• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1002-1011
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• 2000

In this paper, we propose a multiresolution progressive image transmission with spatial and bit-rate scalabilities using a $2{\times}2$ DCT. The multiresolition image represented by a $2{\times}2$ DCT is used for the progressive image transmission with spatial and bit-rate scalabilities. Because the proposed progressive image transmission method supports both spatial and bit-rate scalabilities, it can be adaptively applied to the receiver's scalability requests. We compare the proposed progressive transmission with that of the higher-order convolution-based Wavelet method. Comparisons show that the proposed method needs much less computations, but insignificant loss of image quality.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.259-272
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• 2022

The branch of electronics that uses an organic solar cell or conductive organic polymers in order to yield electricity from sunlight is called photovoltaic. Regarding this crucial issue, an artificial intelligence-based predictor is presented to investigate the vibrational behavior of the organic solar cell. In addition, the generalized differential quadrature method (GDQM) is utilized to extract the results. The validation examination is done to confirm the credibility of the results. Then, the deep neural network with fully connected layers (DNN-FCL) is trained by means of Adam optimization on the dataset whose members are the vibration response of the design-points. By determining the optimum values for the biases along with weights of DNN-FCL, one can predict the vibrational characteristics of any organic solar cell by knowing the properties defined as the inputs of the mentioned DNN. To assess the ability of the proposed artificial intelligence-based model in prediction of the vibrational response of the organic solar cell, the authors monitored the mean squared error in different steps of the training the DNN-FCL and they observed that the convergency of the results is excellent.