Analysis performance of database programming for computation in statistical application

Control chart is a graphical tool for monitoring and process control. This chart is widely use in Statistical Process Control (SPC) and it is used to ensure the quality of certain product and services. With the increasing amount of data in a production floor, the computation process of generating th...

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Main Author:	Abdul Rahid @ Abdul Rashid, Nurul Najwa
Format:	Thesis
Language:	English English
Published:	2015
Subjects:	Q Science (General) QA Mathematics QA76 Computer software
Online Access:	http://eprints.utem.edu.my/id/eprint/15894/1/ANALYSIS%20PERFORMANCE%20OF%20DATABASE%20PROGRAMMING%20FOR%20COMPUTATION%20IN%20STATISTICAL%20APPLICATION%20%2824%20pgs%29.pdf http://eprints.utem.edu.my/id/eprint/15894/2/Analysis%20performance%20of%20database%20programming%20for%20computation%20in%20statistical%20application.pdf
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id	my-utem-ep.15894
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Abdullah, Noraswaliza
topic	Q Science (General) QA Mathematics QA76 Computer software
spellingShingle	Q Science (General) QA Mathematics QA76 Computer software Abdul Rahid @ Abdul Rashid, Nurul Najwa Analysis performance of database programming for computation in statistical application
description	Control chart is a graphical tool for monitoring and process control. This chart is widely use in Statistical Process Control (SPC) and it is used to ensure the quality of certain product and services. With the increasing amount of data in a production floor, the computation process of generating the control chart become slower. This research proposes to use database programming (stored procedures) to optimize the computation process to generate control chart application. This research is focusing on analysing the performance of database programming for computation in statistical application. The statistical method involved in this project is control charts. The research methodology for this project is experimental methodology. Two different methods of computation process to generate control charts are developed. One method is based on application programming language and the second method is based on the combination of application programming and database programming. Evaluation was based on average elapsed time taken to complete the process of computation in generating the control charts. The finding suggests that combining the application programming and the database programming can reduce the elapsed time for execution the computation process in statistical application.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Abdul Rahid @ Abdul Rashid, Nurul Najwa
author_facet	Abdul Rahid @ Abdul Rashid, Nurul Najwa
author_sort	Abdul Rahid @ Abdul Rashid, Nurul Najwa
title	Analysis performance of database programming for computation in statistical application
title_short	Analysis performance of database programming for computation in statistical application
title_full	Analysis performance of database programming for computation in statistical application
title_fullStr	Analysis performance of database programming for computation in statistical application
title_full_unstemmed	Analysis performance of database programming for computation in statistical application
title_sort	analysis performance of database programming for computation in statistical application
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Information and Communication Technology
publishDate	2015
url	http://eprints.utem.edu.my/id/eprint/15894/1/ANALYSIS%20PERFORMANCE%20OF%20DATABASE%20PROGRAMMING%20FOR%20COMPUTATION%20IN%20STATISTICAL%20APPLICATION%20%2824%20pgs%29.pdf http://eprints.utem.edu.my/id/eprint/15894/2/Analysis%20performance%20of%20database%20programming%20for%20computation%20in%20statistical%20application.pdf
_version_	1747833882800029696
spelling	my-utem-ep.158942022-04-20T10:44:50Z Analysis performance of database programming for computation in statistical application 2015 Abdul Rahid @ Abdul Rashid, Nurul Najwa Q Science (General) QA Mathematics QA76 Computer software Control chart is a graphical tool for monitoring and process control. This chart is widely use in Statistical Process Control (SPC) and it is used to ensure the quality of certain product and services. With the increasing amount of data in a production floor, the computation process of generating the control chart become slower. This research proposes to use database programming (stored procedures) to optimize the computation process to generate control chart application. This research is focusing on analysing the performance of database programming for computation in statistical application. The statistical method involved in this project is control charts. The research methodology for this project is experimental methodology. Two different methods of computation process to generate control charts are developed. One method is based on application programming language and the second method is based on the combination of application programming and database programming. Evaluation was based on average elapsed time taken to complete the process of computation in generating the control charts. The finding suggests that combining the application programming and the database programming can reduce the elapsed time for execution the computation process in statistical application. 2015 Thesis http://eprints.utem.edu.my/id/eprint/15894/ http://eprints.utem.edu.my/id/eprint/15894/1/ANALYSIS%20PERFORMANCE%20OF%20DATABASE%20PROGRAMMING%20FOR%20COMPUTATION%20IN%20STATISTICAL%20APPLICATION%20%2824%20pgs%29.pdf text en public http://eprints.utem.edu.my/id/eprint/15894/2/Analysis%20performance%20of%20database%20programming%20for%20computation%20in%20statistical%20application.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96237 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Information and Communication Technology Abdullah, Noraswaliza 1. Mitra, A., 2012. Fundamentals of Quality Control and Improvement, 3rd ed., John Wiley & Sons. 2. Sunderic, D. and Woodhead, T., 2001. 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IEEE 29th International Conference on Data Engineering (ICDE), pp. 841-852. 8. Zhou, Y. and Kang, K., 2012. A Federated Approach for Increasing the Timely Throughput of Real-Time Data Services. Real-Time and Embedded Technology and Applications Symposium (RTAS), 2012 IEEE 18th , vol., no., pp.163,172. 9. Seifedine, K. and Khaled, S., 2008. Massively Parallel Processing Distributed Database for Business Intelligence. Information Technology Journal, vol. 7 Issue 1, p70-76. 10. Chang, KC. and Wang, KH., 2013. Enhancing Performance of Traffic Safety Guardian System on Android by Skipping Mechanism. International Symposium on Consumer Electronics (ISCE). pp. 115-116. 11. Moore, D.and McCabe, D., 1993. Introduction to the practice of statistics. New York: Freeman. 12. Gay, L. R., 1992. Educational research, 4thed. New York: Merrill. 13. Douglas, A.L., William, G.M andSamuel, A.W., 2008. Statistical Technoques in Business and Economics, 3rded. New York: McGraw Hill 14. Hunt, C. A., 2011. Qualitative and Quantitative Concepts. (University of North Dakota) Retrieved from http://www.und.nodak.edu/instruct/wstevens/PROPOSALCLASS/ Huntpaper.htm 15. Wang, C.G., Lioa, X.P., Deng, J.X. and Huang, X., 2007. Research and Application of Stored Procedure in ERP System.Equipment Manufacturing Technology, pp. 48-51. 16. Li, T.S., Luo, L.Y., Meng, B. and Yan, Y., 2009. Improving the Execution Efficiency of Application Programs with Storage Procedures.Microcomputth Applications, vol. 9. Pp. 16-18. 17. Ozsoyoglu, G. and Meral, Z., 1985.Statistical Database Query Language.IEEE Transactions of Software Engineering, vol. 10, pp. 1071-1081. 18. Pattabla, N. and Nathan, P. , 2001 .Oracle9i: Program With PL/SQL. 19. Smith, C. U. and Williams, L. G., 2001. Performance solutions: A practical guide to creating responsive, scalable software. 20. Pereira, O.N.M.; de Sousa Pinter, J., 2007. Performance Assessment of an Enhanced Object- Oriented Approach for Wrapping Stored Procedures. EUROCON The International Conference on Computer as a Tool, p. 473-477. 21. Jun, S., 2013. An Efficient Connection between Statistical Software and Database Management System.International Journal of Computer Science and Business Informatic, vol. 8, p.1-12. 22. Gosh, S. P. and senior member, IEEE,1985. An Application of Statistical Databases in Manufacturing Testing.Transaction of Software Engineering, pp 591-598. 23. Ege, R.K.; Rishe, N.; Jingyu Liu; Lebedev, V., 1999. Using Java to add stored procedures to databases. Technology of Object-Oriented Languages and Systems, TOOLS 30 Proceedings , vol., no., pp.322,331. 24. Shi, D.S.,Zhang S. J. and Sun, S., 2004. Database trigger and stored procedure application technology in SQL Server self-defining Table. In Computer and modernization, PP.1 03-105. 25. Bennett ,K.,Ferris, M.E.and Ioannidis ,Y.E., 1991. A Genetic Algorithm for Database Query Optimization. In Proceedings of the fourth International Conference on Genetic Algorithms, pages 400- 407. 26. Codd,E. F., 1972. Relational completeness of database sublanguages, inDatabase Systems. Courant Computer Science Symposia Series, Vol.6. 27. Slivinskas G., Jensen C. S., Snodgrass R. T., 2001. Adaptable Query Optimization and Evaluation in Temporal Middleware. Proceeding ACM SIGMOD, 127-138. 28. Mourad, O. and Athman B., 2004. Query Processing and Optimization on the Web Distributed and Parallel Databases, 15, 187-218. 29. Cole, R.L. and Graefe,G., 1994. Optimization of dynamic query evaluation plans.Proceeding ACM SIGMOD International Conference on Management of Data, 23(2):150-160. 30. Chen,1., DeWitt, D., Tian,F.andWang ,Y., 2000.A scalable continuous query system for internet databases. Proceeding of the ACM SIGMOD Conference on Management of Data. 31. Jing,L. X., 2003. RDBMS Query Optimization.Journal of ZhengZhou Institute of Aeronautical Industry Management,vol21. 32. Kirchberg, M., 2007. An Integrated Database Programming and Querying Language with Support for Simultaneous Processing. International Conference on Software Engineering Advances (ICSE),vol., no., pp.56, 56. 33. Pengfei Li andCaiwu Lu, 2011. Data analysis system research and implementation based on stored procedure, Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on , vol., no., pp.689,691. 34. Lenz, H.-J.; Shoshani, A., 1997. Summarizability in OLAP and statistical data bases. Scientific and Statistical Database Management, Proceedings, Ninth International Conference on , vol., no., pp.132,143. 35. Chin, F.Y. and Ozsoyoglu, G., 1982. Auditing and Inference Control in Statistical Databases. Software Engineering, IEEE Transactions on , vol.SE-8, no.6, pp.574,582.

Analysis performance of database programming for computation in statistical application

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