A year ago today, a violent storm struck the coast of the sleepy Sicilian fishing village of Porticello. High winds and dramatic thunder and lightning are not unheard of around this time of year in ...

Sampling from probability distributions with known density functions (up to normalization) is a fundamental challenge across various scientific domains. From Bayesian uncertainty quantification to ...

Landslide susceptibility assessment is crucial to mitigate the severe impacts of landslides. Although Bayesian network (BN) has been widely used in landslide susceptibility assessment, no study has ...

Numerical optimization plays a vital role in the design of complex engineered systems. Real world engineered systems are seldom designed based on a single objective; rather they involve multiple ...

Scientists from 25 countries have received IAEA training on environmental sampling analysis to help them mitigate the impacts of radioactivity in the environment. The IAEA’s training workshop for the ...

ABSTRACT: This paper introduces the principle of PPS-based adaptive cluster sampling method and its modified HH estimator and HT estimator calculation method. It compares PPS-based adaptive cluster ...

Spiking neural networks (SNNs), as brain-inspired neural network models based on spikes, have the advantage of processing information with low complexity and efficient energy consumption. Currently, ...

Application of rejection sampling and markov chain monte carlo (MCMC) algorithms to approximate bayesian computation (ABC). The project includes application of ABC to model the pharmacokinetics of ...

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