• Advances in Computational Design
• /
• v.9 no.3
• /
• pp.213-227
• /
• 2024

In this study, a framework for coupling of the convolution quadrature time-domain boundary element method (CQBEM) and image-based finite element method (IMFEM) is presented for 2-D elastic wave propagation. This coupling method has three advantages: 1) the finite element modeling for heterogeneous areas can be performed without difficulties by using digital data for the analysis model, 2) wave propagation in an infinite domain can be calculated with high accuracy by using the CQBEM, and 3) a small time-step size can be used. In general, a small time-step size cannot be used in the classical time-domain boundary element method. However, the CQBEM used in this analysis can address a small time-step size. This makes it possible to couple the CQBEM and image-based FEM which require a small-time step size. In this study, the formulation and validation of the pro-posed method are described and confirmed by solving fundamental elastic wave scattering problems. As a numerical example, elastic wave scattering in inhomogeneous media is demonstrated using the proposed coupling method.

• Journal of information and communication convergence engineering
• /
• v.2 no.1
• /
• pp.1-4
• /
• 2004

In this paper, We analyzes how a synchronization error affects receiving system when using OFDM(Orthogonal Frequency Division Multiplexing) transmission method in wireless LAN channel environment in which we can efficiently transmit wide-band information data. As a performance improvement method, performance distortion can be improved by applying convolution coding. As a result, in OFDM system, we could see that the higher a frequency offset is, the worse performance will be, and we could see that there was performance improvement by applying convolution coding in OFDM system in order to reach (BER=$10^{-3}$). However, when we use 64QAM (64Quadrature Amplitude Modulation), there was a huge influence between carriers by frequency offset at 0.05, 0.1.

• Journal of Broadcast Engineering
• /
• v.8 no.2
• /
• pp.163-171
• /
• 2003

In this paper, we develop an approach toward Joint Source-Channel Coding for MPEG-4(Moving picture Experts Group) based video coding In fixed and mobile reception environment. We have considered channel environment of AWGN and mobile reception. The source coder used MPEG-4 video. the channel coder used RCPC(Rate Compatible Punctured Convolution) and the modulation method used QPSK(Quadrature Phase Shift Keying) modulation. This study determined optimum Trade-off point between source bit rate and channel coding rate In variable channel states. We compared Joint Source/channel Coding method and general constant bit rate transmission. In this results, Joint Source/channel Coding was appeared better performance than constant bit rate transmission.

• Proceedings of the Korea Contents Association Conference
• /
• 2003.11a
• /
• pp.303-307
• /
• 2003

In this paper, the W(ultra widebend) system is used for high speed transmission applying BPSK(Binary Phase Shift Keying) and QPSK (Quadrature Phase Shift Keying), and utilizing the convolution coding with code rate, 1/2 and constraint length, K=7 in order to reduce the bit error rate. And the performance of system is analyzed in the AWGN(Additive White Gaussian Noise) channel environment by using the Viterbi decoding algorithm and adopting the time-hopping sequence as a multiple access method in order to avoid the multiuser interference.

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