Integrating Hybrid Team-Based and Case-Based Learning in Dental Education Transformation by Sidra Abid, Humna Rafiq

“…In this vein the combination of CBL and TBL at tertiary level contributes to the improvement of students` academic performance and engagement so the hybrid form of CBL and TBL is qualified to narrow the gap between secondary and higher educational systems creating active learning and positive social interdependence1 and this means that this tactic allows students not only to participate in the topic fully, but also to encourage ethical-based decision- making.2  Hybrid TBL is the method where students learn all concepts of their studies in a way that students are really being engaged. …”
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A diagnosis method based on graph neural networks embedded with multirelationships of intrinsic mode functions for multiple mechanical faults by Bin Wang, Manyi Wang, Yadong Xu, Liangkuan Wang, Shiyu Chen, Xuanshi Chen

“…To address the limitations of existing methods, we propose a fault diagnosis method based on graph neural networks (GNNs) embedded with multirelationships of intrinsic mode functions (MIMF). …”
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Path Planning Method of Mobile Robot Using Improved Deep Reinforcement Learning by Wei Wang, Zhenkui Wu, Huafu Luo, Bin Zhang

“…A mobile robot path planning method based on improved deep reinforcement learning is proposed. …”
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Implementation of home visit method in offline learning during the Covid-19 pandemic by Benjamin Metekohy, Novita Sahertian, David Ming

“…What is the home visit method in offline learning? Is the Home visit method an alternative to learning during the Covid-19 pandemic? …”
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A Deep Learning Method for Automatic Coronal Mass Ejection Feature Identification by P. Yang, H. S. Fu, J. B. Cao, F. Shen

“…Here, we present a deep learning–based algorithm for automated CME feature extraction, comprising four key stages: image preprocessing, segmentation, tracking, and feature extraction. …”
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Comprehensive evaluation of U-Net based transcranial magnetic stimulation electric field estimations by Taylor A Berger, Kathleen Mantell, Zachary Haigh, Nipun Perera, Ivan Alekseichuk, Alexander Opitz

“…Deep learning (DL) methods, particularly U-Nets, are being investigated for TMS electric field estimations. …”
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Mobile Robot Positioning with Wireless Fidelity Fingerprinting and Explainable Artificial Intelligence by Hüseyin Abacı, Ahmet Çağdaş Seçkin

“…In addition, unlike the Global Navigation Satellite System (GNSS), Wi-Fi is more suitable for use indoors because signal blocking, attenuation, and reflection restrictions create a unique pattern in places with many Wi-Fi transmitters, and more precise positioning can be performed than GNSS. This paper proposes a machine learning-based method for Wi-Fi-enabled robot positioning in indoor environments. …”
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Using Life’s Essential 8 and heavy metal exposure to determine infertility risk in American women: a machine learning prediction model based on the SHAP method by Xiaoqing Gu, Qianbing Li, Xiangfei Wang

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An Investigation of the Flipped Learning Method to Physical Education Classes in the University: Systematic Review by Procopio B. Dafun Jr., Nurhasan Nurhasan, Heryanto Nur Muhammad, Dyah Fitria Padmasari, Novadri Ayubi

“…In all aspects of learning such as cognitive, affective and motoric learning in several sports disciplines such as basketball, martial arts, gymnastics and dance, FL provides very positive results. …”
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Application of Emerging Teaching Models in Dental Education: A Systematic Review and Meta-Analysis by Xuefei Pang, Ling Li, Xu Liu, Yan Wang, Bo Yang

“…Introduction and aims: As an experimental teaching method, emerging learning methods including problem-based learning (PBL), case-based learning, team-based learning and flipped classroom (FC) have been widely applied in dental education. …”
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A facial structure sampling contrastive learning method for sketch facial synthesis by Kangning Du, Jiyu Zhang, Lin Cao, Yanan Guo, Wenwen Sun

“…However, when applying traditional contrastive learning to sketch face synthesis, the random sampling strategy and the imbalance between positive and negative samples result in poor performance of synthesized sketch images regarding local details. …”
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Initiating a Full Fulfilment Curriculum-Based Deep Learning: Integration of Knowledge and Character in Learning by Aulia Fitri, Khairul Amin, Zuhri Tauhid, Aulia Ramadona, Wismanto

“… An effective educational curriculum must integrate the development of students' knowledge and character, especially for facing the challenges of the modern era. Based on these needs, the full fulfilment curriculum was developed to combine aspects of academic knowledge with character formation through deep learning approaches, namely Mindful Learning, Meaningful Learning, and Joyful Learning. …”
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Ubiquitous UWB Ranging Error Mitigation With Application to Infrastructure-Free Cooperative Positioning by Maija Makela, Martta-Kaisa Olkkonen, Martti Kirkko-Jaakkola, Toni Hammarberg, Tuomo Malkamaki, Jesperi Rantanen, Sanna Kaasalainen

“…This ranging error can be corrected with machine learning (ML) methods, such as convolutional neural networks (CNNs). …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…In UWB-based indoor positioning research, NLOS signals severely degrade localization accuracy. …”
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Overcoming Challenges and Promoting Positive Education in Inclusive Schools: A Multi-Country Study by Angel Deroncele-Acosta, Althia Ellis

“…The results identified eight persistent challenges to inclusive education. In addition, positive education was highlighted as the fundamental core of inclusive schools, with emphasis on the development of learning, well-being, engagement, resilience, motivation, mental health, affective and social outcomes, creativity, and happiness. …”
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Martian Skylight Identification Based on the Deep Learning Model by Lihong Li, Lingli Mu, Wei Zhang, Weihua Dong, Yuqing He

“…In this article, 151 positive samples and 920 negative samples based on the MRO-HiRISE image data was used to create an initial skylight dataset, which contained few positive samples. …”
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Disease candidate genes prediction using positive labeled and unlabeled instances by Sepideh Molaei, Saeed Jalili

“…Notably, there is no source for the negative data set. The proposed method is a two-step process: The first step is the extraction of reliable negative genes from a set of unlabeled genes by one-class learning and a filter based on distance indicators from known disease genes; this step is performed separately for each disease. …”
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Machine learning-based optimization of photogrammetric JRC accuracy by Qinzheng Yang, Ang Li, Yipeng Liu, Hongtian Wang, Zhendong Leng, Fei Deng

“…Second, a portable positioning plate containing ground control points and checkpoints was designed based on optical principles, and a moving camera capture strategy guided by SPSA was proposed. …”
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3D Model Classification Based on Contrastive Learning by QU Zhongshui, LIU Shan, GAO Yuan, DING Bo

“…We propose a 3D model classification method based on contrastive learning. In this method, the training is divided into a sample discrimination stage and a classification stage. …”
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Sorogan-Based Learning to Stimulate Early Counting Skills by Osfir Candikia Rara Komara, Sumaji, Wahyudi, Ahmad Azzam Al Qoyyimuddin

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