Deriving tissue physical densities based on Dixon magnetic resonance images and tissue composition prior knowledge for voxel-based internal dosimetry by Cheng-Ting Shih, Ko-Han Lin, Bang-Hung Yang, Chien-Ying Li, Tzu-Lin Lin, Greta S. P. Mok, Tung-Hsin Wu

“…On average of a validation set, the mean absolute percent errors (MAPEs) of the whole-body ρ derivation and internal dose calculation using the proposed method were 14.28 ± 11.11% and 3.31 ± 0.69%, respectively. …”
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Automated dairy cow identification and feeding behaviour analysis using a computer vision model based on YOLOv8 by Claudia Giannone, Mohsen Sahraeibelverdy, Martina Lamanna, Damiano Cavallini, Andrea Formigoni, Patrizia Tassinari, Daniele Torreggiani, Marco Bovo

“…Traditional methods for monitoring feeding behaviour are labour-intensive, time-consuming, and prone to errors. To address these challenges, precision livestock farming technologies have gained increasing attention. …”
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Sea Surface Height Inversion Model Based on Multimodal Deep Learning for the Fusion of Heterogeneous FY-3E GNSS-R Data by Yun Zhang, Ganyao Qin, Shuhu Yang, Yanling Han, Zhonghua Hong

“…Traditional physical altimetry methods based on delay–Doppler mapping (DDM) are subject to errors that are difficult to correct computationally. …”
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Non-clinical factors influencing discharge and admission decisions in the emergency department: a focus group study among Israeli physicians by Ofer Kobo, Itay Itzhaki, Michael J. Drescher, Jacob Glazer, Avi Israeli, Bruce E. Landon, Shuli Brammli-Greenberg

“…Clinical trial number Not applicable.…”
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Water inrush mechanism and the minimum safety thickness of the rock wall of a tunnel crossing a fault fracture zone by YUAN Dong, XIAO Kun

“…Conclusion  In practical engineering, there are certain empirical judgments and errors in obtaining excavation disturbance factors via rock integrity assessment and rock wave velocity testing. …”
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Can Separation Enhance Fusion? An Efficient Framework for Target Detection in Multimodal Remote Sensing Imagery by Yong Wang, Jiexuan Jia, Rui Liu, Qiusheng Cao, Jie Feng, Danping Li, Lei Wang

“…Furthermore, small-target detection remains a critical challenge in remote sensing image analysis, as small targets occupy only a few pixels, making feature extraction difficult and prone to errors. To address these challenges, this paper revisits the existing multimodal fusion methodologies and proposes a novel framework of separation before fusion (SBF). …”
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Simultaneous multi-class detection of interplanetary space weather events by Nguyen Gautier, Bernoux Guillerme, Ferlin Antoine

“…A detailed analysis of our method output shows that the great majority of detection errors are short events with a weak in-situ signature, which are expected to be among the least geoeffective event or misclassified events. …”
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Fault detection for stochastic time-varying systems based on adaptive disturbance rejection observers by Wenli ZHANG, Anning LIU, Jiantao SHI

“…To tackle these challenges, this paper proposes an adaptive disturbance rejection observer that can decouple state estimation errors from unknown disturbances. A novel, easily implementable full-order observer design method is introduced, offering highly adaptable performance across diverse disturbances and control system structures. …”
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Three-dimensional creep constitutive model of sandstone based on damage statistics by Wang Liukai, Cai Guojun, Zhao Weiping, Hu Xing

“…The conventional triaxial compression test was carried out on the MTS-815 rock rigidity testing machine, and the applicability of the damage statistical model was verified by comparing the compression test results with the damage evolution curve. …”
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Optimized DenseNet Architectures for Precise Classification of Edible and Poisonous Mushrooms by Jay Prakash Singh, Debolina Ghosh, Jagannath Singh, Anurag Bhattacharjee, Mahendra Kumar Gourisaria

“…Traditional methods often result in errors which led to misclassifications and conventional machine learning models often struggle in feature extraction due to subtle differences in mushroom species. …”
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Neural Classification of Argument Elements and Styles in Arabic Competitive Debates by Al-Zawqari Ali, Mohamed Ahmed, Abdul Gabbar Al-Sharafi, Mohammad M. Khader, Ali Safa, Gerd Vandersteen

“…For the second task, all models drop to 50% F1-score, yet performance rebounds to 81% accuracy and 80% F1-score when predictions are post-processed back to Logos, Pathos, Ethos, revealing that most errors in the second task occur within persuasion modes rather than across them. …”
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Semantic Fusion Algorithm of 2D LiDAR and Camera Based on Contour and Inverse Projection by Xingyu Yuan, Yu Liu, Tifan Xiong, Wei Zeng, Chao Wang

“…Traditional calibration methods for LiDAR and cameras often rely on precise targets and can accumulate errors, leading to significant limitations. Additionally, the semantic fusion of LiDAR and camera data typically requires extensive projection calculations, complex clustering algorithms, or sophisticated data fusion techniques, resulting in low real-time performance when handling large volumes of data points in dynamic environments. …”
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Advances in the pilot point inverse method: Où En Sommes-Nous maintenant? by White, Jeremy, Lavenue, Marsh

“…The paper ends with newly developed applications of the PPM, given modern machine learning capabilities, and some foreshadowing as to where the PPM might evolve.…”
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An Improved Fitting Method for Predicting the Zernike Coefficient–Wavelength Curves by Fang Wang, Qiyuan Zhang, Haoyu Wang, Dayong Zhu, Huaikang Zhu, Wenxin Jia, Sen Han

“…Owing to the inevitable errors in the actual measurements, the fitting method is preferred to determine the coefficients of the Conrady formula. …”
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Hypervolemia screening in predialysis healthcare for hemodialysis patients using fuzzy color reason analysis by Wei-Ling Chen, Chung-Dann Kan, Chia-Hung Lin, Ying-Shin Chen, Yi-Chen Mai

“…In contrast to the experienced anthropometric formulas, Watson formula has less than 2% of margin errors and provides a criterion as a reference manner to estimate the total body water in patient’s normal dry weight. …”
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OWL model of multi-agent Smart-system of distance learning for people with vision disabilities by Galina A. Samigulina, Asem S. Shayakhmetova, Adlet Nyusupov

“…Multi-agent approach provides multi functionality of system, stability to system errors, and optimization of computing resources.…”
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Evaluation of DNA barcoding reference databases for marine species in the western and central Pacific Ocean by Yufei Zhou, Alejandro Trujillo-González, Simon Nicol, Roger Huerlimann, Stephen D. Sarre, Dianne Gleeson

“…This study highlights the need for standardized database curation and sequencing practices to improve the global reliability and applicability of DNA barcoding.…”
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A national survey on community pharmacists’ perception, practice and perceived barriers towards pharmaceutical care services in the United Arab Emirates by Salma Mohamed, Subish Palaian, Muaed Alomar, Mohammad M. Al-Ahmad

“…Most of the CPs felt that patients’ medications should be reviewed by them to prevent medicine-related errors and promote the appropriate medication use [median (IQR) 5 (4–5)]. …”
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Research on Algorithms for Local Robot Positioning Using Methods of Discrete Optimization by Vyacheslav Korolyov, Maksim Ogurtsov, Oleksandr Khodzinskyi

“…It allows for optimizing the coordinates of three objects, minimizing distance and angle errors considering physical constraints, such as fixing the coordinates of certain points and ensuring the minimum distance between objects is not exceeded. …”
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Boreal tree species classification using airborne laser scanning data annotated with harvester production reports, and convolutional neural networks by Raul de Paula Pires, Christoffer Axelsson, Eva Lindberg, Henrik Jan Persson, Kenneth Olofsson, Johan Holmgren

“…The CNN models were trained and evaluated to classify trees into Norway spruce, Scots pine, Deciduous, and a “Noise” class for segmentation errors. The classification accuracy varied according to the dataset used, with the dual-wavelength dataset achieving the highest macro-F1 score (0.896), followed by the VUX dataset (0.894) and miniVUX dataset (0.835). …”
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