Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

Get full text

Sustainable analysis of COVID-19 Co-packaged paxlovid: exploring advanced sampling techniques and multivariate processing tools by Shymaa S. Soliman, Nisreen F Abo- Talib, Mohamed R. Elghobashy, Mona A. Abdel Rahman

“…Various preprocessing techniques were employed to improve signal quality for PLS construction, yielding superior results (RMSEC of 0.19 for both RNV and NMV) compared to the original, unprocessed spectral data (RMSEC of 0.21 for both RNV and NMV). The Principal Component Analysis score plot was constructed, confirming the consistency of the dataset and the absence of systematic errors, enhancing confidence in the models’ robustness. …”
Get full text

Machine learning prediction and explainability analysis of high strength glass powder concrete using SHAP PDP and ICE by Muhammad Sarmad Mahmood, Tariq Ali, Inamullah Inam, Muhammad Zeeshan Qureshi, Syed Salman Ahmad Zaidi, Muwaffaq Alqurashi, Hawreen Ahmed, Muhammad Adnan, Abdul Hakim Hotak

Get full text

Mitigation of Atmospheric Effects in Deformation Monitoring Using Dual-Polarization MTInSAR and Improved Wavelet Correlation Analysis by Guanxin Liu, Xiaoli Ding, Songbo Wu, Haiqiang Fu, Jianjun Zhu

“…To address this issue, we propose a novel MTInSAR approach that utilizes dual-polarization data and an improved WCA to effectively separate the deformation and APS. …”
Get full text

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis. by Claudia Bühnemann, Simon Li, Haiyue Yu, Harriet Branford White, Karl L Schäfer, Antonio Llombart-Bosch, Isidro Machado, Piero Picci, Pancras C W Hogendoorn, Nicholas A Athanasou, J Alison Noble, A Bassim Hassan

“…We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF) machine learning. …”
Get full text

Mechanical characteristics analysis of coal around borehole based on three-stage constitutive model and its numerical validation by XiuFeng Zhang, Yulin Lu, Haichen Yin, Xun Guo, Hao Wang, Yang Chen

Get full text

Theoretical and Numerical Analysis of Impact Forces on Blocking Piles Within Embankment Breaches Using Flow Velocity Signals by Xing-Huai Huang, Yu Fang, Sheng-Yu Chang, Ying-Qing Guo

“…To assess the accuracy and validity of the proposed theoretical calculation method, a 3D finite element model considering the coupling effect of water flow and pile arrangement was established, and the effects of flow velocity, water depth, and other factors on the force of the plugging structure were studied. A comparative analysis was conducted and indicated that the Morison equation method based on the flow velocity signals can calculate the impact force of the structure within a certain error range when the value of drag force coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>D</mi></mrow></msub></mrow></semantics></math></inline-formula> is set to 1.0 and the value of inertia force coefficient <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>C</mi></mrow><mrow><mi>M</mi></mrow></msub></mrow></semantics></math></inline-formula> is set to 2.0, providing a reference for emergency plugging decisions for embankment breaches. …”
Get full text

Red blood cell transfusion strategy in traumatic brain injury patients: a systematic review and meta-analysis by Jing Wang, Xiang-Hui Li, Jiang-Quan Yu, Rui-Qiang Zheng

“…Results In the results, our analysis revealed that compared to a restrictive transfusion strategy, a liberal strategy did not significantly reduce the risk of ICU mortality (RR: 0.74; 95% CI 0.28–1.91; P = 0.53) and long-term mortality (RR: 1.02; 95% CI 0.83–1.25; P = 0.87), but it was able to reduce the risk of unfavorable functional outcomes (RR: 0.90; 95% CI 0.82–0.98; P = 0.01), although there may be a false positive error. …”
Get full text

Stability analysis of slag heap in “scoop-shaped” valley area based on multi-profile residual thrust method by Yanyan YU, Yi ZHAO, Yi FANG, Minfeng LU, Jiewen ZHU, Zhaohui TANG, Bo CHAI

“…The calculation results of the multi-profile method are smaller than those of the single-profile method, and the residual sliding force on the main profile calculated by the multi-profile method is basically consistent with the monitoring data, with the error of less than 5%. Therefore, the multi-profile residual thrust method has high reliability in calculating the stability of the slag heap slope in the “scoop-shaped” site. …”
Get full text

Surface Deformation Monitoring and Prediction of Longtantian Open-Pit Mine Based on SBAS-InSAR and CNN-BiLSTM Techniques by Xiaoxiao Zhang, Qi Chen, Mengshi Yang, Zhifang Zhao, Yu Zheng, Qixue Dai, Yang He, Dayu Cai, Ting Xu

“…The experimental results show that the CNN-BiLSTM architecture has significantly improved prediction accuracy compared to the basic LSTM model. The prediction error distribution of the original LSTM model is in the range of [&#x2013;196.55, 106.91] mm, while the improved CNN-BiLSTM model reduces the error range to the range of [&#x2013;58.22, 74.33] mm, with extreme error values reduced by 70.40% and 30.47%, respectively. …”
Get full text

Cloud-Integrated Meteorological Parameter Prediction by Leveraging Multivariate Statistical Time Series and GANs by Archana Rout, Biswa Ranjan Senapati, Debahuti Mishra

“…Hence, the present work predicts six important meteorological parameters using the vector autoregression model (VAR), vector moving average model (VMA), vector autoregression moving average model (VARMA), and cointegrated vector autoregression model (CVAR). The comparative analysis demonstrates the superior performance of the CVAR model over other models, as measured by the normalized mean square error (nMSE) and normalized root mean square error (nRMSE) for a single parameter (2.12, 0.3) and (1.21, 0.24) for both the cities, in forecasting all the specified meteorological parameters.…”
Get full text

Application of a Bicubic Quasi-Uniform B-Spline Surface Fitting Method for Characterizing Mesoscale Eddies in the Atlantic Ocean by Chunzheng Kong, Shengyi Jiao, Xuefeng Cao, Xianqing Lv

“…This study focuses on the northern Atlantic Ocean, employing B-spline surface fitting to derive SLA fields from satellite along-track data. The results show strong agreement with in situ measurements, yielding a mean absolute error (MAE) of 1.89 cm and a root mean square error (RMSE) of 3.02 cm. …”
Get full text

Two-dimensional analysis of plasma-derived extracellular vesicles to determine the HER2 status in breast cancer patients by Alexis Wilhelm, Charlotte Flynn, Evelyn Hammer, Johannes Roessler, Bernhard Haller, Rudolf Napieralski, Moritz Leuthner, Sanja Tosheska, Kèvin Knoops, Anjusha Mathew, Giuliano Ciarimboli, Jan Kranich, Lavinia Flaskamp, Siobhan King, Heidrun Gevensleben, Quirin Emslander, Anna Pastucha, Mathias Reisbeck, Lukas Rief, Holger Bronger, Tobias Dreyer, Andreas R. Bausch, Andreas Pichlmair, Thomas Brocker, Reinhard Zeidler, Wolfgang Hammerschmidt, Melanie Piedavent-Salomom, Carmen López-Iglesias, Gabrielle Schricker, Oliver Haydn, Marion Kiechle, Sabine Grill, Ron Heeren, Percy A. Knolle, Olaf Wilhelm, Bastian Höchst

“…In a clinical study of 115 breast cancer patients, this optimised flow cytometric analysis detected a range of 1.3 to 50 × 103 HER2+EVs per µl of plasma. …”
Get full text

Analysis of Academic Information System Using Information System Success Model and System Quality Model Case Study of Institut Teknologi Nasional Malang by Kurnia Dwi setyowati, Totok Chamidy, Muhammad Faisal

Get full text

Assessment of Machine Learning Methods for Concrete Compressive Strength Prediction by Oluwafemi Omotayo, Chinwuba Arum, Catherine Ikumapayi

“…The model performances were evaluated based on mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE) and coefficient of determination (R2). …”
Get full text

Inertial measurement units-based two-dimensional joint angle estimation method of lower limb for running using a camera tracking calibration by Kiyoshi HIROSE, Wako KAJIWARA, Akiko KONDO, Hiroshi NAKANO, Masaki TAKEDA

“…The proposed method employs an extended Kalman filter (EKF) to compensate for drift error and position data from a camera to compensate for mounting error. …”
Get full text

From lab to field with machine learning – Bridging the gap for movement analysis in real-world environments: A commentary by Carlo Dindorf, Fabian Horst, Djordje Slijepčević, Bernhard Dumphart, Jonas Dully, Matthias Zeppelzauer, Brian Horsak, Michael Fröhlich

“…This commentary explores the transformative potential of ML in biomechanics, focusing on enhancing data collection and analysis in real-world environments. …”
Get full text

A Comparative Analysis of the Forecasted Mortality Rate under Normal Conditions and the COVID-19 Excess Mortality Rate in Malaysia by Robiaatul Adawiah Edrus, Zailan Siri, Mohd Azmi Haron, Muhammad Aslam Mohd Safari, Mohammed K. A. Kaabar

Get full text

Prediction and analysis of thermal drift in large-scale tooling reference points under non-uniform temperature field by LI Yan, ZHANG Shang'an, WANG Shouchuan, WEI Hongyang, LI Shuanggao, HOU Guoyi

Get full text

Utilización de redes neuronales para la determinación de respuestas de sitio a partir de Ondas coda Aplicación para Armenia Colombia by Vargas Jiménez Carlos A., Monsalve Hugo, Bermúdez María L., Cuenca Julio C.

Get full text