0.003°/h bias instability of honeycomb disk resonator gyroscope achieved by mode reversal combined mode deflection control method by Liangqian Chen, Qingsong Li, Tongqiao Miao, Peng Wang, Xuhui Zhang, Yang Zhang, Xuezhong Wu, Dingbang Xiao

“…This paper incorporates electrode machining error and capacitance detection nonlinear error into the gyroscope model, resulting in a more comprehensive bias output model. …”
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Long-term trajectory prediction method based on highway vehicle-following behavior patterns by Zhichao An, Yimin Wu, Fan Zhang, Dong Zhang, Bolin Gao, Suying Zhang, Guang Zhou, Aoning Jia

“…In scenarios with two vehicles ahead and conservative short-distance following, the SDVIDM model exhibits reductions of 83.42%, 92.85%, and 92.25%, while the SVIDM model shows reductions of 82.31%, 92.47%, and 94.02%, respectively, compared to the IDM model.…”
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Robust Monocular Visual-Inertial Odometry for Agricultural Vehicles Based on IMU-Augmented 3D Feature Point Correction by Quoc Duy Tran, Quoc Hung Hoang, Gon-Woo Kim

“…The effectiveness of the method is validated through real-time experiments across various scenarios, with the proposed system achieving approximately an 80% reduction in translation error and about a 60% reduction in rotation error compared to state-of-the-art methods. …”
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To What Extent Does Discounting ‘Hot’ Climate Models Improve the Predictive Skill of Climate Model Ensembles? by Abigail McDonnell, Adam Michael Bauer, Cristian Proistosescu

“…On regional scales, we find a heterogeneous pattern of error reduction in future regional precipitation. …”
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Modeling the arousal potential of epistemic emotions using Bayesian information gain: a framework for inquiry cycles driven by free energy fluctuations by Hideyoshi Yanagisawa, Shimon Honda

“…This study proposes a novel formulation of these emotions using two types of information gain derived from the principle of free energy minimization: Kullback–Leibler divergence (KLD), representing free energy reduction through recognition, and Bayesian surprise (BS), representing free energy reduction via Bayesian updating. …”
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A data mining approach for proposing a relationship to predict self-compaction concrete crack width after the self-healing period by Saeid Hosseini, Ali Seyedkazemi, Abdullah Davoudi-Kia, Saman Soleimani Kutanaei

“…This model achieved the lowest errors, with MSE, RMSE, and MAE values of 48.5713, 6.969, and 4.878, respectively, indicating its high accuracy in prediction and error minimization. …”
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Real Time MEMS-Based Joint Friction Identification for Enhanced Dynamic Performance in Robotic Applications by Paolo Righettini, Giovanni Legnani, Filippo Cortinovis, Federico Tabaldi, Jasmine Santinelli

“…An experimental comparison with decentralized and non-adaptive regulators highlights severalfold reductions in tracking errors; the ability to track temperature-dependent friction variations is also shown. …”
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A Novel Adaptive Non-Singular Fast Terminal Sliding Mode Control for Direct Yaw Moment Control in 4WID Electric Vehicles by Jung Eun Lee, Byeong Woo Kim

“…Simulation results across various steering maneuvers, including step, sinusoidal, and fish-hook inputs, demonstrate that the proposed method significantly improves tracking accuracy and driving stability over traditional SMC and NFTSMC methods. Marked reductions in RMS and peak yaw rate errors, and effective chattering mitigation, highlight advancements in vehicle safety and stability.…”
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Research on the blasting effect prediction and blasting parameter optimization based on PCA-PSO-DBN by Weilong Ma, Biao Qiao, Tongkai Wen, Zhanping Song, Zhenzhong Ren

“…The results indicated that compared to traditional DBN and PCA-DBN models, the proposed model reduced maximum errors by 16.98, 7.68, and 11.37, 4.85%, respectively, demonstrating higher precision. …”
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Prediction of Freezing Time During Hydrogen Fueling Using Machine Learning by Ji-Ah Choi, Ji-Seong Jang, Sang-Won Ji

“…The comparison revealed that the maximum error rate occurred after the second refueling, with a value of approximately 4.79%. …”
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Low-Power and Reliable Communications for UWB-Based Wireless Monitoring Sensor Networks in Underground Mine Tunnels by Mohamad Abou El-Nasr, Heba Shaban

“…This minimal degradation in performance is traded for more than 90% reduction in power consumption.…”
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A Bio-Inspired Data-Driven Locomotion Optimization Framework for Adaptive Soft Inchworm Robots by Mahtab Behzadfar, Arsalan Karimpourfard, Yue Feng

“…Experimental results demonstrate that the framework achieves an average 9.88% reduction in required pressure for efficient movement and a 6.45% reduction for stable locomotion, with the neural network enabling robust adaptation to varying surfaces. …”
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A New Hybrid Model for Underwater Acoustic Signal Prediction by Guohui Li, Wanni Chang, Hong Yang

“…The experimental results show that the proposed new hybrid model can provide enhanced accuracy with the reduction of prediction error compared with other existing prediction methods.…”
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Active Vibration Control of Plate Partly Treated with ACLD Using Hybrid Control by Dongdong Zhang, Ling Zheng

“…The Golla-Hughes-Mctavish (GHM) method is employed to describe the frequency-dependent characteristics of viscoelastic material (VEM). A model reduction is completed by using iterative dynamic condensation and balance model reduction method to design an effective control system. …”
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Motion estimation algorithm using 2 bit-depth pixel and fuzzy quantization by Chuan-ming SONG, Yan-wen GUO, Xiang-hai WANG, Dan LIU

“…To further predict the precision of the proposed algorithm, a bit resolution reduction error-motion vector precision model was built by exploiting the auto-correlation function. …”
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Impact assessment of integrated-pathy on anthropometric, physiological, biochemical, and psychological parameters on type 2 diabetes mellitus patients: A single-arm, observational... by Akshay Vashisht, Medha Bhatt, Vedpriya Arya

“…By the end of 45th day a 4.7% reduction in HbA1c levels (p = 0.003), a 9.44% reduction in postprandial glucose (p = 0.46), and a 10.9% reduction in fasting glucose were noted. …”
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Multi‐Satellite Data Assimilation for Large‐Scale Hydrological‐Hydrodynamic Prediction: Proof of Concept in the Amazon Basin by S. Wongchuig, R. Paiva, V. Siqueira, F. Papa, A. Fleischmann, S. Biancamaria, A. Paris, M. Parrens, A. Al Bitar

“…Assimilating WSE outperforms daily discharge and water‐level estimations, achieving 38% and 36% error reduction, respectively. However, the monthly evapotranspiration estimate achieves the greatest error reduction by assimilating SM with 11%. …”
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Meta-analysis of Genetic Parameters for Productive and Reproductive Traits in Laying Hens by Maryam Sokhan, Sheida Varkoohi, Ali Hossein Piray

“…Also, the comparison of the standard error by meta-analysis of desired traits with the range of the standard error in different studies showed that the aggregation of the results of different studies has greatly reduced the standard error of all the genetic parameters for investigated traits, for example, the standard error for heritability of egg weight in the studies was in the range of 0.071-0.18, but by meta-analysis it was reduced to 0.004. …”
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A roll attitude determination method based on the jamming energy of GEO satellites and an LSTM neural network by Rundong Li, Lu Feng, Peng Wu, Xiangling Deng, Haonan Shi

“…After real-time roll attitude testing of a rotating vehicle using different methods, the proposed method is found to be superior to the traditional least squares (LS) method, with a 48.97% reduction in the mean self-error and a 48.20% reduction in the mean Hall standardized error for the determined roll angles. …”
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A Study of Forced Vibrations with Nonlinear Springs and Dry Friction: Application to a Mechanical Oscillator with Very Large Vibrating Blades for Soil Cutting by Dario Friso

“…Measuring the maximum blade displacement compared with the calculated one provided a good accuracy of the mathematical modeling, resulting in a mean error of 5.6% and a maximum error of 7.2%.…”
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