Taxonomy of Teaching Methods and Teaching Forms for Youth in Non-Formal Education in the National Youth Council of Slovenia by Vesna Miloševič Zupančič

“…Problem-based learning, case-study method, action learning, and project-based learning are intertwined and connected to the experiential learning method. Other methods include verbal-textual methods, illustrative-demonstration methods, experimental methods, peer learning, and support methods. …”
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Desentiment: A New Method to Control Sentimental Tendency During Summary Generation by Hongyu Cao, Jinlong Li

“…Due to a scarcity of labeled data for sentiment-supervised summarization, we utilize sentiment sentences from original texts as positive samples in the training process, augmented with a prompt learning method. Our method achieves a better result on the CNN/DailyMail and XSum datasets regarding sentiment scores and has a small influence on the semantic information of summaries. …”
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Metode Pembelajaran Bahasa Arab (Studi Kasus di Pondok Modern Zam-Zam Muhammadiyah Cilongok Banyumas) by Kusnan Kusnan

“…Communicative Problem-Based Learning Method, Audiolingual Method, and Grammar-Translation Method. …”
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Developing Inclusive Learning Environments : Collaborative Learning Innovations for Students with Disabilities in Higher Education by Nisak Ruwah Ibnatur Husnul, Nani Rusnaeni

“…This research aims to develop of an inclusive learning environment for students with physical disabilities through learning innovations using collaborative learning methods. The method of research used is research and development (R&D), with the ADDIE model research design, which consists of five stages: analysis, design, development, implementation and evaluation. …”
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DEVELOPMENT OF STUDENTS’ LEARNING ACTIVITY THROUGH TEACHING CHEMISTRY by Marat Akhmetov

“…There is difference between terms “cognitive strategy” and «learning method”. “Learning method” is a particular way of studying. …”
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Isfahan Artificial Intelligence Event 2023: Lesion Segmentation and Localization in Magnetic Resonance Images of Patients with Multiple Sclerosis by Fariba Davanian, Iman Adibi, Mahnoosh Tajmirriahi, Maryam Monemian, Zahra Zojaji, Ahmadreza Montazerolghaem, Mohammad Amin Asadinia, Seyed Mojtaba Mirghaderi, Seyed Amin Naji Esfahani, Mohammad Kazemi, Mohammad Reza Iravani, Kian Shahriari, Nesa Sharifi, Sadaf Moharreri, Farnaz Sedighin, Hossein Rabbani

“…Most of the teams preferred to use deep learning methods. The methods varied from a simple U-net structure to more complicated networks. …”
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Evaluation of MBKM Program Implementation in Elementary Schools by Priyono Tri Febrianto, Irena Yolanita Maureen, Bachtiar Sjaiful Bachri

“…This study concludes that schools and teachers can optimize learning innovations by using various methods adapted to the student's environment, such as; applying student center learning learning methods, exposition discovery learning methods, individual group learning methods, brainstorming methods, blended learning, and other methods that can improve students' skills and creativity, by implementing fun teaching and learning programs.…”
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Robust low frequency seismic bandwidth extension with a U-net and synthetic training data by P. Zwartjes, J. Yoo

“…Instead, our synthetic training data is created from individual randomly perturbed events with variations in bandwidth, making it more adaptable to different data sets compared to previous deep learning methods. The method was tested on both synthetic and real seismic data, demonstrating effective low frequency reconstruction and sidelobe reduction. …”
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Expression Recognition Algorithm of Deeply Separable Residual Network under Joint Loss by LI Jingyu, CHENG Weiyue, LIN Kezheng, MIAO Zhuang, LI Ao

“… In order to enhance the feature extraction ability of neural network and further improve the accuracy of facial expression recognition, this paper proposes a deep separable residual network model under joint loss DSResNet-Jloss.This network is a lightweight network model based on deep separable convolution and residual learning methods.The method of channel-by-channel convolution and point-by-point convolution is used to replace the conventional convolution operation, which solves the problems of traditional convolutional neural network with large parameter redundancy, long training time, slow convergence, and easy overfitting.And add residual unit to the network, use shortcut connection, through identity mapping, to solve the problem of gradient explosion or attenuation caused by too many layers of the network model.A joint loss function is proposed, which fully combines the advantages of cross-entropy loss, center loss and contrast loss to reduce the intra-class distance of expression features and increase the inter-class distance.Experiments show that the model has achieved good results on the two public data sets of FERPlus and RAF-DB, showing good generalization ability and robustness.…”
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Applied Koopman Theory for Partial Differential Equations and Data-Driven Modeling of Spatio-Temporal Systems by J. Nathan Kutz, J. L. Proctor, S. L. Brunton

“…Judiciously chosen observables lead to physically interpretable spatio-temporal features of the complex system under consideration and provide a connection to manifold learning methods. Our method provides a valuable intermediate, yet interpretable, approximation to the Koopman operator that lies between the DMD method and the computationally intensive extended DMD (EDMD). …”
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Improving Learning and Teaching Methods Using Chatgpt in Higher Education: A Case Study of IBB University by Muneer Alsurori, Ayedh Abdulaziz Mohsen, Hezam Gawbah, Soliman Albaraky, Shaima Abdulkreem

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Multi-Agent Hierarchical Graph Attention Actor–Critic Reinforcement Learning by Tongyue Li, Dianxi Shi, Songchang Jin, Zhen Wang, Huanhuan Yang, Yang Chen

“…To address the issues of complex information interaction and model scalability, we propose an innovative hierarchical graph attention actor–critic reinforcement learning method. This method naturally models the interactions within a multi-agent system as a graph, employing hierarchical graph attention to capture the complex cooperative and competitive relationships among agents, thereby enhancing their adaptability to dynamic environments. …”
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Artificial Intelligence for the Foreign Language Classes at Higher Education Institution by Julia E. Valkova

“…The theoretical significance of the work lies in the description of AI tools for classroom and autonomous language learning. Methods. The methods of the work include bibliographic analysis of publications on the research topic and an experiment on the introduction of AI tools into foreign language classes during 2022–2024. …”
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TRAINING OF KAHOOT! AS AN INTERACTIVE GAME-BASED LEARNING EVALUATION PLATFORM FOR STUDENTS by Army Justitia, Badrus Zaman, Rimuljo Hendradi, Fitri Retrialisca, Roslinda Salim

“…Objective: This community service aims to improve the skills of teachers / educators to provide interactive learning and evaluation media based on game learning. Methods: The methods used in this community service activity were training and focus group discussions. …”
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Cross-Scale Guidance Integration Transformer for Instance Segmentation in Pathology Images by Yung-Ming Kuo, Jia-Chun Sheng, Chen-Hsuan Lo, You-Jie Wu, Chun-Rong Huang

“…<italic>Results:</italic> Compared with recent task-specific deep learning methods, our method can achieve state-of-the-art performance in two public gland cell datasets. …”
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Software complex for simulation modelling of single nucleotide genetic polymorphism sites by M. M. Yatskou, D. D. Sarnatski, V. V. Skakun, V. V. Grinev

“…A software complex has been developed for simulation modelling and identification of single nucleotide polymorphism sites using machine learning methods. The methods for the approach to simulation modelling and analysis of single nucleotide polymorphism sites in DNA molecules are implemented based on the beta or normal distributions, the parameters of which are determined from the available experimental data, and machine learning models trained on simulated data and used to accurately identify single nucleotide polymorphism sites. …”
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Illuminant estimation method based on Color Lines and dichroic reflection model by Soshun Muto, Mashiho Mukaida, Noriaki Suetake

“…Various methods for illuminant estimation have been proposed, including hypothesis based approaches, deep learning methods, and methods based on the dichroic reflection model. …”
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Fault Recognition Method and Application Based on Generative Adversarial Network by Shuiliang Luo, Yongmei Huang, Yun Su, Shengkui Wang, Qianqian Liu, Yingqiang Qi, Fuhao Chang

“…The experimental results show that compared with the traditional deep learning method, this method shows significant advantages in fault recognition. …”
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Establishment and comparison of prediction models for early-stage diabetic kidney disease by Yingda Sheng, Jianguo Cheng, Caimei Zhang, Feifei Ma, Qian Xiao, Dan Wang, Jianwen Zhang, Xiaoqin Ha

“…A first-stage study is conducted on how successful conventional statistical models (CSMs) perform when sample sizes are small when compared to machine learning methods (MLMs). Methods A total of 268 observations were collected from two tertiary hospitals in Lanzhou with demographic information, basic medical history, and routine laboratory tests such as blood routine, common biochemical tests, and urine routine. …”
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Damage Identification of Conduit Rack in Offshore Platform Structures Based on a Novel Composite Neural Network by Jiaqiang Yan, Yuanchao Qiu, Renhe Shao, Ziqiao Ling, Ruixiang Zhang

“…Experimentally validated by finite element model simulation and testbed construction, our proposed NRBO-TCN-BiLSTM combined neural network damage identification accuracy is as high as 99 % on average, exceeding existing deep learning methods. The method has a wide range of applications in SHM for offshore platforms.…”
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