Time-domain electromagnetic inversion and application for VTI media based on convolutional neural networks by Pan Aohuai, Pan Aohuai, Yan Liangjun, Yan Liangjun, Zhou Lei, Zhou Lei

“…Tests on noisy data demonstrate the model’s noise resistance, with average relative errors remaining within an acceptable range when Gaussian noise below 5% is added. …”
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A systematic review with meta-analysis on the efficacy of 0.01% atropine eyedrops in preventing myopia progression in worldwide children’s populations by Pierluigi Navarra, Luca Buzzonetti, Valentina Amico, Melina Cro, Bruno Federico

“…Atropine was significantly more effective than placebo, with an average reduction of 0.16/year (95% CI: 0.11–0.22) and −0.07/year (95% CI: −0.09 to −0.05) in spherical equivalent refractive errors and axial length, respectively. …”
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OPTIMIZATION OF CONFIGURATION OF INDUSTRIAL ETHERNET NETWORKS DURING DESIGN OF THE AUTOMATED PRODUCTION MANAGEMENT SYSTEM by V. A. Kholopov, E. N. Kashirskaya, M. V. Gusev

“…The results of using the method are: reduction of the number of errors at the working project creation stage; design process structuring; clear requirements formalization; saving man hours of qualified employees in drawing up topologies, specifications and other project documents; reduction of the system cost.…”
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Identifying Factors for Creating Healing Environments by Ghassem Mottalebi, Ladan Vojdanzadeh

“…This can also help increase staff confidence and efficiency leading to a reduction in prescription errors and unwanted spread of infections. …”
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A Dual Filter Based on Radial Basis Function Neural Networks and Kalman Filters with Application to Numerical Wave Prediction Models by Athanasios Donas, Ioannis Kordatos, Alex Alexandridis, George Galanis, Ioannis Th. Famelis

“…Unlike the existing methods, which focus solely on systematic errors, the proposed framework concurrently targets both systematic and non-systematic parts of forecast errors, significantly reducing the bias and variability in significant wave height predictions. …”
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Cole–Cole Model for the Dielectric Characterization of Healthy Skin and Basal Cell Carcinoma at THz Frequencies by Enrico Mattana, Matteo Bruno Lodi, Marco Simone, Giuseppe Mazzarella, Alessandro Fanti

“…Compared with the Double Debye model, a maximum reduction of the RMSE value up to more than 50% and maximum relative percentage errors of 2.8% have been measured for both second and third order Cole-Cole models. …”
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Hysteresis and Eddy Currents Effects Simulation in Idling Mode of the Transformer by Yarymbash D.S., Kotsur M.I., Yarymbash S.T., Divchuk T.Ye.

“…To reduce the error of engineering techniques modifying the circuit-analytical model. …”
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Cost-effectiveness of financial incentives to improve glycemic control in adults with diabetes: A pilot randomized controlled trial. by Leonard E Egede, Rebekah J Walker, Clara E Dismuke-Greer, Sarah Pyzyk, Aprill Z Dawson, Joni S Williams, Jennifer A Campbell

“…Group 1 (low frequency) received a single incentive for absolute HbA1c reduction, Group 2 (moderate frequency) received a two-part incentive for home testing of glucose and absolute HbA1c reduction and Group 3 (high frequency) received a multiple component incentive for home testing, attendance of weekly telephone education classes and absolute HbA1c reduction. …”
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Digital Health Technology Interventions for Improving Medication Safety: Systematic Review of Economic Evaluations by Widya Norma Insani, Neily Zakiyah, Irma Melyani Puspitasari, Muhammad Yorga Permana, Kankan Parmikanti, Endang Rusyaman, Auliya Abdurrohim Suwantika

“…On average, DHT interventions reduced ADEs by 37.12% (range 8.2%-66.5%) and medication errors by 54.38% (range 24%-83%). The key drivers of cost-effectiveness included reductions in outcomes, the proportion of errors resulting in ADEs, and implementation costs. …”
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Sustainable energy: Advancing wind power forecasting with grey wolf optimization and GRU models by Zainab Al-Ibraheemi, Samaher Al-Janabi

“…The proposed approach addresses both larger datasets and the impact of noise samples on prediction errors. Additionally, an MLDDR model was introduced to predict DC power generated from wind datasets, encompassing five stages: Data Preparation, Feature Selection, Data Compression, GRU-Based Predictions, and Rate of Reduction. …”
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Auto-expansion software prompting reduces abbreviation use in electronic hospital discharge letters: an observational pre- and post-intervention study by Shamus Toomath, Emily J Hibbert

“…Post-intervention there was a 34.4% reduction in the total number of abbreviations used, with 1093 abbreviations identified in 200 eDLs. …”
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Nonvariational ADAPT algorithm for quantum simulations by Ho Lun Tang, Yanzhu Chen, Prakriti Biswas, Alicia B. Magann, Christian Arenz, Sophia E. Economou

“…Since it does not rely on a classical optimization subroutine, it may provide robustness against circuit parameter errors due to imperfect control or gate synthesis.…”
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Extending measurement range for three-dimensional structured light imaging with digital exponential fringe pattern by Abel, Kamagara

“…Experimental simulations and results show that within the desired region of defocus or at an extended measurement range, the proposed method exhibits a 45% comparative reduction in root-mean-square phase error hence improvement in final measurement result.…”
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Leveraging social science research to combat poverty and inequality in the Middle East - a pathway to achieving SDGs 1 and 10 by Chadi Azmeh, Hiba Darwich

“…The study analyzes data from 15 Middle Eastern countries from 2000 to 2023 using a panel regression model based on Panel-Corrected Standard Errors (PCSE) and Feasible Generalized Least Squares (FGLS) techniques. …”
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Evaluation of the CRISPR/Cas9 system as genome editing platform for the Mucopolysaccharidosis IV A using a strategy for induction of higher homologous recombination frequency by Diego Alejandro Suarez, Andrés Felipe Leal, Carlos Javier Alméciga Díaz

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A Novel Hybrid Approach for UT1-UTC Ultra-Short-Term Prediction Utilizing LOD Series and Sum Series of LOD and First-Order-Difference UT1-UTC by Fei Ye, Minsi Ao, Ningbo Li, Rong Zeng, Xiangqiang Zeng

“…The evaluation demonstrated promising results: (1) The mean absolute errors (MAEs) of the proposed method range from 21 to 869 µs in 1–10-day UT1-UTC predictions. (2) Comparative analysis against zero-/first-/second-order-difference LS + AR and zero-/first-order-difference LS + MAR hybrid method reveals a substantial reduction in MAEs by an average of 54/64/44 µs, and 47/20 µs, respectively, with the proposed method. (3) Correspondingly, the proposed method achieves average improvement percentages of 17%/18%/15%, and 13%/3% in 1–10-day UT1-UTC predictions.…”
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An improved calibration method for magnetic sensor of multipoint inclinometer by Yi ZHANG

“…In order to improve the calibration accuracy of the inclinometer and its adaptability to random errors, aiming at the problems that the current multi-position calibration method of the inclinometer does not consider the effect of symmetry on error reduction, the measurement error is introduced in angle rotation correction, and the calibration time is reduced, a multi-point calibration and error simulation method is first established. …”
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NUMERICAL MODELING OF SWASH ZONE MORPHOLOGICAL PROCESSES IN COARSE-GRAINED BEACHES WITH XBEACH OPEN-SOURCE MODEL by S. Maleki Taghiabad, M. Adjami, A. Ahmadi

“…The results of this research indicate that the XBeach model has an acceptable performance in modeling hydrodynamic and morphodynamic processes in the Swash region, and simulation with the NH module performs better compared to the SB module (with a reduction in modeling error of over in various models). …”
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Novel sliding mode control of the manipulator based on a nonlinear disturbance observer by Keyou Guo, Haoze Zhang, Caili Wei, Haibing Jiang, Jiangnan Wang

“…Through simulation and comparative experiments conducted using MATLAB/Simulink, the controller model exhibited a 16.4% average reduction in the mean square value of tracking errors compared to existing control strategies, with improvements observed in various performance indicators. …”
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Research on the prediction algorithm of tread wear for locomotive wheels based on GA-ridge regression analysis by FANG Xin, LIU Tong, CHENG Yaping, SUN Yuduo, WANG Feier

“…The results indicate relatively lower prediction errors and standard deviations of errors when using the GA-ridge regression prediction algorithm. …”
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