Advanced Materials Research Vols. 108-111

Abstract: Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate professionals, association rule mining is receiving increasing attention. The technology of data mining is applied in analyzing data in databases. This paper puts forward a new method which is suit to design the distributed databases.

Abstract: We investigate inter-session network coding for networks with heterogeneous receivers in this paper. Based on layered source coding, we define the hierarchical inter-layer random network codes, and propose a hierarchical multicast scheme. Moreover, we compare our hierarchical multicast scheme with the layered multicast schemes in theory and with simulations. Simulation results show that our hierarchical multicast scheme can achieve the optimal aggregate throughput for some networks where the layered multicast schemes are suboptimal.

Abstract: This paper proposed a new method of image registration based on clustering algorithm. It used clustering algorithm to cluster all the feature vectors of images, and adopted EM algorithm to optimize the parameters and algorithm. Experimental result shows that the proposed image registration method can improve the precise of image registration, and reduce error.

Abstract: Direct 3D volume segmentation is one of the difficult and hot research fields in 3D medical data field processing. Using K-means clustering techniques, a new clustering segmentation algorithm is presented. Firstly, According to the physical means of the medical data, the data field is preprocessed to speed up succeed processing. Secondly, the paper deduces and analyzes the clustering and segmentation algorithm and presents some methods to increase the process speed, including improving cluster seed selection, improving calculation flow, and amending pixel processing and operational principle of algorithm. Finally, the experimental results show that the algorithm has high accuracy when used to segment 3D medical tissue and can improve process speed greatly.

Abstract: This paper presents a novel transport layer protocol for multi-level wireless sensor networks. The node of lower level uses a lightweight transmission protocol, which predigests the head of segment and a six-state finite state machine is applied. In order to make the highest nodes convenient for connecting with exterior networks, we modify TCP in the aspects of segment caching and local segment retransmissions, and use the TCP modified in wireless sensor networks directly. Simulation results show that our design can improve the communication capability of the transmission layer in multilevel wireless sensor networks greatly.

Abstract: Existing image annotation approaches mainly concentrate on achieving annotation results. Annotation order has not been taken into account carefully. As orderly annotation list could enhance the performance of image retrieval system, it is of great importance to rank annotations. This paper presents an algorithm to rank Web image annotating results. For an annotated Web image, we firstly partition the image by a region growing method. Secondly, relevance degree between two annotations is estimated through considering both semantic similarity and image content. Next, the regions of unlabeled image to be ranked serve as queries and annotations are used as the data points to be ranked. And then, manifold-ranking algorithm is executed to get the ordered annotation list. Experiments conducted on real-world Web images through NDCG metric demonstrate the effectiveness of the proposed approach.

Abstract: This paper presents LDA-based automatic image annotation by visual topic learning and related annotation extending. We introduce the Latent Dirichlet Allocation (LDA) model in visual application domain. Firstly, the visual topic which is most relevant to the unlabeled image is obtained. According to this visual topic, the annotations with highest likelihood serve as seed annotations. Next, seed annotations are extended by analyzing the relationship between seed annotations and related Flickr tags. Finally, we combine seed annotations and extended annotations to construct final annotation set. Experiments conducted on corel5k dataset demonstrate the effectiveness of the proposed model.

Abstract: A comparative method for studying road network based on GIS will be proposed in this paper, in which Axwoman is involved as an ArcView extension for urban morphological analysis. Finally, the case of Nanyang city is applied to show the expansion of road network in 1984, 1996 and 2008, by comparing the changes of global integration value, local integration value and connectivity value of whole city, special roads and different sub-areas respectively.

Abstract: Leader can be regarded as the core resource and soul of the enterprise, because the leader is charged of making policies and strategies, which would affect the development orientation of the enterprise. To further analyze, the trait and character of a leader would directly decide what kind of strategies or actions would be adopted facing the given situation. In practice we can see that the successful leaders express some common things and traits, which would be meaningful to analyze the trait that successful leaders own, and to analyze what kind of trait the entrepreneur needs to possess. Relevant literatures and investigations were cited in this paper to make the research more persuasive. On the basis of literature review, a two-layer leader traits model was brought forward, which classify the leader’s needed traits into two groups, one is basic traits that would be remain constant from time to time. The other is changeable group that would be affected by the particular economic and social situation and needn’t to be persisted in. Then we make further analyze on the domestic entrepreneurs needed traits on the basis of the existed investigation. Relevant basic traits and changeable traits were drawn on the basis of the conclusion of the investigation made by the task Group of enterprise research institute. The conclusion of this paper would be meaningful for the selection and cultivation of leaders and entrepreneurs in China.

Abstract: In order to solve the problem in k-means algorithm that inappropriate selection of initial clustering centers often causes clustering in local optimum and the time complexity is too high when handling large amounts of data, a fusion clustering algorithm based on geometry is proposed in this paper. The result of experiments shows this algorithm is better than the traditional k-means and the k-means++ algorithms, with higher quality and faster speed. And at last in this paper, we apply it in marine engineering.