Hui Yuan

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST, also called the Guo Shou Jing Telescope) is a special reflecting Schmidt telescope. LAMOST's special design allows both a large aperture (effective aperture of 3.6 m-4.9 m) and a wide field of view (FOV) (5 degrees). It has an innovative active reflecting Schmidt configuration which continuously changes the mirror's surface that adjusts during the observation process and combines thin deformable mirror active optics with segmented active optics. Its primary mirror (6.67 m x 6.05 m) and active Schmidt mirror (5.74 m x 4.40 m) are both segmented, and composed of 37 and 24 hexagonal sub-mirrors respectively. By using a parallel controllable fiber positioning technique, the focal surface of 1.75 m in diameter can accommodate 4000 optical fibers. Also, LAMOST has 16 spectrographs with 32 CCD cameras. LAMOST will be the telescope with the highest rate of spectral acquisition. As a national large scientific project, the LAMOST project was formally proposed in 1996, and approved by the Chinese government in 1997. The construction started in 2001, was completed in 2008 and passed the official acceptance in June 2009. The LAMOST pilot survey was started in October 2011 and the spectroscopic survey will launch in September 2012. Up to now, LAMOST has released more than 480 000 spectra of objects. LAMOST will make an important contribution to the study of the large-scale structure of the Universe, structure and evolution of the Galaxy, and cross-identification of multi-waveband properties in celestial objects.

We introduce the LAMOST Stellar Parameter Pipeline at Peking University --- LSP3, developed and implemented for the determinations of radial velocity $V_{\rm r}$ and stellar atmospheric parameters (effective temperature $T_{\rm eff}$, surface gravity log\,$g$, metallicity [Fe/H]) for the LAMOST Spectroscopic Survey of the Galactic Anti-center (LSS-GAC). We describe the algorithms of LSP3 and examine the accuracy of parameters yielded by it. The precision and accuracy of parameters yielded are investigated by comparing results of multi-epoch observations and of candidate members of open and globular clusters, with photometric calibration, as well as with independent determinations available from a number of external databases, including the PASTEL archive, the APOGEE, SDSS and RAVE surveys, as well as those released in the LAMOST DR1. The uncertainties of LSP3 parameters are characterized and quantified as a function of the spectral signal-to-noise ratio (SNR) and stellar atmospheric parameters. We conclude that the current implementation of LSP3 has achieved an accuracy of 5.0\,km\,s$^{-1}$, 150\,K, 0.25\,dex, 0.15\,dex for the radial velocity, effective temperature, surface gravity and metallicity, respectively, for LSS-GAC spectra of FGK stars of SNRs per pixel higher than 10. The LSP3 has been applied to over a million LSS-GAC spectra collected hitherto. Stellar parameters yielded by the LSP3 will be released to the general public following the data policy of LAMOST, together with estimates of the interstellar extinction $E(B-V)$ and stellar distances, deduced by combining spectroscopic and multi-band photometric measurements using a variety of techniques.

For the purpose of improving the low detection performance of network intrusion detection model caused by high‐dimensional data, and from the perspective of time correlation characteristics of intrusion detection datasets, the authors present a network intrusion detection model based on the multivariate correlations analysis – long short‐term memory network (MCA‐LSTM). Firstly, this model selects the optimal feature subsets through the information gain feature selection method, the MCA module is then used to change the feature subset into the triangle area map (TAM) matrix, and finally inputs the TAM matrix into the LSTM module for the training and testing purpose. To better demonstrate the performance of the proposed model, it is compared with those of convolutional neural networks, recurrent neural network, deep forest, support vector machine, and k‐nearest neighbour methods proposed by the previous researchers. Experimental results show that the testing accuracy of the proposed model on 5‐classification task using NSL‐KDD dataset is up to 82.15%, and that on 10‐classification task using UNSW‐NB15 dataset is up to 77.74%. Moreover, compared with the traditional machine learning and existing deep learning models, the proposed model has shown to achieve better classification detection performance.

We present new quasars discovered in the vicinity of the Andromeda and Triangulum galaxies with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, also named the Guoshoujing Telescope, during the 2010 and 2011 observational seasons. Quasar candidates are selected based on the available Sloan Digital Sky Survey, Kitt Peak National Observatory 4 m telescope, Xuyi Schmidt Telescope Photometric Survey optical, and Wide-field Infrared Survey Explorer near-infrared photometric data. We present 509 new quasars discovered in a stripe of similar to 135 deg(2) from M31 to M33 along the Giant Stellar Stream in the 2011 pilot survey data sets, and also 17 new quasars discovered in an area of similar to 100 deg(2) that covers the central region and the southeastern halo of M31 in the 2010 commissioning data sets. These 526 new quasars have i magnitudes ranging from 15.5 to 20.0, redshifts from 0.1 to 3.2. They represent a significant increase of the number of identified quasars in the vicinity of M31 and M33. There are now 26, 62, and 139 known quasars in this region of the sky with i magnitudes brighter than 17.0, 17.5, and 18.0, respectively, of which 5, 20, and 75 are newly discovered. These bright quasars provide an invaluable collection with which to probe the kinematics and chemistry of the interstellar/intergalactic medium in the Local Group of galaxies. A total of 93 quasars are now known with locations within 2.degrees 5 of M31, of which 73 are newly discovered. Tens of quasars are now known to be located behind the Giant Stellar Stream, and hundreds are behind the extended halo and its associated substructures of M31. The much enlarged sample of known quasars in the vicinity of M31 and M33 can potentially be utilized to construct a perfect astrometric reference frame to measure the minute proper motions (PMs) of M31 and M33, along with the PMs of substructures associated with the Local Group of galaxies. Those PMs are some of the most fundamental properties of the Local Group.