Trials and tribulations: how we established a major incident database
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Abstract:
We describe the process of setting up a database of major incident reports and its potential future application.A template for reporting on major incidents was developed using a consensus-based process involving a team of experts in the field. A website was set up as a platform from which to launch the template and as a database of submitted reports. This paper describes the processes involved in setting up a major incident reporting database. It describes how specific difficulties have been overcome and anticipates challenges for the future.We have successfully set up a major incident database, the main purpose of which is to have a repository of standardised major incident reports that can be analysed and compared in order to learn from them.Keywords:
Incident report
Nowadays we usually act based on information in order to act effectively, we should enlarge our access to information of course, we have several methods to choose from, but commercial databases are the most advantageous. One reason is that everyone has equal access to commercial databases. As a result, people or companies who use commercial database information skillfully have a distince advantage over those who don't commercial database services in japan have been changing rapidly since their birth more than twenty years ago. For example, the distribution mode of databases is changing : from the original batch(off line) to on-line and most recently to the coexistence of batch and on line with the advent of CD-ROM. It is important for us to keep up with the new trends in databases, and to utilize them effectively as a tool in the information age.
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Eight large chemical databases have been analyzed and compared to each other. Central to this comparison is the open National Cancer Institute (NCI) database, consisting of approximately 250 000 structures. The other databases analyzed are the Available Chemicals Directory ("ACD," from MDL, release 1.99, 3D-version); the ChemACX ("ACX," from CamSoft, Version 4.5); the Maybridge Catalog and the Asinex database (both as distributed by CamSoft as part of ChemInfo 4.5); the Sigma-Aldrich Catalog (CD-ROM, 1999 Version); the World Drug Index ("WDI," Derwent, version 1999.03); and the organic part of the Cambridge Crystallographic Database ("CSD," from Cambridge Crystallographic Data Center, 1999 Version 5.18). The database properties analyzed are internal duplication rates; compounds unique to each database; cumulative occurrence of compounds in an increasing number of databases; overlap of identical compounds between two databases; similarity overlap; diversity; and others. The crystallographic database CSD and the WDI show somewhat less overlap with the other databases than those with each other. In particular the collections of commercial compounds and compilations of vendor catalogs have a substantial degree of overlap among each other. Still, no database is completely a subset of any other, and each appears to have its own niche and thus "raison d'être". The NCI database has by far the highest number of compounds that are unique to it. Approximately 200 000 of the NCI structures were not found in any of the other analyzed databases.
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The author puts forward that the customer total of erupting is an important parameter of evaluating and using database.And the thesis induces and analyses the researches about the evaluation of the present several kinds of database,pointing out that database evaluation system tacks the index,that is the customer total of erupting,customer inaction deadline,it will lose sound and authoritative.It establishes a database evaluation system which is more complete and maneuverable.
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Context: There has been an exponential growth in the size of the databases in the recent times and the same amount of growth is expected in the future. There has been a firm drop in the storage cost followed by a rapid increase in t he storage capacity. The entry of Cloud in the recent times has changed the equations. The Performance of the Database plays a vital role in the competition. In this research, an attempt has been made to evaluate and compare the performance of the traditional database and the Cloud Database. Objectives: This thesis investigates about the prior works on the issues that affect the performance of Cloud Database. And compares the performance of a Database in Traditional to that Cloud Environments Methods: Two different research methods are used to carry the research. They are Systematic Literature Review (SLR) and Quantitative Methodology. Articles from Scientific Databases are chosen for SLR process. Results: From the SLR process, 4 issues were identified. From the Experimentation results, Cloud Database is having poor performance compared to the Traditional Database. Conclusions: Issues that affect the performance of Cloud Database are identified and a test bed is created to test the performance of a Database. Attempts are to be made to improve the performance of Cloud Database.
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In this paper, we introduce some new collections of sets such as α– σ–field and β– σ–field as two generalizations of the notion of σ–field and we discuss the properties of these collections. Furthermore, we study the relationships between α– σ–field and σ–field. As a first result, we prove that every σ–field is α– σ–field and β– σ–field. Finally, we establish new collection of sets such as δ–field and obtain some results deals with this concept and we conclude that each of α– σ–field and β– σ–field are generalizations of δ–field.
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