Normal and slow learners: a new discriminative method based on the speed of spatial learning in aged mice by Céline Duffau, Senka Hadzibegovic, Senka Hadzibegovic, Vojislav Andelkovic, Vojislav Andelkovic, Bruno Bontempi, Bruno Bontempi, Olivier Nicole, Olivier Nicole

“…SL mice demonstrated significantly delayed spatial memory acquisition compared to NL and young mice, suggesting pronounced heterogeneity in cognitive aging. This method provides a robust framework to explore the neurobiological underpinnings of learning deficits and may inform the development of targeted interventions to mitigate age-related memory decline.…”
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Hydraulic Pump Fault Diagnosis Method Based on EWT Decomposition Denoising and Deep Learning on Cloud Platform by Wanlu Jiang, Zhenbao Li, Sheng Zhang, Teng Wang, Shuqing Zhang

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Research on Iterative Learning Method for Lower Limb Exoskeleton Rehabilitation Robot Based on RBF Neural Network by Jing Li, Huimin Jiang, Moyao Gao, Shuang Li, Zhanli Wang, Zaixiang Pang, Yang Zhang, Yang Jiao

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Machine Learning Strategy to Achieve Maximum Energy Harvesting and Monitoring Method for Solar Photovoltaic Panel Applications by Bibhu Prasad Ganthia, Sudheer Hanumanthakari, Hemachandra Gudimindla, Harishchander Anandaram, M. Siva Ramkumar, Monalisa Mohanty, S. Raja Gopal, Atul Sarojwal, Kibrom Menasbo Hadish

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A soil organic carbon mapping method based on transfer learning without the use of exogenous data by Jingfeng Han, Mujie Wu, Yanlong Qi, Xiaoning Li, Xiao Chen, Jing Wang, Jinlong Zhu, Qingliang Li

“…Accurate and cost-effective mapping of soil organic carbon (SOC) is critical for understanding carbon dynamics and informing sustainable land management. Although deep learning-based methods have demonstrated strong potential in digital soil mapping, they typically require large amounts of data. …”
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Continuous professional development and instructors’ beliefs about and practice of active learning method in Bahir Dar university by Mulugeta Teka Kahsay

“…They responded to a questionnaire having two parts: beliefs about active learning methods and application of active learning methods. …”
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An Optimization Method for Green Permutation Flow Shop Scheduling Based on Deep Reinforcement Learning and MOEA/D by Yongxin Lu, Yiping Yuan, Adilanmu Sitahong, Yongsheng Chao, Yunxuan Wang

“…This paper addresses the green permutation flow shop scheduling problem (GPFSP) with energy consumption consideration, aiming to minimize the maximum completion time and total energy consumption as optimization objectives, and proposes a new method that integrates end-to-end deep reinforcement learning (DRL) with the multi-objective evolutionary algorithm based on decomposition (MOEA/D), termed GDRL-MOEA/D. …”
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Publisher Correction: The intelligent fault identification method based on multi-source information fusion and deep learning by Dashu Guo, Xiaoshuang Yang, Peng Peng, Lei Zhu, Handong He

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deep-Sep: a deep learning-based method for fast and accurate prediction of selenoprotein genes in bacteria by Yao Xiao, Yan Zhang

“…We have developed a deep learning-based algorithm to predict selenoprotein genes in bacterial genomic sequences, which demonstrates superior performance compared to currently available methods. …”
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scSMD: a deep learning method for accurate clustering of single cells based on auto-encoder by Xiaoxu Cui, Renkai Wu, Yinghao Liu, Peizhan Chen, Qing Chang, Pengchen Liang, Changyu He

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Effectiveness of the flipped classroom versus the traditional teaching method in enhancing learning among undergraduate medical students by Dipti Mohapatra, Arati Meher, Prakash Kumar Sahoo, Tapaswini Mishra, Arati Mohanty

“…Results: The result showed a significant improvement in the post-test marks for both the teaching learning methods. However, the flipped classroom groups outperformed the didactic groups, with mean post-test scores of 82.2 (10.8) and 84.2 (10.3) for the <50% and ≥50% groups, respectively, compared to 63.2 (9.4) and 72.4 (14.9) for the traditional groups, with a P <0.001. …”
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A Deep Learning-Driven Black-Box Benchmark Generation Method via Exploratory Landscape Analysis by Haoming Liang, Fuqing Zhao, Tianpeng Xu, Jianlin Zhang

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A low-cost IoT-based deep learning method of water gauge measurement for flood monitoring by Leila Hashemi-Beni, Megha Puthenparampil, Ali Jamali

“…An automated and immediate water stage estimate is provided by this simple, low-cost method. The methodology’s applicability to water resource management systems and flood disaster prevention engineering opens up new possibilities for the deployment of intelligent IoT-based flood monitoring systems in the future.…”
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The Effect of Focus Group Discussion Learning Method on Cognitive Ability and Cooperation Skills of Students on Redox Material by Vivin Fasihatul Harfiah, Setia Rahmawan

“…This research was motivated by the misconceptions about teacher learning methods in chemistry subjects. This study aims to determine the effect of Focus Group Discussion method on cognitive abilities and cooperation skills of students on redox material. …”
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E-learning Method and University Life of Married Female Students in Patriarchal Social Structure in Sociological Perspective by Shukra Raj Adhikari, Bhawani Shankar Adhikari, Ganga Acharya

Subjects: “…education, e-learning method, gender, patriarchal social structure, married female student…”
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Deep Learning Based 3D Visualization Health Condition Monitoring Method for Anchor Digging Machines by YANG Xueqi, GAO Xinqin, ZHENG Haiyang, YANG Jun

“…This study integrates deep learning and 3D visualization technology, designs a comprehensive health monitoring system framework, and proposes a health monitoring method for anchor digging machines.MethodsBased on deep learning, a data-driven remaining useful life (RUL) prediction method was proposed for key components of anchor digging machines. …”
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A 7T MRI-Guided Learning Method for Automatic Hippocampal Subfield Segmentation on Routine 3T MRI by Linjin Wang, Jiangtao He, Guohong Geng, Lisha Zhong, Xinwei Li

“…Our method was validated on PAIRED 3T-7T HIPPOCAMPAL SUBFIELD DATASET, and the experimental results demonstrate that GLNet outperforms other competitive methods.…”
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Identification and Forecasting of Key Influencing Factors in China’s Agricultural Carbon Emissions: Based on Machine Learning Method by Juntong Liu, Xiong Peng, Malan Huang, Yuzhou Ma, Cancan Jiang, Wanling Hu, Jinxin Zhang

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Automatic identification of slip pathways in ductile inorganic materials by combining the active learning strategy and NEB method by Jun Luo, Tao Fan, Jiawei Zhang, Pengfei Qiu, Xun Shi, Lidong Chen

“…Our computational approach consists of two key stages: first, an active learning strategy is utilized to efficiently and accurately model the interlayer slip potential energy surfaces; second, the climbing image nudged elastic band method is employed to identify minimum energy pathways, followed by comparative analysis to determine the final slip pathway. …”
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Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning by Yanzi Li, Cai Chen, Fuqiang Liu, Jian Wang

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