Machine learning-based prediction of pervaporation permeation using physicochemical properties of permeant-membrane and process conditions by Muhammad Mujiburohman, Marwen Elkamel, Farzad Hourfar, Ali Elkamel

“…The correlation coefficients (R) during model training for Type I and Type II were 0.93674 and 0.88332, respectively, while the root mean square errors (RMSE) were 42.2558 and 38.0766, respectively. …”
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A Study of the Thermodynamic Properties of Nd-C and Ce-C TRISO Fission Product Binary Systems by Ryan Varga, Steven J. Cavazos, Elizabeth S. Sooby, Markus H. A. Piro, Bernard W. N. Fitzpatrick

“…The following phase transition temperatures are reported for Ce-C with an error of ±32.7 °C: 20 mol%C—<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>878.6</mn></mrow></semantics></math></inline-formula> °C; 32 mol%C—<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>714.7</mn></mrow></semantics></math></inline-formula> °C and 857 °C; 67 mol%C—<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1138.7</mn></mrow></semantics></math></inline-formula> °C.…”
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Validation of Replicable Pipeline 3D Surface Reconstruction for Patient-Specific Abdominal Aortic Lumen Diagnostics by Edoardo Ugolini, Giorgio La Civita, Moad Al Aidroos, Samuele Salti, Giuseppe Lisanti, Emanuele Ghedini, Gianluca Faggioli, Mauro Gargiulo, Giovanni Rossi

“…Clinical reliability is assessed using the mean absolute errors for diameter and length measurements, respectively, of 1.73 mm and 2.27 mm. …”
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Analytical review of visualization methods for launch and landing of spacecraft with consideration of 64-bit system boundary value issues by Oleksii Vynokur, Iryna Perova, Polina Zhernova

“…However, due to the limitations of 64-bit precision, they are prone to visualization artifacts and computational errors that compromise the accuracy of the simulations. …”
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Establishing a Junior Doctor Digital Network to help implement digital transformation by Marie-Therese Angus, Ragaul Rajagopal, Vivienne MacCallum, Marten Lau

“…Introduction: Electronic prescribing systems provide advanced decision support to reduce medication errors, adverse drug interactions, and transcription mistakes.1 Thus, effective electronic prescribing is vital for enhancing patient safety and care. …”
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Study on natural gas metering technology and pricing methods in China by Yunyun XIE, Yao SU, Pengtao LI, Fan ZHANG, Wenyao LIU, Jianwen GUO

“…Additionally, there will be a gradual transition from traditional volumetric metering to energy-based metering in custody transfer. …”
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The potential &amp; limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…This proposed methodology demonstrates an average 42x improvement in feature matching between CVGL image pairs, which improves on inconsistent baseline methodology by reducing translation errors between 50%–75%.…”
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Evaluating the Effectiveness of Artificial Intelligence in Prostate Cancer Detection using Biparametric Magnetic Resonance Imaging: A Comparative Study by Rossy Vlăduţ TEICĂ, Ioana Andreea GHEONEA

“…The software proved beneficial in 94 cases (52%) by reducing lesion identification time by 10-15% and prompted a reassessment of initial diagnoses in seven cases (4%). Among the 49 errors recorded by Mediaire's AI, 57% occurred in the transitional zone and 43% in the peripheral zone. …”
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Dynamic Balance Correction of Active Magnetic Bearing Rotor Based on Adaptive Notch Filter and Influence Coefficient Method by Xudong Guan, Hao Peng, Hui Li, Jiajing Zhang

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Weighted-Combined Model for Reclaimed Foundation Settlement Prediction in Coastal Sludge-Bearing Composite Stratum by Boyan Li, Zaobao Liu, Wen Chen, Ziang Li, Xilei Ma, Jing Zhang

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Using traffic data to identify land-use characteristics based on ensemble learning approaches by Jiahui Zhao, Zhibin Li, Pan Liu

“…The result averages improved 12.63%, 12.84%, 11.05%, 5.44%, 12.84% for Area Under ROC Curve (AUC), Classification Accuracy (CA), F-Measure (F1), Precision, and Recall, respectively, in classification tasks and 56.81%, 21.20%, 47.29% for Mean Squared Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE), respectively, in regression tasks than other models. …”
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Deciphering Design of Aggregation‐Induced Emission Materials by Data Interpretation by Junyi Gong, Ziwei Deng, Huilin Xie, Zijie Qiu, Zheng Zhao, Ben Zhong Tang

“…The fingerprints are readily interpretable and have demonstrated promising efficacy in addressing influences related to the photophysics of organic light‐emitting materials, achieving high accuracy and precision in the regression of emission transition energy (mean absolute error (MAE) ∼ 0.13eV) and the classification of optical features and excited state dynamics mechanisms (F1score ∼ 0.94). …”
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Use of artificial neural network for optimization of irreversibility analysis in radiative Cross nanofluid flow past an inclined surface with convective boundary conditions by Ali Farhan, Zaib Aurang, Zafar Syed Sohaib, Khan Umair, Ahmed Muhammad Faizan, Elattar Samia, Khashi’ie Najiyah Safwa

“…To evaluate the correctness of the proposed model, the results of training, testing, and validation are analyzed using the performance charts, error histograms, transition state analysis, comparisons between bvp4c and ANN, and regression plots. …”
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Explosion characteristics and overpressure prediction of hydrogen-doped natural gas under ambient turbulence conditions by Ranran Li, Zhongmo Xu, Mingzhi Li, Shuhong Li, Zhenyi Liu, Zihao Xiu, Qiqi Liu

“…The proposed model achieves a root mean square error of 0.140 kPa under various wind speed conditions, demonstrating good predictive accuracy.…”
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Automatic pelvic fracture segmentation: a deep learning approach and benchmark dataset by Yanzhen Liu, Sutuke Yibulayimu, Gang Zhu, Chao Shi, Chendi Liang, Chunpeng Zhao, Xinbao Wu, Yudi Sang, Yu Wang, Yu Wang

“…The traditional manual slice-by-slice segmentation by surgeons is time-consuming, experience-dependent, and error-prone. The complex anatomy of the pelvic bone, the diversity of fracture types, and the variability in fracture surface appearances pose significant challenges to automated solutions.MethodsWe propose an automatic pelvic fracture segmentation method based on deep learning, which effectively isolates hipbone and sacrum fragments from fractured pelvic CT. …”
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Study on the evolution of regional future drought-flood abrupt alternation events by Yanqi Wei, Haichao Li, Yuliang Zhou, Nii Amarquaye Commey, Juliang Jin, Ping Zhou

“…Study region: Bengbu City, situated on the transition zone between southern and northern China. …”
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Simple Polynomial Reissner–Mindlin Shell Model and Its Application in Efficient Analysis of Complex Underground Structures by Jingxu Chen, Jihui Huang, Yifeng Peng

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Cyber epidemic spread forecasting based on the entropy-extremal dynamic interpretation of the SIR model by Viacheslav Kovtun, Krzysztof Grochla, Mohammed Al-Maitah, Saad Aldosary, Tetiana Gryshchuk

“…The empirical results are characterized by a significant reduction in the Mean Absolute Percentage Error regarding the etalon data over the prediction interval, which proves the adequacy of the proposed approach.…”
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AI-driven design: powered by large language model and intelligent computation by Guodong Sa, Zhinan Li, Zhenyu Liu, Jianrong Tan

“…Conventional experience-driven design approaches exhibit fundamental limitations when confronting high-dimensional parameter spaces, complex multidisciplinary coupling effects, and dynamic performance prediction requirements, rendering trial-and-error iterative optimization processes inefficient and incapable of achieving optimal solutions. …”
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Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…Abstract The transition to sustainable energy has become imperative due to the depletion of fossil fuels. …”
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