Constructing segmentation method for wheat powdery mildew using deep learning by Hecang Zang, Hecang Zang, Congsheng Wang, Qing Zhao, Qing Zhao, Jie Zhang, Jie Zhang, Junmei Wang, Guoqing Zheng, Guoqing Zheng, Guoqiang Li, Guoqiang Li

“…Compared with other mainstream deep learning methods U-Net, PSPNet, DeepLabV3+, and Swin-Unet, the proposed RSE Swin-Unet method can detect wheat powdery mildew and stripe rust image in a challenging situation and has good computer vision processing and performance evaluation effects. …”
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THE USE OF PROJECT BASED LEARNING METHOD IN DEVELOPING STUDENTS' CRITICAL THINKING by Iskandar Iskandar, Sri Mulyati

“…This research aims to determine the difference of students' critical thinking ability between class which get Project Based Learning (PjBL) method and expository method. The method use experimental method with factorial design 2x2. …”
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The classification method of donkey breeds based on SNPs data and machine learning by Dekui Li, Dekui Li, Xiaolong Hu, Yongdong Peng

“…A method for accurately classifying donkey breeds has been developed by integrating single nucleotide polymorphism (SNPs) data with machine learning algorithms. …”
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The Effectiveness of Grammatical Hunting Game Method Students’ Arabic Learning Motivation by Muhammad Jafar Shodiq, Zaimatuz Zakiyah, Zainal Abidin Hajib

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Transmission Lines Insulator State Detection Method Based on Deep Learning by Xu Tan, Shiying Hou, Fan Yang, Zhimin Li

“…Therefore, to achieve automation in insulator state detection, this paper proposes a method based on deep learning for insulator state detection in transmission lines. …”
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Benchmark dataset and deep learning method for global tropical cyclone forecasting by Cheng Huang, Pan Mu, Jinglin Zhang, Sixian Chan, Shiqi Zhang, Hanting Yan, Shengyong Chen, Cong Bai

“…Comprehensive evaluations demonstrate that TCN M outperforms both existing deep learning methods and official meteorological forecasts across multiple metrics. …”
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Strain perturbation method for atomic stress calculation with machine-learning potentials by Suyue Yuan, Kwangnam Kim, Bo Wang, Wonseok Jeong, Tae Wook Heo, Brandon C. Wood, Liwen F. Wan

“…Accurate computation of local atomic virial stress is crucial for predicting materials’ mechanical response in large-scale molecular dynamic simulations, but conventional methods struggle with high-order atomic environment descriptors' encoded machine-learning many-body potentials. …”
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Case method textbook innovation for Autodesk inventor- assisted CAM learning by Elfahmi Dwi Kurniawan, Nopriyanti Nopriyanti, Rudi Hermawan, Patterson Nji Mbakwa, Abi Pratama, Rianto Rianto, Febriansyah Febriansyah, Putri Indah Yanti

“…This textbook, which was systematically designed according to the students' characteristics and learning strategies and integrates Autodesk Inventor and Case Method teaching materials, is expected to bridge the theory-practice gap and improve students' technological literacy critically and creatively.…”
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Deep learning method for finding eigenpairs in Sturm-Liouville eigenvalue problems by Sen Zhang, Jian Zu, Jingqi Zhang

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Implementation of the Tahqiq Method in Learning the Qur'an at the Nurul Ummah International Madrasah by Rahmat Rahmat, Novy Setia Yunas, Fachrurazi Fachrurazi

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Road-Adaptive Precise Path Tracking Based on Reinforcement Learning Method by Bingheng Han, Jinhong Sun

“…This paper proposes a speed-adaptive autonomous driving path-tracking framework based on the soft actor–critic (SAC) and pure pursuit (PP) methods, named the SACPP controller. The framework first analyzes the obstacles around the vehicle and plans an obstacle-free reference path with the minimum curvature using the hybrid A* algorithm. …”
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Edge computing privacy protection method based on blockchain and federated learning by Chen FANG, Yuanbo GUO, Yifeng WANG, Yongjin HU, Jiali MA, Han ZHANG, Yangyang HU

“…Aiming at the needs of edge computing for data privacy, the correctness of calculation results and the auditability of data processing, a privacy protection method for edge computing based on blockchain and federated learning was proposed, which can realize collaborative training with multiple devices at the edge of the network without a trusted environment and special hardware facilities.The blockchain was used to endow the edge computing with features such as tamper-proof and resistance to single-point-of-failure attacks, and the gradient verification and incentive mechanism were incorporated into the consensus protocol to encourage more local devices to honestly contribute computing power and data to the federated learning.For the potential privacy leakage problems caused by sharing model parameters, an adaptive differential privacy mechanism was designed to protect parameter privacy while reducing the impact of noise on the model accuracy, and moments accountant was used to accurately track the privacy loss during the training process.Experimental results show that the proposed method can resist 30% of poisoning attacks, and can achieve privacy protection with high model accuracy, and is suitable for edge computing scenarios that require high level of security and accuracy.…”
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Optimization method of electric vehicle energy system based on machine learning by Huanmei Ren

“…IntroductionTo enhance energy management in electric vehicles (EVs), this study proposes an optimization model based on reinforcement learning.MethodsThe model integrates gated recurrent units (GRU) with double deep Q-networks (DDQN) to improve time-series data processing and action value estimation.ResultsResults show that the model achieves the lowest estimation bias (0.017 in training, 0.018 in testing) and the highest cumulative reward (97.1) among all compared methods. …”
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A Method for the Automatic Selection of Training Tasks in Learning Environment for IT Students by S. U. Rzheutskaya, M. V. Kharina

“…Methods and materials. The article provides a distinction between the concepts of complexity, difficulty, and the learning effect of training tasks. …”
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Intelligent monitoring method for conveyor belt misalignment based on deep learning by ZUO Mingming, ZHANG Xi, YANG Zihao, SUN Qifei, ZHANG Mengchao, ZHANG Yuan, LI Hu

“…This paper proposed an intelligent monitoring method for conveyor belt misalignment based on deep learning. …”
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Faulty Links’ Fast Recovery Method Based on Deep Reinforcement Learning by Wanwei Huang, Wenqiang Gui, Yingying Li, Qingsong Lv, Jia Zhang, Xi He

“…Aiming to address the high recovery delay and link congestion issues in the communication network of Wide-Area Measurement Systems (WAMSs), this paper introduces Software-Defined Networking (SDN) and proposes a deep reinforcement learning-based faulty-link fast recovery method (DDPG-LBBP). …”
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Machine learning with analysis-of-variance-based method for identifying rice varieties by Nabin Kumar Naik, M. Venkata Subbarao, Prabira Kumar Sethy, Santi Kumari Behera, Gyana Ranjan Panigrahi

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Image Characteristic-Guided Learning Method for Remote-Sensing Image Inpainting by Ying Zhou, Xiang Gao, Xinrong Wu, Fan Wang, Weipeng Jing, Xiaopeng Hu

“…Since RSIs contain complex land structure features and concentrated obscured areas, existing inpainting methods often produce color inconsistency and structural smoothing when applied to RSIs with a high missing ratio. …”
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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

“…This study evaluates a method of learning skull anatomy and improving three-dimensional comprehension through systematic drawings. …”
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A Machine Learning Method for Monte Carlo Calculations of Radiative Processes by William Charles, Alexander Y. Chen

“…In particular, we apply our technique to inverse Compton radiation and find that our ML method can be up to an order of magnitude faster than traditional methods currently in use.…”
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