Earticle

In this paper, we presented the performance of forecasting model and error correction will affect the accuracy of short-term load forecasting. Least squares support vector machines (LS-SVM) based on improved particle swarm optimization is selected as load forecasting model. Forecasting accuracy and generalization performance of LS-SVM depend on selection of its parameters greatly. Adaptive particle swarm optimization (APSO) based on fitness function was put forward to optimize the kernel parameter σ and regularization parameter γ of LS-SVM. Based on the optimized forecasting model, non-parametric error correction model is also presented by iterative method. The error forecasted by non-parametric model was used to update the forecasted load so as to improve the forecasting accuracy. Load data selected from some area in South China as training and forecasting data is used to analyze. Case study illustrates that the proposed forecasting model (NP-APSO-SVM) has more generalized performance and better forecasting accuracy compared with the method of standard SVM.

As smartphones rapidly improve and as their supply increases, not only high quality images but also creative and diverse functions are expected from the cameras mounted on smartphones. In this paper we propose a method of automatic photography shooting by recognizing common hand gestures used during photography shooting. From the image acquired from a smartphone camera, skin area is extracted based on the skin color data value from YCbCr color space in which characteristics of the color of the skin is well expressed. From the extracted skin area, labeling method is applied to analyze contour data, and then skin object is extracted. By using the location data of the fingers, hand area is extracted from the skin object. Then the hand gesture can be recognized by the camera which takes the photograph automatically. We were able to confirm through experiments that recognition speed was fast even under the low-end environment and that it is more effective than smartphone camera’s timers.

In this paper, an image compression scheme is proposed, based on discrete cosine transform (DCT). This scheme is a hybrid method, which combines vector quantization (VQ) and differential pulse code modulation (DPCM). This scheme begins with transforming image from spatial domain to frequency domain using DCT. Then the block data is transformed into a vector according to zigzag order, and then truncated. After that, the vector is split into DC coefficient and AC coefficients. After scale quantization, DC coefficient is coded using DPCM. AC coefficients are coded using multistage vector quantization (MSVQ). Then, entropy encoding is performed on index-tables and DC part, separately. The experimental results show that, compared to conventional VQ and DCT-VQ schemes, proposed scheme has a better performance.

In this paper, we proposed an algorithm which efficiently detects salient objects. First of all, yellow and intensity images are generated from input image and the feature map is generated using a contrast difference between red-green and blue-yellow channel. Secondly, Lookup-Table(LUT) is obtained by histogram of the feature map. Finally, the saliency map is obtained from LUT. The proposed saliency detector shows that this method is able to efficiently extract saliency maps by improving the AUC 10-40%, comparing to existing color-based method and frequency space transform method.

This paper studies the influence factors and the influence mechanism which effect adoption intention of online customized marketing system, which is based on TRI model and the theory of resistance to marketing persuasion as the main framework of the research model from two aspects of technical and marketing characteristics. According to empirical study based on 303 Chinese users, we found that the user’s optimism, creativity and system inadaptability directly influence on the adoption intention in terms of technology attribution, marketing supply appeal, marketing supply fitness, perceived controlling and perceived pressure influence on the adoption intention in terms of marketing attribute, meanwhile, recommendation fitness are influenced by customized label, customized participation and explanation of recommendation. Marketing supply attractiveness is influenced by product attributes, novelty and form of customized supply. And users’ concern about security of system has no significant influence on users’ adoption of online customized marketing system. The people at different education are different significantly in their adaption attention. Finally management suggestion for operators was given.

R-Learning is en educational system that makes use of robot functions, contents and IT convergence. R-Learning system was used in 1,843 kindergartens(2.147 EA) as of October, 2013. To accelerate the universalization of R-Learning, the related laws and system should be reviewed to seek workable reform measures. The purpose of this study was to examine an act on the development of the e-learning industry and the promotion of e-learning and an intelligent robot act in an effort to offer an overview of the legal system related to R-Learning. Besides, the regulations of the copyright law and the personal information protection law that were associated with R-Learning were reviewed to expedite the vitalization of R-Learning.

Wireless Mesh Network (WMN) presents us a key emerging technology which can construct the next generation wireless multi-hop network. It combines the advantages of both mobile ad-hoc network (MANET) and traditional fixed network. The applications of WMNs also attract significant industrial and academic attentions. As a vital function of network communication, multicast is normally applied to transmit data for high-definition video and gaming in WMNs. Therefore, the multicast routing algorithms are very important to the performance of group communication in WMNs. In this paper, we review a list of existing multicast routing algorithms in WMNs. Based on the findings, we also point out the open issues of multicast routing algorithms.

Modeling method to render cloud on the simulation is divided into two schemes, static and dynamic, depending on the accessibility of the cloud. Two schemes show the complete dissimilar properties in the aspects of realism and real-time processing. Thus, in this paper, we propose a new scheme that merges two modeling methods of the cloud for flight simulation by using the L-system. Since the proposed scheme considers both realism and rendering speed, it is possible to be implemented the formation and growth of the cloud in real-time manner. Finally, the proposed method is evaluated by the experimental results of real implementation in the flight simulation software based on OpenSceneGraph(OSG).

A nonlinear mathematical model of the flow-coupled secondary regulation system was established. Then, the exact feedback linearization was applied to transform the system into a linear one by coordinates transformation and state-space feedback based on its nonlinear model. Furthermore, the zero dynamics was analyzed to prove the stability of the system so as to verify the feasibility of the exact linearization control scheme. And the LQR controller was design on the basis of the exact linearization control scheme. Finally, the experimental results show that the Flow-coupled secondary regulation system using the LQR controller based on the exact linearization control scheme has good performance and does better than PID controller when it works far from zero point.