Nanjing University of Information Science and Technology

About: Nanjing University of Information Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Precipitation & Aerosol. The organization has 14129 authors who have published 17985 publications receiving 267578 citations. The organization is also known as: Nan Xin Da.

Low-Rank Tensor Constrained Multiview Subspace Clustering

Abstract: In this paper, we explore the problem of multiview subspace clustering. We introduce a low-rank tensor constraint to explore the complementary information from multiple views and, accordingly, establish a novel method called Low-rank Tensor constrained Multiview Subspace Clustering (LT-MSC). Our method regards the subspace representation matrices of different views as a tensor, which captures dexterously the high order correlations underlying multiview data. Then the tensor is equipped with a low-rank constraint, which models elegantly the cross information among different views, reduces effectually the redundancy of the learned subspace representations, and improves the accuracy of clustering as well. The inference process of the affinity matrix for clustering is formulated as a tensor nuclear norm minimization problem, constrained with an additional L2,1-norm regularizer and some linear equalities. The minimization problem is convex and thus can be solved efficiently by an Augmented Lagrangian Alternating Direction Minimization (AL-ADM) method. Extensive experimental results on four benchmark datasets show the effectiveness of our proposed LT-MSC method.

Feature Extraction for Hyperspectral Imagery: The Evolution From Shallow to Deep: Overview and Toolbox

Abstract: Hyperspectral images (HSIs) provide detailed spectral information through hundreds of (narrow) spectral channels (also known as dimensionality or bands), which can be used to accurately classify diverse materials of interest. The increased dimensionality of such data makes it possible to significantly improve data information content but provides a challenge to conventional techniques (the so-called curse of dimensionality) for accurate analysis of HSIs.

A novel routing protocol providing good transmission reliability in underwater sensor networks

Abstract: As the network communications technology developing, a new type of networks has appeared in the daily life which is named underwater sensor networks (UWSNs). UWSNs are a class of emerging networks that experience variable and high propagation delays and limited available bandwidth. There are comprehensive applications in this area such as oceanographic data collection, pollution monitoring, offshore exploration, assisted navigation and so on. Due to the different environment under the ocean, routing protocols in UWSNs should be re-designed to fit for the surroundings. In particular, routing protocols in UWSNs should ensure the reliability of message transmission, not just decrease the delay. In this paper, we propose a novel routing protocol named Location-Aware Routing Protocol (LARP) for UWSNs, where the location information of nodes is used to help the transmission of the message. Simulation results show that the proposed LARP outperforms the existing routing protocols in terms of packet delivery ratio and normalized routing overhead. We expect LARP to be of greater value than other existing solutions in underwater environment.

Contributions of open crop straw burning emissions to PM 2.5 concentrations in China

Abstract: PM2.5 inventories have been developed in major Chinese cities to quantify the contributions from various sources based on annual emissions. This approach, however, could substantially underestimate the contribution from open straw burning during the harvest or other active burning periods. This study examines this issue by estimating monthly and annual straw-burning PM2.5 emissions in China and comparing with them with the corresponding emissions from other anthropogenic sources. Annually burned straw PM2.5 emissions during 1997 ~ 2013 for 31 China provinces were calculated based on crop and related burning information for 12 months based on satellite detection of agricultural burning. Annual emissions from other anthropogenic sources were collected from the literature and allocated to monthly values using air pollution index measurements. The results indicate that the annual PM2.5 emissions from open straw burning in China were 1.036 m tons. The monthly PM2.5 emission ratios of straw burning to other anthropogenic sources during June, the harvest period for many regions, were several times larger than the annual ratios at national, regional, and province levels, suggesting that, in contrast to annual emissions that were used in the PM2.5 inventories in Chinese cities to assess the contributions from other sources, monthly emissions should be used to assess the contributions from straw burning during the harvest or other active burning periods. The larger contributions from straw burning shown in this study also suggest that substantial reduction of open field straw burning would dramatically improve air quality in many Chinese regions during the harvest or other active burning periods.