Advanced Materials Research Vols. 1049-1050

Abstract: Maritime search and rescue is important for the maritime traffic safety. A maritime search and rescue capability evaluation algorithm based on cloud model is proposed in this paper. Firstly, we established the evaluation system; Secondly, we determined the expert evaluation cloud model according the scoring; Thirdly, we calculated the evaluation result by the comprehensive cloud; Finally, we used the digital characteristics to restore the cloud chart. The experimental result shows that our method is objective and accurate.

Abstract: The traditional methods of power flow calculation are no longer applicable for microgrid for the reason that there are many kinds of DG(distributed generation) in it, the mathematical models of these DGs are different from traditional generations. An unified method is proposed to improve Newton-Raphson power flow calculation method for the bus types of PQ(V) and PI after analyzing and establishing power flow calculation model for each kind of DG. It is proved that this method is correct by comparing the results with the simulation results of DigSILENT. The influences on voltage and power loss in microggirds brought by DGs are studied at last.

Abstract: Efficient network resource utilization is crucial in Virtual Network Embedding (VNE) problem. The diversity of virtual topologies belong to various services providers (SPs) severely affects the efficiency of VNE algorithms and fairness between SPs. This paper proposes a fair VNE algorithm with a topological transformation mechanism. Such mechanism will transform virtual topology to reduce complexity. Then the algorithm will felicitously map the virtual network onto substrate network through a Disperse Particle Swarm Optimization (DPSO) based process. Simulation results show that due to the topological transformation procedure the algorithm can achieve more fairness than traditional VNE algorithms.

Abstract: The network system reliability research contains a number of problems, such as: Reliability analysis and reliability design, reliability, maintenance and a lot of problems so on. The calculation of reliability of the network is the important area of network reliability analysis, State enumeration method and principle of a class, don't pay the product and method, the factor decomposition method is a classic accurate algorithm of computing network reliability. Due to the difficulty of precise calculation, in the method, appeared and bound method, Monte carol method, the reliability of the approximate algorithm. Compared with the accurate algorithm, approximate algorithm is still under development. So far, no recognized classic algorithms, so the method to improve calculation accuracy, reduce the complexity of the target of the researchers.

Abstract: In order to predict the maize yield of changes in the following years for our managers and framers, we have applied a statistical model based on time series analysis. Nowadays, there is a variety of methods on yield prediction in agricultural .In order to prove the accuracy of prediction models, more than prediction model can be used. In the paper, the establishment of ARIMA (2, 1, 1) model was been established by using the timing sequence analysis on yield data. The partition results can not only guide farmer, provide an important method for accurately predicting in agricultural products, and can be used to implement variable input and precise fertilization recommendation.

Abstract: Graph clustering is an important technology in graph analysis area, the measure of similarity between node of graph is the presise for graph clustering. SimRank algorithm is a kind of universal structure similarity calculation model which is proposed by Jeh and Widom. SimRank algorithm using iterative method to calculate the similarity between nodes, so the time and space complexity is very high. With the rapid increase of data, the ability of single machine can not meet the requirement of the large-scale data calculation. In this paper, the distributed SimRank algorithm was proposed based on Mapreduce and was used to measure the similarity of graph. Then the distributed AP clustering algorithm was designed for clustering analysis graph nodes. The experimental was executed to compare the clustering running time and speedup and results show that the method can efficiently complete graph nodes similarity measure and clustering the large graph effectively.

Abstract: This study focuses on analytical solution of a fractional Pennes bioheat transfer equation on skin tissue. The method of separating variables, finite Fourier sine transformation, Laplace transformation and their corresponding inverse transforms are used to solve this equation with three kinds of nonhomogeneous boundary conditions, namely, Dirichlet, Neumann and Robin boundary value conditions. The exact solutions are discussed and derived in the form of generalized Mittag-Leffler function. In addition, numerical results are presented graphically for various values of order factional derivative.

Abstract: This paper proposes a novel multi-view learning framework which leverages the information contained in pseudo-labeled images to improve the prediction performance of image classification using multiple views of an image. In the training process, labeled images are first adopted to train view-specific classifiers independently using uncorrelated and sufficient views, and each view-specific classifier is then iteratively re-trained using initial labeled samples and additional pseudo-labeled samples based on a measure of confidence. In the classification process, the maximum entropy principle is utilized to assign appropriate category label to each unlabeled image using optimally trained view-specific classifiers. Experimental results on a general-purpose image database demonstrate the effectiveness and efficiency of the proposed multi-view semi-supervised scheme.

Abstract: When the number of arrays increases, the triangular systolic array for QR decomposition of the received data matrix has an increasing significantly hardware resource consumption. In order to reduce the hardware cost, the triangular systolic array (TSA) architecture could be modified into a multiplexing architecture called MQRD which could call the same module at the different time. Then MQRD was designed and simulated on the software ISE. More, MQRD was added to the adaptive beanforming system to study its computing performance. The results showed that MQRD not only kept the numerical stability and scaled well, but also reduced the hardware resource cost efficiently. Theoretical analysis and simulation results show that MQRD can reduce hardware cost efficiently. So, MQRD is a better choice than TSA in the multi-antenna system.

Abstract: This paper proposes a novel multi-view semi-supervised learning scheme to improve the performance of image annotation by using multiple views of an image and leveraging the information contained in pseudo-labeled images. In the training process, labeled images are first adopted to train view-specific classifiers independently using uncorrelated and sufficient views, and each view-specific classifier is then iteratively re-trained using initial labeled samples and additional pseudo-labeled samples based on a measure of confidence. In the annotation process, each unlabeled image is assigned appropriate semantic annotations based on the maximum vote entropy principle and the correlationship between annotations with respect to the results of each optimally trained view-specific classifier. Experimental results on a general-purpose image database demonstrate the effectiveness and efficiency of the proposed multi-view semi-supervised scheme.