Abstract: Flight simulator fidelity is assessed in pitch task. In the introduction of the assessment for the flight simulator fidelity, the assessing method is specified, and then the required subsystem models are described. The results of an example with pitch task show that the assessing procedure is quite contributive
Abstract: Aiming at problems such as: surface interpolation reconstruction of points cloud data，surface hole filling and two simple surface connection, a neural network arithmetic was employed. Based on radial basis function neural network, simulated annealing was employed to adjust the network weights. The new arithmetic can approach any nonlinear function by arbitrary precision, and also keep the network from getting into local minimum for global optimization feature of simulated annealing. MATLAB program was compiled, experiments on points cloud data have been done employing this arithmetic, the result shows that this arithmetic can efficiently approach the surface with 10-4 mm error precision, and also the learning speed is quick and reconstruction surface is smooth.
Abstract: Analysis and evaluation to quality and precision of reconstruction model is an important technique in reverse engineering, determining avail and accuracy of reconstruction model. Error analysis and precision evaluation have been done to reconstruction model based on measured mouse data. The origin of error has been gotten, data measuring and processing method which can reduce error have been prompted.
Abstract: In this paper, We proposed a Servlet grouping framework with non-intrusive implementation. Java Servlet is an important means to build web applications with java language. Including Struts and Web Work. Nowadays most of the popular java web frameworks are developed and designed based on Servlet. Servlets provide a component-based, platform-independent method to build Web-based applications. However, the Servlet must be configured in the deployment descriptor, that is, the Web.xml file. With the increasing of the number of Servlets, the Web.xml file will become extremely complex and chaos. So, we need to develop a framework, which can deploy the Servlets independently without the Web.xml file, and manage them by groups.
Abstract: Green building is the only way to change the development mode of China's building materials industry from extensive to the efficient type and it is a necessary requirement to achieve sustainable economic development. This paper points out the direction for development of green building materials by the characteristics and the significance of the green building materials development is explained. The paper makes a comprehensive analysis of the approach to develop green building materials from the design, production, usage, standards, evaluation and many areas in which the development of green building materials is involved.
Abstract: In this paper, a method based on wavelet transform, which is used to analyze near infrared spectra, is discussed with the purpose of prediction of the content of oil, crude protein(CP) and moisture in sunflower seeds. By using different decomposing levels of Daubechies 2 wavelet transform, the near infrared spectra signals obtained from 105 intact sunflower seed samples were de-noised. Calibration equations were developed by partial least square regression (PLS) using the reconstructed spectra data with internal cross validation. It was indicated that the prediction effects varied when different wavelet decomposing level were employed. At the wavelet decomposing level 5, the best prediction effect was obtained, with the coefficient of correlation(R)and root mean square error prediction (RMSEP) being 0.953 and 0.466% for moisture;0.963 and 1.259% for crude protein; 0.801 and 1.874% for oil on a dry weight basis. It was concluded that the near infrared spectral model de-noised by means of wavelet transform can be used for the prediction of chemical composition in sunflower seeds for rapid pre-screening of quality characteristics on breeding programs.
Abstract: his paper reports a practical approach for detecting and diagnose engine faults in real-time based on both the historical and the real-time engine operation data using a specially design neural networks-based fault diagnosis expert system. This system consisted of multiple sensors for real-time monitoring, an engine database for historic data comparison, and a neural network-bases classifier for detecting faults based on both the real-time and the historic data. This neural network-based engine fault diagnosis system was evaluated in a series of validation tests. The results indicated that the system was capable to detect the predefined faults reliably, and the diagnosis error was less than 5%.
Abstract: The research presented here constructed highway landscape quality evaluation indexes and a model based on public satisfaction. The goal was to determine if public satisfaction of highway landscape quality can be statistically measured. Several methods of highway landscape quality evaluation were first reviewed to determine what limitations were existed. From that review, a highway landscape quality evaluation indexes were selected and a model based on the selected indexes were constructed according to theory of public satisfaction. An on-site study was conducted to obtain public satisfaction of a scenic road using the selected indexes and model, statistical methods were employed to test the validity and reliability. Results indicate that the public satisfaction can reflect the quality of highway landscape, and the selected indexes can fully represent highway landscape quality.
Abstract: Aiming at time-consuming and ineffective problem of image window division in fabric defect detection, this paper proposes a new adaptive division method after a large number of experiments. This method can quickly and exactly recognize defect feature. Firstly, a division model on adaptive window is established, secondly, the formula to anticipate generally situation of fabric image is given according to the peaks and valleys change in the model, and methods to calculate the division size and position of adaptive window are given. Finally, we conclude that the algorithm in this paper can quickly and simply select the size and position of window division according to actual situation of different fabric images, and the time of image analysis is shortened and the recognition efficiency is improved.
Abstract: Aiming at lack of effective algorithm for image gray feature wave analysis, this paper proposes a new local extreme extraction for image gray feature, which can establish full information of image feature wave for continue analysis. Firstly, the definition of image gray feature wave is given. Secondly, methods of local extreme extraction of feature wave are detail described, and specific calculation formulas are given. Finally, some examples of local extreme extraction of different fabric images are listed. Results show that this method is fast and easy, can exactly judge local extreme of feature wave, and lay a good foundation of data for continue image analysis and recognition.