Synthesis of N-doped mesoporous carbons under different carbonization temperature and their application in supercapacitors

We have synthesized N-doped mesoporous carbon by the in-suit doping template method under the carbonized temperature of 900?°C. We found that the electrochemical performance of mesoporous carbon was enhanced by N-doping. So, we tried to increase the content of nitrogen to further optimize the electrochemical performance of the mesoporous carbon as electrode materials. During the process of synthesizing mesoporous carbon, the carbonized temperature played an important role in the formation of the carbon structure and its morphology, as well as in determining the content of nitrogen. We attained a considerable electrochemical performance enhancement by changing the carbonized temperature from 900 to 700?°C. We found the content of Nitrogen decreased with the increase of the carbonized temperature and the content of Nitrogen is 6.11% at 700?°C, 5.39% at 800?°C, 3.9% at 900?°C, respectively. The best electrochemical performance was observed in the product carbonized at 700?°C, which exhibited high specific capacitance (245.6 F/g at 0.5 A/g) and good cycle ability (more than 90% of the initial capacitance after 5000 cycles) in 6 M KOH electrolyte.     

Studying the influence of search rule and context shape in filtering impulse noise images with Markov chains

The paper presents an improved context-based denoising method for gray scale images affected by impulse noise. The proposed algorithm is using Markov chains to replace the detected noise with the intensity having the highest number of occurrences in similar contexts. The context of a noisy pixel consists in its neighbor pixels and is searched in a larger but limited surrounding area. We have analyzed different search methods and different context shapes. The experimental results obtained on the test images have shown that the most efficient model applies the search in form of   “*”  of contexts in form of   “+”. Besides the better denoising performance obtained on all the noise levels, the computational time has been also significantly improved with respect to our previous context-based filter which applied full search of full context. We have also compared this improved Markov filter with other denoising techniques existing in the literature, most of them being significantly outperformed.     

Stochastic stabilization and destabilization of nonlinear and time‐varying hybrid systems by noise

The aim of this article is to design a suitable strength function g(t,x,r(t)) such that the Wiener noise g(t,x(t),r(t))dw(t) either stabilizes or destabilizes a given nonlinear and time‐varying hybrid system . To this end, the basic properties, including the existence and uniqueness of the local and global solutions and the nonzero property of solutions of the nonlinear and time‐varying hybrid stochastic systems, are first investigated as the theoretical basis of the article. Second, two theorems and the corresponding corollaries on the stability and instability of the hybrid stochastic systems are established. Third, the design method for the noise strength g(t,x,r(t)) is then proposed based on the established theorems. We also point out that the Markov jump r(t) may have a stabilizing (respectively, destabilizing) effect when we design the noise strength g(t,x,r(t)) so that the introduced noise g(t,x(t),r(t))dw(t) stabilizes (respectively, destabilizes) the corresponding hybrid system. Finally, we illustrate our method using two examples. Compared with the existing literature, our method is suitable for a wider class of nonlinear and time‐varying systems with weaker conditions than quasi‐linear systems.     

Global Exponential Stability of Hybrid Non-autonomous Neural Networks with Markovian Switching

Neural Processing Letters - This paper discusses the global exponential stability for a class of hybrid non-autonomous neural networks (HNNNs) with Markovian switching, which includes the factors...     

A Dynamic Programming Framework for Large-Scale Online Clustering on Graphs

Neural Processing Letters - As a fundamental technique for data analysis, graph clustering grouping graph data into clusters has attracted great attentions in recent years. In this paper, we...     

An image segmentation approach on improved implicit surface model in straddle strategy

Multimedia Tools and Applications - At present, some experts and scholars do not explicitly mention the static model in the analysis of the straddle strategy, which leads to the research results...