ψt(Q t ),i ∂∂t ψt (x )=H ψt (x ).(15)According to the quantum equilibrium hypothesis ([10],Born’s law),the positions of particles in an ensemble of particles each having wave function ψare always |ψ|2-dis-tributed.Note that if Q 0is |ψ0|2-distributed then Q t is |ψt |2-distributed.Under two assumptions we have the |ψ0|2almost-sure existence and uniqueness of the Bohmian dynamics:A 1.The initial wave function ψ0is normalized, ψ0 =1,and ψ0∈C ∞(H )=∞ n =1D (H n ).A 2.The potential V is in V 2and C ∞except,perhaps,at a finite number of singularities.(See Berndl et al.[4],Theorem 3.1and Corollary 3.2for the proof,as well as Theorem 3and Corollary 4in [23].The conditions in [4,23]are much more gen-eral.In our context,however,we have to restrict to the case where V ∈(V )2.)Hence,depending on the initial position q 0∈ 0,where 0is the set of “good”points,the particle has the trajectory Q ψt (q 0).On the set of “good”points,ψ0(x )is different from zero and is differentiable.The complement R 3\ 0of 0has measure 0(with respect to |ψ0|2).Given a trajectory Q ψt (q 0),q 0∈ 0,we can define the number of crossings in a natural way.For the surface R ⊂RS 2with unit and normal vector n (x )=x x ,x ∈R we define N ψ+(R )on 0by:N ψ+(R )(q 0):= t ≥0|Q ψt (q 0)∈R and ˙Q ψt (q 0)·n Q ψt (q 0) >0 ,(16)the number of crossings of the trajectory Q ψt (q 0)through R in the direction of the orientation in the time interval [0,∞)(“problematical crossings”where the velocity is “orthogonal”to the orientation of R have measure zero and need not concern us,see [3],p.28-34).If N ψ+(R )(q 0)≥1,we can define t R exit as the time when the particle crosses the surface R in the positive direction for the first time:t R exit (q 0):=min t ≥0|Q ψt (q 0)∈R and ˙Q ψt (q 0)·n Q ψt (q 0) >0 .(17)In the case that the particle does not cross the surface in the positive direction,we sett R exit(q 0):=∞,if N ψ+(R )(q 0)=0.(18)Analogously to (16)we have N ψ−(R ),the number of crossings in the opposite direc-tion.For convenience we define N ψ+(R )and N ψ−(R )on the whole of R 3by settingD.Dürr,S.Goldstein,T.Moser,N.ZanghìNψ+(R )=Nψ−(R )=0for all q0∈R3\ 0.Then we can define the number of signed crossings on R3byNψsig(R ):=Nψ+(R )−Nψ−(R ).(19) The total number of crossings defined on R3is thenNψtot(R ):=Nψ+(R )+Nψ−(R ).(20) These quantities are random variables on the space R3of initial conditions,see[3], Lemma4.2.The expectation values of Nψsig(R )and Nψtot(R )are given byflux inte-grals and arefinite,see Proposition4below.This means that Nψsig(R )and Nψtot(R ) are almost surelyfinite.Before we give a precise statement we argue heuristically for the connection between the quantumflux and the expectation values.For a particle to cross an infinitesimal surface dσ:=n dσin a time interval[t,t+dt),it must be at time t in the appropriate cylinder of size|vψt(x)·dσdt|.The probability is therefore|ψt(x)|2|vψt(x)·dσdt|=|jψt(x)·dσ|dt.Because the intervals are infinitesimal,we have for Nψsig(dt,dσ)∈{−1,0,1},6where the sign will be the same as that of j·dσ.Therefore E(Nψsig(dt,dσ))=jψt(x)·dσdt and integration over R and[0,∞)yields(21).The precise statement is: Proposition4.Let A1and A2be satisfied.In addition suppose that the conditions of Proposition3are satisfied.Then for sufficiently large R the expectation values of Nψsig(R )and Nψtot(R )arefinite andE(Nψsig(R ))=∞Rjψt(x)·dσdt,(21)E(Nψtot(R ))=∞R|jψt(x)·dσ|dt.(22)The proof of Proposition4can be found in[3],pp.34–37,and under slightly different conditions in[24].The results in the references hold under more general conditions on the surfaces.Consider now a scattering situation where we want to calculate the number offirst crossings.The detector corresponds to the surface R :={x∈R3:x=Rω,ω∈ ⊂S2}⊂RS2.Then we define Nψdet([0,∞),R, )to be equal to one if the parti-cle with the wave functionψ0=ψis“detected”in[0,∞)and zero otherwise.More precisely,Nψdet(R, ):R3→{0,1},6Nψsig(dt,dσ)is the number of signed crossings in the time interval[t,t+dt)through the surface dσ.A Microscopic Derivation of the Quantum Mechanical Formal Scattering Cross SectionN ψdet (R , )(q 0):=⎧⎨⎩1,if q 0≤R ,t RS 2exit <∞and Q ψt RS 2exit (q 0)∈R ,0otherwise .(23)The definition is motivated by the idea that particles are detected when they cross the boundary RS 2for the first ing the fact that RS 2is closed we can estimate N ψdet (R , )−N ψsig (R ) ≤N ψ−(RS 2)so that by the triangle inequality E (N ψdet (R , ))−E (N ψsig (R )) ≤E (N ψ−(RS 2)).(24)With (19),(20)and Proposition 4we obtain for the right-hand side of (24),E (N ψ−(RS 2))=12E N ψtot (RS 2)−N ψsig (RS 2) =12∞ 0 RS 2 |j ψt (x )·d σ|−j ψt (x )·d σ dt .(25)If j ψt (x )·d σ≥0for all d σ∈RS 2and t >0then we have by (24)and (25)that E (N ψsig (R ))=E (N ψdet (R )).In general j ψt (x )·d σdoes not have to be positive,but the flux-across-surfaces theorem (Proposition 3)ensures that the flux is asymptotically outwards.Thus we can estimate the difference between E (N ψsig (R ))and E (N ψdet (R ))for all ψwhich satisfy the flux-across-surfaces theorem using (24)and (25),E (N ψsig (R ))−E (N ψdet (R , )) ≤12∞ 0 RS 2|j ψt (x )·d σ|−j ψt (x )·d σ dt →R →∞0.(26)In particular under the hypotheses of Proposition 3and the general assumptions A1and A2we obtain asymptotic equality between the expectation values E (N ψdet (R , ))and E (N ψsig (R )).4.A Model for the BeamIn a scattering situation a beam of particles is scattered off a target.We now wish to focus on the beam.We take the beam to be produced by a particle source located in the plane Y L perpendicular to the x 3-axis:Y L :={−L e 3+a |a ⊥e 3},L >0.The particles are created with wave functions ψ∈H a.c.translated to the plane Y L .Calling ψy the translation of ψby y ,the “centers”of the translated wave functions,with which we are concerned,are located aty =y 1e 1+y 2e 2−L e 3∈Y Land are uniformly distributed in a bounded region A ⊂Y L with area |A |.We call A the beam profile.The momentum distribution of the wave function is concentrated around the momentum k 0 e 3.D.Dürr,S.Goldstein,T.Moser,N.ZanghìRemark3.This model of a beam,in which the particles have random impact parameters and are scattered off a single target“particle,”is equivalent to the more realistic descrip-tion of the scattering situation,in which all the target particles are randomly distributed (e.g.,in a foil)and the incoming particles have the very same impact parameter,provided coherent and multiple-scattering effects are neglected(see e.g.[17],p.214).The translated wave functionψy of a wave functionψ∈H a.c.will not in general be in H a.c.,but can have a part in H p.p..This is problematical for the application of our general results(see Sect.9).To avoid this difficulty,we assume:A3.The Hamiltonian H=−12+V has no bound states,i.e.H p.p.={0}.Thenψy∈H a.c.,∀y∈R3.We specify now more precisely the model for the beam,which has been already men-tioned in[9].The particles are created with wave functionsψat random times t∈R+ and where the wave function of a particle is shifted randomly by the uniformly distrib-uted“impact parameter”y∈A,the“center”of the wave function at the moment of emission.In Bohmian mechanics the initial position q∈R3of the particle determines its trajectory.The initial position is|ψy|2-distributed.We shall not need many stochastic details about the beam.The reader may think of a Poisson point process with points in=R+×A×R3,with a pointλ=(t,y,q)∈ representing a particle with wave functionψy(x)≡ψ(x−y),y∈A(27)emitted at the time t∈R+and with initial position q∈R3.We shall consider a general point process( ,F,P)built on( ,B( ),µ),whereλ ∈ represents a configura-tion of countably many points in ,i.e.λ ={λ},λ∈ ,λ countable.For the number of pointsχ B(λ )≡λ∈λχB(λ)in a set B∈B( ),whereχB is the indicator function of the set B,we have thatEχ B=µ(B),(28)where the intensity measureµon B( )is given bydµ=|ψ(x−y)|2χA(y)dtd2yd3x.(29) Remark4.For a Poisson process we would have,in addition to(28),thatPχ B=k=exp(−µ(B))µ(B)kk!(30)as well as the independence ofχ A andχ B,for A∩B=∅,A,B∈B( ).We shall assume that the point process is ergodic in the following sense:For any B∈B( )letB(τ):={(t,y,q)∈B|t∈[0,τ)}.(31) Then for any >0,lim τ→∞Pχ B(τ)τ−Eχ B(τ)τ≥=0,(32)with Eχ B(τ)given by(28).Remark5.Because of the independence property(cf.Remark4),(32)holds for the case of a Poisson process.Remark6.The point process has unit density in the following sense:Let C⊂A,τ>0 and B:=[0,τ)×C×R3be given.Then with(32)for any >0,lim τ→∞Pχ B−Eχ B≥=0,(33)andEχ B(τ)|C|τ=1|C|τµ(B)=1.(34)5.The Definition of the Scattering Cross SectionWe shall now start to define N (τ,R,A,L,ψ, ),the number of detected particles. To simplify the notation we do not always indicate the dependence of N on A,L andψ.Sometimes we will also suppress the dependence on R and .We definefirst N det(τ,R, )for a single particle corresponding toλ=(t,y,q)byN det(τ,R,ψ, ): →{0,1},N det(τ,R,ψ, )(λ):=χ[0,τ)(t)Nψy det(R, )(q),(35)where Nψy det(R, )(q)is defined by(23).The characteristic function ensures that no particle is counted which is emitted after the timeτ.Note thatψy must satisfy condition A1(Sect.3)to ensure that Nψy det(R, )(q)is well defined.ThenN (τ,R,A,L,ψ, ): →N0,N (τ,R,A,L,ψ, )(λ )=λ∈λN det(τ,R,ψ, )(λ).(36)The empirical scattering cross sectionσemp( )for the solid angle is the random variable7σemp( ):=N (τ,R,A,L,ψ, )τ,(37)which by the law of large numbers(for the Poisson case and by the ergodicity assumption (32)for the general case)should approximate for largeτin P-probability its correspond-ing P-expectation value.The expected value of(37)is then the theoretically predicted cross section.This theoretically predicted cross section involves a very complicated formula which is not very explicit,cf.(47)and Remark7.It depends of course on the detection directions ,the potential V and the approximate momentum k0of the parti-cles in the beam,but depends also on the other details of the experimental setup such as R,A,L and the detailed specification ofψ.By taking the scaling limit described in the next section,we shall arrive at(1),which does not depend on these additional details.6.The Scaling of the ParametersAccording to the usual asymptotic picture of scattering theory where the particles are prepared long before and are detected long after the scattering event has occurred,the preparation and detection should be far away from the scattering center.That means the limits R→∞and L→∞have to be taken.However,increasing L has the (undesirable)effect of an increased spreading of the beam,which reduces the beam intensity in the scattering region.To maintain the beam intensity in the scattering region we must widen the beam profile A as L→∞.The idealization of an incoming plane wave corresponds to particles with a narrow distribution in momentum space,i.e.,to a limit in which the Fourier transform of the initial wave function becomes more and more concentrated around afixed initial wave vector k0.For a detailed discussion of the scattering regime see[8].The limits for the parameters L,A,andψwill be combined by simultaneously scaling them using a small parameter :We introduce L ,A andψ ,whose precise dependence on will be given below,and consider the cross section corresponding to (37),depending on ,R,τ,σ emp( )=N (τ,R,A ,L ,ψ , )τ,(38)to which the limit →0is to be applied.However,the limit R→∞is taken before we take →0;this is because we must have that the diameter of the beam profile A is much smaller than R,since otherwise un-scattered particles will often contribute to what should be the cross section for scattered particles.For convenience,wefirst take the limitτ→∞,required for the stabilization of the empirical cross section produced by the law of large numbers.We are thus led to consider a limit for the cross section of the formσ( )=lim→0limR→∞limτ→∞σ emp( ).(39)7We shall ignore the dimension factor[unit area·unit time]which comes from the normalization of(37) by the unit density1[unit area·unit time]of the underlying point process,cf.Remark6.One can also normalize by the beam density,i.e.with the number of detected particles(by a detector in the beam with a surface perpendicular to the beam axis)per unit time and unit area,in front of the target.In the scattering regime,i.e. if the parameters are suitably scaled(cf.Section6),the beam will have unit density in front of the target.We shall not elaborate on this further in this paper,see however[8].The precise definition of L ,A andψ ,used in our main results,is the following:ψ (x)= 32e i k0·xψ( x),(40)with the Fourier transformψ (k)= −32 ψk−k0.(41)The particle source is located on Y L ,withL =Ll,l>2.(42)For the beam profile A ⊂Y L we take the circular regionA ={x∈R3|x21+x22<D2and x3=L }(43)with the beam diameter D given byD =D,d>2l−3.(44)(One might be inclined to consider a scattering experiment in which the diameter of the beam is much smaller than the distance of the particle source from the scattering center. Indeed,if2<l<3,d<l is consistent with(44).Hence,such a scenario is covered by our results.)7.The Scattering Cross Section TheoremWe can now formulate our main results.Our basic assumptions are that V∈(V)5(Defi-nition1),A2(Sect.3),A3(no bound states,Sect.4)and hat for all small enough ψ y is“good”for all y∈A in the sense that it satisfies A1(Sect.3)as well as thecondition for the FAST(Prop.3).Moreover,we need to assume that the potential has no zero energy resonances.However,instead of invoking the implicit condition onψthat theψ y are“good,”we impose stronger but more explicit conditions onψ,namely thatψ∈C∞0(R3)(Theorem2)orψ∈S(Theorem1),with corresponding additional conditions on the potential(Definitions4and3,respectively).Definition3.V is in V if(i)the Hamiltonian H=−12 +V has no bound states,i.e.H p.p.={0},(ii)the Hamiltonian H=−12 +V has no zero energy resonances,(iii)V is a C∞-function on R3,(iv)V and its derivatives of all orders are uniformly bounded in x:For all multi-indices αthere exist an Mα<∞such that|∂αx V(x)|<Mαfor all x∈R3,(v)there exist positive numbersδand C such that|V(x)|≤C x −5−δfor all x∈R3.。