Implementing EUCAST rapid antimicrobial susceptibility testing method for sepsis: lessons learned in a tertiary care center by Mohammad Aadam Bin Najeeb, Ayush Gupta, Shashank Purwar, Vishnu Teja Nallapati, Jogender Yadav, Farha Siddiqui

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Soil Structure Analysis with Attention: A Deep-Learning-Based Method for 3D Pore Segmentation and Characterization by Italo Francyles Santos da Silva, Alan de Carvalho Araújo, João Dallyson Sousa de Almeida, Anselmo Cardoso de Paiva, Aristófanes Corrêa Silva, Deane Roehl

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Retracted: Improving Students’ Learning Motivation and Attitude in Physical Education by Using Algorithm Thinking Innovation Teaching Method by International Transactions on Electrical Energy Systems

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Using E-Portfolios as an Integrated-Workflow Teaching Method and Tool in Open Distance Electronic Learning (ODeL). by Moffat Majola

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A Fine-Grained Image Classification Method Based on ConvNeXt Heatmap Localization and Contrastive Learning by Qiyu Pan, Kaiyuan Liu, Shijie Zheng, Gaocai Wang

“…Aiming at the challenges of high intra-class disparity and low inter-class disparity in fine-grained image classification, a multi-branch fine-grained image classification method based on ConvNeXt network as the backbone and using GradCAM heatmap for cropping and attention erasure is proposed. …”
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Machine Learning Method for TOC Prediction: Taking Wufeng and Longmaxi Shales in the Sichuan Basin, Southwest China as an Example by Jia Rong, Zongyuan Zheng, Xiaorong Luo, Chao Li, Yuping Li, Xiangfeng Wei, Quanchao Wei, Guangchun Yu, Likuan Zhang, Yuhong Lei

“…The results showed that the TOC value prediction accuracy was improved by more than 50% by using the well-trained machine learning models compared with the traditional ΔLogR method in an overmature and tight shale. …”
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A Novel Method for a Pursuit–Evasion Game Based on Fuzzy Q-Learning and Model-Predictive Control by Penglin Hu, Chunhui Zhao, Quan Pan

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Vehicle Re-Identification Method Based on Efficient Self-Attention CNN-Transformer and Multi-Task Learning Optimization by Yu Wang, Rui Li, Yihan Shao

“…Furthermore, a multi-task learning strategy is adopted, creating specialized learning pathways for classification tasks and metric learning tasks. …”
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Towards real-world monitoring scenarios: An improved point prediction method for crowd counting based on contrastive learning. by Rundong Cao, Jiazhong Yu, Ziwei Liu, Qinghua Liang

“…Due to the reliance on supervised learning with labeled data, current methods struggle to adapt to crowd detection in complex scenarios when training data is limited; Moreover, detection-based methods may lead to numerous missed detections when dealing with dense, small-scale target groups. …”
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FA-Unet: A Deep Learning Method with Fusion of Frequency Domain Features for Fruit Leaf Disease Identification by Xiaowei Li, Wenlin Wu, Fenghua Zhu, Shenhao Guan, Wenliang Zhang, Zheng Li

“…In the recognition of fruit leaf diseases, image recognition technology based on deep learning has received increasing attention. However, deep learning models often perform poorly in complex backgrounds, and in some cases, they even outperform traditional algorithms. …”
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SELECTION OF VIDEO CONFERENCE APPLICATION FOR MATHEMATICS LEARNING USING INTUITIONISTIC FUZZY MAX-MIN AVERAGE COMPOSITION METHOD by Kiki Henra, Efuansyah Efuansyah, Raden Sulaiman

“…In this article, the Intuitionistic Fuzzy Max-Min Average Composition method is used which aims to choose the right video conferencing application for learning mathematics. …”
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A Video-Based Cognitive Emotion Recognition Method Using an Active Learning Algorithm Based on Complexity and Uncertainty by Hongduo Wu, Dong Zhou, Ziyue Guo, Zicheng Song, Yu Li, Xingzheng Wei, Qidi Zhou

“…In this paper, a cognitive emotion recognition method based on video data is proposed, in which 49 emotion description points were initially defined, and the spatial–temporal features of cognitive emotions were extracted from the video data through a feature extraction method that combines geodesic distances and sample entropy. …”
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Improving Hyperspectral Image Classification Method for Fine Land Use Assessment Application Using Semisupervised Machine Learning by Chunyang Wang, Zengzhang Guo, Shuangting Wang, Liping Wang, Chao Ma

“…The study on fine land use/cover assessment using hyperspectral image classification is a focal growing area in many fields. Semisupervised learning method which takes a large number of unlabeled samples and minority labeled samples, improving classification and predicting the accuracy effectively, has been a new research direction. …”
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Research on the Error Estimation Method for Electric Energy Meters of Electric Vehicle Charging Piles based on Deep Learning by Wang Juan, Liu Wei, Zhang Yong, Liu Zhi, Zheng Xiaolei, Wang Yuxin, Hao Jianshu, Dai Xuanding

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APPLICATION OF EXTREME LEARNING MACHINE METHOD ON STOCK CLOSING PRICE FORECASTING PT ANEKA TAMBANG (PERSERO) TBK by Rita Apriliyanti, Neva Satyahadewi, Wirda Andani

“…Artificial neural networks are modeling methods that can capture complex input and output relationships. …”
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Fault Detection of Cyber-Physical Systems Using a Transfer Learning Method Based on Pre-Trained Transformers by Pooya Sajjadi, Fateme Dinmohammadi, Mahmood Shafiee

“…The large volume of data generated by CPSs has made deep learning (DL) methods an attractive solution; however, imbalanced datasets and the limited availability of fault-labeled data continue to hinder their effective deployment in real-world applications. …”
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An islanding detection method for grid-connect inverter based on parameter optimized variational mode decomposition and deep learning by Yan Xia, Yan Xia, Yuli Lv, Feihong Yu, Yiqiang Yang, Yili Yang, Wei Li, Ke Li

“…To address the drawbacks of active methods and passive methods, an intelligent islanding detection strategy based on parameter-optimized variational mode decomposition (VMD) and deep learning was developed. …”
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An Improved Method for Human Activity Detection with High-Resolution Images by Fusing Pooling Enhancement and Multi-Task Learning by Haoji Li, Shilong Ren, Lei Fang, Jinyue Chen, Xinfeng Wang, Guoqiang Wang, Qingzhu Zhang, Qiao Wang

“…Deep learning has garnered increasing attention in human activity detection due to its advantages, such as not relying on expert knowledge and automatic feature extraction. …”
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Machine Learning Based Localization of LoRa Mobile Wireless Nodes Using a Novel Sectorization Method by Madiyar Nurgaliyev, Askhat Bolatbek, Batyrbek Zholamanov, Ahmet Saymbetov, Kymbat Kopbay, Evan Yershov, Sayat Orynbassar, Gulbakhar Dosymbetova, Ainur Kapparova, Nurzhigit Kuttybay, Nursultan Koshkarbay

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A Deep Reinforcement Learning Method with a Low Intercept Probability in a Netted Synthetic Aperture Radar by Longhao Xie, Ziyang Cheng, Ming Li, Huiyong Li

“…A deep reinforcement learning (DRL)-based power allocation method is proposed to achieve a low probability of intercept (LPI) in a netted synthetic aperture radar (SAR). …”
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