• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1325-1334
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• 2014

Recently game addiction of young people has become a social issue. Therefore, many studies, mostly surveys, have been conducted to diagnose game addiction. In this paper, we suggest how to distinguish levels of addiction based on EEG. To this end, we first classify four groups by the degrees of addiction to internet games (High-risk group, Vigilance group, Normal group, Good-user group) using CSG (Comprehensive Scale for Assessing Game Behavior) and then measure their Event Related Potential(ERP) in the Go/NoGo Task. Specifically, we measure the signals of P300, N400 and N200 from the channels of the NoGo stimulus and Go stimulus. In addition, we extract distinct features from the discrete wavelet transform of the EEG signal and use these features to distinguish the degrees of addiction to internet games. The experiments in this study show that High-risk and Vigilance group exhibit lower Go-N200 amplitude of Fz channel than Normal and Good-user groups. In Go-P300 and NoGo-P300 of Fz channel, High-risk and Vigilance groups exhibit higher amplitude than Normal and Good-user group. In Go-N400 and NoGo-N400 of Pz channel, High-risk and Vigilance group exhibit lower amplitude than Normal and Good-user group. The test after the learning study of the extracted characteristics of each frequency band from the EEG signal showed 85% classification accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.155-160
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• 2010

In this paper, we proposed a forensic mark algorithm which can embed the distributor's information at each distribution step to trace the illegal distribution path. For this purpose, the algorithm has to have the high capacity payload for embedding the copyright and user information at each step, and the embedded information at a step should not interfere with the information at other step. The proposed algorithm can trace the multilevel distribution because the forensic mark is generated by digital hologram and embedded in the DWT-SVD domain. For the high capacity embedding, the off-axis hologram is generated from the forensic mark and the hologram is embedded in the HL, LH, HH bands of the DWT to reduce the signal interference. The SVD which is applied the holographic signal enhanced the detection performance and the safety of the forensic mark algorithm. As the test results, this algorithm was able to embed 128bits information for the copyright and user information at each step. In this paper, we can embed total 384bits information for 3 steps and the algorithm is also robust to the JPEG compression.

• Land and Housing Review
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• v.2 no.4
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• pp.407-413
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• 2011

This paper reports a novel structural health monitoring (SHM) technique for detecting de-bonding between a concrete beam and CFRP (Carbon Fiber Reinforced Polymer) sheet that is attached to the concrete surface. To achieve this, a multi-scale actuated sensing system with a self-sensing circuit using piezoelectric active sensors is applied to the CFRP laminated concrete beam structure. In this self-sensing based multi-scale actuated sensing, one scale provides a wide frequency-band structural response from the self-sensed impedance measurements and the other scale provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. To quantify the de-bonding levels, the supervised learning-based statistical pattern recognition was implemented by composing a two-dimensional (2D) plane using the damage indices extracted from the impedance and guided wave features.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.2
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• pp.89-105
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• 2008

Sea level and atmospheric pressure data of 1999-2005 from four stations along the Korean east coast were analyzed to understand the sea level variability and its causal mechanism. The results of the wavelet and the auto-spectrum analyses indicate that the sea level fluctuations of 3-17 day period are statistically significant at the 95% confidence level, especially in spring to early summer. In this period, the coherency between the sea levels and the atmospheric pressures in a cross-spectrum is high, implying the importance of an inverted barometric effect in generation of the sea level fluctuations. To learn about the sea level variability, the cross-spectrum analyses were applied between the sea levels of the adjacent stations. The results show a case of southward phase propagations along the coast, as in 1999, 2003 and 2005, and an another case of no progressive phase lags between the stations, as in 2000-2002, and 2004. The phase speed in the former case is 12-15 m/s, which is a commonly observed phase speed of coastal Kelvin waves. Generation of such fluctuations seems to be related to low pressure cells developed in the Asian continent in spring and summer and moving eastward over the coastal region north of the stations. The latter case of no progressive phase lag, however, occurs when the low pressure cells developed in the continent move along the region south of the stations. In this case, the northeastward phase propagation with a speed of 5-8 m/s is observed along the southwestern coast of Japan.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.4
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• pp.351-359
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• 2011

In a structure, damage can occur at several scales from micro-cracking to corrosion or loose bolts. This makes the identification of damage difficult with one mode of sensing. Hence, a multi-mode actuated sensing system is proposed based on a self-sensing circuit using a piezoelectric sensor. In the self sensing-based multi-mode actuated sensing, one mode provides a wide frequency-band structural response from the self-sensed impedance measurement and the other mode provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. In this study, an experimental study on the pipeline system is carried out to verify the effectiveness and the robustness of the proposed structural health monitoring approach. Different types of structural damage are artificially inflicted on the pipeline system. To classify the multiple types of structural damage, a supervised learning-based statistical pattern recognition is implemented by composing a two-dimensional space using the damage indices extracted from the impedance and guided wave features. For more systematic damage classification, several control parameters to determine an optimal decision boundary for the supervised learning-based pattern recognition are optimized. Finally, further research issues will be discussed for real-world implementation of the proposed approach.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.277-284
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• 2013

The analysis of phase synchronization characteristics from EEG signals is important for the understanding of information processing functionality in the brain network. In this paper, wavelet transformation(WT), Hilbert tansformation (HT), complex demodulation (CD) methods having time localization characteristics were applied to real evoked potential data and noise added simulation data with center frequencies corresponding to EEG bands for the estimation performance analysis of phase offset, phase changing point, and interband crosstalk. The WT is the best both in ${\delta}$, ${\theta}$, and ${\alpha}$ band signal decomposition, and in analyzing phase synchronization performance. The CD can be efficiently used in changing point detection under tolerant noise condition because of its abrupt performance degradation over noise endurance level. From experimental observations, the WT is the most suitable in phase synchronization application of EEG signal, and the CD can be affordable in restricted application such as changing point detection for higher bands than ${\delta}$. Particularly, WT and CD can be used to detect the changing instant of brain function by indirectly estimating the phase changing point.