Address for correspondence
写信有什么规定吗英语作文
写信有什么规定吗英语作文写信的规定在不同的情境下可能会有所不同，比如正式的公函、私人信件或是电子邮件等等。
下面是一个例子，你可以根据这个例子进行仿写：Title: Regulations on Writing Letters。
In this digital age where instant messaging and emails dominate communication, the art of letter writing might seem to have lost its significance. However, despite the prevalence of electronic communication, there are still regulations and etiquettes to be followed when composing letters, whether they are formal or informal.Firstly, when writing a formal letter, it is crucial to include the sender's address, date, recipient's address, salutation, body, closing, and signature. These components establish the professionalism and credibility of the correspondence. The sender's address should be positionedat the top right corner of the page, followed by the date.The recipient's address should be aligned with the left margin, followed by the salutation, such as "Dear Mr./Ms. [Last Name]," or "To Whom It May Concern," if therecipient's name is unknown.Secondly, the body of the letter should be organized logically and coherently. It should address the purpose of the correspondence concisely and respectfully. Whether itis a business inquiry, a formal complaint, or a job application, the language used should be clear, polite, and professional. It is advisable to avoid using slang, abbreviations, or overly casual language in formal letters.Furthermore, the closing of the letter should reflect the tone and purpose of the communication. Common closings include "Sincerely," "Yours faithfully," or "Best regards," followed by the sender's signature. The signature should be handwritten for formal letters to add a personal touch and authenticity to the correspondence.In contrast, informal letters allow for greater flexibility and creativity in expression. While stilladhering to basic letter-writing conventions, informal letters often include more personal anecdotes, emotions, and colloquial language. They may lack the rigid structure of formal letters but should still maintain clarity and coherence in communication.Additionally, with the advent of electronic communication, the rules for writing emails have emerged as a hybrid of traditional letter-writing etiquette and modern digital norms. Similar to formal letters, emails should include a clear subject line, salutation, body, closing, and signature. However, emails offer the advantage of instant delivery and accessibility, making them a convenient choice for both personal and professional correspondence.In conclusion, while the modes of communication may evolve with time, the regulations for writing letters remain relevant in conveying messages effectively and respectfully. Whether it's a formal letter on official letterhead or a heartfelt note to a friend, understanding and adhering to these regulations ensures that the intendedmessage is conveyed with clarity, professionalism, and sincerity.。
tms320vc5416数据手册
TMS320VC5416Fixed-Point Digital Signal Processor Data ManualPRODUCTION DATA information is current as of publication date.Products conform to specifications per the terms of the TexasInstruments standard warranty.Production processing does notnecessarily include testing of all parameters.Literature Number:SPRS095PMarch1999–Revised October2008Revision HistoryTMS320VC5416Fixed-Point Digital Signal ProcessorSPRS095P–MARCH 1999–REVISED OCTOBER 2008NOTE:Page numbers for previous revisions may differ from page numbers in the current version.This data sheet revision history highlights the technical changes made to the SPRS095O device-specific data sheet to make it an SPRS095P revision.Scope:This document has been reviewed for technical accuracy;the technical content is up-to-date as of the specified release date with the following corrections.2Revision History Submit Documentation FeedbackContentsTMS320VC5416Fixed-Point Digital Signal ProcessorSPRS095P–MARCH 1999–REVISED OCTOBER 2008Revision History ...........................................................................................................................1TMS320VC5416Features.......................................................................................................2Introduction.......................................................................................................................2.1Description ..................................................................................................................2.2PinAssignments............................................................................................................2.2.1TerminalAssignments forthe GGUPackage...............................................................2.2.2Pin AssignmentsforthePGEPackage......................................................................2.2.3Signal Descriptions ..............................................................................................3Functional Overview ...........................................................................................................3.1Memory ......................................................................................................................3.1.1Data Memory .....................................................................................................3.1.2Program Memory ................................................................................................3.1.3Extended Program Memory ...................................................................................3.2On-Chip ROM With Bootloader ...........................................................................................3.3On-Chip RAM ...............................................................................................................3.4On-Chip Memory Security .................................................................................................3.5Memory Map ................................................................................................................3.5.1Relocatable Interrupt Vector Table ............................................................................3.6On-Chip Peripherals .......................................................................................................3.6.1Software-Programmable Wait-State Generator .............................................................3.6.2Programmable Bank-Switching ................................................................................3.6.3Bus Holders ......................................................................................................3.7Parallel I/O Ports ...........................................................................................................3.7.1Enhanced 8-/16-Bit Host-Port Interface (HPI8/16)..........................................................3.7.2HPI Nonmultiplexed Mode ......................................................................................3.8Multichannel Buffered Serial Ports (McBSPs)..........................................................................3.9Hardware Timer ............................................................................................................3.10Clock Generator ............................................................................................................3.11Enhanced External Parallel Interface (XIO2)...........................................................................3.12DMA Controller .............................................................................................................3.12.1Features ..........................................................................................................3.12.2DMA External Access ...........................................................................................3.12.3DMA Memory Maps .............................................................................................3.12.4DMA Priority Level ...............................................................................................3.12.5DMA Source/Destination Address Modification .............................................................3.12.6DMA in Autoinitialization Mode ................................................................................3.12.7DMA Transfer Counting .........................................................................................3.12.8DMA Transfer in Doubleword Mode ..........................................................................3.12.9DMA Channel Index Registers .................................................................................3.12.10DMA Interrupts ..................................................................................................3.12.11DMA Controller Synchronization Events .....................................................................3.13General-Purpose I/O Pins .................................................................................................3.13.1McBSP Pins as General-Purpose I/O .........................................................................3.13.2HPI Data Pins as General-Purpose I/O ......................................................................3.14Device ID Register .........................................................................................................3.15Memory-Mapped Registers ...............................................................................................3.16McBSP Control Registers and Subaddresses ..........................................................................3.17DMA Subbank Addressed Registers ....................................................................................3.18Interrupts ....................................................................................................................4Support .............................................................................................................................Contents3TMS320VC5416Fixed-Point Digital Signal ProcessorSPRS095P–MARCH1999–REVISED 4.1Documentation Support...................................................................................................4.2Device and Development-Support Tool Nomenclature................................................................5Electrical Specifications......................................................................................................5.1Absolute Maximum Ratings...............................................................................................5.2Recommended Operating Conditions...................................................................................5.3Electrical Characteristics.................................................................................................5.3.1Test Loading.....................................................................................................5.3.2Timing Parameter Symbology............................................................................................5.3.3Internal Oscillator With External Crystal.................................................................................5.4Clock Options...............................................................................................................5.4.1Divide-By-Two and Divide-By-Four Clock Options..........................................................5.4.2Multiply-By-N Clock Option(PLL Enabled)...................................................................5.5Memory and Parallel I/O Interface Timing..............................................................................5.5.1Memory Read....................................................................................................5.5.2Memory Write....................................................................................................5.5.3I/O Read..........................................................................................................5.5.4I/O Write..........................................................................................................5.5.5Ready Timing for Externally Generated Wait States..................................................................5.5.6and Timings...............................................................................................5.5.7Reset,BIO,Interrupt,and MP/MC Timings.............................................................................5.5.8Instruction Acquisition and Interrupt Acknowledge Timings..........................................5.5.9External Flag(XF)and TOUT Timings..................................................................................5.5.10Multichannel Buffered Serial Port(McBSP)Timing...................................................................5.5.10.1McBSP Transmit and Receive Timings....................................................................5.5.10.2McBSP General-Purpose I/O Timing.......................................................................5.5.10.3McBSP as SPI Master or Slave Timing....................................................................5.5.11Host-Port Interface Timing...............................................................................................5.5.11.1HPI8Mode.....................................................................................................5.5.11.2HPI16Mode....................................................................................................6Mechanical Data.................................................................................................................6.1Package Thermal Resistance Characteristics..........................................................................4Contents Submit Documentation FeedbackTMS320VC5416Fixed-Point Digital Signal Processor SPRS095P–MARCH1999–REVISED OCTOBER2008List of Figures2-1144-Ball GGU MicroStar BGA™(Bottom View).............................................................................2-2144-Pin PGE Low-Profile Quad Flatpack(Top View).......................................................................3-1TMS320VC5416Functional Block Diagram..................................................................................3-2Program and Data Memory Map................................................................................................3-3Extended Program Memory Map...............................................................................................3-4Process Mode Status Register..................................................................................................3-5Software Wait-State Register(SWWSR)[Memory-Mapped Register(MMR)Address0028h].........................3-6Software Wait-State Register(SWWSR)[Memory-Mapped Register(MMR)Address0028h].........................3-7Bank-Switching Control Register BSCR)[MMR Address0029h]...........................................................3-8Host-Port Interface—Nonmulltiplexed Mode.................................................................................3-9HPI Memory Map.................................................................................................................3-10Multichannel Control Register(MCR1).........................................................................................3-11Multichannel Control Register(MCR2).........................................................................................3-12Pin Control Register(PCR)......................................................................................................3-13Nonconsecutive Memory Read and I/O Read Bus Sequence.............................................................3-14Consecutive Memory Read Bus Sequence(n=3reads)..................................................................3-15Memory Write and I/O Write Bus Sequence.................................................................................3-16DMA Transfer Mode Control Register(DMMCRn)...........................................................................3-17On-Chip DMA Memory Map for Program Space(DLAXS=0and SLAXS=0).........................................3-18On-Chip DMA Memory Map for Data and IO Space(DLAXS=0and SLAXS=0)....................................3-19DMPREC Register................................................................................................................3-20General-Purpose I/O Control Register(GPIOCR)[MMR Address003Ch]................................................3-21General-Purpose I/O Status Register(GPIOSR)[MMR Address003Dh].................................................3-22Device ID Register(CSIDR)[MMR Address003Eh].........................................................................3-23IFR and IMR Registers...........................................................................................................5-1Tester Pin Electronics............................................................................................................5-2Internal Divide-By-Two Clock Option With External Crystal...............................................................5-3External Divide-By-Two Clock Timing.........................................................................................5-4Multiply-By-One Clock Timing..................................................................................................5-5Nonconsecutive Mode Memory Reads.......................................................................................5-6Consecutive Mode Memory Reads............................................................................................5-7Memory Write(MSTRB=0)....................................................................................................5-8Parallel I/O Port Read(IOSTRB=0).........................................................................................5-9Parallel I/O Port Write(IOSTRB=0)..........................................................................................5-10Memory Read With Externally Generated Wait States.....................................................................5-11Memory Write With Externally Generated Wait States.....................................................................5-12I/O Read With Externally Generated Wait States...........................................................................5-13I/O Write With Externally Generated Wait States...........................................................................5-14HOLD and HOLDA Timings(HM=1).........................................................................................List of Figures5TMS320VC5416Fixed-Point Digital Signal ProcessorSPRS095P–MARCH1999–REVISED 5-15Reset and BIO Timings.........................................................................................................5-16Interrupt Timing..................................................................................................................5-17MP/MC Timing...................................................................................................................5-18Instruction Acquisition(IAQ)and Interrupt Acknowledge(IACK)Timings................................................5-19External Flag(XF)Timing......................................................................................................5-20TOUT Timing.....................................................................................................................5-21McBSP Receive Timings.......................................................................................................5-22McBSP Transmit Timings.......................................................................................................5-23McBSP General-Purpose I/O Timings........................................................................................5-24McBSP Timing as SPI Master or Slave:CLKSTP=10b,CLKXP=0....................................................5-25McBSP Timing as SPI Master or Slave:CLKSTP=11b,CLKXP=0....................................................5-26McBSP Timing as SPI Master or Slave:CLKSTP=10b,CLKXP=1....................................................5-27McBSP Timing as SPI Master or Slave:CLKSTP=11b,CLKXP=1....................................................5-28Using HDS to Control Accesses(HCS Always Low)........................................................................5-29Using HCS to Control Accesses...............................................................................................5-30HINT Timing......................................................................................................................5-31GPIOx Timings...................................................................................................................5-32Nonmultiplexed Read Timings.................................................................................................5-33Nonmultiplexed Write Timings.................................................................................................5-34HRDY Relative to CLKOUT....................................................................................................6List of Figures Submit Documentation FeedbackTMS320VC5416Fixed-Point Digital Signal Processor SPRS095P–MARCH1999–REVISED OCTOBER2008List of Tables2-1Terminal Assignments for the TMS320VC5416GGU(144-Pin BGA Package).........................................2-2Signal Descriptions...............................................................................................................3-1Standard On-Chip ROM Layout...............................................................................................3-2Processor Mode Status(PMST)Register Bit Fields........................................................................3-3Software Wait-State Register(SWWSR)Bit Fields.........................................................................3-4Software Wait-State Control Register(SWCR)Bit Fields..................................................................3-5Bank-Switching Control Register(BSCR)Fields..............................................................................3-6Bus Holder Control Bits..........................................................................................................3-7Sample Rate Input Clock Selection...........................................................................................3-8Clock Mode Settings at Reset.................................................................................................3-9DMD Section of the DMMCRn Register......................................................................................3-10DMA Reload Register Selection...............................................................................................3-11DMA Interrupts...................................................................................................................3-12DMA Synchronization Events..................................................................................................3-13DMA Channel Interrupt Selection..............................................................................................3-14Device ID Register(CSIDR)Bits................................................................................................3-15CPU Memory-Mapped Registers................................................................................................3-16Peripheral Memory-Mapped Registers for Each DSP Subsystem........................................................3-17McBSP Control Registers and Subaddresses.................................................................................3-18DMA Subbank Addressed Registers...........................................................................................3-19Interrupt Locations and Priorities................................................................................................5-1Input Clock Frequency Characteristics.........................................................................................5-2Clock Mode Pin Settings for the Divide-By-2and By Divide-By-4Clock Options.......................................5-3Divide-By-2and Divide-By-4Clock Options Timing Requirements.......................................................5-4Divide-By-2and Divide-By-4Clock Options Switching Characteristics...................................................5-5Multiply-By-N Clock Option Timing Requirements..........................................................................5-6Multiply-By-N Clock Option Switching Characteristics......................................................................5-7Memory Read Timing Requirements..........................................................................................5-8Memory Read Switching Characteristics.....................................................................................5-9Memory Write Switching Characteristics.....................................................................................5-10I/O Read Timing Requirements................................................................................................5-11I/O Read Switching Characteristics...........................................................................................5-12I/O Write Switching Characteristics............................................................................................5-13Ready Timing Requirements for Externally Generated Wait States......................................................5-14Ready Switching Characteristics for Externally Generated Wait States..................................................5-15HOLD and HOLDA Timing Requirements....................................................................................5-16HOLD and HOLDA Switching Characteristics...............................................................................5-17Reset,BIO,Interrupt,and MP/MC Timing Requirements..................................................................5-18Instruction Acquisition(IAQ)and Interrupt Acknowledge(IACK)Switching Characteristics...........................List of Tables7TMS320VC5416Fixed-Point Digital Signal ProcessorSPRS095P–MARCH1999–REVISED 5-19External Flag(XF)and TOUT Switching Characteristics...................................................................5-20McBSP Transmit and Receive Timing Requirements.......................................................................5-21McBSP Transmit and Receive Switching Characteristics..................................................................5-22McBSP General-Purpose I/O Timing Requirements........................................................................5-23McBSP General-Purpose I/O Switching Characteristics...................................................................5-24McBSP as SPI Master or Slave Timing Requirements(CLKSTP=10b,CLKXP=0).................................5-25McBSP as SPI Master or Slave Switching Characteristics(CLKSTP=10b,CLKXP=0).............................5-26McBSP as SPI Master or Slave Timing Requirements(CLKSTP=11b,CLKXP=0).................................5-27McBSP as SPI Master or Slave Switching Characteristics(CLKSTP=11b,CLKXP=0).............................5-28McBSP as SPI Master or Slave Timing Requirements(CLKSTP=10b,CLKXP=1).................................5-29McBSP as SPI Master or Slave Switching Characteristics(CLKSTP=10b,CLKXP=1).............................5-30McBSP as SPI Master or Slave Timing Requirements(CLKSTP=11b,CLKXP=1).................................5-31McBSP as SPI Master or Slave Switching Characteristics(CLKSTP=11b,CLKXP=1).............................5-32HPI8Mode Timing Requirements.............................................................................................5-33HPI8Mode Switching Characteristics..........................................................................................5-34HPI16Mode Timing Requirements............................................................................................5-35HPI16Mode Switching Characteristics.......................................................................................6-1Thermal Resistance Characteristics............................................................................................8Submit Documentation Feedback List of Tables1TMS320VC5416FeaturesTMS320VC5416 Fixed-Point Digital Signal Processor SPRS095P–MARCH1999–REVISED OCTOBER2008Reads•Advanced Multibus Architecture With ThreeSeparate16-Bit Data Memory Buses and One•Arithmetic Instructions With Parallel Store and Program Memory Bus Parallel Load•40-Bit Arithmetic Logic Unit(ALU)Including a•Conditional Store Instructions40-Bit Barrel Shifter and Two Independent•Fast Return From Interrupt 40-Bit Accumulators•On-Chip Peripherals•17-×17-Bit Parallel Multiplier Coupled to a–Software-Programmable Wait-State 40-Bit Dedicated Adder for Non-Pipelined Generator and ProgrammableSingle-Cycle Multiply/Accumulate(MAC)Bank-SwitchingOperation–On-Chip Programmable Phase-Locked •Compare,Select,and Store Unit(CSSU)for the Loop(PLL)Clock Generator With External Add/Compare Selection of the Viterbi Operator Clock Source–One16-Bit Timer•Exponent Encoder to Compute an Exponent–Six-Channel Direct Memory Access(DMA) Value of a40-Bit Accumulator Value in aControllerSingle Cycle–Three Multichannel Buffered Serial Ports •Two Address Generators With Eight Auxiliary(McBSPs)Registers and Two Auxiliary Register–8/16-Bit Enhanced Parallel Host-Port Arithmetic Units(ARAUs)Interface(HPI8/16)•Data Bus With a Bus Holder Feature•Power Consumption Control With IDLE1,•Extended Addressing Mode for8M×16-Bit IDLE2,and IDLE3Instructions With Maximum Addressable External ProgramPower-Down ModesSpace•CLKOUT Off Control to Disable CLKOUT •128K×16-Bit On-Chip RAM Composed of:•On-Chip Scan-Based Emulation Logic,IEEE –Eight Blocks of8K×16-Bit On-ChipStd1149.1(JTAG)Boundary Scan Logic(1) Dual-Access Program/Data RAM•144-Pin Ball Grid Array(BGA)(GGU Suffix)–Eight Blocks of8K×16-Bit On-ChipSingle-Access Program RAM•144-Pin Low-Profile Quad Flatpack(LQFP)(PGE Suffix)•16K×16-Bit On-Chip ROM Configured forProgram Memory• 6.25-ns Single-Cycle Fixed-Point InstructionExecution Time(160MIPS)•Enhanced External Parallel Interface(XIO2)•8.33-ns Single-Cycle Fixed-Point Instruction •Single-Instruction-Repeat and Block-RepeatExecution Time(120MIPS) Operations for Program Code• 3.3-V I/O Supply Voltage(160and120MIPS)•Block-Memory-Move Instructions for BetterProgram and Data Management• 1.6-V Core Supply Voltage(160MIPS)•Instructions With a32-Bit Long Word Operand• 1.5-V Core Supply Voltage(120MIPS)(1)IEEE Standard1149.1-1990Standard-Test-Access Port and •Instructions With Two-or Three-OperandBoundary Scan ArchitectureTMS320C54x,TMS320are trademarks of Texas Instruments.All other trademarks are the property of their respective owners.PRODUCTION DATA information is current as of publication date.Copyright©1999–2008,Texas Instruments Incorporated Products conform to specifications per the terms of the TexasInstruments standard warranty.Production processing does notnecessarily include testing of all parameters.。
Correspondence Address
ŸComputer aided three dimensional reconstruction course,March 7-8, 2003, Hacettepe University, Ankara, Turkey Published online 28 April, 2003 © Neuroanatomy, 2003, Volume 2, Pages 20-21.Deniz Demiryurek Department of Anatomy, Faculty of Medicine,University of HacettepeCorrespondence Address Deniz Demiryurek, MD, PhD Department of Anatomy Hacettepe University Faculty of Medicine 06100, Ankara, Turkey Phone: +90 312 305 23 59Fax: +90 312 310 71 69E-mail: mdeniz@.trReceived 4 April 2003One of the most ancient of sciences, anatomy has evolved over many centuries. Its methods have progressively encompassed dissection instruments, manual illustration,stains, microscopes, cameras and photography, and digital imaging systems. Like many other more modern scientific disciplines in the late 20th century, anatomy has also benefited from the revolutionary development of digital computers and their automated information management and analytical capabilities. By using newer methods of computer and information sciences, anatomists have made outstanding contributions to science, medicine, and education. In that regard, there is a strong rationale for recognizing anatomical informatics as a proper subdiscipline of anatomy. A high-level survey of the field reveals important anatomical applications of computer sciences methods in imaging, image processing and visualization, virtual reality, modeling and simulation, structural database processing, networking, and artificial intelligence [1].Within this framework, computer aided three dimensional (3D) reconstruction course was held on March 7 and 8, 2003 at Department of Anatomy, Faculty of Medicine,Hacettepe University as a part of continuing medical education activities. The course coordinators were Ruhgun Basar and M. Mustafa Aldur. The goal of this course was to inform researchers about the basic principles of 3D reconstruction and its wide range usage in neuroanatomy; and to provide them an opportunity for making practice with Surfdriver software. 30 participants from anatomists, dentists, engineers and students attended the course.Ruhgun Basar started and chaired the plenary session on the first morning by welcoming the attendees. The first presentation by H. Hamdi Celik was on the history of three dimensional reconstruction. He summerized the detailed and very interesting history of 3D reconstruction since Leonardo Da Vinci up today including its story in our country. Following M. Mustafa Aldur presented the basic principles in 3D recontruction and possible problems that can be rised during performing reconstructions. He mentioned the importance of tracing contours, obtaining wireframe images, surface rendering;and explained how to correct misalignments and rotational problems. The third presentation by Alp Bayramoglu was on the computer softwares used for performing 3D reconstructions. He gave an excellent overview about the softwares including their fields of use and prices. In the following presentation, Selcuk Surucu described that a space image with true spatial perception could only be conveyed with two lenses and imitating the eyes; and this is called streoscopy. Additionally he demonstrated many neuroanatomical samples with and without streoscopic efects. During the session Iskender Sayek, Dean of Faculty of Medicine, made a surprise visit and congratulated the organising committe with a meaningfull plaque.After a fifteen minute coffee break the second part of the plenary session started with the presentation by Mustafa F. Sargon on the 3D reconstruction of semi-thin and thin serial sections. He gave detailed information about the reconstruction processes with semi-thin and thin sections obtained for light, transmission electron and comfocal microscopy. The sixth presentation by Deniz Demiryurek was on The Visible Human Project by National Library of Medicine (NLM). He reviewed the project’s history,its important role in providing a unique and important computerized database of the human body and being an international platform for general use as well as for research in many fields including neuroanatomy [2-6]. The following talks by Bulent Ozdemir,Ilkan Tatar, Samet Kapakin and Selcuk Tunali reported briefly the literature about computer aided 3D reconstruction and the fields of use of anaglyph technique. The last presentation of the plenary session by M. Mustafa Aldur was about SURFdriver 3.5, the surface reconstruction programme. He adressed SURFdriver software [7] as a powerfull tool for developing detailed morphological reconstructions of neuroanatomical features using sequential image slices through the structure. During the lunch break,the participants had the opportunity for discussing the plenary talks in detail.The afternoon session and second day were devoted to reconstruction practicals. 30attendees were divided into 10 groups. During one hour, each participant with a private computer and accompanying one demonstrator, performed splanchnic recontructions by following tracing, surfacing and adjusting steps. After final practical all those attending were given a cd-rom copy of presentations and a certificate of attendance.The course was not all work and education. On the evening it was dining in a peacefull atmosphere, as participants gathered in the Senior Staff Lounge of Hacettepe University to sample delicious food and wine.20ISSN 1303-1775 (electronic) 1303-1783 (printed)This computer aided 3D reconstruction course was of great interest to the scientific research community. The quality of all of the presentations was exceedingly high and the discussion following each talk revealed an audience that was both informed and interested. The course series will continue based upon the new approaches in three-dimensional reconstruction techniques.21Neuroanatomy, 2003, Volume 2, Pages 20-21.Demiryurek References[1] Trelease RB. Anatomical Informatics: millennial perspectives on a newer frontier. Anat. Rec. (New Anatomist) 2002 (269) 224-235.[2] /research/visible/[3] /dlib/october95/10ackerman.html [4] /research/visible/vhp_conf/vhpconf.htm [5] /research/visible/vhpconf98/main.htm [6] /research/visible/vhpconf2000/main.htm [7] Ÿ。
CORRESPONDENCE ADDRESS
DISCRIMINATIVE COMMON VECTORS FOR FACE RECOGNITION Hakan Cevikalp1, Marian Neamtu2, Mitch Wilkes1, and Atalay Barkana31Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA.2Center for Constructive Approximation, Department of Mathematics, Vanderbilt University, Nashville, Tennessee, USA.3Department of Electrical and Electronics Engineering, Osmangazi University, Eskisehir, Turkey.CORRESPONDENCE ADDRESS:Prof. Mitch WilkesDepartment of Electrical Engineering and Computer Science,Vanderbilt University, Nashville, Tennessee, USATel: (615) 343-6016Fax: (615) 322-7062e-mail: mitch.wilkes@AbstractIn face recognition tasks, the dimension of the sample space is typically larger than the number of the samples in the training set. As a consequence, the within-class scatter matrix is singular and the Linear Discriminant Analysis (LDA) method cannot be applied directly. This problem is known as the “small sample size” problem. In this paper, we propose a new face recognition method called the Discriminative Common Vector method based on a variation of Fisher’s Linear Discriminant Analysis for the small sample size case. Two different algorithms are given to extract the discriminative common vectors representing each person in the training set of the face database. One algorithm uses the within-class scatter matrix of the samples in the training set while the other uses the subspace methods and the Gram-Schmidt orthogonalization procedure to obtain the discriminative common vectors. Then the discriminative common vectors are used for classification of new faces. The proposed method yields an optimal solution for maximizing the modified Fisher’s Linear Discriminant criterion given in the paper. Our test results show that the Discriminative Common Vector method is superior to other methods in terms of recognition accuracy, efficiency, and numerical stability.Index Terms: Common Vectors, Discriminative Common Vectors, Face Recognition, Fisher’s Linear Discriminant Analysis, Principal Component Analysis, Small Sample Size, Subspace Methods.I. INTRODUCTIONRecently, due to military, commercial, and law enforcement applications, there has been much interest in automatically recognizing faces in still and video images. This research spans several disciplines such as image processing, pattern recognition, computer vision and neural networks. The data come from a wide variety of sources. One group of sources is the relatively controlled format images such as passports, credit cards, photo ID’s, driver’s licenses, and mug shots. A more challenging class of application imagery includes real-time detection and recognition of faces in surveillance video images, which present additional constraints in terms of speed and processing requirements [1].Face recognition can be defined as the identification of individuals from images of their faces by using a stored database of faces labeled with people’s identities. This task is complex and can be decomposed into the smaller steps of detection of faces in a cluttered background, localization of these faces followed by extraction of features from the face regions, and finally recognition and verification [2]. It is a difficult problem as there are numerous factors such as 3-D pose, facial expression, hair style, make up, and so on, which affect the appearance of an individual’s facial features.In addition to these varying factors, lighting, background, and scale changes make this task even more challenging. Additional problematic conditions include noise, occlusion, and many other possible factors.Many methods have been proposed for face recognition within the last two decades [1], [3]. Among these methods, appearance-based approaches operate directly on images or appearances of face objects, and process the images as two-dimensional (2-D) holistic patterns. In these approaches, a two-dimensional image of size w by h pixels is represented by a vector in a wh-dimensional space. Therefore, each facial image corresponds to a point in this space. This spaceis called the sample space or the image space, and its dimension typically is very high [4]. However, since face images have similar structure, the image vectors are correlated, and any image in the sample space can be represented in a lower-dimensional subspace without losing a significant amount of information. The Eigenface method has been proposed for finding such a lower-dimensional subspace [5]. The key idea behind the Eigenface method, which uses Principal Component Analysis (PCA), is to find the best set of projection directions in the sample space that will maximize the total scatter across all images such that ||max arg )(W S W W J T T Wopt PCA = is maximized. Here T S is the total scatter matrix of the trainingset samples, and W is the matrix whose columns are the orthonormal projection vectors. The projection directions are also called the eigenfaces. Any face image in the sample space can be approximated by a linear combination of the significant eigenfaces. The sum of the eigenvalues that correspond to the eigenfaces not used in reconstruction gives the mean square error of reconstruction. This method is an unsupervised technique, since it does not consider the classes within the training set data. In choosing a criterion that maximizes the total scatter, this approach tends to model unwanted within-class variations such as those resulting from differences in lighting, facial expression, and other factors [6], [7]. Additionally, since the criterion does not attempt to minimize within-class variation, the resulting classes may tend to have more overlap than other approaches. Thus, the projection vectors chosen for optimal reconstruction may obscure the existence of the separate classes.The Linear Discriminant Analysis (LDA) method is proposed in [6] and [7]. This method overcomes the limitations of the Eigenface method by applying the Fisher’s Linear Discriminant criterion. This criterion tries to maximize the ratio ||||maxarg )(W S W W S W W J W T B T W opt FLD =, where B S isthe between-class scatter matrix, and W S is the within-class scatter matrix. Thus, by applying this method, we find the projection directions that on one hand maximize the Euclidean distance between the face images of different classes and on the other minimize the distance between the face images of the same class. This ratio is maximized when the column vectors of the projection matrix W are the eigenvectors of B W S S 1−. In face recognition tasks, this method cannot be applied directly since the dimension of the sample space is typically larger than the number of samples in the training set. As a consequence, W S is singular in this case. This problem is also known as the “small sample size problem” [8].In the last decade numerous methods have been proposed to solve this problem. Tian et al . [9] used the Pseudo-Inverse method by replacing 1−W S with its pseudo-inverse. The Perturbation method is used in [2] and [10], where a small perturbation matrix ∆ is added to W S in order to make it nonsingular. Cheng et al . [11] proposed the Rank Decomposition method based on successive eigen-decompositions of the total scatter matrix T S and the between-class scatter matrix B S . However, the above methods are typically computationally expensive since the scatter matrices are very large (e.g., images of size 256 by 256 yield scatter matrices of size 65,536 by 65,536). Swets and Weng [7] proposed a two stage PCA+LDA method, also known as the Fisherface method, in which PCA is first used for dimension reduction so as to make W S nonsingular before the application of LDA. In this method the final optimal projection vector matrix becomes FLD PCA opt W W W =, where ||max arg W S W W T T W PCA =, and||||max arg W W S W W W W S W W W PCA W T PCA T PCA B T PCA T WFLD =. However, in order to make W S nonsingular, some directions corresponding to the small eigenvalues of T S are thrown away in the PCA step. Thus,applying PCA for dimensionality reduction has the potential to remove dimensions that contain discriminative information [12]-[16]. Chen et al . [17] proposed the Null Space method based on the modified Fisher’s Linear Discriminant criterion, W S W W S W W J T T B T W opt MFLD maxarg )(=. Thismethod was proposed to be used when the dimension of the sample space is larger than the rank of the within-class scatter matrix, W S . It has been shown that the original Fisher’s Linear Discriminant criterion can be replaced by the modified Fisher’s Linear Discriminant criterion in the course of solving the discriminant vectors of the optimal set in [18]. In this method, all image samples are first projected onto the null space of W S , resulting in a new within-class scatter that is a zero matrix. Then, PCA is applied to the projected samples to obtain the optimal projection vectors. Chen et al . also proved that by applying this method, the modified Fisher’s Linear Discriminant criterion attains its maximum. However, they did not propose an efficient algorithm for applying this method in the original sample space. Instead, a pixel grouping method is applied to extract geometric features and reduce the dimension of the sample space. Then they applied the Null Space method in this new reduced space. In our experiments, we observed that the performance of the Null Space method depends on the dimension of the null space of W S in the sense that larger dimension provides better performance. Thus, any kind of pre-processing that reduces the original sample space should be avoided.Another novel method, the PCA+Null Space method was proposed by Huang et al . in [15] for dealing with the small sample size problem. In this method, at first, PCA is applied to remove the null space of T S , which contains the intersection of the null spaces of B S and W S . Then, the optimal projection vectors are found in the remaining lower-dimensional space by using the Null Space method. The difference between the Fisherface method and the PCA+Null Space methodis that for the latter, the within-class scatter matrix in the reduced space is typically singular. This occurs because all eigenvectors corresponding to the nonzero eigenvalues of T S are used for dimension reduction. Yang et al . applied a variation of this method in [16]. After dimensionreduction, they split the new within-class scatter matrix, PCA W T PCAW P S P S =~ (where PCA P is the matrix whose columns are the orthonormal eigenvectors corresponding to the nonzeroeigenvalues of T S ), into its null space },...,{)~(1t r W span S N ξξ+= and orthogonal complement(i.e., range space) },...,{)~(1r W span S R ξξ= (where r is the rank of W S , and )(T S rank t = is thedimension of the reduced space). Then, all the projection vectors that maximize the between-class scatter in the null space are chosen. If, according to some criterion, more projection vectors are needed, the remaining projection vectors are obtained from the range space. Although the PCA+Null Space method and the variation proposed by Yang et al ., use the original sample space, applying PCA and using all eigenvectors corresponding to the nonzero eigenvalues make these methods impractical for face recognition applications when the training set size is large. This is due to the fact that the computational expense of training becomes very large.Lastly, the Direct-LDA method is proposed in [12]. This method uses the simultaneous diagonalization method [8]. First, the null space of B S is removed, and then the projection vectors that minimize the within-class scatter in the transformed space are selected from the range space of B S . However, removing the null space of B S by dimensionality reduction will also remove part of the null space of W S and may result in the loss of important discriminative information [13], [15], [16]. Furthermore, B S is whitened as a part of this method. This whitening process can be shown to be redundant and therefore should be skipped.In this paper, a new method is proposed which addresses the limitations of other methods that use the null space ofS to find the optimal projection vectors. Thus, the proposed method canWbe only used when the dimension of the sample space is larger than the rank ofS. TheW remainder of the paper is organized as follows. In Section II, the Discriminative Common Vector approach is introduced. In Section III, we describe the data sets and experimental results. Finally, we formulate our conclusions in Section IV.II. DISCRIMINATIVE COMMON VECTOR APPROACHThe idea of common vectors was originally introduced for isolated word recognition problems in the case where the number of samples in each class was less than or equal to the dimensionality of the sample space [19], [20]. These approaches extract the common properties of classes in the training set by eliminating the differences of the samples in each class. A common vector for each individual class is obtained by removing all the features that are in the direction of the eigenvectors corresponding to the nonzero eigenvalues of the scatter matrix of its own class. The common vectors are then used for recognition. In our case instead of using a given class’s own scatter matrix, we use the within-class scatter matrix of all classes to obtain the common vectors. We also give an alternative algorithm based on the subspace methods and the Gram-Schmidt orthogonalization procedure to obtain the common vectors. Then, a new set of vectors, called the discriminative common vectors, which will be used for classification are obtained from the common vectors. We introduce algorithms for obtaining the common vectors and the discriminative common vectors below.A. Obtaining the Discriminative Common Vectors by Using the Null Space of W S Let the training set be composed of C classes, where each class contains N samples, and let i mx be a d -dimensional column vector which denotes the m-th sample from the i-th class. There will be a total of M=NC samples in the training set. Suppose that d>M-C. In this case, W S , B S , and T S are defined as,T i i m i C i N m i m W x x S ))((11µµ−−=∑∑==, (1)T i C i i B N S )()(1µµµµ−−=∑=, (2)andB W T i mC i Nm i m T S S x x S +=−−∑∑===))((11µµ, (3) where µ is the mean of all samples, and i µ is the mean of samples in the i -th class.In the special case where 0=w S w W T and 0≠w S w B T , for all }0{\d R w ∈, the modified Fisher’s Linear Discriminant criterion attains a maximum. However, a projection vector w , satisfying the above conditions, does not necessarily maximize the between-class scatter. In this case, a better criterion is given in [6] and [13], namely||max arg ||max arg )(0||0||W S W W S W W J T T W S W B T W S W opt W T W T ====. (4)To find the optimal projection vectors w in the null space of W S , we project the face samples onto the null space of W S and then obtain the projection vectors by performing PCA. To do so, vectors that span the null space of W S must first be computed. However, this task is computationally intractable since the dimension of this null space can be very large. A moreefficient way to accomplish this task is by using the orthogonal complement of the null space of W S , which typically is a significantly lower-dimensional space.Let d R be the original sample space, V be the range space of W S , and ⊥V be the null space of W S . Equivalently,},...,1,0|{r k S span V k W k =≠=αα (5)and},...,1,0|{d r k S span V k W k +===⊥αα, 6)where d r < is the rank of W S , },....,{1d αα is an orthonormal set, and },....,{1r αα is the set of orthonormal eigen vectors corresponding to the nonzero eigenvalues of W S .Consider the matrices ]....[1r Q αα= and ]....[1d r Q αα+=. Since⊥⊕=V V R d , every face image d i m R x ∈ has a unique decomposition of the formi m i m i m z y x +=, (7)where V x QQ Px y i m T i m i m ∈==, ⊥∈==V x Q Q x P z i m T i m i m , and P and P are the orthogonal projection operators onto V and ⊥V , respectively. Our goal is to computei m i m i m i m i m Px x y x z −=−=. (8)To do this, we need to find a basis for V , which can be accomplished by an eigen-analysis of W S . In particular, the normalized eigenvectors k α corresponding to the nonzero eigenvalues of W S will be an orthonormal basis for V. The eigenvectors can be obtained by calculating the eigenvectors of the smaller M by M matrix, A A T , defined such that T W AA S =, where A is a d by M matrix of the form]........[22111111C C N N x x x x A µµµµ−−−−=. (9)Let k λand k v be the k -th nonzero eigenvalue and the corresponding eigenvector of A A T , where C M k −≤. Then k k Av =α will be the eigenvector that corresponds to the k -th nonzero eigenvalue of W S . The sought-for projection onto ⊥V is achieved by using (8). In this way, it turns out, we obtain the same unique vector for all samples of the same class,i m T i m T i m i com x Q Q x QQ x x =−=, m=1,…,N , i=1,...,C , (10)i.e., the vector on the right-hand side of (10) is independent of the sample index m . We refer tothe vectors i com x as the common vectors. The above fact is proved in the following theorem.Theorem 1: Suppose Q is a matrix whose column vectors are the orthonormal vectors thatspan the null space ⊥V of W S . Then, the projections of the samples i mx of the class i onto ⊥V produce a unique common vector i com x such thati m T i com x Q Q x =, m =1,…,N , i=1,…,C . (11)Proof : By definition, a vector d R ∈α is in ⊥V if 0=αW S . Let i µ be the mean vector of the i -th class, G be the N by N matrix whose entries are all 1−N , and i X be the d by N matrix whosem -th column is the sample i m x . Thus, multiplying both sides of identity 0=αW S by T α andwriting∑==Ci i W S S 1, (12)withT i i i i T i i m i Nm i m i G X X G X X x x S ))(())((1−−=−−=∑=µµ, (13)immediately leads to 211||))((||)())((0ααα∑∑==−=−−=Ci T i T i T i C i T X G I X G I G I X , (14)where ||.|| denotes the Euclidean norm. Thus, (14) holds if 0))((=−k T i X G I α, or k T i k T i X G X αα)()(=. From this relation we can see that,d r k C i N m x k T i k T i m ,...,1,,...,1,, (1))()(+====αµα. (15) Thus, the projection of i m x onto ⊥V ,k k d r k i k k d r k i m i com x x ααµαα〉〈=〉〈=∑∑+=+=,,11, (16)is independent of m , which proves the theorem.The theorem states that it is enough to project a single sample from each class. This will greatly reduce the computational burden of the calculations. This computational savings has not been previously reported in the literature.After obtaining the common vectors i com x , optimal projection vectors will be those thatmaximize the total scatter of the common vectors,||max arg ||max arg ||max arg )(0||0||W S W W S W W S W W J com T WT T W S W B T W S W opt W T W T =====, (17)where W is a matrix whose columns are the orthonormal optimal projection vectors k w , and com S is the scatter matrix of the common vectors,T com i com com Ci i com com x x S ))((1µµ−−=∑=, i =1,…,C , (18) where com µ is the mean of all common vectors, ∑==C i i com com x C 11µ.In this case optimal projection vectors k w can be found by an eigen-analysis of com S . In particular, all eigenvectors corresponding to the nonzero eigenvalues of com S will be the optimal projection vectors. com S is typically a large d by d matrix and thus we can use the smaller matrix, com T com A A , of size C by C, to find nonzero eigenvalues and the corresponding eigenvectors ofT com com com A A S =, where com A is the d by C matrix of the form]....[1com C com com com com x x A µµ−−=. (19)There will be C -1 optimal projection vectors since the rank of com S is C -1 if all common vectors are linearly independent. If two common vectors are identical, then the two classes which are represented by this vector cannot be distinguished. Since the optimal projection vectors k wbelong to the null space of W S , it follows that when the image samples i m x of the i -th class areprojected onto the linear span of the projection vectors k w , the feature vectorT C i m i m i w x w x ],....,[11><><=Ω− of the projection coefficients ><k i m w x , will also be independent of the sample index m . Thus, we havei m T i x W =Ω, m=1,…,N, i=1,…,C. (20)We call the feature vectors i Ω discriminative common vectors , and they will be used for classification of face images. The fact that i Ω does not depend on the index m in (20) guarantees 100% accuracy in the recognition of the samples in the training set. This guarantee has not been reported in connection with other methods [15], [17].To recognize a test image test x , the feature vector of this test image is found bytest T test x W =Ω, (21)which is then compared with the discriminative common vector i Ω of each class using the Euclidean distance. The discriminative common vector found to be the closest to test Ω is used to identify the test image.Since test Ω is only compared to a single vector for each class, the recognition is very efficientfor real-time face recognition tasks. In the Eigenface, the Fisherface, and the Direct-LDA methods, the test sample feature vector test Ω is typically compared to all feature vectors ofsamples in the training set, making these methods impractical for real-time applications for large training sets.The above method can be summarized as follows:Step 1: Compute the nonzero eigenvalues and corresponding eigenvectors of W S by using the matrix A A T , where T W AA S = and A is given by (9). Set ]....[1r Q αα=, where r is therank of W S . Step 2: Choose any sample from each class and project it onto the null space of W S to obtain the common vectorsi m T i m i com x QQ x x −=, N m ,...,1=, C i ,...,1=. (22)Step 3: Compute the eigenvectors k w of com S , corresponding to the nonzero eigenvalues, byusing the matrix com T comA A , where T com com com A A S = and com A is given in (19). There are at most C -1 eigenvectors that correspond to the nonzero eigenvalues. Use these eigenvectors to form the projection matrix ]....[11−=C w w W , which will be used to obtain feature vectors in (20) and (21).B. Obtaining the Discriminative Common Vectors by Using Difference Subspaces and the Gram-Schmidt Orthogonalization ProcedureTo find an orthonormal basis for the range of W S , the algorithm described above uses the eigenvectors corresponding to the nonzero eigenvalues of the M by M matrix A A T , whereTW AA S =. Assuming that C M S rank W −=)(, then dC C M dM M M M l +−+−+)(2)234(233floating point operations (flops) are required to obtain an orthonormal basis set spanning the range of W S by using this approach. Here l represents the number of iterations required for convergence of the eigen-decomposition algorithm. However, the computations may become expensive and numerically unstable for large values of M . Since we do not need to find the eigenvalues (i.e., an explicit symmetric Schur decomposition) of W S , the following algorithm can be used for finding the common vectors efficiently. It requires only ))()(2(2C M d C M d −+− flops to find an orthonormal basis for the range of W S and is based on the subspace methods and the Gram-Schmidt orthogonalization procedure.Suppose that d >M-C . In this case, the subspace methods can be applied to obtain the commonvectors i com x for each class i . To do this, we choose any one of the image vectors from the i -th class as the subtrahend vector and then obtain the difference vectors i k b of the so-called difference subspace of the i -th class [20]. Thus, assuming that the first sample of each class istaken as the subtrahend vector, we have i i k i k x x b 11−=+, 1,...,1−=N k .The difference subspace i B of the i -th class is defined as },....,{11i N i i b b span B −=. Thesesubspaces can be summed up to form the complete difference subspace},....,,,....,{....12111111C N N C b b b b span B B B −−=++=. (23)The number of independent difference vectors i k b will be equal to the rank of W S . Forsimplicity, suppose there are M -C independent difference vectors. Since by Theorem 3, B and the range space V of W S , are the same spaces, the projection matrix onto B is the same as the matrix P (projection matrix onto the range space of W S ) defined previously in Section II-A. This matrix can be computed asT T D D D D P 1)(−=, (24)where ]........[1211111C N N b b b b D −−= is a d by M-C matrix [21]. This involvesfinding the inverse of an M -C by M -C nonsingular, positive definite symmetric matrix D D T . A computationally efficient method of applying the projection uses an orthonormal basis for B . Inparticular, the difference vectors i k b can be orthonormalized by using the Gram-Schmidtorthogonalization procedure to obtain orthonormal basis vectors C M −ββ,....,1. The complement of B is the indifference subspace ⊥B such that]....[1C M U −=ββ, T UU P =, (25) ]....[1d C M U ββ+−=, T U U P =, (26)where P and P are the orthogonal projection operators onto B and ⊥B , respectively. Thus matrices P and P are symmetric and idempotent, and satisfy I P P =+. Any sample from each class can now be projected onto the indifference subspace ⊥B to obtain the corresponding common vectors of the classes,.,...,1,,...,1,C i N m x UU x x U U Px x x P x i m T i m im T i mi m i m i com ==−==−== (27)The common vectors do not depend on the choice of the subtrahend vectors and they are identical to the common vectors obtained by using the null space of W S . This follows from Theorem 3 below, which uses the results of Lemma 1 and Theorem 2.Theorem 2: Let ⊥i V be the null space of the scatter matrix i S , and ⊥i B be the orthogonal complement of the difference subspace i B . Then ⊥⊥=i i B V and i i B V =.Proof : See [20].Lemma 1: Suppose that C S S ,....,1 are positive semi-definite scatter matrices. ThenI Ci i C S N S S N 11)()....(==++, (28) where N ( ) denotes the null space.Proof : The null space on the left-hand side of the above identity contains elements α such that0)....(1=++αC S S (29)or0....)....(11=++=++ααααααC T T C T S S S S , (30)by the positive semi-definiteness of C S S ++....1. Thus, again by the positive semi-definiteness, )....(1C S S N ++∈α if and only if0=ααi T S , i=1,...,C , (31)or, equivalently, I Ci i S N 1)(=∈α. Theorem 3: Let C S S ,....,1 be positive semi-definite scatter matrices. ThenC C C W B B S R S R S S R S R B ++=++=++==....)(....)()....()(111, (32)where R denotes the range.Proof : Since it is well known that the null space and the range of a matrix are complementary spaces, using the previous Lemma 1, we have,....)(....)())((....))(())(())....(()....(111111C C C C i i C C B B S R S R S N S N S N S S N S S R ++=++=++==++=++⊥⊥⊥=⊥I (33)where the last equality is a consequence of Theorem 2.After calculating the common vectors, the optimal projection vectors can be found by performing PCA as described previously in Section II-A. The eigenvectors corresponding to the nonzero eigenvalues of com S will be the optimal projection vectors. However, optimal projection vectors can also be obtained more efficiently by computing the basis of the difference subspace com B of the common vectors, since we are only interested in finding an orthonormal basis for the range of com S .The algorithm based on the Gram-Schmidt orthogonalization can be summarized as follows.Step 1: Find the linearly independent vectors i k b that span the difference subspace B and set},....,,,....,{1211111C N N b b b b span B −−=. There are totally r linearly independent vectors, where r is at most M -C .Step 2: Apply the Gram-Schmidt orthogonalization procedure to obtain an orthonormal basis r ββ,....,1 for B and set ]....[1r U ββ=.Step 3: Choose any sample from each class and project it onto B to obtain common vectors by using (27).Step 4: Find the difference vectors that span com B as11com k com k com x x b −=+, 1,...,1−=C k , (34)。
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Instructions for Authors(limited to about15words)James Finser1,Duobao Liu2,Hailiang Wang2,*,Mark Tera3,Mickey Shin31School of Materials Science and Engineering,Shenzhen High-Tech University,Shenzhen312341,China2School of Mechanical Engineering,Shenzhen High-Tech University,Shenzhen312341,China3Centre of Advanced Materials,University of Hyderabad,Hyderabad500046,IndiaCorresponding author:Dr.Hailiang WangMailing Address:School of Mechanical Engineering,Shenzhen High-Tech University, Shenzhen312341,ChinaTelephones:+86-755-88888888(office),+86-138********(Mobile)Fax:+86-755-88888888E-mail:*****************.cn,*********************Author to whom correspondence should be addressed.Abstract:This document explains and demonstrates how to prepare your manuscript for American Scientific Publisher.All manuscripts must be in English,typed double-spaced.The best is to read these instructions and follow the outline of this text.This word template mainly aims at the format. 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ASP or Editors will not return manuscripts to authors and keep any records whatsoever after a formal decision has been made about the manuscript.Editors have the right to reject the manuscript.17.COPYRIGHTAll authors are responsible for the complete contents of their manuscript.The author(s)warrant that the work contains no unlawful or libelous statements and opinions and liable materials of any kind whatsoever,do not infringe on any copyrights,intellectual property rights,personal rights or rights of any kind of others,and contain any materials,instructions,procedures,information or ideas that might cause any harm,damage,injury,losses or costs of any kind to person or property.It is authors' responsibility to obtain written copyright permissions from other sources for reproduction of any figures,tables,photos,illustrations,text or other copyright materials from previously published work. It is the policy of American Scientific Publishers to own the copyright of all contributions it publishes.To comply with the U.S.Copyright Law,a Copyright Transfer Form that transfer copyright of the article to the publisher must be completed by the authors prior to publication of an accepted article in this journal.Authors must submit a signed copy of this form with their manuscript.Acknowledgments:The Committee of ISMST2010acknowledges the support from American Scientific Publisher for publishing the accepted paper in Advanced Science Letters.References and Notes1.M.Valden,i,and D.W.Goodman,Science281,1647(1998).2.C.A.Mirkin,R.L.Letsinger,R.C.Mucic,and J.J.Storhoff,Nature382,607(1996).3.Y.Sun and Y.Xia,Science5601,2176(2002).4.D.H.Gracias,J.Tien,T.L.Breen,C.Hsu,and G.M.Whitesides,Science289,1170(2000).5.E.Hao,K.L.Kelly,J.T.Hupp,and G.C.Schatz,J.Am.Chem.Soc.124,15182(2002).6.J.Huang,Q.Li,D.Sun,Y.Lu,Y.Su,X.Yang,H.Wang,Y.Wang,W.Shao,N.He,J.Hong,and C. Chen,Nanotechnology18,105104(2007).7.A.Ahmad,S.Senapati,M.I.Khan,R.Kumar,and M.Sastry,Langmuir.19,3550(2003).8.B.Nair and T.Pradeep,Crys.Growth Des.2,293(2002).9.T.K.Joerger,R.Joerger,E.Olsson,and C.G.Granqvist,Trends Biotechnol.19,15(2001).10.A.R.Shahverdi,S.Minaeian,H.R.Shahverdi,H.Jamalifar,and A.A.Nohi,Proc.Biochem.42, 919(2007).Figures and TablesTable1.The students have been registered at a local university in2009. Fig.1.The style of figures for Adv.Sci.Lett.Fig.2.One example of figureTitle:Instructions for Authors2009..Table1.The students have been registered at a local university in2009College Freshman Granduate Variation Cedarr University2420+4 Elmee College4353-10 Maple Institute311-8 Pinel University94+5Title:Instructions for AuthorsFig.1.T he style of figures for Adv.Sci.Lett.Title:Instructions for Authors Fig.2.One example of figure。
2.马德里商标外文申请书MM2表格-中文翻译
MM2 (E) – APPLICATION FOR INTERNATIONAL REGISTRATION UNDER THE MADRID PROTOCOL 根据马德里议定书申请国际注册For use by the applicant: 供申请人使用Number of continuation sheets for several applicants: 多个申请人的续页数Number of continuation sheets: 续页数For use by the Office of origin: 供原商标局使用Office’s reference (optional): 办事处说明（选填）1If there is more than one applicant, indicate the details for the first applicant only and provide the details requested in the “Continuation Sheet for Several Applicants” attached to this form. 2 You must indicate your e-mail address. WIPO will send all communications concerning this international application and the resulting international registration to the e-mail address indicated here, unless an alternative e-mail address for correspondence is indicated in item 2(g)(ii) or a representative is appointed. The applicant must ensure that the e-mail address indicated here is correct and kept up to date. 3 Indicating a phone number is not required, but it will allow WIPO to reach you if needed.(f) Preferred language for correspondence 5:通信语言选择 ☐ English 英语 ☐ French 法语☐ S panish 西班牙语4Certain designated Contracting Parties may require these indications; only provide indications in either item (i) or item (ii) but not in both items. 某些指定缔约方可要求提供这些指示；仅在项目（i ）或项目（ii ）中提供指示，但不在两个项目中提供指示 5 If you do not indicate your preferred language, WIPO will send all communications concerning thisinternational application and the resulting international registration in the language of the international application. 如果您没有指明您的首选语言，WIPO 将以国际申请的语言发送有关本国际申请和由此产生的国际注册的所有通信 6 Use this only if you want WIPO to send all communications concerning this international application and the resulting international registration to an address and e-mail address different from those indicated in item 2 (b) and (c). 仅当您希望WIPO 将与本国际申请和由此产生的国际注册有关的所有通信发送到与项目2（b ）和（c ）中所示地址和电子邮件地址不同的地址和电子邮件地址时，才可使用此项3. ENTITLEMENT TO FILE7(a) Check the appropriate box:选中相应的框(i) ☐where the Contracting Party mentioned in item 1 is a State, the applicant isa national of that State; or 1中缔约国是国家的，申请人是该国国民；或(ii) ☐where the Contracting Party mentioned in item 1 is an organization, thename of the State of which the applicant is a national:(iii) ☐the applicant is domiciled in the territory of the Contracting Party mentioned in item 1; or申请人的住所在第1项所述缔约国境内；或(iv) ☐the applicant has a real and effective industrial or commercial establishment in the territory of the Contracting Party mentioned in item 1.申请人在1所述缔约国境内有实际有效的工商机构。
【论文】英文科技论文写作第三课AuthorshipAuthorsBylineAddress
【关键字】论文Workshop 3: Authorship, Author By-line & Names & AddressIntroductionIn today’s workshop we consider the vexed question of authorship. Who should be included as an author on your paper? Or alternatively, what contribution is required for someone to qualify as an author? We also examine issues as the order of names on a paper, the format for citing your own name on a paper and address for correspondence. These issues may seem citing trivial, but an understanding of them can prevent problems and disputes from occurring in future.Who should be an author?The part of paper that comes immediately after the title is the author’s by-line, which is a list of people who made an important contribution to the published paper. Writing this by-line is usually straight-forward, but great judgment is needed in some cases when deciding on whether someone should be included a co-author, and also the order in which the names of co-authors are cited. Dispute over a co-authorship can arise, and as pointed out by Day (1998) “reasonable, rational, colleagues can become bitter enemies solely because they could not agree on whose names should be listed or in what order.” After all the only people who never get upset about authorship are the people who do not publish papers!Comprehensive guidelines on authorship are published by the International Committee of Medical Journal Editors (). This organization states that:“Each author should have participated sufficiently in the work to take public responsibility for appropriate portions of the content.”Failure to take responsibility for the content of a paper is important as the following editorial in Nature points out: “Few would dispute that researchers have to take responsibility for papers that have their names on them. A senior laboratory figure who puts his or her name on a paper without direct supervision or involvement is unquestionably abusing the system of credit. There have been occasions where distinguished scientists have put their names irresponsibly on a paper that has turned out to contain serious errors or fraud. Rightly some of them have paid a heavy price.”(Anon 1997)Criteria for co-authorshipThe International Committee of Medical Journal Editors state that “one or more authors should take responsibility for the integrity of the work as a whole from inception to published article.”Agreement on who this person is should be reached before embarking on a piece of research. The International Committee of Medical Journal Editors defines an author using the following criteria (see /ethical 1author.html):(1)Substantial contributions to conception and design, or acquisition of data, or analysis andinterpretation of data.(2)Drafting the article of revising it critically for important intellectual content.(3)Final approval of the version to be published.All the three criteria must be met, according to the International Committee of Medical Journal Editors before someone can qualify as an author. This organization does not consider the following contributions as giving someone the right to be an author:(1)Acquisition of funding.(2)Collection of data (technical help of a routine nature).(3)General supervision of research group or student.(4)Writing assistance of a routine nature.Many people consider the aforementioned guidelines as too restrictive. In particular some feel that they undervalue the contributions of skilled technicians (see below). Furthermore, the guidelines do not specify what should be considered as a substantial intellectual contribution to the research (criteria 1). To overcome this problem and to make it easier to come to a judgment about who should be an author on a paper some professors have developed criteria for authorship that weight the different criteria and assign points to each criterion. The decision on whether to include a person as an author on a paper is then based upon whether they reached a minimum point score, for example 10% of the total points allocated to all criteria. For example, Kosslyn (2002) allocated 1000 points to the following 6 criteria:(1)The idea (250 points)(2)Experimental design (100 points)(3)The implementation; translating experimental design into instructions and ensuring thatexperimentation proceeds according to the design (100 points)(4)Conducting the experiment (100 points)(5)Data analysis (200 points)(6)Writing (250 points)A person achieving 100 points is granted co-authorship. Kosslyn’s guidelines can be found at /fs/docs/icb.topic562342.files/authorship_criteria_Nov02.pdf. Technician & statistician as co-authors?Kosslyn (2002) stated that the key to fair allocation of authorship and equitable ordering is to have criteria that are known to all and that all can discuss. These should be agreed upon and discussed before starting any research that could lead to the publication of a paper. Both the guidelines published by the International Committee of Medical Journal Editors and those written by Kosslyn (2002) emphasize the intellectual contributions to the published paper. Simply carrying out research work under instruction is deemed by many to be insufficient for co-authorship. Hence, a technician who carries out research for a paper can in theory be excluded as a co-author. However, in many cases technicians modify experimental procedures to make them better or more efficient, or they are involved in the generation of research questions as a result of making original observations during the course of doing practical research. Such inputs are important intellectual contributions for any piece of research and certainly qualify technicians for co-authorship. Hence, technicians are often co-authors on a paper. There has also been debate in the scientific literature about whether statisticians involved in research should be granted co-authorship. The answer to this question is much more straight-forward than the question of whether to grant a technician co-authorship. Statisticians should always be granted co-authorship if they are involved in the design or analysis of experiments. Good experimental design and correct and efficient analysis and interpretation of data are the hallmarks of high quality scientific research. Statisticians can ensure that your research has these qualities, but they are unlikely to become involved if their contributions are relegated to the acknowledgement section of a paper. Statisticians understandably become quite annoyed when their contributions to papers are undervalued as the following abstract of a letter in the British Medical Journal points out (Mullee et al. 1995): “Statisticians should be co-authors”“EDITOR, -Neville W Goodman outlines criteria for authorship of published material. Medicalresearch is often, by its nature, multidisciplinary, and frequently the authorship or papers reflects this. As statisticians we find that analysis is rarely just a “simple manipulation on a computer” but involves a great deal of time and care from the study’s design stage, through checking of the data and statistical analysis to presentation of the results. The application of “standard statistical tests”does not necessarily imply that the analysis was straightforward; it may imply that more complicated methods of analysis, which are often less easy to interpret, were considered to be inappropriate. We therefore believe that statisticians’contribution to medical research should generally be recognized through co-authorship and not simply through their receiving credit for what they have done and nothing more.”Guest authorshipThe inclusion of a person’s name on a paper in the author’s by-line implies that they have made an important contribution to the work being reported. A guest author is a person who has not made an important contribution to a paper, but nevertheless is included as a co-author. Guest authorship can arise for a number of reasons. Firstly, many scientists are not aware that material support, general supervision or simple editing does not qualify them for co-authorship, and insist that they receive co-authorship to which they are not entitled. Some scientists may be aware that their contributions do not entitle them to co-authorship, but nevertheless insist on co-authorship to inflate their publication record. Such dishonest practice has been encouraged by administrators of universities who equate research productivity and quality with numbers of papers and provide incentives (tenure, promotion and merit awards) for scientists based on the number of papers they have authored. Faculty members of University Departments who sit on review panels are aware of this problem and look quite closely at the records of people who appear as co-authors on papers that lie outside of their main field of research or who publish large numbers of paper without appearing as first author on many of them. In such cases it may be necessary to clarify the authors’contribution to some of the papers to remove any suspicion that they have accepted guest authorship. Most good scientists are too honest to accept guest authorships, now would they grant guest authorships, as they are aware that such practice dilutes and undervalues the contributions of co-authors who have made substantial contributions to published work. In some societies, however, there is strong pressure on researchers to grant co-authorship to the head of their laboratory. Failure to follow this practice would lead to the termination of their research contract. Therefore, it is understandable that many of them comply by granting co-authorship to the head of their laboratory. Most scientists, however, are aware of the countries in which such practices is common and discount the contribution of the head of the laboratory, which is unfortunate because that person may actually deserve co-authorship.Contributors listTo fairly assign credit to authors and overcome problems such as guest authorship many journals are now including a contributors list. To contributors list is a section included at the end of a paper (or submitted to the journal), which lists the authors and describes their contributions to a paper. The contributors list serves two purposes; Firstly, it makes the practice of guest authorship more difficult as the editor of a journal is able to evaluate the contributions of each author. Secondly, the contributors list allows the reader to identify the people to contact to obtain more information on a particular area of interest to them or request samples or reagents. The contributors list should not be too detailed. Here is an example of a contributors list from a paper in Nature Nanotech (Peng et al 2008).Author contributions“H.E. conceived and designed the experiments. B.P. and S.L. performed the experiments. H.E., P.Z., G.S. and M.L. conceived the simulations. All authors analyzed the data. S.M. contributed analysis tools. All authors discussed the results and co-wrote and commented on the manuscript.B.P. and M.L. contributed to this work.”Even if the journal that you are submitting your paper to does not a contributors list, it is a good idea to develop one with your co-author(s) and include it in the letter you write when you submit the paper to a journal. The editor of the journal will be pleased to have such information and it may encourage him/he to adopt the idea of a contributors list.Order of authorsAs pointed out by Day (1998) the sequence of authors on a published paper “should be decided before the research commences, and it is foolish to leave this question to the end of the research.”A number of conventions are used to denote the relative importance of authors’ contributions to a published paper:(1)List authors in order of importance to the experiments, the first author being the senior author,the second author the primary associate etc.(2)First and last author’s spots have seniority with the first spot representing the senior author,(usually the person who had the greatest experimental contributions to the paper), and the last position allocated to the person (usually a senior scientist) who conceived of the study.Between these two positions the order of scientists is listed according to their relative contributions.(3)As above for 1 or 2, but a scientist can receive recognition equivalent to that of the seniorauthor by marking the authors names with a superscript to a footnote or subheading that indicates that the authors made equal contributions to the work.(4)As an alternative to 3 a subheading or footnote can be used to indicate that all authorscontributed equally to the work or the published paper.(5)In some fields such as mathematics it is common for authors to be listed alphabetically,presumably to avoid conflicts over author’s credit.The first position in the author’s by-line is known as the senior author and certainly carries more prestige than other authors’ positions in the by-line. Most people would agree that the first author has made the largest contribution to the publication of research work and if there are two people with equivalent publication records in terms of number of papers and the quality of journals they have published in, then the person who has authored more papers as a senior author will be regarded as having the superior publication record. For this reason it is quite important for junior scientists seeking their first appointment or tenure or promotion to author papers as a senior author rather than act as a co-author on papers, particularly if the other co-authors are more senior faculty.All people listed as co-authors on a paper should agree to be co-authors and you should resist requests for guest authorship (as discussed above). Even though scientists may agree to be co-author on a paper, it is unlikely, as mentioned by Gustavii (2003), that they will be happy with their position/ranking within the by-line because many authors tend to overestimate their own particular contribution to a paper.NamesThe citing of people’s names within the authors by-line usually follows the following convention:First name (in full), middle initial and surname (in full). The middle name is not spelled out in full because it could lead to confusion about whether it is part of the surname i.e., Callum B. Evans, rather than Callum Bowen Evans (Bowen being a surname).Whenever possible a scientist should try to cite his/her name in the same way on every paper they publish so that search engines such as Web of Science will retrieve all of the published work. therefore, avoid the temptation to shorten your first name (Barb instead of Barbara or Phil instead of Philip) and always include your middle initial, if you have one. Certain situations can lead to inconsistencies in the citing of people’s names on papers. Foremost amongst these are a change of name resulting from marriage or divorce and re-marriage. This type of inconsistency only affects women and can be avoided if female scientist retain their maiden names. Scientists from China who work in the West often adopt an English name and inconsistencies can arise if they first publish using their Chinese name, for example, N.S. Hon and then when they move to the West subsequently prefix their Chinese initial(s) with the initial of a English name such as David (D.N.S. Hon). Inconsistencies in the citing of people’s names can make it difficult to easily retrieve a person’s publication record using the Web of Science. The same is true of people with very common names as John Smith or Philip Evans! Fortunately, the inclusion of a subject are, journal titles and institutional details in the search can usually result in the retrieval of most of a person’s publication record.AddressesThe listing of authors’ addresses below the authors by-line on a paper can be straightforward if the scientist who published the paper worked at one institution. Even if they work at different institutions then their affiliations can be indicated with a superscript (1, 2, 3 or a, b, c) after their names. Sometimes scientists move institutions and their new address can be indicated in a footnote such as Present Address. A scientist may occasionally be affiliated with two institutions or publish work that was done in two different institutions. In such a situation their names may carry two superscripted symbols to indicate affiliation with two institutions. In some countries institutional funding provided by government is linked to the numbers of papers published and hence it is important to indicate if work was done in an institution in that country. The address and email is important because if allows scientist to contact authors about the published work (see also comments above about the role of the corresponding author).ReferencesAnon. (1997). Games people play with author’s name. Nature 387(6636): 831Day, R.A. (1998). How to write & publish a scientific paper (5th Edition), Oryx Press, Westport C T.Gustavii, B. (2003). How to write and illustrate a scientific paper. Cambridge Univ Press, Cambridge.Mullee, M.A., Lampe, F.C., Pickering, R.M., Julious, S.A. (1995). Statisticians should be co-authors. British Medical Journal. 310: 869.Peng, B., Locascio, M., Zapol, P., Li, S., Mieke, S.L., Schatz, G.C., Espinosa, H.D. (2008). Measurements of near-ultimate strength for multi-walled carbon nano-tubes and irradiation-induced crosslinking improvements. Nature nanotechnology 3, 626-631 (2008)此文档是由网络收集并进行重新排版整理.word可编辑版本！。
address的用法和例句
address的用法和例句Address，英语单词，主要用作名词、动词。
作名词时意为“地址，住址；网址；电子邮箱地址；演讲，演说”。
作动词时意为“演说，演讲；处理，设法解决；在（信封、包裹等）上写姓名和地址，致函”等。
单词释义英[əˈdres] 美[əˈdres]n. 地址，住址；网址；电子邮箱地址；演讲，演说；（电子表格中某个单元格的）位置；<古>（对他人的）谈吐；<古>谦恭（或脉脉含情）的方式；<旧>机敏，迅速；位置存储编码v. 演说，演讲；处理，设法解决；在（信封、包裹等）上写姓名和地址，致函；<正式> 向……讲话；称呼；<正式>（向某人）提出（陈述、投诉等）；（高尔夫）就位击（球）短语搭配email address 电子邮箱信箱ip address 网络地址，IP地址address book 通讯簿；住址名册home address 家庭住址；标识地址；内部地址mailing address 邮寄地址network address 网络地址address space 地址空间address as 称呼e-mail address 电子邮件地址public address 公用地址；扩音装置address system 地址系统；称谓系统inaugural address 就职演说address translation 地址转换；位址翻译public address system 扩声系统；有线广播系统；公用地址系统correspondence address 通讯地址；通信地址specific address 专用地址full address 全地址physical address 物理地址；实际地址permanent address 永久地址；永久住址；原籍mail address 邮件地址；信件地址双语例句1、They had no permanent address. 他们没有固定的地址。
商务英语邮件
商务邮件英语：咨询建议10个常用句子1 Shall you have any problem accessing the folders, please let me know.如果存取文件有任何问题请和我联系。
2 Thank you and look forward to having your opinion on the estimation and schedule.谢谢你,希望能听到更多你对评估和日程计划的建议。
3 Look forward to your feedbacks and suggestions soon.期待您的反馈建议!4 What is your opinion on the schedule and next steps we proposed?你对计划方面有什么想法?下一步我们应该怎么做?5 What do you think about this?这个你怎么想?6 Feel free to give your comments.请随意提出您的建议。
7 Any questions , please let me know .有任何问题，欢迎和我们联系。
8 Please contact me if you have any questions.有任何问题，欢迎和我们联系。
9 Please let me know if you have any question on this.有任何问题，欢迎和我联系。
10 Your comments and suggestions are welcome!欢迎您的评论和建议!关于英文书信的开头和结尾的写法一：开始语1、 Thank you for your letter of September 1.2、 Many thanks for your kind letter which reached me yesterday.3、 You letter come to me this morning.4、 I was delighted to receive your letter .5、 I am in receipt of your letter .6、It’s a long time since I saw your last .7、 I have been missing you a lot since we met last time .8、 I am sorry for not writing to you sooner .9、 I am writing to you tell that ……10.I often think of you. How are you recently?Thank you for your kind letter．（谢谢你的友好来信。
Address correspondence to
- 1 -Verifying Properties from Different Modalities for ConceptsProduces Switching CostsDiane PecherUtrecht UniversityRené ZeelenbergUniversity of AmsterdamLawrence W. BarsalouEmory UniversityApril 22, 2002RUNNING HEAD: Switching costs in property verificationWord count (text and notes): 3,855Address correspondence to:Lawrence W. BarsalouDepartment of PsychologyEmory UniversityAtlanta, GA 30322(404) 727-4338 office(404) 727-0372 faxbarsalou@AbstractAccording to perceptual symbol systems (Barsalou, 1999), sensory-motor simulations underlie the representation of concepts. It follows that sensory-motor phenomena should arise in conceptual processing. Previous studies have shown that switching from one modality to another during perceptual processing incurs a processing cost. If perceptual simulation underlies conceptual processing, then verifying the properties of concepts should exhibit a switching cost as well. For example, verifying a property in the auditory modality (e.g., BLENDER-loud) should be slower after verifying a property in a different modality (e.g., CRANBERRIES-tart) than in the same modality (e.g., LEAVES-rustling). Only words were presented to subjects, and there were no instructions to use imagery. Nevertheless switching modalities incurred a cost, analogous to switching modalities in perception. A second experiment showed that this effect was not due to associative priming between properties in the same modality. These results support the hypothesis that perceptual simulation underlies conceptual processing.Modern psychology relies heavily on the digital computer as a metaphor for human cognition (e.g., Fodor, 1975; Pylyshyn, 1984). According to this view, the software of the mind can be distinguished from the hardware of the body, with mental representations being amodal redescriptions of sensory-motor experience. Increasingly, however, researchers argue that this approach is fundamentally wrong, suggesting instead that interactions between sensory-motor systems and the physical world underlie cognition.For example, Barsalou’s (1999) theory of perceptual symbol systems proposes that conceptual knowledge is grounded in sensory-motor systems. To represent a concept, neural systems partially run as if interacting with an actual instance. For example, to represent the concept CHAIR, neural systems for vision, action, touch, and emotion partially reenact the experience of a chair. Increasingly, behavioral evidence supports this view (e.g., Klatzky, Pellegrino, McKloskey, & Doherty, 1989; Solomon & Barsalou, 2001, 2002; Spivey, Tyler, Richardson, & Young, 2000; Stanfield & Zwaan, 2001; Wu & Barsalou, 2002; Zwaan, Stanfield, & Yaxleu, in press), as does neural evidence (e.g., Martin, 2001; Martin & Chao, 2001; Martin, Ungerleider, & Haxby, 2000; Pulvermüller, 1999). See Barsalou (1999; in press) and Glenberg (1997) for further evidence.Several aspects of sensory-motor simulations are important for the experiments presented shortly. First, simulations are componential, not holistic. Rather than being like a holistic video recording, a simulation contains many small elements of perception—perceptual symbols—organized coherently. Second, perceptual symbols arise on all modalities of experience—vision, audition, smell, taste, touch, action, emotion, introspection, etc. Third, perceptual symbols vary in accessibility. On a given occasion, only those perceptual symbols most active enter a simulation, such that the simulations of a concept vary considerably across occasions. Furthermore—and most importantly for our purposes—the modalities represented in simulations vary as well. On one occasion, the simulation of a concept might focus on how an object looks (e.g., a LEMON is yellow); on another occasion, a simulation might focus on how the object tastes (e.g., a LEMON is sour).1 Although multiple modalities may typically be represented, one may often be more salient than others.Furthermore, over time, the focus may remain in a single modality, or it may switch from one modality to another.If switching between modalities occurs during conceptual processing, then a phenomenon from the perception literature is relevant. Spence, Nicholls, and Driver (2000) had subjects discriminate whether a signal occurred on the left or the right in any of three modalities monitored simultaneously (i.e., a light in vision, a touch on a finger, a tone in audition). When two consecutive signals occurred on the same modality, processing stayed within a single system. When consecutive signals occurred on different modalities, processing had to switch between systems. Most importantly, Spence et al. found that switching modalities incurred a cost: Detecting a signal was slower when the previous signal was on a different modality than on the same (also see Spence & Driver, 1998).If conceptual processing utilizes sensory-motor systems, then an analogous cost should occur when conceptual processing switches from one modality to another. To investigate this prediction, we used the property verification task. On target trials, subjects verified a property in one of six modalities (vision, audition, taste, smell, touch, action). For example, subjects might verify the auditory property loud for BLENDER. On the previous trial, subjects either verified a property from a different concept on the same modality or on a different modality (e.g., LEAVES-rustling versus CRANBERRIES-tart). Table 1 provides examples of the critical materials. Because the concepts on the two trials were always unassociated, no associative priming between concepts should occur. Also a high ratio of filler trials to critical trials masked the purpose of the experiment (i.e., the number of paired trials on the same modality was relatively small). The key prediction was that having to switch modalities would slow verification time, relative to staying within the same modality, analogous to modality-switching costs in perceptual processing.Experiment 1 also explored whether the stimulus onset asynchrony (SOA) between presentation of the concept and presentation of the property is a factor in switching costs. Perhaps switching costs disappear when properties lag behind concepts, because the concept has longer to activate properties across modalities. Alternatively, switching costs may remain constant across SOAs if subjects do not commit to a dominant modality until receiving theproperty word. To assess these possibilities, some subjects received the concept and property on each trial simultaneously (SOA=0 ms), whereas others received the concept first, followed by the property 260 ms later (SOA=260 ms).-----------------------------------------------Insert Table 1 about here-----------------------------------------------Experiment 1MethodSubjects and design. Sixty-four volunteers from Emory University participated for course credit. Thirty-two were assigned randomly to each of the two between-subjects conditions for SOA. Same versus different modality was manipulated within subjects, with equal numbers receiving each counterbalanced version of the list.Materials. A set of 100 concept-property items was developed. Each property was more salient on one modality than on the others. We selected 26 properties from vision, 24 from motor actions, 18 from audition, 12 from touch, 12 from taste, and 8 from smell. Because some modalities have more words for properties than others, the number of properties differed across modalities by necessity.From the 100 concept-property items, 50 pairs were formed. Half contained two properties from the same modality; half contained properties from different modalities. The two items forming a same-modality pair were chosen randomly from items on the relevant modality. According to the norms of Nelson, McEvoy, and Schreiber (1999), the properties in these pairs were not associated.2 One item in each same-modality pair was randomly assigned to be presented first (the context item), and the other to be presented second (the target item). Table 1 presents an example from each modality. The two items comprising a different-modality pair were chosen randomly from the remaining items. In pairs of both types, if the two concepts exhibited a relation, they were replaced with items having no relation. Two lists were created such that each target had a same modality context in one list but a different-modality context in the other. Thus each target item appeared with both same-modality and different-modality contexts, counterbalanced across lists. All critical properties were true of their respective concepts.The experimental trials included 150 pairs, with 50 being critical, for a total of 300 trials. The remaining 100 pairs were fillers, designed to mask the nature of the experiment. Within the filler pairs, 50 contained two false items, 25 contained a true item then a false item, and 25 contained a false item then a true item. Thus true and false responses were equally likely overall. Properties in the fillers sometimes referred to a specific modality but also referred to properties that are represented on multiple modalities (e.g., CAMERA-compact, TOY-plastic, MAP-complicated). To ensure that subjects actually verified the properties of concepts (Solomon & Barsalou, 2002), the concept and property in many false items were related (e.g., OVEN-baked, BUFFALO-winged, BUTTERFLY-bird). The critical and filler pairs were randomly intermixed for each subject. All concepts and properties were used only once. The practice trials consisted of 24 true items and 24 false items, similar in nature to the experimental trials.Procedure. Each trial began with a fixation stimulus (* * * * *) two lines above where the concept name would appear. After 500 ms, the fixation stimulus disappeared. In the 0 ms SOA condition, three lines of text appeared aligned vertically, each two lines apart. The first line contained the concept word in upper case; the second line contained the words “can be” in lowercase; the third line contained the property word in upper case. In the 260 ms SOA condition, the concept word appeared for 160 ms, then “can be” was added for 100 ms, then the property name was added. RTs in all cases were measured from the onset of the property word. All lines remained on the screen until the subject made a "true" (?/ key) or "false" (z key) response.The initial instructions stressed that a decision should be based on whether the property was "usually true" of the concept. For example, the pair CARNATION-black could theoretically be true, but black would be a highly unusual property for CARNATION. Therefore, the correct response for such a property was "false". Subjects received feedback for 600 ms after pressing the wrong key (“ERROR”) or after taking 2000 ms or longer to respond (“TOO SLOW”). The next trial began 300 ms after the response, or in the case of feedback, 300 ms after the feedback disappeared. Because subjects responded to each item individually, nothing indicated that items were paired in the underlying design. Also, becauseonly 1 of every 12 trial transitions contained properties from the same modality, it was not obvious that modality switching was of interest.The experiment began with 48 practice trials, followed by the 100 critical and 200 filler trials in a different random order for each subject. After each block of 50 trials, subjects took a brief break and saw the percentage of errors from the previous block. When errors exceeded 15%, subjects were urged to be more accurate. When errors fell below 5%, subjects were complimented. When ready, subjects began the next block.Results and DiscussionRTs were removed for target trials on which errors occurred. Target RTs were also removed when subjects erred on the previous context trial, given that an assessment of modality switching assumes that subjects processed both the context and target items correctly. When subjects erred on a context trial, a variety of complicating factors could affect processing on the target trial. Medians for same-modality versus different-modality RTs on target trials were computed for each subject and then averaged.-----------------------------------------------Insert Table 2 about here-----------------------------------------------As Table 2 illustrates, RTs on the target trials were slower when the modality switched from the context trial to the target trial than when modality remained constant,F(1,62)=6.87, p<.05. Although the switching effect was slightly larger in the 0 ms SOA condition than in the 260 ms SOA condition (29 ms vs. 20 ms), the interaction between SOA and switching was not significant, F(1,62)=0.24. No effects occurred for errors, indicating that a speed-accuracy tradeoff was unlikely.The effect of SOA was significant, F(1,62)=56.12, p<.01. Subjects in the 260 ms SOA condition were 270 ms faster than subjects in the 0 ms SOA condition. The near equivalence between the difference in RTs and the difference in SOAs indicates that subjects in the 260 ms SOA condition began task-relevant processing immediately on receiving the concept in isolation. By the time the property arrived, these subjects were further into the necessary processing than the 0 ms SOA subjects. Most importantly, however, the effect of modality switching occurred for both groups.We began with the hypothesis that modality-specific brain areas represent properties in concepts. Based on this assumption, we predicted that switching modalities while verifying properties would incur a processing cost, analogous to the cost incurred while switching modalities in perceptual processing. Unlike perceptual studies, however, the switching costs here occurred while subjects processed linguistic stimuli, not perceptual ones. This suggests that the linguistic stimuli initiated sensory-motor simulations, which behaved similarly to sensory-motor processing.Experiment 2An alternative explanation remains to be addressed. Perhaps properties across all modalities are stored together in a single system of amodal knowledge. Within this system, amodal symbols that represent properties from the same modality are associated to each other, such that they prime each other when processed sequentially. If so, then these associations could underlie the switching costs in Experiment 1. When a subject verifies two properties from the same modality, associations between their amodal symbols speed processing, relative to properties from different modalities whose symbols are not associated.As already noted, the critical property pairs in Experiment 1 were not associated in the Nelson et al. (1999) norms. Perhaps, however, these norms are not sufficiently sensitive to detect weak associations that link properties from the same modality. This hypothesis can be tested by using highly associated property pairs from the Nelson et al. norms. If non-measurable associations speed same-modality pairs whose normed strengths are 0, then even greater priming should occur as associative strength increases.Thus Experiment 2 sampled pairs of properties from the Nelson et al. norms that are highly associated (e.g., spotless-clean; polyester-cheap). These associated properties were then combined with concepts to form pairs of verification trials (e.g., “SHEET can be SPOTLESS”—“AIR can be CLEAN”; “SHIRT can be POLYESTER”—“MEAL can be CHEAP”). If the associative hypothesis is correct, then substantial priming should be found for the second members of these pairs, relative to when the context and target items have unassociated properties (e.g., “SHEET can be SPOTLESS”—“MEAL can be CHEAP”).In contrast, we did not predict an associativeness effect. Many previous studies have found that priming diminishes substantially—and typically disappears—when an unrelated word separates two associated words (Bentin & Feldman, 1990; Dannenbring & Briand, 1982; Joordens & Besner, 1992; Masson, 1995; McNamara, 1992). Given that three words stood between properties on adjacent trials in Experiment 1, it seems unlikely that the first property could have primed the second associatively. For example, in “SHEET can be SPOTLESS” followed by “AIR can be CLEAN”, the three words “AIR can be” lie between “SPOTLESS” and “CLEAN”. We expected that these intervening words would extinguish any possible priming.3In addition to the strongly associated properties, we also presented pairs of unassociated properties from the same vs. different modalities (a replication of Experiment 1). First, we wanted to replicate the modality shifting effect in another experiment. Second, we wanted to directly compare this effect with any associative priming effect. Because highly associated properties are necessary for testing the associativeness effect, whereas unassociated properties are necessary for testing the modality-switching effect, different property pairs were used to test the two effects.MethodSubjects and design. Eighty-eight volunteers from Emory University participated for course credit. Associated versus unassociated pairs were manipulated within subjects, as were same vs. different modalities, with counterbalanced versions of the list being distributed equally across subjects.Materials. Thirty pairs of associated properties were selected from the Nelson et al. (1999) norms that averaged 23.1% in associative frequency (i.e., how often the second property was produced as an association of the first). This is a very high level of associative strength, with approximately 95% of the words in the norms having a lower first associate (Nelson, personal communication). The first property in a pair was always the cue in the norms, and the second property was always a response. The introduction to this experiment provides examples.Two critical lists were formed from the 30 pairs of associated properties. In one list, 15 of the associated pairs remained intact, and the other 15 were scrambled to form unassociated pairs (as illustrated in the introduction). In the other list, the first 15 pairs were scrambled to form unassociated pairs, whereas the second 15 pairs remained intact to form associated pairs. All critical items were true.An additional 30 pairs of trials were selected from the materials of Experiment 1. Two lists were created so that each list contained 15 pairs from the same modality and 15 from different ones. For the same pairs, the associative strength between properties was 0. Across lists, each concept-property combination occurred in both conditions.An additional set of 120 filler pairs was constructed. Within these fillers, 60 contained 2 false items, 30 contained a true item then a false item, and 30 contained a false item then a true item. Fifteen of the false target items were associatively related to the previous trial, and 15 were in the same modality as the previous trial. Thus, the relation between two consecutive trials was not predictive of the correct response for targets. Subjects could not give a "true" response on the basis of the context item being associated or in the same modality as the target. The remaining 90 filler pairs were unrelated. The practice materials consisted of 48 additional trials that were comparable to the experimental materials. No concept or property was repeated across the materials.Procedure. The 0 ms SOA procedure from Experiment 1 was used here.Results and DiscussionAs in the previous experiment, target trials were removed either when subjects erred in response, or when they erred on the previous context trial. Median RTs in the relevant conditions were computed for each subject and then averaged.-----------------------------------------------Insert Table 3 about here-----------------------------------------------As Table 3 illustrates, an associative priming effect did not occur in the RTs,F(1,87)=0.016, or in the errors, F(1,87)=0.22. Unassociated properties were not reliably slower than associated properties, indicating that associations between properties did not underlie the switching effect in Experiment 1. Indeed, these two condition differed by only 1ms. In contrast, the RTs on the different modality trials were 41 ms slower than those on the same modality trials, F(1,87)=9.40, p<.01. The difference between associative priming and modality switching was nearly significant in the two-way interaction, F(1,87)=3.76, p=.056. The error data did not show any significant effect.4As these results show, associative strength does not explain the switching costs in Experiment 1. If associations between properties from the same modality had been responsible, an associative effect should have occurred in Experiment 2, given that the property pairs were much more associated than those in Experiment 1. Instead, no associative priming effect was obtained, whereas there was again a reliable effect of modality switching. This leaves modality-specific processing as the best account of the switching costs. After verifying a property, attention rests on its modality. If the subsequent property resides on a different modality, attention must shift, thereby incurring a cost.General DiscussionAccording to perceptual symbols theory (Barsalou, 1999), simulations in sensory-motor areas represent properties during conceptual processing. If the conceptual system rests on sensory-motor systems, then phenomena in perceptual processing should also occur in conceptual processing, at least to some extent. Thus, the presence of switching costs in perceptual processing suggests that analogous switching costs should occur during property verification.The results of Experiments 1 and 2 support this prediction. When subjects verified pairs of properties, they verified the second property faster when it came from the same modality as the first property than when it came from a different modality. Experiment 2 ruled out the alternative hypothesis that associations between properties from the same modality were responsible. When subjects verified a pair of associated properties, no priming occurred, even though the associations between them were considerably stronger than any associations that might have existed between properties from the same modality in Experiments 1 and 2. Thus, switching from one modality-specific brain system to another appears to be the critical factor in these experiments—not associative strength. Recent neuroimaging work on the localization of concepts corroborates this conclusion (e.g., Martin,2001; Martin & Chao, 2001; Martin et al., 2000), as does the literature on lesion-based conceptual deficits (e.g., McRae & Cree, in press; Simmons & Barsalou, 2002). Recent fMRI work in our lab shows that verifying the six types of properties assessed in Experiments 1 and 2 activates the respective modality-specific neural systems (Pecher, Hamann, Simmons, Zeelenberg, & Barsalou, 2002).One issue is the generality of the modality-shifting effect. Within the experiments reported here—and subsequent ones like them—all six modalities generally exhibit trends in the predicted direction (due to the noisiness of the data and the small number of properties on each modality, individual trends are rarely significant). Across four replications of the basic paradigm—an unpublished initial experiment, Experiment 1 (SOA=0), Experiment 1 (SOA=260), and Experiment 2—the mean differences between the same-modality RTs and the different modality RTs were: 37, 28, -7, 65 for vision; 42, -2, -38, 43 for audition; 48, 48, 20, 39 for motor; 86, 59, 104, -18 for smell; 10, 32, 100, 10 for taste; -10, 42, -20, -34 for touch. In a given experiment, not every modality shows a trend, but across experiments, each modality shows one at least once.5A related issue is whether modality shifting effects occur for properties that do not come from the six modalities we address, such as the properties of abstract concepts. Barsalou (1999) suggests that abstract concepts draw heavily on introspective experience, such as emotional states and cognitive operations. Wiemer-Hastings, Krug, and Xu (2001) provide evidence for this hypothesis. To the extent that other sorts of properties arise on different modalities of experience, shifting effects should occur between them as well. For example, if emotion and cognitive operations constitute different domains of introspection, they might exhibit shifting effects. This issue awaits further research.Together with other recent evidence, the findings here converge on the conclusion that the conceptual system is grounded in sensory-motor simulation. It is becoming increasingly difficult to argue that the conceptual system is completely modular and amodal. To the contrary, the conceptual system appears to share many mechanisms with perception and action, thereby making it non-modular and modal.ReferencesBarsalou, L. W. (1999). Perceptual symbol systems. Behavioral & Brain Sciences, 22, 577-660.Barsalou, L. W. (in press). Situated simulation in the human conceptual system. Language and Cognitive Processes.Bentin, S., & Feldman, L. B. (1990). The contribution of morphological and semantic relatedness to repetition priming at short and long lags: Evidence from Hebrew.Quarterly Journal of Experimental Psychology, 42A, 693-711.Dannenbring, G. L. & Briand, K. (1982). Semantic priming and the word repetition effect in a lexical decision task. Canadian Journal of Psychology, 36, 435-444.Fodor, J. A. (1975). The language of thought. Cambridge, MA: Harvard University Press. Glenberg, A. M. (1997). What memory is for. Behavioral and Brain Sciences, 20, 1-55. Joordens, S., & Besner, D. (1997). Priming effects that span an intervening unrelated word: Implications for models of memory representation and retrieval. Journal ofExperimental Psychology: Learning, Memory and Cognition, 18, 483-491. Klatzky, R. L., Pellegrino, J. W., McCloskey, B. P., & Doherty, S. (1989). Can you squeeze a tomato? The role of motor representations in semantic sensibility judgements. Journal of Memory and Language, 28, 56-77.Martin, A. (2001). Functional neuroimaging of semantic memory. In. R. Cabeza & A.Kingstone (Eds.), Handbook of functional neuroimaging of cognition (pp. 153-186).Cambridge, MA: MIT Press.Martin, A., & Chao, L. (2001). Semantic memory and the brain: structure and process.Current Opinion in Neurobiology, 11, 194-201.Martin, A., Ungerleider, L. G., & Haxby, J. V. (2000). Category-specificity and the brain: The sensory-motor model of semantic representations of objects. In M. S. Gazzaniga (Ed.), The new cognitive neurosciences (2nd ed., 1023-1036). Cambridge, MA: MIT Press. Masson, M. E. J. (1995). A distributed memory model of semantic priming. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 3-23.McNamara, T. P. (1992). Theories of priming: I. Associative distance and lag. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 1173-1190. McRae, K., & Cree, G. S. (in press). Factors underlying category-specific deficits. In E.M.E.Forde & G.W. Humphreys (Eds.), Category specificity in mind and brain. London:Psychology Press.Nelson, D. L. (personal communication). January, 23, 2002.Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (1999). The University of South Florida word association, rhyme and word fragment norms./FreeAssociation/ .Pecher, D., Hamann, S. B, Simmons, W. K., Zeelenberg, R., & Barsalou, L. W. (2002). fMRI evidence for modality-specific conceptual processing in six modalities. Manuscript in preparation.Pulvermüller, F. (1999). Words in the brain's language. Behavioral and Brain Sciences, 22, 253-336.Pylyshyn, Z. W. (1984). Computation and cognition. Cambridge, MA: MIT Press. Simmons, K., & Barsalou, L. W. (2002). The similarity-in-topography principle: Reconciling theories of conceptual deficits. Invited article to appear in a special issue of Cognitive Neuropsychology.Solomon, K. O., & Barsalou, L. W. (2001). Representing properties locally. Cognitive Psychology, 43, 129-169.Solomon, K. O., & Barsalou, L. W. (2002). Perceptual simulation in property verification.Under review.Spence, C., & Driver, J. (1998). Auditory and audiovisual inhibition of return. Perception & Psychophysics, 60, 125-139.Spence, C., Nicholls, M. E. R., & Driver, J. (2000). The cost of expecting events in the wrong sensory modality. Perception & Psychophysics, 63, 330-336.Spivey, M., Tyler, M., Richardson, D., & Young, E. (2000). Eye movements during comprehension of spoken scene descriptions. Proceedings of the 22nd AnnualConference of the Cognitive Science Society, (pp.487-492). Mahwah, NJ: Erlbaum.。
英文科技论文写作 第三课. Authorship,Authors By-line & Address
Workshop 3: Authorship, Author By-line & Names & AddressIntroductionIn today’s workshop we consider the vexed question of authorship. Who should be included as an author on your paper? Or alternatively, what contribution is required for someone to qualify as an author? We also examine issues as the order of names on a paper, the format for citing your own name on a paper and address for correspondence. These issues may seem citing trivial, but an understanding of them can prevent problems and disputes from occurring in future.Who should be an author?The part of paper that comes immediately after the title is the author’s by-line, which is a list of people who made an important contribution to the published paper. Writing this by-line is usually straight-forward, but great judgment is needed in some cases when deciding on whether someone should be included a co-author, and also the order in which the names of co-authors are cited. Dispute over a co-authorship can arise, and as pointed out by Day (1998) “reasonable, rational, colleagues can become bitter enemies solely because they could not agree on whose names should be listed or in what order.” After all the only people who never get upset about authorship are the people who do not publish papers!Comprehensive guidelines on authorship are published by the International Committee of Medical Journal Editors (). This organization states that:“Each author should have participated sufficiently in the work to take public responsibility for appropriate portions of the content.”Failure to take responsibility for the content of a paper is important as the following editorial in Nature points out: “Few would dispute that researchers have to take responsibility for papers that have their names on them. A senior laboratory figure who puts his or her name on a paper without direct supervision or involvement is unquestionably abusing the system of credit. There have been occasions where distinguished scientists have put their names irresponsibly on a paper that has turned out to contain serious errors or fraud. Rightly some of them have paid a heavy price.”(Anon 1997)Criteria for co-authorshipThe International Committee of Medical Journal Editors state that “one or more authors should take responsibility for the integrity of the work as a whole from inception to published article.”Agreement on who this person is should be reached before embarking on a piece of research. The International Committee of Medical Journal Editors defines an author using the following criteria (see /ethical 1author.html):(1)Substantial contributions to conception and design, or acquisition of data, or analysis andinterpretation of data.(2)Drafting the article of revising it critically for important intellectual content.(3)Final approval of the version to be published.All the three criteria must be met, according to the International Committee of Medical Journal Editors before someone can qualify as an author. This organization does not consider the following contributions as giving someone the right to be an author:(1)Acquisition of funding.(2)Collection of data (technical help of a routine nature).(3)General supervision of research group or student.(4)Writing assistance of a routine nature.Many people consider the aforementioned guidelines as too restrictive. In particular some feel that they undervalue the contributions of skilled technicians (see below). Furthermore, the guidelines do not specify what should be considered as a substantial intellectual contribution to the research (criteria 1). To overcome this problem and to make it easier to come to a judgment about who should be an author on a paper some professors have developed criteria for authorship that weight the different criteria and assign points to each criterion. The decision on whether to include a person as an author on a paper is then based upon whether they reached a minimum point score, for example 10% of the total points allocated to all criteria. For example, Kosslyn (2002) allocated 1000 points to the following 6 criteria:(1)The idea (250 points)(2)Experimental design (100 points)(3)The implementation; translating experimental design into instructions and ensuring thatexperimentation proceeds according to the design (100 points)(4)Conducting the experiment (100 points)(5)Data analysis (200 points)(6)Writing (250 points)A person achieving 100 points is granted co-authorship. Kosslyn’s guidelines can be found at /fs/docs/icb.topic562342.files/authorship_criteria_Nov02.pdf.Technician & statistician as co-authors?Kosslyn (2002) stated that the key to fair allocation of authorship and equitable ordering is to have criteria that are known to all and that all can discuss. These should be agreed upon and discussed before starting any research that could lead to the publication of a paper. Both the guidelines published by the International Committee of Medical Journal Editors and those written by Kosslyn (2002) emphasize the intellectual contributions to the published paper. Simply carrying out research work under instruction is deemed by many to be insufficient for co-authorship. Hence, a technician who carries out research for a paper can in theory be excluded as a co-author. However, in many cases technicians modify experimental procedures to make them better or more efficient, or they are involved in the generation of research questions as a result of making original observations during the course of doing practical research. Such inputs are important intellectual contributions for any piece of research and certainly qualify technicians for co-authorship. Hence, technicians are often co-authors on a paper. There has also been debate in the scientific literature about whether statisticians involved in research should be granted co-authorship. The answer to this question is much more straight-forward than the question of whether to grant a technician co-authorship. Statisticians should always be granted co-authorship if they are involved in thedesign or analysis of experiments. Good experimental design and correct and efficient analysis and interpretation of data are the hallmarks of high quality scientific research. Statisticians can ensure that your research has these qualities, but they are unlikely to become involved if their contributions are relegated to the acknowledgement section of a paper. Statisticians understandably become quite annoyed when their contributions to papers are undervalued as the following abstract of a letter in the British Medical Journal points out (Mullee et al. 1995):“Statisticians should be co-authors”“EDITOR, -Neville W Goodman outlines criteria for authorship of published material. Medical research is often, by its nature, multidisciplinary, and frequently the authorship or papers reflects this. As statisticians we find that analysis is rarely just a “simple manipulation on a computer” but involves a great deal of time and care from the study’s design stage, through checking of the data and statistical analysis to presentation of the results. The application of “standard statistical tests”does not necessarily imply that the analysis was straightforward; it may imply that more complicated methods of analysis, which are often less easy to interpret, were considered to be inappropriate. We therefore believe that statistic ians’contribution to medical research should generally be recognized through co-authorship and not simply through their receiving credit for what they have done and nothing more.”Guest authorshipThe inclusion of a person’s name on a paper in the author’s by-line implies that they have made an important contribution to the work being reported. A guest author is a person who has not made an important contribution to a paper, but nevertheless is included as a co-author. Guest authorship can arise for a number of reasons. Firstly, many scientists are not aware that material support, general supervision or simple editing does not qualify them for co-authorship, and insist that they receive co-authorship to which they are not entitled. Some scientists may be aware that their contributions do not entitle them to co-authorship, but nevertheless insist on co-authorship to inflate their publication record. Such dishonest practice has been encouraged by administrators of universities who equate research productivity and quality with numbers of papers and provide incentives (tenure, promotion and merit awards) for scientists based on the number of papers they have authored. Faculty members of University Departments who sit on review panels are aware of this problem and look quite closely at the records of people who appear as co-authors on papers that lie outside of their main field of research or who publish large numbers of paper without appearing as first author on many of them. In such cases it may be necessary to clarify the authors’contribution to some of the papers to remove any suspicion that they have accepted guest authorship. Most good scientists are too honest to accept guest authorships, now would they grant guest authorships, as they are aware that such practice dilutes and undervalues the contributions of co-authors who have made substantial contributions to published work. In some societies, however, there is strong pressure on researchers to grant co-authorship to the head of their laboratory. Failure to follow this practice would lead to the termination of their research contract. Therefore, it is understandable that many of them comply by granting co-authorship to the head of their laboratory. Most scientists, however, are aware of the countries in which such practices is common and discount the contribution of the head of the laboratory, which is unfortunate because that person may actually deserve co-authorship.Contributors listTo fairly assign credit to authors and overcome problems such as guest authorship many journals are now including a contributors list. To contributors list is a section included at the end of a paper (or submitted to the journal), which lists the authors and describes their contributions to a paper. The contributors list serves two purposes; Firstly, it makes the practice of guest authorship more difficult as the editor of a journal is able to evaluate the contributions of each author. Secondly, the contributors list allows the reader to identify the people to contact to obtain more information on a particular area of interest to them or request samples or reagents. The contributors list should not be too detailed. Here is an example of a contributors list from a paper in Nature Nanotech (Peng et al 2008).Author contributions“H.E. conceived and designed the experiments. B.P. and S.L. performed the experiments. H.E., P.Z., G.S. and M.L. conceived the simulations. All authors analyzed the data. S.M. contributed analysis tools. All authors discussed the results and co-wrote and commented on the manuscript.B.P. and M.L. contributed to this work.”Even if the journal that you are submitting your paper to does not a contributors list, it is a good idea to develop one with your co-author(s) and include it in the letter you write when you submit the paper to a journal. The editor of the journal will be pleased to have such information and it may encourage him/he to adopt the idea of a contributors list.Order of authorsAs pointed out by Day (1998) the sequence of authors on a published paper “should be decided before the research commences, and it is foolish to leave this question to the end of the research.”A number of conventions are used to denote the relative importance of authors’ contributions to a published paper:(1)List authors in order of importance to the experiments, the first author being the senior author,the second author the primary associate etc.(2)First and last author’s spots have seniority with the first spot representing the senior author,(usually the person who had the greatest experimental contributions to the paper), and the last position allocated to the person (usually a senior scientist) who conceived of the study.Between these two positions the order of scientists is listed according to their relative contributions.(3)As above for 1 or 2, but a scientist can receive recognition equivalent to that of the seniorauthor by marking the authors names with a superscript to a footnote or subheading that indicates that the authors made equal contributions to the work.(4)As an alternative to 3 a subheading or footnote can be used to indicate that all authorscontributed equally to the work or the published paper.(5)In some fields such as mathematics it is common for authors to be listed alphabetically,presumably to avoid conflicts over author’s credit.The first position in the author’s by-line is known as the senior author and certainly carries moreprestige than other authors’ positions in the by-line. Most people would agree that the first author has made the largest contribution to the publication of research work and if there are two people with equivalent publication records in terms of number of papers and the quality of journals they have published in, then the person who has authored more papers as a senior author will be regarded as having the superior publication record. For this reason it is quite important for junior scientists seeking their first appointment or tenure or promotion to author papers as a senior author rather than act as a co-author on papers, particularly if the other co-authors are more senior faculty.All people listed as co-authors on a paper should agree to be co-authors and you should resist requests for guest authorship (as discussed above). Even though scientists may agree to be co-author on a paper, it is unlikely, as mentioned by Gustavii (2003), that they will be happy with their position/ranking within the by-line because many authors tend to overestimate their own particular contribution to a paper.NamesThe citing of people’s names within the authors by-line usually follows the following convention: First name (in full), middle initial and surname (in full). The middle name is not spelled out in full because it could lead to confusion about whether it is part of the surname i.e., Callum B. Evans, rather than Callum Bowen Evans (Bowen being a surname).Whenever possible a scientist should try to cite his/her name in the same way on every paper they publish so that search engines such as Web of Science will retrieve all of the published work. therefore, avoid the temptation to shorten your first name (Barb instead of Barbara or Phil instead of Philip) and always include your middle initial, if you have one. Certain situations can lead to inconsistencies in the citing of people’s names on papers. Foremost amongst these are a change of name resulting from marriage or divorce and re-marriage. This type of inconsistency only affects women and can be avoided if female scientist retain their maiden names. Scientists from China who work in the West often adopt an English name and inconsistencies can arise if they first publish using their Chinese name, for example, N.S. Hon and then when they move to the West subsequently prefix their Chinese initial(s) with the initial of a English name such as David (D.N.S. Hon). Inconsistencies in the citing of people’s names can make it difficult to easily retrieve a person’s publication record using the Web of Science. The same is true of people with very common names as John Smith or Philip Evans! Fortunately, the inc lusion of a subject are, journal titles and institutional details in the search can usually result in the retrieval of most of a person’s publication record.AddressesThe listing of authors’ addresses below the authors by-line on a paper can be straightforward if the scientist who published the paper worked at one institution. Even if they work at different institutions then their affiliations can be indicated with a superscript (1, 2, 3 or a, b, c) after their names. Sometimes scientists move institutions and their new address can be indicated in a footnote such as Present Address. A scientist may occasionally be affiliated with two institutions or publish work that was done in two different institutions. In such a situation their names maycarry two superscripted symbols to indicate affiliation with two institutions. In some countries institutional funding provided by government is linked to the numbers of papers published and hence it is important to indicate if work was done in an institution in that country. The address and email is important because if allows scientist to contact authors about the published work (see also comments above about the role of the corresponding author).ReferencesAnon. (1997). Games people play with author’s name. Nature 387(6636): 831Day, R.A. (1998). How to write & publish a scientific paper (5th Edition), Oryx Press, Westport C T.Gustavii, B. (2003). How to write and illustrate a scientific paper. Cambridge Univ Press, Cambridge.Mullee, M.A., Lampe, F.C., Pickering, R.M., Julious, S.A. (1995). Statisticians should be co-authors. British Medical Journal. 310: 869.Peng, B., Locascio, M., Zapol, P., Li, S., Mieke, S.L., Schatz, G.C., Espinosa, H.D. (2008). Measurements of near-ultimate strength for multi-walled carbon nano-tubes and irradiation-induced crosslinking improvements. Nature nanotechnology 3, 626-631 (2008)。
清迈大学申请表
CHIANG MAI UNIVERSITYGraduate SchoolApplication for AdmissionPLEASE TYPE OR PRINT IN BLACK INKPLAN FOR STUDYApplication for Semester First (June) Second (Nov.)Academic Year……………………………Faculty………………………………………………….Program of Study:Doctor's Degree (thesis only) Master's Degree (course works and thesis) Doctor's Degree (course works and thesis) Master's Degree (course works only)Master's Degree (thesis only) Others (please specify)Major Fiel d………………………………………………………………………………………………………………Area of Concentration (if required)……………………………………………………………………………………PERSONAL INFORMATION1. Gender : Male Female2. Family Name or Surname…………………………………………..First Name…………………………………Middle Name………………………………………………………………………………………………………… (Name In Thai) ………………………………………………………………………………………………………3. Marital Status Single Married Others……….. Number of Children………………….4. Date of Birth : Day/Month/Year……………../…………………./……………….5. Occupation…………………………………………………Position ……………………………………………..6. Country of Citizenship…………………………………..Religion ……………………………………………….7. Highest Academic Qualification Obtained…………… …………………………………………………………Major Field…………………………………….Grade Point Average/Score…………………………………….8. Address for CorrespondenceMailing address : …………………………………………………………………………………………………….………………………………………………………………………………………………………………………….Telephone or Mobile : ………………………………………………………..Fax : ………………………………Permanent address (if different form above) : ……………………………………………………………………Telephone or Mobile : …………………………...……………………..……….Fax : …………………………....E-mail………………………………………………………………………………………………………………….Address for Correspondence while Studying at CMU : ………………………………………………………….………………………………………………………………………………………………………………………….Telephone or Mobile : …………………………………………………………. Fax : …………………………….E-mail : ………………………………………………………………………………………………………………..9. Identification Document[ ] Thai national ID card Number ………………………………………………………………………………….Date of Issue …………………………………………….. Date of Expiry …………………………………..[ ] Passport Number ……………………………………………………………………………………………….Date of Issue ……………………………………………… Date of Expiry ………………………………….SCHOLARSHIP : particularly for those who get scholarship support or would like to apply for scholarshipI would like to apply for a scholarshipI have a sponsor from …………………………………………….……………………………………………..(please attach documentation)DETAILS OF OTHER QUALIFICATION HELD(e.g.Membership of professional bodies, certificates held) ………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………BRIEF DESCRIPTION OF PROFESSIONAL EXPERIENCE…………………………….…………………………….……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….………………………(Please attach additional page if more space is needed)ENGLISH LANGUAGE PROFICIENCYCertificate of English proficiency held by the applicant:TOEFL IELTS TEGSOther (please specify)…………………………………………………………………………. Date taken or to be taken …………………………………..Score………………………………………………….. (please attach documentation)RESEARCH OUTLINE FOR THE PROGRAM APPLIED FOR (if applicable)Please attach a statement of about one page of you research outline, previous research experience and research work presented at meetings and/or published (if any) to date.REFEREESPlease list names and addresses of three referees who are of senior status and familiar with the applicant's background and capability. One of these referees should be the applicant's direct supervisor.1. Name…………………………………………………..Position……………………………………………………Address………………………………………………………………………………………………………………………………………………………………………………………………………………………………………..2. Name…………………………………………………..Position……………………………………………………Address………………………………………………………………………………………………………………………………………………………………………………………………………………………………………..3. Name…………………………………………………..Position……………………………………………………Address………………………………………………………………………………………………………………………………………………………………………………………………………………………………………..Please inform your referees to send their confidential letters of reference describing your suitability in sealed envelopes addressed directly to the Graduate School by the announced deadline.I certify that my statements made above are correct and complete to the best of my knowledge.Applicant's Signature …………………………………………………..(………………………………………………….)Date ………………………………………………….Before sealing the envelop, please check again if the following documents are enclosed. If an item is sent later and not part of your application package, consideration of your application can be delayed, perhaps up to one year.[ ] Two completed an Application Form;[ ] Official transcript(s) (in English);[ ] copy of degree certificate(s) (with English translation);[ ] two 2.5 cm, full-face photographs, less than 3 months old (affixed in the application form);[ ] TOEFL score or other English certificate;[ ] Research outline (if any);[ ] application fee (20 US$ in case if you are Thai citizen pay only 900 Bath)LETTER OF RECOMMENDATIONTo be completed by the applicant before submitting this form to the refereeName of applicant………………………………………..………………………………………………………………….. Major field of study applied for……………………….………….………………………………………………………….. Faculty…………………………………………….……..…Semester………………..Academic Year……………………Program of StudyDoctor's Degree (thesis only) Master's Degree (course works and thesis)Doctor's Degree (course works and thesis) Master's Degree (course works only)Master's Degree (thesis only) Graduate DiplomaOthers (please specify)…………………..Area of Concentration of Option (if required)……………………………………………………………………….To be completed by the refereeTO THE PERSON EVALUATING THE APPLICANT:The person whose name appears above is applying for admission to the program indicated above at Chiang Mai University. In considering the applicant, particular emphasis is placed on comments from people the applicant has chosen as referees. Your prompt submission of this form will be most helpful as the applicant cannot be considered without your comments.The Admission Office of the Graduate School realizes that considerable time and effort is involved in preparing this evaluation. Your assistance in giving this appraisal is greatly appreciated.Name of person completing this form…………………………………………………………………………………Position/Title………………………………………………………………………………………………………………Organization………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………Address………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….…………………TEL…………………………………How long have you known the applicant? …………………Years …………………………………….Months You have known the applicant as a/an: undergraduate student graduate studentresearch assistant teaching assistantemployee in other capacities (please specify)……………………………………….. You have served as the applicant's division/dept,/school head research supervisorteacher in several classes employerteacher in only one class immediate superior in the organizationin other capacities (please specify)……………………………………….Do you feel graduate study is appropriate for the applicant at this time? Why?In comparison with other graduate school candidates that you have known, how would you rate the applicant with respect to the following qualities:What is your candid opinion of the applicant's chances of completing the program applied for, considering; intellectual capacity, promise of productive scholarship, and potential for research; relative standing among contemporary graduates; ability to follow a course in which the medium of instruction is English; and practical experience, if any, in the chosen area of study?If the applicant has applied for financial aid, which is awarded competitively, please state any outstanding qualities of the applicant including scholastic performance, leadership, personality, and potential for contributing to the development of his/her country, that would justify selection against other well qualified applicants.You, therefore strongly recommend that this applicant be admitted torecommend the applied program at CMU.recommend with some reservationdo not recommendSignature DatePlease return by AIRMAIL DIRECTLY toDeanThe Graduate SchoolChiang Mai UniversityChiang Mai 50200ThailandInquiries: Phone and Fax : (6653) 942422E-mail : suthalee@chiangmai.ac.th。
业务信函格式作文英语模板
业务信函格式作文英语模板Title: Business Correspondence Format and Template。
In the realm of professional communication, business correspondence holds paramount importance. Whether it's drafting a formal letter, an email, or a memo, adhering toa structured format is crucial for clarity, professionalism, and efficacy. Here, we delve into the fundamental elements and conventions of business correspondence, along with a comprehensive template to guide you through crafting effective communication.1. Address and Date:Begin your correspondence with the sender's address, typically aligned to the right side of the page. Followthis with the date of writing, placed a few lines below the address. The date format varies based on location, but the month-day-year format (e.g., April 18, 2024) is commonly accepted.2. Recipient's Address:Directly beneath the date, provide the recipient's address, aligned to the left side of the page. Include the recipient's full name, title, company name (if applicable), and complete postal address. Ensure accuracy and completeness to facilitate smooth delivery.3. Salutation:Next, initiate the correspondence with an appropriate salutation. Use the recipient's title and last name (e.g., Dear Mr. Smith) if known. If unsure about the recipient's gender or name, opt for a generic salutation such as "Dear Sir/Madam" or "To Whom It May Concern."4. Body:The body of the correspondence comprises the main message. Maintain a clear and concise writing style, focusing on conveying the intended information effectively.Organize the content into paragraphs, each addressing a specific point or topic. Use formal language and avoid jargon or colloquialisms that may obscure the message.5. Closing:Conclude the correspondence with a courteous closing remark. Common closings include "Sincerely," "Yours faithfully," or "Best regards," followed by the sender's name and, if applicable, their title or position within the organization.6. Signature:If the correspondence is printed and mailed, leave space for the sender's handwritten signature above their typed name. In digital communications, a typed name suffices, accompanied by any relevant contact information such as phone number or email address.7. Subject Line (for emails):For email correspondence, include a concise and descriptive subject line summarizing the message's content.A clear subject line facilitates efficient email management and ensures the recipient understands the purpose of the communication at a glance.Business Correspondence Template:[Sender's Address][City, State, Zip Code][Email Address][Phone Number][Date: Month Day, Year][Recipient's Name][Recipient's Title/Position][Company Name (if applicable)][Recipient's Address][City, State, Zip Code]Dear [Recipient's Title] [Recipient's Last Name],。
address做处理意思用法
address做处理意思用法
"address" 这个词可以有多种不同的意思和用法，下面是其中一些常见的例子：
1. 地址（n.）：表示一个人、公司或地点的准确位置。
- Please provide your address for delivery.
（请提供您的地址以便进行配送。
）
2. 处理（v.）：表示处理或解决问题，通常指采取某种行动或方法来解决困难或复杂的事情。
- We need to address the issue of pollution in our city.
（我们需要解决我们城市的污染问题。
）
3. 称呼（v.）：表示以某种方式称呼某人，通常用于正式或礼貌地与他人交谈。
- Please address me as Mr. Smith.
（请称呼我史密斯先生。
）
4. 商店（n.）：表示公司或组织的总部或主要营业地点。
- The company's main address is in New York City.
（该公司的总部地址位于纽约市。
）。
Address for correspondence
Jointly published by Akadémiai Kiadó, Budapest Scientometrics, Vol. 70, No. 1 (2007) 3–26 and Springer, DordrechtStandardizing formats of corporate source dataC ARMEN G ALVEZ, FÉLIX M OYA-A NEGÓNScimago Research Group, Department of Information Science, University of Granada, Granada (Spain) This paper describe an approach for improving the data quality of corporate sources when databases are used for bibliometric purposes. Research management relies on bibliographicdatabases and citation index systems as analytical tools, yet the raw resources for bibliometricstudies are plagued by a lack of consistency in fied formatting for institution data. The presentcontribution puts forth a Natural Language Processing (NLP)-oriented method for theidentification of the structures guiding corporate data and their mapping into a standardizedformat. The proposed unification process is based on the definition of address patterns and theensuing application of Enhanced Finite-State Transducers (E-FST). Our procedure was tested onaddress formats downloaded from the INSPEC, MEDLINE and CAB Abstracts. The resultsdemonstrate the helpfulness of the method as long as close control of errors is exercised as far asthe formats to be unified. The computational efficacy of the model is noteworthy, due to the factthat it is firmly guided by the definition of data in the application domain.IntroductionThe general aim of this paper is to present a procedure for improving the data quality of the institutional address field when using databases. Data quality is a complex concept governed by multiple dimensions (completeness, correctness, currency, interpretability, and consistency) and may even depend on a number of rather subjective Received February 3, 2006Address for correspondence:C ARMEN G ALVEZScimago Research Group, Department of Information ScienceUniversity of Granada, 18071 Granada, SpainE-mail: cgalvez@ugr.es0138–9130/US $ 20.00Copyright © 2007 Akadémiai Kiadó, BudapestAll rights reservedC. G ALVEZ, F. M OYA-A NEGÓN: Standardizing corporate source datavariables, often influenced by the context where data are used and also by specific users within a given context (C ATARCI, 2004). In the case of research evaluation, databases provide information that is essential for bibliometric purposes. The results of quantitative studies are known to be determined by the quality of data, both within and across databases; yet quality control of data is still an issue (S HER et al., 1966;H AWKINS, 1977; 1980; G ARFIELD, 1979; 1983a, b; W ILLIAMS& L ANNOM, 1981; P ITERNICK, 1982; S TEFANIAK, 1987; A NDERSON et al., 1988; L EYDESDORFF, 1988; M OED& V RIENS, 1989; D E B RUIN& M OED, 1990; B OURKE& B UTLER, 1996;I NGWERSEN & C HRISTENSEN, 1997; H OOD & W ILSON, 2003; V AN R AAN, 2005).Many problems arise from the fact that most databases are primarily designed for the purpose of information retrieval, but not for secondary use, as in informetric research (H OOD & W ILSON, 2003). Something similar can be seen in digital libraries, where these document repositories are used as a platform for bibliometric research (C UNNINGHAM, 1998). The main limitation commonly seen in conjunction with the use of databases is a lack of unification, with one same ‘object’ having different names (M OED, 1988). While this phenomenon can appear within a single database, it is even greater if a number of databases are merged (B RAUN et al., 1995; F RENCH et al., 2000). The principle shortcomings for bibliometric applications stem from:ck of consistency in author, journal, and institution names.ck of consistency in field formatting for author, journal, and institutiondata.The present study is dedicated to the second problem,*and aims to develop a procedure that resolves the lack of uniformity in field formats, with an eye to establishing regularity in the way name data are structured in corporate sources. Such tools are indeed key for smoothing out the process of normalizing author affiliation for bibliometric analyses, because corporate source data of poor quality have enormous repercussions for collaboration indicators, the delimitation of scientific fields and evaluative scientometrics. In a continued effort to improve the bibliometic data-system, the Leiden Centre for Science and Technology Studies (CWTS) has developed a computerized and manual procedure for cleaning up bibliographic data and unifying hierarchical structures addresses by using the CWTS thesaurus of main organizations and their scientific addresses database. A detailed description of the CWTS data-system is given in M OED et al., (1995).Many researchers depend on corporate addresses in view of the increasing impact of studies about research that are centred on institutional domains (C ARPENTER et al., 1988; M OED& V AN R AAN, 1988; S HRUM& M ULLINS, 1988; D E B RUIN& M OED,* The first problem, relative to the lack of consistency in institutional names, has been dealt with in an earlier study submitted to Scientometrics and now under review by editor and referees (G ALVEZ & M OYA-A NEGÓN, in revision).4Scientometrics 70 (2007)C. G ALVEZ, F. M OYA-A NEGÓN: Standardizing corporate source data 1993; R INIA et al., 1993; H ERBERTZ & MÜLLER-H ILL, 1995; M ELIN & P ERSSON, 1996;B OURKE& B UTLER, 1998; V AN D EN B ERGHE et al., 1998; N OYONS et al., 1999; MÄHLCK& P ERSSON, 2000; M OED, 2000; M OYA-A NEGÓN et al., 2004). Although manual processing will, to some extent, be inevitable for unifying and reformatting the institutional affiliations of authors, it is hoped that the new approach described here provides a means of overcoming the scattering of organization data, thereby facilitating data isolation and unification for later bibliometric analyses.The problem of data formatting in corporate sources Scientific publications always enclose key data regarding author affiliation, information which is to be processed by bibliographic database and citation index systems. One of the pitfalls soon encountered along these unification processes lies in the arbitrary manner in which the name data are structured in the address field of the file. Authors do not use a standard code for affiliation data in scientific publications; though databases such as Science Citation Index Expanded (SCI-E), the Social Science Citation Index (SSCI), and the Arts & Humanities Citation Index (A&HCI) of the Institute for Scientific Information (ISI–Thomson Scientific, Philadelphia, US) afford some logical or hierarchical order in addresses – for instance, names of universities are placed on the whole at the beginning of the address (D E B RUIN & M OED, 1990). The corporate source field in the ISI databases consists of several items separated by commas and semicolons: the first parts of the address refer to the organization and usually contain the names of overall organizations such as universities or hospitals, divisions such as schools or faculties, and subdivisions such as departments or sections (D E B RUIN & M OED, 1993).Although it is widely accepted that the two final elements in corporate sources indicate the city and country where the organization of reference is located, the number of parts used to define this name can differ substantially. And so, raw publication data contain much needless variation in reporting the institutional name. This variety of formats in the address fields results in an eventual “scattering” of affiliations, interfering with the recognition and isolation of the data set regarding a particular organization or subdivision for subsequent bibliometric analyses. Not only does this problem arise within a given database; indeed, it is compounded if we try to gather up data from different databases. For an initial appraisal of this situation, we offer the reader some examples of structural differences in address formats from the MEDLINE, SCOPUS, CAB Abstracts and ISI Web of Science (ISI-WOS) databases, here in Table 1.Scientometrics 70 (2007) 5C. G ALVEZ , F. M OYA -A NEGÓN : Standardizing corporate source data6Scientometrics 70 (2007)Table 1. Several formats of corporate affiliationsThe inconsistencies in formatting make it very difficult to automatically parse this field into its constituent parts. Some handcrafted post-processing is needed to ensure order and consistency in maneuvering corporate source data. This situation led us to delve into two main objectives: 1) the development of a procedure that would allow for the tagging of this type of sequence; and 2) the application of some type of automatic process to help us to recognize equivalent structures and unify them in a fixed format.It is important to point out that beyond the scope of the present work remain those problems originating in any errors or inconsistencies produced by abbreviations,transliteration differences, differences in spelling, or name changes. Nor do we tackle problems deriving from the absence in the address of the first institutional level, or difficulties in the assignment of each document to a center that may result from ambiguity or inconsistency in the use of different names to refer to a single institution,cases where a single same name may designate two or more separate institutions, or assigneeship reflecting different nationalities. The validation and correct institutional assignment of addresses is a task corresponding to experts.Our proposal – bootstrapping and mapping structures with transducersThe a priori understanding guiding our initiative is that the affiliation addresses of scientific publications can be considered structured entities, even if their structure is not manifest. A Named Entity (NE) is a sequence of words that refers to an entity such as persons or organizations. The problem with NE recognition would be a task corresponding to Information Extraction (IE), with IE defined as the set of techniques and methods used to obtain structured data from natural language texts (H OBBS , 1993).In IE processes, texts are taken as input in order to produce fixed formats or unambiguos data as the output. This data may be used directly for display to users, may be stored in a database or spreadsheet for later analysis, or may be used for indexing purposes in Information Retrieval (IR) applications (C UNNINGHAM , 2005).C. G ALVEZ, F. M OYA-A NEGÓN: Standardizing corporate source dataInformation Extraction technology arose in response to a need for efficient processing of texts in specialized domains. It focuses only on the relevant parts of the text, disregarding the rest (G RISHMAN, 1997). As in any other discipline pertaining to Natural Language Processing (NLP), one of two basic approaches may be adopted: linguistic (J ACOBS& R AU, 1990; H OBBS et al., 1992; A BNEY, 1996) and statistical (N ERI & S AITTA, 1997). Linguistic techniques are based on a specialized corpus, and lexical and knowledge resources (such as dictionaries, regular expressions, or patterns and grammars) developed to identify the information to be extracted in the target domain. Statistical techniques, on the other hand, are based on the use of a corpus of data pre-annotated according to the information to be extracted and automatic learning methods. The choice of orientation should be guided by the specific means at our disposal: a knowledge-based approach is chosen if we have lexical and knowledge resources and an un-annotaded corpus; whereas a statistical approach is preferred if we have an annotated corpus (W ATRIN, 2003).These are the two basic options; however, we face the major impediment of not having the lexical resources that would allow us to tag this type of entity, nor pre-annotated data that would allow for a more automatic learning process of the resources. To overcome these two shortcomings we propose a ‘hybrid’ approach: a knowledge based extraction procedure in which manually pre-annotated patterns are defined, and therefore likely to target all the information to be extracted. This general proposal will be developed in the following stages: (i) Definition of corporate address patterns in terms of constituent analysis; (ii) Address matching and bootstrapping structures, to recognize the address patterns, then classify and mark the parts of addresses associated with the corresponding structures; and (iii) Mapping structures, establishing the transformational operations that will allow us to map equivalent structures onto a standardized structure or common format.Definition of address patternsIn order to identify the structured patterns of corporate source data, we shall first adopt what is known as Immediate Constituents (IC)* analysis, a well-known method in linguistics, based on the notion that between sentences and words there exist a series of intermediate degrees with a hierarchical order that divides sentences into successive layers, or constituents, until arriving at the final layer. The purpose of IC analysis would be to determine and show the interrelations between words in a given linguistic structure.*The term Immediate Constituents analysis was introduced by American structuralists through the application of formal methods of linguistic analysis. C HOMSKY (1957) made the first significant technical contribution to linguistics by formalizing Immediate Constituent analysis by means of Context Free Grammars. Scientometrics 70 (2007) 7C. G ALVEZ , F. M OYA -A NEGÓN : Standardizing corporate source data8Scientometrics 70 (2007)Under IC analysis, these patterns would be organized in sets, with consituent labels.We thus define address patterns as sequences of constituents separated by a delimiter character – most often a comma – along with some of the constituents containing triggering words, or ‘core terms’, that define the nuclei of the address pattern (such as ‘Department’, ‘Faculty’, ‘University’, ‘College’, ‘Institute’, ‘School’, ‘Clinic’, ‘Centre’,‘Hospital’, ‘Laboratory’, ‘Foundation’ or ‘Group’). These triggering words are activated within a specific context and serve as selectional restrictions * – which is a way of handling, in linguistics, the free order of the constituents, and is applied to resolve structural ambiguities. For instance, in an address downloaded from the SCOPUS database we can distinguish five immediate constituents:[DEPT. OF MOLECULAR BIOTECHNOLOGY], [FAC. OF AGRIC. AND APPL. BIOL. SCI.], [GHENT UNIVERSITY], [B-9000GHENT], [BELGIUM]We might give these immediate constituents the labels A (DEPT . OF MOLECULAR BIOTECHNOLOGY ), B (FAC. OF AGRIC. AND APPL. BIOL. SCI ‘), C (GHENT UNIVERSITY ), D (B-9000 GHENT ), E (BELGIUM ). However, the description of the linear structure of this address would offer only the horizontal succession of the elements that make it up; and so only a hierarchical placement of the elements would reveal the relationships among the constituents. The tree-diagram (Figure 1) given below is to be read as follows: the ultimate constituents of the address pattern (such as the words ‘Dept’, ‘Molecular’, or ‘Biotechnology’) would, in turn, be the immediate constituents of a complex form indicated by node A.Figure 1. Tree diagram of the constituents of the address pattern* Term coined by C HOMSKY (1965) to account for the variable order of syntactic structures. It is a formal device that limits the combinability of lexical units. The selectional restrictions imply a semantic selection to deal with the free order of constituents; they are usually an effective strategy in the case of very restricted domains, as is the case at hand.C. G ALVEZ, F. M OYA-A NEGÓN: Standardizing corporate source dataUnfortunately, determining the boundaries of address components – a trivial assignment for humans – is difficult to model in automatic form. Like any other natural language processing task, it calls for a means of tagging this type of sequence. Therefore, the main problem is that the entities to be identified are unlabeled data, meaning that we must resort to some procedure for entity tagging in order to identify the structure and classify the component parts.Address matchingAfter defining the address patterns in terms of IC and selectional restrictions based on triggering words that will help identify the relevant information, pattern-matching will be undertaken, using finite state techniques. We choose, from within this array of techniques, to apply finite automata and transducers. A finite automata accepts a string or a sentence if it can trace a path from the initial state to the final state by jumping along the stepping stones of labeled transitions. A finite automata is thus defined as a network of states and transitions, or edges, in which each transition has a label (ROCHE, 1996). Formally, a Finite-State Automata (FSA) is a tupleτ= <Σ, Q, q0, F, δ> where:•Σ is the input alphabet•Q is a finite set of states•q0 is the initial state, q0∈ Q• F is the final state, F ⊆ Q•δ is a function of transition, δ: Q x Σ→ QTo determine whether a string or sequence belongs to the regular language accepted by the FSA, the automata reads the string from left to right, comparing each one of the symbols of the sequence with the symbols tagging the transitions. If the transition is tagged with the same symbol as the input chain, the automata moves on to the following state, until the sequence is recognized in its entirety by reaching the final state. However, a finite automata is not capable of marking the parts of this sort of complex pattern.One possible solution would be to develop a tagger for this type of sequence –though this would be very costly – then apply machine learning techniques,* in which learning algorithms take on a corpus of un-annotated sentences as input and return a corpus of bracketed sentences (V AN Z AANEN, 1999); this type of algorithm is used* Language learning algorithms can be divided into two main groups, supervised and unsupervised ones, depending on the amount of information about language they use (V AN Z AANEN, 1999). The learning process of these algorithms consists of receiving, as input, several examples described by a set of attributes with its corresponding class label (these examples are the training set); then, the learner uses this training set to construct a hypothesis that will help it classify new instances.Scientometrics 70 (2007) 9C. G ALVEZ, F. M OYA-A NEGÓN: Standardizing corporate source datamore and more frequently for the boostrapping structure in natural language applications. The term ‘bootstrapping refers to problem setting in which one is given a small set of labeled data and a large set of unlabeled data, and the task is to induce a classifier’ (A BNEY, 2002, p. 360). The lack of resources and dictionaries for annotating the named entities, along with the need to recognize extraction patterns in specific domains from an untagged corpus, have led to the proliferation of bootstrapping methods.In our proposal, a finite-state method is applied to the problem of bootstrapping structures. We adopt a simplified conception of bootstrapping methods in order to recognize and classify sequence chunks that represent corporate addresses. For this purpose we shall redefine, for the sake of convenience, the notion of bootstrapping as: a problem in which one is given a set of patterns with internal variables that mark the component parts (that is, its structure) and a large set of unannotated data, and the task will likewise be to induce a classifier. In this abridged approach, the proposal for bootstrapping structures will be based on the use of transducers. Here, the procedure will assign a structure to the corporate address that resembles the human-performance-type structure most appropriately given to these sequences.A Finite-State Transducer (FST) is just like an FSA, except that the transitions have both an input label and an output label. An FST transforms one string into another string if there is a path through the FST that allows it to trace the first string using input labels and, simultaneously, the second string using output labels. One outstanding class of FSTs are the Enhanced Finite-State Transducers (E-FST), defined as transducers that use internal variables to identify and position parts of recognized sequences (S ILBERZTEIN, 1999). These variables are set during parsing: they can store affixes of matching sequences, and the contents can then be copied to the output part of the transducers.Using the graphic interface known as FSGraph (S ILBERZTEIN, 2000), we drew E-FSTs that would represent the possible structures of addresses, accounting for triggering words and delimiters. Each constituent is tagged by parentheses (to enter parentheses around the parts, we use the tag $ to indicate the output of the transducer). This procedure will suffice to identify and classify the parts that constitute the linear structures of institutional address patterns (Figure 2).10Scientometrics 70 (2007)C. G ALVEZ , F. M OYA -A NEGÓN : Standardizing corporate source dataScientometrics 70 (2007)11Figure 2. Linear structure of institutional address patternMapping structuresNonetheless, upon segmenting the address patterns we find that the IC order is not fixed – rather, it depends in many cases on database conventions, often determined by the variability of these data themselves within scientific publications. Thus, the relative positions of the constituents vary, giving rise to multiple alignment properties or structures in corporate data. Some possible combinations are:B, A, C, D, EC, B, A, D, EA, C, D, EIn the face of this problem, we set forth: Let A, B, C, D, E be five constituents of some address pattern. A is said to be discontinuous, among other factors, if A is linearly ordered between B and C . Known as discontinuous are those constituents that are not found one beside the other, owing to different conventions. In the tree-diagram representation there will be intersections of the branches. Therefore, a syntagmatic and strictly superficial processing would be inadequate for dealing with the variety of possibilities in constituent order, which would notwithstanding give rise to equivalent structures.In order to elaborate a standardized format with a fixed alignment we will need to develop a procedure in charge of mapping surface structures onto regularized structures.To this end we adopt a transformation method based on the interchangeability of constituents, in following the idea of American structuralist H ARRIS (1951), according to whom constituents of the same type can be replaced by each other. Under the transformational theory of H ARRIS (1951) we have as independent operations permutation, addition, substitution, adjunction, conjunction and suppression of constants. The value of the transformational method in light of our objectives resides in its capacity for detecting equivalent structures and producing uniform structures in institutional addresses.C. G ALVEZ , F. M OYA -A NEGÓN : Standardizing corporate source data12Scientometrics 70 (2007)If address structures can be subjected to the same transformational procedure, we infer they are identically structured; but if they cannot, their structure is different. From our viewpoint, some of the operations of transformation could then be modeled using E-FST.* The use of variables in transducers allows us to perform the relevant modifications in texts (S ILBERZTEIN , 2000):•Erasure elements : the replacement of A B C by A C allows us to erase the sequence stored in memory.•Insertions : the replacement of A B C D E by A B Univ C D E allows us to insert the text ‘Univ ’ between sequences B and C .•Duplications : the replacement of A B C D by A A B C D allows us to copy sequence A at two locations.•Permutations : the replacement of A B C D by C A B D allows us to changethe respective positions of A and C .For the time being, we shall limit our focus to the interchangeability of constituents performed through permutation transformations. Using the same graphic interface, we drew enhanced transducers to represent the possible structures of addresses, able to produce as output a fixed-format preselected as the standardized form (Figure 3). In this case we decided to sort by constituent permutation, moving the main organization to theinitial position.Figure 3. Graphical scheme of producing standardized form* Enhanced transducers use internal variable to identify and place parts of recognized sequences. This function is similar to one carried out within programs like UNIX type SED (S ILBERZTEIN , 2000). SED, AWK,and PERL are some of the UNIX utilities that implement Regular Expressions , mostly in tasks requiring pattern matching and substitution. SED is a S tream Ed itor, which follows commands just like an interactive editor to perform repetitive search-and-replace commands untouched by the human hand.C. G ALVEZ, F. M OYA-A NEGÓN: Standardizing corporate source dataThe aim of these transformational operations is to explain the equivalency relations between structures of corporate addresses that have the same set of constituents, and so the constructions are transformed one into the other if – and only if – there is coincidence of the constituent parts and conditions of occurrence. After a pre-processing stage, the application of this transducer will bring the main organization into the first position in the structured format we have selected to represent corporate addresses:GHENT UNIVERSITY, FAC OF AGRIC AND APPL BIOL SCI, DEPT OF MOLECULAR BIOTECHNOLOGY, B-9000 GHENT, BELGIUM By applying E-FST to the data structure of corporate addresses, we manage: (i) to reveal equivalences and differences in the structure of the units being examined; (ii) to expose the structural potential of the unit that will provide for sorting and classifying the parts of corporate sources; and, most importantly, (iii) to avoid any substantial modification of the corporate source data indicated by the author/s that might trigger greater problems in posterior quantitative analyses.MethodologyWe shall describe the components of corporate sources in tems of IC, which for possible bibliometric applications will be considered independent units of analysis (UA). Afterwards, we proceed to identify and structure these data using finite-state graphs compiled in transducers. The implementation of such a process is straighforward: first, the recognition process is activated because the sentences contain core terms; second, the address pattern is matched against the sentences and so the components of address patterns will be identified, labeled and permuted. This procedure will eventually allow us to establish an equivalence relation through permutation transformations, enabling us to produce organization names with a standard position for their components.The application domain dataBecause we use a corpus-based methodology, our system begins with a training phase, during which we learn the relevant address patterns from the application domain. To design the model, we took a sample of corporate names from INSPEC (produced by the Institution of Electrical Engineers), MEDLINE (U.S. National Library of Medicine), and CAB Abstracts (CAB International) databases, all in online version. The choice of these databases is justified by the fact that they no contain uniform format for corporate sources and require manual post-processing to clean-up, order and reformat these fields for automated bibliometric analysis. The dataset need not be very large, as there are Scientometrics 70 (2007) 13。
Correspondence Address
Abstract
The eld of image restoration lacks promising comparison vehicle for judging the e ectiveness of competing algorithms. By far the most widely adopted quantitative measurement of image restoration performance is by means of the SNR improvement. In this paper we address the issues on performance assessment of image restoration and propose a uni ed framework for the performance measure. The SNR improvement, which is within the proposed framework, is shown to be an inappropriate performance measure for image restoration. By introducing a metric for pixel delity improvement and incorporating main properties of the human visual system into the measurement, we devise a performance measure of better quality, particularly of higher precision.
(852) 2766 6224 (Yuk-Hee Chan) (852) 2766 6229 (Wan-Chi Siu)
address的用法和短语例句
address的用法和短语例句address有住址;网址;电子邮箱地址;称呼等意思，那么你知道address的用法吗?下面跟着店铺一起来学习address的用法和短语例句吧，希望对大家的学习有所帮助!address的用法address的用法1：address的基本含义有三:①指正式的、有准备的讲话,含有讲话有目的、有分量、有长度或讲话者与众不同等意味。
②指应付困难的或新的局面以及与陌生人交往时表现出的机敏、得体,从而能博得他人好感或获得成功,可灵活译为“儒雅的风度”“得体的举止”“圆滑的手段”“巧妙的本领”等。
③指人们生活、工作地点的市镇、街区、门牌号和电话、传真号等,即通讯地址。
有时也包括姓名。
address的用法2：表示“在某地址”时,该地址如明确具体, address前用介词at,如较笼统,则可用in。
address的用法3：address的复数(addresses)可以表示“(求爱时所献的)殷勤”。
address的用法4：address作“收件人地址”解时,美国发音往往为 [' dres] ,作其他意义解时,英美发音均为 [ə'dres] 。
address的用法5：address用作动词时其意思是“向…讲话”“向…提出”“致力于”,此外还可表示“在(信封或包裹)上写地址”或“称呼”,用于科技术语还可指“存入或取出”。
address的用法6：address是及物动词,后接名词或代词作宾语,有时可接双宾语,其间接宾语可转化为介词for或to的宾语,还可接由“as+ n. ”充当补足语的复合宾语。
address的用法7：address可用于被动结构,过去分词addressed 可用作形容词,在句中作表语或定语。
address的用法8：address多用于address sth to sb 句型,而较少使用address sb sth 和address to sb sth 两个句型。
swift是什么意思 [bank,address是什么意思]
![swift是什么意思 [bank,address是什么意思]](https://img.taocdn.com/s3/m/f31e3968195f312b3169a5c4.png)
swift是什么意思[bank,address是什么意思]bank address是什么意思呢?下面是小编给大家整理的bank address是什么意思，供大家参阅!bank address是什么意思bank address银行地址例句:Non-local bank, please fill in bank address. 如非本地银行,请填写银行地址。
bank address英语例句While the name tagged to an email sender might suggest “NatWest Bank”, a nonsensical emailaddress or one clearly outside the country should raise suspicion.He added the funds, which will be released to the Central Bank of Libya, would help to addressurgent humanitarian needs.The simple, straightforward address focused on explaining the bank crisis in a way that people would understand, and that would encourage them to trust the banking system.Nick Pickles, from civil liberties group Big Brother Watch, said that when children leave home it is not uncommon for them to use their parent's address for their correspondence and bankaccount details.The court determined that because the Bank Secrecy Act regulations were designed to addresscivil issues as well as criminal issues they were essentially regulatory, and not criminal, even though a significant purpose of the regulations is to detect money laundering, terrorism and tax evasion.Bank of America, for example, is studying “optio ns to address some of the other costsassociated with the loans, “ says Steve Boland, the bank's reverse-mortgage executive.The fraudulent eBay site not only asks for users' eBay identification, password and emailaddress but also credit card, bank account, drivers license and social security numbers.Choosing to remain anonymous, they happily accept players worldwide and all cash-ins and cash-outs are denominated in bitcoin so no bank accounts are required and even your emailaddress is optional.Both questions address a fundamental misunderstanding of the Bank.”We have to address the fact that a bad bank in one country can undermine good banks in every country, and that multibillion-dollar markets still exist outside the supervisory net, “ Brown said.By way of comparison, China is tightly controlling its currency, and only allowing minimal appreciation against the dollar, preferring to address currency and inflationary concerns with higher bank reserve requirements and increased tariffs on imports.The Bank called on this week's G20 meeting to address the problem.Draghi, the Ex-Goldman Sachs investment banker, is very much a devotee of central bankthought, and defers to using monetary policy to address fiscal issues, as any acolyte of Jean Claude-Trichet would be.The papers showed the name and address of Ersin Tatar and details from Barclays bankstatements and references to financial transfers to Impexbank in 1990, a Turkish bankpurchased in 1988 by Asil Nadir.bank address银行地址双语例句中情局的科学家正在研究超乎寻常的超级计算机程序和人工智能，这可能有助于分析人员把几十万个名字、地址和银行账号联系起来。
怎么询问对方住址英语作文
怎么询问对方住址英语作文Title: Inquiring About Someone's Address。
When it comes to building relationships or simply being well-prepared for correspondence, knowing someone's address is often essential. However, asking for such personal information requires a delicate approach, especially in English, where politeness is highly valued. Here's a comprehensive guide on how to inquire about someone's address politely and respectfully.Introduction: Setting the Context。
In our interconnected world, communication is key, and having someone's address can facilitate various forms of interaction, from sending letters or invitations to simply knowing where to reach them in case of necessity. Therefore, it's perfectly reasonable to ask for someone's address, but it's crucial to do so in a courteous manner that respects the other person's privacy and comfort.Body: Crafting the Inquiry。
迁址通知英语作文模板
迁址通知英语作文模板英文回答：Change of Address Notification Template。
[Your Name][Your New Address][City, State, Zip Code][Email Address][Phone Number][Date][Recipient Name][Recipient Address][City, State, Zip Code]Subject: Notice of Change of Address。
Dear [Recipient Name],。
Please be advised that my permanent address has changed effective [date]. My new address is as follows:[Your New Address][City, State, Zip Code]My new telephone number is [phone number], and my new email address is [email address].I kindly request that you update your records accordingly. Please direct all future correspondence to my new address.I appreciate your attention to this matter.Sincerely,。
[Your Signature][Your Typed Name]中文回答：迁址通知模板。
[您的姓名][您的新地址][城市、州、邮政编码] [电子邮件地址][电话号码][日期][收件人姓名][收件人地址][城市、州、邮政编码]主题，迁址通知。
尊敬的 [收件人姓名]，。
谨此通知您，我的永久地址已于 [日期] 生效后更改。
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Jointly published by Akadémiai Kiadó, Budapest Scientometrics, and Kluwer Academic Publishers, Dordrecht Vol. 60, No. 3 (2004) 333–351Citation Database for Japanese Papers:A new bibliometric tool for Japanese academic societyM ASAMITSU N EGISHI, Y UAN S UN, K UNIHIRO S HIGINational Institute of Informatics (NII), Tokyo (Japan)The paper describes the construction and functions of the Citation Database for Japanese Papers (CJP) developed at the National Institute of Informatics, Japan (NII), and the ImpactFactors of CJP’s source journals. Then statistical analyses of multidimensional scaling on citationcounts for the academic society journals to measure relationship among the societies are described.We also introduce a new citation navigation system, CiNii, which enables users to access variousresources provided by NII, such as NACSIS Electronic Library Service (NACSIS-ELS) to getelectronic full-text of journal articles through citation links. Recent political developments in Japantowards enhancement of scientific information infrastructure are also introduced with itsimplication to research evaluation systems incorporating citation analyses.IntroductionMany bibliometric researches are based on analyses of data extracted from the Science Citation Index (SCI) and sometimes Social Science Citation Index (SSCI), Arts and Humanities Citation Index(A&HCI), produced by the Institute for Scientific Information (ISI). The ISI databases are no doubt very useful and powerful for evaluating research performance from an international perspective: international trend of research activities, position at the international research front and international research collaboration. However, for the assessment of research activities or for science policy making from a national perspective, they can not be sufficient (M OED, 2002). We need our own Japanese citation databases with a good coverage of Japanese journals with no language bias.We, National Institute of Informatics (NII), formerly National Center for Science Information Systems (NACSIS), started to construct the Citation Database for Japanese Papers (CJP) in 1995, and release the service from January 2000. At present, the CJP database provides access to current and retrospective bibliographic information and cited references found in approximately 550 titles of Japanese academic society journals covering engineering, science, agriculture and medical science disciplines. The source of the journals is expected to be expanded to 1,000 titles in 2003.Received January 30, 2004Address for correspondence:M ASAMITSU N EGISHINational Institute of Informatics (NII)2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, JapanE-mail: negishi@nii.ac.jp0138–9130/2004/US $ 20.00Copyright © 2004 Akadémiai Kiadó, BudapestAll rights reservedM. N EGISHI et al.: Citation Database for Japanese PapersIn China local databases such as the Chinese Science Citation Database(CSCD), the China Scientific and Technical Papers and Citations Database(CSTPC) and the Chinese Social Science Citation Index(CSSCI) have been developed. The Documentation and Information Center of the Chinese Academy of Science (DICCAS), ISTIC and the Nanjin University in collaboration with the Hong Kong University of Science and Technology were the respective organizations responsible for their development and maintenance (J IN & W ANG, 1999; W U et al., 2003; S U et al., 2001). This shows that construction of non-English citation indices reflecting scientific activities in each country is important and necessary.In the present paper, we describe the compilation process of the CJP and the searching functions. Then some results from statistical analyses on CJP including the Impact Factors and relationship among academic societies are discussed. The future image of the citation information system will also be depicted with its implication to research evaluation systems and the national science policy.Situation of Japanese academic society journalsJapanese research community holds a big population of 756,000 including researchers in universities, research institutions and industry. Some 57% of them are in industry forming a largest group, while 37% are in universities and 6% are in public or non-profit institutions (S TATISTICS B UREAU, 2002). A breakdown by fields of science gives an estimation that 87% are in natural sciences and the rest are working in humanities and social sciences.Science Council of Japan (SCJ), an assembly of 210 prominent scientists, is operating an accreditation program for academic societies, which is related to its member election system (SCJ, 2003). The SCJ members of 3 year term are elected through voting by the acknowledged academic societies, where the societies are assigned certain voting rights and also the right to recommend candidates for the council. Thus the academic societies have a crucial role in forming the assembly, and the process of accreditation of societies by SCJ is also important. SCJ has established the criteria for the accreditation based on the number of society members, regularity of its publications, composition of its officials, etc.Table 1 is derived by counting descriptions in Directory of Academic Societies 2002-03(Gakkai Meikan) compiled by a SCJ related foundation (J APAN S CIENCE S UPPORT F OUNDATION, 2001). Because some of the descriptions on publications for societies in literature and law are missing, we can assume more publications than those in the table. According to the figures in the table, more than 2,000 journals are published and around 340 of them are written in English language. Large societies are 334Scientometrics 60 (2004)M. N EGISHI et al.: Citation Database for Japanese PapersScientometrics 60 (2004) 335typically publish 3 publications, that is, a bulletin or magazine for communication among members, a journal for original research papers and an English language journal for overseas dissemination of scientific achievements of the members.Table 1. Number of journals by the academic societies registeredat Science Council of JapanSource: Directory of Academic Societies 2002-03 (Gakkai Meikan )FieldN of Societies N of Journals Japanese English Literature404 404 379 25 Law50 42 40 2 Economics105 142 129 13 Science130 273 190 83 Engineering129 399 327 72 Agriculture145 213 176 37 Medicine393 546 437 109 Total 1,356 2,019 1,678 341However, almost all English language journals of Japanese academic societies have been suffering from their low circulation overseas in spite of the quality of their papers.The national government has been supporting those English journals by establishing a funding program and now 120 English journals are being published with this funding.The government together with NII also plans to enhance the support by establishing a new program in which electronification of publication or electronic journal approach should be introduced. They expect that current information and telecommunication technology would help to shrink the distance between Japan and the West, and to realize good circulation worldwide.Besides the above problem of improving the circulation of Japanese academic journals in English language, we have another problem of improving utilization of papers written in Japanese mainly among Japanese researchers. The citation indexes compiled by ISI are giving us an efficient way to trace series of papers connected by the references. However ISI's indexes include limited number of world prominent journals mainly in English language, and incorporate few journals of Japanese academic societies. As is assumed with Table 1, we have a large number of scholarly papers which are written in Japanese language, many of them being published on Japanese society journals. For those papers there had not been any mean to trace citation chains,and a citation index type database for them would be expected to help their utilization and circulation.M. N EGISHI et al.: Citation Database for Japanese Papers336 Scientometrics 60 (2004)Construction of citation database for Japanese papers (CJP)In 1995, NACSIS, the former name of NII, planed to compile a citation index type database for Japanese academic papers and got some funding from the government. At the beginning of the project, due to the limitation of budget, we selected 200 journals in science and engineering. The selection criteria included the followings: journals published by the SCJ registered societies, large societies being preferred, original paper journals rather than magazines being given high priority. A balance among fields was also considered to cover all the area in science and engineering.The data input process consists of two stages: (1) marking items in references in papers with designated colors to indicate authors, titles, volumes, numbers and pages;(2) keyboarding the items together with bibliographic data of the papers. As the style of reference greatly varies among journals, it took a lot of time to analyze them and to design practical operations.Some of the problems we noticed there include the followings. (1) Variations in notation of author names: In some style only family names are noted while there are many cases where full names with given names are written. Note that Japanese names have no space to delimit the two parts. As we input them as they appeared on the originals, database users should search with family names and also full names to make their search comprehensive. (2) Variations in notation of journal titles: journal titles areoften abbreviated, but the abbreviations are not unified and vary depending on the styleof citing journals. For example orM. N EGISHI et al.: Citation Database for Japanese PapersScientometrics 60 (2004)337Figure 1. Searching CJP in NACSIS-IR. Specify a cited author as the search term in this caseFigure 2. Select papers in the list of searched titlesM. N EGISHI et al.: Citation Database for Japanese Papers338Scientometrics 60 (2004)Figure 3. Display data for papersFigure 4. List of holdings at university librariesM. N EGISHI et al.: Citation Database for Japanese PapersScientometrics 60 (2004)339Figure 5. Browsing index for citation data. Specify a cited author to be searchedFigure 6. Browse citation data and citation countsM. N EGISHI et al.: Citation Database for Japanese PapersUsers can specify author names (RA), publication years (RY), words in paper titles (RT), journal titles (RW), journal IDs (RI), volume numbers (RV) and pages (RP), or their combination as the search term (Figure 1). The search gives a list of relevant papers (Figure 2), and users can display the bibliographic and citation data for each paper (Figure 3). Clicking journal IDs on the display when available leads users to Union Catalog Serials Database where they can check holdings of the particular issue of the journal at university libraries (Figure 4).NACSIS-IR provides the other route of access via citations, that is, browsing citations where users are given citation counts for papers together with variant forms of citations (Figures 5, 6). By summing up citation counts of the variations, users should tell more precise number of times the paper cited.Impact Factors of Japanese society journal and their implicationto research evaluationAs has been touched upon, CJP was planed to make Japanese papers more usable by providing access through citations. However CJP now appears to be used more often for counting citations for papers, in parallel with the ISI databases. Japanese university system is in the process of reformation, which is typically denoted as “From a convoy to a competitive system.” In 2001 the government announced its plan, TOP 30 or the COEs (Centers of Excellence) for the 21st Century, in which it would select 30 university departments in each fields and give them additional funds for the promotion of their research activities. With this program, research evaluation for universities has been given actuality, and researchers at universities have rapidly become conscious about citation counts and the Impact Factors as objective measures for their performance (N EGISHI, 2001). In this circumstance, we are now in the process of compiling statistics on CJP like the impact factors for Japanese society journals.For the efficient preparation of statistics, an efficient automatic unification process of citations by matching notation variations in citations is crucial, and we are now developing the system as is described later.In the course of the development of more automated system, we calculated the impact factors (IF) for Japanese society journals included in CJP where manual inspections was heavily incorporated. The impact factor for year 2000 is defined as number of times papers of 1998 and 1999 in a journal were cited from all the paper of 2000 in the database, divided by number of papers of 1998 and 1999.340Scientometrics 60 (2004)M. N EGISHI et al.: Citation Database for Japanese PapersScientometrics 60 (2004) 341Thus the impact factor means average number of citations from all papers in 2000 to a paper in a journal in 1998 and 1999. In our survey, 103,500 citations of year 2000 to papers of 1998/99 were checked and the cited journals in 87,606 citations were identified with the IDs of Union Catalog of Serials Database . To summarize, 87,606citations from 29,648 papers in 543 journals were found to go to papers on 7,027journals. Table 2 shows basic statistics from the survey, denoting that 95,646 papers in 356 journals in CJP database were cited 18,116 times.We find here that the IFs are rather small when compared to those of ISI’s JCR (Journal Citation Reports – 2000 Science Edition), mainly because of the difference in the journal coverage. ISI covers world prominent journals of high citations, while CJP embraces only Japanese society journals, and citations are counted within this limited world. As is seen in the above figures, only 21% of citations (18,116/87,606) from Japanese society journals come back to themselves, and many of the others are assumed to go to the foreign journals.The IFs for medical and biological journals should generally be large when compared to those for journals in science and engineering, because the number of citations in a paper in biosciences is large. On the contrary, Table 2 shows that IF of engineering is largest and that of medicine is smallest. This seems to reflect the number of journals covered in CJP as it includes 190 titles in engineering and 53 in medicine.Here again we should confirm the importance of journal coverage in assessing impact factors.Table 2. Citations and impact factors (IF) for Japanese society journals in CJPField N of journals N of papers(98-99) (A)Times cited from papers 2000 (B)Self-citations (C)IF (B/A)Ratio of self-citation (C/B)Engineering 190 62,34213,002 6,143 0.210.47Agriculture 29 5,9481,113 651 0.190.58Medicine 53 13,7341,959 1,297 0.140.66Total 35695,646 18,116 9,108 0.190.50M. N EGISHI et al.: Citation Database for Japanese Papers342 Scientometrics 60 (2004)Table 3. Journals with high impact factors in CJPJournal (J: in Japanese; E: in English)Number of papers (98-99) (A)Times cited from papers 2000 (B)Self-citations (C)Impact Factor (B/A)Journal of the Geological Society of Japan (J)178137450.77CAJ Proceedings of Cement & Concrete (Japan Cement Association) (J)167115510.69Journal of the Iron and Steel Institute of Japan (J)289180600.62Japanese Journal of Applied Physics. Pt. 1: Regular Papers & Short Notes(Japan Society of Applied Physics) (E)303716488200.54Journal of the Acoustical Society of Japan (J)242125290.52Journal of the Society of Naval Architects of Japan (J)281137700.49Proceedings of Annual Conference (Japan Concrete Institute) (J)11004633370.42Journal of the Japan Society of Powder and Powder Metallurgy (J)4231761200.42Journal of the Japan Society of Precision Engineering (J)6402501300.39Transactions of Information Processing Society of Japan (J)7922911160.37Chemical & Pharmaceutical Bulletin (Pharmaceutical Society of Japan) (E)7032572090.37M. N EGISHI et al.: Citation Database for Japanese PapersA statistical analysis on electricity and electronics related society journalsWe made a citation analysis on the journals published by the 5 electricity and electronics related societies, i.e. Institute of Electronics, Information & Communica-tions Engineers (IEICE), Institute of Electrical Engineers of Japan (IEEJ), Institute of Image Information and Television Engineers (ITE), Information Processing Society of Japan (IPSJ) and Society of Instrument and Control Engineers (SICE), upon request by IEICE in 1999 (N EGISHI, 1999). The 5 societies are cooperative as frequently holing joint conferences. In the analysis, we collected very preliminary statistics for their citations from CJP in its early stage, just showing the applicability of CJP to these analyses. Now we are making the same type of analysis on these journals again upon the request by IEICE on a comprehensive basis, as is described here.Table 4 is a summary of citation counts to and from the journals published by electricity and electronics related societies in Japan, where counts are summed up by society. For example, IEICE publishes 5 Japanese language journals and 4 English language journals, and all the citations from papers in them in year 2000 to those papers in 1998/1999 or self-citations are 824. Citations from IEICE journals to IEEJ journals are 30, whereas the citations from IEEJ to IEICE are 61. The table also contains the other societies than the 5 which are revealed to be closely connected to them by citations, such as Japan Society of Applied Physics and IEEE.As the columns from IEEE (A) to NE (H) for the cited societies list the related external societies which are not covered by CJP, only cited counts for them appear, depicting that IEEE journals get highest citations of 573 from IEICE journals when self-citations are excluded. The identical situations are found for the other journals that the foreign journals get more citations rather than Japanese journals. This should pose a problem from the view point of promoting activities of Japanese academic societies. In order to make their activities more visible worldwide, the 5 societies are said to be planning to publish a joint journal in English language, to attract both Japanese and foreign authors and readers.With this concern, we tried to depict relationship among the 14 societies covered by CJP applying statistical techniques on the citation data in Table 4. Citation counts in the rows and columns 1 through 14 in Table 4 are interpreted as represent closeness between societies. The data can be considered to form a similarity data matrix indicating that pairs of societies with more citations have more similarities. Here Multidimensional Scaling (MDS) analyses are expected to give pictures where the 14 societies are placed with appropriate distances representing their communication network.Scientometrics 60 (2004) 343M. N EGISHI et al.: Citation Database for Japanese Papers344Scientometrics 60 (2004)Table 4. Citations to / from journals published by electricity and electronics related societies in Japan(Number of citations from papers in year 2000 to papers in 1998-99)Cited society (Journal)C.s.(J)1234567891011121314A B C D E F G H Total 1824302312310845713132417355737321353416213199326158541430312211451071111716131312259643127797231341192168835293213218353847335197111212121231051532368668211421879227642131189724141404212281298710152094727101633247414551258087541822494267611150294633718130255281562225104642025785295311801119162434111945213101176127521121144793128138132611212217514631192839T.122476813942721011165363011811589116371591066580373231163121272680311: Institute of Electronics, Information & Communications Engineers; 2: Institute of Electrical Engineers of Japan; 3: Institute of Image Information and Television Engineers; 4: Information Processing Society of Japan; 5: Society of Instrument and Control Engineers; 6: Japan Society of Applied Physics; 7: Acoustical Society of Japan; 8: Magnetic Society of Japan; 9: Japan Society for Precision Engineering; 10: Japan Society of Mechanical Engineers; 11: Institute of Systems, Control and Information Engineers; 12: Robotics Society of Japan; 13: Japanese Society for Artificial Intelligence; 14: Japanese Society of Medical Imaging TechnologyA: IEEE – Institute of Electrical and Electronics Engineers; B: AIP – American Institute of Physics; C: APS –American Physical Society; D: SPIE – International Society for Optical Engineering; E: OSA – Optical Society of America; F: JCG – Journal of Crystal Growth (North-Holland); G: SID – Society for Information Display; H: NE – NIKKEI Electronics (Nikkei Business Publications)M. N EGISHI et al.: Citation Database for Japanese PapersScientometrics 60 (2004)345Prior to the analyses, the raw similarity data are needed to be converted into distance data indicating dissimilarity of each society pair. Firstly, dissimilarities were calculated by multiplying raw data with –1 and setting the smallest dissimilarity equal to zero.Figure 7 shows the two-dimensional map constructed from the converted distance values using the SPSS ALSCAL procedure under the assumption of interval measurement. The societies are placed along a smooth contour in the order of information processing (IPSJ), electronics & communication (IEICE), physics (JSAP),electricity (IEEJ), mechanical engineering (JSPE, SICE, JSME), going through systems & control (ISCIE), robotics (RSJ), artificial intelligence (JSAI) and back to the information processing. It seems to illustrate a kind of communication network around these academic societies.To get further insight into the structure of the data, we adapted a different method to transform the raw proximities. Figure 8 shows another MDS map which displays a different view of the journal co-citation dataset in Table 4. In this case, dissimilarities were calculated simply by taking the inverse of the raw similarity data after replacing zero citation with 0.01. Model for ratio scale in the ALSCAL procedure wasused.Figure 7. Positions of 14 societies derived from a multidimensional scaling analysisM. N EGISHI et al.: Citation Database for Japanese Papers346Scientometrics 60 (2004)Figure 8. Another positioning of the societies with a different distance modelFigure 9. Dendrogram suggesting a grouping of societies based on their coordinates in Figure 8.M. N EGISHI et al.: Citation Database for Japanese Papers Although the STRESS (fitness index) = 0.69 is a little large, comparing with the first transformation (0.33), which indicates larger lack-of-fit between the fitted distances and the original proximity values, the figure seems to give a fairly reasonable and interpretable configuration.In this figure we see IEICE (electronics, information and communication), IEEJ (electricity) and somewhat IPSJ (information) are relatively close to each other meaning that these societies have stronger communication tie, while RSJ (robotics), SICE (instrument), ISCIE (systems and control) are forming another cluster. Meanwhile, we have JSAP (physics) and MSJ (magnetic) on the left. There seems to be the “Physics –Electricity/Electronics – Mechanical Engineering” dimension from down-left to up-right of the figure.To examine how the societies are grouped together, we applied clustering analysis as well. The dendrogram shown in Figure 9 was determined by submitting the coordinates of the two-dimensional MDS solution of the above to the SPSS hierarchical clustering procedure with Ward’s method. The figure suggests the following society grouping:1. a cluster of societies on electricity, electronics and information, such as Institute of Electronics, Information and Communication Engineers (IEICE), Institute of Electrical Engineers of Japan (IEEJ), Information Processing Society of Japan (IPSJ) and Institute of Image Information and Television Engineers (ITE);2. a cluster of societies of mechanical engineering, including Japan Society of Mechanical Engineers (JSME), Robotics Society of Japan (RSJ), Institute of Systems, Control and Information Engineers (ISCIE), Japanese Society for Artificial Intelligence (JSAI), Society of Instrument and Control Engineers (SICE), Japan Society for Precision Engineering (JSPE) and Acoustical Society of Japan (ASJ);3. a cluster of physics consisting of Japan Society of Applied Physics (JSAP) and Magnetic Society of Japan (MSJ) with Japanese Society of Medical Imaging Technology (JAMIT) a little apart from them.As is already mentioned, the electricity related 5 societies seem to be thinking of joint publication of an English language journal. In order to promote societies’activities, these joint projects would be quite effective. The groupings derived from citation links such as the above give some suggestions for potential joint projects based on an objective measure of citation links. Those types of analyses on citation data from various aspects should be positively explored.However the previous examples illustrate that using different way to convert original similarity data into distances will conduct fairly different MDS configuration. Note also that sometimes higher-dimensional spaces may be needed in order for the fitted distances to sufficiently match the original similarity data. The selection of data transformation method and interpretation of the reduced space are obviously important, and we are in our way to carry out the research in more detail.Scientometrics 60 (2004) 347M. N EGISHI et al.: Citation Database for Japanese PapersFuture direction of CJP database and policy development for electronic scientificcommunicationIn 2001, the Council for Science and Technology to the Minister of Education, Culture, Sports, Science and Technology (MEXT) publicized a report titled Enhancing Infrastructure for Circulating Scholarly Information, covering various aspects of scholarly information circulation including acquisition of foreign electronic journals at university libraries, transmission of information from universities and academic societies, transmission of Japanese information abroad (N EGISHI, 2002; T HE C OUNCIL FOR S CIENCE AND T ECHNOLOGY, 2002). In the report, NII is expected to play crucial roles for enhancement of academic information infrastructure. Along with this line, NII has launched a portal system for academic contents, GeNii (Global Environment for Networked Intellectual Information), in 2002 making Japanese scholarly information more efficiently accessible worldwide by providing researchers with unified interface to various types of databases which have been serviced at NII (NII, 2003c).CJP is utilized as the core database to coordinate scientific papers, authors/researchers, projects, societies, etc. through citations. In establishing those links, unification of bibliographic and citation records by fuzzy match processing to absorb variations in descriptions and merge them to unified forms is crucial. However efficient matching technique for large-scale Japanese data has not been be developed. NII is making research and development for it, and is well on the way of solution with a matching system for CJP citations based on the Support Vector Machine algorism being developed.CiNii (Citation Information by NII), a component of GeNii, is now on the web on an experimental basis. As is depicted on Figure 10, CiNii gives links to citing and cited papers for each paper and direct users to their page images stored in NII's Electronic Library Service (NACSIS-ELS) (Figure 11) (NII, 2003d). NII plans rapid enhancement of GeNii and CiNii to cover various types of contents at universities as well as at NII, and co-operation with ISI would also be discussed.Due to the long-lasting economic difficulties, Japanese policy makers are quite interested in research evaluation for efficient investment to research projects which would bring some technological evolution and strengthen the national competitiveness in the worldwide scene. The citation oriented systems such as CJP and CiNii are expected to work for the aim in the two ways as follows. First, they will accelerate research process by efficiently providing research information among researchers. Secondly they will provide some evaluation measures which lead research polices at the national and local governments, universities, research institutions and industry, effective to prioritize prospective fields. Now citation related systems are more and more attracting a great deal of attention in the country.348Scientometrics 60 (2004)。