The Use of Cloud Computing to Process Big Data: An Applied Study of the Virtual Library at the University of Mosul

Ibtisam Kareem AI –Dulaimi
International Journal of Computational and Electronic Aspects in Engineering
Volume 4: Issue 2, April-June 2023, pp 38-43


Author's Information
Ibtisam Kareem AI –Dulaimi1 
Corresponding Author
1College of Administration and Economics, University of, Mosul, Iraq
ibtisam_karem@uomosul.edu.iq

Article -- Peer Reviewed
First online on – 30 June 2023

Open Access article under Creative Commons License

Cite this article –Ibtisam Kareem AI –Dulaimi “The Use of Cloud Computing to Process Big Data: An Applied Study of the Virtual Library at the University of Mosul”, International Journal of Computational and Electronic Aspects in Engineering, RAME Publishers, vol. 4, Issue 2, pp. 38-43, 2023.
https://doi.org/10.26706/ijceae.4.2.20239815


Abstract:-
Several issues have arisen for investigators and informational establishments as a result of the ever-increasing amount of creative work and the wide variety of its themes, resources, and dialects. In addition to difficulties with knowledge transfer and ways to get value for all of this, there are other issues associated with the supply of storing place for knowledge and the variety of processed technology. The current study set out to gain insight on virtualization, elucidating its core concepts and the offerings it offers and the concepts it has inspired in academic libraries as well as data commons for the benefit of scholars and users alike. The researcher will employ the qualitative approach by drawing from a wide range of relevant sources, such as textbooks, papers, dissertations, and academic papers, to provide the necessary findings. The study found that informational facilities and librarians may benefit greatly from cloud applications because of the expense savings and expansion of activities they can also provide. Virtualization has several advantages, but only a small percentage of institutions have adopted them. It's challenging to adopt cutting-edge tech when there aren't enough educated personnel to manage it, however, in the not-too-distant era, many institutions will provide their services using drop box.
Index Terms:-
Models, cloud computing, services, libraries, information center
REFERENCES
  1. W. Hardle and L. Simar. “Applied Multivariate Statistical Analysis” Springer Berlin Heidelberg. 2nd ed., New York, 2007, pp.289-301

  2. P. Jolicoeur. “Sexual dimorphism and geographical distance as factors of skull variation in the wolf Canis lupus L.,” in M.W, Fox,(ed.), The wild canids, Van Nostrand Reinhold Company, New York, 1975,pp. 409 – 432

  3. L.D. Mech. Canis Lupus. Mammalian Species, 1974. Vol. 37, pp.1-6

  4. L.D. Mech. Estimated costs of maintaining a recovered wolf population in agricultural regions of Minnesota. Wildlife Society Bulletin, 2001, vol. 26, pp. 817-822

  5. L.D. Mech, S.H. Fritts and D. Wagner. Minnesota wolf dispersal to Wisconsin and Michigan. American Midland Naturalist, 1995, vol. 133(2), pp. 368-370

  6. P.E. Anyanwu, D.D. Ekezie and I.S.Onyeagu. A Review of the Limitations of Some Discriminant Analysis Procedures in Multi-Group Classification. Mathematical Theory and Modeling, 2015, vol.5, No.9, www.iiste.org ISSN 2224-5804 (Paper) ISSN 2225-0522 (Online)

  7. T. W. Anderson. “An Introduction to Multivariate Statistical Analysis” Published by John Wiley & Sons, Inc. Hoboken, 3rd ed, 2003, New Jersey, pp.207-208

  8. G. O. Nwafor and C. E Onwukwe. On Proper Classification and Placement of Students in Nigerian University Systems Using Discriminant Analysis. American Journal of Applied Mathematics and Statistics, 2014, Vol. 2, No. 6, pp. 394-397

  9. J.O. Onu and O. J. Onyedikachi. An Application of Discriminant Analysis to the Classification of Students on the Basis of their Academic Performances. Journal of Research in Physical Sciences, vol. 2, no. 3, 2006.

  10. M.G. Obudho, G.O. Orwa,, R.O. Otieno, and F.A. Were. Classification of Stateless People through a Robust Nonparametric Kernel Discriminant Function. Open Journal of Statistics, vol. 12, 2022, pp. 563-580.https://doi.org/10.4236/ojs.2022.125034

  11. M. AlKubaisi, W. A. Aziz, S. George and K. Al-Tarawneh. Multivariate Discriminant Analysis Managing Staff Appraisal Case Study. Asian Academy of Management Journal, 9(2), 2021, pp.35-62.

  12. D.F. Morrison. “Multivariate Statistical Methods” McGraw-Hill Publishing Company, 3rd ed., New York, 1996, pp.269-289

  13. A.M. Ksirsagar and E. Arseven “A note on the equivalency of two discrimination procedures” The American statistician, vol.29, 1975, pp.38-39

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