Advanced Materials Research Vols. 121-122

Abstract: Both top management support and departmental manager IT knowledge have significant effect on the IT application maturity. However, little is known about the dynamic effect of the top management support and the departmental manager IT knowledge on the IT application maturity. A multilevel study of 283 departmental managers from 42 companies supports that company ITAM moderates the relationship between the top management support and department ITAM, and the relationship between the departmental manager IT knowledge and department ITAM. The effect of top management on department ITAM will be weaker in companies with higher company ITAM, while the effect of the departmental manager IT knowledge on department ITAM will be stonger in companies with higher company ITAM. Theoretical and practical implication is discussed.

Abstract: It has important practical significance to study technical innovation capacity deeply for enterprises which are in the economic globalization. This paper directs at the form of property value are interval numbers and the weight information is completely unknown case, It determines the weights of the attributes by the entropy method based on changing interval numbers decision matrix into single point decision matrix, then measure and evaluate enterprise technical innovation capacity scientifically. Finally, a example indicates that this method is a scientific and practical one for enterprises.

Abstract: In this paper, We carried a series of actual inspecting, monitoring and evaluation on the north boiler room of Hebei University of Engineering .The results show that: the main source of the noise in the boiler room is not the combustion noise, but the aerodynamic noise generated from the induced draft fan and blower by monitoring and analysis and single-factor evaluation. The sensitive point around the school north boiler room and measuring points in the internal part of the boiler room both exceeded.

Abstract: Greenhouse irrigation control technology is an important content in the research of modern agriculture technologies. The traditional agriculture greenhouse used man-made irrigation approach to add moisture and nutrient to crops, which is difficult to control and easily to cause resource waste. The paper brought out a networked agriculture greenhouse irrigation control based on wireless network, which obtained temperature and humidity information of crops with network sensor and distance control irrigation system with algorithm, so that the automation of supply be achieved. The research fully utilizes modern computer network technologies and improves the accuracy of agriculture greenhouse irrigation control and work.

Abstract: The traditional algorithms of shortest path, different path and etc can only solve the path optimization problems of static network. Based on the fact of actual transport network as dynamic random network, the paper used method of shortest route to optimize the path. The solution of shortest route was on the basis of genetic algorithm. The paper designed operators of crossover, mutation and selection. In addition, the specific example of dynamic random network route selection based on the proposed algorithm also verified the feasibility of the algorithm.

Abstract: Color control for color Scanner is a key and difficult technique in Computer color image reproduction. After analyzing rendering principle of color scanner a new color control model based on subsectional fitting is preseed. First, The paper analyzes the color error source of scanner in theory; Then standard color target is taken for experimental sample to substitute color blocks in color shade district for complete color space to solve the difficulties of experimental color blocks selecting; Third the model for correcting color error is deduced; Finally the experimental results show that the model can improve scanner color control accuracy and can be used in scanner color control practically.

Abstract: Data replication is adopted to improve data access performance in cloud computing environment. When different sites hold replicas, there are significant benefits while selecting the best replica. In this paper, we propose a new replica selection algorithm based on prediction. Analyzing the factors infecting replica selection, The grey system theory is utilized to help predicting the data response time on the basis the GM(1,1) grey dynamic model; Meanwhile the Markov chain is applied to achieve state transition probability matrix to predict the reliability of replicas in the form of probability by the system state classification. The simulation results show that in our replica selection model, the prediction is valid, helpful to selection decision, and is able to achieve load balance between nodes holding replicas.

Abstract: In this paper, including the introduction of image processing and image processing factors influence the discussion, after the RGB image access to the transformation of HSV, mainly through the robot to select the image of the identification process design, completed the capture of a robot A specific color of the entity, after the robot moves to give you accurate basis for the judgment. First of all, the introduction for images on the basis of the relevant knowledge is presented. Second, the image and the image of the divisions are briefly introduced. Third, we proposed the image factors and image processing technology. Fourth, conversion from RGB to HSV model is presented. Finally, we designed the image of the robot to access and identify procedures modular.

Abstract: On the basis of wavelet packet-characteristic entropy(WP-CE) and multiclass fuzzy support vector machine(MFSVM), the author proposes a new fault diagnosis method of vibrating of hearings，in which three layers wavelet packet decomposition of the acquired vibrating signals of hearings is performed and the wavelet packet-characteristic entropy is extracted，the eigenvector of wavelet packet of the vibrating signals is constructed，and taking this eigenvector as fault sample multiclass fuzzy support vector machine is trained to implement the intelligent fault diagnosis. The simulation result from the proposed method is effective and feasible.

Abstract: Support vector machine (SVM) is a novel machine learning method based on statistical learning theory. SVM is powerful for the problem with small sampling, nonlinear and high dimension. A decision directed acyclic graph(DDAG) based on SVM classifier is applied to fault diagnosis of power transformer. We optimize the structure of a decision directed acyclic graph by putting SVM with higher generalization ability at the upper nodes of the decision tree. The test results show that the classifier has an excellent performance on training speed and reliability.