Experimental Study on Hydraulic Characteristics of Trapezoidal Control Gate with Upstream Water Diversion Outlets in Irrigation Area by LI Lin, LIU Yan, WANG Yan-wen, DAI Wen-hong

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Experimental Calibration of Parameters of Discrete Element Model for Ginkgo Nut by Minji Liu, Jiannan Wang, Zhaoyan You, Yanghua Wu, Ni Wang, Huanxiong Xie

“…The stacking angle was found to be 41.12°. The relative error was 3.86%, indicating that the model is reliable and can provide a useful reference for relevant research.…”
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Cognitive Control After ACL Reconstruction: A Cross-Sectional Study on Impaired Proactive Inhibition Compared to Healthy Controls by Jesús Jiménez-Martínez, Alejandro Gutiérrez-Capote, Iker Madinabeitia, David Cárdenas, Francisco Alarcón

“…<b>Background/Objectives</b>: Anterior cruciate ligament (ACL) injury is common in interaction sports and has severe physical and psychological consequences. Recent research suggests that neurocognitive factors, such as proactive inhibitory control, may influence injury risk. …”
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Load Forecast of Electric Trucks Aggregation Based on Higher-order Markov Chains by Hang LIU, Hao SHEN, Yong YANG, Ling JI, Yang YU

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Forecasting Human Core and Skin Temperatures: A Long-Term Series Approach by Xinge Han, Jiansong Wu, Zhuqiang Hu, Chuan Li, Boyang Sun

“…Specifically, the approach of pretraining the model on in-distribution samples followed by fine-tuning markedly outperformed other methods in terms of prediction accuracy, with a prediction error for T_cr within ±0.14 °C and T_{sk, mean} within ±0.46 °C. …”
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Hydrological Drought Assessment of Energy-Based Water Deficit Index (EWDI) at Different Geographical Regions by Chanyang Sur, Dongkyun Kim, Joo-Heon Lee, Muhammad Mazhar Iqbal, Minha Choi

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Filling the data gap between GRACE and GRACE-FO based on a two-step reconstruction method by Fengmin Hu, Beibei Yang, Zushuai Wei, Changlu Cui, Lingkui Meng

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Predicting hydrocarbon reservoir quality in deepwater sedimentary systems using sequential deep learning techniques by Xiao Hu, Jun Xie, Xiwei Li, Junzheng Han, Zhengquan Zhao, Hamzeh Ghorbani

“…The Adam-LSTM model outperformed the others, achieving a Root Mean Square Error of 0.009 and a correlation coefficient (R2) of 0.9995, indicating excellent predictive performance. …”
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A Comprehensive Review of MI-HFE and IPHFE Cryptosystems: Advances in Internal Perturbations for Post-Quantum Security by Yong Wang, Lingyue Li, Ying Zhou, Huili Zhang

“…In light of these challenges, there has been an intensified focus on developing quantum-resistant cryptography. Current research is exploring cryptographic techniques based on error-correcting codes, lattice structures, and multivariate public key systems, all of which leverage the complexity of NP-hard problems, such as solving multivariate quadratic equations, to ensure security in a post-quantum landscape. …”
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Design Flood Calculation Model for Extra-Small Watersheds in Ungauged Basin by Yun Wang, Zengchuan Dong, Xinhua Zhu, Wenzhuo Wang, Yupeng Liu, Ronghao Chen, Yunjia He

“…The calculation results are analyzed in terms of reasonableness through the distribution pattern of the flood peak modulus under different frequencies of the constructed reservoirs, the relative error analysis, and the HEC-RAS model. Based on the one-day flood process of the adjacent basin, the calculation of deducing the design flood process using the hydrological comparison method was proposed. …”
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Design of a multi-view photogrammetric system based on low cost cameras for the 3D forensic face recognition by S. Giuliani, F. Tosti, P. Lopes, C. Ciampini, C. Nardinocchi

“…For the first two test, a quantitative analysis of the reconstruction error was performed by measuring the distance between the generated point cloud and the 3D reference model. …”
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LFEN: A language feature enhanced network for scene text recognition by Hui Chen, Runming Jiang, Fang Hu, Min Chen, Yin Zhang

“…By directly embedding language features into the text recognition model, we effectively address the issue of accuracy in scene text recognition, reducing the potential risk of error accumulation compared to traditional language recognition-text recognition serial connections. …”
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Prediction Analysis of Pre-Camber for Continuous Girder Bridge Cantilever Casting Construction Based on DBO-CNN-BiLSTM-Attention Neural Network by Jinyang Zhang, Haiqing Liu, Xiangen Gong, Ming Lei, Zimu Chen

“…Applying the model proposed in this paper to the cantilever casting stage of the elevated continuous girder bridges in Shenyang Metro, China, enables pre-camber prediction with an accuracy of an average absolute error of less than 2 mm, providing a new efficient method for pre-camber prediction in cantilever casting construction.…”
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Modeling of Exhaust Gas Temperature at the Turbine Outlet Using Neural Networks and a Physical Expansion Model by Alessandro Brusa, Alice Grossi, Mirco Lenzi, Fenil Panalal Shethia, Nicolò Cavina, Ioannis Kitsopanidis

“…Results show an average root mean square error of 14%, including the initial portions of driving cycles performed with a cold engine. …”
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Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike by Hojat Karami, Alireza Rezaei, Amin Atarodi

“…For example, in the combination of all four input data, the amount of root mean square error (RMSE) for SVR-BA was approximately 24% lower and the amount of squared correlation coefficient (R2) was approximately 2% higher, compared to SVR model.…”
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Computer-Aided Diagnosis Techniques for Brain Tumor Segmentation and Classification Using MRI by Gadicha A. B., Kale Prachi V., Dalvi G. D., Mohod M. M., Pakhale S. C., Khan S. M.

“…However, manual interpretation of MRI scans is often time-consuming and prone to human error. In response, artificial intelligence (AI)-based methods, particularly those employing machine learning and deep learning, have shown significant potential in enhancing the accuracy and efficiency of tumor segmentation and classification. …”
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A control strategy for shipboard stabilization platforms based on a fuzzy adaptive proportional–integral–derivative (PID) control architecture by H. Liu, Z. Zeng, X. Yang, Y. Zou, X. Liu

“…Comparative simulations indicate a 50 % reduction in settling time (7.0 <span class="inline-formula">s</span> to 3.5 <span class="inline-formula">s</span>), zero overshoot, and <span class="inline-formula">&lt;</span> 0.03° steady-state tracking error under 2 <span class="inline-formula">Hz</span> sinusoidal excitation. …”
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Dynamic Response and Residual Bearing Capacity of Corroded RC Piers Under Rockfall Impact by Jieqiong Wu, Feiyang Ye, Jian Yang, Jianchao Xu

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Analysis of Inertial Measurement Unit Data for an AI-Based Physical Function Assessment System Using In-Clinic-like Movements by Nobuji Kouno, Satoshi Takahashi, Ken Takasawa, Masaaki Komatsu, Naoaki Ishiguro, Katsuji Takeda, Ayumu Matsuoka, Maiko Fujimori, Kazuki Yokoyama, Shun Yamamoto, Yoshitaka Honma, Ken Kato, Kazutaka Obama, Ryuji Hamamoto

“…A linear regression model using PVV as the input variable achieved a mean absolute error of 1.322 s and a correlation of 0.713 with the measured TUG results during five-fold cross-validation. …”
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Controlled Signal Technique in VL‐NOMA Communication Under Interference‐Controlled Environment With Intelligent Reflecting Surfaces by C. E. Ngene, Prabhat Thakur, Ghanshyam Singh

“…The entire system is successfully synchronized, and then the bit error rate (BER), line of sight (LOS), and non‐line of sight (NLOS) performances are investigated. …”
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