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Table of Contents
Papers
By Ken Cai, Fenglian Tie, Haoran Huang, Hanhui Lin and Huazhou Chen
Abstract
By analyzing the current situation of experimental platforms which is based on the Internet of Things (IOT) and the cultivation of talents, we established the talents' cultivating orientation and experiment platform for innovation. In accordance with the requirements of a students' practical and creative ability curriculum, the method of modularization was adopted to design this platform. With this, the platform can basically satisfy the needs of the varying teaching experiments, which can increase opportunities for the students on their comprehensive application. The platform was widely used in experimental and practice teaching in the past three years, such as synthetic experiment, graduate programs, and practice project in Zhongkai University of Agriculture and Engineering, Guilin University of Technology etc. Result shows that the innovation experimental platform has broad application prospects, and effectiveness to meet the requirements of students' in-depth learning and research of IOT technologies. Meanwhile, the platform expanded the students' basic understanding of IOT and improved their innovation.
By Jozsef Katona and A. Kovari
Abstract
Recently more and more research methods are available to observe brain activity; for instance, Functional Magnetic Resonance Imaging (fMRI), Positron Emission Tomography (PET), Transcranial Magnetic Stimulation (TMS), Near Infrared Spectroscopy (NIRS), Electroencephalograph (EEG) or Magnetoencephalography (MEG), which provide new research opportunities for several applications. For example, control methods based on the evaluation of measurable signals of human brain activity. In the past few years, more mobile EEG (electroencephalogram) based brain activity biosensor and signal processing devices have become available not only for medical examinations, but also to be used in different scopes; for instance, in control applications. These methods provide completely new possibilities in human-machine interactions by digital signal processing of brain signals. In this study, the program model, the establishment, the implementation and the test results of the quantitative EEG-based computer control interface, protocol and digital signal processing application are demonstrated. The user-friendly visualization of the evaluated brain wave signals is implemented in visual C# object-oriented language. This EEG-based control unit and interface provides an adequate basis for further research in different fields of brain-machine control methods regarding the examination of possible machine control applications.
Abstract
Online STEM (Science, Technology, Engineering and Mathematics) education needs online labs - the same way as classical education at schools need access to real laboratories, because various technical skills and prowesses can be effectively achieved only by putting theory into practice. There are series of open online labs available today, especially thanks to fast ICT (Information and Communications Technology) growth and innovations provided by many universities. Nevertheless integration of online labs into education systems occurs sporadically. Article aims to map the current integration options, give some existing examples and analyze how it would be possible to start the integration of online labs on a global scale.
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Souce: International Journal of Online Engineering (iJOE)
