Deep reinforcement learning (DRL) is one promising approach to teaching robots perform complex tasks. Because methods that directly reuse the stored experience data cannot follow change of environment in robotic problems with a time-varying environment, online DRL required. The eligibility traces method well known as an technique for improving sample efficiency traditional linear regressors rat...

abstract objectives: this study aimed to determine the effectiveness of schema therapy in the treatment of social anxiety disorder.method: the research method was a single-case experimental design with multiple baselines. five patients were selected by purposive sampling method. they were treated in 20 individual sessions according to young's schema therapy model. the data were collected by tes...

In this paper, we propose a multi-scale deep feature learning method for high-resolution satellite image classification. Specifically, we firstly warp the original satellite image into multiple different scales. The images in each scale are employed to train a deep convolutional neural network (DCNN). However, simultaneously training multiple DCNNs is time-consuming. To address this issue, we e...

In the framework of mapped pseudospectral methods, we introduce a new polynomialtype mapping function in order to describe accurately the dynamics of systems developing almost singular structures. Using error criteria related to the spectral interpolation error, the new polynomialtype mapping is compared against previously proposed mappings for the study of collapse and shock wave phenomena. As...