Journal of Research in Multidisciplinary Methods and Applications
http://www.satursonpublishing.com/jrmma
<h1>About the Journal</h1> <p>Journal of Research in Multidisciplinary Methods and Applications (JRMMA) is a peer-reviewed, monthly, online international refereed journal, which emphasizes on the progress in multidisciplinary methods and applications, and publishes original articles, research articles, review articles with top-level work from all areas of science and engineering research including Mechanical, Civil, Electrical, Chemical, Electronics, Mathematics and Geological etc. Researchers in all science and engineering fields are encouraged to contribute articles based on recent research. Journal publishes research articles and reviews within the whole field of science and engineering research, and it will continue to provide information on the latest trends and developments in this ever-expanding subject.</p> <p>This journal covers almost all disciplines of science, engineering and applied sciences. Researchers and students of M.S., M. Phil and PhD are encouraged to send their original research articles to JRMMA.</p> <h1>Journal Details</h1> <p>ISSN 2957-3920 (Online)</p> <p>ISSN 3007-7060 (Print)</p> <p>Frequency: monthly</p> <p>Accepted Language: English</p> <p>Publisher: Saturson Publishing Limited</p> <p>Format: Online/Print</p> <p>Submit Manucript to:</p> <p>jrmma@satursonpublishing.com</p> <h1><img src="http://www.satursonpublishing.com/public/site/images/stephen/cover-04402784691d8cf8909a13ae5984383c.png" alt="" width="300" height="424" /></h1>Saturson Publishing Limiteden-USJournal of Research in Multidisciplinary Methods and Applications3007-7060An Automatic Data Augment Method for Remaining Useful Life Prediction of Aeroengines
http://www.satursonpublishing.com/jrmma/article/view/a01260501001
<p class="abstractandkeywords"><span lang="EN-US">The prediction of remaining service life in complex aviation engine systems is of great significance for airlines to develop maintenance plans for engines and reduce maintenance cost. However, the complex operating conditions of the engine and insufficient fault mode data limit the prediction accuracy. One direction to solve such problems is data augmentation, which aims to generate synthetic data from real datasets to expand training samples and improve the model's generalization ability. Admittedly, there are already many mature data augmentation methods, but the optimal data augmentation strategy for RUL prediction tasks varies in different situations. Confirming which data augmentation strategy is most suitable for the current remaining useful life prediction problem requires human experience or extensive parameter experiments. This work proposes an automatic data augmentation method(AdaRUL),Build an automatic search space and use reinforcement learning algorithms to search for the optimal strategy in the automatic search space to expand the sample dataset. The experiments conducted on the C-MAPSS public dataset provided by NASA demonstrate that AdaRUL has successfully generated high fidelity multivariate monitoring data. In addition, these generated data effectively support RUL prediction tasks and significantly improve the predictive ability of underlying deep learning models.</span></p>Zequan WangHanqing ZhouJianfeng YangXing Ding
Copyright (c) 2026
https://creativecommons.org/licenses/by-nc-nd/4.0
2026-01-152026-01-15510126050100101260501001Research On the Teaching Integration of Vocal Music and Ancient Poetry Culture in Colleges and Universities Under the Vision of Interdisciplinary Integration
http://www.satursonpublishing.com/jrmma/article/view/a01260501002
<p> Ancient poetry is a treasure of traditional Chinese culture, and ancient Chinese poetry and songs are an important vocal genre created on its basis. By analyzing the development context of ancient poetry and songs and their cultural connotations, this paper explains their importance in current college education, and puts forward specific paths to strengthen cultural self-confidence from the long history, taste the cultural connotation from desk work, and broaden the path of cultural inheritance from multiple presentations. In the context of advocating interdisciplinary integration in the construction of new liberal arts in colleges and universities, this paper puts forward the teaching concept of deep integration of vocal music performance and ancient poetry culture in view of the current phenomenon of emphasizing skills over literature in vocal music teaching in colleges and universities. This study takes the famous work of Song Dynasty poet Yan Shu, "Butterfly Love Flower, Threshold Chrysanthemum Sorrowful Smoke Orchid Weeping Dew" as the core case, and comprehensively uses literature research, case analysis and teaching practice to deeply explore the literary meaning, musical characteristics and integration path of the lyrics in vocal music teaching.</p>Li Liu Li Zhang
Copyright (c) 2026
https://creativecommons.org/licenses/by-nc-nd/4.0
2026-01-152026-01-15510126050100201260501002Research On the Problems and Countermeasures of Teacher-Child Interaction in Small Class Health Education Teaching Activities
http://www.satursonpublishing.com/jrmma/article/view/a01260501003
<p> The health field is the first of the five major fields, and health education lays a good foundation for children's health and a better life throughout their lives. Teacher-child interaction is a two-way communication between teachers and children. Correct teacher-student interaction can promote the creation of a democratic and harmonious classroom atmosphere, the interpersonal communication of preschool children, and the sensitivity of teachers in activities. This study mainly uses the observation method to analyze the current situation of teacher-child interaction in small class health teaching activities, and finds that there is a lack of teaching of children's daily health knowledge, the dominance of teachers in teacher-child interaction, and the "adult" language expression of teachers in teaching activities.</p>Yuchen Luo Hailing Cheng Chunmao Ren Xing Liu
Copyright (c) 2026
https://creativecommons.org/licenses/by-nc-nd/4.0
2026-01-152026-01-15510126050100301260501003