A Simple Formula for Local Burnup and Isotope Distributions Based on Approximately Constant Relative Reaction Rate by Cenxi Yuan, Xuming Wang, Shengli Chen

“…Starting from an initial burnup level, the parameters of the formula are fitted to the reaction rates given by a Monte Carlo (MC) calculation. Then the present formula independently gives very similar results to the MC calculation from the starting to high burnup level but takes just a few minutes. …”
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Scatter and Blurring Compensation in Inhomogeneous Media Using a Postprocessing Method by Yan Yan, Gengsheng L. Zeng

“…This 2D-PSF in the inhomogeneous medium is fitted with an asymmetric Gaussian function based on Monte Carlo simulation results. An efficient further blurring and deconvolution method was used to restore images from the spatially variant 2D-PSF kernel. …”
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Bayesian Estimation of Ammunition Demand Based on Multinomial Distribution by Kang Li, Xian-ming Shi, Juan Li, Mei Zhao, Chunhua Zeng

“…Bayesian inference is made through the Markov chain Monte Carlo method based on Gibbs sampling, and ammunition demand at different damage grades is obtained by referring to cumulative damage probability. …”
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Experimental evidence for a shallow cumulate remelting origin of lunar high-titanium mare basalts by Shuchang Gao, Yanhao Lin, Wim van Westrenen

“…These results, compared with Monte-Carlo simulations and modelled rare earth element abundances and samarium–neodymium-lutetium–hafnium isotopic signatures of the experimental melts, remove the requirement of a deep origin of the lunar high-Ti mare basalts. …”
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Heterogeneous UAV Swarm Collaborative Search Mission Path Optimization Scheme for Dynamic Targets by Kaixin Cheng, Tao Hu, Di Wu, Tingli Li, Shu Wang, Kaiyue Liu, Zhifu Tian, Dong Yi

“…Finally, to improve the global searching capability of a UAV, an improved path optimization algorithm PSO-Rolling Horizon Control (PSO-RHC) is designed. Multiple Monte Carlo simulations are performed for three time-sensitive moving target types and three constraint types. …”
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Validation of Simple Equations Describing the Adsorption of Binary Gas Mixtures onto Surfaces with an Asymmetric Distribution of Adsorption Energy by Paweł Szabelski, Krzysztof Nieszporek, Mateusz Drach

“…The Monte Carlo simulation method was used to test the accuracy of approximate equations derived for binary gas adsorption onto a heterogeneous surface characterized by a Dubinin-Astakhov adsorption energy distribution (AED) function. …”
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Stability Optimization of a Disc Brake System with Hybrid Uncertainties for Squeal Reduction by Hui Lü, Dejie Yu

“…The combinational algorithm of Genetic Algorithm and Monte-Carlo method is employed to perform the optimization. …”
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PROBABILITY ANALYSIS ON LAST PLY FAILURE OF COMPOSITE LAMINATES BASED ON UNIVERSAL GENERATING FUNCTION METHOD by LIU ChengLong, ZHOU JinYu, QIU Rui, ZHUANG BaiLiang, HU Jian

“…The reliability value is close to the Monte Carlo simulation results. The new method can provide a new idea for reliability analysis of composite laminates.…”
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Instantaneous Impact Point Guidance with Coast Arcs for Solid Rockets by Shengwei Jia, Fugui Li, Mingbo Tong

“…The proposed guidance method is verified by Monte Carlo simulations, and the testing results demonstrate the adaptability, strong robustness, and excellent performance for different desired impact point missions.…”
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Relay Protection Device Reliability Assessment Through Radiation, Fault Injection and Fault Tree Analysis by Hualiang Zhou, Hao Yu, Zhiyang Zou, Zhantao Su, Zheng Xu, Weitao Yang, Chaohui He

“…This study evaluates the impact of SEE on relay protection devices through a Monte Carlo simulation, which is verified by α-particle radiation, fault injection, and fault tree analysis. …”
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Exploring replica-Potts CFTs in two dimensions by Stefanos R. Kousvos, Alessandro Piazza, Alessandro Vichi

“…The model has been studied in earlier works using perturbation theory, transfer matrices, and Monte Carlo simulations. This work represents an independent non-perturbative analysis. …”
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Evaluating the Effect of Modelling Errors in Load Identification Using Classical Identification Methods by Michael Vigsø, Rune Brincker, Christos Georgakis

“…From a numerical perspective, uncertainty is quantified through Monte Carlo simulations. Two results are outlined: one where the identification process is completely blindfolded in its most naive form, and one where the spatial distribution of the load is predefined. …”
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Aircraft Position Estimation Using Deep Convolutional Neural Networks for Low SNR (Signal-to-Noise Ratio) Values by Przemyslaw Mazurek, Wojciech Chlewicki

“…In the learning process, a database of actual aircraft images was used. Using the Monte Carlo method, four types of Max algorithms, i.e., Pixel Value, Min. …”
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Explaining Unwanted Radial Oscillations in Single-Bubble Sonoluminescence by Mohamad Mansouri, Farough Molaei, Majid Vaezzadeh

“…The authors use the Monte Carlo method to calculate the number of released electrons and demonstrate that the amplitude and frequency of these oscillations can be reduced by manipulating the electron density and energy distribution. …”
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Short‐Term Prediction of the Dst Index and Estimation of Efficient Uncertainty Using a Hybrid Deep Learning Network by Ruyao Wang, Jianhui Wang, Tuo Liang, Huixiong Zhang

“…We also employed the Monte Carlo (MC) dropout technique to estimate the uncertainty and provide the prediction interval by introducing a recalibration factor. …”
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On Particle Swarm Optimization for MIMO Channel Estimation by Christopher Knievel, Peter Adam Hoeher

“…A detailed discussion about the complexity of the PSO algorithm and a comparison to a conventional minimum mean squared error (MMSE) estimator are given. Furthermore, Monte Carlo simulations are provided to illustrate the MSE performance compared to an MMSE estimator.…”
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Reliability analysis of new jointly Type-II hybrid NH censored data and its modeling for three engineering cases by Maysaa Elmahi Abd Elwahab, Ahmed Elshahhat, Ohud A. Alqasem, Mazen Nassar

“…The Bayesian estimates are obtained using the squared error loss function and the Markov Chain Monte Carlo procedure. To assess the performance of these different estimation methods, we conduct a simulation study that incorporates various testing plans. …”
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Analysis and Optimization on Transmission Accuracy of Shoulder Joint Reducer for an Upper Limb Rehabilitation Robot by Zou Shuaidong, Wang Guangjian, Xie Guanghui, Hou Jingming, Yang Renqiang, Sun Fanwei

“…From the perspective of statistics, Monte Carlo method is used to analyze the effects of eccentricity error and initial phase on the transmission accuracy of the shoulder joint of upper limb rehabilitation robots. …”
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The Last and Latest Dickens by Clotilde De Stasio

“…A brief comparison with Carlo Fruttero and Franco Lucentini’s re-writing—The D. …”
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Annealing dynamics of regular rotor networks: Universality and its breakdown by András Grabarits, Gaetano Sammartino, Adolfo del Campo

“…The spin-vector Monte Carlo model is widely used as a benchmark for the classicality of quantum annealers but severely restricts the time evolution. …”
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