Research on the Dynamic Modeling of Rigid–Flexible Composite Spacecraft Under Fixed Constraints Based on the ANCF by Jiaqi Wu, Guohua Kang, Junfeng Wu, Chuanxiao Xu, Jiayi Zhou, Xinyong Tao, Yinmiao Hua

“…The proposed model exhibits displacement errors less than 1 mm, highlighting its efficiency and accuracy.…”
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Assessing the Reliability of Predicted Decadal Surface Temperatures in Southeast Asia by Dara Kasihairani, Rahmat Hidayat, Supari Supari

“…The metrics of Anomaly Correlation Coefficient (ACC) and Mean Error (ME) are employed to assess the model outputs, with 51 hindcast datasets spanning initial years from 1960 to 2010 and ERA5 reanalysis data serving as the reference. …”
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Ensemble learning methods with single and multi-model deep learning approaches for cephalometric landmark annotation by S. Rashmi, S. Srinath, R. Rakshitha, B. V. Poornima

“…The ensemble meta-model further boosts accuracy to 83.61% and 95.4%, respectively, reducing mean radial errors by 0.38 mm and 0.33 mm. These results highlight significant improvements in accuracy and error reduction through strategic combinations of deep learning architectures and ensemble techniques demonstrating the ability to significantly enhance cephalometric landmark annotation accuracy, which is critical for the practical applicability of the methodology.…”
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Cable Force Optimization of Circular Ring Pylon Cable-Stayed Bridges Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization by Shengdong Liu, Fei Chen, Qingfu Li, Xiyu Ma

“…It achieves over 80% reduction in computational costs while enhancing critical structural performance metrics. …”
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Medical VR Simulator for Pediatric Strabismus Treatment by Artem Obukhov, Elena Kutimova, Julia Matrosova, Daniil Teselkin, Maxim Shilcin

“…In terms of exercise quality metrics, a selected subgroup of participants who have been training for a long time have shown positive dynamics in terms of improved accuracy and a reduction in their average number of errors. In summary, virtual reality technologies demonstrated a statistically significant improvement in the metrics used to evaluate orthoptic treatment in the control group and the superiority of this approach over standard treatment.…”
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An Integrated Model for Dam Break Flood Including Reservoir Area, Breach Evolution, and Downstream Flood Propagation by Huiwen Liu, Zhongxiang Wang, Dawei Zhang, Liyun Xiang

“…Although the relative error of the completion time of the final breach is greater than 10%, it is about 30% less than the relative error of the physical model.…”
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Hybrid machine learning-enabled multivariate bridge-specific seismic vulnerability and resilience assessment of UHPC bridges by Tadesse G. Wakjira, M. Shahria Alam

“…The hybrid ML-enabled multi-variate bridge-specific fragility analysis results are used to investigate the functionality recovery and resilience of the bridge, which demonstrate the reduction in the residual functionality and overall bridge resilience with the increase in the ground motion intensity.…”
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Enhancing Multi-Flight Unmanned-Aerial-Vehicle-Based Detection of Wheat Canopy Chlorophyll Content Using Relative Radiometric Correction by Jiale Jiang, Qianyi Zhang, Shuai Gao

“…The predictive accuracy of CCC models improved after the relative radiometric correction, with validation errors decreasing by 17.1–45.6% across different growth stages and with full-season integration yielding a 44.3% reduction. …”
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The Direct Assimilation of Radar Reflectivity Data with a Two-Moment Microphysics Scheme for a Landfalling Typhoon in an OSSE Framework by Ziyue Wang, Jingyao Luo, Hong Li, Yijie Zhu, Rui He

“…Though the most notable reduction in the Root Mean Square Errors (RMSEs) is observed through mixing the ratio of rainwater and snow, the analysis of other variables is also significantly improved with the accumulation of assimilation cycles. …”
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Exploring the Effect of a Wavy Sea Surface on NLOS-UOWC Systems: A Novel Deterministic Approach by Paulo Samaniego-Rojas, Rubén Boluda-Ruiz, José María Garrido-Balsells, Beatriz Castillo-Vázquez, Antonio Puerta-Notario, Antonio García-Zambrana

“…These findings enhance the preliminary considerations in NLOS link design, particularly in scenarios with autonomous underwater vehicles in constant motion, aiding in the reduction of pointing errors.…”
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GPS/VIO integrated navigation system based on factor graph and fuzzy logic by M. M. Karimi, M. R. Mosavi

“…These techniques involve optimizing image data by adjusting contrast and brightness levels and applying noise reduction to the Inertial Measurement Unit (IMU) data. …”
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Compact H-Plane CLAF-SIW Horn Antenna With Phase Front Correction by Andres Biedma-Perez, Cleofas Segura-Gomez, Angel Palomares-Caballero, Pablo Padilla

“…By tuning the distribution of the unit cells of the metalens, it is possible to reduce phase errors at the aperture, a common issue in horn antennas. …”
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Multiresponse Optimization of Wire Electrical Discharge Machining Parameters for Ti-6Al-2Sn-4Zr-2Mo (α-β) Alloy Using Taguchi-Grey Relational Approach by A. Perumal, C. Kailasanathan, Balasubramaniam Stalin, S. Suresh Kumar, P. R. Rajkumar, T. Gangadharan, G. Venkatesan, N. Nagaprasad, V. Dhinakaran, Ramaswamy Krishnaraj

“…Wire electrical discharge machining with Ti-6242 alloy to optimum conditions resulted in better MRR and surface integrity with good surface finish and integrity as evidenced by a substantial reduction in the crack formation, lumps, and accumulated surfaces.…”
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Implementation of an Advanced Macroelement Beam Model under Moving Load (Case Study: Iranian Railroad Projects) by Hamid Reza Vaziri, Mohammad Reza Mansoori, Fereydoon Arbabi, Armin Aziminejad

“…The latter is to use moving elements to ensure that the loads do not approach the boundaries of the model, thus leading to boundary errors. Accordingly, the moving element was formulated at different velocities to allow correct evaluation of the trains’ acceleration and deceleration effect. …”
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Robust Photovoltaic Power Forecasting Model Under Complex Meteorological Conditions by Yuxiang Guo, Qiang Han, Tan Li, Huichu Fu, Meng Liang, Siwei Zhang

“…However, traditional PV power forecasting models designed for distributed PV power stations often struggle with accuracy due to unpredictable meteorological variations, data noise, non-stationary signals, and human-induced data collection errors. To effectively mitigate these limitations, this work proposes a dual-stage feature extraction method based on Variational Mode Decomposition (VMD) and Principal Component Analysis (PCA), enhancing multi-scale modeling and noise reduction capabilities. …”
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Predictive Machine Learning Approaches for Supply and Manufacturing Processes Planning in Mass-Customization Products by Shereen Alfayoumi, Amal Elgammal, Neamat El-Tazi

“…It demonstrated up to a 37% reduction in both time and cost for orders compared to traditional expert estimates.…”
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Advanced sentiment analysis in online shopping: Implementing LSTM models analyzing E-commerce user sentiments by Lu Liyuan

“…Sarcasm and irony accounted for 22% of the classification errors, while mixed sentiment accounted for 18%, and implicit accounted for 15%. …”
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Hybrid Improved PSO Algorithm for Soil Property Parameter Estimation by Mude Li, Aiping Shi, Yefan Shi, Tao Zhang, Cu Qu, Lihua Ye

“…For multimodal functions (e.g., F3), PSO-EDO significantly outperforms PSO-WOA (Particle Swarm Optimization-Whale Optimization Algorithm) with a 22.3% reduction in error. Simulation experiments further validate its engineering practicality: in soil parameter estimation, PSO-EDO completes 1000 iterations in just 1.95 s, with key parameters (e.g., sinkage coefficient n) controlled within a 7.32% error margin. …”
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Identification and modelling of applicable wear conditions for stir cast Al-composite by Santanu Sardar, Santanu Kumar Karmakar, Debdulal Das

“…Abstract A comprehensive study of the tribological performance of the Al-Zn-Mg-Cu/Al2O3 composite and its matrix alloy is presented in this paper, with a specific emphasis to identify and model the applicable wear conditions where the composite provides a minimum of 50% reduction in wear rate and 25% lowering of the friction coefficient. …”
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Interpreting the edge angle efficiency of middle palaeolithic lithic assemblage with Artifact-3D – A case study Barwaniya W1, North Karanpura Valley, Eastern India by Shubham Rajak, Pronil Das

“…This research has digitally measured the Middle Palaeolithic quartzite flake-based assemblage from Barwaniya W1 and their working edge angle, parallel edge (thick blunt side used for hafting), and centre of gravity with Artefact-3D software which has provided us with precise measurement without human errors and ambiguity. Further, this research has replicated the quartzite lithic assemblage of Barwaniya W1 with the Levallois reduction technique to interpret the edge angle efficiency.…”
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