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Kirjailija

Qianlong Lan

Kirjat ja teokset yhdessä paikassa: 2 kirjaa, julkaisuja vuosilta 2020–2021, suosituimpiin kuuluu Development of a Remote Laboratory for Engineering Education. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.

2 kirjaa

Kirjojen julkaisuvuodet: 2020–2021.

Development of a Remote Laboratory for Engineering Education

Development of a Remote Laboratory for Engineering Education

Ning Wang; Qianlong Lan; Xuemin Chen; Gangbing Song; Hamid Parsaei

TAYLOR FRANCIS LTD
2021
nidottu
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

Development of a Remote Laboratory for Engineering Education

Ning Wang; Qianlong Lan; Xuemin Chen; Gangbing Song; Hamid Parsaei

CRC Press
2020
sidottu
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.