Deep and Reinforcement Learning Technologies on Internet of Vehicle (IoV) Applications: Current Issues and Future Trends by Lina Elmoiz Alatabani, Elmustafa Sayed Ali, Rania A. Mokhtar, Rashid A. Saeed, Hesham Alhumyani, Mohammad Kamrul Hasan

“…In this paper, some concepts related to deep learning networks will be discussed as one of the uses of machine learning in IoV systems, in addition to studying the effect of neural networks (NNs) and their types, as well as deep learning mechanisms that help in processing large amounts of unclassified data. …”
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Students’ writing strategies in accomplishing final exams: lessons learned from an Islamic higher education institution by Siti Aisyah Pranita, Muhammad Husin Al Fatah

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Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes. by Deborah Kunkel, Peter Sørensen, Vijay Shankar, Fabio Morgante

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Impact of Simulation-Based and Flipped Classroom Learning on Self-Perceived Clinical Skills Compared to Traditional Training by Samuel Agostino, Gian Maria Cherasco, Grazia Papotti, Alberto Milan, Federico Abate Daga, Massimiliano Abate Daga, Franco Veglio

“…This quasi-experimental study examines how a combined approach—flipped classroom learning and simulation-based internships—affects medical students’ self-assessed clinical abilities. …”
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A novel machine learning methodology for the systematic extraction of chronic kidney disease comorbidities from abstracts by Eszter Sághy, Mostafa Elsharkawy, Frank Moriarty, Sándor Kovács, István Wittmann, Antal Zemplényi, Antal Zemplényi

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Digital technologies in music education. Using Digital Audio Workstations (DAW) with Project-Based Learning (PBL) by María Elena Cuenca-Rodríguez, Ignacio Pascual-Moltó, Raquel Pastor-Prada

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Profundización del profesorado español en flipped learning según el nivel de competencia digital by Jesús LÓPEZ BELMONTE, Santiago POZO SÁNCHEZ, Santiago ALONSO GARCÍA

“…Se concluye que la proyección del flipped learning aún no es determinante pues la cifra de docentes que utilizan tales recursos como explicación en medios digitales no es significativa.…”
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What’s in, and what’s out? A study of student choice of learning activities in a flipped EFL classroom by Shen Yan

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GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images by Sonam Aggarwal, Isha Gupta, Ashok Kumar, Sandeep Kautish, Abdulaziz S. Almazyad, Ali Wagdy Mohamed, Frank Werner, Mohammad Shokouhifar

Subjects: “…deep learning…”
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A Framework for Promoting Passive Breast Cancer Monitoring: Deep Learning as an Interpretation Tool for Breast Thermograms by Mohamad Firouzmand, Keivan Majidzadeh, Maryam Jafari, Shahpar Haghighat, Rezvan Esmaeili, Leila Moradi, Nima Misaghi, Mahsa Ensafi, Fatemeh Batmanghelich, Mohammadreza Keyvanpour, Seyed Vahab Shojaedini

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Research on noise-induced hearing loss based on functional and structural MRI using machine learning methods by Minghui Lv, Liping Wang, Ranran Huang, Aijie Wang, Yunxin Li, Guowei Zhang

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Ignition delay prediction for fuels with diverse molecular structures using transfer learning-based neural networks by Mo Yang, Dezhi Zhou

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Machine Learning and hybrid models for assessing climate change impacts on runoff in the Kasilian catchment, Northern Iran by Farhad Hajian, Hossein Monshizadeh Naeen

“…Furthermore, hybrid models, integrating HEC-HMS with GEP and HEC-HMS with ANN, exhibited superior performance compared to individual machine learning (ML) or HEC-HMS models. Input variables (temperature and rainfall) were generated using LARS-WG software, incorporating five climate models and the SSP585 scenario for future climate change studies. …”
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A Novel MoCo-Based Self-Supervised Learning Framework for Solar Panel Defect Detection by Jun Huang, Shamsul Arrieya Ariffin, Yongqiang Chen, Jinghui Lin, Wanting Xu

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Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study by Xiaojuan Xiong, Hong Fu, Bo Xu, Wang Wei, Mi Zhou, Peng Hu, Yunqin Ren, Qingxiang Mao

“… BackgroundRecent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. …”
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Metode Deteksi Intrusi Menggunakan Algoritme Extreme Learning Machine dengan Correlation-based Feature Selection by Sulandri Sulandri, Achmad Basuki, Fitra Abdurrachman Bachtiar

“…The method used to do intrusion detection by classification is using the Extreme Learning Machine (ELM) method. However, using the ELM method alone is not able to produce good accuracy, so the ELM method needs to be added to the Correlation-Based Feature Selection (CFS) feature selection method to improve the accuracy and computational time. …”
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Decoding Consumer Behavior in the Used Car Market: A Machine Learning Approach to Key Decision Factors by Zhang Minshun

“…The focus is on how online and offline trading platforms affect purchasing behavior. Using machine learning techniques, the paper compares multiple models to predict key purchase factors and visualize the data through various graphs. …”
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The effect of interactive learning on nutritional knowledge among teachers, parents and students at primary schools in Central Java by Rachmawati Emma, Umniyatun Yuyun, Iqbal Nurmansyah Mochamad, Hidayati, Kharisma Saraswati Lia, Sahidin Didin, Sulistio Gohardi Virgo, Wulandari Eka

“…Apart from interactive games, the lecture method can also be used to emphasize several important points during learning.…”
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Evaluation of Students' Use of Visual Learning Representations in Science Classes: A Case Study from Turkey by Tufan Inaltekin, Volkan Goksu

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PLncWX: A Machine-Learning Algorithm for Plant lncRNA Identification Based on WOA-XGBoost by Fei Guo, Zhixiang Yin, Kai Zhou, Jiasi Li

“…There have been a large number of identification tools based on machine-learning and deep learning algorithms, mostly using human and mouse gene sequences as training sets, seldom plants, and only using one or one class of feature selection methods after feature extraction. …”
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