• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.716-723
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• 2008

With rapid development of science and technology and recent widening of mankind's range of activities, development of coastal waters and the environment have emerged as global issues. In relation to this, to allow more extensive analyses, the use of satellite images has been on the increase. This study aims at utilizing hyperspectral satellite images in determining the depth of coastal waters more efficiently. For this purpose, a partial image of the research subject was first extracted from an EO-1 Hyperion satellite image, and atmospheric and geometric corrections were made. Minimum noise fraction (MNF) transformation was then performed to compress the bands, and the band most suitable for analyzing the characteristics of the water body was selected. Within the chosen band, the diffuse attenuation coefficient Kd was determined. By deciding the end-member of pixels with pure spectral properties and conducting mapping based on the linear spectral unmixing method, the depth of water at the coastal area in question was ultimately determined. The research findings showed the calculated depth of water differed by an average of 1.2 m from that given on the digital sea map; the errors grew larger when the water to be measured was deeper. If accuracy in atmospheric correction, end-member determination, and Kd calculation is enhanced in the future, it will likely be possible to determine water depths more economically and efficiently.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.125-131
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• 2021

In recent years, Convolutional Neural Networks (CNNs) have achieved outstanding performance in the fields of computer vision such as image classification, object detection, visual quality enhancement, etc. However, as huge amount of computation and memory are required in CNN models, there is a limitation in the application of CNN to low-power environments such as mobile or IoT devices. Therefore, the need for neural network compression to reduce the model size while keeping the task performance as much as possible has been emerging. In this paper, we propose a method to compress CNN models by combining matrix decomposition methods of LR (Low-Rank) approximation and CP (Canonical Polyadic) decomposition. Unlike conventional methods that apply one matrix decomposition method to CNN models, we selectively apply two decomposition methods depending on the layer types of CNN to enhance the compression performance. To evaluate the performance of the proposed method, we use the models for image classification such as VGG-16, RestNet50 and MobileNetV2 models. The experimental results show that the proposed method gives improved classification performance at the same range of 1.5 to 12.1 times compression ratio than the existing method that applies only the LR approximation.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.768-779
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• 2018

In this paper, we propose a novel video quality function for video processing based on MSSSIM to select an appropriate video processing filter and to accommodate multiple processing filters to each pixel block in a picture frame by a mathematical selection law so as to maintain video quality and to reduce the bitrate of compressed video. In viewpoint of video compression, since the properties of video quality and bitrate is different for each picture of video frames and for each areas in the same frame, it is difficult for the video filter with single property to satisfy the object of increasing video quality and decreasing bitrate. Consequently, to maintain the subjective video quality in spite of decreasing bitrate, we propose the methodology about the MSSSIM as the measure of subjective video quality, the KL-Divergence as the measure of bitrate, and the combination method of those two measurements. Moreover, using the proposed combinatorial measurement, when we use the multiple image filters with mutually different properties as a pre-processing filter for video, we can verify that it is possible to compress video with maintaining the video quality under decreasing the bitrate, as possible.

• Korean Journal of Heritage: History & Science
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• v.50 no.3
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• pp.88-109
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• 2017

As the technique to remove Paraloid B-72, which is known as an irreversible material, the method using organic solvent and heating, though the ways vary depending on the kind of material to be removed, has been usually used, but it has yet to apply to mud mural because of the technical limit in processing and the potential risk of damage and, moreover, the removal efficiency which also remains unproven. Thus, in a bid to seek the way to safely remove Paraloid B-72 contained in mural, the test was conducted in a way of applying a compress method, which is deemed most efficient. The solvents which are proven to be Paraloid B-72 were applied to the absorbents such as active carbon fiber and methyl cellulose and then were eluted to the surface of mud mural sample which was prepared in the same size and condition for a certain time before evaluating the stability and removal efficiency. Such test was intended to identify the applicability to the mural of Mireukjeon Hall at Geunsansa Temple, which had been treated with Paraloid B-72 for preservation in the past. As a result, the way of mixing the absorbent such as active carbon fiber and Xylene alone or with other quick vaporable solvents proved to be most efficient in removing Paraloid B-72 from mud mural and particularly Acetone:Xylene(1:1wt%) was found to be the most stable among others. Such a test outcome is expected to be a useful data for removing Paraloid B-72 from the mural of Mireukjeon Hall at Geunsansa Temple as well as for restoring other mural cultural assets in the coming days.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.553-565
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• 2021

Point cloud is a set of points for representing a 3D object, and consists of geometric information, which is 3D coordinate information, and attribute information, which is information representing color, reflectance, and the like. In this way of expressing, it has a vast amount of data compared to 2D images. Therefore, a process of compressing the point cloud data in order to transmit the point cloud data or use it in various fields is required. Unlike color information corresponding to all 2D geometric information constituting a 2D image, a point cloud represents a point cloud including attribute information such as color in only a part of the 3D space. Therefore, separate processing of geometric information is also required. Based on these characteristics of point clouds, MPEG under ISO/IEC standardizes V-PCC, which imitates point cloud images and compresses them into 2D DCT-based 2D image compression codecs, as a compression method for high-density point cloud data. This has limitations in accurately representing 3D spatial information to proceed with compression by converting 3D point clouds to 2D, and difficulty in processing non-existent points when utilizing 3D DCT. Therefore, in this paper, we present 3D Discrete Cosine Transform-based Point Cloud Compression (3DCT PCC), a method to compress point cloud data, which is a 3D image by utilizing 3D DCT, and confirm the efficiency of 3D DCT compared to V-PCC based on 2D DCT.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.39-47
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• 2020

In this paper, we proposed a deep learning-based detection method using Saliency Attention to detect salient objects in images. The salient object detection separates the object where the human eye is focused from the background, and determines the highly relevant part of the image. It is usefully used in various fields such as object tracking, detection, and recognition. Existing deep learning-based methods are mostly Autoencoder structures, and many feature losses occur in encoders that compress and extract features and decoders that decompress and extend the extracted features. These losses cause the salient object area to be lost or detect the background as an object. In the proposed method, Saliency Attention is proposed to reduce the feature loss and suppress the background region in the Autoencoder structure. The influence of the feature values was determined using the ELU activation function, and Attention was performed on the feature values in the normalized negative and positive regions, respectively. Through this Attention method, the background area was suppressed and the projected object area was emphasized. Experimental results showed improved detection results compared to existing deep learning methods.

• Smart Media Journal
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• v.9 no.4
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• pp.26-35
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• 2020

Attempts to predict future stock prices have been studied steadily since the past. However, unlike general time-series data, financial time-series data has various obstacles to making predictions such as non-stationarity, long-term dependence, and non-linearity. In addition, variables of a wide range of data have limitations in the selection by humans, and the model should be able to automatically extract variables well. In this paper, we propose a 'sliding time step normalization' method that can normalize non-stationary data and LSTM autoencoder to compress variables from all variables. and 'moving transfer learning', which divides periods and performs transfer learning. In addition, the experiment shows that the performance is superior when using as many variables as possible through the neural network rather than using only 100 major financial variables and by using 'sliding time step normalization' to normalize the non-stationarity of data in all sections, it is shown to be effective in improving performance. 'moving transfer learning' shows that it is effective in improving the performance in long test intervals by evaluating the performance of the model and performing transfer learning in the test interval for each step.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1C
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• pp.25-31
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• 2006

It is common to use the unconfined compressive strength (UCS) of intact rock to estimate the shaft resistance of rock socketed drilled shaft. Therefore the most design manuals give a guide to use the UCS of rock core to estimate the shaft resistance of rock-socketed drilled shaft. Recently, however the design manuals for highway bridge (KSCE, 2001) and of AASHTO (2000) were revised to use the UCS of rock mass with RQD instead of the UCS of rock core so that the estimated resistance could be representative of field conditions. Questions have been raised in application of the new guide to the domestic main bed rock types. The intrinsic drawbacks in terms of RQD were comprised in the questions, too. As the results, in 2002 the new guide in the design manual for highway bridge (KSCE, 2001) were again revised to use the UCS of rock core to estimate the shaft resistance of rock-socketed drilled shafts. In this paper, various methods which can estimate the UCS of rock mass from intact rock core were reviewed. It seems that among those, the Hoek-Brown method is very reliable and practical for the estimation of the UCS of rock mass from rock cores. As the results, using the Hoek-Brown failure criterion a modified guide for the estimation of the shaft resistance of rock-socketed drilled shafts was suggested in this paper. Through a case study it is shown that the suggested method gives a good agreement with the measured data.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.89-103
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• 2024

In the disposal environment, gases can be generated at the interface between canister and buffer due to various factors such as anaerobic corrosion, radiolysis, and microbial degradation. If the gas generation rate exceeds the diffusion rate, the gas within the buffer may compress, resulting in physical damage to the buffer due to the increased pore pressure. In particular, the rapid movement of gases, known as gas breakthroughs, through the dilatancy pathway formed during this process may lead to releasing radionuclide. Therefore, understanding these gas generation and movement mechanism is essential for the safety assessment of the disposal systems. In this study, an experimental apparatus for investigating gas migration within buffer was constructed based on a literature review. Subsequently, a gas injection experiment was conducted on a compacted bentonite block made of Bentonile WRK (Clariant Ltd.) powder. The results clearly demonstrated a sharp increase in stress and pressure typically observed at the onset of gas breakthrough within the buffer. Additionally, the range of stresses induced by the swelling phenomenon of the buffer, was 4.7 to 9.1 MPa. The apparent gas entry pressure was determined to be approximately 7.8 MPa. The equipment established in this study is expected to be utilized for various experiments aimed at building a database on the initial properties of buffer and the conditions during gas injection, contributing to understanding the gas migration phenomena.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.829-849
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• 2017

Due to the large-scale TV display, the convergence of broadcasting and broadband, and the advancement of signal compression and transmission technology, terrestrial digital broadcasting has evolved into UHD broadcasting capable of providing simultaneous broadcasting of fixed UHD and mobile HD. The Korean standard for terrestrial UHDTV broadcasting is based on ATSC 3.0, the broadcasting standard of North America. The terrestrial UHDTV broadcasting standard chose that as a new AV codec standard, HEVC video codec which can compress with higher efficiency compared to AVC, and MPEG-H 3D audio codec for realistic audio. Also, DASH and MMT are adopted as transmission format instead of MPEG-2 TS to support broadband as well as broadcasting network, and in order to provide 4K UHD/mobile HD service simultaneously ROUTE multiplexing technology is applied. In this paper, we propose an audio/video encoder, which is required to provide HDR/WCG supported high quality video service, 10.2 channel/4 object supporting stereo sound service, fixed UHD and mobile HD simultaneous broadcasting service based on ATSC3.0, also we implemented the ATSC 3.0 LDM system for ROUTE/DASH packager, multiplexing system and physical layer transmission/reception, and verified the service ability by applying it to real time broadcast environment.