Abstract A product-line approach to database reporting
Abstract A Language Abstraction Layer for Relational DBMS
A Language Abstraction Layer for Relational DBMSNigel StangerDepartment of Information Science, University of Otago,Dunedin, New ZealandAbstractCurrent database definition techniques tend to be either purely language-based or purely graphical. There is little or no integration between the two. This places artificial limits on the environment that developers must work in; ideally, they should be able to switch paradigms as the need arises. This lack of integration also causes problems with database reengineering. This paper describes an architecture for a relational abstraction layer, which isolates the front-end “dialect” used from the underlying relational implementa-tion. This allows tighter integration between different database definition techniques.1. IntroductionThere are numerous software tools available for use with database design and definition. The two most common generic products are graphical CASE tools and SQL. Both are equally effective at what they do, but usually work in isolation from each other. A perfect example of this is a CASE tool that generates SQL code from an entity-relationship diagram (ERD) and associated data dictionary. Generally, the code is generated after the diagram is completed, and it is usually not a simple task to reengineer the generated code back into a diagram. This problem is further exacerbated if the ERD has been altered in the meantime.Many CASE tools have reasonable reverse engineering capabilities (for example, Sybase’s Deft), but more often than not, information is lost in the process of converting back to an ERD.Graphical tools were developed as a more intuitive method of defining databases than a purely language-based approach. During the last decade, much research has been done on visual environments for database design, definition and manipulation; for example, the SUPER environment [1, 2] and the GOOD environment [3]. It is argued here, however, that such purely graphical approaches suffer from the same problem as the purely language-based approach. That is, by enforcing a “one size fits all” approach, we artificially limit our capabilities.What is needed is a more general method of database definition, which is independent of the paradigm used.Ideally, a developer would be able to choose the paradigm that best suits the situation; for example, they might prefer to use SQL. A different developer working on the same project might prefer to use ERDs. In such a case, they would want to simply “flip a switch” within the development environ-ment and change from one representation (SQL) to the other (ER diagram), without losing any information. Such a mechanism would require some form of intermediate representation which is independent of the way it is to be viewed. In other words, the environment that the end-user sees is really just a front end to the real environment.What we propose is an architecture for implementing a language abstraction layer for relational DBMS. This architecture will consist of the following: a collection of front end “dialects”, including such things as SQL and ERDs; the abstraction layer itself; and a collection of plug-in modules for communicating with different DBMSs.2. Basis for the architectureThe architecture is based on a combination of two separate developments. One is the Open Scripting Architecture (OSA), developed by Apple Computer as part of the OpenDoc initiative [4, 5]. The other is a hypothetical language called D, developed by Chris Date and Hugh Darwen as part of their Third Manifesto [6].The Open Scripting ArchitectureThe OSA is an open architecture developed by Apple Computer which allows end-users to script applications which adhere to the architecture [7]. In that respect it is very similar to the shell scripting languages used under Unix. The OSA is currently only available on the Macintosh platform, but it is being ported to Windows and Unix as a fundamental part of the OpenDoc working environment.An OSA-compliant scripting language is characterised by the following: a central abstraction layer, or scripting component; an optional collection of language dialects such as English, French or C-like; and an optional collection of plug-in modules (scripting additions) for defining additional language capabilities. Extra functionality may also be added to the language by installing OSA-aware applications.3. The architectureWhat is proposed here is an abstraction layer similar to that used in the OSA, based around a language equivalent in capability to the D language. Let us call this language L ,although “language” is possibly not the correct term — as already stated, the language itself may have no direct textual representation. Rather, what end-users see as the “language”would actually be implemented as a dialect on top of the abstraction layer.The direct result of this abstraction layer is that database designers will be able to choose their favourite dialect for database definition, or indeed, switch between dialects on the fly. This allows the developer to choose the environment that best suits the way they work and think, without disad-vantaging those who work in different ways.The intention is that this architecture will be implemented directly on top of the existing OSA as a completely distinct language environment. More precisely, L will be implemented as an OSA scripting component, albeit a slightly unorthodox one, as it will not be used as a true “scripting language” in the OSA sense. Front ends such as ER diagramming and SQL will be implemented as dialects of this component. Specific DBMS functionality will be incorporated via plug-in modules which describe the capabilities and “vocabulary” of the target DBMS. The back end will consist of some sort of communications link to the target DBMS.The initial implementation will target a subset of data definition and manipulation functions for at least three dialects: E-R diagrams, SQL and a D -like dialect. The target DBMS will be Oracle 7.1 running on a DEC 3000 Model 400 under OSF/1. The only complete OSA implementation at the time of writing is on the Macintosh, so this will be the target platform for the front end. The abstraction layer will communicate directly with Oracle using the Oracle Call Interface (OCI) over a client-server link. It is unclear at present as to whether the L scripting component will be able to open a direct client-server link to Oracle; it may be neces-sary to develop a special-purpose application which receives Apple events from the L scripting component and converts them into appropriate OCI calls.Figure 2 shows the structure of the architecture; compare this with the OSA structure shown in Figure 1.4. ConclusionCurrent methods of database definition tend to favour either a purely language-based approach, or a purely graphi-cal approach — there is a lack of integration between the two. What is needed is a paradigm-independent method of defining a database. In other words, an abstraction layer between the selected front end and the target DBMS isnecessary.yerL);Apple, AppleScript, Macintosh, MacOS and OpenDoc are registered trademarks of Apple Computer, Inc.DEC is a trademark of Digital Equipment Corporation. Oracle is a trademark of Oracle Corporation.OSF/1 is a registered trademark of Open Software Foundation, Inc.Unix is a registered trademark of Unix System Laboratories, Inc., a wholly owned subsidiary of Novell, Inc. References[1] A. Auddino, E. Amiel, Y. Dennebouy, Y. Dupont, E.Fontana, S. Spaccapietra, and Z. Tari, “Database Visual Environments Based on Advanced Data Models,” 1992.<ftp://lbdsun.epfl.ch/pub/avi92.ps.Z>[2] A. Auddino, Y. Dennebouy, Y. Dupont, E. Fontana, S.Spaccapietra, and Z. Tari, “SUPER — Visual Interaction with an Object-based ER Model,” 1992.<ftp://lbdsun.epfl.ch/pub/er92.ps.Z>[3]M. Gyssens, J. Paredaens, J. Van den Bussche, and D. VanGucht, “A Graph-Oriented Object Database Model,”University of Antwerp (UIA), Technical Report 92-35, 1992.[4]Apple Computer, “OpenDoc™ for Macintosh: An Overviewfor Developers,” Apple Computer, Inc., Cupertino, California, White Paper December 1994.[5]K. Piersol, “A Close-Up of OpenDoc,” BYTE, vol. 19, pp.183–188, 1994.[6] C. J. Date, “The Third Manifesto,” in Relational DatabaseWritings 1991–1994, C. J. Date, Ed. Reading, Massachusetts: Addison-Wesley, 1995, pp. 309–336.[7]W. R. Cook and W. H. Harris, “The Open ScriptingArchitecture,” Apple Computer, Inc. 1994.<:80/sdm7g/Projects/Python /OSA/OSA.ps.gz>[8] E. M. Berdahl, “Better Apple Event Coding ThroughObjects,” develop, The Apple Technical Journal, vol. 12, pp.58–83, 1992.[9]R. Clark, “Apple Event Objects and You,” develop, the AppleTechnical Journal, vol. 10, pp. 8–32, 1992.[10]H. Darwen and C. J. Date, “Introducing the Third Manifesto,”Database Programming & Design, pp. 25–35, 1995.。
医疗机构药品遴选指南
医疗机构药品遴选指南作者：李正翔张玉张伶俐段蓉来源：《中国药房》2022年第07期中图分类号 R95 文献标志码 A 文章编号 1001-0408（2022）07-0769-08 DOI 10.6039/j.issn.1001-0408.2022.07.01摘要为促进医疗机构药品遴选工作规范开展，提升医疗机构药事管理水平，促进患者在疾病的药物治疗中安全、有效、经济、适宜地使用药品，制定《医疗机构药品遴选指南》。
该指南的构建严格遵循了美国国家科学院医学研究所（IOM）关于指南的最新定义，并以世界卫生组织（WHO）标准指南制定的方法学为基本依据。
在指南构建的过程中，基于德尔菲法构建《医疗机构药品遴选指南》研究问题，并设计了以10个一级指标、30个二级指标为核心的药品遴选评价体系，评估指标按其属性及主要证据来源可划分为研究型指标和政策型指标。
其中研究型指标采用GRADE方法评价问题证据体系的质量，政策型指标按照《立法法》进行证据分级。
在此基础上，应用循证医学方法建立各项指标的评价方法和内容，并通过专家共识法形成推荐意见，最终形成医疗机构药品遴选的标准指南。
关键词药品遴选;医疗机构;遴选指标;评价体系;指南ABSTRACT In order to promote the standardization of drug selection in medical institutions，enhance the level of pharmaceutical affairs management of medical institutions and promote the safe， effective， economical and appropriate use of drugs in the treatment of diseases， the Drug Selection Guideline for Medical Institutions （hereinafter refer to as the Guideline） is formulated. The development of the Guideline for medical institutions is following the latest definition of Institution of Medicine （IOM）， National Academy of Sciences and based on the methodology of WHO handbook for guideline development. During the construction of the Guideline， the research points of the Guideline are constructed on the basis of Delphi method; a drug selection and evaluation system with 10 primary indicators and 30 secondary indicators as the core is also designed. The evaluation indexes can be divided into research indexes and policy indexes according to their attributes and main sources of evidence. The GRADE method is used to evaluate the quality of the evidence system for research indexes， while the policy indexes are graded according to the Legislation Law of the People’s Republic of China. On this basis， the evaluation methods of those indexes are constructed by using evidence-based medicine method， the recommendation is formed through expert consensus method， and finally a standard guideline for drug selection in medical institutions is formed.KEYWORDS drug selection; medical institutions; selection index; evaluation system; guideline近年來，随着医药卫生事业的持续发展，大量药品不断迭代上市，在为临床诊疗工作提供了更多选择的同时，也对医疗机构药事管理工作提出了更高的要求和巨大的挑战。
英文数据库与英文文献检索通用课件
These databases combine elements of structured and unstructured databases They provide some structure for organizing information, but not as strictly as fully structured databases
English Database and English Literature Retrieval
2023
REPORTING
Overview of English databasesIntroduction to commonly used English databasesEnglish Literature Retrieval SkillsReading and organizing English literaturePractice of English Database and Literature RetrievalAdvanced English Database and Literature Retrieval
PART
03
English Literature Retrieval Skills
2023
REPORTING
Choosing the appropriate keywords
The selection of keywords is crucial for the search results. Choosing keywords that are relevant to the topic and representative can improve the accuracy and efficiency of retrieval.
基于FAERS数据库的儿童实体器官移植受者应用他克莫司相关药物不良事件的研究
· 论著·基于FAERS 数据库的儿童实体器官移植受者应用他克莫司相关药物不良事件的研究董博清 王婧雯 毕焕京 陈祖涵 路翠楠 薛武军 李杨 丁小明【摘要】 目的 探讨他克莫司（Tac ）在儿童实体器官移植受者中的不良药物事件（ADE ）特征。
方法 研究数据来源于美国食品与药品监督管理局不良事件报告系统数据库，时间覆盖2004年第1季度至2023年第2季度，提取了以Tac 为首要怀疑药物的儿童器官移植受者的ADE 数据，运用比例失衡法对Tac 与ADE 之间的关联进行定量分析。
分析Tac 相关ADE 的基本特征及信号强度。
探究不同年龄儿童及不同移植器官类型的Tac 相关ADE 。
结果 共筛选出1 443份涉及Tac 的儿童ADE 报告，其中心脏移植188例（13.0%）、肝移植668例（46.3%）、肾移植531例（36.8%）、肺移植56例（3.9%），儿童的中位年龄为10岁，ADE 上报国家的前3位分别是美国、法国及英国，中国上报为26例，占比为1.8%。
感染及侵染类疾病在Tac 相关ADE 报告中占比最高（20.96%），包括EB 病毒及巨细胞病毒感染等。
不同年龄段儿童的Tac 相关ADE 中感染及侵染类疾病均占据最大比例，但病原体种类存在差异。
排斥反应、免疫抑制水平不稳定以及肾功能损伤也是各年龄段儿童常见的Tac 相关ADE 。
心脏移植受者中以神经系统疾病的ADE 为主，而肝移植和肾移植受者中感染及侵染类疾病更为常见，肺移植受者中的ADE 以排斥反应最为常见。
结论 Tac 相关ADE 在不同器官移植类型中呈现出不同的分布特点，需重视在儿童器官移植中进行个性化药物监测和风险评估，以优化Tac 治疗并降低ADE 风险。
【关键词】 实体器官移植；儿童；他克莫司；不良药物事件；感染；排斥反应；食物过敏；神经系统疾病【中图分类号】 R617, R392.4 【文献标志码】 A 【文章编号】 1674-7445（2024）04-0010-10Study of adverse drug events related to tacrolimus in pediatric solid organ transplant recipients based on FAERS database Dong Boqing, Wang Jingwen, Bi Huanjing, Chen Zuhan, Lu Cuinan, Xue Wujun, Li Yang, Ding Xiaoming. Department of Kidney Transplantation , the First Affiliated Hospital of Xi'an Jiaotong University , Institute of Organ Transplantation of Xi'an Jiaotong University , Xi'an 710061, ChinaCorresponding author: Ding Xiaoming, Email: ***************.cn【Abstract 】 Objective To investigate the characteristics of adverse drug event (ADE) related to tacrolimus (Tac) in pediatric solid organ transplant recipients. Methods The data were retrieved from the US Food and Drug Administration Adverse Event Reporting System database from the first quarter of 2004 to the second quarter of 2023. The ADE data of pediatric organ transplant recipients with Tac as the primary suspected drug were extracted. The relationship between Tac and ADE was quantitatively analyzed by proportional imbalance method. Basic characteristics and signal strength of ADE related to Tac were analyzed. ADE related to Tac in children of different ages and different types of organ transplantation were analyzed. Results A total of 1 443 children's ADE reports involving Tac were screened, including 188 cases (13.0%)of heart transplantation, 668 cases (46.3%) of liver transplantation, 531 cases (36.8%) of kidney transplantation and 56cases (3.9%) of lung transplantation. The median age of children was 10 years old. The top three countries with ADE reporting were the United States, France and the United Kingdom. China reported 26 cases, accounting for 1.8%. InfectionDOI: 10.3969/j.issn.1674-7445.2024031基金项目：国家自然科学基金（82370802）；创新药物上市后临床研究科研专项（WKZX2023CX190002）；西安交通大学医学“基础-临床”融合创新项目（YXJLRH2022049）作者单位： 710061 西安，西安交通大学第一附属医院肾移植科 西安交通大学器官移植研究所作者简介：董博清（ORCID 0000-0001-9748-9321），博士研究生，住院医师，研究方向为肾移植，Email ：******************通信作者：丁小明（ORCID 0000-0002-9082-9191），博士，主任医师，研究方向为肾移植，Email: ***************.cn第 15 卷 第 4 期器官移植Vol. 15 No.4 2024 年 7 月Organ Transplantation Jul. 2024 and infectious diseases accounted for the highest proportion (20.96%) in ADE related to Tac, including EB virus and cytomegalovirus infection, etc. Infection and infectious diseases occupied the largest proportion of ADE related to Tac in children of different ages, whereas the pathogen types were different. Rejection, unstable immunosuppression level and renal function damage were also common ADE related to Tac in children of all ages. Nervous system disease was the main ADE in heart transplant recipients, while infection and infectious diseases were more common in liver and kidney transplant recipients. Rejection was the most common ADE in lung transplant recipients.Conclusions ADE related to Tac possess different distribution characteristics in different types of organ transplantation. Extensive attention should be paid to individualized drug monitoring and risk assessment in pediatric organ transplant recipients, thereby optimizing Tac treatment and reducing the risk of ADE.【Key words】Solid organ transplantation; Children; Tacrolimus; Adverse drug event; Infection; Rejection; Food allergy; Nervous system disease实体器官移植是儿童终末期疾病的有效治疗方法，包括心脏、肝脏、肾脏及肺移植等[1-3]。
IntelliTrax软件用户手册：自动归档概述说明书
IntellItrax: auto archIve OverviewThe DBat Auto Archive functionality allows theuser to keep their database size manageable byarchiving and optimizing older jobs. It featuresthe following benefits:• Makes regular and safe backups of customerdata, which are then available for reporting.• Keeps application performance optimal bykeeping table size consistent.• Allows customers to continue using the freeMicrosoft SQL Server engine without reachingits 2 GB database size limitation, and withouthaving to upgrade to its more expensive edition.Setting up Scheduled AutO ArchiveScheduled auto archive uses SQL Server’s SQLAgentfunctionality to run a script on a regular basis tooptimize the database.auto archive functionality as soon asthe software is installed, and before anysize or performance issues may occur.Procedure1. Start DBat. Connect to a database and clickArchive. 2. Click the Auto archive old non-OK sheets and optimize databaseradio button. 3. Set the auto archive options to match the customer’s environment. • Recommendation: keep the default values for “archive sheets older than X months” and “archive every Y months”. • For the “archive start date and time,” choose a time when most downtime is available. Although the schedule auto archive can be done at the same time that users are running applications, users may experience slowdowns in this case. 4. Click Save to create the scheduled job and close the screen. Advise customers to close all running applications during the Auto Archive scheduled time. To verify the process has finished, check the “Last Archive”field on the “Auto Archive” screen.changes month to month based oncustomer work load, modify the scheduleon a monthly basis to prevent anyconflicts with running applications.IntellItrax: auto archIveMAnuAl ArchiveThe archive script can also be triggered manually, and run along with the normal scheduled archive on an as-needed basis. It can also be used instead of the scheduled process, but this is not recommended. Although the scheduled and manual archive processes are essentially the same, they do optimize sheets in different ways. The scheduled script is meant for coexistence with running applications, and therefore uses more frequent smaller transactions to commit its changes. The manual script uses one large transaction, which is more efficient, but prevents any other applications from using or changing data. This forces it to also check that it is the only ATSII database user at the beginning of the process. Procedure1. From the Auto Archive screen, click the ArchiveSheets and Optimize button.2. Choose the optimize sheets month interval. Thedefault setting is recommended.3. Make sure all users are disconnected from thedatabase, and click Yes. If any users are stillconnected, an error such as this may appear:The easiest way to disconnect other users is to restart the SQL Server service and try this operation again.4. Click OK on the prompt to acknowledge that nousers should be connected to the database whilethe archive process is running.5. The following screen is shown while the archiveprocess is running.Be advised that the archive process may take a very long time (up to several hours), depending on the size of the database. Customers should not terminate the DBat application or use other applications during this time.If the application is terminated prematurely, a long period may occur where the database cannot be used. This would happen because SQL Server would try to rollback the transaction and restore the database to the original state.6. When this prompt appears, the archive processhas finished successfully.MAnuAl Archive trOubleShOOtingIf an error occurs during the archive process, e.g. if the server runs out of disk space, SQL Server might not rollback the transaction right away because it might think the operation is still pending. The best way to force the transaction to be rolled back is to restart the SQL Server service. After this point, it may take a long time for SQL Server to restore the databaseIntellItrax: auto archIve back to a usable state. To verify the rollback processis happening, monitor the varying CPU and memoryusage of the server in Task Manager.To ensure no other users interfere with the archiveprocess, DBat locks the database exclusively to itself.If the application is terminated before the processfinishes, the database might not be usable for otherapplications even after the rollback process describedabove happens. This is because the first user toconnect to the database will lock everyone else out.In Enterprise Manager, this database state will appearlike this:To unlock the database and stop errors, restart theSQL Server service to make sure that no one else isconnected and connect to the database with DBat.Restarting SQL Server Service1. From Control Panel / Administrative tools,launch the “Services” applet.2. Find the MSSQL$ATSII service and click theRestart link.3. Select Yes to “Restart Other Services”, whichmentions the SQLAgent$ATSII servicedependency.After successfully connecting to the database, theexclusive state is cleared and other applications should be able to connect. repOrting On Archived dAtA All backups, including backups created automatically by Auto Archive, are available in the ReportingTool for reporting as part of Change Source functionality. This is the recommended way for customers to access their archived data, and is safer than the process outlined in the upcoming “Restoring Archived Data” section. Changing the data source restores the backup file into a separate database, named in a unique way based on the connected user’s computer. This allows multiple users to work with a different set of archived data from the same database server. Procedure 1. Launch ReportingTool and click the Change Source button on the main screen. 2. The “Database Selection” screen lists each database backup available to be restored. Customers can optionally use the date and time in the automatic backup filename to help them determine which backup to restore. In this example, the ATSII database is the primary database that all users are connected to. The first file below it represents a full backup made of thedatabase on 6/20/2006 at 9:38 AM. the date when a particular job was run, they can reference the scan info dialog for the remaining OK sheet in the job, which never gets archived.Other production and make ready sheets should be present in the backup at around the same creation date. 3. Select a database and click OK . The backupwill be restored, which may take a long time.IntellItrax: auto archIve If any database patches have become availablesince the backup was made, they are appliedto the database after it is restored. This ensuresthat ReportingTool is working with the latestdatabase structure.4. When the main screen appears, the databaseselected for the reporting is now the restoreddatabase. Job and Sheet reports can be run asnormal.reStOring ArchiveddAtAThe backups created by the Archive process go intothe default SQL Server backup directory and becomeavailable in DBat for restoration.If a customer wants to restore an older job toview it in PressTool (e.g. to view its make ready orproduction sheets), they should make a full backupof the current database and follow the normal DBatrestore process.Customers should not write any new data to thisrestored database. New data should only be writtento the latest database.When done using the archived data in PressTool, thecustomer should restore the backup made earlier.。
国外管道失效数据库简介及参考
国外管道失效数据库简介及参考作者：齐先志杨静王晓霖谢成曹加园席罡来源：《当代化工》2016年第04期摘要：管道失效数据库在管道完整性管理实施和安全监管方面起着重要作用，介绍了国外PHMSA、EGIG、Concawe、NEB等管理机构成熟运行的管道失效数据库，从数据库的统计范围、事故上报、事故统计等方面分析了不同国家管道失效数据库的差异和对我国数据库建设的参考。
关键词：油气管道；管道失效数据库；管道完整性管理；管道失效；管道泄漏中图分类号：TQ 000E 832 文献标识码： A 文章编号： 1671-0460（20142016）0004-00000853-0003Abstract： Pipeline incident database（PID） played a crucial role in the pipeline integrity management and safety supervision. The PIDs abroad founded by PHMSA，EGIG，Concawe and NEB were briefly introduced. Among these databases the differences in the scope of pipeline types in the database， incident reporting， the pipeline incident statistics were compared and analyzed，providing some guidelines and references for us.Key words： Oil and gas pipeline ； Pipeline incident database； Pipeline integrity management； pipeline Pipeline failure； pipeline Pipeline release油气管道属于重大危险源，油气一旦泄漏可能引发环境污染、火灾、爆炸等严重事故。
SQL Server 2019 数据库系统用户手册说明书
5 Make faster, better decisions
Use data virtualization to combine and query a variety of external relational and non-relational data sources without moving or replicating data.
Mission critical security 4
Access rich, interactive reports and enterprise reporting for better analysis and decision-making.
Create, deploy, and manage mobile and paginated reports with rich visualizations in SQL Server Reporting Services. Author beautiful reports with Power BI Desktop. Publish Power BI reports to the cloud or Power BI Report Server in SQL Server 2019, and distribute and consume reports across devices. Consume interactive dashboards and reports, both online and offline, with mobile reporting on iOS, Android, and Windows devices.
英语学术论文中Abstract写作总结！
英语学术论文中Abstract写作总结！作者简介：晨星，男，湖北武汉人，副高职称，博士，高级程序员，IAMG（国际数学地质协会）会员。
目前研究方向为地理信息数据挖掘与知识发现、地学信息三维可视化。
当年我在攒第一篇 SCI 论文的时候，是先写的 Abstract，然后再写的正文。
在我将自以为很用心撰写的论文交给副导师审阅后，就被他立即请到办公室去畅谈了一番心声：「不是 Abstract 的位置放在正文前面，就将Abstract 放在论文前面写的！你没看到你的Abstract 有问题吗？和全文对得起来吗？」那么，好的 Abstract 应该是怎么样呢？在 SCI 论文写作中，Abstract 是很重要的一部分。
所谓 Abstract，就是对所写论文主要内容的精炼概括。
Abstract 是美国人的说法，英国的科技期刊喜欢称之为Summary。
在英文中，有资料是这么对其定义的：Abstract is a sketchy summary of the main points of an argument or theory in a paper.一篇英文科技论文特别是SCI 论文，是否能被编辑发出审稿乃至最后被录用，在很大程度上取决于论文的 Abstract 质量。
事实上，摘要由于其独特的功能，通常被认为是科技论文最重要的组成部分之一（有的文献认为是最重要的，没有之一）。
据我了解，英文科技论文的 Abstract 主要功能有以下三点：1. 提纲携领，方便检索Abstract 作为对英文科技论文的最主要内容进行不加注释和评论的简短陈述那一部分。
与整篇论文的其他部分相比，它起着至关重要的概括要点的作用。
从本质上讲，Abstract 是把论文的内容浓缩成一篇简短、简洁、概括性强的一个段落的文本。
Abstract 被看成是论文的缩略版或缩写，概括了主体的内容，例如背景、主题/问题、方法、结论和意义。
精心撰写的Abstract是检索科技文献的有用工具（反之，如果 Abstract 写得不佳，对检索该篇论文是个误导），它能使读者能够更快、更方便地识别论文的基本内容，确定论文与其个人兴趣相关性，并最终决定是否需要继续阅读整篇论文。
Project2007培训 Module 2-Reporting
Configuration - Creating Data Analysis Views
▪ ▪ ▪ ▪
Created on Manage Views page View Type is Data Analysis Add a Name and Description for the View. Specify Analysis Server information, and database information ▪ Choose proper cubes to generate the report ▪ Security categories
can customize ▪ To see a list of Reports
▪ From the Report menu, choose Reports.
Editing Reports
▪ If you choose to work with one of the standard report
▪ Report menu on the Standard Toolbar
Project 2007 Visual Reports
▪ Overview ▪ Creating a New Template using Excel ▪ Creating a Report Template using Visio
Creating Custom Reports
Report Templates
▪ When you create a custom report, you use one of four report
templates rather than a predefined report.
信息系统建设英文课件 (8)
Database Management Systems
Database Management Systems
• Select:
• One field in each table • Cannot be duplicated • Provides unique identifier for all information in any row
The Database Approach to Data Management
A relational database organizes data in the form of two-dimensional tables. Illustrated here is a table for the entity SUPPLIER showing how it represents the entity and its attributes. Supplier_Number is the key field.
• Fields (columns) store data representing an attribute. • Rows store data for separate records, or tuples. • Key field: uniquely identifies each record. • Primary key:
R.R. Donnelley Tries to Master Its Data
• Master data management (MDM) enables companies like R.R. Donnelley to eliminate outdated, incomplete or incorrectly formatted data.
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Aproduct-lineapproachtodatabasereportingFelipeI.Anfurrutia,OscarDíaz,SalvadorTrujilloONEKINGroup.UniversityoftheBasqueCountryPOBox:64920009SanSebastiánPhone:+34943018064{felipe.anfurrutia,oscar.diaz,struji}@ehu.es
AbstractReportingforanalysisisacommondemandtodatabaseprogrammers.Unlikedynamicdataanal-ysis,reportingtendtobeforeseeable.Despitethisfact,staffwastetheirtimeprogrammingsimilarre-portstimeandagain,wherereportsareoftenbuiltfromscratchwithlittleifanyreuseatall.Basedonthepredictabilityandsimilarityamongreports,thisworkpresentsaproduct-lineapproachtodatabasereporting.Thefeaturemodel,coreassetsandpro-ductionplanoftheproductlinearesketched,andthearchitecturediscussed.Theworkwasconductedunderamainrequirement:datawarehousetechnol-ogywasnotavailable.Eitherthecostorthelackofappropriatestaffmakessmall-and-mediumcompa-niesreluctanttousethesesophisticatedtoolswhilesimplereportingisalltheyneed.Inthisscenario,theproduct-lineapproachcanbeacost-effectiveso-lutiontoachievereuse.
1IntroductionManysmallorganizationsoftenaccessdataforre-portingdirectlyfromon-linetransactionprocess-ing(OLTP)systems.Thisapproachcansufficeifsophisticateddataanalysisisnotrequired,orre-sourcesarenotavailable.Datawarehousetech-nologyofferseffectivesupportforanalysisbuttheyalsoimplyqualifiedstaffandequipmentthatsmallorganizationscannotalwaysafford.AccessingtheOLTPsystemdirectlyforreport-ingincursintwomainlimitations(apartfromhan-dlingofhistoricaldataandETLissues).First,thesystemperformancefortransactionsisadverselyaf-fectedasnowtheverysamedataisusedtofeedbothOLTPandreportingapplications.Anadditionalcomplexityassociatedwithreport-ingdirectlyfromthesourcesystemisthattheorga-nizationofthedataisrarelyintuitivetoabusinessuser.Thedatahasbeenstoredtooptimizedataen-try,nottooptimizedataaccess.Thisoftenleadstodevotespecializedpersonneltoproducingreportsforothersintheorganization.Theseteammem-bersareincreasinglyreliedupontoprovidenewandmodifiedreports,preventingthemfromcompletingtheirassigneddutiesorforcingadepartmenttoded-icatestafftoproducingreports[12].Unlikedynamicdataanalysis,reportingtendtobeforeseeable.Basedonthepredictabilityandsim-ilarityamongreports,thisworkpresentsaproduct-lineapproachtodatabasereporting.SoftwareProd-uctLines(SPLs)aredefinedas“asetofsoftware-intensivesystems,sharingacommon,managedsetoffeaturesthatsatisfythespecificneedsofapar-ticularmarketsegmentormissionandthatarede-velopedfromacommonsetofcoreassetsinapre-scribedway”[6].Areportfamilyisthenasetofreportsthatsharesomecommonalities.Theproduct-linedesignershouldstrivetoapprehendthiscommonalityaswellasidentifyingtheirdifferences.Agivenreportisthenaproductofthislinewhereareportischarac-terizedbythedataused,itslayoutanditsformat.Therequirementofthesystemfollows:
1.nodatawarehousetechnologyisavailable.Ei-therthecostorthelackofappropriatestaffmakessmall-and-mediumcompaniesreluctanttousethesesophisticatedtoolswhilesimplereportingisalltheyneed.2.detachingasmuchaspossiblereportingfromthedatabaseitself.Tothisend,cubesareex-tractedandsavedasXMLfiles.Then,cubesareconceivedasakindofdatacache[1].AelapsedTimefeatureisadded.Thisfeaturecapturethemaximumelapsedtime.Basedonourexperience,thiselapsedtimetendtobelargerenoughtoallowtore-calculatethecubeinbatchmode(i.e.normallythisimpliestorunthequeryatnight).Notethatinsmallorgani-zationsthevolumeofdataissmallenoughtomakethisviable.
3.promotingself-servicereportingforendusers.Implementationwise,thesystemmakesintensiveuseofXMLtechnologies.All,thedatacube(XCube[13]),thefeaturemodel(XML-based[3]),theformatter(XSL[17])andthebuildprocess(Ant[9,16])arealldescribedusingXMLvocabularies.Thismakesthesystemplatform-independent,andprovidesagoodexampleoftheincreasinguseful-nessofXML.Therestofthepaperisstructuredasfollows.Section2presentsasamplecase.Section3outlinesproductlines.Section4and5introducethefeaturemodelandthecoreassetsofthereportingproductline,respectively.Finally,section6discussesandsection7concludesthepaper.
2ThesamplecaseThisworkhasbeenconductedfortheTRACELIAsystemwhichaddressesthemanagementofthein-formationflowsinmanufacturingplants.Aspectsoftheproductionprocesstobecontrolledincludeproduction-processmonitoring,machine-levelin-ventorycontrolormaintenancecontrol.Anexam-pleofananalyticalqueryinthisscenariois:"givemethetotalelapsedtimeperstateformachinesofallsectionsbystatecategoryduringmarch2005"where“state”referstowhetherthemachinewasidle,outoforderandthelike.Figure1showsasamplereport,wherestatesarelabeledas“lackofair”(“Faltadeaire”),“lackofwater”(“Faltadeagua”),etc.Theanalysisrequiresfirsttoidentifythesubjectoftheanalysis:thefact.Inourcase,thiscor-respondstomachine-transitionevents,i.e.entries