Indoor Positioning in Wireless Local Area Networks with Online Path-Loss Parameter Estimation by Luigi Bruno, Paolo Addesso, Rocco Restaino

“…It is based on a Sequential Monte Carlo realization of the optimal Bayesian estimation scheme, whose functioning is improved by exploiting the Rao-Blackwellization rationale. …”
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The nonlinear cysteine redox dynamics in the i-space: A proteoform-centric theory of redox regulation by James N. Cobley, Panagiotis N. Chatzinikolaou, Cameron A. Schmidt

“…Their dynamics are inherently nonlinear, context-dependent, and fundamentally constrained by protein copy numbers. Monte Carlo simulations of the human protein PTP1B reveal extensive i-space sampling beyond site-centric models, supporting the “oxiform conjecture”. …”
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Uncertainty Quantification of GEKO Model Coefficients on Compressible Flows by Yeong-Ki Jung, Kyoungsik Chang, Jae Hyun Bae

“…The affine invariant ensemble algorithm (AIES) is selected to characterize the posterior distribution via Markov chain Monte Carlo sampling. Calibrated model coefficients are extracted from posterior distributions obtained through Bayesian inference, which is based on the point-collocation nonintrusive polynomial chaos (NIPC) method. …”
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Optimum Geometric Position of Detectors Around Thick Hydrocarbon Pipes for Deposition Pattern Detection and Scale Thickness Measurement by Rasmieh Zeinavi Mianabi, Ataollah Rabiee, Mohsen Sharifzadeh

“…In this study, using the geometric analysis and Monte Carlo simulation, it is shown that the fan-shaped arrangement of the detectors with certain spacing around the pipe can lead to an optimal measurement of the deposition regime and the scale thickness.…”
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Diffusion rate determines balance between extinction and proliferationin birth-death processes by Hilla Behar, Alexandra Agranovich, Yoram Louzoun

“…   Using a combination of Monte Carlo simulation and percolation theorybased estimations; the asymptotic behavior of such systems is studied.In all studied cases, it turns out that the overall survival of thereactant population in the long run is based on the size and shapeof the reactant aggregates, their distribution in space and the reactantdiffusion rate. …”
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Time-Dependent Reliability Analysis of RC Deep Beams considering Linear/Nonlinear Creep and Shrinkage Using ANFIS Network and MCS by Seyed Bahram Beheshti Aval, Mohsen Ghabdian

“…Due to the complicated and time-consuming nature of the finite element method (FEM), adaptive neuro-fuzzy inference system (ANFIS) and Monte Carlo simulation (MCS) replaced these complex analyses. …”
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A Probabilistic Assessment Model for Train-Bridge Systems: Special Attention on Track Irregularities by Dejun Liu, Lifeng Xin, Xiaozhen Li, Jiaxin Zhang

“…Besides, compared to the Monte Carlo method, the high efficiency and the accuracy of this proposed model are validated. …”
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Low-Voltage Renewable Energy Communities’ Impact on the Distribution Networks by Susanna Mocci, Simona Ruggeri, Fabrizio Pilo

“…By leveraging the software tool OpenDSS and Monte Carlo simulations over an entire year, the analysis captures the inherent variability of load demand and photovoltaic generation, as well as the resulting network imbalances under diverse policy scenarios. …”
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Enhancing imputation accuracy for catch-all missing data mechanisms with DFBETAS and leverage by Fares Qeadan, William A. Barbeau

“…We validate the proposed approach through Monte Carlo simulations with data generating mechanisms based on probability distributions. …”
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The Radiation Impact of Solar Energetic Particle Events on the Moon: A Statistical Study Using Data‐Based Modeling Results by Bailiang Liu, Jingnan Guo, Yubao Wang, Mikhail I. Dobynde

“…In this paper, we use the Radiation Environment and Dose at the Moon (REDMoon) model based on GEometry And Tracking (GEANT4) Monte‐Carlo method to calculate the body effective dose induced by 262 large historical SEP events on the Moon under different shielding depths which can result from the lunar regolith shielding and/or additional aluminum shielding. …”
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Cooperation evolution of dynamic interaction based on threshold in public goods game by Xiangyang XU, Yajie LIU, Jinlong MA

“…To analyze the impact of interaction size on cooperation level and population average payoff in the public goods game with punishment, by combining Monte Carlo simulation with the characteristics of real complex interaction environments, a dynamic interaction domain model was proposed based on a cooperation threshold. …”
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Study on the REV Size of Fractured Rock in the Non-Darcy Flow Based on the Dual-Porosity Model by Yuan Wang, Yu-long Niu, Qiang Feng

“…Combined with fracture networks generated by Monte Carlo Simulation technique, the PPCE is applied to the study on the REV size. …”
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A-priori multi-objective optimization for the short-term dispatch of distributed energy resources by G. Carpinelli, A.R. Di Fazio, S. Perna, A. Russo, M. Russo

“…A validation procedure, based on Monte Carlo simulation, is introduced to determine on a case-by-case basis the best SWM for the short-term dispatch of the DERs. …”
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Study on the Effect of Amygdales on Mechanical Characteristics of Basalt Using the Combined Finite-Discrete Element Method by Shirui Zhang, Shili Qiu, Ping Li, Yongyuan Kou, Pengfei Kou

“…Then, the heterogeneous models (HMs) with prescribed geometric features were generated by the inverse Monte-Carlo (IMC) algorithm. The uniaxial compression experiments based on HMs were conducted to study the mechanism of the crack initiation and propagation in the amygdaloidal basalt. …”
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Cooperative Localization of Multi-Agent Autonomous Aerial Vehicle (AAV) Networks in Intelligent Transportation Systems by S. Shahkar

“…Theoretical derivations and results have been validated through case studies and Monte Carlo simulations, and suggest cooperative localization as a complementary navigation technique to odometery, and other advanced solutions that are available in the literature.…”
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Predicting Wet-Road Crashes Using the Finite-Mixture Zero-Truncated Negative Binomial Model by Ying Chen, Zhongxiang Huang

“…The model is applied to three-year wet-road crash data on 395 divided roadway segments (total 586 km), and the parameters are estimated using the Markov chain Monte Carlo (MCMC) method. Comparison indicates that the proposed FMZTNB model has better fitting performance and is more accurate in predicting the number of wet-road crashes. …”
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Calibration verification for stochastic agent-based disease spread models. by Maya Horii, Aidan Gould, Zachary Yun, Jaideep Ray, Cosmin Safta, Tarek Zohdi

“…The first calibration method is a Bayesian inference approach using an empirically-constructed likelihood and Markov chain Monte Carlo (MCMC) sampling, while the second method is a likelihood-free approach using approximate Bayesian computation (ABC). …”
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Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI by Benjamin C. Tendler

“…Investigations incorporating free-diffusion and tissue-relevant microscopic restrictions (cylinder of varying radius) give excellent agreement to complementary analytical models and Monte Carlo simulations. Experimentally, the time-independent representation is used to derive Tensor and proof-of-principle NODDI estimates in a whole human post-mortem brain. …”
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Conceptual Study on Recriticality Prevention Core Having Duplex Pellets with Neutron Absorber in Outer Core in a Fast Reactor by Toshio Wakabayashi, Makoto Takahashi, Naoyuki Takaki, Yoshiaki Tachi, Mari Yano

“…Analysis by the continuous energy model Monte Carlo code MVP using the JENDL-4.0 nuclear data library revealed that this fast reactor core has large negative reactivity due to fuel melting at the time of a severe accident, so that the core prevents recriticality. …”
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Interpreting convolutional neural networks' low-dimensional approximation to quantum spin systems by Yilong Ju, Shah Saad Alam, Jonathan Minoff, Fabio Anselmi, Han Pu, Ankit Patel

“…Convolutional neural networks (CNNs) have been employed along with variational Monte Carlo methods for finding the ground state of quantum many-body spin systems with great success. …”
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