Advances in Science and Engineering II

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Authors: Yun Ge, Yan Feng Sun, Bao Cai Yin, Heng Liang Tang
Abstract: 3D face sample is an important data platform for model training, algorithm design. Subject to the constraint of data acquisition equipment the size of current 3D face databases are relatively small and insufficient. To solve this problem, this paper presents a modeling way for generating 3D novel samples based on surface stitching. First we use morphable model to build a global model. Then, we replace each patch of the global model based on surface stitching. We demonstrate that with appropriate choice of local models it is possible to reliably generate new realistic face samples.
Authors: Fu Lai Yao, He Xu Sun
Abstract: This paper presents a class of optimization functions, and gives the optimal value. The optimal conclusion is applied to energy optimization for general devices. When the total load is fixed and the devices are used with same model, the optimal control method is given: adjusting each device to the same load, the minimum energy is required.
Authors: Shan Lin, Tao Lin, Zhan Wen Liu
Abstract: A bit full adder is a very important component in the digital system. Design of a full-adder circuit, as an example, by changing its output function expression in the form of expression, use the gates, decoder, multiplexer etc 74 series devices, the eight circuits realization form are given respectively, and briefly analyzed the advantages and disadvantages of the various circuit implementation. The example show that the design of combinational logic circuits has mobility and variety, it could give the instructiveness and the guiding for other design of combinational logic circuits.
Authors: Hai Feng Li, Ning Zhang
Abstract: Maximal frequent itemsets are one of several condensed representations of frequent itemsets, which store most of the information contained in frequent itemsets using less space, thus being more suitable for stream mining. This paper focuses on mining maximal frequent itemsets approximately over a stream landmark model. A false negative method is proposed based on Chernoff Bound to save the computing and memory cost. Our experimental results on a real world dataset show that our algorithm is effective and efficient.
Authors: Fang Yuan Wu, Feng Kong, Jiang Yun Yao
Abstract: This paper presents an intelligent fault diagnostic approach for a steer-by-wire (SBW) system. A rough set model is utilized to reduce the redundant information. On the base of the reduction, the classifying rules can be extracted. A radical basis function (RBF) neural network optimized by particle swarm optimization (PSO) algorithm is designed to learn the fault rules that are extracted from the reduction of the redundant information. The proposed approach is simulated in MATLAB. Simulation results show that the proposed intelligent fault diagnostic algorithm provides a higher level of diagnostic accuracy than the approach without any optimization.
Authors: Kun He, Wen Qi Huang
Abstract: This paper presents a Fit Degree based Two-step Lookahead algorithm (FDTL) for the NP hard container loading problem. Several evaluation criteria, the fit degrees, are defined to construct different initial solutions as well as to explore different portions of the search space. Then a two-step lookahead tree search procedure is incorporated for the sufficient search such that the algorithm could find better layouts compared to a one-step lookahead tree search procedure. FDTL is tested on two sets of typical instances: 800 instances as proposed by Bischoff and Ratcliff (1995), and 15 instances as proposed by Loh and Nee (1992). Experiments show that this new algorithm improves among the known algorithms on the space utilization.
Authors: Yan Li, Yang Gao
Abstract: Vehicle navigation system (VNS) is a world acknowledged efficient way of solving the urban traffic problem, and road network database is one of the core component parts in the system. In order to improve performance of VNS, this paper conducts a research on data organization technique of road network, and proposes a novel data model of road network, which includes spatial index and topology structure. Firstly, some common spatial index structures, such as regular grid index, R-tree index and quad-tree index, are studied, and a novel spatial index structure based on “hierarchical quad-tree and R-tree” index of two ranks is proposed. This structure can greatly reduce the access time of map data and raise index performance. Secondly, a topology model of road network based on arc-relation is presented, which can effectively solve turn penalty problems in the conventional topology model based on vertex-relation and represent real road network. Thirdly, a real topology storage structure using adjacency list is designed and a corresponding creating algorithm is put forward. Finally, the tests on the practical system prove that the proposed model effectively support kinds of data-processing and greatly raise the performance of the system.
Authors: Han Ning Wang, Wei Xiang Xu, Chao Long Jia
Abstract: The application of high-speed railway data, which is an important component of China's transportation science data sharing, has embodied the typical characteristics of data-intensive computing. A reasonable and effective data placement strategy is needed to deploy and execute data-intensive applications in the cloud computing environment. Study results of current data placement approaches have been analyzed and compared in this paper. Combining the semi-definite programming algorithm with the dynamic interval mapping algorithm, a hierarchical structure data placement strategy is proposed. The semi-definite programming algorithm is suitable for the placement of files with various replications, ensuring that different replications of a file are placed on different storage devices. And the dynamic interval mapping algorithm could guarantee better self-adaptability of the data storage system. It has been proved both by theoretical analysis and experiment demonstration that a hierarchical data placement strategy could guarantee the self-adaptability, data reliability and high-speed data access for large-scale networks.
Authors: Yuan Bin Hou, Yang Meng, Jin Bo Mao
Abstract: According to the requirements of efficient image segmentation for the manipulator self-recognition target, a method of image segmentation based on improved ant colony algorithm is proposed in the paper. In order to avoid segmentation errors by local optimal solution and the stagnation of convergence, ant colony algorithm combined with immune algorithm are taken to traversing the whole image, which uses pheromone as standard. Further, immunization selection through vaccination optimizes the heuristic information, then it improves the efficiency of ergodic process, and shortens the time of segmentation effectively. Simulation and experimental of image segmentation result shows that this algorithm can get better effect than generic ant colony algorithm, at the same condition, segmentation time is shortened by 6.8%.

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