Applied Mechanics and Materials Vols. 182-183

Abstract: In digital image processing, classical histogram equalization produce the loss of image information the caused by gray level of the output image may be too much merged. This paper mainly based on the concepts of the set approximate, classification approximate measurement and importance in the rough set theory, divided the appropriate boundary of the set, proposed an improved histogram equalization method, thus effectively solved the problem, gave the experimental simulation confirmation.

Abstract: In this paper, the grid computing environment resource reservation problem of using the parallel machine, proposed the relaxed time parallel scheduling models and algorithms support resource reservation. The simulation results of FCFS and EASY backfill algorithms in resource utilization, job bounded slowdown factor and the success rate of Advanced Reservation (AR) jobs were studied. Show that the relaxation mechanism, the average waiting time and the average bounded slowdown factor of non-reserved jobs down. EASY backfill algorithm which guarantees AR jobs quality of service at the same time, the better the performance improvement of non-AR jobs.

Abstract: Localization has been a major challenge in Wireless Sensor Networks (WSNs), especially for the applications requiring the accurate position of the sensed information. In this paper, we propose a new localization algorithm based on the Centroid algorithm and the DV-Hop algorithm to improve the positioning accuracy without increasing any extra hardware for sensor nodes. This paper firstly analyzed the advantages and disadvantages of the centroid algorithm and the DV-Hop algorithm. Then we put forward an iterated hybrid algorithm, which is comprised of three steps. Firstly, obtaining the initial location of each unknown node by using the centroid algorithm; secondly, computing the distances among each unknown node to the anchor nodes based on the DV-Hop algorithm; finally, Taylor Series Expansion (TSE) algorithm is utilized to estimate coordinate of each unknown node. Simulation results show that our iterated hybrid algorithm has better positioning accuracy.

Abstract: The application of coherent cube and volume curvature algorithm to analyze and process the three-dimensional seismic data of Ordovician carbonate rocks in the Tazhong area of Tarim Basin, and to predict the faults and fractures development. After the comparison, coherent cube algorithm is fit for prediction of main faults development with the clear result in oilfield exploration stage , volume curvature algorithm is fit for prediction of faults and fractures development with the abundant information in oilfield development stage. Therefore, according to different purposes of exploration and development, different algorithms could be applied to prediction of faults and fractures. This would be useful to guide the oilfield exploration and development.

Abstract: This paper presents an improved method to detect moving object and obtain the relative accurate location. First we detect the edge difference of continuous frames. Then we utilize the contour matching to find the edge pairs in order to reach a good detection of the moving object and location. The extensive experiments show that our method is robust and efficient to the moving object detection.

Abstract: A new approach is presented to match two images in presenting large scale changes. The novelty of our algorithm is a hierarchical matching strategy for global region features and local descriptors, which combines the descriptive power of global features and the discriminative power of local descriptors. To predict the likely location and scale of an object, global features extracted from the segmentation regions is used in the first stage for an efficient region matching. This initial matching can be ambiguous due to the instability and unreliability of global region feature, and therefore in the later stage local descriptors are matched within each region pair to discard false positives and the final matches are filtered by RANSAC. Experiments show the effectiveness and superiority of the proposed method in comparing to other approaches.

Abstract: The working environment of the PLC application system is bad as usual, and there are kinds of interference around. In this paper some main sources of the disturbance of the PLC application system and the interference suppression measures was discussed in order to apply the PLC system reliably.

Abstract: To calculate difference scheme’s accuracy of differential equation, the normal way is using Taylor format. This paper utilizes tectonic process of differential format to calculate truncation error and gets the accuracy. Compared with the traditional way, not only reduces the amount of calculation, but also calculates the accuracy more quickly and accurately for high-order equations.

Abstract: In this paper a novel document clustering spectral algorithm is proposed, which uses a minimum maximum principle. Firstly the low dimensional embedding of documents is attained by eigenvalue decomposition, and then a minimum maximum principle is used to get the initial seeds for k-means algorithm. Finally, K-means algorithm is performed to get the clustering results. Experimental results show that the clustering results found by this method is better than traditional clustering algorithm.

Abstract: Movement whether it is actual or imaginary can produce different electroencephalogram (EEG) signals. How to extract features of signals and accurately classify them is a key to brain-computer interface(BCI) system. In the paper, BCI competition data downloaded from BCI website are used as study object, through time-domain analysis and frequency-domain analysis, according to the attribute of event-related synchronization (ERS) and event-related desynchronization (ERD) during imagery movement, energy difference of lead C3 and C4 are selected as features and wavelet package is used to extract them. Probabilistic neural networks (PNN) is used as classification method. Compared with other two calssification methods such as support vector method (SVM) and liner classifier, the classification accuracy rate of PNN reaches to 89.2% steadily and is higher than them. It is proved that the method provided in the paper are effective for identifying imaginary movements.