Applied Mechanics and Materials Vols. 719-720

Abstract: Practical networks have community and hierarchical structure. These complex structures confuse the community detection algorithms and obscure the boundaries of communities. This paper proposes a delicate method which synthesizes spectral analysis and local synchronization to detect communities. Communities emerge automatically in the multi-dimension space of nontrivial eigenvectors. Its performance is compared to that of previous methods and applied to different practical networks. Our results perform better than that of other methods. Besides, it’s more robust for networks whose communities have different edge density and follow various degree distributions. This makes the algorithm a valuable tool to detect and analysis large practical networks with various community structures.

Abstract: Multi-channel dynamic matrix sound system (DMS) is a multi-channel input and output sound system which is based on source synthesis and Huygens' principle. The sound sources are recorded by microphone array and multi-channel independent recording, instead of the field. This paper describes the results of the subjective evaluation experiments between DMS and conventional stereo system by the semantic differential (SD) method. Five parts of the audio materials and a training material, including the human voice, music, sound effects, were used as the stimuli. All of the stimuli were recorded by the DMS and conventional stereo system respectively. The results proof that the effectiveness of DMS, which has a higher level of sound quality and can give the audience the experience of dynamic subjective feelings compared with conventional stereo system. Furthermore, sound designers must carefully consider the influence of gender, age, preferences on the hearing impression.

Abstract: The island survey is important in economic and strategic field, and in recent years the use of remote sensing technology becomes the mainstream in island investigation. As an effective way for improving the efficiency and accuracy of island survey, the automatic segmentation and recognition algorithm has greater significance. For the difficulty in application of deformed model to high-resolution remote sensing images, the segmentation framework of global initial segmentation and local extractive segmentation based on narrow band deformable model is proposed. Based on the sea and land extraction the island initial segmentation is accomplished, and then the narrow band deformable model is used to increase the accuracy of segmentation. Finally the double rings feature of island is used to improve the quality of the segmentation.

Abstract: In order to capture high quality binocular stereo video, it is necessary to manipulate both the convergence and the interaxial to take control of the depth of objects within the 3D space. Therefore the scene understanding becomes important as it can increase the efficiency of parameters control. In this paper, a camera calibration based multi-objects location method is introduced with the motivation that supply prior information of adjusting the convergence and the interaxial during capturing. Firstly, we are intended to calibrate the two cameras to get the intrinsic and extrinsic parameters. And then, we select points of the object in the images taken by left and right cameras respectively to determine its locations in the two images. With three-dimensional coordinate of objects, the distance between the object and camera baseline is calculated by mathematical methods.

Abstract: In this paper, we give a fuzzy decision tree (simply FDT) induction algorithm, named FDT_Ambig, to handle the classification with discrete attributes through the uncertainty reduction. In FDT_Ambig, the uncertainty is measured with classification ambiguity. FDT_Ambig selects the attribute which will cause the further reduction of uncertainty as the expanded attribute for each decision node. The experimental result shows that FDT_Ambig has the better generalization capability in comparison with the FDT induced with classification entropy (FDT_Entr).

Abstract: A co-evolutionary algorithm is proposed for the play between a submarine and a helicopter equipped with dipping sonar. First, the theoretical foundation of co-evolution is elaborated. The movement model of helicopter and submarine, the detection model of dipping sonar under certain ocean environment are established. After defining the strategies of helicopter and submarine and fitness evaluation methods, the process of co-evolutionary algorithm is described. The optimal strategy of helicopter after helicopter evolution, and the optimal strategies of both helicopter and submarine after co-evolution are given

Abstract: Aiming at multi directions analysis problem of surface feature extraction from point cloud data, Curvelet transform is introduced to multi directions analysis of point cloud data. Based on the preprocessing of location and expansion, second-generation discrete Curvelet transform is used to analyze point cloud data. Curvelet transform coefficients are processed to enhance the contour of point cloud data. Nonlinear function is used to process Curvelet transform coefficients of coarse layer. Compromise for soft and hard thresholds is used to process Curvelet transform coefficients of detail layer. Piecewise nonlinear function is used to process Curvelet transform coefficients of fine layer. The data point is reconstructed from the enhanced Curvelet transform coefficient with Curvelet inverse transformation. Initial surface feature is achieved with edge detection. The precise surface feature is achieved with morphological dilation and erosion to filter edge without real shape significance. Example of part point cloud data of brake shell shows the proposed surface feature extraction method can accurately extract surface feature from data point.

Abstract: The traditional high altitude long endurance UAV ground testing system (referred to as: testing system) not only lacks of universality and scalability, also incapable of handling faculties during flying procedure. In the paper, by using the new generation of automatic test system (New ATS), the flight simulation method, embedded technology and fault diagnosis technology, we are able to expand the testing system from ground to the sky, improving the generality of the system and UAV’s testing ability, also ensure the safety and reliability of the UAV flight at the same time.Keywords: Unmanned aerial vehicle; Automatic test system; Fault diagnosis ; Embedded bus

Abstract: The importance of safety climate on safety performance in construction has been highly acknowledged, and the definitions and elements of safety climate have been widely discussed over the years. However, researches about how to improve constructions safety climate have been less focused. The aim of this study was to find the impact of social capital on safety climate. A questionnaire of social capital and safety climate was conducted by 316 employees from 45 construction sites, and an empirical analysis was made by exploratory factor analysis (EFA) and structural model theory (SEM). The results showed that: the cognitive dimension and relational dimension of social capital are significantly positive correlation to safety climate, while the structural dimension is not significant. The findings of this study provide useful information to improve safety climate for construction enterprises.

Abstract: This paper addressed two key issues: firstly, the cost incurred to complete an activity depends on its random duration; secondly, multiple methods to account for an activity cost are introduced. The upper and the lower bounds for cumulative cost curves over time can be tracked along a project progressed, which is obtained by mixing Monte Carl sampling with Gantt chart analysis. Moreover, these two bounds statistically represent the range for the budget cost of work scheduled; thus, the uncertain earned value analysis (EVA) is probed in our investigation. The conclusions indicate that project managers can obtain a degree of flexibility when adopting uncertain EVA to monitor status during project execution, which differs greatly from deterministic situations. Our study aims to illuminate some insights for the application of EVA under uncertain environments.