• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1518-1531
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• 1999

The reconstructed images from highly compressed MPEG or H.263 data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at cross points of blocks, and ringing noise near image edges, because the MPEG or H.263 quantizes the transformed coefficients of 8$\times$8 pixel blocks. A post-processing algorithm has been proposed by authors to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. Our signal-adaptive post-processing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the subjective quality evaluation using modified single stimulus method (MSSM), the objective quality evaluation (PSNR) and the computation complexity analysis between the signal-adaptive post-processing algorithm and the MPEG-4 VM (Verification Model) post-processing algorithm is performed by computer simulation with several MPEG-4 image sequences. According to the comparison study, the subjective image qualities of both algorithms are similar, whereas the PSNR and the comparison complexity analysis of the signal-adaptive post-processing algorithm shows better performance than the VM post-processing algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.135-140
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• 2012

The mirror neuron system in the cerebrum, which are handled by visual information-based imitative learning. When we observe the observer's range of mirror neuron system, we can assume intention of performance through progress of neural activation as specific range, in include of partially hidden range. It is goal of our paper that imitative learning is applied to 3D vision-based intelligent system. We have experiment as stereo camera-based restoration about acquired 3D image our previous research Using Optical flow, unscented Kalman filter. At this point, 3D input image is sequential continuous image as including of partially hidden range. We used Hidden Markov Model to perform the intention recognition about performance as result of restoration-based hidden range. The dynamic inference function about sequential input data have compatible properties such as hand gesture recognition include of hidden range. In this paper, for proposed intention recognition, we already had a simulation about object outline and feature extraction in the previous research, we generated temporal continuous feature vector about feature extraction and when we apply to Hidden Markov Model, make a result of simulation about hand gesture classification according to intention pattern. We got the result of hand gesture classification as value of posterior probability, and proved the accuracy outstandingness through the result.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.482-486
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• 2009

Conventional music players offer simple replay and one way entertainment. The paper presents an algorithm to extract, within a digitally recorded music file, the temporal information of a sequence of target notes (i.e. melody). We assume to have the score (e.g. MIDI or printed score), and using this information, it becomes possible to first sequentially predict the probable location of the target notes. However, recorded music is hardly performed according to the score, especially temporally. Thus, additional analysis is carried out to hone in on the exact location of the target note from the initially predicted location. This prediction and correction process is repeated to find one note after another. This allows us to develop an interactive music player that is enacted by rhythmic interaction, and induce a new user experience, i.e. as if one is playing the music oneself.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.22-29
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• 2016

Many studies in detection and classification of the targets in the underwater environments have been conducted for military purposes, as well as for non-military purpose. Due to the complicated characteristics of underwater acoustic signal reflecting multipath environments and spatio-temporal varying characteristics, active sonar target detection technique has been considered as a difficult technique. In this paper, we describe the basic concept of Fractional Fourier transform and optimal transform order. Then we analyze the relationship between time-frequency characteristics of an LFM signal and its spectrum using Fractional Fourier transform. Based on the analysis results, we present active sonar target detection method. To verify the performance of proposed methods, we compared the results with conventional FFT-based matched filter. The experimental results demonstrate the superiority of the proposed method compared to the conventional method in the aspect of AUC(Area Under the ROC Curve).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.321-340
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• 2016

The Compressive Video Sensing (CVS) is a useful technology for wireless systems requiring simple encoders but handling more complex decoders, and its rate-distortion performance is highly affected by the quantization of measurements and reconstruction of video frame, which motivates us to presents the Space-Time Quantization (ST-Q) and Motion-Aligned Reconstruction (MA-R) in this paper to both improve the performance of CVS system. The ST-Q removes the space-time redundancy in the measurement vector to reduce the amount of bits required to encode the video frame, and it also guarantees a low quantization error due to the fact that the high frequency of small values close to zero in the predictive residuals limits the intensity of quantizing noise. The MA-R constructs the Multi-Hypothesis (MH) matrix by selecting the temporal neighbors along the motion trajectory of current to-be-reconstructed block to improve the accuracy of prediction, and besides it reduces the computational complexity of motion estimation by the extraction of static area and 3-D Recursive Search (3DRS). Extensive experiments validate that the significant improvements is achieved by ST-Q in the rate-distortion as compared with the existing quantization methods, and the MA-R improves both the objective and the subjective quality of the reconstructed video frame. Combined with ST-Q and MA-R, the CVS system obtains a significant rate-distortion performance gain when compared with the existing CS-based video codecs.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.49.1-49.1
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• 2010

The study of pores, small penumbraless sunspots, can give us a chance to understand how strong magnetic fields interact with convective motions in the photosphere. For a better understanding of this interaction, we investigate the temporal variation of several tiny pores smaller than 2". These pores were observed by the Solar Optical Telescope (SOT) onboard Hinode on 2006 December 29. We have analyzed the high resolution spectropolarimetric (SP) data and the G-band filtergrams taken during the observation. Magnetic flux density and Doppler velocities of the pores are estimated by applying the center of gravity (COG) method to the SP data. The horizontal motions in and around the pores are tracked by adopting the Nonlinear Affine Velocity Estimator (NAVE) method to the G-band filter images. As results, we found the followings. (1) Darkness of pores is positively correlated with magnetic flux density. (2) Downflows always exist inside and around the pores. (3) The speed of downflows inside the pores is negatively correlated with their darkness. (4) The pores are surrounded by strong downflows. (5) Brightness changes of the pores are correlated with the divergence of mass flow (correlation coefficient > 0.9). (6) The pores in the growing phase are associated with the converging flow pattern and the pores in the decay phase with the diverging flow pattern. Our results support the idea that a pore grows as magnetic flux density increases due to the convergence of ambient mass flow and it decays with the decrease of the flux density due to the diverging mass flow.

• Journal of Korean Society on Water Environment
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• v.30 no.5
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• pp.549-558
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• 2014

Occurrence frequency of flood and drought tends to increase in last a few decades, leading to social and economic damage since the abnormality of climate changes is one of the causes for hydrologic facilities by exceedance its designed tolerance. Soil and Water Assessment Tool (SWAT) model was used in the study to estimate temporal variance of groundwater recharge and baseflow. It was limited to consider recession curve coefficients in SWAT model calibration process, thus the recession curve coefficient was estimated by the Baseflow Filter Program (BFLOW) before SWAT model calibration. Precipitation data were estimated for 2014 to 2100 using three models which are GFDL-ESM2G, IPSL-CM5A-LR, and MIROC-ESM with Representative Concentration Pathways (RCP) scenario. SWAT model was calibrated for the Soyang watershed with NSE of 0.83, and $R^2$ of 0.89. The percentage to precipitation of groundwater recharge and baseflow were 27.6% and 17.1% respectively in 2009. Streamflow, groundwater recharge, and baseflow were estimated to be increased with the estimated precipitation data. GFDL-ESM2g model provided the most large precipitation data in the 2025s, and IPSL-CM5A-LR provided the most large precipitation data in the 2055s and 2085s. Overall, groundwater recharge and baseflow displayed similar trend to the estimated precipitation data.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.E1
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• pp.15-28
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• 2004

To study the characteristics of ammonia and the related compounds, atmospheric aerosols and gases were collected using a triple filter pack sampler, a low volume air sampler, and a three-stage Anderson air sampler in Seoul and Kangwha Island, Korea from Dec. 1996 to Oct. 1997. Ammonia concentrations showed approximately two times higher in summer than in winter at both sites. The highest $HNO_3$ levels were generally observed in summertime at two sampling sites. The average mass concentration of $PM_{2.5}$ in heavily industrialized Seoul was about three times higher than that of Kangwha. In winter, the sum of $NH_4^+$ and its counter ions (such as $Cl^-,\;NO_3^-$, and $SO_4^{2-}$) comprised $30-41\%$ of $PM_{2.5}$ mass concentration at each sampling site. Temperature dependence of particulate nitrate was examined at the urban sampling site. The formation of the nitrate in the fine mode was dependent not only on the amount of precursors but also on the variation of temperature. $(NH_4)_2SO_4$ and $NH_4HSO_4$ coexisted with $NH_4NO_3$ and $NH_4Cl$ at each site. According to the summertime backward trajectory analysis, $NO_3^-$ showed higher level with air parcels transported from northeast Asian continent. On the other hand, the concentration of $SO_4^{2-}$ showed significantly higher level when air masses originated from Pacific Ocean, southern part of Japan, and Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.154-154
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• 2019

Characterization of reliable field-scale root-zone soil moisture (RZSM) variability contribute to effective hydro-meterological monitoring. Although a promising cosmic-ray neutron probe (CRNP) holds the pontential for field-scale RZSM measurement, it is often restricted at deeper depths due to the non-unique sensitivity of CRNP-measured fast neutron signal to other hydrogen pools. In this study, a merging framework relied on coupling cosmic-ray soil moisture with a representative additional RZSM, was introduced to scale shallower CRNP effective depth to represent root-zone layer. We tested our proposed framework over a densely vegetated region in South Korea covering a network of one CRNP and nine in-situ point measurements. In particular, cosmic-ray soil moisture and ancillary RZSM retrieved from the most time stable location were considered as input datasets; whereas the remaining point locations were used to generate a reference RZSM product. The errors between these two input datasets and the reference were forecasted by a linear autoregressive model. A linear combination of forecasts was then employed to compute a suitable weight for merging two input products from the predicted errors. The performance of merging framework was evaluated against reference RZSM in comparison to the two original products and a commonly used exponential filter technique. The results of this study showed that merging framework outperformed other products, demonstrating its robustness in improving field-scale RZSM. Moreover, a strong relationship between the quality of input data and the performance merging framework in light of CRNP effective depth variation has been also underlined via the merging framework.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.599-606
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• 2019

The Arena Fragmentation Test(AFT) is one of the important tasks for designing a high-explosive warhead. In order to measure the statistics of a warhead in the test, fragments of a warhead that penetrate steel plates are detected by using complex and expensive measuring equipment. In this paper, instead of using specific hardware to measure the statistics of a warhead, we propose to use an image processing based object detection algorithm to detect fragments in AFT. To this end, we use a hard-thresholding method with a brightness feature and apply a morphology filter to remove noise components. We also propose a simple yet effective temporal filtering method to detect only the first penetrating fragments. We show that the performance of the proposed method is comparable to that of a hardware system under the same experimental conditions. Furthermore, the proposed method can produce better results in terms of finding exact positions of fragments.