Application of the Project Based Learning Model in Natural and Social Science Subjects to Increase the Activeness of Class IV Students at SD Sumoroto 02 Ponorogo Regency by Andik Angga Vigit

“…These results indicate a significant improvement in student engagement through the implementation of the Project Based Learning model. Based on the positive student response, it can be concluded that the Project Based Learning model has been successfully implemented in IPAS instruction at the elementary school level …”
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Optimized predictive maintenance for streaming data in industrial IoT networks using deep reinforcement learning and ensemble techniques by K. Varalakshmi, J. Kumar

“…This paper introduces an ensemble-based framework combining Deep Reinforcement Learning (DRL), Random Forest (RF), and Gradient Boosting Machines (GBM) to improve fault prediction and maintenance efficiency. …”
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Intelligent Deep Learning and Keypoint Tracking-Based Detection of Lameness in Dairy Cows by Zongwei Jia, Yingjie Zhao, Xuanyu Mu, Dongjie Liu, Zhen Wang, Jiangtan Yao, Xuhui Yang

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Full Data-Processing Power Load Forecasting Based on Vertical Federated Learning by Zhengxiong Mao, Hui Li, Zuyuan Huang, Yuan Tian, Peng Zhao, Yanan Li

“…To validate the proposed method, we conducted experiments to compare centralized learning and vertical FL on several real-world datasets. …”
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Residual attention based multi-label learning for apple leaf disease identification by Changjian Zhou, Zhenyuan Zhao, Wenzhuo Chen, Yuquan Feng, Jia Song, Wensheng Xiang

“…Here, we present residual attention based multi-label learning framework (RAMDI), a method for predicting apple leaf diseases in natural environment. …”
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Deep-learning-based detection of underwater fluids in multiple multibeam echosounder data by Tyméa Perret, Gilles Le Chenadec, Arnaud Gaillot, Yoann Ladroit, Stéphanie Dupré

“…Our study investigated the use of a YOLO-based deep learning supervised approach to automate the detection of fluids emitted from cold seeps (gaseous methane) and volcanic sites (liquid carbon dioxide). …”
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Cutting Force Estimation Using Milling Spindle Vibration-Based Machine Learning by Je-Doo Ryu, Hoon-Hee Lee, Kyoung-Nam Ha, Sung-Ryul Kim, Min Cheol Lee

“…This study proposes a cost-effective alternative by estimating cutting forces using spindle vibration data through a long short-term memory (LSTM)-based machine learning model. First, the correlation between cutting force and tool wear is analyzed to emphasize the need for accurate force estimation. …”
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Research on a Joint Extraction Method of Track Circuit Entities and Relations Integrating Global Pointer and Tensor Learning by Yanrui Chen, Guangwu Chen, Peng Li

“…Next, the Tucker decomposition method is utilized to capture the semantic correlations between relations, and an Efficient Global Pointer is employed to globally predict the start and end positions of subject and object entities, incorporating relative position information through rotary position embedding (RoPE). …”
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Resilience and online learning emotional engagement among college students in the digital age: a perspective based on self-regulated learning theory by Dandan Ge

“…Abstract Background Self-efficacy perception and strategy use are two key processes for achieving self-regulated learning. Based on the perspective of self-regulated learning theory, this study explores the mediating mechanism of self-regulated learning efficacy, and strategy use (self-control and emotion regulation strategies) between resilience and online learning emotional engagement. …”
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A Delphi-based needs assessment to identify and prioritise procedural skills through consensus for simulation-based learning in neurosurgery by Adam F. Roche, Dara O. Kavanagh, Darach Crimmins, Vincent Healy, Gulam Zilani, Lars Konge, Leizl Joy Nayahangan, Danyal Z. Khan, Daniel Murray, Javier Francisco Cuello, Caitriona Cahir, Niamh Murphy, Claire M. Condron

“…This approach aimed to enhance understanding of the essential procedures that should shape a technical skills framework for neurosurgical simulation-based learning curricula. Methods We utilised a modified Delphi process and Copenhagen Academy for Medical Education and Simulation (CAMES) Needs Assessment Formula (NAF) to reach consensus. …”
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PENGARUH MODEL PROBLEM BASED LEARNING BERBANTUAN GEOGEBRA DAN TEKA TEKI SILANG (TTS) TERHADAP HASIL BELAJAR SISWA KELAS XI-4 SMA NEGERI 3 SALATIGA by Kamelia Nahar, Anna Royyana Nikmah, Kriswandani Kriswandani

“…This means that the average score after being taught using the Problem Based Learning model assisted by GeoGebra and Crossword Puzzles is better or has a positive effect compared to the average score before the model was applied. …”
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A Semantic Segmentation-Based GNSS Signal Occlusion Detection and Optimization Method by Zhe Yue, Chenchen Sun, Xuerong Zhang, Chengkai Tang, Yuting Gao, Kezhao Li

“…To address this issue, we dig into the environmental perception perspective to propose a semantic segmentation-based GNSS signal occlusion detection and optimization method. …”
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An efficient non-parametric feature calibration method for few-shot plant disease classification by Jiqing Li, Zhendong Yin, Dasen Li, Hongjun Zhang, Mingdong Xu

“…The temporal and spatial irregularity of plant diseases results in insufficient image data for certain diseases, challenging traditional deep learning methods that rely on large amounts of manually annotated data for training. …”
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PAMFPN: Position-Aware Multi-Kernel Feature Pyramid Network with Adaptive Sparse Attention for Robust Object Detection in Remote Sensing Imagery by Xiaofei Yang, Suihua Xue, Lin Li, Sihuan Li, Yudong Fang, Xiaofeng Zhang, Xiaohui Huang

“…Deep learning methods have achieved remarkable success in remote sensing object detection. …”
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An object detection method in foggy weather based on novel feature enhancement and fusion by ZHU Lei, ZHAO Han, WANG Weili

“…To further improve the detection accuracy of objects in foggy scenes for deep learning networks, a foggy object detection method called NFF-YOLOX is proposed based on the YOLOX network. …”
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Improving Cell Nuclei Segmentation in Pathological Tissues Using Self-Supervised Regression Method by Hesham Ali, Mostafa Hammouda, Mustafa Elattar, Sahar Selim

“…This study introduces a novel self-supervised learning approach for nuclei segmentation in WSIs, comparing its efficacy against other self-supervised techniques and traditional methods. …”
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Pre-class learning assessment on integrating artificial intelligence into evidence-based medicine curriculum by ZUHAER·Yisha, CHEN Xiaowei, CAO Wangnan, WU Shanshan, LIU Junchang, SUN Yumei, WU Tao, ZHAN Siyan, SUN Feng

“…Objective To investigate the knowledge base, learning attitudes, and practical abilities of students enrolling in an evidence-based medicine (EBM) course integrated with artificial intelligence (AI).Methods The study targeted students enrolled in the 2024–2025 academic year course “Evidence Synthesis and Application: Network Meta-Analysis” at Peking University Health Science Center. …”
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Artificial Intelligence Dystocia Algorithm (AIDA) as a Decision Support System in Transverse Fetal Head Position by Antonio Malvasi, Lorenzo E. Malgieri, Tommaso Difonzo, Reuven Achiron, Andrea Tinelli, Giorgio Maria Baldini, Lorenzo Vasciaveo, Renata Beck, Ilenia Mappa, Giuseppe Rizzo

“…Transverse fetal head position during labor is associated with increased rates of operative deliveries and cesarean sections. …”
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Enhancing medical education in Nepal through problem-based learning (PBL) and collaborative action research strategies by Alok Atreya, Laxman Gnawali, Ritesh G. Menezes, Samata Nepal

“…Abstract Background Teamwork and collaboration among students are essential for successful problem-based learning (PBL) implementation; however, many medical colleges in Nepal face obstacles to implementing successful PBL sessions. …”
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Development of an imitation learning method for a neural network system of mobile robot’s movement on example of the maze solving by T. Yu. Kim, R. A. Prakapovich

“…Objectives. To develop a new method for training a mobile robot control system to use a maze solver algorithm based on reinforcement learning and the right-hand algorithm.Methods. …”
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