Design of a New Mobile-Optimized Remote Laboratory Application Architecture for M-Learning

发布时间:2017-06-24发布部门:信息科学与技术学院

主题:   Design of a New Mobile-Optimized Remote Laboratory Application Architecture for M-Learning主讲人:   陈学敏地点:   松江校区二号学院楼226室时间:   2017-07-11 10:30:00组织单位:   信息科学与技术学院 数字化纺织服装技术教育部工程研究中心

主讲人简介: Dr.Xuemin Chen is the founding Director of Virtual and Remote Laboratory (VR-Lab)and an Associate Professor of Electricaland Computer Engineering at the Texas Southern University (TSU). He receivedhis BS, MS and Ph.D. degrees in Electrical Engineering from the Nanjing University of Science and Technology (NJUST), China, in 1985, 1988 and 1991 respectively. He joined the faculty of TSU in the Department of EngineeringTechnology in September 2006. Prior to that, he had fifteen years workingexperience in academia with six years at NJUST and another nine years atUniversity of Houston. He was the recipient of the Top Research Innovations andFindings Award from Texas Department of Transportation (TxDOT) for hiscontribution in the “Thickness Measurement of Reinforced Concrete Pavement byUsing Ground Penetrating Radar” in 2004. Upon joining the TSU, he activelyengaged in the conception and implementation of next-generation remotelaboratory. He initiated the Virtual and Remote Laboratory at TSU in 2008. Withthe support of NSF HBCU-UP, CCLI and IEECI programs, and Qatar NPRP award, hehas established a state of the art VR-Lab at TSU. His other interests includewireless sensor networks. He is an investigator of NSF Center for Research onComplex Networks at TSU.

内容摘要:As mobile learning (M-Learning) has demonstrated increasing impacts on onlineeducation, more and more mobile applications are designed and developed for theM-Learning. In this presentation, a new mobile-optimized application architectureusing Ionic framework is proposed to integrate the remote laboratory intomobile environment for the M-Learning. With this mobile-optimized applicationarchitecture, remote experiment applications can use a common codebase todeploy native-like applications on many different mobile platforms such as iOS,Android, Windows Mobile, and Blackberry. To demonstrate the effectiveness ofthe proposed new architecture for M-Learning, an innovative remote networkedproportional–integral–derivative control experiment has been successfullyimplemented based on this new application architecture. The performance isvalidated by the Baidu mobile cloud testing bed.

 


视频:   摄影: 撰写:马骏  信息员:马骏  编辑:陈前

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