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>[email protected],[email protected]</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>[email protected] (M A Naidu)[email protected] (Mr. Nilesh Jain)Fri, 15 Dec 2023 00:00:00 +0000OJS 3.3.0.13http://blogs.law.harvard.edu/tech/rss60SUITABILITY OF COINTEGRATION TESTS ON DATA STRUCTURE OF DIFFERENT ORDERS
http://ajms.in/index.php/ajms/article/view/520
<p>When selecting a method to evaluate theories about the relationship between two variables that have a<br>unit root or, it is necessary to consider the potential existence of cointegration. If the relationship exists<br>between the two variables, it should be able to forecast one variable based on the other, which is why<br>cointegration is significant for time series data including many variables. Using the three approaches, this<br>research investigates the cointegration processes and integration level. Determine whether the time series<br>is stationary and if there is a seasonal effect before looking at cointegration in a combination of variables.<br>A time series plot is used to monitor patterns and the time series data's behaviors. Applying the log<br>transformation and differencing approach will make the data stationar. The data was then subjected to the<br>Augmented Dickey Fuller (ADF) test, which verifies whether or not a unit -root exists by following a<br>unit-root procedure. In the event that the series lacks a unit root process, the data may be considered<br>stationary. The analysis techniques used in the research include the Granger Causality Test, Johansen test,<br>Phillips-Ouliarisco integration test, Engle–Granger two-step method, and simple correlation and<br>regression analysis. R statistical software was used for all of the analyses on a time series data set<br>containing these variables. In conclusion, the results of the three tests indicate cointegration, with the<br>Phillips–Ouliaris test being the most effective whether the sample size is small, medium, or big,<br>respectively, for both normal and gamma distributions. Engle–Granger and Johansen tests are then<br>optimal. Additionally, it was noted that as correlation confidence levels rose, so did the strength of the<br>determination of the cointegration across the correlation.</p>Muhammad G. Bukar
Copyright (c) 2024 Muhammad G. Bukar
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http://ajms.in/index.php/ajms/article/view/520Fri, 15 Dec 2023 00:00:00 +0000SYMMETRIC BILINEAR CRYPTOGRAPHY ON ELLIPTIC CURVE AND LIE ALGEBRA
http://ajms.in/index.php/ajms/article/view/521
<p>Elliptic Curve Cryptography (ECC) has gained widespread adoption in the field of cryptography due to<br>its efficiency and security properties. Symmetric bilinear pairings on elliptic curves have emerged as a<br>powerful tool in cryptographic protocols, enabling advanced constructions and functionalities. This paper<br>explores the intersection of symmetric bilinear pairings, elliptic curves, and Lie algebras in the context of<br>cryptography. We provide a comprehensive overview of the theoretical foundations, applications, and<br>security considerations of this amalgamation.</p>Michael N. John
Copyright (c) 2024 Michael N. John
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http://ajms.in/index.php/ajms/article/view/521Fri, 15 Dec 2023 00:00:00 +0000TRANSCENDENTAL CANTOR SETS AND TRANSCENDENTAL CANTOR FUNCTIONS
http://ajms.in/index.php/ajms/article/view/516
<p>In this article, we consider the self-similar generalized Cantor set ,,, n n<br>l C i C i i 1 , and we<br>establish the existence of probability true measure<br><br>such that<br> <br>,..,<br>1<br>j<br>j s<br>E E<br>s<br> <br> <br> 1<br>0 1<br>generated by n Ci<br>. The Holder order of the set n Ci<br>is logn s<br>and we establish that<br> , , l l x n x s i i n<br> <br> <br> <br>1 1<br>2<br>for all not finite n -adic ,..., . n<br>l xC i i 1<br>Transcendental numbers, such as e and are a mathematical expression of nature, we introduce the<br>transcendental Cantor set generated by transcendental numbers, which can be defined by<br> <br>, ,...,<br>lim n<br>k k<br>k<br>k<br>C C C<br><br><br> <br>0 1 , where the sequence k C<br>is non-increasing and corresponds with the<br>transcendental number<br><br>, for such a set, we consider an analog of the Cantor function.</p>Yaremenko Mykola Ivanovich
Copyright (c) 2024 Yaremenko Mykola Ivanovich
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http://ajms.in/index.php/ajms/article/view/516Fri, 15 Dec 2023 00:00:00 +0000AN ASSESSMENT ON THE SPLIT AND NON-SPLIT DOMINATION NUMBER OF TENEMENT GRAPHS
http://ajms.in/index.php/ajms/article/view/517
<p>One of the primary fields of mathematics, graph theory is an intriguing and exciting subject. A network is<br>represented mathematically by a graph, which identifies the connections between nodes and edges. One<br>of the fascinating areas of mathematics is Graph Theory. A large area of graph theory is called<br>dominance in graphs. Claude Berge formalised dominance as a theoretical field in graph theory.<br>Domination is one of the fascinating and active areas of Graph Theory research. In this paper, we first<br>provide basic definitions, outlining both core ideas and certain dominant concepts. In specifically,<br>Tenement graphs, a novel type of graph, are defined. Tenement graphs' Split and Non-Split Domination<br>Numbers are addressed.</p>AMRIN M
Copyright (c) 2024 AMRIN M
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http://ajms.in/index.php/ajms/article/view/517Fri, 15 Dec 2023 00:00:00 +0000ALPHA LOGARITHM TRANSFORMED SEMI LOGISTIC DISTRIBUTION USING MAXIMUM LIKELIHOOD ESTIMATION METHOD
http://ajms.in/index.php/ajms/article/view/518
<p>In this article, we review the maximum likelihood method for estimating the parameters of a fitted model<br>and show that this method generally provides the asymptotically best estimate with the smallest mean<br>Error. Therefore, maximum likelihood estimation is sufficient for most applications in data science. The<br>Fisher data matrix describes the orthogonality of parameters in a probabilistic model and always results<br>from the highest possible estimate. Parameters associated with the model were estimated using the<br>Maximum Likelihood Estimation (MLE) method. The maximum likelihood estimation method in a risk<br>function is used to estimate the parameters of the alpha log-transformed semi-logistic distribution to<br>determine the best method. Since the inverse of the Fisher data matrix provides the variance matrix of the<br>prediction error, orthogonalizing the parameters ensures that the parameters are distributed independently<br>of each other. Finally, the extended model was applied to real data and results showing the performance<br>of ALTSL classification compared to other classification methods are presented. We present the MLE of<br>the unknowns in this distribution using Newton-Raphson. We also calculate the Average Estimation<br>(AE), Variance (VAR), Mean Absolute Deviation (MAD), Mean Square Error (MSE), Relative Absolute<br>Bias (RAB) and Relative Efficiency (RE) for both the parameters under sample based on 10000<br>simulations to assess the performance of the estimators. Also, we derive the asymptotic confidence<br>bounds for unknown parameters.</p>I. Narasimha Rao
Copyright (c) 2024 I. Narasimha Rao
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http://ajms.in/index.php/ajms/article/view/518Fri, 15 Dec 2023 00:00:00 +0000