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公共场所中图形符号国家标准使用指南邹小阳1 陈永权2（1.海南省市场监督管理局；2.中国标准化研究院）摘 要：图形符号在传递信息方面具有直观、易懂、能够跨越语言和文化障碍等独特优势，因此在公共场所中使用的标识上大量使用了图形符号。
为了提升公共场所中公共信息图形符号、安全标志和道路交通标志的规范化应用水平，本文以文献研究为主，整理并探讨了适用于公共场所的图形符号国家标准，为公共场所中图形符号相关国家标准的使用指明了方向。
关键词：公共场所，公共信息图形符号，安全标志，道路交通标志，国家标准DOI编码：10.3969/j.issn.1674-5698.2023.07.014Guidelines for the Use of National Standards for GraphicalSymbols in Public AreasZOU Xiao-yang 1 CHEN Yong-quan 2（1. Market Supervision Authority of Hainan Province ；2.China National Institute of Standardization ）Abstract: Graphic symbols have unique advantages in conveying information, such as being intuitive, easy to understand, and able to overcome language and cultural barriers. Therefore, graphic symbols are widely used in public areas. In order to improve the standardized application level of public information graphical symbols, safety signs and road traffic signs in public areas, the national standards of graphical symbols applicable to public places are sorted out and discussed based on literature research, which points out the direction for the use of national standards related to graphical symbols in public areas.Keywords: public area, public information graphical symbol, safety sign, road traffic sign, national standards基金项目：本文受中央基金科研业务费项目“公共场所标识评测技术与应用研究”（项目编号522022Y-9403）资助。
计算机常用英语术语、词汇表一、硬件类(Hardware)二、软件类(Software)三、网络类(Network)四、其它CPU(Center Processor Unit)中央处理单元Main board主板RAM(random access memory)随机存储器(内存)ROM(Read Only Memory)只读存储器Floppy Disk软盘Hard Disk硬盘CD-ROM光盘驱动器(光驱)monitor监视器keyboard键盘mouse鼠标chip芯片CD-R光盘刻录机HUB集线器Modem= MOdulator-DEModulator,调制解调器P-P(Plug and Play)即插即用UPS(Uninterruptable Power Supply)不间断电源BIOS(Basic-input-OutputSystem)基本输入输出系统CMOS(Complementary Metal-Oxide-Semiconductor)互补金属氧化物半导体setup安装uninstall卸载wizzard向导OS(Operation Systrem)操作系统OA(Office AutoMation)办公自动化exit退出edit编辑copy复制cut剪切paste粘贴delete删除select选择find查找select all全选replace替换undo撤消redo重做program程序license许可(证)back前一步next下一步finish结束folder文件夹Destination Folder目的文件夹user用户click点击double click双击right click右击settings设置update更新release发布data数据data base数据库DBMS(Data Base ManegeSystem)数据库管理系统view视图insert插入object对象configuration配置command命令document文档POST(power-on-self-test)电源自检程序cursor光标attribute属性icon图标service pack服务补丁option pack功能补丁Demo演示short 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添加监视点all files 所有文件allrightsreserved 所有的权力保留altdirlst 切换目录格式andotherinFORMation 以及其它的信息archivefileattribute 归档文件属性assignto 指定到autoanswer 自动应答autodetect 自动检测autoindent 自动缩进autosave 自动存储available on volume 该盘剩余空间bad command 命令错bad command or filename 命令或文件名错batch parameters 批处理参数binary file 二进制文件binary files 二进制文件Borland international borland国际公司bottommargin 页下空白bydate 按日期byextension 按扩展名byname 按名称bytesfree 字节空闲callstack 调用栈casesensitive 区分大小写centralpointsoftwareinc central point 软件股份公司changedirectory 更换目录changedrive 改变驱动器changename 更改名称characterset 字符集checkingfor 正在检查chgdrivepath 改变盘/路径chooseoneofthefollowing 从下列中选一项clearall 全部清除clearallbreakpoints 清除所有断点clearsanattribute 清除属性clearscommandhistory 清除命令历史clearscreen 清除屏幕closeall 关闭所有文件codegeneration 代码生成colorpalette 彩色调色板commandline 命令行commandprompt 命令提示符compressedfile 压缩文件conventionalmemory 常规内存copydiskette 复制磁盘copyrightc 版权(ccreatedospartitionorlogicaldosdrive 创建DOS分区或逻辑DOS驱动器createextendeddospartition 创建扩展DOS分区createprimarydospartition 创建DOS主分区createsadirectory 创建一个目录currentfile 当前文件defrag 整理碎片dele 删去deltree 删除树devicedriver 设备驱动程序dialogbox 对话栏directionkeys 方向键directly 直接地directorylistargument 目录显示变量directoryof 目录清单directorystructure 目录结构diskaccess 磁盘存取diskcopy 磁盘拷贝diskspace 磁盘空间displayfile 显示文件displayoptions 显示选项displaypartitioninFORMation 显示分区信息dosshell DOS 外壳doubleclick 双击driveletter 驱动器名editmenu 编辑选单emsmemory ems内存endoffile 文件尾endofline 行尾enterchoice 输入选择entiredisk 转换磁盘environmentvariable 环境变量everyfileandsubdirectory 所有的文件和子目录existingdestinationfile 已存在的目录文件时expandedmemory 扩充内存expandtabs 扩充标签explicitly 明确地extendedmemory 扩展内存fastest 最快的fatfilesystem fat 文件系统fdiskoptions fdisk选项fileattributes 文件属性fileFORMat 文件格式filefunctions 文件功能fileselection 文件选择fileselectionargument 文件选择变元filesin 文件在filesinsubdir 子目录中文件fileslisted 列出文件filespec 文件说明filespecification 文件标识filesselected 选中文件findfile 文件查寻fixeddisk 硬盘fixeddisksetupprogram 硬盘安装程序fixeserrorsonthedisk 解决磁盘错误floppydisk 软盘FORMatdiskette 格式化磁盘FORMatsadiskforusewithmsdos 格式化用于MS-DOS的磁盘FORMfeed 进纸freememory 闲置内存fullscreen 全屏幕functionprocedure 函数过程graphical 图解的graphicslibrary 图形库groupdirectoriesfirst 先显示目录组hangup 挂断harddisk 硬盘hardwaredetection 硬件检测hasbeen 已经helpfile 帮助文件helpindex 帮助索引helpinFORMation 帮助信息helppath 帮助路径helpscreen 帮助屏helptext 帮助说明helptopics 帮助主题helpwindow 帮助窗口hiddenfile 隐含文件hiddenfileattribute 隐含文件属性hiddenfiles 隐含文件howto 操作方式ignorecase 忽略大小写incorrectdos 不正确的DOSincorrectdosversion DOS 版本不正确indicatesabinaryfile 表示是一个二进制文件indicatesanasciitextfile 表示是一个ascii文本文件insertmode 插入方式insteadofusingchkdsktryusingscandisk 请用scandisk,不要用chkdsk inuse 在使用invaliddirectory 无效的目录kbytes 千字节keyboardtype 键盘类型labeldisk 标注磁盘laptop 膝上largest executable program 最大可执行程序large stmemory block available 最大内存块可用left handed 左手习惯left margin 左边界line number 行号line numbers 行号line spacing 行间距list by files insorted order 按指定顺序显示文件listfile 列表文件listof 清单locatefile 文件定位lookat 查看lookup 查找macroname 宏名字makedirectory 创建目录memoryinfo 内存信息memorymodel 内存模式menubar 菜单条menucommand 菜单命令menus 菜单messagewindow 信息窗口microsoft 微软microsoftantivirus 微软反病毒软件microsoftcorporation 微软公司modemsetup 调制解调器安装modulename 模块名monitormode 监控状态monochromemonitor 单色监视器moveto 移至multi 多newdata 新建数据newer 更新的newfile 新文件newname 新名称newwindow 新建窗口norton nortonnostack 栈未定义noteusedeltreecautiously 注意:小心使用deltree onlinehelp 联机求助optionally 可选择地pageframe 页面pagelength 页长pctools pc工具postｓｃｒｉｐｔ附言printall 全部打印printdevice 打印设备printerport 打印机端口programfile 程序文件pulldown 下拉pulldownmenus 下拉式选单quickFORMat 快速格式化quickview 快速查看readonlyfile 只读文件readonlyfileattribute 只读文件属性readonlyfiles 只读文件readonlymode 只读方式redial 重拨repeatlastfind 重复上次查找reportfile 报表文件resize 调整大小respectively 分别地rightmargin 右边距rootdirectory 根目录runtimeerror 运行时出错saveall 全部保存saveas 另存为scandisk 磁盘扫描程序screencolors 屏幕色彩screenoptions 屏幕任选项screensaver 屏幕暂存器screensavers 屏幕保护程序screensize 屏幕大小scrollbars 翻卷栏scrolllockoff 滚屏已锁定searchfor 搜索sectorspertrack 每道扇区数selectgroup 选定组selectionbar 选择栏setactivepartition 设置活动分区setupoptions 安装选项shortcutkeys 快捷键showclipboard 显示剪贴板singleside 单面sizemove 大小/移动sorthelp S排序H帮助sortorder 顺序stackoverflow 栈溢出standalone 独立的startupoptions 启动选项statusline 状态行stepover 单步summaryof 摘要信息swapfile 交换文件switchto 切换到sync 同步systemfile 系统文件systemfiles 系统文件systeminfo 系统信息systeminFORMation 系统信息程序tableofcontents 目录terminalemulation 终端仿真terminalsettings 终端设置testfile 测试文件testfileparameters 测试文件参数theactivewindow 激活窗口togglebreakpoint 切换断点tomsdos 转到MS-DOStopmargin 页面顶栏turnoff 关闭unmark 取消标记unselect 取消选择usesbareFORMat 使用简洁方式useslowercase 使用小写useswidelistFORMat 使用宽行显示usinghelp 使用帮助verbosely 冗长地videomode 显示方式viewwindow 内容浏览viruses 病毒vision 景象vollabel 卷标volumelabel 卷标volumeserialnumberis 卷序号是windowshelp windows 帮助wordwrap 整字换行workingdirectory 正在工作的目录worm 蠕虫writemode 写方式writeto 写到xmsmemory 扩充内存--------------------------------------------------------------------------------网络安全方面的专业词汇Access Control List（ACL）访问控制列表access token 访问令牌account lockout 帐号封锁account policies 记帐策略accounts 帐号adapter 适配器adaptive speed leveling 自适应速率等级调整Address Resolution Protocol(ARP) 地址解析协议Administrator account 管理员帐号ARPANET 阿帕网（internet的前身）algorithm 算法alias 别名allocation 分配、定位alias 小应用程序allocation layer 应用层API 应用程序编程接口anlpasswd 一种与Passwd+相似的代理密码检查器applications 应用程序ATM 异步传递模式attack 攻击audio policy 审记策略auditing 审记、监察back-end 后端borde 边界borde gateway 边界网关breakabie 可破密的breach 攻破、违反cipher 密码ciphertext 密文CAlass A domain A类域CAlass B domain B类域CAlass C domain C类域classless addressing 无类地址分配cleartext 明文CSNW Netware客户服务client 客户，客户机client/server 客户机/服务器code 代码COM port COM口（通信端口）CIX 服务提供者computer name 计算机名crack 闯入cryptanalysis 密码分析DLC 数据链路控制decryption 解密database 数据库dafault route 缺省路由dafault share 缺省共享denial of service 拒绝服务dictionary attack 字典式攻击directory 目录directory replication 目录复制domain 域domain controller 域名控制器domain name 域名域名其实就是入网计算机的名字，它的作用就象寄信需要写明人们的名字、地址一样重要。
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InPromoting Research Integrity in a GlobalEnvironment; Mayer, T., Steneck, N., eds.;Imperial College Press / World ScientificPublishing: Singapore; Chapter 50, pp.309-16.[Return to top]。
Featuring innovative designs guided by customer input, PC Series printers areoptimized for healthcare, retail and hospitality markets – as well as light-duty manufacturing, warehousing and general office duties.Designed for user-friendliness and flexibility, compact PC Series desktop printers provide an intuitive label printing solution. Available in two-inch wide direct thermal (PC23d), four-inch wide direct thermal (PC43d) or four-inch wide thermal transfer (PC43t) models, PC Series printers are perfect for space-constrained settings. Their low cost and fast operation make them thesmart choice for light-duty labeling applications where users need reliable, easy-to-use printers.PC Series printers were designed for quick set-up and trouble-free use. With a variety of placement options including wall-mounted and battery-powered, these printers adapt to their environment and fit right in. Common printer tasks are simple and training needs are reduced, because PC Series printers come with either a universal icon interface or color LCD in 10 languages. It’s even possible to configure and update your printer on the spot, using a USB thumbdrive – no computer necessary. The PC43t thermal transfer printer supports both 12.7 mm (0.5 in) and 25.4 mm (1 in) ribbon cores. By accommodating larger ribbon lengths of up to 300 m (984 ft), the need for frequent media supply replenishment is reduced, eliminating downtime and hassle.Considering the switch to the PC Series from another printer brand? Withcomprehensive command language support – including ZSim2, our fast, friendly and complete ZPL-II emulation – upgrading to the PC Series has never been simpler.PC SERIESDesktop PrintersFEATURES AND BENEFITSTen-language LCD or intuitive icon graphical user interface.Simple to use and maintain, with easy one-handed media reloading.Comprehensive printer command language support,including ZSim2, makes upgrading easy.Flexible, with user-installableconnectivity upgrades and accessories.This Smart Printer runs apps right inside the printer; you can add keyboards, scanners or other USB peripherals for increased efficiency.With a wide variety of user-installable options, you can rest assured PC Series printers can grow as your business grows. Modular connectivity allows PC Series printers to fit into your existing network environment. USB comes standard along with options for user-installable serial, parallel, secure Ethernet and dual wireless card with Bluetooth® and CCX-compliant 802.11 b/g/n.PHYSICAL DESCRIPTIONThe compact PC Series includes both direct thermal (PC23d and PC43d) or thermal transfer (PC43t) printers designed for self-adhesive labels, non-adhesive tags, linerless, floodcoat or continuous paper strip roll.SPECIFICATIONS BY MODELPC43D 167 mm(6.6 in)180 mm(7.1 in)215 mm(8.4 in)1.72 kg(3.8 lb)PC43T182 mm(7.2 in)227 mm(8.9 in)281 mm(11.1 in)2.7 kg(5.9 lb)PC23D177 mm(6.9 in)125 mm(4.9 in)215 mm(8.5 in)1.45 kg(3.2 lb)Real-Time Clock: Standard (LCD) Adjustable Gap Sensor: Standard (LCD)PRINT SPECIFICATIONSMaximum Label Width:PC43: 118 mm (4.65 in)PC23d: 60 mm (2.36 in)Maximum Label Length:Standard: 203 dpi – 1727 mm (68 in); 300 dpi – 900 mm (35 in)Print Direction: Prints text, barcodes and graphics in all four directionsPrint Resolution: 8 dots/mm (203 dpi) or 12 dots/mm (300 dpi)Print Width:PC43: 203 dpi – max. 104 mm (4.1 in); 300 dpi – max. 106 mm (4.2 in)PC23d: 203 dpi – max. 56 mm (2.2 in); 300 dpi – max. 54 mm (2.1 in)Printing Speed: Selectable up to 8 ips (203.2 mm/ sec) for 203 dpi; 6 ips (152.4 mm/sec) for 300 dpiMEDIA SPECIFICATIONSLabel Roll:Maximum Diameter: 127 mm (5 in) Core Diameter: Min. 25.4 mm (1 in); Max.38.1 mm (1.5 in)Paper Width:PC43: Max. 118 mm (4.7 in); Min. 19mm (0.75 in)PC23d: Max. 60 mm (2.36 in); Min. 15mm (0.59 in)Label Length: Min. 6.35 mm (0.25 in) Labels: A wide selection of stock and custom size labels are available from Honeywell Media.Ribbon Roll: PC43t accepts both 12.7 mm (0.5 in) and 25.4 mm (1.0 in) coreCore: 12.7 mm ID (0.5 in ID) or 25.4 mm ID (1.0 in ID)Min Width: 25.4 mm (1.0 in) – ribbon only,core width must be 111 mm (4.37 in)Max Width: 110 mm (4.3 in)Max. Length: 12.7 mm (0.5 in): 91 m(299 ft); 25.4 mm (1.0 in): 300 m (984 ft)Thickness (Includes Liner): 0.06 mm(0.003 in) to 0.15 mm (0.006 in); optionalthick media spring kit for media up to0.20 mm (0.008 in)Ribbons: A wide selection of widths andformulations availableConnect to Print: The printer comeswith all included: software, drivers, USBcable, power adapter, power cord, a handyQuickGuide to facilitate getting started, aPrinterCompanion CD with label designprogram, Windows® driver, configurationsoftware and documentationCommunications: 802.11 b/gSOFTWAREPrinter Command Languages:IPL, DP, ZSim2 (ZPL-II), DSim (DPL),ESim (EPL)XML enabled for SAP® AII and Oracle®WMSApplications/Drivers:InterDriver Windows printer driverCUPS driver for LinuxHoneywell Device Types for SAPHoneywell label design and print packageSmart Printing Languages:Honeywell C# for PrintersSmart Printing Developer Resource KitWrite apps with .NET-compatibledevelopment environmentsHoneywell Fingerprint – Use HoneywellFingerprint Application Builder (IFAB)Configuration and DeviceManagement Support:PrintSet for printer configurationHoneywell SmartSystems™ FoundationSophisticated web interface forconfiguration, upgrade and 1:1managementWavelink Avalanche™CHARACTER SETS/FONTSPrinting Character Sets: English andExtended Latin, Cyrillic, Greek, Turkish,Hebrew, Arabic, Baltic, Baltic RIM,Vietnamese, Thai and more withMonotype Universal Font ScalingTechnology (UFST) and WorldTypeLayout Engine (WTLE)Resident Fonts: Century Schoolbook, CGTimes, CG Times Bold, Letter Gothic, AndaleMono, Andale Mono Bold, Univers, UniversBold, Univers Condensed Bold, UniversExtra Condensed, OCR-A, OCR-BOptional: Support for downloadingTrueType and TrueType-based OpenTypefonts and user-defined fontsLCD DISPLAY LANGUAGEStandard: English, French, German, Italian,Portuguese, Russian, SpanishOptional: Simplified Chinese, TraditionalChinese, KoreanGRAPHICSNative support for one-bit BMP, GIF,PCX and PNG graphics format sBARCODE SYMBOLOGIESAll major one-dimensional barcodesymbologies are available, plus two-dimensional and composite codes:Aztec, Code 16K, Code 49, Data Matrix,Dot Code, EAN-8, EAN-13, EAN.UCC 128,Grid Matrix, HIBC 39, HIBC 128, MaxiCode,MSI (modified Plessey), PDF417, MicroPDF417, Planet, Plessey, Postnet, QR-Code,RSS-14 (variations)Environment (Printing): +5°C to +40°C(+40°F to +104°F)Humidity (Printing): 10–80% RHnon-condensingMaterials: Disinfectant-resistant plasticcase will not be damaged when cleanedwith any chemical in the following list.These chemical disinfectants and cleaningsolutions have been successfully testedon the printers. Cleaning the printers byusing a wipe or cloth dampened by anyof the following disinfectants or cleaningsolutions will not cause damage to theprinter case or media window.SOFTWARESeparate Power Supply:Input: 100–240V AC/50–60 Hz, 1.5 A Output: 24V DC, 2.5 AEnergy Star CompliantSmart Battery unit accessory(PC43d only)MEMORYStandard: 128 MB Flash, 128 MBRAM (DDR2)Optional: Up to 32 GB via userUSB thumbdriveINTERFACEStandard: USB Device Type B connector v.2.0 high speed, USB Host Type A connector v.2.0 high speedField-Installable: Ethernet 10/100 Mbps module, Dual radio module (802.11 b/g/n and Bluetooth V2.1), USB to Serial adapter (RS-232), USB to Parallel adapterPROTOCOLSerial Flow Control: XON/XOFF, RTS/CTS (DTR/DSR)Wireless Protocol: WEP static (64/128 bits), WPA, WPA2, WEP dynamic, EAP-PEAP, EAP- TTLS, LEAP, EAP-FAST, EAP-TLS, Wi-Fi certifieREGULATORY APPROVALSCE, FCC Class A, cULus, UL, GS, TUVGS, BSMI, D Mark, cUL, CCC (China), KCC (South Korea), C-Tick (Australia/New Zealand)FACTORY-INSTALLED OPTIONS13.56 MHz HF RFID ISO 15693 (PC23d), UHF RFID (PC43)USER-INSTALLABLEACCESSORIES/ UPGRADESFor complete list of accessories, see thePC Series Accessory Catalog.SERVICENo tools required to replace printhead andplaten roller, user-accessible odometer.USER INTERFACEChoice of:• 59.94 mm (2.36 in) color LCD, 480x 234 resolution in 10 languages, 8buttons and ready-to-work LED• Graphical back-lit icons: cover open,paper out, ribbon out (PC43t), generalerror, maintenance, pause, thermalprinthead too hot, data status, wirelessstatus (if installed), Bluetooth status (ifinstalled), ready-to-work LED and onePrint/Feed button• User-configurable audiosounds with volume levelsINDUSTRY APPROVALSHealthcare: Epic (Validated), McKesson(Certified), Sunquest (Validated)SAFETY APPROVALSNorth America: UL and cUL Listed,UL 60950-1Europe: D Mark, EN 60950-1;CE markedMexico: NYCE Certified, NOM 19Other Countries: IEC 60950-1EMC APPROVALSUSA FCC Title 47, Part 15, Subpart A, ClassB; Europe EMC Directive (EN55022 Class B+ EN55024); CISPR22WARRANTYOne-year standard warranty; additionalservice packages available throughHoneywell Repair ServicesFor a complete listing of all complianceapprovals and certifications, please visitwww.honeywellaidc. com/compliance.For a complete listing of all supportedbarcode symbologies, please visit www./ symbologies.SmartSystems is a trademark or registeredtrademark of Honeywell International Inc.Windows is a trademark or registeredtrademark of Microsoft Corporation.The Bluetooth trademarks are owned byBluetooth SIG, Inc. U.S.A. and licensedto Honeywell International Inc.SAP is a trademark or registered trademarkof SAP SE.Oracle is a trademark or registeredtrademark of Oracle Corporation.Wavelength Avalanche is atrademark or registered trademarkof Wavelength Corporation.Viraguard is a trademark or registeredtrademark of Veridien Corporation.All other trademarks are the propertyof their respective owners.PC Series Desktop Printers PC23d/PC43d/PC43t Data Sheet LTR | Rev K | 06/21©2021 Honeywell International Inc.For more informationHoneywell Safety and Productivity Solutions300 S Tryon St Suite 500Charlotte, NC 28202800-582-4263。
医学英文摘要写作How to write a medical English abstract第一章概述一、摘要的定义、用途、和长度二、摘要的内容三、摘要的类型四、摘要的写作格式五、摘要写作的注意事项What is an abstract?An abstract is a brief summary of the most important points in a scientific paper.摘要是作者研究过程、研究目的、研究方法和研究结果的简要陈述和概括。
Purposes for AbstractsAbstracts typically serve five main goals:Help readers decide if they should read an entire articleHelp readers and researchers remember key findings on a topicHelp readers understand a text by acting as a pre-reading outline of key points Index articles for quick recovery and cross-referencingAllow supervisors to review technical work without becoming bogged down in details二、摘要的内容Contents1. Title2. Name of the author3. Unit of the author/address4. Text of the abstract5. Keywords1）目的2）方法3）结果4）结果的分析、比较、评价以及应用，提出的问题以及建议5）其他三、摘要的类型1. descriptive abstract ——描述性摘要2. informative abstract——资料性摘要3. descriptive-informative abstract——描述-资料性摘要1. Non-structured abstract （非结构式摘要）2. Structured abstract （结构式摘要）full-structuredsemi-structured1.描述性摘要Descriptive Abstract/ Indicative AbstractThe descriptive abstracts tell what topics are taken up in the paper. They contain indicative information on purpose, scope, or methodology in the original documents, but mention little or nothing about details of results, conclusions or recommendations. The advantages of a descriptive abstract are that it is easy to write and is usually short; a serious disadvantage is that it contains little information.一般只用两三句话概括论文或报道的主题，而不涉及具体的数据和结论，通常用于综述、会议报告等。
摘要抽象英语作文Abstract。
Abstract writing is an important skill that is required in many academic and professional settings. It involves summarizing the main points of a document or presentationin a concise and clear manner. This skill is particularly important in scientific research, where abstracts are often the first point of contact between researchers and their audience.In this article, we will discuss the key elements of a good abstract and provide some tips on how to write an effective one.Introduction。
The introduction of an abstract should provide some context for the research or presentation that is being summarized. This may include a brief overview of the topic,the research question, and the methods used to answer it.Methods。
The methods section of an abstract should provide a concise summary of the research methods used in the study. This may include the sample size, the type of data collected, and the statistical analyses used to analyze the data.Results。
回顾某领域已取得的研究结果或介绍相关知识常用动词：present, summarize, review, outline句式：…is presented in this paper.This paper reviews the method for dealing with…This article summarizes the theory on...阐明论文写作和研究目的常用词：名词：purpose, aim, objective, goal动词：aim, attempt to, initiate, intend to, seek句式：The purpose of this study is to explore new methods on …The paper attempts to define ..in terms of.The study is aimed at finding out the basic similarities between … and …The main objective of the work is to justify.The primary goal of this research is …The main objective of our investigation has been to obtain some knowledge of …Based on recent research, the author intends to outline the framework of…The authors are now initiating some experimental investigation to establish.论文观点和作者观点常用词：argue, account for, address, characterize, concern, contribute, describe, disclose, deal with, devote to, explain, introduce, present, report句式：This paper presents the mathematical model and its algorithm used for …The calibration and experiment design of multivariate force sensors are discussed. This paper reports the preparation and quantum confinement effects of…The principles and methodology of language teaching are described in this article. This paper is mainly devoted to ...介绍研究过程和研究范围常用词:过程：analyze, consider, discuss, examine, study, investigate, state, propose 范围：contain, cover, include, outline, scope, field, domain句式:The characteristic of …was investigated.The paper analyzes the possibility of ...We study the one-step-synthesis method for …in this paper.This article discusses the method of calculation of …The principle of constructing … is proposedThis paper states the reasons for...This study identifies some procedures for …This article outlines the preliminary process of …The scope of the study covers.The study includes.The paper contains the specific topic on …介绍计算、测量常用词：calculate, compute, determine, estimate, measure, work out句式：This paper determines the proper temperature for …The cooling rate was calculated by means of.The rational rage of power is measured by …In the paper, we measured the orientation and estimated parameter for ...The author worked out the probability of ...The author has computed equilibrium constant K and …阐明论证常用词：confirm, demonstrate, find, identify, indicate, monitor, note, observe, point out, prove, provide句式：The initial particles are found to be …It is found that the amorphous silicon nitride show a tendency in...It is noted that …can be found in …The result provides a sound basis for …The study of those properties indicate…The experimental results demonstrate that…The effects of …were observed and monitored.说明试验过程常用词：experiment, test, sample句式：The samples of pyroelectric ceramics （电释热陶瓷）亚©[© collected by …We sampled the blood and urine of …The blood screening test for the AIDS antibody has been carried out on…We experimented on the sintering property（流延特性）of …The new protocol architecture for distributed multimedia systems has been tested in …介绍应用、用途常用词：application, use及其动词形式句式：In this paper, the czochralski crystal growth method has been applied in ……technique is used to …The application of the new design is to develop and maintain …展示研究结果常用词：result, cause, increase, lessen, as a result, result in, arrive at句式：As a result we have got pure particle of ...The finding of our research on methodologies in …is….The results of calculation show that the minimum velocity arrives at...The relationship between …and ...is characterized by …The room temperature resistivity is lessened to …介绍结论常用词：conclude, summary, to sum up, lead to, in conclusion, conclusion句式：It is concluded that the absorption spectra of two kinds of particles include... We concluded that …It is concluded that...The conclusion of our research is …On the basis of …，the following conclusion can be drawn …Finally, a summary is given of …To sum up, we have revealed …Our argument proceeds in …The research has led to the discovery of …进行评述句式：There are hardly any data about …Middle management is considered as the go-between of …The shapes and locations of these inclusions are believed to be related to …The finding is acknowledged as essential to ...Existing methods are not sufficient for ...It is difficult to improve the therapy under the conditions of ...The disproportion of age groups will unfortunately lead to …The improper use of methods would seriously influence the performance of …The subject will deepen the understanding of …However, it does not mean that there is no limitation of ...It is well-known that in the field of .., there are still difficulties and challenges. Environmental protection has become the most important concern of …推荐和建议常用词：propose, suggest, recommend句式:The calculation suggests that…Bulk silk is proposed to be the alternative of ordinary silk because ...The finite element method is recommended to …提出进一步研究的可能性常用词：demand, desirable, expect, necessary, necessity, need, require, requirement 句式:Another term of the …need addressing because…However, the development of MRI is absolutely necessary for …To establish a .. .model continues to be a major concern for ...The underway measurement of sea surface temperature has made it necessary to... ..requires more work on …More concern about the blood cleaning point out the need for …There is a growing demand for …There is a surge in the use of …Although there is already an efficient procedure, more study is still needed.突出论文重点句式：The development of…is the primary concern of this paper.Particular attention is paid on the cultivation of …Interface structure is emphasized in the article because …This paper concentrates on the effects of …The chief consideration is …。
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255,130resultsJournal of Cleaner ProductionVolume 243, 10 January 2020, 118595OutlineHighlightsAbstractGraphical abstractKeywords1. Introduction2. Literature review2.1. Green hiring2.2. Green training and involvement2.3. Green performance management and compensation2.4. Hypotheses development3. Research methodology3.1. Sampling techniques3.2. Measurement development4. Data results4.1. Interviews analysis4.2. Questionnaires analysis4.2.1. Assessment of the measurement model4.2.2. Assessment of the structural model5. Framework development6. General discussion and conclusions7. Managerial implications and future studies7.1. Implications for practice on cleaner production and sustainability 7.2. Limitations and future research workThe impact of green human resource management practices onsustainable performance in healthcare organisations: A conceptual frameworkAuthor links open overlay panelSharifa K.MousaaMohammedOthmanbaEngineering Management Program, Faculty of Graduate Studies, An-Najah National University, P.O. Box 7, Nablus, West Bank, Palestine bDepartment of Industrial Engineering, Faculty of Engineering and Information Technology, An-Najah National University, P.O. Box 7, Nablus, West Bank, PalestineReceived 1 July 2019, Revised 18 September 2019, Accepted 24 September 2019, Available online 25 September 2019.Handling editor: Cecilia Maria Villas Bôas de Almeida1. IntroductionProtecting and preserving the natural eco-system’s resources has been considered a main priority of decision-makers and top managers in various business fields (Howard-Grenville et al., 2014). Currently, companies are engaging in increased competition, which requires managers to keep finding new ways in which to optimise their essential organisational resources, i.e. human resources (HR), where HR isconsidered a key success factor for the implementation of polices, practices, and boosting sustainable performance (Harel and Tzafrir, 1999, Sheehan, 2014).2、点击高级检索页面的Search tips，复制其中你感兴趣的部分内容到作业中。
On User Choice in Graphical Password Schemes Darren Davis Fabian Monrose Michael K.Reiter Johns Hopkins University Carnegie Mellon University {ddavis,fabian}@ reiter@AbstractGraphical password schemes have been proposed as an alternative to text passwords in applications that support graphics and mouse or stylus entry.In this paper we detail what is,to our knowledge,the largest published empirical evaluation of the effects of user choice on the security of graphical password schemes.We show that permitting user selection of passwords in two graphical password schemes,one based directly on an existing commercial product, can yield passwords with entropy far below the the-oretical optimum and,in some cases,that are highly correlated with the race or gender of the user.For one scheme,this effect is so dramatic so as to ren-der the scheme insecure.A conclusion of our work is that graphical password schemes of the type we study may generally require a different posture to-ward password selection than text passwords,where selection by the user remains the norm today.1IntroductionThe ubiquity of graphical interfaces for applications, and input devices such as the mouse,stylus and touch-screen that permit other than typed input, has enabled the emergence of graphical user authen-tication techniques(e.g.,[2,8,4,24,7,30]).Graphi-cal authentication techniques are particularly useful when such devices do not permit typewritten input. In addition,they offer the possibility of providing a form of authentication that is strictly stronger than text passwords.History has shown that the dis-tribution of text passwords chosen by human users has entropy far lower than possible[22,5,9,32], and this has remained a significant weakness of user authentication for over thirty years.Given the fact that pictures are generally more easily remembered than words[23,14],it is conceivable that humans would be able to remember stronger passwords of a graphical nature.In this paper we study a particular facet of graphical password schemes,namely the strength of graphi-cal passwords chosen by users.We note that not all graphical password schemes prescribe user cho-sen passwords(e.g.,[24]),though most do(e.g.,[2, 8,3,4,7]).However,all of these schemes can be implemented using either system-chosen or user-chosen passwords,just as text passwords can be user-chosen or system-chosen.As with text pass-words,there is potentially a tradeoffin graphical passwords between security,which benefits by the system choosing the passwords,and usability and memorability,which benefit by permitting the user to choose the password.Our evaluation here focuses on one end of this spectrum,namely user chosen graphical passwords. The graphical password schemes we evaluate are a scheme we call“Face”that is intentionally very closely modeled after the commercial Passfaces TM scheme[3,24]and one of our own invention(to our knowledge)that we call the“Story”scheme.In the Face scheme,the password is a collection of k faces, each chosen from a distinct set of n>1faces,yield-ing n k possible choices.In the Story scheme,a pass-word is a sequence of k images selected by the user to make a“story”,from a single set of n>k im-ages each drawn from a distinct category of image types(cars,landscapes,etc.);this yields n!/(n−k)! choices.Obviously,the password spaces yielded by these schemes is exhaustively searchable by a com-puter for reasonable values of k and n(we use k=4 and n=9),and so it relies on the authentication server refusing to permit authentication to proceed after sufficiently many incorrect authentication at-tempts on an account.Nevertheless,an argument given to justify the presumed security of graphical passwords over text passwords in such environments is the lack of a predefined“dictionary”of“likely”choices,as an English dictionary provides for En-glish text passwords,for example(c.f.,[8,Section 3.3.3]).For our study we utilize a dataset we collected dur-ing the fall semester of2003,of graphical password usage by three separate computer engineering and computer science classes at two different universi-ties,yielding a total of154subjects.Students used graphical passwords(from one of the two schemes above)to access their grades,homework,homework solutions,course reading materials,etc.,in a man-ner that we describe in Section3.2.At the end of the semester,we asked students to complete an exit survey in which they described why they picked the faces they did(for Face)or their chosen sto-ries(for Story)and some demographic information about themselves.Using this dataset,in this paper we evaluate the Face and Story schemes to estimate the ability of an attacker to guess user-chosen passwords,possibly given knowledge of demographic information about the user.As we will show,our analysis suggests that the faces chosen by users in the Face scheme is highly affected by the race of the user,and that the gender and attractiveness of the faces also bias password choice.As to the latter,both male and female users select female faces far more often than male faces,and then select attractive ones more of-ten than not.In the case of male users,we found this bias so severe that we do not believe it possible to make this scheme secure against an online attack by merely limiting the number of incorrect password guesses permitted.We also quantify the security of the passwords chosen in the Story scheme,which still demonstrates bias though less so,and make rec-ommendations as to the number of incorrect pass-word attempts that can be permitted in this scheme before it becomes insecure.Finally,we benchmark the memorability of Story passwords against those of the Face scheme,and identify a factor of the Story scheme that most likely contributes to its relative security but also impinges on its memorability.On the whole,we believe that this study brings into question the argument that user-chosen graphical passwords of the type we consider here are likely to offer additional security over text passwords,unless users are somehow trained to choose better pass-words,as they must be with text passwords today. Another alternative is to utilize only system-chosen passwords,though we might expect this would sacri-fice some degree of memorability;we intend to eval-uate this end of the spectrum in future work.The rest of this paper is structured as follows.We describe related work in Section2.In Section3 we describe in more detail the graphical password schemes that we evaluate,and discuss our data sources and experimental setup.In Section4we in-troduce our chosen security measures,and present our results for them.In Section5we discuss issues andfindings pertinent to the memorability of the two schemes.Finally,we conclude in Section6.2Related WorkThis work,and in particular our investigation of the Face scheme,was motivated in part by scientific lit-erature in psychology and perception.Two results documented in the psychological literature that mo-tivated our study are:•Studies show that people tend to agree about the attractiveness of both adults and children, even across cultures.(Interested readers are referred to[10]for a comprehensive literature review on attractiveness.)In other words,the adage that“beauty is in the eye of the be-holder,”which suggests that each individual has a different notion of what is attractive,is largely false.For graphical password schemes like Face,this raises the question of what in-fluence general perceptions of beauty(e.g,fa-cial symmetry,youthfulness,averageness)[1,6] might have on an individual’s graphical pass-word choices.In particular,given these a pri-ori perceptions,are users more inclined to chose the most attractive images when constructing their passwords?•Studies show that individuals are better able to recognize faces of people from their own race than faces of people from other races[31,20, 11,29].The most straightforward account of the own-race effect is that people tend to have more exposure to members of their own racial group relative to other-race contact[31].As such,they are better able to recognize intra-racial distinctive characteristics which leads to better recall.This so-called“race-effect”[13, 15]raises the question of whether users would favor members of their own race when selecting images to construct their passwords.To the best of our knowledge,there has been no prior study structured to quantify the influence of the various factors that we evaluate here,including those above,on user choice of graphical passwords, particularly with respect to security.However,prior reports on graphical passwords have suggested the possibility of bias,or anecdotally noted apparent bias,in the selection or recognition of passwords. For example,a document[24]published by the cor-poration that markets Passfaces TM makes reference to the race-effect,though stops short of indicating any effect it might have on password choice.In a study of twenty users of a graphical password sys-tem much like the Story scheme,except in which the password is a set of images as opposed to a sequence, several users reported that they did not select pho-tographs of people because they did not feel they could relate personally to the image[4].The same study also observed two instances in which users se-lected photographs of people of the same race as themselves,leading to a conjecture that this could play a role in password selection.The Face scheme we consider here,and minor vari-ants,have been the topic of several user studies fo-cused on evaluating memorability(e.g.,[34,27,28, 3]).These studies generally support the hypothe-sis that the Face scheme and variants thereof of-fer better memorability than text passwords.For instance,in[3],the authors report results of a three month trial investigation with34students that shows that fewer login errors were made when us-ing Passfaces TM(compared to textual passwords), even given significant periods of inactivity between logins.Other studies,e.g.,[34,4],have explored memora-bility of other types of graphical passwords.We em-phasize,however,that memorability is a secondary consideration for our purposes.Our primary goal is to quantify the effect of user choice on the security of passwords chosen.3Graphical Password SchemesAs mentioned earlier,our evaluation is based on two graphical schemes.In the Face scheme,the pass-word is a collection of k faces,each selected from a distinct set of n>1faces.Each of the n faces are chosen uniformly at random from a set of faces classified as belonging to either a“typical”Asian,Figure1:In the Face scheme,a user’s password is a sequence of k faces,each chosen from a distinct set of n>1faces like the one above.Here,n=9,and images are placed randomly in a3×3grid.black or white male or female,or an Asian,black or white male or female model.This categorization is further discussed in Section3.1.For our evaluation we choose k=4and n=9.So,while choosing her password,the user is shown four successive3×3 grids containing randomly chosen images(see Fig-ure1,for example),and for each,she selects one im-age from that grid as an element of her password. Images are unique and do not appear more than once for a given user.During the authentication phase,the same sets of images are shown to the user,but with the images randomly permuted.In the Story scheme,a password is a sequence of k unique images selected by the user to make a “story”,from a single set of n>k images,each de-rived from a distinct category of image types.The images are drawn from categories that depict every-day objects,food,automobiles,animals,children, sports,scenic locations,and male and female mod-els.A sample set of images for the story scheme is shown in Figure2.3.1ImagesAs indicated above,the images in each scheme were classified into non-overlapping categories.In Face, there were twelve categories:typical Asian males,Figure2:In the Story scheme,a user’s password is sequence of k unique images selected from one set of n images,shown above,to depict a“story”.Here, n=9,and images are placed randomly in a3×3grid.typical Asian females,typical black males,typical black females,typical white males,typical white females,Asian male models,Asian female mod-els,black male models,black female models,white male models and white female models.In the Story scheme,there were nine categories:animals,cars, women,food,children,men,objects,nature,and sports.The images used for each category were carefully selected from a number of sources.“Typical male”and“typical female”subjects include faces selected from(i)the Asian face database[26]which con-tains color frontal face images of103people and (ii)the AR Face database[17]which contains well over4000color images corresponding to126peo-ple.For the AR database we used images in angle2 only,i.e,frontal images in the smile position.These databases were collected under controlled conditions and are made public primarily for use in evaluating face recognition technologies.For the most part, the subjects in these databases are students,and we believe provide a good representative population for our study.Additional images for typical male subjects were derived from a random sampling of images from the Sports Illustrated TM NBA gallery.Images of“female models”were gathered from a myriad of pageant sites including Miss USA TM,Miss Universe TM,Miss NY Chinese,and fashion mod-eling sites.Images of“male models”were gath-ered from various online modeling sources including and .For the Story scheme,the“men”and“women”cat-egories were the same as the male and female models in our Face experiment.All other images were cho-sen from and span the previously mentioned categories.To lessen the effect that an image’s intensity,hue, and background color may have on influencing a user choice,we used the ImageMagick library(see )to set image backgrounds to a light pastel color at reduced intensity.Ad-ditionally,images with bright or distracting back-grounds,or of low quality,were deleted.All remain-ing images were resized to have similar aspect ratios. Of course,it is always possible that differences in such secondary factors influenced the results of our experiment,though we went to significant effort to avoid this and have found little to support a hypoth-esis of such influence.3.2ExperimentFor our empirical evaluation we analyze observa-tions collected during the fall semester(roughly the four month period of late-August through early-December)of2003,of graphical password usage by three separate computer engineering and computer science classes at two different universities,yielding a total of154subjects.Each student was randomly assigned to one of the two graphical schemes.Each student then used the graphical password scheme for access to published content including his or her grades,homework,homework solutions,course reading materials,etc.,via standard Java enabled browsers.Our system was designed so that instruc-tors would not post documents on the login server, but rather that this server was merely used to en-crypt and decrypt documents for posting or retrieval elsewhere.As such,from a student’s perspective, the login server provided the means to decrypt doc-uments retrieved from their usual course web pages. Since there was no requirement for users to change their passwords,most users kept one password for the entire semester.However,a total of174pass-Population SchemeGender Race Face Storyany any7995Male any5577Female any2013Male Asian2427Female Asian128Male Black3-Female Black--Male Hispanic-2Female Hispanic--Male White2748Female White84Table1:Population breakdown(in passwords). words were chosen during the semester,implying that a few users changed their password at least once.During the evaluation period there were a to-tal of2648login attempts,of which2271(85.76%) were successful.Toward the end of the semester, students were asked to complete an exit survey in which they described why they picked the faces they did(for Face)or their chosen stories(for Story) and provide some demographic information about themselves.This information was used to validate some of ourfindings which we discuss shortly.Ta-ble1summarizes the demographic information for our users.A gender or race of any includes those for which the user did not specify their gender or race. Such users account for differences between the sum of numbers of passwords for individual populations and populations permitting a race or gender of any.The students participating in this study did so vol-untarily and with the knowledge they were par-ticipating in a study,as required by the Institu-tional Review Boards of the participating univer-sities.However,they were not instructed as to the particular factors being studied and,in particular, that the passwords they selected were of primary interest.Nor were they informed of the questions they would be asked at the end of the study.As such,we do not believe that knowledge of our study influenced their password choices.In addition,since personal information such as their individual grades were protected using their passwords,we have rea-son to believe that they did not choose them inten-tionally to be easily guessable.4Security evaluationRecall that in both the Face and Story schemes,images are grouped into non-overlapping categories.In our derivations below,we make the simplifyingassumption that images in a category are equiva-lent,that is,the specific images in a category thatare available do not significantly influence a user’schoice in picking a specific category.First we introduce some notation.An -element tu-ple x is denoted x( ).If S is either the Face or Storyscheme,then the expression x( )←S denotes the selection of an -tuple x( )(a password or passwordprefix,consisting of image categories)accordingto S,involving both user choices and random algo-rithm choices.4.1Password distributionIn this section we describe how we approximatelycompute Prp(k)←Sfor any p(k),i.e.,the proba-bility that the scheme yields the password p(k).This probability is taken with respect to both random choices by the password selection algorithm and user choices.We compute this probability inductively as follows.Suppose p( +1)=q( )r(1).ThenPrp( +1)←S=Prq( )←S·Prq( )r(1)←S|q( )←S(1) if p( +1)is valid for S and zero otherwise,where Prq(0)←Sdef=1.Here,p( +1)is valid iff <k and,for the Story scheme,p( +1)does not con-tain any category more than once.The second factor Prq( )r(1)←S|q( )←Sshould be under-stood to mean the probability that the user selects r(1)after having already selected q( )according to scheme S.If the dataset contains sufficiently many observations,then this can be approximated byPrq( )r(1)←S|q( )←S≈#q( )r(1)←S#q( )←S,(2)i.e.,using the maximum likelihood estimation, where#x( )←Sdenotes the number of occur-rences of x( )←S in our dataset,and where# x (0)←Sis defined to be the number of pass-words for scheme S in our dataset.A necessary condition for the denominator of (2)to be nonzero for every possible q (k −1)is that the dataset contain N k −1samples for scheme S where N ≥n denotes the number of image categories for S .(N =12in Face,and N =9in Story.)N k −1is over 1700in the Face scheme,for example.And,of course,to use (2)directly to perform a meaningful approximation,significantly more samples would be required.Thus,we introduce a simplifying,Markov assumption:a user’s next decision is influenced only by her immediately prior decision(s)(e.g.,see [16]).In other words,rather than condition on all of the previous choices made in a password (q ( )),only the last few choices are taken into account.Let ...x ( )←S denote the selection of an -tuple, ≥ ,for which the most recent selections are x ( ).Assumption 4.1There exists a constant ˆ≥0such that if ≥ˆthen Prq ( )r (1)←S |q ( )←S≈Pr...s (ˆ )r (1)←S |...s (ˆ)←S(3)where s (ˆ )is the ˆ-length suffix of q ( ).We denote probabilities under this assumption by Pr ˆ [·].In other words,we assume that if ≥ˆ,then the user’s next selection r (1)is influenced only by herlast ˆchoices.This appears to be a reasonable as-sumption,which is anecdotally supported by certain survey answers,such as the following from a user of the Face scheme.“To start,I chose a face that stood out from the group,and then I picked the closest face that seemed to match.”While this user’s intention may have been to choosea selection similar to the first image she selected,we conjecture that the most recent image she selected,being most freshly on her mind,influenced her next choice at least as much as the first one did.Assump-tion 4.1also seems reasonable for the Story scheme on the whole,since users who selected passwords by choosing a story were presumably trying to continue a story based on what they previously selected.Assumption 4.1permits us to replace (2)byPr ˆ q ( )r(1)←S |q ( )←S ≈#...s (ˆ)r (1)←S# ...s (ˆ )←S(4)where s (ˆ )is theˆ -length suffix of q ( )and we define # ...s (0)←S to be the total number of category choices (k times the number of passwords)in our dataset for scheme S .Here,the necessary condition for the denominator of (4)to be nonzero for each s (ˆ )is that the dataset for S contain N ˆsamples,e.g.,in the Face scheme,twelve for ˆ=1,and so on.We further augment the above approach with smoothing in order to compensate for gaps in the data (c.f.,[16]).Specifically,we replace (4)withPr ˆq ( )r (1)←S |q ( )←S ≈# ...s (ˆ)r (1)←S+λˆ ·Ψˆ −1# ...s (ˆ )←S +λˆ(5)where s (ˆ )is the ˆ -length suffix of q ( );λˆ>0is a real-valued parameter;and where if ˆ >0thenΨˆ −1=Pr ˆ −1 q ( )r(1)←S |q ( )←S and Ψˆ −1=1/N otherwise.Note that as λˆ is re-duced toward 0,(5)converges toward (4).And,as λˆ is increased,(5)converges toward Ψˆ −1,i.e.,a probability under Assumption 4.1for ˆ−1,a stronger assumption.So,with sufficient data,we can use a small λˆ and thus a weaker assumption.Otherwise,using a small λˆ risks relying too heavilyon a small number of occurrences of ...s (ˆ)←S ,and so we use a large λˆ and thus the stronger as-sumption.4.2MeasuresWe are primarily concerned with measuring the abil-ity of an attacker to guess the password of a user.Given accurate values for Pr p (k )←S for each p (k ),a measure that indicates this ability is the “guessing entropy”[18]of rmally,guessing entropy measures the expected number of guesses an attacker with perfect knowledge of theprobability distribution on passwords would need in order to guess a password chosen from that distri-bution.If we enumerate passwords p 1(k ),p 2(k ),...in non-increasing order of Pr p i (k )←S ,then the guessing entropy is simplyi>0i ·Pr p i (k )←S (6)Guessing entropy is closely related to Shannon en-tropy,and relations between the two are known.1Since guessing entropy intuitively corresponds more closely to the attacker’s task in which we are inter-ested (guessing a password),we will mainly consider measures motivated by the guessing entropy.The direct use of (6)to compute guessing entropy using the probabilities in (5)is problematic for two reasons.First,an attacker guessing passwords will be offered additional information when performing a guess,such as the set of available categories from which the next image can be chosen.For example,in Face,each image choice is taken from nine images that represent nine categories of images,chosen uni-formly at random from the twelve categories.This additional information constrains the set of possible passwords,and the attacker would have this infor-mation when performing a guess in many scenarios.Second,we have found that the absolute probabil-ities yielded by (5)can be somewhat sensitive to the choice of λˆ ,which introduces uncertainty into calculations that utilize these probabilities numeri-cally.2^02^22^42^62^82^102^12Figure 3:Measures versus λ0for Face To account for the second of these issues,we use the probabilities computed with (5)only to determine an enumeration Π=(p 1(k ),p 2(k ),...)of passwords in non-increasing order of probability (as computed with (5)).This enumeration is far less sensitive to variations in λˆ than the numeric probabilitiesare,2^02^22^42^62^82^102^122^-152^-122^-92^-62^-32^02^32^62^92^122^15Figure 4:Measures versus λ0for Story and so we believe this to be a more robust use of (5).We use this sequence to conduct tests with our dataset in which we randomly select a small set of “test”passwords from our dataset (20%of the dataset),and use the remainder of the data to compute the enumeration Π.We then guess passwords in order of Πuntil each test password is guessed.To account for the first issue identified above,namely the set of available categories during password selection,we first filter from Πthe passwords that would have been invalid given the available categories when the test pass-word was chosen,and obviously do not guess them.By repeating this test with non-overlapping test sets of passwords,we obtain a number of guesses pertest password.We use G avg Sto denote the average over all test passwords,and G med Sto denote the me-dian over all test passwords.Finally,we use G x S for 0<x ≤100to denote the number of guesses sufficient to guess x percent of the test passwords.For example,if 25%of the test passwords could be guessed in 6or fewer guesses,then G 25S =6.We emphasize that by computing our measures in this fashion,they are intrinsically conservative given our dataset.That is,an attacker who was given 80%of our dataset and challenged to guess the remain-ing 20%would do at least as well as our measures suggest.4.3Empirical resultsTo affirm our methodology of using G avg S ,G medS ,and G x S as mostly stable measures of password quality,we first plot these measures under various instancesof Assumption 4.1,i.e.,for various values of ˆand,for each,a range of values for λˆ .For example,inthe case of ˆ =0,Figures 3and 4show measures G avg S ,G med S ,G 25S and G 10S ,as well as the guessing entropy as computed in (6),for various values of λ0.Figure 3is for the Face scheme,and Figures 4is for the Story scheme.The key point to notice is that each of G avg S ,G medS ,G 25S and G 10S is very stable as a function of λ0,whereas guessing entropy varies more (particularly for Face).We highlight this fact to reiterate ourreasons for adopting G avg S ,G med S ,and G xS as our measures of security,and to set aside concerns over whether particular choices of λ0have heavily influ-enced our results.Indeed,even for ˆ=1(with some degree of back-offto ˆ=0as prescribed by (5)),val-ues of λ0and λ1do not greatly impact our measures.For example,Figures 5and 6show G avg S and G 25S for Face.While these surfaces may suggest more vari-ation,we draw the reader’s attention to the small range on the vertical axis in Figure 5;in fact,the variation is between only 1361and 1574.This is in contrast to guessing entropy as computed with (6),which varies between 252and 3191when λ0and λ1are varied (not shown).Similarly,while G 25S varies between 24and 72(Figure 6),the analogous compu-tation using (5)more directly—i.e.,computing thesmallest j such that ji =1Pr p i (k )←S ≥.25—varies between 27and 1531.In the remainder ofthe paper,the numbers we report for G avg S ,G medS ,and G x S reflect values of λ0and λ1that simultane-ously minimize these values to the extent possible.2^102^10!1!0Figure 5:G avg Sversus λ0,λ1for Face Tables 2and 3present results for the Story scheme2^10!1!0Figure 6:G 25S versus λ0,λ1for Face PopulationG avg S G med S G 25S G 10S Overall 79042811235Male 8264048753Female98972312598White Male 84439414676Asian Male87758915520Table 2:Results for Story,λ0=2−2and the Face scheme,respectively.Populations with less than ten passwords are excluded from these ta-bles.These numbers were computed under Assump-tion 4.1for ˆ=0in the case of Story and for ˆ =1in the case of Face.λ0and λ1were tuned as indicated in the table captions.These choices were dictated by our goal of minimizing the various measures weconsider (G avg S ,G med S ,G 25S and G 10S ),though as al-ready demonstrated,these values are generally not particularly sensitive to choices of λ0and λ1.The numbers in these tables should be considered in light of the number of available passwords.StoryPopulation G avg S G med S G 25S G 10S Overall 1374469132Male 123421882Female 2051145425512Asian Male 108425721 5.5Asian Female 97344519 5.2White Male12608181.6Table 3:Results for Face,λ0=2−2,λ1=22。
