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  1. 3381

    Hartley-Domain DD-FTN Algorithm for ACO-SCFDM in Optical-Wireless Communications by Chun Shan, Ji Zhou, Dong Guo, Haide Wang, Long Liu, Qi Wang, Weiping Liu, Changyuan Yu

    Published 2019-01-01
    “…In conclusion, the ACO-SCFDM system using the HD-DD-FTN algorithm shows great potential for bandwidth-limited OWC.…”
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    Article
  2. 3382

    The Effect of Gamified Physical Activities on the Quality of Students' Leisure Time (Case Study: Female Secondary School Students in Ardabil City) by aylar sefidgar, Hamed Kheirollahi Meidani, Mehrdad Moharramzadeh

    Published 2024-01-01
    “…All these activities were conducted under strict supervision to prevent external influences and potential errors. The classes were held over two months, with two one-hour sessions each week. 4. …”
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  3. 3383

    Feasibility Assessment of Using Smart Trackers in Telemedicine Systems to Remotely Monitor the Overall Health of Patients in Real-Time by I. V. Pospelova, I. V. Cherepanova, D. S. Bragin, V. N. Serebryakova

    Published 2021-12-01
    “…In order to avoid the high error in measuring systolic pressure, an algorithm for assessing the general health of patients was developed. …”
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  4. 3384

    Adaptation of Everyday Discrimination Scale (EDS) for Nurses: A Validity and Reliability Study in Turkish by Nazan Ulusoy, Hatice Ulusoy, Albert Nienhaus, Patrick Brzoska

    Published 2024-12-01
    “…It improved significantly after addition of two error covariances between items 1 and 2 and items 7 and 8 (RMSEA= 0.051; CFI= 0.982; TLI= 0.973; SRMR= 0.036). …”
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  5. 3385

    Improving TerraClimate hydroclimatic data accuracy with XGBoost for regions with sparse gauge networks: A case study of the Meknes plateau and the Middle Atlas Causse, Morocco by Hammoud Yassine, Allali Youssef, Saadane Abderrahim

    Published 2025-06-01
    “…Applying the XGBoost algorithm significantly improves the raw TerraClimate data, reducing the average Mean Absolute Error (MAE) across all parameters from 3.08 to 0.29, and the average Root Mean Square Error (RMSE) from 4.84 to 0.46, and increasing the average Nash-Sutcliffe Efficiency (NSE) from 0.82 to 0.99. …”
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  6. 3386

    How digital therapeutic alliances influence the perceived helpfulness of online mental health Q&A: An explainable machine learning approach by Yinghui Huang, Hui Liu, Maomao Chi, Sujie Meng, Weijun Wang

    Published 2025-05-01
    “…Results The machine learning-based model for predicting perceived helpfulness demonstrated strong performance, achieving an root mean square error of 0.8234 and a mean absolute percentage error of 22.7288%. …”
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  7. 3387

    Accuracy of intertrochanteric osteotomy for patients with slipped capital femoral epiphysis operated with 3D printed patient-specific guides by M. van den Boorn, J. G. G. Dobbe, V. Lagerburg, M. M. E. H. Witbreuk, G. J. Streekstra

    Published 2024-11-01
    “…Conclusion Although the postoperative position improved after surgery with 3D printed surgical guides and plates, there was a residual deviation from the planned position persisted. …”
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  8. 3388

    Ship motion identification model based on enhanced Bi-LSTM by Haozhe ZHANG, Zhibo YANG, Xuguo JIAO, Chengxing LÜ, Peng LEI

    Published 2025-02-01
    “…Finally, using the navigation data of KLVCC2 ships, the prediction effects of the enhanced Bi-LSTM model are compared with those of the Support Vector Machine (SVM), Gate Recurrent Unit (GRU), and long short-term memory (LSTM) models.ResultsThe Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) performance indicators of the enhanced Bi-LSTM model in the test set are lower than 0.015 and 0.011 respectively, and the coefficient of determination(R2)is higher than 0.99913, demonstrating prediction accuracy significantly higher than that of the SVM, GRU, and LSTM models.ConclusionThe proposed enhanced Bi-model has excellent generalization performance and excellent prediction stability and precision, and effectively realizes ship motion identification.…”
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  9. 3389

    A Method for Predicting the Main Indicators of Cardiopulmonary Stress Testing for Patients with Chronic Heart Failure by A. S. Krasichkov, E. Mbazumutima, F. Shikama, E. M. Nifontov

    Published 2020-02-01
    “…Based on the analysis of the data obtained, a method for assessing the peak values of HR and of PC of the patients with chronic heart failure was developed.Conclusion. The relative error of the proposed estimate of the HR peak in most cases was no more than 10 %, which allows it to be used for practical purposes. …”
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  10. 3390

    Tras la recuperación de la quebrada Machángara en Quito by Matheo Vallejo, M. Lenin Lara Calderón

    Published 2024-07-01
    “…Para ello, se propone una metodología combinada que permite obtener un panorama de la problemática, como también un vistazo hacia posibles soluciones a los puntos evidenciados. En conclusión, se destaca la necesidad de implementar medidas y corregir errores de política territorial para reducir los efectos nocivos en la población expuesta y mejorar la calidad urbana de los asentamientos de la quebrada Machángara.   …”
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  11. 3391

    Published population pharmacokinetic models of mycophenolate sodium: a systematic review and external evaluation in a Chinese sample of renal transplant recipients by Tong Gao, Wen Xu, Xiao Li, Qie Guo, Donghua Liu, Xiaolei Zhang, Ping Leng, Jialin Sun

    Published 2025-08-01
    “…In the goodness-of-fit diagnosis and prediction error test based on model prediction, the population prediction data of all models were not good, while the individual prediction data showed that the fitting result of Model 1 was relatively better. …”
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  12. 3392

    Effect of Capsular Tension Ring on Refractive and Morphological Outcomes in Pseudoexfoliative Eyes by Cunha B, Gil P, Rodrigues Alves N, Hipólito-Fernandes D, Maduro V, Feijão J, Alves N

    Published 2025-03-01
    “…In Group 2, a significant hyperopic shift (p=0.035) and 12% of eyes with a prediction error above 1D was observed, which were not seen in Groups 1 or 3. …”
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  13. 3393

    Comparison of the Effectiveness of Gamification, Tracking Patterns, and Visual Gauges in Improving Hand Motor Performance Through Biofeedback by Ayda Ebrahimi, Amir Salar Jafarpishe, Mohsen Vahedi, Marzieh Izadi Laybidi, Somayeh Mohammadi

    Published 2025-12-01
    “…Statistical analysis was conducted using the paired t-test to compare the root mean square error between groups. Results: The pattern-tracking group demonstrated significant motor performance improvement, with a statistically significant difference in root mean square error (P<0.001). …”
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  14. 3394

    Comparison of Predictability in Vault Using NK Formula and KS Formula for the Implantable Collamer Lens Surgery by Xin Zhong, Yan Li, Yuancun Li, Geng Wang, Yali Du, Mingzhi Zhang

    Published 2024-01-01
    “…The two formulas showed no statistically significant difference in absolute prediction error (APE). Conclusion. The NK formula exhibited superior consistency and low predictive error compared to the KS formula in the 12.6 mm ICL group. …”
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  15. 3395

    Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control. by Casey Olives, Joseph J Valadez, Simon J Brooker, Marcello Pagano

    Published 2012-01-01
    “…In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error.…”
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  16. 3396

    Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

    Published 2025-04-01
    “…Compared with the traditional Gaussian fitting algorithm, the demodulation speed of the 1D-CNN-based algorithm is improved by 2.72 times. 1D-CNN shows high stability and low error under different temperature conditions.【Conclusion】1D-CNN has significant advantages in dealing with complex nonlinear relationships and feature extraction, not only superior in computational efficiency and robustness, but also effective in dealing with noise and environmental interference. …”
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  17. 3397

    Assessment of executive functions of poisoning following suicide by Nastaran Eizadi-Mood

    Published 2025-01-01
    “…However, in the commission error component, the mean scores were higher in the patients with recurrent suicide. …”
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  18. 3398

    Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

    Published 2025-07-01
    “…Across various climatic conditions, the average prediction error remains below 2.5%, indicating strong adaptability and stability. …”
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  19. 3399

    Spatial Interpolation Methods of Temperature Data Based on Geographic Information System—Taking Jiangxi Province as an Example by Zihao Feng, Runjie Wang, Xianglei Liu, Ming Huang, Liang Huo

    Published 2024-12-01
    “…At the same time, the method of cross-validation was adopted, and the average error and the root-mean-square error were quoted as the evaluation indexes for accuracy assessment. …”
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  20. 3400

    Methods for assessing integral parameters of arterial stiffness: comparative analysis and new potential by Yu. E. Teregulov, E. A. Atsel, M. S. Maksimova, N. V. Maksumova, S. N. Prokopyeva, F. R. Chuvashaeva

    Published 2020-12-01
    “…This made it possible to calculate the dependence of Ev on SAC and E∑ using regression analysis.Conclusion. Using linear regression, the formula for calculating the Ev using SAC was obtained, which has a high accuracy at a heart rate of 60 to 90 bpm (error, no more than ±5%). …”
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