Applied Mechanics and Materials Vols. 303-306

Abstract: Considering the low efficiency of massive data retrieving in traditional parallel processing, by taking advantage of the great availability of cloud computing paradigm, we propose a hybrid solution based on Map-Reduce model and distributed computing framework--Spark. Moreover, we design and implement this solution in our lab. The results show that the solution can effectively improve the performance of massive data retrieving.

Abstract: Load balancing problems play a special role in the operation of parallel and distribution systems. The core technology of load balancing is the task scheduling. In order to achieve equally distribute the load on processors and maximize their utilities while minimizing the total task execution time, this article analyses a large number of data retrieval requests content. It shows different tasks have different resource occupation rate on the server node and the current server load is also different. The demand of different task types on CPU and I/O resources are not same. So, this paper presents a dynamic load balancing algorithm which is based on task classification, and applies it to the cluster system data retrieval.

Abstract: Fast video tracking can result in irregular sampling tracking problem. This paper transforms the irregular sampling measurement to the time-varying parameters and develops a model with adaptive parameters on line by the autocorrelation function of Markov random processing. Simulations and experiments show the good fast-tracking performance can be get by the model developed here even at very high irregular rate of measurement sampling time.

Abstract: We will undertake an in-depth analysis of the data conversion,and take a detailed study of thoughts and realization methods of data conversion. On the basis of methods above-mentioned,we design and implement the sofeware of the data conversion between the heterogeneous databases of MS SQL Server,Oracle,Access,Excel.

Abstract: This paper presents an algorithm about the extraction of left channel video object which based on high-order statistical change detection and the segmentation of right channel video object based on parallax matching. This algorithm combines the advantages of disparity map segmentation and multiple frame difference motion segmentation. First of all, through the segmentation of the parallax matching video objects in the right channel, we can get primary partition templates in different layers of parallax targets; Secondary with high-order statistical change detection, we can extract video objects in the left channel from templates. Finally we obtain the accurate moving target. Based on 3D multi-view video segmentation, we use H.264-based method to encode the main image flow and then get object-based 3D video coding

Abstract: Firstly challenges in P2P media streaming applications were pointed out, then some recent research results such as application-level multicast tree, heterogeneity of network and incentive mechanism and so on were introduced. This paper has proposed a new model of application level multicast named DHCM (density-based hierarchical clustering multicast)which has improved IHC arithmetic．DHCM divides the hosts into many hierarchies according to their density，and constructs a density tree to realize the shortest routing．The tree delivers the content of video server to each host in density tree and uses a P2P scheme in data transmission．By this way the application-level multicast has been realized．This density tree has the homogeneity and monotonic properties．The experiment result has proved that DHCM can transmit the video stream efficiently and robustly.

Abstract: With the development of information technology, electronic data exchange to some extent takes the place of the traditional transaction based on paper contract, which challenged the legal system and the information security system while facilitating the transaction. This paper studied the typical procedures of signing a E-commerce contract, found that there are some problems on legal and operation levels, especially on the TTP system, and put forward some suggestions to improve it.

Abstract: The webcams are installed on students’ LCD monitors to take, via an ordinary video processing program, the half-length pictures of students in a real-time manner whenever they are distracted from the class or not in their seats. Result shows that the grades of the students in the experiment group become less scattered. This means the difference among students’ grades have been reduced and students’ overall grades have also been improved.

Abstract: This paper presents an algorithm for three-dimensional medical image segmentation based on the Contrast and Shape Constrained Local Binary Fitting improved model. Due to Local Binary Fitting model is sensitive to initialization and easy to fall into local extreme value, the new algorithm adds contrast constraint term to the Local Binary Fitting model, aiming at solving the common existed problem of inconsistent brightness and low contrast ratio. Adding shape constraint term can improve the original Local Binary Fitting model by constructing shape constraint energy field around the average shape by the level set method to deal with the leak of deformation curve. In order to promote the speed of model evolution, the kernel function is simplified. Two-dimensional Contrast and Shape Constrained Local Binary Fitting model is then extended to three-dimensional and a three-dimensional dental pulp image is segmented. Experimental results show that the segmentation accuracy, the connection degree and the efficiency of the new method are greatly improved compared to original LBF model.

Abstract: In this study, a system is designed using the local network in a computer classroom to monitor students’ learning situation and classroom order in a real-time manner. Teachers can use a network management program to monitor students’ use of computers. A questionnaire on the installation of computer classroom monitoring system is created after a post-test is administered to the experiment group. The result shows that 59.52% say that pay more attention to what teachers teach in the class.