Prediction of fire danger index using a new machine learning based method to enhance power system resiliency against wildfires by Tan Nhat Pham, Rakibuzzaman Shah, Nima Amjady, Syed Islam

“…Afterwards, an effective machine learning‐based forecast methodology using a new deep feature selection model is proposed to predict fire danger indexes. …”
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Remote Sensing Change Detection With Forward–Backward Diffusion and Multidirectional Scanning by Hexin Yuan, Peng Wang, Haibo Wang, Cui Ni, Yali Liu, Chao Ma

“…The backward diffusion process, along with a state-space model that incorporates multidirectional scanning, is subsequently employed during feature extraction to mitigate the adverse effects of low resolution and noise on detection accuracy. …”
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CV-Cities: Advancing Cross-View Geo-Localization in Global Cities by Gaoshuang Huang, Yang Zhou, Luying Zhao, Wenjian Gan

“…To address these issues, we propose a novel CVGL framework that integrates the vision foundational model DINOv2 with an advanced feature mixer. Our framework introduces the symmetric InfoNCE loss and incorporates near-neighbor sampling and dynamic similarity sampling strategies, significantly enhancing localization accuracy. …”
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Successes and limitations of pretrained YOLO detectors applied to unseen time-lapse images for automated pollinator monitoring by Valentin Ștefan, Thomas Stark, Michael Wurm, Hannes Taubenböck, Tiffany M. Knight

“…YOLOv5-small, the model with the highest number of trainable parameters, performed best, localising 91.21% of Hymenoptera and 80.69% of Diptera individuals. …”
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Advanced fault detection in photovoltaic panels using enhanced U-Net architectures by Khalfalla Awedat, Gurcan Comert, Mustafa Ayad, Abdulmajid Mrebit

“…Compared to standard U-Net, the proposed model achieves more than a 29% increase in F1-score and a 62% improvement in Intersection over Union (IoU) while reducing segmentation loss by 71%. …”
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A Novel Data-Driven MPC Framework Using KDE and KPCA for Autonomous Vehicles by Romdhane Nasri, Jannet Jamii, Majdi Mansouri, Zouhaier Affi, Vicenc Puig

“…Modeling and controlling complex, nonlinear, large-scale systems such as autonomous vehicles presents significant challenges due to high dimensionality, uncertain dynamics, and real-time constraints. …”
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Preliminary evaluation of a gamified smartphone intervention (O2O-PEP) for enhancing HIV post-exposure prophylaxis uptake in men who have sex with men: pilot feasibility study by Tianyu Cui, Tianying Li, Luyao Gong, Kexiang Wang, Qianqian Luo

“…To address this issue, we developed an innovative, gamified mini-app embedded in WeChat, known as O2O-PEP (online-to-offline collaborative model for HIV postexposure prophylaxis), that targets PEP uptake. …”
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Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach by Ajan Subramanian, Rui Cao, Emad Kasaeyan Naeini, Seyed Amir Hossein Aqajari, Thomas D Hughes, Michael-David Calderon, Kai Zheng, Nikil Dutt, Pasi Liljeberg, Sanna Salanterä, Ariana M Nelson, Amir M Rahmani

“…Although single-modality models, especially RR, generally provided higher performance compared to multimodal approaches, our multimodal framework still delivered results that surpassed most previous works in terms of overall accuracy. …”
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XI2S-IDS: An Explainable Intelligent 2-Stage Intrusion Detection System by Maiada M. Mahmoud, Yasser Omar Youssef, Ayman A. Abdel-Hamid

“…By leveraging SHAP values, XI2S-IDS enhances transparency in decision-making, allowing security analysts to gain clear insights into feature importance and the model’s rationale. Experiments conducted on the UNSW-NB15 and CICIDS2017 datasets demonstrate significant improvements in detection performance, with a notable reduction in false negative rates for low-frequency attacks, while maintaining high precision, recall, and F1-scores.…”
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Comparative Analysis of Non-Negative Matrix Factorization in Fire Susceptibility Mapping: A Case Study of Semi-Mediterranean and Semi-Arid Regions by Iraj Rahimi, Lia Duarte, Wafa Barkhoda, Ana Cláudia Teodoro

“…NMF is a factorization method renowned for performing dimensionality reduction and feature extraction. …”
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Predicting Movie Production Years through Facial Recognition of Actors with Machine Learning by Asraa Muayed Abdalah, Noor Redha Alkazaz

“…The study demonstrated the effectiveness of the Logistic Regression model exhibited the best performance compared to other models in the training phase, as evidenced by its AUC, precision, CA and F1score values of 99%, 86%, 85.5% and 84.2% respectively. …”
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An improved Harris hawks optimizer with enhanced logarithmic spiral and dynamic factor and its application for predicting molten iron temperature in the blast furnace by Zhendong Liu, Yiming Fang, Le Liu, Shuidong Ma

“…The simulation results based on real production data show that the proposed prediction model achieves a high prediction precision with RMSE=6.1305, R2=0.9322, and HR=89.…”
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Enhanced RT-DETR with Dynamic Cropping and Legendre Polynomial Decomposition Rockfall Detection on the Moon and Mars by Panpan Zang, Jinxin He, Yongbin Yang, Yu Li, Hanya Zhang

“…Experimental validation on the optimized RMaM-2020 dataset demonstrates that Real-Time Detection Transformer with a ResNet-18 backbone and Kolmogorov–Arnold Network based C3 module (RT-DETR-R18-KANC3) achieves 0.982 precision, 0.955 recall, and 0.964 mAP50 under low-contrast conditions, representing a 1% improvement over the baseline model and exceeding YOLO-series models by >40% in relative performance metrics.…”
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UKSSL: Underlying Knowledge Based Semi-Supervised Learning for Medical Image Classification by Zeyu Ren, Xiangyu Kong, Yudong Zhang, Shuihua Wang

“…Thus, training a high-performance model with limited labeled data has become a crucial challenge. …”
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Numerical Analysis of Pressure Drops in Single-Phase Flow Through Channels of Brazed Plate Heat Exchangers with Dimpled Corrugated Plates by Lorenzo Giunti, Francesco Giacomelli, Urban Močnik, Giacomo Villi, Adriano Milazzo, Lorenzo Talluri

“…The presented research examines the performance characteristics of Brazed Plate Heat Exchangers through computational fluid dynamics (CFD), focusing on pressure drop calculations for single-phase flow within full channels of plates featuring dimpled corrugation. …”
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Corner Enhancement Module Based on Deformable Convolutional Networks and Parallel Ensemble Processing Methods for Distorted License Plate Recognition in Real Environments by Sehun Kim, Seongsoo Cho, Jangyeop Kim, Kwangchul Son

“…For this purpose, the proposed system incorporates vehicle and license plate detection based on YOLOv8 and integrates a Corner Enhancement Module (CEM) utilizing a Deformable Convolutional Network (DCN) into the model’s neck to ensure robust feature extraction against geometric transformations. …”
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A comparative study of query strategies in Pareto active learning for heat treatment optimization of medium-Mn steel by Seung-Hyeon Kim, Jin-Young Lee, Young-Kook Lee

“…Microstructural analysis of optimized specimens revealed structure–property relationships underlying their mechanical performance: high-strength specimens exhibited predominantly martensitic structures, those with enhanced ductility featured ferritic structures, and specimens with balanced strength and ductility displayed optimized multiphase microstructures composed of tempered martensite, ferrite, and retained austenite. …”
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Unsupervised Multivariate Time Series Data Anomaly Detection in Industrial IoT: A Confidence Adversarial Autoencoder Network by Jiahao Shan, Donghong Cai, Fang Fang, Zahid Khan, Pingzhi Fan

“…In this paper, we propose an innovative model, namely the confidence adversarial autoencoder (CAAE). …”
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A risk nomogram for 30-day mortality in Chinese patients with acute pancreatitis using LASSO-logistic regression by Ying Chen, Jingping Liu, Qiuxia Ge, Min Wang, Jun Zhou

“…A retrospective study on 965 adult AP patients started from January 2017 and December 2019 was conducted. Feature selection is carried out by using LASSO regression, and the model was established through logistic regression (P < 0.05). …”
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Predicting Ozone Concentrations in Ecologically Sensitive Coastal Zones Through Structure Mining and Machine Learning: A Case Study of Chongming Island, China by Yan Liu, Tingting Hu, Yusen Duan, Jingqi Deng

“…By comparing the performance of O₃ concentration prediction of multiple machine learning models, this study found that the random forest model achieved the highest accuracy (R² = 0.9, RMSE = 11.5). …”
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