A Radio Frequency Interference Screening Framework—From Quick-Look Detection Using Statistics-Assisted Network to Raw Echo Tracing by Jiayuan Shen, Bing Han, Yang Li, Zongxu Pan, Di Yin, Yugang Feng, Guangzuo Li

“…By combining the statistics-assisted network with the sliding-window algorithm and the error-tolerant training strategy, it is possible to accurately detect and locate RFI in the quick looks of an SLC product. …”
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Integrative modeling of POPs output flux from soil at a regional scale: A comprehensive approach by Xinyue Chen, Meie Wang, Tian Xie, Yutong Song, Weiping Chen

“…Performance evaluation through 10-fold cross-validation yielded coefficient of determination (R2) values greater than 0.7 and root mean square error (RMSE) below 3 %, outperforming the previous model. …”
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Modeling the Dynamic Global Distribution of the Ring Current Oxygen Ions Using Artificial Neural Network Technique by Qiushuo Wang, Chao Yue, Jinxing Li, Jacob Bortnik, Donglai Ma, Chae‐Woo Jun

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AI-enabled driver assistance: monitoring head and gaze movements for enhanced safety by Sayyed Mudassar Shah, Gan Zengkang, Zhaoyun Sun, Tariq Hussain, Khalid Zaman, Abdullah Alwabli, Amar Y. Jaffar, Farman Ali

“…Finally, the implications of these findings are discussed, and potential avenues for future research are outlined.…”
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Robust Framework for PMU Placement and Voltage Estimation of Power Distribution Network by Nida Khanam, Mohd. Rihan, Salman Hameed

“…The proposed approach reduces voltage estimation errors significantly by strategically placing PMUs in a distribution network. …”
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SMOTE-LOF for noise identification in imbalanced data classification by Asniar, Nur Ulfa Maulidevi, Kridanto Surendro

“…The unequal distribution of data leads to the machine's inability to carry out predictive accuracy in determining the minority classes, thereby causing various costs of classification errors. Currently, the standard framework used to solve the unequal distribution of imbalanced data learning is the Synthetic Minority Oversampling Technique (SMOTE). …”
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A Shield Segment Bolt Detection and Localization Method Based on Ellipse Detection by Jie Liu, Shuaishuai Liu, Zhendong He, Yanqiu Xiao, Guangzhen Cui, Pengpeng Wang

“…However, during the automatic segment gripping process, traditional methods of setting targets introduce manual errors and complicate operations. Moreover, single-object detection methods only capture the bolt area, which makes precise bolt positioning challenging. …”
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First Investigation of Long-Term Methane Emissions from Wastewater Treatment Using Satellite Remote Sensing by Seyed Mostafa Mehrdad, Bo Zhang, Wenqi Guo, Shan Du, Ke Du

“…Extrapolation introduces substantial errors, as it fails to account for the spatial and temporal variations of fugitive emissions. …”
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Online Estimation of the State of Health for the Lithium-Ion Battery Based on Open Circuit Model by Pan Yajia, Junda Li, Wang Tian'An, Yang Shengxun, Zhang Yunxuan, Li Zigang, Hu Yanwen

“…The results indicate that the available capacity estimated with the proposed method converges quickly to the vicinity of the true value under accelerated aging and normal aging conditions. The relative errors under these two aging conditions are respectively confined to below 3% and 2.3%. …”
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Predicting forest understory habitat for Canada lynx using LIDAR data by Patrick A. Fekety, Rema B. Sadak, Joel D. Sauder, Andrew T. Hudak, Michael J. Falkowski

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Evaluation of FASTinov for rapid antimicrobial susceptibility testing in Pseudomonas aeruginosa by Carmen Cintora-Mairal, José Manuel Ortiz de la Rosa, Cidália Pina-Vaz, Guillermo Martín-Gutiérrez, José Antonio Lepe

“…Additionally, the system exhibited lower rates of major and very major errors compared to MicroScan, further reinforcing its reliability. …”
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Ensemble Deep Learning Object Detection Fusion for Cell Tracking, Mitosis, and Lineage by Imad Eddine Toubal, Noor Al-Shakarji, D. D. W. Cornelison, Kannappan Palaniappan

“…However, manual tracking is labor-intensive, tedious, and prone to selection bias and errors. Building upon our previous work, we propose a new deep learning-based method, EDNet, for cell detection, tracking, and motility analysis that is more robust to shape across different cell lines, and models cell lineage and proliferation. …”
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Bridging Technology and Justice: The Role of AI in Law Enforcement through Pancasila’s Ideals by Wijayanti Annisa Tunjung, Anggraeni Dita Septia, Dewi Dyah Adriantini Sintha, Hakim Hary Abdul, Kurniaty Yulia, Basri, Setiawati Diana

“…AI technologies, such as predictive policing systems and facial recognition, have the potential to streamline operations, reduce human errors, and accelerate decision-making processes. …”
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Multi-Route Aircraft Trajectory Prediction Using Temporal Fusion Transformers by Jorge Silvestre, Paula Mielgo, Anibal Bregon, Miguel A. Martinez-Prieto, Pedro C. Alvarez-Esteban

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Experimental and Artificial Neuron Network Insights into the Removal of Organic Dyes from Wastewater Using a Clay/Gum Arabic Nanocomposite by Malak F. Alqahtani, Ismat H. Ali, Saifeldin M. Siddeeg, Fethi Maiz, Sawsan B. Eltahir, Saleh S. Alarfaji

“…These dyes are used in various industries; therefore, recent research focuses on the problem of their removal from wastewater. …”
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The Effects of Pilates in Parkinson’s Disease—A Narrative Review by Józef Alfons Opara, Jarosław Wojciech Szczygieł, Krzysztof Mehlich, Katarzyna Szczygieł

“…Therefore, many authors emphasize the need for further, better-planned research.…”
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Advances in Biomedical Missing Data Imputation: A Survey by Miriam Barrabes, Maria Perera, Victor Novelle Moriano, Xavier Giro-I-Nieto, Daniel Mas Montserrat, Alexander G. Ioannidis

“…Ensuring data quality in biomedical sciences is crucial for reliable research outcomes, particularly as precision medicine continues to gain prominence. …”
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Population pharmacokinetics of vancomycin in non-extremely preterm neonates based on real-world studies: influence of daily fluid input and diuretics by Kai Zhao, Fang Zhao, KangLu Ju, Hui Chen, Xin Zhai, Ying Chang, ZhenGuo Liu

“…The predictive power and stability of the final model were assessed through visual predictive checks, normalized prediction distribution errors, and bootstrapping. Serum creatinine (Scr) level, body weight, daily fluid input, and diuretic usage were identified as significant covariates affecting vancomycin clearance. …”
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Automatic Detection of Equatorial Plasma Bubbles in Airglow Images Using Two-Dimensional Principal Component Analysis and Explainable Artificial Intelligence by Moheb Yacoub, Moataz Abdelwahab, Kazuo Shiokawa, Ayman Mahrous

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Counting touching wheat grains in images based on elliptical approximation by D. R. Avzalov, E. G. Komyshev, D. A. Afonnikov

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