Jianyong F.,Jiangsu Automation Research Institute
Proceedings - 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016 | Year: 2016
There are often a few harsh testing scenarios need to simulate, such as the bandwidth of the network is limited, the memory is overload or the file system access is denied. Now, there have been some traditional methods to simulate those faults, but these methods often make damage on the system resource or the code of the system under testing. Using the interception service of Windows system, the nonintrusive resource level fault injection methods are proposed to simulate resource level faults accurately. Then a fault injection tool named JariFI is designed, which can inject faults needed in software testing and reliability evaluation. At last, the accuracy and the function applicability about the tool are verified by the fault injection experiment. © 2016 IEEE.
Han Y.,Shanghai JiaoTong University |
Han Y.,Jiangsu Automation Research Institute |
Cai Y.,Shanghai JiaoTong University |
Cao Y.,Shanghai JiaoTong University |
And 2 more authors.
Information Fusion | Year: 2013
Because subjective evaluation is not adequate for assessing work in an automatic system, using an objective image fusion performance metric is a common approach to evaluate the quality of different fusion schemes. In this paper, a multi-resolution image fusion metric using visual information fidelity (VIF) is presented to assess fusion performance objectively. This method has four stages: (1) Source and fused images are filtered and divided into blocks. (2) Visual information is evaluated with and without distortion information in each block. (3) The visual information fidelity for fusion (VIFF) of each sub-band is calculated. (4) The overall quality measure is determined by weighting the VIFF of each sub-band. In our experiment, the proposed fusion assessment method is compared with several existing fusion metrics using the subjective test dataset provided by Petrovic. We found that VIFF performs better in terms of both human perception matching and computational complexity. © 2011 Elsevier B.V. All rights reserved.
Ni W.,Jiangsu Automation Research Institute
Computer Journal | Year: 2016
Location awareness has become one of the most popular areas for mobile internet applications. Normally, the method of maximum likelihood estimation (MLE) can be used to estimate the position of the unknown nodes. However, when the number of anchor nodes is small within the communication range, the traditional methods cannot work very well. This paper provides a novel location approach to estimate the position by selecting valuable neighbors (both anchor and regular nodes) with Minimized Error Propagation Location method based on Error estimation (MEPLE). The simulation results show that the MEPLE outperforms the MLE overall, especially when the number of anchor nodes is relatively small such as between 10 and 20, MEPLE can reduce 50-80% estimation error on average. © 2015 The British Computer Society 2015. All rights reserved.
Song C.,Jiangsu Automation Research Institute
Lecture Notes in Electrical Engineering | Year: 2015
The intelligent 1553B-bus communication module based on the ARM platform is mainly applied to extending the 1553B-bus interface of the Compact PCI computer system. In terms of hardware, the module adopts the ARM control unit and dual-port RAM while incorporating the round buffer design with respect to software, which effectively strengthens the stability of data transmission and substantially decreases the possibility of data loss during transmission. © Springer International Publishing Switzerland 2015.
Ding Y.-Y.,Jiangsu Automation Research Institute
IEEE Region 10 Annual International Conference, Proceedings/TENCON | Year: 2013
Target association is a crucial technique in information fusion of underwater platform and its weapon sensors, which can generate a more clear situation picture. In this paper, DEMON spectrum analysis was used for target association of two platforms to improve the association performance. Based on the computation of the similarity of DEMON spectrum, an improved cross-correlation method was introduced for spectrum association and the comparision of it with two classical methods was conducted. The simulation results using sea recorded data show that the correlation-based methods can realize the right association between the same targets and have potential application in practical system. © 2013 IEEE.
Zhao Y.,Jiangsu Automation Research Institute
Proceedings of IEEE International Conference on Grey Systems and Intelligent Services, GSIS | Year: 2015
In software reliability testing based on Markov chain usage model, how to assign the migrating probability between states of the Markov chain usage model is still a problem yet to be solved. In order to deal with the problems such as the sample data for estimating the migrating probability being small and uncertain, a migrating probability assignment method based on a three-parameter interval number is proposed to build the Markov chain usage model. The method for generating test cases is also given. An example shows in this paper, the software usage model based on the three-parameter interval number is closer to the actual situation, and the software reliability testing efficiency is improved. © 2015 IEEE.
Zhi H.,Jiangsu Automation Research Institute
Journal of Infrared, Millimeter, and Terahertz Waves | Year: 2010
It is a challenging task to detect point targets from an infrared image. Recently, the pattern recognition theory has been used to detect targets. The principal component analysis (PCA) has gained success in this field. We propose a linear subspace detection method based on Fisher linear discriminant (FLD) in this paper. If we consider images are made up of target class data and background class data, the target detection problem can be translated into a two-class classification problem. The FLD as one of pattern recognition algorithms can be used to find potential targets from image background. After classification by FLD, a map function, Gaussian map function, is developed to generate detection images in which the larger target-to-background contrast is obtained. FLD is a linear detection method without taking the higher-order statistics of image data into account. To improve detection performance, we extend this detection method to its nonlinear version, kernel FLD (KFLD) detection. Because the nonlinear subspace is capable of capturing the part of higher-order statistics, the better detection performance can be achieved. The well-devised experiments verify that KFLD detection outperforms FLD and other common used detection methods. © 2010 Springer Science+Business Media, LLC.
Hu Q.J.,Jiangsu Automation Research Institute
Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS | Year: 2014
It is necessary to carry out the research on intelligent system in the field of digital publishing at the condition of saas and big data. Based on this situation, the author of the present paper proposes to apply intelligent system of the digital publishing, a intelligent system formulated according to Symfony2.0 framework, to the Journals and publishers for digital publishing. With the information on the needs of Journals and Publishers collected from questionnaires and interviews, the author designs this model of Intelligent system, which is technically realized with the help of the Symfony2.0 framework. The author explores the application and technical methods of Symfony2.0 framework in the extension and exploration of Web system, and describes the realization of intelligent system through analyzing its important module of Bundle. © 2014 IEEE.
Ma S.,Jiangsu Automation Research Institute
Proceedings - 2013 International Conference on Mechatronic Sciences, Electric Engineering and Computer, MEC 2013 | Year: 2013
As measurements errors are assumed to be zero-mean, Gaussian distributed and uncorrelated, an improved method of target state estimation for multi-sensor target tracking is presented based on Gauss-Markove estimate. By minimizing the error covariance matrix, weighted least square method is exploited to obtain the Gauss-Markove estimate. Applying Gauss-Markove estimate to Kalman filter, the target state was estimated. The Monte-Carlo simulation results show that Gauss-Markove estimate can efficiently improve the accuracy of observations. The performance of proposed algorithm for state estimation is better than that with single sensor observations. Presented approach and obtained results may be useful in multi-sensor target tracking. © 2013 IEEE.
Jiangsu Automation Research Institute | Date: 2016-04-20
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