Neural Computing and Applications - Adaptive (sub)gradient methods have received wide applications such as the training of deep networks. The square-root regret bounds are achieved in convex... 相似文献
Pattern Analysis and Applications - The designed method aims to perform image classification tasks efficiently and accurately. Different from the traditional CNN-based image classification methods,... 相似文献
The Journal of Supercomputing - With the wide spread of image information, it is an urgent problem to protect image property rights and crack down on piracy. Watermarking algorithm is an effective... 相似文献
Applied Intelligence - Implicit discourse relation classification is one of the most challenging tasks in discourse parsing. Without connectives as linguistic clues, classifying discourse relations... 相似文献
The purpose of this study is to analyze the environmental pollution effects elicited by industrial agglomeration and to devise necessary changes before and after China going into the New Normal, a contemporary phase of less rapid but more sustainable economic development. An empirical model is constructed based on the Copeland–Taylor model, and empirical research is conducted using statistical panel data derived from 285 Chinese cities between 2003 and 2014. To study the relationship between industrial agglomeration and industrial pollutant emission both before and after the ‘New Normal,’ the sample data are divided into two time periods: 2003–2008 and 2009–2014. Estimated results are as follows. First, industrial agglomeration exacerbates industrial pollution levels overall although the negative environmental effect of industrial agglomeration is weakened following China’s entry into the New Normal phase of economy. Second, both the interaction term of industrial agglomeration and foreign direct investment (FDI) and the interaction term of industrial agglomeration and environmental regulation are negatively related to industrial agglomeration. These findings indicate that FDI and environmental regulation can indirectly reduce industrial pollutant emissions by way of industrial agglomeration. 相似文献
The homogeneous incorporation of heteroatoms into two-dimensional C nanostructures, which leads to an increased chemical reactivity and electrical conductivity as well as enhanced synergistic catalysis as a conductive matrix to disperse and encapsulate active nanocatalysts, is highly attractive and quite challenging. In this study, by using the natural and cheap hydrotropic amino acid proline—which has remarkably high solubility in water and a desirable N content of ~12.2 wt.%—as a C precursor pyrolyzed in the presence of a cubic KCl template, we developed a facile protocol for the large-scale production of N-doped C nanosheets with a hierarchically porous structure in a homogeneous dispersion. With concomitantly encapsulated and evenly spread Fe2O3 nanoparticles surrounded by two protective ultrathin layers of inner Fe3C and outer onion-like C, the resulting N-doped graphitic C nanosheet hybrids (Fe2O3@Fe3C-NGCNs) exhibited a very high Li-storage capacity and excellent rate capability with a reliable and prolonged cycle life. A reversible capacity as high as 857 mAh•g–1 at a current density of 100 mA•g–1 was observed even after 100 cycles. The capacity retention at a current density 10 times higher—1,000 mA•g–1—reached 680 mAh•g–1, which is 79% of that at 100 mA•g–1, indicating that the hybrids are promising as anodes for advanced Li-ion batteries. The results highlight the importance of the heteroatomic dopant modification of the NGCNs host with tailored electronic and crystalline structures for competitive Li-storage features.
