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Suresh Kumar Sahani
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Mikailalsys Journal of Mathematics and Statistics
Published by Lembaga Yasin Alsys
ISSN : 30308399     EISSN : 3030816X     DOI : https://doi.org/10.58578/mjms
Core Subject : Education, Engineering,
Engineering Mathematics Mechanical Engineering
The journal contains scientific articles covering topics such as mathematical theory, statistical methods, the application of mathematics in various disciplines, and statistical data analysis. The primary objective of this journal is to promote a better understanding of mathematical and statistical concepts and to encourage advancements in the methods and applications of mathematics and statistics in various contexts. The journal serves as a platform for researchers, academics, and practitioners to share knowledge and the latest research findings in the fields of mathematics and statistics. MJMS publishes three editions a year in February, June, and October.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 102 Documents
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An Overview of Integral Transformation Methods for Solving Physical Problems Umar Mujahid Aliyu; A. G. Madaki; A. M. Kwami; M. I. Bello; J. O. Okai; Abubakar Assidiq Hussaini
Mikailalsys Journal of Mathematics and Statistics Vol 4 No 3 (2026): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v4i3.9378

Abstract

Integral transformation methods are widely used to solve physical problems formulated through differential equations; however, their effectiveness may vary across linear, nonlinear, and fractional systems. This study provides an analytical overview of major integral transforms, with particular emphasis on the Kamal and Laplace transforms and their integration with decomposition-based techniques, including the Adomian decomposition method. Through a critical discussion of relevant analytical procedures and illustrative examples, the study examines the applicability, efficiency, and accuracy of these methods in solving linear, nonlinear, and fractional differential equations arising in physical systems. The analysis indicates that integral transforms offer efficient and accurate solution procedures, particularly for linear differential equations. Nevertheless, their direct application to nonlinear and fractional problems presents computational and analytical challenges, thereby requiring hybrid approaches that combine transformation techniques with decomposition methods. The study concludes that hybrid integral-transform methods can extend the applicability of conventional analytical techniques to more complex differential equations. It contributes to the literature by synthesizing the strengths and limitations of integral-transform approaches and identifying opportunities to improve their computational efficiency and applicability in modeling physical systems.
Sensitivity Analysis of the Basic Reproduction Number for Two Strains Covid-19 Model with Vaccination and Awareness Program Anate A.O.; Adamu M. M.; Adamu M.S.; Kwami A. M.
Mikailalsys Journal of Mathematics and Statistics Vol 4 No 3 (2026): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v4i3.9382

Abstract

Sensitivity analysis of the basic reproduction number is an essential mathematical tool for identifying the parameters that most strongly influence disease transmission in epidemiological models. This study analyzes the sensitivity of the basic reproduction number in a COVID-19 transmission model comprising seven mutually exclusive compartments and incorporating vaccination and awareness interventions. The basic reproduction number, R₀, was derived using the next-generation matrix method, after which local sensitivity analysis was conducted using data obtained from the Nigeria Centre for Disease Control and other sources. The analysis produced two values of R₀ whose magnitudes depend on the model parameters, particularly those associated with vaccination and public awareness. The findings indicate that recruitment and infection rates exert strong positive effects on disease transmission, whereas vaccination and natural recovery rates have negative effects on disease progression. These results demonstrate that reducing infection-related parameters while strengthening vaccination and recovery mechanisms is critical for controlling COVID-19 transmission. The study contributes to epidemiological modeling by identifying the parameters that should be prioritized in disease-control strategies. Accordingly, policymakers should implement coordinated interventions, including quarantine, lockdown measures, vaccination programs, and effective public awareness campaigns, to reduce transmission and limit disease growth.

Page 11 of 11 | Total Record : 102

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