Experimental and Numerical Study of Shape Memory Alloys for Vibration Amplitude Reduction in Mechanical Structures by Hyginus Chidiebere Onyekachi Unegbu, Danjuma Saleh Yawas, Bashar Dan-asabe, Abdulmumin Akoredeley Alabi

“…A finite element model was developed to simulate the behavior of the system, showing strong correlation with experimental data, with a root mean square error (RMSE) of less than 4%. The validated model was further used to predict SMA performance under conditions not tested experimentally, confirming its reliability for broader applications. …”
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Enhanced Moisture Retrieval Near Boundary Layer From Satellite Sounder Data Through Atmospheric‐Surface Radiance Separation by Ronglian Zhou, Di Di, Jun Li, Zhenglong Li

“…Validated against ERA5 and radiosonde observations, compared with the traditional Rt‐based method, the Ra‐based atmospheric profile retrievals show distinct improvements in boundary‐layer humidity retrieval with at least 20% error reduction. This approach provides a new thought to enhance humidity retrievals from hyperspectral sounders and benefits other quantitative applications such as data assimilation.…”
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Received value flipping based sphere decoding algorithm for polar codes by Rui Wang, Haiqiang Chen, Yan Chen, Yuanbo Liu, Xiangcheng Li, Youming Sun, Qingnian Li

“…Finally, we also verify the applicability of the proposed algorithm over Rayleigh fading channel and observe similar results.…”
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Hardware-Accelerated Infrared Small Target Recognition Based on Energy-Weighted Local Uncertainty Measure by Xiaoqing Wang, Zhantao Zhang, Yujie Jiang, Kuanhao Liu, Yafei Li, Xuri Yao, Zixu Huang, Wei Zheng, Jingqi Zhang, Fu Zheng

“…Infrared small target detection is a key technology with a wide range of applications, and the complex background and low signal-to-noise ratio characteristics of infrared images can greatly increase the difficulty and error rate of small target detection. …”
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DQRNet: Dynamic Quality Refinement Network for 3D Reconstruction from a Single Depth View by Caixia Liu, Minhong Zhu, Haisheng Li, Xiulan Wei, Jiulin Liang, Qianwen Yao

“…With the widespread adoption of 3D scanning technology, depth view-driven 3D reconstruction has become crucial for applications such as SLAM, virtual reality, and autonomous vehicles. …”
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Model based multi-loop predictive control scheme for multivariable processes by Arun Ramaveerapathiran, Muniraj Rathinam, Karuppiah Natarajan, Muthiah Athi, Patil Mounica

“…Abstract Industry applications of multi loop controller approaches are common because of their robustness, minimal tuning parameter, and straightforward design. …”
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Estimating and Downscaling ESA-CCI Soil Moisture Using Multi-Source Remote Sensing Images and Stacking-Based Ensemble Learning Algorithms in the Shandian River Basin, China by Liguo Wang, Ya Gao

“…We compared the predicted SM and ESA-CCI SM; it is evident that the predicted results exhibit a strong correlation with ESA-CCI SM, with a maximum Pearson correlation coefficient (PCC) value of 0.979 and a minimum value of 0.629. The Mean Absolute Error (MAE) values range from 0.002 to 0.005 m³/m³, and the Root Mean Square Error (RMSE) ranges from 0.003 to 0.006 m³/m³. …”
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Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…The average absolute relative error (AARE) of uranium distribution ratio prediction reaches 7.73%, which is about 7% higher than that of the traditional model. …”

High-Throughput DNA Extraction Using Robotic Automation (RoboCTAB) for Large-Scale Genotyping by Vincent-Thomas Boucher St-Amour, Vipin Tomar, François Belzile

“…Efficient and consistent DNA extraction is crucial for genotyping but often hindered by the limitations of traditional manual processes, which are labour-intensive, error-prone, and costly. We introduce a semi-automated, robotic-assisted DNA extraction (RoboCTAB) tailored for large-scale plant genotyping, leveraging advanced yet affordable liquid-handling robotic systems. …”
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Predictive models for overall health of hydroelectric equipment based on multi-measurement point output by Liu Dong, Kong Lijun, Song Jinghui, Zhou Yiming

“…The overall average error has decreased by 55.6%, and the real-time prediction performance has improved by 10.4%. …”
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True-Time-Delay Unit Cell for Ultra-Wideband Single- and Wideband Dual-Polarized Large Reflectarrays by Reza Shamsaee Malfajani, Karim Glatre, Jean-Jacques Laurin

“…This paper presents the design and experimental validation of novel ultra-wideband true-time-delay (TTD) reflectarray unit cells for large-scale antenna applications. Two configurations are proposed: a single-polarized unit cell and a dual-polarized unit cell, both utilizing aperture-coupled stacked microstrip circular patches. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…The results showed that: 1） The Beggs & Bill model and Gray model exhibited poor applicability for predicting the bottom-hole flowing pressure of deep CBM wells, while the single-phase gas model demonstrated reduced overall error as water production declined. …”
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A Soft Sensor Based Inference Engine for Water Quality Assessment and Prediction by Micheal A Ogundero, Theophilus A Fashanu, Foluso O Agunbiade, Kehinde Orolu, Ahmed A Yinusa, Usman A Daudu, Muhammed O H Amuda

“…The developed soft sensor solution is applicable in situations with complete or incomplete instrumentation data. …”
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Soil Hydrothermal Characteristics of Orchard Based on Leaf Area Index Coupled with STEMMUS Model by YANG Yumeng, GAO Xiaodong, SHAO Xiaoya, YANG Min

“…[Results] By optimizing the plant growth parameters, the coupled leaf area development sub-module of the STEMMUS model significantly improved the simulation accuracy of the transpiration and water consumption process of apple trees, with the normalized root mean square error (NRMSE) of the calibration and validation years decreasing from 40.2% and 61.9% in the Original model to 30.0% and 33.2% in the coupled model, respectively, and the mean absolute error (MAE) decreasing from 0.52 and 0.64 mm/d to 0.42 and 0.38 mm/d, respectively. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…In future work, we propose integrating this algorithm into driver assistance systems (ADAS) and exploring its applicability in autonomous vehicles to enhance real-time decision making. …”
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DaGAM-Trans: Dual graph attention module-based transformer for offline signature forgery detection by Sara Tehsin, Ali Hassan, Farhan Riaz, Inzamam Mashood Nasir

“…Its outstanding performance, especially in reducing error rates and handling cross-linguistic signature variability, demonstrates its robustness and applicability for real-world biometric and forensic authentication tasks.…”
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Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin by M. D. Gladyshev, A. V. Rybakov

“…It was also found that the average error along X — 3.11 mm, along Y — 2.92 mm. The average error in angle Z — 1.8°. …”
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Rapid Quality Assessment of Polygoni Multiflori Radix Based on Near-Infrared Spectroscopy by Bin Jia, Ziying Mai, Chaoqun Xiang, Qiwen Chen, Min Cheng, Longkai Zhang, Xue Xiao

“…To further improve the model’s performance and applicability, it is necessary to continuously expand the sample set with different varieties and locations for wide variation.…”
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Navigating cognitive boundaries: the impact of CognifyNet AI-powered educational analytics on student improvement by Mrim M. Alnfiai, Faiz Abdullah Alotaibi, Mona Mohammed Alnahari, Nouf Abdullah Alsudairy, Asma Ibrahim Alharbi, Saad Alzahrani

“…Evaluated through rigorous 5-fold cross-validation on a comprehensive dataset of 1200 anonymized student records and validated across multiple educational platforms, including UCI Student Performance and Open University Learning Analytics datasets, CognifyNet demonstrates superior performance over conventional approaches, achieving 10.5% reduction in mean squared error and 83% reduction in mean absolute error compared to baseline random forest models, with statistical significance confirmed through paired t-tests (p < 0.01). …”
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Empirical modeling of tropospheric delays with uncertainty by J. Wang, J. Wang, J. Wang, J. Chen, J. Chen, J. Chen, Y. Zhang

“…The formal error modeling is based on a similar dataset to that of the GPT series, and thus it is also applicable for these empirical models.…”
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