• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.611-613
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• 2021

Recently, research and development of quantum computers, which exceed the limits of classical computers, have been actively carried out in various fields. Quantum computers, which use quantum mechanics principles in a way different from the electrical signal processing of classical computers, have various quantum mechanical phenomena such as quantum superposition and quantum entanglement. It goes through a very complicated calculation process compared to the calculation of a classical computer for performing an operation using its characteristics. In order to utilize each element efficiently and accurately, it is necessary to visualize the data before driving the actual quantum computer and perform error verification, optimization, reliability, and verification. However, when visualizing all the data of various elements configured inside the quantum computer, it is difficult to intuitively grasp the necessary data, so it is necessary to visualize the data selectively. In this paper, we visualize the data of various elements that make up a quantum computer, and hierarchically visualize the internal circuit components of a quantum computer that are complicatedly configured so that the data can be observed and utilized intuitively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1C
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• pp.11-20
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• 2009

A new alternative method based on HWAW method to detect underground anomaly was introduced. The location of underground anomaly can be estimated by using 2-dimensional image of phase velocity image with position and wavelength based on distortion phenomena of surface wave due to underground anomaly. Overall procedure of proposed method such as field testing, signal processing and interpretation of the result was introduced. Numerical verification study was performed by using various ground models containing underground anomaly. According to the condition of anomaly, the propagation and reflection characteristics of surface wave were different and this could be more easily shown in the image of phase velocity. Some rules of distortion phenomena were found and these become clues for estimating underground anomaly in interpreting real field data. Field verification tests were performed with conventional geophysical methods such as DC resistivity method and GPR. Though field condition is not homogeneous like numerical models, similar distortion phenomena were found in the testing results and estimated location of underground anomaly was agreed well with the results of another geophysical methods.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1245-1254
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• 2023

Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.91-100
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• 2023

Reverberation time (T60) is a typical acoustic parameter that provides information about reverberation. Since the impacts of reverberation vary depending on the frequency bands even in the same space, frequency-dependent (FD) T60, which offers detailed insights into the acoustic environments, can be useful. However, most conventional blind T60 estimation methods, which estimate the T60 from speech signals, focus on fullband T60 estimation, and a few blind FDT60 estimation methods commonly show poor performance in the low-frequency bands. This paper introduces a modified approach based on Attentive pooling based Weighted Sum of Spectral Decay Rates (AWSSDR), previously proposed for blind T60 estimation, by extending its target from fullband T60 to FDT60. The experimental results show that the proposed method outperforms conventional blind FDT60 estimation methods on the acoustic characterization of environments (ACE) challenge evaluation dataset. Notably, it consistently exhibits excellent estimation performance in all frequency bands. This demonstrates that the mechanism of the AWSSDR method is valuable for blind FDT60 estimation because it reflects the FD variations in the impact of reverberation, aggregating information about FDT60 from the speech signal by processing the spectral decay rates associated with the physical properties of reverberation in each frequency band.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.479-493
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• 2023

The need for safety management has arisen due to the increasing number of years of operated underground structures, such as tunnels and utility tunnels, and accidents caused by those aging infrastructures. However, in the case of privately managed underground utility ducts, there is a lack of detailed guidelines for facility safety and maintenance, resulting in inadequate safety management. Furthermore, the absence of basic design information and the limited space for safety assessments make applying currently used non-destructive testing methods challenging. Therefore, this study suggests non-destructive inspection methods using ultrasonic and impact-echo techniques to assess the quality of underground structures. Thickness, presence of rebars, depth of rebars, and the presence and depth of internal defects are assessed to provide fundamental data for the safety assessment of box-type general underground structures. To validate the proposed methodology, different conditions of concrete specimens are designed and cured to simulate actual field conditions. Applying ultrasonic and impact signals and collecting data through multi-channel accelerometers determine the thickness of the simulated specimens, the depth of embedded rebar, and the extent of defects. The predicted results are well agreed upon compared with actual measurements. The proposed methodology is expected to contribute to developing safety diagnostic methods applicable to general underground structures in practical field conditions.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.112-118
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• 2009

This paper proposes a rapid detection algorithm of a salient region for music video browsing system, which can be applied to mobile device and digital video recorder (DVR). The input music video is decomposed into the music and video tracks. For the music track, the music highlight including musical chorus is detected based on structure analysis using energy-based peak position detection. Using the emotional models generated by SVM-AdaBoost learning algorithm, the music signal of the music videos is classified into one of the predefined emotional classes of the music automatically. For the video track, the face scene including the singer or actor/actress is detected based on a boosted cascade of simple features. Finally, the salient region is generated based on the alignment of boundaries of the music highlight and the visual face scene. First, the users select their favorite music videos from various music videos in the mobile devices or DVR with the information of a music video's emotion and thereafter they can browse the salient region with a length of 30-seconds using the proposed algorithm quickly. A mean opinion score (MOS) test with a database of 200 music videos is conducted to compare the detected salient region with the predefined manual part. The MOS test results show that the detected salient region using the proposed method performed much better than the predefined manual part without audiovisual processing.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.572-577
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• 2009

Large corpus-based concatenating Text-to-Speech (TTS) systems can generate natural synthetic speech without additional signal processing. To prune the redundant speech segments in a large speech segment DB, we can utilize a decision-tree based triphone clustering algorithm widely used in speech recognition area. But, the conventional methods have problems in representing the acoustic transitional characteristics of the phones and in applying context questions with hierarchic priority. In this paper, we propose a new clustering algorithm to downsize the speech DB. Firstly, three 13th order MFCC vectors from first, medial, and final frame of a phone are combined into a 39 dimensional vector to represent the transitional characteristics of a phone. And then the hierarchically grouped three question sets are used to construct the triphone trees. For the performance test, we used DTW algorithm to calculate the acoustic similarity between the target triphone and the triphone from the tree search result. Experimental results show that the proposed method can reduce the size of speech DB by 23% and select better phones with higher acoustic similarity. Therefore the proposed method can be applied to make a small sized TTS.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.12 no.1
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• pp.25-50
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• 2001

Using Fourier transformation and wavelet analysis, we compared the auditory event-related potentials of the patients with attention deficit-hyperactivity disorders(abbr. ADHD, 13 boys) and normal control children(8 boys). Amplitudes of the event-related potentials which were calculated via Fourier transformation were compared between the groups and between conditions(non-target versus target) in each group. To the non-target stimuli, the patients with ADHD showed significantly greater amplitudes across almost all of the electrode sites and frequencies. To the target stimuli, the incidents which ADHD patients showed much higher amplitudes than normal controls significantly decreased, while those of the reverse results increased significantly. These results were consistent with the comparison results about negative difference wave(abbr. Nd wave) using Fourier transformation. In summary, it was proved that non-target stimulus which should be ignored elicited more robust electrical response from the patients with ADHD than normal children, but the target stimulus which reguired active processing did much less electrical activity in the patients. For the patients, they showed much inhibited electrical response to the target stimuli in some electrodes and frequency ranges. Normal children were more strongly stimulated by the target stimuli in almost all electrodes and frequency ranges than the patients, but less in prefrontal leads and frontal leads. Wavelet analysis results proved that early responses(0-300msec) to the nontarget stimuli of the patients were significantly greater than the normal controls in prefrontal, anterior frontal, some parts of temporal, and occipital lobes and that late response(300-370msec) were significantly lesser than normal children in parietal and central electrodes. Target stimuli elicited significantly higher electrical activity in both group than non-target stimuli did. Prefrontal and frontal lobes showed stronger responses in the patients than normal children irrespective of stimulus condition, but parietal and temporal lobes did higher activities in normal children than the patients only to the target stimuli. In conclusion, the patients with ADHD showed much greater responses to the stimuli which should be ignored, but failed to activated the necessary processes to the target stimuli. Also, we found that the frequency-dimension analysis and wavelet analysis were useful for the signal processing such as event related potentials.

• Geophysics and Geophysical Exploration
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• v.8 no.2
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• pp.145-155
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• 2005

A two-dimensional (2-D) interpretation of MT data has been performed for the purpose of fracture detection for geothermal development. Remote stations have been operated in Kyushu, Japan (480 km apart) as well as in Korea (60 km and 165 km apart in 2002 and 2003 data set, respectively). Apparent resistivity and phase curves calculated by remote processing with the Japan remote data showed enough quality for 2-D inversion for the whole frequency range. Remote reference processing with Korea remote reference data also showed quite good continuity in apparent resistivity and phase curves except some noisy frequency bands; around the power frequency, 60 Hz, and around the dead band $10^{-1}Hz\;Hz\;\~1\;Hz$, where the natural EM signal is known to be very weak. Even though the subsurface showed severe three-dimensional (3-D) characteristics in the survey area so that 2-D inversion by itself could not give enough information for deep geological structures, the 2-D inversion for the 5 survey lines showed several common features. The conductive semi-consolidate mudstone layer is dipping from north to south (about 500 m depth on the south and 200 m on the north most part of the survey area). The boundary between the low (L-2) and high (H-2) resistivity anomalies can be thought as a major fault with strike $N15^{\circ}E$, passing through the sites 206, 112 and 414. The shallow (< 1 km) conductive anomalies (L-4) seem to be fracture zones having strike E-W (at site 105) and $N60^{\circ}W$ (at site 434). And there exists a conductive layer in the western and west-southern part of the survey area in the depth below $2\~3\;km$, for which further investigation is to be needed.