Results 71 to 80 of about 348,082 (329)

Machine Learning‐Driven Multi‐Objective Optimization of Microchannel Reactors for CO₂ Conversion

Advanced Sustainable Systems, EarlyView.
This study introduces a novel method that combines CFD, RSM, and ML to improve a microreactor's performance utilizing the Sabatier reaction. A range of ML models is assessed, and the best one is selected to predict optimal reactor conditions. ML shows the ability to predict performance in just milliseconds, leading to a decrease in computational time ...
Sandeep Kumar, Parmod Kumar, Kuljeet Singh Grewal   +2 more
wiley   +1 more source

Hierarchical optimal designs and modeling for engineering: A case‐study in the rail sector

Applied Stochastic Models in Business and Industry, Volume 38, Issue 6, Page 1061-1078, November/December 2022., 2022
Abstract Complex engineering and technological processes typically generate data with a non‐trivial hierarchical structure. To this end, in this article we propose a full procedure for optimizing such processes through optimal experimental designs and modeling. In order to study a hierarchical structure, several types of experimental factors may arise,
Rossella Berni, Luciano Cantone, Alessandro Magrini, Nedka D. Nikiforova   +3 more
wiley   +1 more source

A Bayesian probability model for Android malware detection

ICT Express, 2022
The unprecedented growth of mobile technology has generated an increase in malware and raised concerns over malware threats. Different approaches have been adopted to overcome the malware attacks yet this spread is still increasing. To combat this issue,
Sharfah Ratibah Tuan Mat, Mohd Faizal Ab Razak, Mohd Nizam Mohmad Kahar, Juliza Mohamad Arif, Ahmad Firdaus   +4 more
doaj  

Fault diagnosis of mine hoist based on fuzzy fault tree and Bayesian network

Gong-kuang zidonghua, 2020
In order to solve problems of low efficiency and poor accuracy of existing mine hoist fault diagnosis methods, a fault diagnosis method of mine hoist based on fuzzy fault tree and Bayesian network was proposed.
ZHANG Mei, XU Tao, SUN Huihuang, MENG Xiangyu   +3 more
doaj   +1 more source

Activation of Glutamatergic Neurons in the Supramammillary Nucleus Promotes the Recovery of Consciousness under Sevoflurane Anesthesia

Advanced Science, EarlyView.
Selective lesioning of SuM glutamatergic neurons promoted the induction of and delayed emergence from sevoflurane anesthesia and increased sevoflurane sensitivity. Optogenetic stimulation of SuM glutamatergic neurons or the SuM‐MS projection promoted behavioral arousal and cortical activation under steady‐state sevoflurane anesthesia and reduced the ...
Jiayan Li, Yehui Wu, Yihan Wang, Yumin Wu, Rong Hu, Si Long, Wenqi Huang, Liming Nie, Zhongxing Wang   +8 more
wiley   +1 more source

A Bayesian homogeneity test for comparing Poisson populations

Applied Stochastic Models in Business and Industry, Volume 38, Issue 6, Page 1158-1171, November/December 2022., 2022
Abstract For a wide class of daily applications in industrial quality control, there may be interest in comparing several Poisson means. A large catalogue of frequentist procedures for this hypothesis testing problem is available. However, some common drawbacks of them are their low power, interpretation of the p$$ p $$‐values for multiple comparison ...
Francisco Javier Girón, María Martel–Escobar, Francisco–José Vázquez–Polo   +2 more
wiley   +1 more source

A Software Tool for Estimating Uncertainty of Bayesian Posterior Probability for Disease

Diagnostics
The role of medical diagnosis is essential in patient care and healthcare. Established diagnostic practices typically rely on predetermined clinical criteria and numerical thresholds.
Theodora Chatzimichail, Aristides T. Hatjimihail   +1 more
doaj   +1 more source

A Bayesian Statistics Course for Undergraduates: Bayesian Thinking, Computing, and Research [PDF]

arXiv, 2019
We propose a semester-long Bayesian statistics course for undergraduate students with calculus and probability background. We cultivate students' Bayesian thinking with Bayesian methods applied to real data problems. We leverage modern Bayesian computing techniques not only for implementing Bayesian methods, but also to deepen students' understanding ...
arxiv  

A Multi‐Objective Molecular Generation Method Based on Pareto Algorithm and Monte Carlo Tree Search

Advanced Science, EarlyView.
Pareto Monte Carlo Tree Search Molecular Generation (PMMG), a molecular generation approach leveraging Monte Carlo Tree Search (MCTS) and Pareto algorithm, efficiently explores the Pareto front in high‐dimensional objective spaces for multi‐objective drug design.
Yifei Liu, Yiheng Zhu, Jike Wang, Renling Hu, Chao Shen, Wanglin Qu, Gaoang Wang, Qun Su, Yuchen Zhu, Yu Kang, Peichen Pan, Chang‐Yu Hsieh, Tingjun Hou   +12 more
wiley   +1 more source

Model Multinomial Bayesian Network pada Data Simulasi Curah Hujan

Statistika, 2012
Bayesian Networks is one of simple Probabilistic Graphical Models are built from theory of bayes probability and graph theory. Probability theory Is directly related to data while graph theory directly related to the form representation to be obtained ...
Nanda Arista Rizki, Syaripuddin Syaripuddin, Sri Wahyuningsih   +2 more
doaj