Advanced Materials Research Vols. 532-533

Abstract: In this paper, a novel method to estimate ARMA time-varying parameter is proposed, based on ESCGMmv grey forecasting model. The estimation procedure of this method consists of two phases, first estimating online ARMA parameter by the least squares method. Then, using ESCGMmv grey forecasting model to forecast the error between and .The model gives an adequate description of the system under consideration. Finally, modify the estimate parameter by the estimate error. Simulation results confirm that the propose method can obtain more accurate estimate time- varying parameter.

Abstract: For decentralized ordered statistics (OS) constant false alarm ration (CFAR) detection system, the parameter estimation and performance analysis in complicated detection condition is a typical nonlinear optimization problem. Owing to the nonlinear property of distributed OS-CFAR detection system, it is seriously difficult to obtain optimal threshold values using some optimization method at the fusion center. This paper provides a novel solution based on an effective and flexible particle swarm optimization (PSO) algorithm. As a novel evolutionary computation technique, PSO has attracted much attention and wide applications, owing to its simple concept, easy implementation and quick convergence. Using this approach, all system parameters can be optimized simultaneously. The simulation results show that the proposed approach can achieve effective performances with the above method.

Abstract: Collecting data from spatially distributed sensor nodes is a generic form of sensor network applications. Multihop forwarding has been broadly used for this purpose, but it could be inefficient in terms of energy consumption.A downside of this approach is an increased data delivery latency, and thus we should optimize the motion of data mule so that we can minimize the latency. In this paper, we survey the existing work on the mobility-assisted data collection by classifying them into three categories based on the mobility exploited: the random mobility, the predictable mobility, and the controlled mobility. We also highlight several open problems on this topic.

Abstract: In this paper, we propose a novel edge and region-based active contour model. We consider geodesic curve and region-based model, and evolve a contour based on global information. Moreover, we add to the level set regularization term in the energy functional to ensure accurate computation and avoids expensive re-initialization of the level set function. Experiments on synthetic and real images show desirable performances of our method.

Abstract: This paper firstly analyzes the importance and necessity of location dependent query in the mobile computing. Then, it proposes a special case in the application of the location dependent query. That is as follows: Inquirers may send the same location dependent query in different but similar positions. However, the server will not deal with them together but treat them separately. Thus, it will not only cause the waste of system resources but also delay disposal of other queries. According to the principal of clustering we propose a new location Analysis Algorithms-similar merging location analysis algorithm (SMLA). By the algorithm, similar queries can be combined into the same query, so as to reduce the load on central servers, improve system efficiency and query processing performance.

Abstract: It is well known that by using caching geo-data, the pressure from a GIS server is alleviated greatly, and the client experience is improved sharply. At present, most tools for generating caching geo-data suffered a poor performance in transferring over networks, especially when the parallel computing technology is not adopted. In this paper, we introduce a middleware model based on MPICH2 and OGC WMTS. Moreover, we apply the computer cluster technology to generate tiles over the huge size of image data to high up the response time rapidly and efficiently. The model as the foundation of realization will be used to implement the caching geo-data interoperability by standard interfaces that process various types of geo-data including the distributed resources throughout the network.

Abstract: Axle detection is an important way to ensure the safety of rail transport. To meet the requirements of the Ministry of Railways, ZTY-1 type digital ultrasonic flaw detector is developed. It is designed based on VC++ 6.0 and runs on the PC system. The detector consists of five functional parts, which are flaw detecting, daily performance checking, quarterly performance checking, probe test and data management. In this paper, design of the detector’s software system is introduced, as well as solutions to some problems such as waveform flicker, double detection, waveform playback and document print.

Abstract: Aiming at the problem of joins query in MANET, we proposed a grouping cache mechanism, which builds grouping cache considering the features of data. The proposed mechanism can implement the cooperating cache between groups and update cache information dynamically, which leads to the improvement of query hit ratio and decrease of response time. Based on the grouping cache, a novel joins query algorithm is presented. The algorithm optimizes the query plan using dynamic programming scheme. Then it constructs an optimal execution plan for each sub join query with available cache data taken into account. Simulation results indicated that the group-based cache mechanism can improve the hit ratio, reduce query response time and conserve energy of the network efficiently.

Abstract: To improve the data mining efficiency, analyzed existing algorithm for data mining.However,it has some uncertain knoledge are a major concern in data mining, it is great difficulty for data mining in web knoledge,which contains more uncertainty than an affirmatory one dees. In this paper, with web mining method based on the cloud computing analysis. One is the main issues related to the web knowledge problem are detaled, the other is the commonly used methods of handling web knowledge problems in data mining are reviewed, with a diseussion about a number of their known strength and weakness. This can be used to improve the quality of information service on web and can assist the web master to optimize site architec and increase visiting efficiency. The results of experiment show that it is better than that of the existing methods proposed in the literature.

Abstract: Low-altitude unmanned airship remote sensing is attractive to various applications. However, at present, since the airship is bulky, weak to resist wind, unstable to flight attitude, and can not be equipped with specialized remote sensing sensors, image data processing is confronted with new challenges when traditional data processing methods are used. In this paper, improved hybrid ant colony algorithm (HACA), a new image matching method, is proposed. Firstly we perform a pre-registration process that roughly aligns the image pairs by GPS/electronic compass geolocation. Once the pre-registration is completed, a fine-scale registration process is executed by applying a hybrid algorithm of genetic algorithm (GA) and ant colony algorithm (ACA) based on neighborhood search strategy that is detected by the linear quadtree Morton coding. The image pairs are then matched by using optimal solution obtained from the automatic updates of ant colony pheromone. By compared with traditional genetic algorithm and ant colony algorithm, the improved HACA results show that search calculation time is increased by the maximum 406℅, standard root mean square error of image matching by the best 235℅. The experiment result proves that improved HACA exactly provides an effective method for image matching. The local maxima of the function can be avoided efficiently and search speed of the global optimum is increased greatly.