Machine Learning-Driven Structural Optimization of a Bistable RF MEMS Switch for Enhanced RF Performance by J. Joslin Percy, S. Kanthamani, S. Mohamed Mansoor Roomi

“…The proposed I-clamp switch was optimized using an eXtreme Gradient Boost (XGBoost) ML model to predict optimal design parameters while significantly reducing the computational overhead of conventional EM simulations. Activation functions were employed within the ML model to improve the accuracy of predicting optimal design parameters by capturing complex nonlinear relationships. …”
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Design of a Prediction Model to Predict Students’ Performance Using Educational Data Mining and Machine Learning by Jayasree R, Sheela Selvakumari

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Machine learning-enabled multiscale modeling platform for damage sensing digital twin in piezoelectric composite structures by Somnath Ghosh, Saikat Dan, Preetam Tarafder

“…Artificial neural network operates on micro-electro-mechanical data to derive PUCCDM constitutive coefficients as functions of underlying representative aggregated microstructural parameters (RAMPs). …”
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A Portable and Affordable Four-Channel EEG System for Emotion Recognition with Self-Supervised Feature Learning by Hao Luo, Haobo Li, Wei Tao, Yi Yang, Chio-In Ieong, Feng Wan

“…It features over 7 h of continuous operation, plug-and-play functionality, and modular expandability. At the algorithmic level, we introduce a self-supervised feature extraction framework that combines contrastive learning and masked prediction tasks, enabling robust emotional feature learning from a limited number of EEG channels with constrained signal quality. …”
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rocorl: Transferable Reinforcement Learning-Based Robust Control for Cyber-Physical Systems With Limited Data Updates by Gwangpyo Yoo, Minjong Yoo, Ikjun Yeom, Honguk Woo

“…Autonomous control systems are increasingly using machine learning technologies to process sensor data, making timely and informed decisions about performing control functions based on the data processing results. …”
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Automated orthodontic diagnosis via self-supervised learning and multi-attribute classification using lateral cephalograms by Qiao Chang, Yuxing Bai, Shaofeng Wang, Fan Wang, Shuang Liang, Xianju Xie

“…Abstract Background Malocclusion, characterized by dental misalignment and improper occlusal relationships, significantly impacts oral health and daily functioning, with a global prevalence of 56%. Lateral cephalogram is a crucial diagnostic tool in orthodontic treatment, providing insights into various structural characteristics. …”
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Detecting muscle fatigue during lower limb isometric contractions tasks: a machine learning approach by Jiaqi Sun, Cheng Zhang, Guangda Liu, Wenjie Cui, Yubing Sun, Chunyan Zhang

“…The EMG signals were decomposed into multiple intrinsic mode functions (IMFs) using improved complementary ensemble empirical mode decomposition adaptive noise (ICEEMDAN). …”
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A Holistic Approach to Enhance Learning Experiences for People With Hearing Disabilities in Online and Traditional Classroom Settings by Mario Perez-Enriquez, Jose Luis Lopez-Cuadrado, Israel Gonzalez-Carrasco

“…This paper presents an integral framework for hybrid and online learning environments that provides different functionalities to address the diverse needs of students with disabilities in educational environments. …”
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Scientific Machine Learning for Elastic and Acoustic Wave Propagation: Neural Operator and Physics-Guided Neural Network by Nafisa Mehtaj, Sourav Banerjee

“…Scientific machine learning (SciML) offers an emerging alternative to the traditional modeling approaches for wave propagation. …”
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Hierarchical Information-Extreme Machine Learning of Hand Prosthesis Control System Based on Decursive Data Structure by Anatolii Dovbysh, Vladyslav Piatachenko, Mykyta Myronenko, Mykyta Suprunenko, Julius Simonovskiy

“…The article considers the machine learning method for a hand prosthesis control system that recognizes electromyographic signals with a non-invasive recording system. …”
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Nerve growth factor: what can surgeons and oncologists learn from a neurological and psychological biomarker? by Fei Xiong, Ben-li Xiao, Qi Wang, Kun Liu, Hong-wei Wu, Chao Jing, Kui-nan Tong, Zhong-tao Zhang, Wei Guo

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Development of the Mbojo Culinary Application in Local Content Learning to Improve Students' Knowledge of Bima Traditional Cuisine by Laudiya Centiya Della, Mariamah Mariamah, Hardiansyah Hardiansyah

“…This research was motivated by the low level of students' knowledge of Bima traditional cuisine due to the limited availability of interactive and engaging learning media. This research aims to develop the Mbojo Culinary Application in local content learning to improve students' knowledge of Bima traditional cuisine is to produce a learning medium that is valid, effective, and practical in supporting the learning process of elementary school students.This research used the Research and Development (R&D) method using the ADDIE model (Analysis, Design, Development, Implementation, eval_uation) and a mixed methods approach. …”
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An ensemble deep learning framework for multi-class LncRNA subcellular localization with innovative encoding strategy by Wenxing Hu, Yan Yue, Ruomei Yan, Lixin Guan, Mengshan Li

“…Abstract Background Long non-coding RNA (LncRNA) play pivotal roles in various cellular processes, and elucidating their subcellular localization can offer crucial insights into their functional significance. Accurate prediction of lncRNA subcellular localization is of paramount importance. …”
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Investigating the Machining Behavior of the Additively Manufactured Polymer-Based Composite Using Adaptive Neuro-Fuzzy Learning by Anastasios Tzotzis, Dumitru Nedelcu, Simona-Nicoleta Mazurchevici, Panagiotis Kyratsis

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Using machine learning to predict anesthetic dose in fish: a case study using nutmeg oil by Mert Minaz, Cem Alparslan, Akif Er

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Comparison of Machine Learning and Classic Methods on Aerodynamic Modeling and Control Law Design for a Pitching Airfoil by Lang Yan, Xinghua Chang, Nianhua Wang, Laiping Zhang, Wei Liu, Xiaogang Deng

“…To conduct this, a modified NACA0012 airfoil with a tail functioning as an elevator is employed as the geometry model. …”
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Evaluating visitor perception and spatial preferences of various museums based on machine learning from 2016 to 2024. by Yuandi Jiang, Kalyna Pashkevych, Shibo Bi

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A Study of Deep Learning Models for Audio Classification of Infant Crying in a Baby Monitoring System by Denisa Maria Herlea, Bogdan Iancu, Eugen-Richard Ardelean

“…By comparing the performance of different machine learning algorithms, this study seeks to determine the most effective approach for the detection of infant crying, enhancing the functionality of baby monitoring systems and contributing to a more advanced understanding of audio-based deep learning applications. …”
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Beacon2Science: Enhancing STEREO/HI Beacon Data With Machine Learning for Efficient CME Tracking by J. Le Louëdec, M. Bauer, T. Amerstorfer, J. A. Davies

“…We then increase the time resolution of enhanced beacon images through learned interpolation to match science data's 40‐min resolution. …”
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The chronODE framework for modelling multi-omic time series with ordinary differential equations and machine learning by Beatrice Borsari, Mor Frank, Eve S. Wattenberg, Ke Xu, Susanna X. Liu, Xuezhu Yu, Mark Gerstein

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