A federation of VISIR remote laboratories through the PILAR Project
This paper describes how a new Erasmus Plus project, PILAR, (Platform Integration of Laboratories based on the Architecture of visiR), is being developed and how the startup of the partnership and the project is reinforcing the VISIR (Virtual Instrument Systems in Reality) network and the Special Interest Group of VISIR under the Global Online Laboratory Consortium (GOLC) of the International Association of Online Engineering (IAOE). The Spanish University for Distance Education (UNED) coordinates the project that aims to federate the existing (or new) VISIR systems in order to use the resources more effectively and in a more efficient way, making transparent to the final user the election of the shared resources.
Gender comparative research on learning strategies applying the cognitive‐motor model methodology and VISIR remote lab
The research work hereby presented shows some findings about the different ways used by girls and boys, at secondary school, to assimilate the electricity concepts and electric magnitudes to be able to design and assemble electric circuits. The methodology applied to learning, the cognitive‐motor model (CMM), is also presented, and it is based on the mutual interaction of cognitive skills and motor capabilities. Students have followed a specific course designed under CMM specifications. The course contains a combination of theoretical activities and practical tasks by means of which cognitive and motor skills have been measured. To carry out the practical tasks, the Virtual Instrument Systems in a reality remote lab have been used by students as the technical resource. In the study, different learning strategies between male and female students, what affects each gender effectiveness, and learning performance have been found.
ANALYSIS OF BOLT′S ANCHORING QUALITY BASED ON WAVELET NEURAL NETWORK
The dynamic response of bolt achieved by impact-echo method can be effected easily by some factors.It′s difficult to classify bolt′s anchoring quality according to the dynamic response of bolt.In this paper,a new analytical method of bolt′s dynamic response is put forward.The new analytical method combing with advantages of wavelet analysis and artificial neural network is presented.Firstly,the dynamic response of bolt by numerical simulation software FLAC3D is obtained.Secondlyt,he features are extracted from the dynamic response of bolt by wavelet analysis.Thirdlyt,hese features are fed into the artificial neural network for training.Finallyt,his artificial neural network to classify the bolt′s anchoring quality intelligent according to the dynamic response of bolt is employed.In order to validate this new analytical method,some practical signals of bolt′s dynamic response are used for the test.The results indicate that the new analytical method is practicable.