Applied Mechanics and Materials Vols. 347-350

Abstract: Based on actual project of unit test,it disscussed the application of testbed in unit test of aviation software.It introduced the configure of three general aviation software's development environment in testbed,and some modifications of code before test.It analysed steps of unit test and several common problems during steps,in addition,it introduces defect of testbed in unit test. Each function can be verified after unit test,at the same time,other test processes are guaranteed.

Abstract: Aiming at the disadvantage of existing materiel maintainability quantitative requirements demonstration method, this paper studied the project of the materiel maintainability qualitative requirement demonstration Based on virtual simulation, in order to determine the materiel maintainability qualitative requirement, the accessibility and visibility as an example to illustrate the virtual demonstration method. It is significant for developing maintainability demonstration and increasing materiel maintainability in the course of materiel digital mock-up designing.

Abstract: With a view to reverse design of product layer, a tri-level precision model of product-part-functional face based on functional face was organized. The products precision information model was recovered from the 3D model, and the precision design was achieved. The implementation process of precision reconstruction was introduced in detail and a piston fixture was presented as an example for validation.

Abstract: Aim at large amount and complex features of network video data, this paper proposed a fast algorithm of detecting pornographic video in streaming media. Combining the information of motion vector field and the features of pornographic behavior trajectory, we could judge that weather a video is pornographic or not without decoding it. The experiment show that the algorithm recognition rate is reached 80%, and is robust for network video detection environment

Abstract: Inspired by the research of human visual system in neuroanatomy and psychology, the paper proposes a two-way collaborative visual attention model for target detection.In this new method , bottom-up attention information cooperates with top-down attention information to detect a target rapidly and accuractly. Firstly,the statistical prior knowledge of target and background is applied to optimize bottom-up attention information in different feature space and scale space.Secondly, after the SNR of salience difference between target and interference is computed ,the bottom-up gain factor is obtained.Thirdly, the gain factor is applied to adjust bottom up attention information extraction and then to maximize the salience contrast of target and background.Finally, target is detected by adjusted saliency.Experimental results shows that the proposed model in this paper can improve the real-time capability and reliability of target detection.

Abstract: The passive direction finding cross localization has got great achievement and has been widely used in military and civilian fields. Currently, the researches on passive localization have focused on AOA, TDOA and FDOA. In our system, the passive direction finding cross localization is more effective and useful. We use two UAVs to locate a single source. We apply the geometric method to analysis positioning accuracy. In order to study the performance of a passive direction finding cross localization, MATLAB is used to simulate the result. Finally, the simulation results and performance analysis provide operational technical principle for such a system.

Abstract: With a focus on complex environments, the present paper describes a new algorithm in scale changed object tracking through color feature. Mean shift (MS) iterative procedure is the best color-based algorithm to find the location of an object. The algorithm performance is not acceptable once tracking scale changed objects in complex environments. In this paper, the main aim is to improve the MS method, using corrected background-weighted histogram (CBWH) algorithm to reduce the interference of background in target localization. To fit the object scale change, the sum of gradient mode (SGM) is employed. The experimental results show that the proposed method is superior to the traditional mean shift tracking in the following aspects: 1) it provides consistent object tracking throughout the video; 2) it is not influenced by the tracked objects scale changes; 3) it is less prone to the background clutter.

Abstract: Although spatio-temporal features (ST) have recently been developed and shown to be available for facial expression recognition and behavior recognition in videos, it utilizes the method of directly flattening the cuboid into a vector as a feature vector for recognition which causes the obtained vector is likely to potentially sensitive to small cuboid perturbations or noises. To overcome the drawback of spatio-temporal features, we propose a novel method called fused spatio-temporal features (FST) method utilizing the separable linear filters to detect interesting points and fusing two cuboids representation methods including local histogrammed gradient descriptor and flattening the cuboid into a vector for cuboids descriptor. The proposed FST method may robustness to small cuboid perturbations or noises and also preserve both spatial and temporal positional information. The experimental results on two video-based facial expression databases demonstrate the effectiveness of the proposed method.

Abstract: The stress calculated method of isogeometric structure analysis is studied in this paper. Based on the fact that stress calculated values at Guass integral points are more accurate than other locations, the stress field can be rebuilt by fitting the Guass integral points stress value from the displacement field, and two methods including stress interpolation and least square fit are presented to reduce the stress error. The example of infinite plate with circular hole is used to illustrate our methods performance, and the results show that our methods can improve the stress calculate accuracy notable.

Abstract: An efficient approach based on particle filter and FCM is presented to realize moving infrared multi-target tracking under Island shore background. Some possible targets can be obtained and saved by processing IR data through denoising by median filter, extracting edge, identifying and eliminating sea-sky line, morphological filtering and etc. Data association and robust multi-target tracking can be realized by the proposed particle filter and FCM algorithm. The proposed approach is validated to track multi-target effectively by using actual infrared image sequences with Island shore background. Experiment results indicate the feasibility and effectiveness of the proposed method.