원자력발전소의 중대사고 발생 시 신속하고 정확하게 사고 상황을 파악해야 하며, 이러한 사고진단 정보를 획득했을 때 적절한 사고관리 및 대응을 수행할 수 있다. 본 연구에서는 국가 원자력 재난관리 시스템인 AtomCARE (Computerized technical Advisory system for a Radiological Emergency)로 전송되는 주요 발전소 정보로부터 중대사고 상황을 진단하는데 있어 딥러닝 기술의 접목을 고려하였다.

Recent advances in computing power have enabled the generation of large datasets for materials, enabling data-driven approaches to problem-solving in materials science, including materials discovery. Machine learning is a primary tool for manipulating such large datasets, predicting unknown material properties and uncovering relationships between structure and property. Among state-of-the-art machine learning algorithms, gradient-boosted regression trees (GBRT) are known to provide highly accurate predictions, as well as interpretable analysis based on the importance of features. Here, in a search for lead-free perovskites for use in solar cells, we applied the GBRT algorithm to a dataset of electronic structures for candidate halide double perovskites to predict heat of formation and bandgap. Statistical analysis of the selected features identifies design guidelines for the discovery of new lead-free perovskites.

In this paper, we analyze the dynamic bifurcation of the general Brusselator model when the order of reaction is p ∈ (1, ∞). We verify that the Turing instability occurs above the critical control number and obtain a rigorous formula for the bifurcated stable patterns.

We present a search for continuous gravitational waves from five radio pulsars, comprising three recycled pulsars (PSR J0437？4715, PSR J0711？6830, and PSR J0737？3039A) and two young pulsars: the Crab pulsar (J0534+2200) and the Vela pulsar (J0835？4510).

We report the observation of a compact binary coalescence involving a 22.2？24.3 M ⊙ black hole and a compact object with a mass of 2.50？2.67 M ⊙ (all measurements quoted at the 90% credible level).

We present results on the mass, spin, and redshift distributions with phenomenological population models using the 10 binary black hole (BBH) mergers detected in the first and second observing runs completed by Advanced LIGO and Advanced Virgo.

We present a multi-messenger measurement of the Hubble constant H 0 using the binary？black-hole merger GW170814 as a standard siren, combined with a photometric redshift catalog from the Dark Energy Survey (DES).