Asian Journal of Mathematical Sciences(AJMS) http://ajms.in/index.php/ajms <p>Mathematics in the Asian region has grown tremendously in recent years. There is a need to have a journal to unite such a development. The Asian Journal of Mathematical Sciences (AJMS) is a new journal that aims to stimulate mathematical research in the Asian region. It publishes original research papers and survey articles on all areas of pure mathematics and theoretical applied mathematics. High standards will be applied in evaluating submitted manuscripts, and the entire editorial board must approve the acceptance of any paper.</p> <p> </p> <p><strong>Asian Journal of Mathematical Sciences (AJMS) </strong>is an international Referred and Peer Reviewed Online Journal with E-ISSN: 2581-3463 published by B.R. Nahata Smriti Sansthan for the enhancement of Pure and Applied Mathematics, Mathematical Physics, Theoretical Mechanics, Probability and Mathematical Statistics, and Theoretical Biology. </p> <p>AJMS is an Open Access Online Journal that publishes full-length papers, reviews and short communications exploring and to promote diverse and integrated areas as Applied Mathematics and Modeling, Analysis and Its Applications, Applied Algebra and Its Applications, Geometry and Its Applications, Algebraic Statistics and Its Applications, Algebraic Topology and Its Applications.</p> <p><strong><u>SUBJECT CATEGORY </u></strong></p> <p>Papers reporting original research and innovative applications from all parts of the world are welcome.</p> <p><strong>Subject areas suitable for publication include, but are not limited to the following fields:</strong></p> <p><strong>Applied Mathematics and Modeling:</strong></p> <ul> <li>Computational Methods,</li> <li>Ordinary and partial Differential Equations,</li> <li>Mathematical Modeling and Optimization,</li> <li>Probability and Statistics Applications,</li> <li>Operations research,</li> <li>Model selection,</li> <li>Bio Mathematics,</li> <li>Data Analysis and related topics. </li> <li>Mathematical Finance,</li> <li>Numerical Solution of Stochastic Differential Equations,</li> <li>Stochastic Analysis and Modeling.</li> </ul> <p><strong>Analysis and Its Applications: </strong></p> <ul> <li>Approximation Theory and Its Applications,</li> <li>Ergodic Theory,</li> <li>Sequence Spaces and Summability,</li> <li>Fixed Point Theory,</li> <li>Functional Analysis and Its Applications and related topics.</li> </ul> <p><strong>Applied Algebra and Its Applications</strong>:</p> <ul> <li>Information Theory and Error Correcting Codes,</li> <li>Cryptography,</li> <li>Combinatorics and Its Applications,</li> <li>Cellular Automata,</li> <li>Fuzzy and Its Applications,</li> <li>Computational Algebra,</li> <li>Computational Group Theory and related topics</li> </ul> <p><strong>Geometry and Its Applications</strong>:</p> <ul> <li>Algebraic Geometry and Its Applications,</li> <li>Differential Geometry,</li> <li>Kinematics and related topics</li> </ul> <p><strong>Algebraic Statistics and Its Applications</strong>:</p> <ul> <li>Algebraic statistics and its applications</li> </ul> <p><strong>Algebraic Topology and Its Applications</strong>:</p> <ul> <li>Algebraic Topology and Its Applications,</li> <li>Knot Theory and related topics</li> </ul> <p><strong>Pure and Applied Mathematics and its Applications</strong>:</p> <ul> <li>Biology,</li> <li>Chemistry,</li> <li>Physics,</li> <li>Zoology,</li> <li>Health Science,</li> <li>Earth Science,</li> <li>Geology,</li> <li>Social Sciences,</li> <li>Industrial research,</li> <li>Computer Science,</li> <li>Agriculture and Forestry,</li> <li>Environmental Sciences,</li> <li>Statistics,</li> <li>Engineering,</li> <li>Natural Sciences,</li> <li>Political Sciences.</li> </ul> <p><strong><u>JOURNAL PARTICULARS</u></strong></p> <table> <tbody> <tr> <td width="281"> <p>Title</p> </td> <td width="517"> <p><strong>Asian Journal of Mathematical Sciences</strong></p> </td> </tr> <tr> <td width="281"> <p>Frequency</p> </td> <td width="517"> <p>Quarterly</p> </td> </tr> <tr> <td width="281"> <p>E- ISSN</p> </td> <td width="517"> <p><strong>2581-3463</strong></p> </td> </tr> <tr> <td width="281"> <p>P-ISSN</p> </td> <td width="517"> <p><strong>-</strong></p> </td> </tr> <tr> <td width="281"> <p>DOI</p> </td> <td width="517"> <p><strong>https://doi.org/10.22377/ajms.v1i1</strong></p> </td> </tr> <tr> <td width="281"> <p>Publisher</p> </td> <td width="517"> <p><strong>Mr. Rahul Nahata</strong>, B.R. Nahata College of Pharmacy, Mhow-Neemuch Road, Mandsaur-458001, Madhya Pradesh</p> </td> </tr> <tr> <td width="281"> <p>Chief Editor</p> </td> <td width="517"> <p>Dr. M.A. Naidu</p> </td> </tr> <tr> <td width="281"> <p>Starting Year</p> </td> <td width="517"> <p>2017</p> </td> </tr> <tr> <td width="281"> <p>Subject</p> </td> <td width="517"> <p>Mathematics subjects</p> </td> </tr> <tr> <td width="281"> <p>Language</p> </td> <td width="517"> <p>English Language</p> </td> </tr> <tr> <td width="281"> <p>Publication Format</p> </td> <td width="517"> <p>Online</p> </td> </tr> <tr> <td width="281"> <p>Email Id</p> </td> <td width="517"> <p>editorajms@brnsspublicationhub.org,editor@brnsspublicationhub.org</p> </td> </tr> <tr> <td width="281"> <p>Mobile No.</p> </td> <td width="517"> <p>+91-7049737901</p> </td> </tr> <tr> <td width="281"> <p>Website</p> </td> <td width="517"> <p>www.ajms.in</p> </td> </tr> <tr> <td width="281"> <p>Address</p> </td> <td width="517"> <p>B.R. Nahata Smriti Sansthan, BRNSS PUBLICATION HUB, B.R. Nahata College of Pharmacy, Mhow-Neemuch Road, Mandsaur-458001, Madhya Pradesh</p> </td> </tr> </tbody> </table> <p> </p> en-US <p>This is an Open Access article distributed under the terms of the Attribution-Noncommercial 4.0 International License [CC BY-NC 4.0], which requires that reusers give credit to the creator. It allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, for noncommercial purposes only.</p> editorajms@brnsspublicationhub.org (M A Naidu) hodca@meu.edu.in (Mr. Nilesh Jain) Tue, 14 Jun 2022 04:20:49 +0000 OJS 3.3.0.8 http://blogs.law.harvard.edu/tech/rss 60 Review on the Inverse Rayleigh Distribution http://ajms.in/index.php/ajms/article/view/407 <p>This article discusses Bayesian and non-Bayesian estimation problem of the unknown parameter for the inverse Rayleigh distribution based on the lower record values. Maximum likelihood estimators of the unknown parameters were obtained. Furthermore, Bayes estimator has been developed under squared error and zero one loss functions. We discuss also statistical properties and estimation of power-transmuted inverse Rayleigh distribution (EIRD). We introduce the transmuted modified inverse Rayleigh distribution using quadratic rank transmutation map, which extends the modified inverse Rayleigh distribution. We introduce a generalization of the inverse Rayleigh distribution known as EIRD which extends a more flexible distribution for modeling life data. Some statistical properties of the EIRD are investigated, such as mode, quantiles, moments, reliability, and hazard function. We describe different methods of parametric estimations of EIRD discussed by using maximum likelihood estimators, percentile-based estimators, least squares estimators, and weighted least squares estimators and compare those estimates using extensive numerical simulations. The new two-scale parameters generalized distribution were studies with its distribution and density functions, besides that the basic properties such as survival, hazard, cumulative hazard, quantile function, skewness, and Kurtosis functions were established and derived. To estimate the model parameters, maximum likelihood, and rank set sampling estimation methods were applied with real-life data. We have introduced weighted inverse Rayleigh (WIR) distribution and investigated its different statistical properties. Expressions for the Mode and entropy have also been derived. A comprehensive account of the mathematical properties of the modified inverse Rayleigh distribution including estimation and simulation with its reliability behavior is discussed.</p> Amel Abd-El- Monem Copyright (c) 2022 Amel Abd-El- Monem https://creativecommons.org/licenses/by-nc/4.0 http://ajms.in/index.php/ajms/article/view/407 Tue, 14 Jun 2022 00:00:00 +0000 On the Analytic Review of Some Contraction and Extension Results in the Hilbert Space with Applications in the Solution of Some Elasticity Problems http://ajms.in/index.php/ajms/article/view/412 <p>This research reviews the analysis of contraction and extension maps in the Hilbert space through the spectral theory approach. Some very important results were discussed and illustrated fully the aid of which analytical works on contraction and extension was fully utilized in the applied mathematics of elasticity theory of various deformation problems as seen in section three of this work.</p> Eziokwu C. Emmanuel Copyright (c) 2022 Eziokwu C. Emmanuel https://creativecommons.org/licenses/by-nc/4.0 http://ajms.in/index.php/ajms/article/view/412 Tue, 12 Jul 2022 00:00:00 +0000 A Monte Carlo Study of Empirical Performance of Threshold Autoregressive Models on Nonlinear Non-Stationary http://ajms.in/index.php/ajms/article/view/413 <p>One of the major importance of modeling in time series is to forecast future values of that series which requires the use of appropriate method to fit the time series data that are dependent on the nature of the data. However, real-life data are mostly non-stationary and nonlinear. This will be a problem when a model is in appropriately applied to data that does not fits in, the result of the outcome will be inaccurate and this will not give the clear picture of what the data entails in the future events. In this study, the performances of the smooth transition autoregressive (STAR) and the self-exciting threshold autoregressive (SETAR) models of different orders and regimens were compared on different forms of nonlinear cases of autoregressive under violation of stationarity assumption. Simulated data with features of nonlinearity and non-stationarity were used to compare the performance of the models. The relative performances of the models were examined with a view to identify the best models at orders 1, 2, and 3, and regimen 2 when fitted to linear, trigonometric, exponential, and polynomial autoregressive functions. It was concluded that the SETAR (2, 1) is the best model followed by SETAR (2, 2) to fit linear data, whereas the SETAR (2, 2) and STAR (2, 3) are considered to be the best for an exponential and SETAR (2, 2) and STAR (2, 2) for a polynomial data.</p> Alhaji Umar Abubakar Copyright (c) 2022 Alhaji Umar Abubakar https://creativecommons.org/licenses/by-nc/4.0 http://ajms.in/index.php/ajms/article/view/413 Tue, 12 Jul 2022 00:00:00 +0000 A Mathematical Model for the Control on the Transmission Dynamics of COVID-19 Pandemic Containing Asymptomatic and Symptomatic Classes http://ajms.in/index.php/ajms/article/view/414 <p>In this research paper work, we developed a COVID-19 epidemic disease model fitted in Nigeria situation. In this model system, we divided Nigeria population into six subpopulations such as Susceptible population, Exposed population, Infected asymptomatic population, Infected symptomatic population, isolated symptomatic population, and the fully recovered population. Control measures parameter (hand sanitizers and nose masks) was incorporated into the model. We obtained the disease-free equilibrium and endemic equilibrium points. The basic reproduction number was obtained using the new generation matrix, the local and global stability was also obtained to be locally and globally asymptotically stable at R0&lt;1 for the DFE. We did numerical simulations using (Maple 17) software. The results showed the importance of the control measures and social distancing through graph.</p> O. A. Adedayo Copyright (c) 2022 O. A. Adedayo https://creativecommons.org/licenses/by-nc/4.0 http://ajms.in/index.php/ajms/article/view/414 Tue, 12 Jul 2022 00:00:00 +0000 A Study on Selected Mathematical Theories for Decision-Making Problems http://ajms.in/index.php/ajms/article/view/411 <p>The most appropriate mathematical theory for dealing with uncertainty in decision making problems, the theory of fuzzy set developed by Zedeh in 1965. Later in 1999, Molodstov introduced another one namely, soft set theory for modelling vagueness and uncertainty in decision making problems. In this paper, we study some mathematical tools such as fuzzy set, soft set and fuzzy soft set for solving decision making problems.</p> Sreelekshmi C. Warrier Copyright (c) 2022 Sreelekshmi C. Warrier https://creativecommons.org/licenses/by-nc/4.0 http://ajms.in/index.php/ajms/article/view/411 Tue, 12 Jul 2022 00:00:00 +0000 Mathematical Modeling for the Transmission Dynamics Control of HIV and Malaria Coinfection in Nigeria towards Attaining Millenium Development Goal http://ajms.in/index.php/ajms/article/view/415 <p>Human immune deficiency virus and malaria coinfection are among the greatest health problems globally and the understanding of how the two infections network could be imperative for the control of both diseases. Hence, this research formulated a mathematical model to study the coinfection of human immunodeficiency virus/acquired immunodeficiency syndrome and malaria in the presence of treatment as control measures. The basic reproduction number was obtained using the next generation matrix method. The simulations were carried out using MAPLE 18 software. The result shows that the malaria treatment does not have any effect on the total coinfected populations. Thus, every sick person should be tested to ascertain the source of their health challenges.</p> S. Ale Copyright (c) 2022 S. Ale https://creativecommons.org/licenses/by-nc/4.0 http://ajms.in/index.php/ajms/article/view/415 Tue, 12 Jul 2022 00:00:00 +0000 Application of Multi-server Queue Model (m/m/c) for Waiting Lines Management in Banking System http://ajms.in/index.php/ajms/article/view/418 <p>Queues or waiting lines arise when the demand for service exceeds the capacity of a service facility.<br>One of the major challenges bank customers encounter in banks is the waiting lines in automated teller<br>machines (ATMs). This study formulated a Multi-Server Queue Model (M/M/C) for Queue Management<br>in Banking ATM. The performance level of a typical bank ATM has been effectively investigated using<br>the M/M/S queuing model. It was observed that the busy time of the machine is 2.6 h while the idle time<br>is 7.4 h in the 10 h of banking time which is attributed to the availability of many servers in the system.<br>The utilization factor is 0.26 or 26.0% shows that the service delivery of the machine is very efficient and<br>there is no urgent need for an additional server. The researcher thereby recommended that banks should<br>consider the use of the queue model to test the performance of waiting lines in the ATMs.</p> S. A. Akande Copyright (c) 2022 S. A. Akande https://creativecommons.org/licenses/by-nc/4.0 http://ajms.in/index.php/ajms/article/view/418 Thu, 28 Jul 2022 00:00:00 +0000