https://jase.a2zjournals.com/index.php/ase <p><img style="float: left; padding-right: 10px; width: 300px; height: 400px;" src="https://jase.a2zjournals.com/public/site/images/editor/jase-ls-c781415c41980bc6d1e6e4bc6dadc8fb.jpg" alt="" width="300" height="400" /></p> <p align="justify">International journal <strong>"Journal of Applied Science and Education (JASE)"</strong> is a scholarly, peer-reviewed, and fully refereed open access international research journal published twice a year in the Multiple Languages (English, Hindi), provides an international forum for the publication and dissemination of theoretical and practice-oriented papers, dealing with problems of modern technology (Applied Engineering, Mathematics, Chemistry, Physics, Engineering Physics, Statistics, Environmental Sciences, Geology, Social Sciences, Biology, Natural and Technological Sciences, Linguistics, Food Science, Agricultural Engineering, Professional Ethics, Behavioural Science, etc). <strong>JASE</strong> welcomes regular papers, short papers, review articles, etc. The journal reviews papers within three-six weeks of submission and publishes accepted articles online immediately upon receiving the final versions. All the papers in the journal are freely accessible as online full-text content and permanent worldwide web link. The article will be indexed and available in major academic international databases. <strong>JASE</strong> welcomes you to submit your research for possible publication in <strong>JASE</strong> through our online submission system. <strong>ISSN: 2583-1372 (E)</strong></p> A2Z Journals en-US Journal of Applied Science and Education (JASE) 2583-1372 https://jase.a2zjournals.com/index.php/ase/article/view/78 <p><em>The physico-chemical and microbiological characteristics of Jaisamand Dam in Alwar are examined in this work. The adjacent rural villages rely on Jaisamand Dam for drinking water and irrigation. The Ruparail River and Siliserh Lake have been over-flowing, creating the lake. The data collected throughout the year 2024. Low visibil-ity, dissolved oxygen, and low fluoride levels, along with high temperature, pH, BOD, TDS, TSS, alkalinity, total hardness, chloride, DO, conductivity and alkalinity clearly indicate poor water quality.</em></p> Dr Ashok Kumar Kakodia Dr Shiv Lal L.N. Jatolia Kumud Tanwar Copyright (c) 2025 Dr Ashok Kumar Kakodia, Dr Shiv Lal, L.N. Jatolia, Kumud Tanwar https://creativecommons.org/licenses/by/4.0 2024-11-25 2024-11-25 4 3 1 10 10.54060/a2zjournals.jase.78 https://jase.a2zjournals.com/index.php/ase/article/view/71 <p><em>This study investigates the effectiveness of three machine learning classifi-ers—Random Forest, SVM, and XGBoost—in detecting benign files using a dataset of file features. The dataset is cleaned by removing rows with missing values and du-plicates, followed by feature scaling with StandardScaler. Correlation heatmaps and confusion matrix visualizations are used to explore data relationships and model performance. The classifiers are trained and evaluated based on accuracy, precision, recall, F1-score, and ROC-AUC. Results indicate the comparative performance of each model, highlighting their strengths and weaknesses in distinguishing between benign and non-benign files. This comprehensive approach provides insights into the most suitable classifier for this specific detection task.</em></p> Ujjwal Singh Dr P. Singh Copyright (c) 2025 Ujjwal Singh, Dr P. Singh https://creativecommons.org/licenses/by/4.0 2024-11-25 2024-11-25 4 3 1 13 10.54060/a2zjournals.jase.71