Nonlinear vibration analysis of cantilever beams: Analytical, numerical and experimental perspectives by Qamar Abbas, Rab Nawaz, Haseeb Yaqoob, Hafiz Muhammad Ali, Muhammad Musaddiq Jamil

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Black-box and white-box machine learning tools to estimate the frost formation condition during cryogenic CO2 capture from natural gas blends by Farag M.A. Altalbawy, Fadhel F. Sead, Dharmesh Sur, Anupam Yadav, José Gerardo León Chimbolema, Suhas Ballal, Abhayveer Singh, Anita Devi, Kamal Kant Joshi, Nizomiddin Juraev, Hossein Mahabadi Asl

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Experimental and heat transfer studies of MHP-PV/T by Reynolds number and heat transfer coefficient enhancement by Rui Li, Jinping Li, Junjie Zhu, Xuemin Zhang, Xiao Guo, Vojislav Novakovic

“…Furthermore, in order to reduce the simulation time and facilitate the research, the study establishes the fitting equation of MHP-PV/T surface temperature based on solar radiation intensity and environmental temperature with an average error of 7.6 %. …”
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Accuracy of a step counter during treadmill and daily life walking by healthy adults and patients with cardiac disease by Erik Elgaard Sørensen, John Hansen, Charlotte Brun Thorup, Mette Grønkjær, Jan Jesper Andreasen, Birthe Irene Dinesen

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Comprehensive investigation and evaluation for the different multiphase flow correlations in gas wells by Mohamed A. Abd El-Moniem, Noura Sudan, Ahmed H. El-Banbi

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Predicting Irrigation Water Quality Indices Based on Data-Driven Algorithms: Case Study in Semiarid Environment by Dimple Dimple, Jitendra Rajput, Nadhir Al-Ansari, Ahmed Elbeltagi

“…The accuracy of these models was determined serially using the mean squared error (MSE), correlation coefficients (r), mean absolute error (MAE), and root mean square error (RMSE). …”
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Prediction of Vehicle Interior Wind Noise Based on Shape Features Using the WOA-Xception Model by Yan Ma, Hongwei Yi, Long Ma, Yuwei Deng, Jifeng Wang, Yudong Wu, Yuming Peng

“…The prediction results on the test set demonstrate that the WOA-Xception model attains mean absolute percentage error (MAPE) values of 9.78% and 9.46% and root mean square error (RMSE) values of 3.73 and 4.06, respectively, for sedan and Sports Utility Vehicle (SUV) samples, with prediction trends that align with the measured data. …”
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A Fast-Response Method for Determining the Amplitude of a Signal in Microprocessor Automation and Control Systems with Frequency Fluctuations by Yu. V. Rumiantsev, F. A. Romaniuk, V. Yu. Rumiantsev

“…In this case, both sinusoidal input signals and complex ones, close to the real secondary signals of measuring transformers, were used as test actions. As a result of the research, it was found that the proposed method for determining the amplitude during frequency fluctuations has a performance at the level of a quarter of the period and provides effective elimination of frequency error both in load modes and in damage modes.…”
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Comparison of Least Squares and Some Bias Estimators in Multicollinearity by Furkan Yılmaz, Lütfi Bayyurt, Samet Hasan Abacı, Yalçın Tahtalı

“…For this aim, the effect of some body measurements on body weight (BW), body length (BL), height at withers (HW), height at rump (HR), chest depth (CD), chest girth (CG) and chest width (CW) obtained from 59 Saanen kids at weaning period raised at Research Farm of Tokat Gaziosmanpaşa University. Determination coefficient (R2) and mean square error (MSE) values were used to evaluate the estimation performance of the methods. …”
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PID Sliding Mode Control of PMSM Based on Improved Terminal Sliding Mode Reaching Law by Guodong Qin, Min Wang, Guizhou Cao, Qi Wang, Yuefeng Liao

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Soil-Water Characteristic Curve Model Based on Particle Size Distribution and Pellicular Water by ZHU Shi-wang, LI Shuang-yang, JIANG Qi, ZHAO Jian-yuan, ZHOU Shang-qi, LIU Hui-ying

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Augmenting Fatigue Datasets for Improved Multiaxial Fatigue Strength Prediction with Neural Networks by Napon Opasanon, Leon Josef Stahr, Lukas Suchy, Alexander Hasse

“…This research underscores the potential of data augmentation techniques to enhance machine learning models for fatigue analysis.…”
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A Model Based on Neural Network to Predict Surface Settlement During Subway Station Construction: A Case Study of the Dongba-Zhongjie Station in Beijing, China by Jiaqi Zhang, Hua Jiang, Jinsen Wang, Jili Feng

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Innovation on credit: the role of fintech and institutional quality in global technological advancements by Abhinav Pal, Abel Dula Wedajo, Mohd. Abass Bhat, Chandan Kumar Tiwari, Shagufta Tariq Khan

“…We examine Fintech and Bigtech credit markets, along with institutional quality using two-way error component model (2ECM) and least square dummy variable (LSDV) model estimators to determine their effect on innovation activities. …”
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IoTDQ: An Industrial IoT Data Analysis Library for Apache IoTDB by Pengyu Chen, Wendi He, Wenxuan Ma, Xiangdong Huang, Chen Wang

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Enhanced Output Performance of Two-Level Voltage Source Inverters Using Simplified Model Predictive Control with Multi-Virtual-Voltage Vectors by Hyeongyo Chae, Chan Roh

“…Through simulation and experiments, improved output current THD and current error were observed under various load conditions. …”
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Prediction of Red Mud Bound-Soda Losses in Bayer Process Using Neural Networks by M. Mahmoudian, A. Ghaemi, H. Hashemabadi

“…In the Bayer process, the reaction of silica in bauxite with caustic soda causes the loss of great amount of NaOH. In this research, the bound-soda losses in Bayer process solid residue (red mud) are predicted using intelligent techniques. …”
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Mathematical modeling and statistical analysis of breast cancer drugs using M-polynomial indices for the physical properties by Qasem M. Tawhari, Muhammad Naeem, Saba Maqbool, Abdul Rauf, Oladele Oyelakin

“…Additionally, we proposed the models against each physical property. This research facilitates the design of novel cancer therapeutics and enables the prediction of physical properties for uncharacterized drugs.…”
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Lower-Bound Solution of Foundation-Bearing Capacity under Circular Uniformly Distributed Load by Fang Wei, Wang Jiao, Zhang Wan-dongxing, Shi Li-jun

“…The influence of the amount of stress columns and soil shear strength parameters on the lower-bound solution of the foundation-bearing capacity is analyzed. The research showed that (1) when the number of stress columns is more than 9 (n > 4) and the friction angle is less than 30°, the relative error between the lower-bound solution of the bearing capacity and exact solution is less than 6.6%, (2) the suggested analytical solution is applicable for common clayey materials; thus, the application scope of the analytical lower-bound solution is further expanded, and (3) the influence of cohesion on bearing capacity is linear. …”
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Statistical damage constitutive model of soft rock based on Improved Hoek-Brown strength criterion by Zhenhua Wang, Zecheng Wang, Xin Chen, Gang Wang, Dongwei Li

“…This model provides a more realistic depiction of damage change, failure processes, and stress-strain evolution in soft rock, thereby validating its scientific and rational foundation. The research findings can serve as a valuable reference for mountain tunnel construction.…”
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