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Development of a Remote Laboratory for Engineering Education (Paperback): Ning Wang, Qianlong Lan, Xuemin Chen, Gangbing Song,... Development of a Remote Laboratory for Engineering Education (Paperback)
Ning Wang, Qianlong Lan, Xuemin Chen, Gangbing Song, Hamid Parsaei
R758 Discovery Miles 7 580 Ships in 12 - 19 working days

The field of information technology continues to advance at a brisk pace, including the use of Remote Laboratory (RL) systems in education and research. To address the needs of remote laboratory development for such purposes, the authors present a new state-of-the-art unified framework for RL system development. Included are solutions to commonly encountered RL implementation issues such as third-party plugin, traversing firewalls, cross platform running, and scalability, etc. Additionally, the book introduces a new application architecture of remote lab for mobile-optimized RL application development for Mobile Learning (M-Learning). It also shows how to design and organize the remote experiments at different universities and make available a framework source code. The book is intended to serve as a complete guide for remote lab system design and implementation for an audience comprised of researchers, practitioners and students to enable them to rapidly and flexibly implement RL systems for a range of fields.

Development of a Remote Laboratory for Engineering Education (Hardcover): Ning Wang, Qianlong Lan, Xuemin Chen, Gangbing Song,... Development of a Remote Laboratory for Engineering Education (Hardcover)
Ning Wang, Qianlong Lan, Xuemin Chen, Gangbing Song, Hamid Parsaei
R1,821 Discovery Miles 18 210 Ships in 12 - 19 working days

The field of information technology continues to advance at a brisk pace, including the use of Remote Laboratory (RL) systems in education and research. To address the needs of remote laboratory development for such purposes, the authors present a new state-of-the-art unified framework for RL system development. Included are solutions to commonly encountered RL implementation issues such as third-party plugin, traversing firewalls, cross platform running, and scalability, etc. Additionally, the book introduces a new application architecture of remote lab for mobile-optimized RL application development for Mobile Learning (M-Learning). It also shows how to design and organize the remote experiments at different universities and make available a framework source code. The book is intended to serve as a complete guide for remote lab system design and implementation for an audience comprised of researchers, practitioners and students to enable them to rapidly and flexibly implement RL systems for a range of fields.

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