A Comprehensive Feature Extraction Network for Deep-Learning-Based Wildfire Detection in Remote Sensing Imagery by Haiyan Pan, Die Luo, Yuewei Zhang

“…To mitigate these challenges, this study proposes a deep-learning-based fire point detection method that integrates Swin Transformer and BiLSTM for the extraction of the multi-dimensional features associated with fire points. …”
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Design of an Efficient Deep Learning-Based Diagnostic Model for Wind Turbine Gearboxes Using SCADA Data by Xuan-Kien Mai, Jun-Yeop Lee, Jae-In Lee, Byeong-Soo Go, Seok-Ju Lee, Minh-Chau Dinh

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How does interactive case-based learning improve students' complex mathematical problem-solving abilities? by Ramdani Miftah, Jarnawi Afghani Dahlan, Lia Kurniawati, Tatang Herman, Lutfiana Lutfiana

“…The study's findings are that students instructed using the ICBL model demonstrated superior CMPS abilities compared to those instructed using traditional methods, and students responded positively to the ICBL instructional model in mathematics learning. …”
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Context-Aware Machine Learning-Based Beam Selection With Multi-Panel Devices in the Presence of Self-Blockage by Sajad Rezaie, Joao Morais, Ahmed Alkhateeb, Preben Mogensen, Carles Navarro Manchon

“…Context-aware beam management in millimeter-wave (mmWave) wireless communication systems has received increasing attention over the past few years. Machine learning (ML) has played a key role in leveraging different types of context information from the device position and orientation to more ambitious scenarios using RADAR, LIDAR, or camera images. …”
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Metabolomic machine learning-based model predicts efficacy of chemoimmunotherapy for advanced lung squamous cell carcinoma by Liang Zheng, Wei Nie, Shuyuan Wang, Ling Yang, Fang Hu, Fang Hu, Meili Ma, Lei Cheng, Jun Lu, Bo Zhang, Jianlin Xu, Ying Li, Yinchen Shen, Wei Zhang, Runbo Zhong, Tianqing Chu, Baohui Han, Xiaoxuan Zheng, Xiaoxuan Zheng, Hua Zhong, Xueyan Zhang

“…Patients were divided into non-response (NR) and response (R) groups according to overall survival (OS), and prognostic models were constructed and validated using different machine learning methods. The patients were further categorized into high-risk and low-risk groups based on the median risk score, to assess the model's predictive performance.ResultsThere were significant differences in metabolites and metabolic pathways between NR and R groups, and 117 differential metabolites were preliminarily screened (p < 0.05, VIP > 1). …”
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Surface-Related Multiple Suppression Based on Field-Parameter-Guided Semi-Supervised Learning for Marine Data by Jiao Qi, Siyuan Cao, Zhiyong Wang, Yankai Xu, Qiqi Zhang

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Machine learning model based on survey assessment of sleep quality in chronic obstructive pulmonary disease patients. by Miraç Öz, Banu Eriş Gülbay, Barış Bulut, Elif Akıncı Aydınlı, Aslıhan Gürün Kaya, Öznur Yıldız, Turan Acıcan, Sevgi Saryal

“…<h4>Purpose</h4>The aim is to develop a learning model based on clinical and survey data to assess sleep quality and identify determining factors affecting sleep quality in chronic obstructive pulmonary disease (COPD) patients.…”
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A deep learning based automatic two-dimensional digital templating model for total knee arthroplasty by Jaeseok Park, Sung Eun Kim, Back Kim, Sanggyu Lee, Jae-Jun Lee, Du Hyun Ro

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The application of suitable sports games for junior high school students based on deep learning and artificial intelligence by Xueyan Ji, Shamsulariffin Bin Samsudin, Muhammad Zarif Bin Hassan, Noor Hamzani Farizan, Yubin Yuan, Wang Chen

“…In HMDB51 dataset, the proposed average detection accuracy of ST-GCN action recognition algorithm based on MediaPipe framework reaches 88.3%. The proposed method has advantages in long-term prediction (> 500ms), especially at 1000ms, the values of Mean Absolute Error and Mean Per Joint Position Error are 71.1 and 1.04 respectively. …”
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Identification of Crucial Genes Associated With MYCN‐Driven Neuroblastoma Based on Single‐Cell Analysis and Machine Learning by Jiasi Zhang, Yichen Lei, Yaqin Wang, Wen Yu, Xiaoyan Zhao, Yongbing Zhu, Dedong Zhang, Siying Liu, Aiguo Liu

“…Key genes were then identified using machine learning based random survival forest (RSF) and nomogram analyses. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…To address these challenges, this study proposes a novel deep reinforcement learning (DRL)-based framework, integrating a convolutional neural network (CNN) for hierarchical feature extraction and a recurrent neural network (RNN) for sequential pattern recognition and time-series modeling. …”
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Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding by Yani Zhang, Qiankun Li, Haijun Duan, Liang Tan, Ying Cao, Junxin Chen

“…The results of real-time polymerase chain reaction (RT-PCR) tests determined the duration of viral shedding from the first day of SARS-CoV-2 positivity to the day of SARS-CoV-2 negativity. The extreme gradient boosting (XGBoost) machine learning method was employed to establish a prediction model for prolonged SARS-CoV-2 shedding and analyze significant risk factors. …”
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Integrating Basic Electrocardiogram Interpretation into Advanced Cardiovascular Life Support Stations Through Simulation-Based Learning Among Preclinical Medical Students: Comparin... by Kaophiphat Thammasoon, Sethapong Lertsakulbunlue, Anupong Kantiwong

“…Background: Simulation-based learning (SBL) was introduced at Phramongkutklao College of Medicine to improve electrocardiogram skills within an advanced cardiovascular life support (ACLS) context for pre-clinical students.Objectives: This study compared the perceptions of third-year students and teachers regarding the SBL course.Methods: A cross-sectional study included 96 students and 10 instructors. …”
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Deep Learning-Based Cascaded Light Source Detection for Link Alignment in Underwater Wireless Optical Communication by Bowen Jia, Wenmin Ge, Jingxuan Cheng, Zihao Du, Renming Wang, Guangbin Song, Yufan Zhang, Chengye Cai, Sitong Qin, Jing Xu

“…Obtaining the light source position from the image is an important solution for achieving link alignment in laser-based underwater wireless optical communication (UWOC) systems. …”
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Zebra optimization algorithm incorporating opposition-based learning and dynamic elite-pooling strategies and its applications. by Tengfei Ma, Guangda Lu, Zhuanping Qin, Tinghang Guo, Zheng Li, Changli Zhao

“…To address the limitations of the Zebra Optimization Algorithm (ZOA), including insufficient late-stage optimization search capability, susceptibility to local optima, slow convergence, and inadequate exploration, this paper proposes an enhanced Zebra Optimization Algorithm integrating opposition-based learning and a dynamic elite-pooling strategy (OP-ZOA: Opposition-Based Learning Dynamic Elite-Pooling Zebra Optimization Algorithm). he proposed search algorithm employs a good point set-elite opposition-based learning mechanism to initialize the population, enhancing diversity and facilitating escape from local optima. …”
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Post-COVID-19 Benign Paroxysmal Positional Vertigo by Siniša Maslovara, Andro Košec

“…The symptoms occurred when lying in bed and turning to the right and assuming an upright position. The diagnosis of posterior semicircular canal BPPV (PC-BPPV) was made based on a subjectively and objectively positive right-sided Dix–Hallpike test. …”
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Queue Formation and Obstacle Avoidance Navigation Strategy for Multi-Robot Systems Based on Deep Reinforcement Learning by Tianyi Gao, Zhanlan Li, Zhixin Xiong, Ling Wen, Kai Tian, Kewei Cai

“…This study proposes a novel deep reinforcement learning (DRL)-based method for achieving queue formation, obstacle avoidance, and navigation in multi-robot systems. …”
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How can ecology-based civics learning media "PKN Ekologi" foster ecological competence in students? by Yoga Ardian Feriandi, Risti Aulia Ulfah

“…PKN Ecology is a digital-based learning media that adopts the principle of augmented Reality. …”
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Can digital economy improve urban ecological development? evidence based on double machine learning analysis by Yuchen Jiang, Lei Li, Yue Xu

“…In response to these problems, the double machine learning method is applied to assess the effect of DE on UED. …”
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Detection of Invasive Species (Siam Weed) Using Drone-Based Imaging and YOLO Deep Learning Model by Deepak Gautam, Zulfadli Mawardi, Louis Elliott, David Loewensteiner, Timothy Whiteside, Simon Brooks

“…We specifically examined the effects of input training images, solar illumination, and model complexity on the model’s detection performance and investigated the sources of false positives. Drone-based RGB images were acquired from four sites in the Townsville region of Queensland to train and test a deep learning model (YOLOv5). …”
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