Advanced Materials Research Vols. 108-111

Abstract: A GSP integrated learning and assessment system (LAS-GSP) is developed to provide students an interactive exploration environment and on-line feedbacks on geometric problem solving. Three tasks of maximal segmentation are developed to investigate the applicability and intervention effect of the system. There are four scoring elements for students’ on line assignments: (1) systematic approaches, (2) correct solutions, (3) originality of representation, and (4) function derived. The characteristics of students’ learning progress are discussed by the scoring rubrics applied. The results suggest abstract geometric concepts can be visualized, internalized, and enhanced at an earlier age, if mind-tool can be effectively implemented.

Abstract: In the present day, many universities have put their efforts on teaching reform. As for linguistic teaching reform, many teachers have probed into reform measures concerning character-oriented education to success and information technology. Therefore, the author has put her focus on linguistic teaching reform of independent college . Thus, zero-approach teaching mode and self-study center become her study focuses in the paper. The author tries her best to study relationships among them and tries to improve linguistic teaching reform in independent college.

Abstract: To achieve success in the marketplace, human factors play an important role in product development. In this paper a design strategy considering anthropometric variability for different demographic data was put forward. With the aid of parametric technology of Computed Aided Design (CAD), concept model of products was initialized. Detailed parameters of products were configured according to the anthropometric information based on measurement of customers’. Multiple linear regression were used to model the relation between the product comfort and design variables, thus the sizes of products could adapt to specific customers of certain age, height and gender. A children’s scooter was demonstrated as a case to validate this strategy. A three dimension parametric model of a scooter was built first, the parameters concerned with human factors were determined according to the knowledge of anthropometry.

Abstract: Autonomous learning abilities plays an important roles in linguistic learning course. Nowadays, with development of modern information technology and teaching reform in universities, improvement of autonomous learning abilities becomes more and more important for linguistic learners. It is teachers' responsibilities to improve autonomous learning abilities of students with a large variety of measures and strategies. Therefore, the author puts her efforts on studying teaching measures and strategies for improving teaching efficiencies. How do teachers make his or her measures be scientific and effective How do teaching measures stimulate students and promote students How do students turn their learning into autonomous learning All of those questions should be probed by researchers and teachers. In the paper, the author tries her best to solve those problems and tries to find out effective teaching strategies for improvement teaching efficiencies.

Abstract: Accurate forecasting of building cooling load has been one of the most important issues in the electricity industry. Recently, along with energy-saving optimal control, accurate forecast of electricity load has received increasing attention. Because of the general nonlinear mapping capabilities of forecasting, artificial neural networks have played a crucial role in forecasting electricity load. Support vector machines (SVMs) have been successfully employed to solve nonlinear regression and time series problems. In order to improve time efficiency of prediction, a new hourly cooling load prediction model and method based on Support Vector Machine in this paper. Moreover, simulated annealing (SA) algorithms were employed to choose the parameters of a SVM model. Subsequently, examples of cooling load data from Guangzhou were used to illustrate the proposed SVM-SA model. A comparison of the performance between SVM optimized by Particle Swarm Optimization (SVM-PSO) and SVM-SA is carried out. Experiments results demonstrate that SVM-SA can achieve better accuracy and generalization than the SVM-PSO. Consequently, the SVM-SA model provides a promising alternative for forecasting building load.

Abstract: Manifold structure shows important effects on the velocity distribution among parallel microchannels. The bifurcation structure was adopted as the manifolds of microchannel array in a plane and a specific case was illustrated to estimate the effects of structural parameters on the velocity distribution using numerical simulation. Simulation result indicated that the velocity distribution appeared to be double W-shape, and somewhat symmetrical. In addition, the velocity values in each W-shape distribution also appeared symmetrical. It also indicated that two bifurcation channels from the same low-level bifurcation channel had different velocity values due to different singular losses. Larger microchannel length, smaller microchannel width or depth, larger RW or RL, suitable RZ were favor in obtaining relatively uniform velocity distribution among microchannels.

Abstract: This article is in use of the method of AHP and VIKOR, with which to introduce the present situation and evaluate the competitive ability, and then draw a conclusion that it is vary strong in Baoding. The conclusion of this paper is useful for Baoding based on analyzing the advantage of it, which point out that make full use of it and then realize and enhance the power.

Abstract: Wavelet analysis has become a popular subject in scientific research in the past twenty years. In this work, we develop the concept of a class of vector-valued multivarition matrix. A new method for constructing multidimensional vector-valued wavelet packets is formulated. Their characteristics are researched by means of operator theory, time-frequency analysis method and matrix theory. There orthogonality formulas regarding the wavelet packets are provided. Orthogonality decomposition relation formulas of the space L2(Rs)r are obtained by constructing a series of subspaces of the vector-valued wavelet packet. Furthermore, several orthonormal wavelet packet bases of space L2(Rs)r are constructed from the wavelet packets.

Abstract: Based on the investigation on vibration characteristics of certain off-road vehicle, a new type of damping-adjustable hydro-pneumatic suspension was put forward. After the analysis of its working principle, the nonlinear dynamic mathematical models of this suspension were set up. Using the method of theoretical calculation and simulation by MATLAB/Simulink, the nonlinear vibration characteristics of this damping- adjustable hydro-pneumatic suspension were studied, including static and dynamic stiffness, dynamic output force and damping force.

Abstract: Gearboxes are extensively used in various areas including aircraft, mining, manufacturing, and agriculture, etc. The breakdowns of the gearbox are mostly caused by the gear failures. It is therefore crucial for engineers and researchers to monitor the gear conditions in time in order to prevent the malfunctions of the plants. In this paper, a condition monitoring and faults identification technique for rotating machineries based on independent component analysis (ICA) and fuzzy k-nearest neighbor (FKNN) is described. In the diagnosis process, the ICA was initially employed to separate characteristic vibration signal and interference vibration signal from the parallel time series obtained from multi-channel accelerometers mounted on different positions of the gearbox. The wavelet transform (WT) and autoregressive (AR) model method then were performed as the feature extraction technique to attain the original feature vector of the characteristic signal. Meanwhile, the ICA was used again to reduce the dimensionality of the original feature vector. Hence, the useless information in the feature vector could be removed. Finally, the FKNN algorithm was implemented in the pattern recognition process to identify the conditions of the gears of interest. The experimental results suggest that the sensitive fault features can be extracted efficiently after the ICA processing, and the proposed diagnostic system is effective for the gear multi-faults diagnosis, including the gear crack failure, pitting failure, gear tooth broken, compound fault of wear and spalling, etc. In addition, the proposed method can achieve higher performance than that without ICA processing with respect to the classification rate.