Pose measurement method for coal mine drilling robot based on deep learning by Jiangnan LUO, Jianping LI, Hongxiang JIANG, Deyi ZHANG

“…This method consists of two parts: a segmentation model based on an improved PointNet++ and a point cloud registration process using the drill head and gripper. …”
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Marine motor fault diagnosis based on CEEMDAN and BRECAN under strong noise conditions by Renjie ZHU, Enzhe SONG, Chong YAO, Yun KE

“…Next, the BRECAN network is constructed, based on the principle of Variational Bayesian (VI-Bayesian ) using the network parameters instead of the traditional network point estimation training method, the parameters are built to simulate the interference of synthetic noise on the model training, and the network is guided by the Residual Efficient Channel Attention (RECA) module to extract the fault difference features. …”
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Forecasting Area, Production and Productivity of Vegetable Crops in Nepal using the Box-Jenkins ARIMA Model by Rabin Thapa, Shivahari Devkota, Sandip Subedi, Babak Jamshidi

“…The model was cross-validated by comparing the point prediction with the actual test series data from 2015/16 to 2019/20. …”
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Set-Word Embeddings and Semantic Indices: A New Contextual Model for Empirical Language Analysis by Pedro Fernández de Córdoba, Carlos A. Reyes Pérez, Claudia Sánchez Arnau, Enrique A. Sánchez Pérez

“…Since we adopt an empirical point of view for the semantic issues, we also provide the keys for the interpretation of the results using probabilistic arguments (to facilitate the subsequent integration of the model into Bayesian frameworks for the construction of inductive tools), as well as in fuzzy set-theoretic terms. …”
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Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…The bagging ensemble method was utilized on top of Bayesian ridge regression, decision tree regression (DT), and weighted least squares regression as the underlying models. …”
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Modelling adrenal steroid profiles to inform monitoring guidance in congenital adrenal hyperplasiaResearch in context by Neil R. Lawrence, Jeremy Dawson, Zi-Qiang Lang, Alessandro Prete, Elizabeth S. Baranowski, Lina Schiffer, Angela E. Taylor, Aude Brac de la Perrière, Angelica Lindén Hirschberg, Anders Juul, Deborah P. Merke, John Newell-Price, D. Aled Rees, Nicole Reisch, Nike Stikkelbroeck, Philippe A. Touraine, Nils Krone, Brian Keevil, Gary S. Collins, Wiebke Arlt, Richard J.M. Ross

“…Cross-correlation showed no lag between serum 17OHP and A4. In CAH, Bayesian multiple change point analysis converged on a 17OHP of 4.5 nmol/l below which in proportion to 17OHP the A4 is lower. …”
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Trends in burden and mortality of congenital birth defects in G20 countries (1990–2021) and predictions for 2022–2040 by Xiangwen Li, Pengfei Qu, Pu Yan, Yule Kou, Jian Song, Di Wu, Jiayi Wang, Siyu Pan, Yufei Liu, Xinrui Li, Rongqiang Zhang

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Source analysis of nitrogen pollution in basin by export coefficient modeling and microbial source tracking with mutual verification by Qian-hang Sun, Jiang-nan Li, Chun-he Zhou, Kun Lei, Wei-jun Jiang

“…The export coefficient model estimated that point-source nitrogen loads were primarily derived from domestic wastewater, whereas non-point source nitrogen loads predominantly originated from rural domestic wastewater and agricultural cultivation. …”
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A neural network design for black-box identification of converter impedance models in arbitrary operating conditions by CHEN Bing, ZHAO Chongbin, JIANG Qirong, WANG Xu, WANG Fangming

“…Considering that the impedance characteristics of AC grid-connected equipment represented by power electronic converters are easily affected by the AC steady-state operating point, quickly deriving an impedance model for any operating condition of the converter using black-box identification can greatly improve the efficiency of stability analysis. …”
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Relative Performance of Model Selection Criteria for Cox Proportional Hazards Regression Based on Kullback’s Symmetric Divergence by Clarisse Houénafa Dete, Bruno Enagnon Lokonon, Kossi Essona Gneyou, Marcel Senou, Romain Glèlè Kakaï

“…The decision on the most suitable model for those data is an essential analysis point. …”
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State-space modelling for infectious disease surveillance data: Stochastic simulation techniques and structural change detection by Christopher D. Prashad

“…Our approach begins with the application of a Kalman smoothing technique, integrated with MCMC for state sampling within local level and seasonal models, alongside Bayesian inference for non-linear dynamic regression models. …”
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Spatial and temporal modeling of the global burden of Cutaneous Leishmaniasis in Brazil: A 21-year ecological study. by Erica Santos Dos Reis, Wandklebson Silva Paz, Rosália Elen Santos Ramos, Caíque Jordan Nunes Ribeiro, Laiza Santos Biano, Márcio Bezerra-Santos, Camila Indiani de Oliveira, Michael Wheeler Lipscomb, Tatiana Rodrigues de Moura

“…These maps were constructed to visualize the inferences from Bayesian spatial statistics and Moran's autocorrelation using the Poisson model. …”
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Efficiency Comparison of New Adjusted Nonparametric and Parametric Statistics Interval Estimation Methods in the Simple Linear Regression Model by Saichon Sinsomboonthong, Juthaphorn Sinsomboonthong

“…Six point estimations were performed, for example, least squares, Bayesian, Jack knife, Theil, optimum-type Theil, and new adjusted Theil–Sen and Siegel methods in the simple linear regression model with 1,000 iterations. …”
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Statistical Analysis of a Generalized Variant of the Weibull Model Under Unified Hybrid Censoring with Applications to Cancer Data by Mazen Nassar, Refah Alotaibi, Ahmed Elshahhat

“…The study focuses on classical and Bayesian estimation frameworks for the model parameters and associated reliability metrics under a unified hybrid censoring scheme. …”
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Characterization and prediction of non-melanoma skin cancer incidence in China: Joinpoint regression and age-period-cohort model. by Su Liang, Tao Sun, Xue Song Jia, Juan Mei Cao, Xue Wang

“…Bayesian age-period-cohort (BAPC) model with integrated nested laplace approximation was used for prediction.…”
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A supervised machine learning statistical design of experiment approach to modeling the barriers to effective snakebite treatment in Ghana. by Eric Nyarko, Edmund Fosu Agyemang, Ebenezer Kwesi Ameho, Louis Agyekum, José María Gutiérrez, Eduardo Alberto Fernandez

“…<h4>Method</h4>We used a MaxDiff statistical experiment design to collect data, and six supervised machine learning models were applied to predict responses whose performance showed an advantage over the other through 6921 data points partitioned using the hold-back validation method, with 70% training and 30% validation. …”
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Data driven models for predicting pH of CO2 in aqueous solutions: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Moein Kafi, Hamed Nikravesh, Maryam Aghel, Erfan Mohammadian, Yousef Kazemzadeh, Reza Azin

“…The boosted trees model optimized with grid search was found to estimate all data points with a residual error of less than 0.15 and an absolute relative error of 4.62 %. …”
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Prediction of tablet disintegration time based on formulations properties via artificial intelligence by comparing machine learning models and validation by Mohammed Ghazwani, Umme Hani

“…Abstract This research assesses multiple predictive models aimed at estimating disintegration time for pharmaceutical oral formulations, based on a dataset comprising nearly 2,000 data points that include molecular, physical, compositional, and formulation attributes. …”
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Using hierarchical drift diffusion models to elucidate computational mechanisms of reduced reward sensitivity in adolescent major depressive disorder by Lei Shen, Ya-xin Hu, Qin-yu Lv, Zheng-hui Yi, Jing-bo Gong, Chao Yan

“…Bayesian hierarchical drift diffusion modeling (HDDM) was employed to determine changes in reward sensitivity and computational process during decision-making. …”
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Assessing the stock status of Megalaspis cordyla in the northern Arabian Sea: a multi-model approach for sustainable fishery management by Muhsan Ali Kalhoro, Muhsan Ali Kalhoro, Jing Sun, Jing Sun, Lixin Zhu, Zhenlin Liang, Chunli Liu, Hasnain Raza

“…This study utilized stock assessment techniques, including the Catch-Based Monte Carlo Maximum Sustainable Yield (CMSY), length-based Bayesian Biomass (LBB), Just Another Bayesian Biomass Assessment (JABBA), and ARIMA models. …”
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