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Magnetic shape memory alloy (MSMA) has recently emerged as a new type of multifunctional material exhibiting excellent performance as fast response and large strain. Constitution equations are derived based on the magnet-strain effect of MSMA. Experiments are conducted to explore the magnetic field induced strain, and data are applied to establish neural network based models to build the nonlinear...
SARSA, as one kind of on-policy reinforcement learning methods, is integrated with deep learning to solve the video games control problems in this paper. We use deep convolutional neural network to estimate the state-action value, and SARSA learning to update it. Besides, experience replay is introduced to make the training process suitable to scalable machine learning problems. In this way, a new...
Testing is one of the most labor-intensive activities in software development life cycle and consumes between 30% and 50% of total development costs according to many studies. The communication gap between testers and developers that is caused by unclear or even invalid defect reporting usually makes the testing schedule delay, and contributes large amount of testing effort to rework and re-communication...
Traditional dimension reduction approaches always consider the samples in a class are uni-modal. In real world, samples in a class are usually multi-modal, for instance, the manifold of the facial appearance of a person under different illumination, expression, and poses is multi-modal. Recently, dimension reduction approaches based on manifold learning are presented, the main purpose is to preserve...
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