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Lu X.,Tianjin University | Yu R.,Tianjin University | Dong W.,Wuhan University | Lei M.,Tianjin University of Technology | And 2 more authors.
Journal of Computational Information Systems | Year: 2012

In physics, damping is any effect that tends to reduce the amplitude of oscillations in an oscillatory system. Inspired by this, we present a new traffic allocation algorithm for Wireless Networks in order to limit the packet delay variance. We refer to our algorithm as the damping based traffic allocation algorithm (DBTA). DBTA computes the queuing delay and queuing delay variance, configures system parameters, and finally reduces the amplitude of delay variations. We realize DBTA based on Dynamic Source Routing (DSR) protocol. Performance comparison of DBTA with DSR using Network Simulator (NS-2) simulation shows that DBTA can achieve a remarkable improvement in decreasing the packet delay variance. © 2011 by Binary Information Press.


Zhang D.,Key Laboratory of Computer Vision and System | Zhang D.,Tianjin University of Technology | Zhang D.,University of Sydney | Zhu Y.,Key Laboratory of Computer Vision and System | And 6 more authors.
Journal of Information Science and Engineering | Year: 2016

Wireless Mesh network (WMN) is multi-hop heterogeneous network, which breaks shortcomings of traditional wireless network. WMN comes into sight with more advantages. To the multi-radio multi-channel (MRMC) wireless mesh networks (MRMCWMN), routing distribution, channel assignment and rate allocation can be united to optimize network performance. MRMC resource optimization method based on convex theory for WMN is presented in this paper. According to convex theory, we use the convex optimization function to get the optimal solution in the limited network supporting by Ad hoc On-Demand Distance Vector (AODV) routing method. At the same time, we resolve the optimal solution into three simple sub-problems according to the Lagrange duality method supporting by multi-radio multi-channel AODV (MAODV). We use MATLAB simulation tools to simulate the new and improved optimization method. The experimental results show that our method has better network performance in the applications of WMN.


Yang S.,Tianjin University of Technology | Yang S.,Key Laboratory of Computer Vision and System | Shen T.,Tianjin University of Technology | Shen T.,Key Laboratory of Computer Vision and System | And 2 more authors.
Journal of Computational Information Systems | Year: 2015

A new approach of gear fault diagnosis based on Gaborlet Transform A tlas is presented. Gaborlet Transform A tlas is extended from wavelet transform. It is a linear transformation of time-frequency scale three-dimensional space and a combination of wavelet transform and Gabor transform. It has powerful analysis capabilities for the non-stationary signals. The signal spectral estimation based on this method has the wavelet transform advantage of a high frequency resolution. Besides, it is not limited to the width of signal frequency range. The needed scale parameter can be chosen freely and the spectral estimated value is accurate and efficient. The experimental results indicate that the proposed method can get better results than the classic local power spectrum estimation in gear fault diagnosis. It highlights the gear sideband structure. So, it is suitable for local fault diagnosis. 1553-9105/Copyright © 2015 Binary Information Press


Wang H.-B.,Tianjin University of Technology | Wang H.-B.,Key Laboratory of Computer Vision and System | Yang H.-L.,Tianjin University of Technology | Yang H.-L.,Key Laboratory of Computer Vision and System | And 4 more authors.
Proceedings of the International Conference on E-Business and E-Government, ICEE 2010 | Year: 2010

Improving detection definition is a pivotal problem for intrusion detection. Many intelligent algorithms were used to improve the detection rate and reduce the false rate. Traditional SOM cannot provide the precise clustering results to us, while traditional K-Means depends on the initial value serious and it is difficult to find the center of cluster easily. Therefore, in this paper we introduce a new algorithm, first, we use SOM gained roughly clusters and center of clusters, then, using K-Means refine the clustering in the SOM stage. At last of this paper we take KDD CUP-99 dataset to test the performance of the new algorithm. The new algorithm overcomes the defects of traditional algorithms effectively. Experimental results show that the new algorithm has a good stability of efficiency and clustering accuracy. © 2010 IEEE.


Ren B.,Key Laboratory of Intelligence Computing and Novel Software Technology | Ren B.,Key Laboratory of Computer Vision and System | Li Y.,Tianjin University of Technology | Tang S.,Tianjin University of Technology | And 2 more authors.
Proceedings - 2014 10th International Conference on Semantics, Knowledge and Grids, SKG 2014 | Year: 2014

With the development of network technology, the amount of information on network has been exploded. How to effectively make use of the web information resource has been an important problem which need to be solved. Facing the problem, scholars have some works on web information integration. But these studies mainly pay attention to specific domain information integration, such as news field, movie field, music field, blog field, and so on. There are few studies on information collection towards educational field. In this paper we propose an education-oriented approach for integrating test questions towards a special course. The method is based on a textbook's name and authors' information, and integrate the textbook's catalog and test questions automatically from Web, then computing the similarity between catalog of the textbook and test questions for classification, reaching to the purpose of building test question library by automatic method. Based on the method, we develop a prototype system. The precision and feasibility of the method have been verified by experiments. © 2014 IEEE.


Yuan Z.,Tianjin University | Yu R.,Tianjin University | Zhao M.,Tianjin University | Du X.,Tianjin University | And 3 more authors.
Journal of Information and Computational Science | Year: 2013

Mesh Networks (WMNs) is a promising network access technology. As WMNs' applications become more and more popular, the number of users grows quickly and the quality of service needs to be improved. When we try to analyze the load on different paths using the simplest multi-path routing algorithms we find that the load changes just like Simple Harmonic Motion, which inspires us to use physic model to analyze the traffic allocation problems. And then we design a new traffic allocation algorithm and the experiment shows that the algorithm can reduce the path delay variance. © 2013 Binary Information Press.


Gao Z.,Key Laboratory of Computer Vision and System | Gao Z.,Tianjin University of Technology | Zhang H.,Key Laboratory of Computer Vision and System | Zhang H.,Tianjin University of Technology | And 4 more authors.
International Journal of Digital Content Technology and its Applications | Year: 2012

Recently sparse representation based classification (SRC) has been widely used for face recognition (FR). However, in this paper, a sparse representation with structured and discriminative dictionary learning (DL_SL_SC_SRC) algorithm is proposed for human behavior recognition. First, spatio-temporal interested points are extracted for behavior atom representation by the motion-constrained SIFT algorithm and Bag-of-Behavior Atom strategy is utilized to represent each behavior sample with a compact and discriminative feature. Then structured and discriminative sparse decomposition is proposed for behavior representation and recognition. Especially, we reformulate the objective functions for both dictionary learning and sparse representation for classification with the philosophy of structuring and discrimination. Large scale comparative experiments show the accuracy and robustness of the method. Moreover, the proposed method outperforms most of the state-of-art methods for human behavior recognition.


Yang S.,Tianjin University of Technology | Yang S.,Key Laboratory of Computer Vision and System | Tao C.,Tianjin University of Technology | Tao C.,Key Laboratory of Computer Vision and System | And 4 more authors.
Journal of Computational Information Systems | Year: 2014

For the high-order nonlinear systems with unknown control coefficients of non-uniform trajectory tracking problem, a hybrid parameter adaptive iterative learning control algorithm is proposed. An improved Backstepping method is proposed in this algorithm by using recombinant techniques parameters and segmented constructing Lyapunov function. The constant parameter adaptive law, adaptive control law, and time-varying parameter vector adaptive law designed in turn. This algorithm can deal with the unknown time-varying control coefficient non-uniform target tracking problem. By constructing a Lyapunov-like functional, the conclusion that the tracking error converges to zero on finite time interval. The simulation results illustrate the effectiveness of the proposed algorithm in this paper. © 2014 by Binary Information Press


Xiao Y.,Tianjin University of Technology | Xiao Y.,Key Laboratory of Computer Vision and System | Zhang H.,Tianjin University of Technology | Zhang H.,Key Laboratory of Computer Vision and System | And 3 more authors.
Applied Mathematics and Information Sciences | Year: 2012

Real-time systems, which are often employed to monitor and interact with dynamic environments, are widely applied in time-critical applications, such as autopilot systems, medical patient monitoring, robot navigation, military command and control systems, agile manufacturing, etc. These time-critical applications require real-time systems can provide real-time data services ceaselessly. However, real-time systems cannot completely avoid all kinds of failures, so real-time systems must prepare for possible failures and provide fault tolerance capability. The conventional failure recovery methods cannot guarantee real-time data services available when some data items are damaged by failures. In this paper, we present a novel prediction recovery method through the integration of regression model and grey theory. The prediction recovery method guarantees real-time data services available by means of providing predictive values of damaged data to application activities which have to access these data immediately. Performance test shows that the proposed prediction recovery method can significantly improve the real-time performance. © 2012 NSP Natural Sciences Publishing Cor.


Shi K.,Key Laboratory of Intelligent Computing and Novel Software Technology | Shi K.,Key Laboratory of Computer Vision and System | Song Q.,Tianjin Chengjian University | Lin S.,Key Laboratory of Intelligent Computing and Novel Software Technology | And 5 more authors.
Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016 | Year: 2016

The Minimum Spanning Tree (MST) is of crucial importance for Communication Networks (CNs), which can solve problems of unconstrained CNs effectively. However, in practical CNs, the degree of the spanning tree is constrained. In such a case, the problem is very difficult, which has been proved to be NP-hard. In this paper, an improved genetic algorithm (I-GA) is proposed for solving the problem of Degree Constrained Minimum Spanning Tree (DCMST). We use Prufer number as the chromosome, and improve the crossover and mutation processes of the existing genetic algorithm for obtaining high locality, heritability, and self-adaptation. Simulation results show that our mechanism of I-GA can get relatively better results. © 2016 IEEE.

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