Bukola A. Onyekwelu

Work place: Department of Mathematics and Computer Science, Elizade University, P. M. B. 002, Ilara-Mokin, Nigeria

E-mail: bukola-onyekwelu@elizadeuniversity.edu.ng

Website:

Research Interests: Computational Science and Engineering, Computational Engineering, Computational Mathematics, Intrusion Detection System, Mathematics

Biography

Onyekwelu, Bukola Abimbola
Place & Date of Birth: Ado-Ekiti, Nigeria, 05 Dec. 1970
Educational Background:
 Ph.D. in Computer Science, Federal University of Technology, Akure, Ondo State., Nigeria - 2015
 M.Tech in Computer Science, Federal University of Technology, Akure, Ondo State, Nigeria-2009
 Post-Graduate Diploma in Computer Science, Federal University of Technology, Akure, Ondo State, Nigeria -2004
 B.Tech in Computer Science, Federal University of Technology, Akure, Ondo State, Nigeria-1991
Research/Area of Interest: CyberSecurity, Intrusion Detection, Science, Technology, Engineering and Mathematics (STEM) Initiatives.
Working Experience
 Lecturer I, Department of Mathematics and Computer Science, Faculty of Basic and Applied Sciences, Elizade University, Ilara-Mokin, Ondo State. January 2018 to date
 Lecturer I, Department of Computer Science, College of Natural Sciences, Joseph Ayo Babalola University, Ikeji-Arakeji, Osun State. October 2016 to December 2017
 Lecturer II, Department of Computer Science, College of Natural Sciences, Joseph Ayo Babalola University, Ikeji-Arakeji, Osun State. October 2013 to September 2016
 Assistant Lecturer, Department of Computer Science, College of Natural Sciences, Joseph Ayo Babalola University, Ikeji-Arakeji, Osun State. March 2010 to September 2013
 Lecturer (Part-time), Department of Computer Studies, Federal Polytechnic, Ado-Ekiti, Ekiti State. May to August 2009
Membership of Professional Bodies
 Member, Society of Digital Information and Wireless Communications (SDIWC)
 Member, Computer Professionals of Nigeria (CPN)
 Member, Nigerian Computer Society (NCS)
 Member, Nigerian Women In Information Technology (NIWIIT)
Member, Organization for Women in Science for the Developing World (OWSD)

Author Articles
Comparative Empirical Analysis of Female University Enrolment in STEM Courses in the Geopolitical Zones in Nigeria

By Bukola A. Onyekwelu

DOI: https://doi.org/10.5815/ijmecs.2019.01.03, Pub. Date: 8 Jan. 2019

Though University enrolment in Nigeria is on the increase, more males than females are still being enrolled today, which varies according to discipline as well as from one geopolitical zone of the country to another. This is more pronounced in Science, Technology, Engineering and Mathematics fields, as female enrolment seems to be higher in the commercial and arts courses than the sciences and engineering. Secondary data were obtained from the Nigerian Bureau of Statistics, based on the Joint Admission and Matriculation Board registrations for a period of 5 years, spanning 2011 to 2015. The data were classified based on the six geopolitical zones in Nigeria, and multivariate data analysis, supported by Multivariate Analysis of Variance was carried out on the data. The results obtained revealed that there is still a wide variance in male and female enrolment in these fields, with male enrolment being significantly higher than that of female candidates. It also revealed that female enrolment varies depending on the geopolitical zone, with female enrolment in Science, Technology, Engineering and Mathematics being generally higher in geographical zones in southern Nigeria compared with those in northern Nigeria. The results obtained were further compared with data obtained from previous researches and the comparison was discussed. In addition, this study offers recommendations on how to encourage more female participation in Science, Technology, Engineering, and Mathematics.

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Pre-Processing of University Webserver Log Files for Intrusion Detection

By Bukola A. Onyekwelu B. K. Alese A. O. Adetunmbi

DOI: https://doi.org/10.5815/ijcnis.2017.01.03, Pub. Date: 8 Jan. 2017

Web Server log files can reveal lots of interesting patterns when analyzed. The results obtained can be used in various applications, one of which is detecting intrusions on the web. For good quality of data and usable results, there is the need for data preprocessing. In this research, different stages of data preprocessing were carried out on web server log files obtained over a period of five months. The stages are Data Conversion, Session Identification, Data Cleaning and Data Discretization. Data Discretization was carried out in two phases to take care of data with continuous attributes. Some comparisons were carried out on the discretized data. The paper shows that with each preprocessing step, the data becomes clearer and more usable. At the final stage, the data presented offers a wide range of opportunities for further research. Therefore, preprocessing web server log files provides a standard processing platform for adequate research using web server logs. This method is also useful in monitoring and studying web usage pattern in a particular domain. Though the research covers webserver log obtained from a University domain, and thus, reveals the pattern of web access within a university environment, it can also be applied in e-commerce and any other terrain.

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