Developing a New Spatial Unit for Macroscopic Safety Evaluation Based on Traffic Density Homogeneity by Chen Wang, Lin Liu, Chengcheng Xu

“…In this paper, a new spatial unit was developed using a recursive half-cut partitioning procedure based on a normalized cut (NC) minimization method and traffic density homogeneity. Two Bayesian lognormal models with different conditional autoregressive (CAR) priors were applied to examine the safety effects of traffic flow characteristics at the NC level. …”
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Incorporation of Structural Health Monitoring Coupled Data in Dynamic Extreme Stress Prediction of Steel Bridges Using Dynamic Coupled Linear Models by Xueping Fan, Zhipeng Shang, Guanghong Yang, Xiaoxiong Zhao, Yuefei Liu

“…Firstly, the modeling processes about dynamic coupled linear models (DCLM) are provided based on a supposed coupled time series; furthermore, the dynamic probabilistic recursion processes about DCLM are given with Bayes method; secondly, the monitoring dynamic coupled extreme stress data is taken as a time series, historical monitoring coupled extreme stress data-based DCLM and the corresponding Bayesian probabilistic recursion processes are given for predicting bridge extreme stresses; furthermore, the monitoring mechanism is provided for monitoring the prediction precision of DCLM; finally, the monitoring coupled extreme stress data of a steel bridge is used to illustrate the proposed approach which can provide the foundations for bridge reliability prediction and assessment.…”
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The complete plastid genome of Citrus hystrix DC. 1813 (Rutaceae) and its phylogenetic analysis by Wan Shuan Lee, Warut Donrung, Bui Manh Hung, Nurien Hidayu Muhamad Rusly, Shiou Yih Lee, Tawatchai Tanee

“…Using maximum likelihood and Bayesian inference methods, the phylogenetic analysis of the complete plastome sequence revealed a close relationship between C. hystrix and C. aurantiifolia, placing them under the same clade as C. micrantha.…”
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ASMT: An augmented state-based multi-target tracking algorithm in wireless sensor networks by Kejiang Xiao, Rui Wang, Lei Zhang, Jian Li, Tun Fun

“…Then, multi-target tracking in wireless sensor networks can be implemented by augmented state-based multi-target tracking algorithm as a simplified Bayesian estimation method is adopted. The simulation of multi-target tracking in wireless sensor networks demonstrates that augmented state-based multi-target tracking algorithm has less computation and higher accuracy than traditional method, especially in the implementation of maneuvering targets with intersection.…”
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Morphology and multigene phylogeny revealed four new species of Geastrum (Geastrales, Basidiomycota) from China by Xin Yang, Yonggao Zhu, Songjing Duan, Xingxing Wu, Changlin Zhao

“…Sequences of the internal transcribed spacers (ITS), large subunit (nrLSU), the largest subunit of ribosomal polymerase II (RPB1), and subunit 6 of ATP synthase (ATP6) of the nuclear ribosomal DNA (rDNA) markers of the studied samples were generated, and the phylogenetic analyses were performed with maximum likelihood, maximum parsimony and Bayesian inference methods. The results showed that our collection clustered within Geastrum but distinctly from the others. …”
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Port Environmental Quality or Economic Growth? Their Relevance and Government Preference in Developing Countries by Tingliu Xu, Yingjie Xiao, Chatchai Khiewngamdee, Qin Lin

“…In this contribution, a dynamic stochastic general equilibrium model (DSGE) is constructed with the environmental constraints, and Bayesian estimation is used to calibrate the main parameters. …”
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Gradient Enhancement Techniques and Motion Consistency Constraints for Moving Object Segmentation in 3D LiDAR Point Clouds by Fangzhou Tang, Bocheng Zhu, Junren Sun

“…Additionally, we incorporate Bayesian filtering to impose posterior constraints on predictions, enhancing the accuracy of motion segmentation. …”
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Machine Learning-Based Probabilistic Seismic Demand Model of Continuous Girder Bridges by Wenshan Li, Yong Huang, Zikai Xie

“…Subsequently, PSDMs are established for the IMs and engineering demand parameters based on the existing NTHA data using machine-learning methods, which include linear regression, Bayesian regression (BR), and a tree-based model. The results indicated that random forest (RF) is the most suitable model to predict the longitudinal and transverse curvature at the bottom of the four piers from the coefficients of determination. …”
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Perbandingan Kerja Binomial GLMM Tree dan BIMM Forest untuk Memodelkan Status Bekerja Penduduk by Dwi Agustin Nuriani Sirodj, Khairil Anwar Notodiputro, Bagus Sartono

“…Selanjutnya metode alternatif lainnya adalah Binary Mixed Model (BiMM) Forest yang menggabungkan prinsip kerja Bayesian GLMM dan Random Forest. Dari kedua metode yang akan digunakan maka permasalahan yang dihadapi adalah bagaimana kinerja dari metode GLMM Tree dan BiMM Forest jika diterapkan untuk klasifikasi status bekerja  penduduk di Kabupaten Bogor dan Kabupaten Pangandaran. …”
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Core features of positive mental health in adolescents and their protective role against psychopathology by Desiree Y. Phua, Chermaine S. M. Chew

“…We analyzed data from 1909 adolescents aged 16–19 in Singapore using regular Gaussian Graphic models and Bayesian Directed Acyclic Graphs. Here we report positive self-image as a central upstream node with significant downstream effects on various aspects of well-being. …”
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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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Carbon Market Efficiency and Economic Policy Uncertainty: Evidence from a TVP-VAR Model by Min Liu, Rong Huang, Yang Lu

“…Additionally, it assesses the robustness and accuracy of the empirical results through the Bayesian vector autoregressive (BVAR) model. The findings indicate that EPU negatively affects the green bond market in the short term but has a positive impact in the medium and long term. …”
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Enhancing imputation accuracy for catch-all missing data mechanisms with DFBETAS and leverage by Fares Qeadan, William A. Barbeau

“…DFBETAS, a measure of influence in regression, is adapted to capture the intrinsic information of missing values, thereby enhancing the imputation process within a Bayesian multiple imputation (MI) framework. We validate the proposed approach through Monte Carlo simulations with data generating mechanisms based on probability distributions. …”
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Modified Particle Swarm Optimization on Feature Selection for Palm Leaf Disease Classification by Veri Julianto, Ahmad Rusadi Arrahimi, Oky Rahmanto, Mohammad Sofwat Aldi

“…The PSO modification combined with logistic regression and Bayesian Information Criterion (BIC) significantly enhances KNN performance. …”
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A disproportionality analysis of FDA adverse event reporting system events for misoprostol by Li Yang, Wenting Xu

“…This study used proportional disequilibrium methods such as reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM) to detect AEs. …”
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A Fatigue Life Prediction Method for the Drive System of Wind Turbine Using Internet of Things by Hang Zhou, Shi-Jun Yi, Ya-Fei Liu, Yong-Quan Hu, Yong Xiang

“…In order to solve the above challenges, the fatigue life analysis and evaluation method considering the interaction of coupled multiple damages are proposed in this study. The hierarchical Bayesian theory with fault physics technology is introduced to deal with the uncertainty of wind turbine drive system. …”
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Improved Quantile Convolutional and Recurrent Neural Networks for Electric Vehicle Battery Temperature Prediction by Andreas M. Billert, Runyao Yu, Stefan Erschen, Michael Frey, Frank Gauterin

“…The Q*NN hyperparameters are optimized using an efficient Bayesian optimization, before the Q*NN models are compared with regression and quantile regression models for four horizons. …”
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Estimating Bus Loads and OD Flows Using Location-Stamped Farebox and Wi-Fi Signal Data by Yuxiong Ji, Jizhou Zhao, Zhiming Zhang, Yuchuan Du

“…In this study, we propose a hierarchical Bayesian model to estimate trip-level OD flow matrices and a period-level OD flow matrix using sampled OD flow data collected by Wi-Fi sensors and boarding data provided by fareboxes. …”
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A Dynamic Source Tracing Method for Food Supply Chain Quality and Safety Based on Big Data by Jun Song, Hong Huo, Teng Li, Lingyun Chu

“…At first, this paper summarized the variables of food supply chain quality and safety, constructed a Petri net model and a Bayesian network model for food quality prediction and source tracing, and realized the prediction of food quality features. …”
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Diversity of Rust Fungi with Special Emphasis on <i>Hyalopsora erlangensis</i> Causing Disease in <i>Cystopteris chinensis</i> by An Yu, Xia Zhao, Xiaohong Chen

“…Phylogenetic analysis, based on internal transcribed spacer (ITS) sequences and 28S rDNA gene fragments, further confirms its distinctiveness from other Hyalopsora species, supported by high maximum parsimony (MP), maximum likelihood (ML), and Bayesian inference (BI) bootstrap values. Artificial inoculation both in the field and in tissue-cultured seedlings verified this fungus as the causative agent of <i>C. chinensis</i> rust disease. …”
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