Informing Visual Display Design of Electronic Health Records: A Human Factors Cross-Industry Perspective by Zoe M. Pruitt, Jessica L. Howe, Lucy S. Bocknek, Arianna P. Milicia, Patricia A. Spaar, Seth Krevat, Raj M. Ratwani

“…# Background Despite their prevalence, poorly designed electronic health records (EHRs) are common, and research shows poor design consequences include clinician burnout, diagnostic error, and even patient harm. One of the major difficulties of EHR design is the visual display of information, which aims to present information in an easily digestible form for the user. …”
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Molecular property prediction using pretrained-BERT and Bayesian active learning: a data-efficient approach to drug design by Muhammad Arslan Masood, Samuel Kaski, Tianyu Cui

“…This approach establishes a foundation for more efficient screening workflows across diverse pharmaceutical applications.…”
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Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning by Zhangjian Guo, Tongling Wang, Shuxun Chi, Li Huang

“…The experimental results demonstrate that the optimized model achieves a Mean Squared Error (MSE) of 0.273, an R2 of 0.887, and a standard deviation of 0.046 on acceleration data, significantly outperforming comparison models such as Temporal Convolutional Network (TCN), Gated Recurrent Unit with Attention Mechanism (GRU-ATT), and Self-Supervised Transformer (SST). …”
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Optimal fuzzy-PID controller design for object tracking by Yaregal Limenih Melese, Girma Kassa Alitasb, Mequanent Degu Belete

“…The simulation results demonstrate that GA tuned Fuzzy-PID controller has given us the best results in terms of reduced steady-state error, faster rise time and settling time, and object position stabilization than PID, Fuzzy and Fuzzy-PID controllers, which shows that optimal Fuzzy-PID controller designed is more appropriate and efficient.…”
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Machine-learning based high-bandwidth magnetic sensing by Galya Haim, Stefano Martina, John Howell, Nir Bar-Gill, Filippo Caruso

“…Our results indicate a potential reduction of required data points by at least a factor of 3, while maintaining the current error level. Our results promote quantum machine learning protocols for sensing applications towards more feasible and efficient quantum technologies.…”
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A survey of GNSS receiver autonomous integrity monitoring: Research status and opportunities by Zhen Huang, Zhen Huang, Weihua Mou, Weihua Mou, Rui Wang, Pengpeng Li, Pengpeng Li, Zhicheng Lyu, Zhicheng Lyu, Gang Ou, Gang Ou

“…The paper provides a comprehensive review of RAIM algorithms for global navigation satellite system (GNSS) positioning applications. The parameters related to integrity assessment and typical fault detection and exclusion methods are reviewed, and RAIM is categorized into three types of methods: error probability distribution model-based, set representation-based, and machine learning-based. …”
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Rainfall estimation in the West African Sahel: comparison and cross-validation of top-down vs. bottom-up precipitation products in Burkina Faso by Roland Yonaba, Axel Belemtougri, Tazen Fowé, Lawani Adjadi Mounirou, Elias Nkiaka, Moctar Dembélé, Akpoti Komlavi, Serigne M’backé Coly, Mahamadou Koïta, Harouna Karambiri

“…The decomposition of total bias reveals that hit bias are dominant, but are larger in magnitude in SM2RPPs. Systematic errors are the major component of hit biases, suggesting they could be further treated through bias-correction. …”
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Investigating Self-Heating Effects in Ferroelectric FinFETs for Reliable In-Memory Computing by Swati Deshwal, Shubham Kumar, Swetaki Chatterjee, Anirban Kar, Shivendra Singh Parihar, Yogesh Singh Chauhan, Hussam Amrouch

“…Our results reveal an increased error probability in Hamming distance (HD) calculations through the TCAM array when SHE and variations are present. …”
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On the Evaluation of the Hyperthermic Efficiency of Magnetic Scaffolds by Matteo B. Lodi, Antonios Makridis, Konstantina Kazeli, Theodoros Samaras, Makis Angelakeris, Giuseppe Mazzarella, Alessandro Fanti

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Enhancing LEO direct-to-satellite channel modeling with the shadowing effect via K-distribution by Tomás B. Núñez-González, Cesar A. Azurdia-Meza, Raydel Ortigueira, Samuel Montejo-Sánchez, Javier A. Ordenes-Pinto, Melissa E. Diago-Mosquera, Sandra Céspedes

“…This enhancement captures the combined effects of multipath fading and shadowing, providing a more accurate representation of the channel conditions experienced in DtS-IoT applications. Simulation results show that the enhanced model aligns closely with analytical bit error rate (BER) predictions, particularly at higher signal-to-noise ratios (SNRs), with less than 1% deviation from theoretical values. …”
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A comprehensive antigen-antibody complex database unlocking insights into interaction interface by Yuwei Zhou, Wenwen Liu, Ziru Huang, Yushu Gou, Siqi Liu, Lixu Jiang, Yue Yang, Jian Huang

“…This database provides extensive metadata and rectifies annotation errors found in the PDB database. Furthermore, it integrates data on antibody developability and antigen-drug target relationships, making it valuable for assisting new antibody therapies development. …”
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Optimized SVR model for predicting dissolved oxygen levels using wavelet denoising and variable reduction: Taking the Minjiang River estuary as an example by Peng Zhang, Xinyang Liu, Huiru Zhang, Chengchun Shi, Gangfu Song, Lei Tang, Ruihua Li

“…The integrated WD-MIC data processing method shows promising potential in reducing model errors and lowering water monitoring costs by focusing on highly correlated variables.…”
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Measurement-guided therapeutic-dose prediction using multi-level gated modality-fusion model for volumetric-modulated arc radiotherapy by Changfei Gong, Changfei Gong, Changfei Gong, Yuling Huang, Yuling Huang, Yuling Huang, Junming Jian, Junming Jian, Junming Jian, Wenheng Zheng, Wenheng Zheng, Wenheng Zheng, Xiaoping Wang, Xiaoping Wang, Xiaoping Wang, Shenggou Ding, Shenggou Ding, Shenggou Ding, Yun Zhang, Yun Zhang, Yun Zhang

“…Quantitative experimental predictions show that the proposed model achieved the lowest values for the mean absolute error (37.99) and root mean square error (4.916), and the highest values for the peak signal-to-noise ratio (52.622), structural similarity (0.986) and universal quality index (0.932). …”
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FGPointKAN++ point cloud segmentation and adaptive key cutting plane recognition for cow body size measurement by Guoyuan Zhou, Wenhao Ye, Sheng Li, Jian Zhao, Zhiwen Wang, Guoliang Li, Jiawei Li

“…The calculated Mean Absolute Percentage Errors (MAPE) of Wither Height (WH), Body Width (BW), Chest Circumference (CC) and Abdominal Circumference (AC) are 2.07 %, 3.56 %, 2.24 % and 1.42 %, respectively. …”
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Knowledge and perception of artificial lntelligence education among undergraduate healthcare students by Mohammed M. Alsultan, Mohamed A. Baraka, Leena H. Alhajri, Luluah Althayf, Nujud Omar, Faten Alhomoud, Farah Kais Alhomoud, Ahmad Alsultan, Yousef Saeed Alqarni, Fahad T. Alsulami, Feras A. Al-Awad

“…Pharmacy and non-pharmacy students held significantly different knowledge of advanced AI skills (p = 0.0019) and the importance of AI applications (p = 0.0259). Additionally, there were significant differences in perceptions regarding the belief that AI-powered medical devices would help healthcare providers reduce medical errors (p = 0.0279). …”
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Enhancing Urban Road Safety: A 5G NR Model for Vulnerable Road Users Awareness by Alexis Yanez, Felipe Salas, Cesar A. Azurdia-Meza, Jorge Ignacio Sandoval, Sandra Cespedes

“…Results demonstrate high model accuracy, with Root Mean Square Error (RMSE) values of 0.0265 in partially obstructed and 0.0309 in highly obstructed scenarios, using the non-obstructed case as a baseline. …”
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Advanced battery management system enhancement using IoT and ML for predicting remaining useful life in Li-ion batteries by Gopal Krishna, Rajesh Singh, Anita Gehlot, Ahmad Almogren, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen

“…The proposed model demonstrates significant forecasting precision, attaining a root mean square error (RMSE) of 0.01173, outperforming all comparative models. …”
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5G Fronthaul in Modular P4: eCPRI Protocol Processing and Precise BMv2 Timestamps for PTP-1588 by Atabak Nojavan, Bill Pontikakis, Francois-Raymond Boyer, Yvon Savaria

“…Additionally, we introduce precise ingress and automatic egress timestamps for the BMv2 software switch to improve PTP-1588 accuracy, reducing error margins from 24,000 microseconds to 60 microseconds (99.75% improvement) and achieving sub-microsecond precision. …”
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How Different ECMWF Atmospheric Models Impact the Estimation of Sea-Level Trends by M. Joana Fernandes, Telmo Vieira, Pedro Aguiar, Clara Lazaro

“…Results show that, due to regular model updates, ECMWF OP possesses significant discontinuities that induce errors in sea-level trend which, in some regions, can exceed 1 mm yr^−1 in absolute value, over periods of 7–8 years. …”
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Reconfigurable ScAlN Piezoelectric Micromachined Ultrasonic Transducer Arrays for Range Finding by Wenling Shang, Danrui Wang, Bin Miao, Shutao Yao, Guifeng Ta, Haojie Liu, Jinyan Tao, Xiaonan Liu, Xiangyong Zhao, Jiadong Li

“…However, the frequency inconsistency of the PMUT arrays often leads to directional errors with the ultrasonic beams. Herein, we propose a reconfigurable PMUT array based on a Sc_0.2Al_0.8N piezoelectric thin film for in-air ranging. …”
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