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Vol. 15, Special Issue, November 2012, pp.I-II

 

Bullet

Handbook of Laboratory Measurements

Intelligent Data Acquisition and Information Process Technologies and Their Applications

 

1 Gongfa Li, 2 Tinggui Chen, 1 Hegen Xiong

1 Wuhan University of Science and Technology, China

2 Zhejiang Gongshang University, China

 

 

Received: 11 September 2012   /Accepted: 11 October 2012   /Published: 20 November 2012

Digital Sensors and Sensor Sysstems

 

 

Foreword

 

Nowadays, intelligent data acquisition and information process technologies are playing a more and more important role in applied sciences and engineering. This field is experiencing rapid development, and in the last decade has resulted in more intelligent, sensitive, and accurate methods of data acquisition and information process in manufacturing, environmental monitoring, medical monitoring systems and laboratory measurement equipment. Advanced methods have been developed to enhance the measurement of information for automation, in-process inspection, quality control, diagnostics, and other processes.

 

By realizing the challenges and opportunities in this domain, we planned to bring the special issue on the Intelligent Data Acquisition and Information Process Technologies and Their Applications. The purpose of this current issue is to present a collection of high-quality academic papers that cover recent advances in measurement, automation, architecture, algorithms, modeling and other core issues as well as peripheral applications in the field. This issue comprises 34 papers carefully selected from the reviewed papers which were presented in 2012 International Conference on Mechanical Engineering, Automation and Material Science (MEAMS' 2012), December 22 to 23, 2012, held at Wuhan University of Science and Technology, Wuhan, China and published in the conference proceedings. This special issue presents the extended version of the conference papers.

 

Papers in this special issue address many up-to-date efforts for information sciences and technologies such as measurement, network protocols and modeling, web ontology, evolutionary algorithms and data mining algorithms, information processing technologies, production information systems, etc. We believe that the issues addressed in the papers have large impact on applied sciences and engineering. We are thankful to all the contributors for their high quality submissions and timely revision. We are also thankful to the editors and the publishers of the Sensors & Transducers Journal.

 

 

Dr., Prof. Gongfa Li,

Dr., Associate Prof. Tinggui Chen,

Dr., Prof. Hegen Xiong

 

 

Guest Editors:

 

Dr. Gongfa Li received the Ph.D. degree in mechanical design and theory from Wuhan University of Science and Technology in China. Currently, he is a professor at Wuhan University of Science and Technology, China. His major research interests include modeling and optimal control of complex industrial process, mechanical engineering. He is invited as a reviewer by the editors of some international journals, such as Environmental Engineering and Management Journal, International Journal of Engineering and Technology, International Journal of Physical Sciences, International Journal of Water Resources and Environmental Engineering, etc. He has published nearly thirty papers in related journals.

 

Dr. Tinggui Chen is an assistant professor of the school of computer and information engineering, Zhejiang Gongshang University, P. R. China. He graduated from the Jianghan University and earned his B.S. degree in Mechanical design. Then, he received the M.S. degree in industrial engineering from the Wuhan University of Science and Technology and his Ph. D degree in engineering management from Huazhong University of Science and Technology.

 

Hegen Xiong received the Ph.D. degree in materials processing engineering from Huazhong University of Science and Technology, China, in 2005.He is a Professor of College of Machinery and Automation, Wuhan University of Science and Technology. Currently, his research interests are manufacturing information, job shop scheduling, flow shop scheduling and computer aided engineering.

 

 

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