This is the second installment for the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) Quasar Survey, which includes quasars observed from September 2013 to June 2015. There are 9024 confirmed quasars in DR2 and 10911 in DR3. After cross-match with the SDSS quasar catalogs and NED, 12126 quasars are discovered independently. Among them 2225 quasars were released by SDSS DR12 QSO catalogue in 2014 after we finalised the survey candidates. 1801 sources were identified by SDSS DR14 as QSOs. The remaining 8100 quasars are considered as newly founded, and among them 6887 quasars can be given reliable emission line measurements and the estimated black hole masses. Quasars found in LAMOST are mostly located at low-to-moderate redshifts, with a mean value of 1.5. The highest redshift observed in DR2 and DR3is 5. We applied emission line measurements to Hα, Hβ, Mgii and Civ. We deduced the monochromatic continuum luminosities using photometry data, and estimated the virial black hole masses for the newly discovered quasars. Results are compiled into a quasar catalog, which will be available online.

A H ii region is a kind of emission nebula, and more definite samples of H ii regions can help study the formation and evolution of galaxies. Hence, a systematic search for H ii regions is necessary. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) conducts medium-resolution spectroscopic surveys and provides abundant valuable spectra for unique and rare celestial body research. Therefore, the medium-resolution spectra of LAMOST are an ideal data source for searching for Galactic H ii regions. This study uses the LAMOST spectra to expand the current spectral sample of Galactic H ii regions through machine learning. Inspired by deep convolutional neural networks with wide first-layer kernels (WDCNN), a new spectral-screening method, multihead WDCNN, is proposed and implemented. Infrared criteria are further used for the identification of Galactic H ii region candidates. Experimental results show that the multihead WDCNN model is superior to other machine-learning methods and it can effectively extract spectral features and identify H ii regions from the massive spectral database. In the end, among all candidates, 57 H ii regions are identified and known in SIMBAD, and four objects are identified as “to be confirmed” Galactic H ii region candidates. The known H ii regions and H ii region candidates can be retrieved from the LAMOST website.