Performance Analyses and Improvements for IEEE 802.15.4 CSMA/CA Scheme in Wireless Multihop Sensor Networks Based on HTC Algorithm by Jianping Zhu, Chunfeng Lv, Zhengsu Tao

“…Along with these two strategies, the accurate statistical performance metrics of throughput and delay of unsaturated, unacknowledged IEEE 802.15.4 beacon-enabled networks for 1-hop and 2-hop scenarios are then predicted based on the models which contains n modified semi-Markov chains and one macro-Markov chain, in which nodes are assumed to locate randomly over a circle plane according to Poisson distribution. …”
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Modified Stochastic Petri Net-Based Modeling and Optimization of Emergency Rescue Processes during Coal Mine Accidents by Xiao Li, Yongkui Shi, Zaiyong Wang, Wenquan Zhang

“…This paper introduces the stochastic Petri net (SPN) and Markov chain (MC) models based on the system structure flow to analyze the ER processes of coal mine accidents. …”
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Bayesian Inference and Global Sensitivity Analysis for Ambient Solar Wind Prediction by Opal Issan, Pete Riley, Enrico Camporeale, Boris Kramer

“…The UQ framework utilizes variance‐based global sensitivity analysis followed by Bayesian inference via Markov chain Monte Carlo to learn the posterior densities of the most influential parameters. …”
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Heavy Traffic Feasible Hybrid Intracycle and Cyclic Sleep for Power Saving in 10G-EPON by Xintian Hu, Liqian Wang, Zhiguo Zhang, Xue Chen

“…The adoption of cyclic sleep instead of intracycle sleep under light traffic load can reduce unnecessary frequent transitions between sleep and full active work caused by using intracycle sleep. Further, the Markov chain of the proposed mechanism is established. …”
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Unraveling the Kinematic and Morphological Evolution of the Small Magellanic Cloud by S. R. Dhanush, A. Subramaniam, S. Subramanian

“…This analysis is carried out using a robust Markov Chain Monte Carlo method, to derive up to seven kinematic parameters. …”
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Survey the Relationship between Urban Use land Spatial Patterns in the Growth of Urban Growth directions (Case Study: Rasht City) by Rasoul Heidari Sourehjani, Ahmad Ali Beigi

“…Also for horizontal expansion of the city Fuzzy and Cause pattern and Markov chain network in Edrisi software is evaluated and shows that over the course of 18 years Rasht area was 4941.76 hectares It reaches 6202 hectares and represents 1260.243 hectares. …”
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Spatial disparities and dynamics in the high quality agricultural development in Heilongjiang Province of China by Jingting Yu, Guanghao Wu

“…Using the Entropy Weighted-TOPSIS model, Dagum’s Gini Coefficient, and the Markov chain, the study quantifies the HQAD in Heilongjiang from 2013 to 2022, examining regional disparities and development dynamics. …”
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An Overview of Composite Standard Elastic-Net Distribution Based on Complex Wavelet Coefficients by Tahani A. Aloafi, Hassan M. Aljohani

“…A simulated investigation is studied using the Markov Chain Monte Carlo (MCMC) tool to estimate the underlying features, where real data are involved and modelled using the proposed methods. …”
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Statistical analysis of stress–strength in a newly inverted Chen model from adaptive progressive type-Ⅱ censoring and modelling on light-emitting diodes and pump motors by Refah Alotaibi, Mazen Nassar, Zareen A. Khan, Ahmed Elshahhat

“…The Bayes estimates are obtained with the Markov Chain Monte Carlo sampling process leveraging the squared error and LINEX loss functions. …”
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Inferential Statistics from Black Hispanic Breast Cancer Survival Data by Hafiz M. R. Khan, Anshul Saxena, Elizabeth Ross, Venkataraghavan Ramamoorthy, Diana Sheehan

“…We specifically focused on Black Hispanic race. Markov Chain Monte Carlo (MCMC) method was used for obtaining the summary results of posterior parameters. …”
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Integrated land use land cover-energy modeling framework for solar energy planning in the future expansion areas; the case of Luxor city Region, Egypt by Mohammed Hussien Yadem Lamien, Hooman Farzaneh

“…The model integrates Cellular Automata and Markov chain methods to predict future simulated land use land cover and expansion areas, considering the impact of both physical and neighborhood driving factors. …”
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Influence of Uncertainty of Soil Hydraulic Parameters on Stability of Unsaturated Slopes Based on Bayesian Updating by Hsin-Fu Yeh, Tsien-Ting Huang, Ya-Sin Yang, Chien-Chung Ke

“…Bayesian updating was initially used to update the posterior distribution of the SWRC parameters of the model and in situ soil. Subsequently, a Markov Chain Monte Carlo (MCMC) method was used to generate random samples, and the uncertainty of the parameters was analyzed. …”
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Identifying Copy Number Variants under Selection in Geographically Structured Populations Based on -statistics by Hae-Hiang Song, Hae-Jin Hu, In-Hae Seok, Yeun-Jun Chung

“…A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific FST and can identify outlying CNVs loci with large values of FST. …”
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A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition by Hanying Guo, Siying Chen, Yongjiang Zhou, Ting Xu, Yuhao Zhang, Hongliang Ding

“…To minimize redundant information, we propose an improved Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm for selecting the optimal feature subset, ensuring both the efficiency and accuracy of fatigue recognition. …”
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Contrast-Based 3D/2D Registration of the Left Atrium: Fast versus Consistent by Matthias Hoffmann, Christopher Kowalewski, Andreas Maier, Klaus Kurzidim, Norbert Strobel, Joachim Hornegger

“…Moreover, temporal filtering on the obtained registration results of a sequence is applied using a Markov chain framework. Evaluation was performed on 11 well-contrasted clinical angiographic sequences and 10 additional sequences with less CA. …”
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A comparison of Bayesian and frequentist confidence intervals in the presence of a late Universe degeneracy by Eoin Ó. Colgáin, Saeed Pourojaghi, M. M. Sheikh-Jabbari, Darragh Sherwin

“…We explain mathematically why this non-Gaussianity arises and show, using observational Hubble data (OHD), that Markov chain Monte Carlo (MCMC) marginalisation leads to 1D posteriors that fail to track the $$\chi ^2$$ χ 2 minimum at $$68\%$$ 68 % confidence level in high redshift bins. …”
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Measurement of population agglomeration, dynamic change characteristics, and motivations in metropolitan agglomerations-A case study of the Xi'an metropolitan area. by Ke Liu, Xu Bo, Wang Zhaoping, Ran Du, Chen Heng

“…The kernel density estimation method and Markov chain model were used to conduct the study. The results revealed that from 2010 to 2020, the population agglomeration level of the Xi'an metropolitan area showed a trend of first increasing and then decreasing. …”
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Performance characteristics of the fork-join queuing system by V. I. Klimenok

“…The functioning of the system is described in terms of a multidimensional Markov chain. A constructive condition for the existence of a stationary distribution is found, and algorithms for calculating the stationary distribution and stationary performance characteristics of the system are proposed. …”
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Forecast of Freight Volume in Xi’an Based on Gray GM (1, 1) Model and Markov Forecasting Model by Fan Yang, Xiaoying Tang, Yingxin Gan, Xindan Zhang, Jianchang Li, Xin Han

“…In combination with the Markov chain process, the random sequence state is divided into three categories. …”
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Posterior Positivity Distribution Analysis of Subclinical Bluetongue in the Eastern and North-Eastern States of India: A Wakeup Call for Outbreak Preparedness by Siddhartha Narayan Joardar, Aritra Sanyal, Ahmed Abd El Wahed, Saibal Ray

“…With the aim of getting updated and refined estimates of positivity rates, the sero-surveillance data were analyzed using the Markov chain Monte Carlo (MCMC) method to calculate the positivity rates of various species across different states and agro-climatic zones. …”
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