Cai X.,Shaoxing Vocational and Technical College
2011 International Conference on Electrical and Control Engineering, ICECE 2011 - Proceedings | Year: 2011
Industrial wastewater of a chemical plant is tannery wastewater. Its main components are polymer complex, benzene derivatives and hexavalent chromium. It is organic wastewater which is hard to be degraded and has poor biodegradability. Here we describe a complete technology of wastewater treatment system, automatic control system base on PLC and their commissioning and operation. Practice has proved that the system is stable and reliable and the outlet water quality is also good. © 2011 IEEE.
Jiang B.,Shaoxing Vocational and Technical College
Advanced Materials Research | Year: 2012
In this paper, aerosol samples were collected with Andersen cascade sampler on typical polluted days at residential area in Hangzhou, China. The concentrations of sulfate, nitrate and ammonium in aerosol were analyzed by the ion chromatography. Results showed the concentrations of SO 4 2-, NO 3 - and NH 4 + on polluted days were 21.4, 31.2 and 10.8μg m -3 in fine particles, respectively, and were 1.3-1.7 times higher than on unpolluted days. SO 4 2-, NO 3 - and NH 4 + in fine particles were the main threat of athlete health in the urban area of Yangtze River delta.
Wei W.,Shaoxing Vocational and Technical College
Applied Mechanics and Materials | Year: 2010
The home monitoring system designed in this paper used the combination of a home gateway controller and the ZigBee coordinator, the connection of the ZigBee coordinator and the terminal nodes through wireless mode, to issue the collected real-time data to the Intemet with a web page form, and the dynamic real-time update, so that the intelligent monitoring of the home-based internal environment is achieved. This system overcomes the shortcomings of traditional wired control system, has good currency, high expansibility, and can shorten the intelligent home product development cycle, help to design and develop powerful, cost-effective powerful, cost-effective home products. © (2010) Trans Tech Publications.
Zheng Y.,Shaoxing Vocational and Technical College
Advanced Materials Research | Year: 2012
With the popularization of multi-media and network technology, some Chinese schools are applying the high technology to the class. The author believes that the model of teaching and learning focus on the establishment of multi-media class environment and the after-school autonomous learning system. The utilization reflects the development process of the combination of modern information technology and English teaching. The modern teaching technology, which includes multi-media, network system and various teaching aids, enriched the choice of teaching resources and provided plenty of materials for teaching so as to supply more opportunities for students. The applications of information transition to class, such as multi-media and network technology are increasingly concerned and favored by teachers and students and have becoming one of the best devices for modern education. The author of this paper divide the application of multi-media and network technology to English teaching into two parts according to the experience of teaching practice and the utilization of language lab: the language class environment based on the use of multi-media and the after-school autonomous learning system based on network technology. © (2012) Trans Tech Publications, Switzerland.
Wang T.,Shaoxing University |
Chen W.,Shaoxing Vocational and Technical College |
Wang B.,Harbin Institute of Technology
International Journal on Smart Sensing and Intelligent Systems | Year: 2014
In Bag of Words image presentation model, visual words are generated by unsupervised clustering, which leaves out the spatial relations between words and results in such shorting comings as limited semantic description and weak discrimination. To solve this problem, we propose to substitute visual words by visual phrases in this article. Visual phrases built according to spatial relations between words are semantic distrainable, and they can improve the accuracy of Bag of Words model. Considering the traditional classification method based on Bag of Words model is vulnerable to the background, block and scalar variance of an image, we propose in this article a multiple visual words learning method for image classification, which is based on the concept of visual phrases combined with Multiple Instance Learning. The final classification model is able to show the spatial features of image classes. Experiments performed on standard image testing sets, Caltech 101 and Scene 15, show the satisfying performance of this algorithm.