Modeling and Performance for Seabed Airlift Device Based on Pressure Drop by Zhineng WANG, Junwei ZOU, Weiming LIN, Xiaochuan WANG

“…Finally, an experiment is conducted to validate this new model; the results showed that: 1) The new model aligns well with the experimental data with a maximum error of 17.6%. 2) A high gas flow rate increases the pressure drop but reduces the solid fraction. …”
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Effect of Public Health Care Expenditure on Malaria Incidence in Uganda. by Mugabe, Andrew

“…On the contrary, malaria incidence is increased in the long term by female-headed households and GDP per capita, though both factors lead to a short-term decrease, albeit at a slower initial rate. The error correction term (ECT) coefficient, -0.130, was statistically significant at the 1% level. …”
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Prevalence and predictors of statin therapy in the general working-age population by V. S. Kaveshnikov, V. N. Serebryakova, I. A. Trubacheva

“…We used methods of univariate and multivariate statistics. Error probability < 5% was considered significant.Results. …”
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Coffee and tea consumption and glioma risk: a meta-analysis of cohort studies by Jinyu Pan, Chuan Shao, Hui Tang, Nan Wu

“…The analysis explored glioma risk concerning the highest versus lowest levels of coffee and tea intake, supplemented by a dose–response evaluation using a one-stage robust error meta-regression model.ResultsA total of nine studies, published between 2004 and 2020, were included. …”
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Carbon Quota Allocation Prediction for Power Grids Using PSO-Optimized Neural Networks by Yixin Xu, Yanli Sun, Yina Teng, Shanglai Liu, Shiyu Ji, Zhen Zou, Yang Yu

“…Results indicate that the PSO algorithm mitigates local optimization constraints of the standard BP algorithm; the prediction error of carbon emissions by the combined model is significantly smaller than that of the single model, while its identification accuracy reaches 99.46%. …”
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HTSA-LSTM: Leveraging Driving Habits for Enhanced Long-Term Urban Traffic Trajectory Prediction by Yiying Wei, Xiangyu Zeng, Xirui Chen, Hui Zhang, Zhengan Yang, Zhicheng Li

“…In comparison to benchmark models, HTSA-LSTM achieved a 20.72% reduction in the root mean square error (RMSE) and a 24.98% reduction in the negative log likelihood (NLL) for 5 s predictions of long-term trajectories. …”
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RESEARCH INTO SPEECH-TO-TEXT TRANFROMATION MODULE IN THE PROPOSED MODEL OF A SPEAKER’S AUTOMATIC SPEECH ANNOTATION by Olesia Barkovska

“…The following results were obtained: demonstrates the reduction of the word error level descriptor by almost 1.5 times, which influences the quality of word recognition from the audio and may potentially lead to obtaining higher-quality output text data. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…The results show that the proposed prediction model has a root mean square error reduction of about 78.25% and an increase of about 65.63% reliability compared with TCN.DiscussionThe model outperforms traditional methods in terms of accuracy and stability. …”
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Graph2Mat: universal graph to matrix conversion for electron density prediction by Pol Febrer, Peter Bjørn Jørgensen, Miguel Pruneda, Alberto García, Pablo Ordejón, Arghya Bhowmik

“…The novel prediction model also allows for two new and promising measures of uncertainty (total charge error and self-consistency error) that will facilitate its practical usage, e.g. within active learning workflows. …”
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The Effect of Eight Weeks of Motor Control Exercises and Myofascial Release on the Range of Motion of the Lumbar Spine and Disability in People with Non-Specific Chronic Low Back P... by S Jamali Brayjani, M.H Alizadeh, N Rahnama

“…Data analysis was done using repeated measures analysis of variance and Bonferroni's post hoc test at a five percent error level and using SPSS software version 26.ResultsMovement control exercises with and without myofascial release have caused a significant increase in the amount of range of motion of the lumbar spine and significant reduction in the severity of disability of the subjects, after training compared to before training (p<0.001). range of motion of the lumbar spine and severity of disability was not significantly different between the control and experimental groups (p>0.05). …”
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Adaptive Hierarchical Multi-Headed Convolutional Neural Network With Modified Convolutional Block Attention for Aerial Forest Fire Detection by Md. Najmul Mowla, Davood Asadi, Shamsul Masum, Khaled Rabie

“…Additionally, AHMHCNN-mCBAM outperformed HMHCNN-CBAM in recall (25% improvement), precision (21.95%), F1-score (14.94%), and fire detection rate (FDR) reduction (25.01%), while achieving a 100% reduction in error warning rate (EWR). …”
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Cosmology with One Galaxy: Autoencoding the Galaxy Properties Manifold by Amanda Lue, Shy Genel, Marc Huertas-Company, Francisco Villaescusa-Navarro, Matthew Ho

“…In contrast, variations in other parameters such as σ _8 cause negligible error changes, suggesting galaxies shift along the manifold. …”
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Digital Code-Division Multiplexing Channel Aggregation for Mobile Fronthaul Architecture With Low Complexity by Haibo Li, Qi Yang, Songnian Fu, Ming Luo, Xiang Li, Zhixue He, Peng Jiang, Yongpiao Liu, Shaohua Yu

“…After transmission over 5 km SSMF, CWs can be error-free recovered while the LTE signals are recovered with an EVM of &#x223C;3.6&#x0025;.…”
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AI-driven demand forecasting for enhanced energy management in renewable microgrids: A hybrid LSTM-CNN approach by Bashiru olalekan ariyo, mutalub adesina lambe, olalekan ogunbiyi, musa abdulwaheed, bilkisu jimada ojuolape, monsurat omolara balogun

“…Results: The hybrid LSTM-CNN model demonstrated superior performance, achieving an R2 value of 0.87, a Mean Absolute Error (MAE) of 1.45 MWh, and a Root Mean Squared Error (RMSE) of 2.12 MWh. …”
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Pharmacokinetic Model‐Informed Precision Dosing of Natalizumab in Multiple Sclerosis by Stefan P. H. van denBerg, Alyssa A. Toorop, Femke Hooijberg, Gertjan Wolbink, Nivea M. F. Voelkner, Liza M. Y. Gelissen, Joep Killestein, Zoé L. E. vanKempen, Thomas P. C. Dorlo, Theo Rispens

“…Corresponding precision (root mean square error) was 2.3 versus 4.0, and 1.5 versus 5 μg/mL. …”
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A secure and efficient user selection scheme in vehicular crowdsensing by Min Zhang, Qing Ye, Zhimin Yuan, Kaihuan Deng

“…The SEUS-VCS scheme has advantages in reducing loss function (Loss), Mean Square Error (MSE), and Mean Absolute Error (MAE), and the predicted results match the true data very well. …”
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A Predictive Method for Greenhouse Soil Pore Water Electrical Conductivity Based on Multi-Model Fusion and Variable Weight Combination by Jiawei Zhao, Peng Tian, Jihong Sun, Xinrui Wang, Changjun Deng, Yunlei Yang, Haokai Zhang, Ye Qian

“…The experimental results demonstrate that the PCLBX model achieves a mean square error (MSE) of 0.0016, a mean absolute error (MAE) of 0.0288, and a coefficient of determination (R²) of 0.9778. …”
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Study on the localization of tropical cyclone rainfall climatology and persistence model R-CLIPER by Ying LI, Weihua FANG, Yanting YE, Yuejun LI, Yefeng CHEN

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Comparison of Two System Identification Approaches for a Four-Wheel Differential Robot Based on Velocity Command Execution by Diego Guffanti, Moisés Filiberto Mora Murillo, Marco Alejandro Hinojosa, Santiago Bustamante Sanchez, Javier Oswaldo Obregón Gutiérrez, Nelson Gutiérrez, Miguel Sánchez

“…Similarly, the maximum position error averaged 0.522 m for MBM and 0.710 m for SM, confirming that MBM is more accurate and consistent in position tracking. …”
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Frequency Regulation Provided by Doubly Fed Induction Generator Based Variable-Speed Wind Turbines Using Inertial Emulation and Droop Control in Hybrid Wind–Diesel Power Systems by Muhammad Asad, José Ángel Sánchez-Fernández

“…As a result, the FD in the WDPS on San Cristobal Island was reduced by 1.05 Hz, and other quality indices, such as the integral absolute error (IAE), integral square error (ISE), and controller quality index (Z), were improved by 159.65, 16.75, and 83.80%, respectively. …”
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