Advanced Materials Research Vols. 546-547

Abstract: Semantic process modeling approaches are used in modelling, making use of the process ontology, which is the preferred BPMO. In the process of semantically modeling, using ontology to describe the business process is an important step. Therefore, the text proposed for BPMO-based OWL representation of business process, lays the foundation for resolving issues, such as semantic annotation, machine-understandable, and reasoning on business process. We will put forward the construction and representation of our business process knowledge; examine the workshop business process activities; according to business rules, describe business processes on the basis of the BPMO; represent BPMO-based process on the basis of ontology modeling language OWL; model the process on the foundation of softeware BPMO Modeller. Workshop product packaging as an example, we will verify business processes based on BPMO methods.

Abstract: The seismic attribute has multi-solution, and can not correspond to geological bodies exactly, a variety of seismic attributes information interpreted by changes in their characteristic parameters was prone to conflicts, the fusion technology of multi-attribute fuses the independent single-attribute in seismic data together, it can use the advantage of each attribute to display the characterization of geological body vividly. In this paper, we extract the attributes slice under the control of isochronous stratigraphic framework along layers, optimize the attribute using reference well data to select three independent attributes that can reflect lithological and physical properties, and fuse the three favorable attributes using the image of RGB fusion technology for better identification of sedimentary facies.

Abstract: A data fusion method which based on fuzzy theory and evidence theory was discussed in this paper， and it is applied to the vehicle type recognition simulation research using some multi-sensor characteristics such as the appearance and the length of the vehicle. The experimental results show that this method can avoid the limitation of single sensor, reduce the sensors uncertainty, and improve the identification accuracy.

Abstract: Genetic Algorithm affords a new solution to solve complicated problems, especially some NP problems. Genetic Algorithm’s coding method decided the algorithm efficiency and the complicated degree of program design which should use different coding methods to solve different types of problems.

Abstract: Recently, l₁-graph was proposed as a new graph construction procedure. Compared with the kNN-graph and ε-graph, l₁-graph possesses three advantages: robustness to data noise, sparsity and datum-adaptive neighborhood selection. In this paper, we propose a novel semi-supervised feature extraction method based on l₁-graph termed Semi-supervised Sparsity Discriminant Analysis (S³DA). The proposed S³DA maintains the advantages of l₁-graph, and more importantly, it has better capacity of discrimination for classification. Experimental results on face and gene expression databases demonstrate our proposed approach outperform some other state of the art algorithms, and also show the feasibility and effectiveness of our proposed approach.

Abstract: Due to the different structure of the machine parts, machine vibrations sent audio signal have different frequency. The early defect, audio signal can be analyzed well by wavelet packet transform. After wavelet packet decomposition and reconstruction, Audio signal noise reduced. And then through high and low frequency decomposition, we can constitute the energy characteristics. The experiment shows: the extracted features have good structure.

Abstract: OpenGL is independent of the window system, and did not provide the function to draw complex three-dimensional model, so it is difficult to properly control OpenGL and create complex model .This paper will achieve to build complex three-dimensional model efficiently and take good effect in practice with combining OpenGL and 3Dmax or with the help of functions of VC++ to develop based on applying window frame of Windows powerfully.

Abstract: In order to reduce the noise of acquisition signal in laser cutting, an adaptive wavelet denoising method is proposed in this paper. Based on the analysis of the limitations of traditional threshold method, the particle swarm optimization algorithm is used to select the optimal threshold of wavelet. Compared with the commonly hard and soft threshold method, the experiment results show that the method used in this paper is relatively stable, and can reduce noise excellently. The method can provide more accurate signal for quality analysis in laser cutting .So the method can be used in noise denoising of pulse-induced acoustic sound.

Abstract: Automatic exposure control is the process of controlling the exposure time of the digital imaging system to obtain the desired image which can fit the human vision during the imaging process. A new automatic exposure algorithm for astronomical image is proposed. The pixel value weight is determined by exploring the maximum range of the image histogram. Additionally, the structure of the implementation based on FPGA and experiment results for real data are given. The experiment results show that the proposed algorithm can effectively achieve the real-time automatic exposure control.

Abstract: The zero drift of sensor and its solution are presented in this paper. The basic principle of data fusion with two-dimensional regression analysis is expounded and the experimental data of any pressure sensor are fused with the two-dimensional regression analysis. Besides, the input-output mathematical model of sensor under the influence of temperature is established. At last, the linear, fitting and fusion methods are compared.