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>BRNSS Publication Huben-USAsian Journal of Mathematical Sciences(AJMS)<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>ALGEBRAIC SOLUTION OF FERMAT'S THEOREM (MATHEMATICS, NUMBER THEORY)
http://ajms.in/index.php/ajms/article/view/543
<p>Fermat's Last Theorem (or Fermat's last theorem) is one of the most popular theorems in mathematics.<br>Formulated in French mathematician Pierre Fermat in 1637. Despite the simplicity of the formulation,<br>literally, at the “school” arithmetic level, proof of the theorem sought by many mathematicians for more<br>than three hundred years. And only in 1994 year the theorem was proven by the English mathematician<br>Andrew Wilson with colleagues; The proof was published in 1995. [1]-[5] The author of this article has<br>been searching for his own for a long time. accessible algebraic solution to this problem and believes that<br>he succeeded,which he presents in this article.</p>Khusid Mykhaylo
Copyright (c) 2024 Khusid Mykhaylo
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2024-06-152024-06-1580210.22377/ajms.v8i02.543BRIDGING THE KNOWLEDGE GAP: ENHANCING TRACHEOSTOMY CARE SKILLS THROUGH STRUCTURED LEARNING
http://ajms.in/index.php/ajms/article/view/544
<p>Background-Tracheostomy care is essential for patients with severe respiratory issues, yet traditional<br>nursing education often inadequately prepares students for this complex procedure. This study explores<br>the impact of a structured educational program on improving the knowledge and skills of nursing students<br>in tracheostomy care.Aim-The primary objective of this study is to evaluate the effectiveness of a<br>structured educational program in enhancing the knowledge, skills, and confidence of nursing students<br>regarding tracheostomy care.Methods-An evaluative approach with a pre-experimental one-group<br>pretest-post-test design was employed. The study was conducted at SCPM College of Nursing and<br>Paramedical Sciences, Gonda, UP, involving 40 second-year GNM students. A structured questionnaire<br>assessed knowledge levels before and after the intervention and study samples were recruited with the<br>help of purposive sampling technique. Data collection was performed by six trained BSc nursing tutors<br>and analysed using SPSS, with a significance level of <0.05 and a 95% confidence interval.Results-The<br>pretest mean score was 11.42 (SD = 1.9596), while the post-test mean score increased to 17.50 (SD =<br>2.2870), with a mean difference of 6.08. The standard error was 0.47, and the calculated t-value was<br>12.76, compared to the tabulated value of 1.685, indicating a significant improvement in knowledge<br>levels.Conclusion-The structured educational program significantly enhanced the knowledge and<br>practical skills of nursing students regarding tracheostomy care, demonstrating its effectiveness as a<br>teaching method.</p>Jeya Beulah D,
Copyright (c) 2024 Jeya Beulah D,
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2024-06-152024-06-1580210.22377/ajms.v8i02.544PREDICTING DIABETES USING DEEP LEARNING TECHNIQUES: A STUDY ON THE PIMA DATASET
http://ajms.in/index.php/ajms/article/view/545
<p>Diabetes is one of the key reasons of growing death rates around the world. Diabetes is a medical<br>condition that arises from chronic issues that influence carbohydrate metabolism and raise blood glucose<br>levels. Scientific research is needed to diagnose diabetes early for prevention and treatment due to the<br>growing rates of the disease. Researchers have recognized the value of classification models for disease<br>prediction developed using machine learning and deep learning techniques. This study explores the<br>efficacy of deep learning techniques Convolutional Neural Network (CNN), Long Short-Term Memory<br>(LSTM), and Multi-Layer Perceptron (MLP)—in forecasting diabetes using the Pima dataset.<br>Preprocessing steps encompassed normalization, handling missing values, and outlier removal. The<br>models were trained and evaluated, yielding noteworthy performance metrics. The CNN exhibited the<br>highest accuracy of 0.77, while achieving precision, recall, and ROC-AUC scores of 0.69, 0.67, and 0.83,<br>respectively. The LSTM and MLP models also demonstrated competitive results, achieving accuracies of<br>0.75 with similar precision, recall, and ROC-AUC values around 0.64-0.67 and 0.80-0.82, respectively.<br>These findings highlight the potential of deep learning methodologies for predictive diabetes analysis and<br>emphasize the significance of proper preprocessing techniques in enhancing model performance.</p>Emad Majeed Hameed
Copyright (c) 2024 Emad Majeed Hameed
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2024-06-152024-06-1580210.22377/ajms.v8i02.545