Sun Yat-sen University

About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.

The Simons Observatory : Science goals and forecasts

Abstract: The Simons Observatory (SO) is a new cosmic microwave background experiment being built on Cerro Toco in Chile, due to begin observations in the early 2020s. We describe the scientific goals of the experiment, motivate the design, and forecast its performance. SO will measure the temperature and polarization anisotropy of the cosmic microwave background in six frequency bands centered at: 27, 39, 93, 145, 225 and 280 GHz. The initial configuration of SO will have three small-aperture 0.5-m telescopes and one large-aperture 6-m telescope, with a total of 60,000 cryogenic bolometers. Our key science goals are to characterize the primordial perturbations, measure the number of relativistic species and the mass of neutrinos, test for deviations from a cosmological constant, improve our understanding of galaxy evolution, and constrain the duration of reionization. The small aperture telescopes will target the largest angular scales observable from Chile, mapping ≈ 10% of the sky to a white noise level of 2 μK-arcmin in combined 93 and 145 GHz bands, to measure the primordial tensor-to-scalar ratio, r, at a target level of σ(r)=0.003. The large aperture telescope will map ≈ 40% of the sky at arcminute angular resolution to an expected white noise level of 6 μK-arcmin in combined 93 and 145 GHz bands, overlapping with the majority of the Large Synoptic Survey Telescope sky region and partially with the Dark Energy Spectroscopic Instrument. With up to an order of magnitude lower polarization noise than maps from the Planck satellite, the high-resolution sky maps will constrain cosmological parameters derived from the damping tail, gravitational lensing of the microwave background, the primordial bispectrum, and the thermal and kinematic Sunyaev-Zel'dovich effects, and will aid in delensing the large-angle polarization signal to measure the tensor-to-scalar ratio. The survey will also provide a legacy catalog of 16,000 galaxy clusters and more than 20,000 extragalactic sources.

Deep Learning for 3D Point Clouds: A Survey

Abstract: Point cloud learning has lately attracted increasing attention due to its wide applications in many areas, such as computer vision, autonomous driving, and robotics As a dominating technique in AI, deep learning has been successfully used to solve various 2D vision problems However, deep learning on point clouds is still in its infancy due to the unique challenges faced by the processing of point clouds with deep neural networks Recently, deep learning on point clouds has become even thriving, with numerous methods being proposed to address different problems in this area To stimulate future research, this paper presents a comprehensive review of recent progress in deep learning methods for point clouds It covers three major tasks, including 3D shape classification, 3D object detection and tracking, and 3D point cloud segmentation It also presents comparative results on several publicly available datasets, together with insightful observations and inspiring future research directions

Spatial and seasonal distributions of carbonaceous aerosols over China

Abstract: [1] Simultaneous measurements of atmospheric organic and elemental carbon (OC and EC) were taken during winter and summer seasons at 2003 in 14 cities in China. Daily PM2.5 samples were analyzed for OC and EC by the Interagency Monitoring of Protected Visual Environments (IMPROVE) thermal/optical reflectance protocol. Average PM2.5 OC concentrations in the 14 cities were 38.1 μg m−3 and 13.8 μg m−3 for winter and summer periods, and the corresponding EC were 9.9 μg m−3 and 3.6 μg m−3, respectively. OC and EC concentrations had summer minima and winter maxima in all the cities. Carbonaceous matter (CM), the sum of organic matter (OM = 1.6 × OC) and EC, contributed 44.2% to PM2.5 in winter and 38.8% in summer. OC was correlated with EC (R2: 0.56–0.99) in winter, but correlation coefficients were lower in summer (R2: 0.003–0.90). Using OC/EC enrichment factors, the primary OC, secondary OC and EC accounted for 47.5%, 31.7% and 20.8%, respectively, of total carbon in Chinese urban environments. More than two thirds of China's urban carbon is derived from directly emitted particles. Average OC/EC ratios ranged from 2.0 to 4.7 among 14 cities during winter and from 2.1 to 5.9 during summer. OC/EC ratios in this study were consistent with a possible cooling effect of carbonaceous aerosols over China.