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              <text>Effects of Peer Monitoring on Student Stress Level of College Students Based on Multi-Layer Perceptron Approach</text>
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              <text>Individuals with Disabilities Education Act (IDEA); Linear Discriminant Analysis (LDA); MultiLayer Perceptron (MLP)</text>
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              <text>The classroom is just one of many places where the proposed approach encounter stress. Previous studies have shown that college students experience high rates of stress. It is not known if the Student Stress Inventory-Stress Manifestations (SSI-SM) is useful in identifying stressors and evaluating stress manifestations among college students. To this end, it was created a college-specific version of the Student Stress Inventory-Stress Manifestations (SSI-SM) and administered it to students to determine its validity and reliability. These procedures comprise the proposed technique and include preprocessing, feature selection, and model training. It uses Normalization as a preprocessing approach. The term' normalization' refers to the procedure of rescaling or modifying data so that all categories have the same variance. The proposed approach employed linear discriminant analysis as a means of selecting features. The models are then trained using MLP after information gain has been used to choose relevant features. The proposed approach achieves better results than the two leading alternatives, CNN and RNN.   2024 IEEE.</text>
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              <text>Shaikh I.A.K.; Gupta K.; Parasar A.; Thulasimani T.; Little Femilin Jana D.; Chauhan A.</text>
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              <text>2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024, pp. 1370-1375.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/IDCIoT59759.2024.10467811" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/IDCIoT59759.2024.10467811&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190093258&amp;amp;doi=10.1109%2FIDCIoT59759.2024.10467811&amp;amp;partnerID=40&amp;amp;md5=d4b7ab7bb4a33cfde7647bd756591500" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190093258&amp;amp;doi=10.1109%2fIDCIoT59759.2024.10467811&amp;amp;partnerID=40&amp;amp;md5=d4b7ab7bb4a33cfde7647bd756591500&lt;/a&gt;</text>
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              <text>ISBN: 979-835032753-3</text>
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              <text>Shaikh I.A.K., Bahrain Polytechnic, Faculty of Business, Bahrain; Gupta K., School of Commerce and Management, IIMT University, Meerut, India; Parasar A., Galgotias University, India; Thulasimani T., Bannari Amman Institute of Technology, Department of Mathematics, Sathyamangalam, India; Little Femilin Jana D., Prince Shri Venkateshwara Padmavathy Engineering College, Department of Science &amp;amp; Humanities, Tamil Nadu, Chennai, India; Chauhan A., School of Sciences, CHRIST (Deemed to Be University), Department of Life Sciences, Bengaluru, Karnataka, India</text>
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