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Xingtai, China

Xingtai University is a university in Hebei, China under the provincial government. Wikipedia.


Xing J.,Xingtai University
Energy Education Science and Technology Part A: Energy Science and Research | Year: 2014

This paper summarizes the present status of the development about network management technology, and introduces implementation process of management system that based on SNMP network performance management is an important component of network management This system utilize the standard SNMP protocol regularly to collect flow conditions of network key equipment, which be stored by structured, hierarchical, and Provide a graphical user interface The various historical data and real-time data collected by the form of numerical tables and graphs displayed visually, which is convenient for observation and analysis of the whole network performance. © Sila Science. All Rights Reserved. Source


Li Y.S.,Hebei University of Engineering | Feng W.J.,Shijiazhuang University | Cai Z.Y.,Hebei University of Engineering | Cai Z.Y.,Xingtai University
Composite Structures | Year: 2014

A size-dependent functionally graded piezoelectric beam model is developed using a variational formulation. It is based on the modified strain gradient theory and Timoshenko beam theory. The material properties of functionally graded piezoelectric beam are assumed to vary through the thickness according to a power law. The new model contains three material length scale parameters and can capture the size effect, unlike the classical beam theory. To illustrate the new functionally graded piezoelectric beam model, the static bending and free vibration problems of a simply supported beam are numerical solved. These results may be useful in the analysis and design of smart structures constructed from piezoelectric materials. © 2014 Elsevier Ltd. Source


Hui-Jing W.,Xingtai University
Proceedings - 7th International Conference on Intelligent Computation Technology and Automation, ICICTA 2014 | Year: 2015

Green evaluation index system of industrial building is to describe the evaluation content and scope of green industrial building, and reflect the green industrial building direction and the set of important measurable parameters. This paper introduces in the compiling process of Green Industrial Building Evaluation Standard, through the group experts analytic hierarchy process (AHP), the unreasonableness of index weights allocation in the result can be reduced. At the same time, this article discusses the rationality of the weight allocation result, through comparison and analysis on the evaluation index system of green industrial building, the British BREEAM industrial building and domestic green building. © 2014 IEEE. Source


Hui-Jing W.,Xingtai University
Proceedings - 7th International Conference on Intelligent Computation Technology and Automation, ICICTA 2014 | Year: 2015

A novel method for texture image classification was proposed by using dual-tree complex wavelets transform and support vector machines. The dual-tree complex wavelets transform was used to decompose texture image with four levels, feature vector was first used for training and later on for testing the support vector machine classifier. The experimental setup consists of twenty texture images from the Brodatz image database, results of experimental indicate that the presented method provide superior texture classification accuracy over other methods under the condition of limited training samples, and show the validity and the best generalization ability. © 2014 IEEE. Source


Chen S.,Xingtai University
CCIS2011 - Proceedings: 2011 IEEE International Conference on Cloud Computing and Intelligence Systems | Year: 2011

Mutual information (MI) is always used as the indicator of nonlinear correlation between the variables. The computation of MI can be finished only the continuous-value variables are discretized. In this paper, one new strategy of computing the MI between variables is proposed. The probability density estimation (PDE) is used to determine the density functions in our method. An approximate technology is applied to replace the computation of integral. Finally, MI based on PDE can be obtained. Through the artificially experimental simulations, the performance and rationality of our new method are demonstrated. The experimental results show that our method is feasible, effective and efficient. © 2011 IEEE. Source

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