Structural Health Monitoring of a Reinforced Concrete Building during the Severe Typhoon Vicente in 2012 by Sin-Chi Kuok, Ka-Veng Yuen

“…Besides, the structural response measurements of the monitored building were utilized for modal identification using the Bayesian spectral density approach. Detailed analysis of the field data and the typhoon generated effects on the structural performance are discussed.…”
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Integrative Taxonomy, Phylogeny, and New Species of the Weevil Genus Onyxacalles Stüben (Coleoptera: Curculionidae: Cryptorhynchinae) by Peter E. Stüben, Jonas J. Astrin

“…A molecular phylogeny of the western Palearctic weevil genus Onyxacalles Stüben, 1999 is presented, combining two mitochondrial genes (COI and 16S) in a Bayesian analysis. Based on molecular data, Onyxacalles pyrenaeus Boheman, 1844 is transferred into the genus Kyklioacalles Stüben 1999 (K. fausti group) and—in an integrative taxonomy framework—the interaction between morphology and molecular analysis is illustrated. …”
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Analysis of Network Information Retrieval Method Based on Metadata Ontology by Chunping Wang, Keming Chen

“…This article constructs an LDA three-layer Bayesian model with a three-layer structure of document, topic, and single order. …”
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Scénarios d’accidents occasionnés par une perturbation du mouvement dans les secteurs de la construction et de la métallurgie. Pour une prévention locale et diversifiée by Sylvie Leclercq, Faiza Abdat, Xavier Cuny, Claire Tissot

“…The prevention of injuries caused by collisions, slips, or any other movement disturbance at work represents a major challenge. 143 written accounts of accidents in the construction and metallurgy sectors were analyzed using a Bayesian approach to extract recurrent scenarios. These accounts were characterized by 30 generic factors followed by 8 recurrent scenarios. …”
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Markov Switching Model Analysis of Implied Volatility for Market Indexes with Applications to S&P 500 and DAX by Luca Di Persio, Samuele Vettori

“…We will take into account two different approaches for inference on Markov switching models, namely, the classical approach based on the maximum likelihood techniques and the Bayesian inference method realized through a Gibbs sampling procedure. …”
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A scaling law to model the effectiveness of identification techniques by Luc Rocher, Julien M. Hendrickx, Yves-Alexandre de Montjoye

“…Here, we propose a two-parameter Bayesian model for exact matching techniques and derive an analytical expression for correctness (κ), the fraction of people accurately identified in a population. …”
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Development and application of machine learning models in US consumer price index forecasting: Analysis of a hybrid approach by Yunus Emre Gur

“…The data were combined with key economic indicators of the US, and the hyperparameters of the forecasting models were optimized using genetic algorithm and Bayesian optimization methods. According to the VAR model results, variables such as past values of CPI, oil prices (OP), and gross domestic product (GDP) have strong and significant effects on CPI. …”
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VB-Based Gaussian Sum Cubature Kalman Filter for Adaptive Estimation of Unknown Delay and Loss Probability by Ruipeng Wang, Xiaogang Wang, Haojie Zhang

“…Therefore, a variational Bayesian- (VB-) based Gaussian sum cubature Kalman filter is proposed to solve the nonlinear tracking problem of multistep random measurement delay and loss (MRMDL) with unknown probability. …”
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Teaching Quality Evaluation of Ideological and Political Courses in Colleges and Universities Based on Machine Learning by Lijun Qiao

“…Combined with the weighted Bayesian classification incremental learning principle, the performance of the classification model can be better than the traditional classification model.…”
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Morphological and phylogenetic analyses reveal four novel species of Distoseptispora (Distoseptisporaceae, Distoseptisporales) from southern China by Ming-Gen Liao, Xing-Xing Luo, Ya-Fen Hu, Rafael F. Castañeda-Ruíz, Zhao-Huan Xu, Jian Ma

“…Phylogenetic analyses of ITS, LSU, RPB2, and TEF1 sequence data using maximum-likelihood (ML) and Bayesian inference (BI) methods revealed the systematic placement of several Sporidesmium-like species within Distoseptispora. …”
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Marshall–Olkin Alpha Power Weibull Distribution: Different Methods of Estimation Based on Type-I and Type-II Censoring by Ehab M. Almetwally, Mohamed A. H. Sabry, Randa Alharbi, Dalia Alnagar, Sh. A. M. Mubarak, E. H. Hafez

“…Based on Type-I censored and Type-II censored samples, maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation for the MOAPW distribution parameters are discussed. …”
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Estimation and Control for Industrial Products Reliability under Failure Trials by Kui Wang, Lili Ding

“…The failure trial is performed at different operational time points of the products, which provides sole data source for evaluating the status of industrial products. We use Bayesian approach to dynamically estimate the industrial products when the failure trial is available. …”
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Five New Species of Pezizales from Northeastern China by Zhengqing Chen, Tolgor Bau

“…Maximum likelihood and Bayesian analyses were performed using a combined nuc rDNA internal transcribed spacer region (ITS) and nuc 28S rDNA (nrLSU) dataset for the construction of phylogenetic trees. …”
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Diagnostic Accuracy of Non-Invasive Diagnostic Tests for Nonalcoholic Fatty Liver Disease: A Systematic Review and Network Meta-Analysis by Sun Y, Hu D, Yu M, Liang SB, Zheng Y, Wang X, Tong G

“…Statistical analysis was conducted using R 4.0.3 for Bayesian NMA and STATA 17.0 for pairwise meta-analysis. …”
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An IoT-enhanced automatic music composition system integrating audio-visual learning with transformer and SketchVAE by Yifei Zhang

“…At the same time, the Bayesian optimization mechanism is used to finely adjust the hyperparameters in the system to further improve the model performance. …”
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Dynamic Reliability Prediction of Bridges Based on Decoupled SHM Extreme Stress Data and Improved BDLM by Xueping Fan, Yuefei Liu

“…In this paper, considering the coupling, randomness, and time variation of SHM data, firstly, the coupled extreme stress data, which are considered as a time series, are decoupled into high-frequency and low-frequency data with the moving average method. Secondly, Bayesian dynamic linear models (BDLM) without priori monitoring error data (e.g., unknown monitored error variance) are built to dynamically predict the decoupled extreme stress; furthermore, the dynamic reliability of bridge members is predicted with the built BDLM and first-order second moment (FOSM) reliability method. …”
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Balancing specialization and adaptation in a transforming scientific landscape by Lucas Gautheron

“…Drawing from diverse perspectives on adaptation, this paper proposes an unsupervised Bayesian approach motivated by Optimal Transport of the evolution of scientists’ research portfolios in response to transformations in their field. …”
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Model-Based Dependability Analysis of Physical Systems with Modelica by Andrea Tundis, Lena Buffoni, Peter Fritzson, Alfredo Garro

“…Furthermore, they allow exporting a Modelica-based system design as a Bayesian Network in order to analyze its dependability by employing a probabilistic approach. …”
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Effective Density-Based Clustering Algorithms for Incomplete Data by Zhonghao Xue, Hongzhi Wang

“…To avoid these problems, we develop a novel density-based clustering approach for incomplete data based on Bayesian theory, which conducts imputation and clustering concurrently and makes use of intermediate clustering results. …”
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Statistical Modeling of HIV, Tuberculosis, and Hepatitis B Transmission in Ghana by Clement Twumasi, Louis Asiedu, Ezekiel N. N. Nortey

“…The validity of these comorbidity assertions was statistically determined by exploring the conditional dependencies existing among HIV, TB, and HB through Bayesian networks or directed graphical model. Through Classification tree, sex and age group of individuals were found as significant demographic predictors that influence the prevalence of HIV and TB. …”
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