National University of Defense Technology

About: National University of Defense Technology is a education organization based out in Changsha, China. It is known for research contribution in the topics: Radar & Synthetic aperture radar. The organization has 39430 authors who have published 40181 publications receiving 358979 citations. The organization is also known as: Guófáng Kēxuéjìshù Dàxué & NUDT.

Direction-of-Arrival Estimation Based on Deep Neural Networks With Robustness to Array Imperfections

Abstract: Lacking of adaptation to various array imperfections is an open problem for most high-precision direction-of-arrival (DOA) estimation methods. Machine learning-based methods are data-driven, they do not rely on prior assumptions about array geometries, and are expected to adapt better to array imperfections when compared with model-based counterparts. This paper introduces a framework of the deep neural network to address the DOA estimation problem, so as to obtain good adaptation to array imperfections and enhanced generalization to unseen scenarios. The framework consists of a multitask autoencoder and a series of parallel multilayer classifiers. The autoencoder acts like a group of spatial filters, it decomposes the input into multiple components in different spatial subregions. These components thus have more concentrated distributions than the original input, which helps to reduce the burden of generalization for subsequent DOA estimation classifiers. The classifiers follow a one-versus-all classification guideline to determine if there are signal components near preseted directional grids, and the classification results are concatenated to reconstruct a spatial spectrum and estimate signal directions. Simulations are carried out to show that the proposed method performs satisfyingly in both generalization and imperfection adaptation.

The Characteristics of Cloud Computing

Abstract: Cloud computing emerges as one of the hottest topic in field of information technology. Cloud computing is based on several other computing research areas such as HPC, virtualization, utility computing and grid computing. In order to make clear the essential of cloud computing, we propose the characteristics of this area which make cloud computing being cloud computing and distinguish it from other research areas. The cloud computing has its own conceptional, technical, economic and user experience characteristics. The service oriented, loose coupling, strong fault tolerant, business model and ease use are main characteristics of cloud computing. Clear insights into cloud computing will help the development and adoption of this evolving technology both for academe and industry.

In situ synthesis of graphitic-C3N4 nanosheet hybridized N-doped TiO2 nanofibers for efficient photocatalytic H2 production and degradation

Abstract: Graphitic carbon nitride nanosheets (g-C3N4 NSs) hybridized nitrogen doped titanium dioxide (N-TiO2) nanofibers (GCN/NT NFs) have been synthesized in situ via a simple electrospinning process combined with a modified heat-etching method. The prepared GCN/NT NFs were characterized by a variety of methods and their photocatalytic activities were evaluated by hydrogen (H2) production from water splitting and degradation of rhodamine B in aqueous solution. It was found that the GCN/NT NFs have a mesoporous structure, composed of g-C3N4 NSs and N-doped TiO2 crystallites. The g-C3N4 NSs synthesized after heat-etching were found to be embedded in, and covered, the hybrid NFs to form stable interfaces. The partial decomposition of g-C3N4 releases its nitrogen content which eventually gets doped into the nearby TiO2 skeleton. The GCN/NT NFs give a high photocatalytic H2 production rate of 8,931.3 μmol·h−1·g−1 in aqueous methanol solution under simulated solar light. Such a highly efficient photocatalytic performance can be ascribed to the combined effects of g-C3N4 NSs and N-doped TiO2 with enhanced light absorption intensity and improved electron transport ability. Also, the large surface area of the mesoporous NFs minimizes light reflection on the surface and provides more surface-active sites. This work highlights the potential of quasi-one dimensional hybrid materials in the field of solar energy conversion.