Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.
The purpose of this study was to investigate the relationship between parent involvement and preschool disabled children’s development. Parents of 3 year old disabled children (N=440) and 5 year old disabled children (N=937) participating in the Special Needs Education Longitudinal Study were interviewed or answered the web design questionnaire about their actions in parenting their disabled children. These children’s developments were also evaluated by their teachers. Data were analyzed using Structural Equation Modeling. Results were showed by tables and figures. Based on the results, the researcher made some suggestions for future studies.
A two-dimensional linear wave-body interaction problem can be solved using a desingularized integral method by placing free surface Rankine sources over calm water surface and satisfying boundary conditions at prescribed collocation points on the calm water surface. A new free-surface Rankine source distribution scheme, determined by the intersection points of free surface and body surface, is developed to reduce numerical computation cost. Associated with this, a new treatment is given to the intersection point. The present scheme results are in good agreement with traditional numerical results and measurements.
In this work, the effect of the magnetron sputtering system parameters on the optical properties of the Mn doped GeTe were investigated. The optical properties of the Ge1-xMnxTe thin films with different thicknesses are determined by analyzing the transmittance and reflectance data. The energy band gaps of the amorphous Mn-doped GeTe thin films with different thicknesses were calculated. The obtained results demonstrated that the energy band gap values of the amorphous films are quite different and they are dependent on the films thicknesses. The extinction coefficients of amorphous Mn-doped GeTe thin films as function of wavelength for different thicknesses were measured. The results showed that the extinction coefficients of all films are varying inversely with their optical transmission. Moreover, the results emphasis that, not only the microstructure, electrical and magnetic properties of Mn doped GeTe thin films vary with the films thicknesses but also the optical properties differ with the film thickness.