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.

On 2019 April 25, the LIGO Livingston detector observed a compact binary coalescence with signal-to-noise ratio 12.9. The Virgo detector was also taking data that did not contribute to detection due to a low signal-to-noise ratio, but were used for subsequent parameter estimation.

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 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).

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.

The gravitational-wave signal GW190521 is consistent with a binary black hole (BBH) merger source at redshift 0.8 with unusually high component masses, ${85}_{-14}^{+21}$ M ⊙ and ${66}_{-18}^{+17}$ M ⊙, compared to previously reported events, and shows mild evidence for spin-induced orbital precession.