Chongqing, China

Yangtze Normal University
Chongqing, China

Yangtze Normal University is a full-time, comprehensive university under the administration of the Chongqing Municipal Government of the Peoples Republic of China. The campus is located in Fuling District, at the conjunction of the Yangtze and Wu Rivers, the historic capital of the ancient Ba Tribe. It is the only teachers college in the ecological and economic zone of the Three Gorges Reservoir Area and the minority area in South-East Chongqing. Wikipedia.

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Chen Y.,Southwest University | Cao H.,Southwest University | Shi W.,Yangtze Normal University | Liu H.,CAS Chongqing Institute of Green and Intelligent Technology | Huang Y.,Southwest University
Chemical Communications | Year: 2013

This article presents a new enzyme-mimic activity of non-noble metal-based bimetallic Fe-Co NPs. This type of enzyme-mimic exhibits much higher affinity to H2O2 over other NPs-based peroxidase mimetics by at least one order of magnitude due to the synergistic effects between the two metals. This journal is © The Royal Society of Chemistry 2013.

Shi W.,Southwest University | Shi W.,Yangtze Normal University | Zhang X.,Southwest University | He S.,Southwest University | Huang Y.,Southwest University
Chemical Communications | Year: 2011

This communication presents a new peroxidase mimic of CoFe 2O4 nanoparticles evaluated by the luminol-based chemiluminescent (CL) reaction. This offers a new method for evaluation and screening of the nanoparticles-based enzyme mimetics. © 2011 The Royal Society of Chemistry.

Liu Y.,Yangtze Normal University | Yang S.,Hunan University | Niu W.,Yangtze Normal University
Colloids and Surfaces B: Biointerfaces | Year: 2013

Simple, rapid, green and one-step electrodeposition strategy was first proposed to synthesis of graphene/carbon nanotubes/chitosan (GR/CNTs/CS) hybrid. The one-step electrodeposition approach for the construction of GR-based hybrid is green environmentally, which would not involve the chemical reduction of graphene oxide (GO) and therefore result in no further contamination. The whole procedure is simple and needs only several minutes. Combining the advantages of GR (large surface area, high conductivity and good adsorption ability), CNTs (high surface area, high enrichment capability and good adsorption ability) and CS (good adsorption and excellent film-forming ability), the obtained GR/CNTs/CS composite could be highly efficient to capture organophosphate pesticides (OPs) and used as solid phase extraction (SPE). The GR/CNTs/CS sensor is used for enzymeless detection of OPs, using methyl parathion (MP) as a model analyte. Significant redox response of MP on GR/CNTs/CS sensor is proved. The linear range is wide from 2.0ngmL-1 to 500ngmL-1, with a detection limit of 0.5ngmL-1. Detection limit of the proposed sensor is much lower than those enzyme-based sensors and many other enzymeless sensors. Moreover, the proposed sensor exhibits high reproducibility, long-time storage stability and satisfactory anti-interference ability. This work provides a green and one-step route for the preparation of GR-based hybrid, and also offers a new promising protocol for OPs analysis. © 2013 Elsevier B.V.

Fan H.,Yangtze Normal University | Zhong Y.,Chongqing University
Journal of Computational Information Systems | Year: 2012

As an important concept of rough set theory, an attribute reduction is a subset of attributes that are jointly sufficient and individually necessary for preserving a particular property of the given information table. In order to acquire minimal attribute reduction, we propose a wasp swarm optimization algorithm for attribute reduction based on rough set and the significance of feature. The significance of feature is constructed based on the mutual information between selected conditional attributes and decisional attributes. The algorithm dynamically calculates heuristic information based on the significance of feature to guide search. Experimental are carried out on some standard UCI datasets. The results demonstrate that, in terms of solution quality and computational effort, proposed algorithm can get better results than other intelligent swarm algorithms for attribute reduction. 1553-9105/Copyright © 2012 Binary Information Press.

Wang X.,Yangtze Normal University
International Journal of Advancements in Computing Technology | Year: 2012

The Key frame extraction is fundamental of processes in CBVR (content based on video retrieval). This paper proposed an improved key frame extraction algorithm based on the lens for compressed video sequence, which was based on different formulas comparing discrete cosine transform (DC) direct current (DC) coefficients over the I-frames in MPEG video stream, and for which only minimal coding was needed In particular, introduced the importance difference of DC coefficients in one image frame into the process of similarity measure, special analysis the I-frame-based adaptive key frame extraction algorithm. The experiments show that the algorithm is significantly improved than the traditional one about the two indicators of the recall and retrieval time, especially for the more dramatic news documentaries, films and other local sports video sequences.

Li H.,Yangtze Normal University
Lecture Notes in Electrical Engineering | Year: 2012

In general regression models, we often think independent variable observations do not contain errors independent variable and the dependent variable observations contain errors. But in the practical problems, the independent observations contain different kinds of errors. Of course all this errors are random errors, and its expected value is 0. We call that Error-in-Variable. In this paper, we mainly discuss Error-in-Variable Models. © 2012 Springer-Verlag London Limited.

Zhu Q.-H.,Yangtze Normal University
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2013

Samples of LiMn2O4 were digested by microwave digestion, and impurity elements amounts of Na, Mg, Al, K, Ca, Ti, Cr, Fe, Cu, Zn, As, Ag, Cd and Pb in sample solutions were determined by inductively coupled plasma mass spectrometry (ICP-MS). Sample preparation was achieved by digestion with HNO3+HCl in a closed-vessel microwave system. The effects of mass spectrum interference were studied. Sc, Rh and Tl as internal standard elements were used to compensate matrix effect and signal drift. Under the optimal conditions, the detection limits of the 14 elements are in the range of 0.007~0.209 μg·L-1. The recovery was 92.66%~108.34% by adding standard recovery experiment, and the relative standard deviation (RSD) was less than 4.80% for all the elements. This method was simple, sensitive and precise, which could satisfy the sample examination request and provide scientific rationale for determining impurity elements of LiMn2O4.

Huang J.-B.,Yangtze Normal University
International Journal of Advancements in Computing Technology | Year: 2012

Genetic Algorithm is a reference biological and genetic mechanism of natural selection and has highly parallel, randomized, adaptive search algorithm for global optimization probability. Performance of genetic algorithms is dramatically influence by algorithmic settings. To improve the research performance of genetic algorithm and avoid its limitation of local optimization, a new adaptive genetic algorithm which is used in stereo image matching for function optimization, and three commonly used benchmark functions have been optimized. Compared the results of simulation with traditional image, are compared by simulation and match with the traditional image that this adaptive mechanism does improve the search performance of the algorithm, the accuracy of image matching, and achieved good results.

Li L.,Yangtze Normal University
Journal of Software | Year: 2012

In the process of object tracking, the major problem is how to mark the tracking box of the object. Moreover, multi-objects tracking is also difficult. This paper proposed and efficient fast object-tracking scheme based on motion-vector-located pattern match, which adopts motion vector of Mpeg2 to mark the moving targets in static video in order to mark and locate the targets automatically and quickly. Then, extract multi-dimensional characteristics from the initial targets taken by motion vector and make the model. Then accurately identifies the particles of larger weight and combines with inertia factor of velocity through matching the original data and the observations of particle filter. The matching of the characteristics of the new particle and the original one is more accurate and faster because of adopting the method of pattern classifying. The experiments show that the algorithm had good tracking performance and strong robustness. © 2012 Academy Publisher.

Fan H.,Yangtze Normal University
Journal of Computational Information Systems | Year: 2010

Particle swarm optimization (PSO) is a kind of evolutionary algorithm to find optimal solutions for continuous optimization problems. Updating kinetic equations for particle swarm optimization algorithm are improved to solve traveling salesman problem (TSP) based on problem characteristics and discrete variable. Those strategies which are named heuristic factor, reversion mutant and adaptive noise factor, are designed and combined into a new hybrid discrete particle swam optimization algorithms. Experiments on low and high-dimensional data in TSPLIB show that, comparing with other hybrid discrete particle swarm (DPSO), the proposed algorithm can improve the search performance significantly no matter in convergent speed or precision. © 2010 Binary Information Press October, 2010.

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