Learning needs of Comprehensive General Medicine Specialists for the care of suicidal behavior by Dinorah Janet Torres Lugo, Mabel Rocha Vázquez, Idalberto Amado Pérez López, Iván Castillo Ledo, Antonio Masot Rangel, Silvia Janet Masó Torres

“…However, it is noted that there are learning needs for its care by specialists in Comprehensive General Medicine.…”
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Policy design labs and uncertainty: can they innovate, and retain and circulate learning? by Jenny M. Lewis

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Deep learning for cyber threat detection in IoT networks: A review by Alyazia Aldhaheri, Fatima Alwahedi, Mohamed Amine Ferrag, Ammar Battah

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Student’s Perception of their Learning Approach and Relationship with Level of Engagement in Science Lessons by Nasir MAHMOOD

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On Quantum Methods for Machine Learning Problems Part I: Quantum Tools by Farid Ablayev, Marat Ablayev, Joshua Zhexue Huang, Kamil Khadiev, Nailya Salikhova, Dingming Wu

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LANGUAGE LEARNING STRATEGIES EMPLOYED BY EFL LEARNERS IN A RURAL AREA by Yanik Lailinas Sakinah, Putu Dian Danayanti Degeng, Sahiruddin Sahiruddin

Subjects: “…Language Learning Strategies…”
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Drawing as a learning tool for anatomy: design and implementation of a method. by Elena Martínez Carracelas, Miguel Ángel Fernández-Villacañas Marín, Matilde Moreno Cascales, Diego Flores Funes

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Designing a system of learning materials to explain climate change to children by Lucy Blackwell

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Plucking Point and Posture Determination of Tea Buds Based on Deep Learning by Chengju Dong, Weibin Wu, Chongyang Han, Zhiheng Zeng, Ting Tang, Wenwei Liu

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Machine learning-based spectrum occupancy prediction: a comprehensive survey by Mehmet Ali Aygül, Mehmet Ali Aygül, Hakan Ali Çırpan, Hüseyin Arslan

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Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition by Sota Nemoto, Shunsuke Kitada, Hitoshi Iyatomi

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The Application of Machine Learning for Creating a Typology of Universities' Financial Models by I. A. Khodachek, D. V. Minaev, A. V. Zinkovskaya, E. B. Yablokov

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Prediction of Fluid Viscosity in Multiphase Reservoir Oil System by Machine Learning by Lihua Shao, Ru Ji, Shuyi Du, Hongqing Song

“…This study proposed three viscosity prediction models based on machine learning approaches. The prediction accuracy comparison results show that the random forest (RF) model performs accurately in predicting the viscosity of each phase of the reservoir, with the lowest error percentage and highest R2 values. …”
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Semi-Supervised Learning With Wafer-Specific Augmentations for Wafer Defect Classification by Uk Jo, Seoung Bum Kim

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Microcluster-Based Incremental Ensemble Learning for Noisy, Nonstationary Data Streams by Sanmin Liu, Shan Xue, Fanzhen Liu, Jieren Cheng, Xiulai Li, Chao Kong, Jia Wu

“…Our approach integrates three strategies: incremental learning to monitor and adapt to concept drift; ensemble learning to improve model stability; and a microclustering procedure that distinguishes drift from noise and predicts the labels of incoming instances via majority vote. …”
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Enhancing Agricultural Productivity: A Machine Learning Approach to Crop Recommendations by Farida Siddiqi Prity, MD. Mehadi Hasan, Shakhawat Hossain Saif, Md. Maruf Hossain, Sazzad Hossain Bhuiyan, Md. Ariful Islam, Md Tousif Hasan Lavlu

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Explainable machine learning framework for cataracts recognition using visual features by Xiao Wu, Lingxi Hu, Zunjie Xiao, Xiaoqing Zhang, Risa Higashita, Jiang Liu

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Multi-task hybrid dictionary learning for vehicle classification in sensor networks by Rui Wang, Miaomiao Shen, Tao Wang, Wenming Cao

“…In this article, we propose a novel multi-task hybrid dictionary learning approach for moving vehicle classification tasks using multi-sensor networks to improve the classification accuracy in complex scenes with low time complexity, which considers both correlations and complementary information among multiple heterogeneous sensors simultaneously to learn a hybrid dictionary within observations of each sensor. …”
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Machine Learning-Based Classification of Turkish Music for Mood-Driven Selection by Nazime Tokgöz, Ali Değirmenci, Ömer Karal

“…This study seeks to employ machine learning-based methods to classify four different music genres using a minimal set of features. …”
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Social learning activities to improve community engagement in waste management program by S. Sunarti, R.S.Y. Zebua, J.H. Tjakraatmadja, A. Ghazali, B. Rahardyan, K. Koeswinarno, S. Suradi, N. Nurhayu, R.H.A. Ansyah

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