• Journal of The Korean Astronomical Society
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• v.33 no.1
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• pp.37-45
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• 2000

We have investigated the properties of the high-latitude cloud MBM 7 using the 3 mm transitions of CO, CS, HCN, $HCO^+,\;C_3H_2,\;N_2H^+$, and SiO. The molecular component of MBM 7 shows a very clumpy structure with a size of $\le$0.5 pc, elongated along the northwest-southeast direction, perpendicularly to an extended HI component, which could be resulted from shock formation. We have derived physical properties for two molecular cores in the central region. Their sizes are 0.1-0.3 pc and masses 1-2 M$\bigodot$ having an average volume density $\~2{\times}10^3 cm^{-3}$ at the peak of molecular emission. We have tested the stability of the cores using the full version of the virial theorem and found that the cores are stabilized with ambient medium, and they are expected not to be dissipated easily without external perturbations. Therefore MBM 7 does not seem to be a site for new star formation. The molecular abundances in the densest core appear to be much less (by about one order of magnitude) than the 'general' dark cloud values. If the depletions of heavy elements are not significant in the HLCs compared with those in typical dark clouds, our results may suggest different chemical evolutionary stages or different chemical environments of the HLCs compared with dense dark clouds in the Galactic plane.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5464-5484
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• 2016

Few samples face recognition has become a highly challenging task due to the limitation of available labeled samples. As two popular paradigms in face image representation, sparse component analysis is highly robust while parts-based paradigm is particularly flexible. In this paper, we propose a probabilistic generative model to incorporate the strengths of the two paradigms for face representation. This model finds a common spatial partition for given images and simultaneously learns a sparse component analysis model for each part of the partition. The two procedures are built into a probabilistic generative model. Then we derive the score function (i.e. feature mapping) from the generative score space. A similarity measure is defined over the derived score function for few samples face recognition. This model is driven by data and specifically good at representing face images. The derived generative score function and similarity measure encode information hidden in the data distribution. To validate the effectiveness of the proposed method, we perform few samples face recognition on two face datasets. The results show its advantages.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.47.1-47.1
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• 2020

Multi-band photometry provides an advantage in being able to perform taxonomic classification analysis on a large number of asteroids in a much shorter period of time than spectroscopy. We observed main-belt asteroids using Korea Microlensing Telescope Network (KMTNet) in CTIO during the summer seasons in the southern hemisphere, mostly in December 2015, 2016 and 2017 with two visible photometric systems, SDSS (g, r, i, and z), and Johnson-Cousins (B, V, R, and I). Targets were selected for the asteroids which had already been classified based on Bus-Binzel taxonomy (Bus & Binzel, 2002) and DeMeo taxonomy (DeMeo et al. 2009). Not only the targets but also numerous serendipitously observed asteroids were identified. In summary, 6817 and 5456 known objects, including 307 and 233 already classified asteroids were observed with SDSS and Johnson-Cousins systems, respectively. Using principal component analysis, the three major asteroid complexes and a class, S-, C-, and X-complexes and V class are found to be well separated in the principal component plane (spectral slope and 1 micron absorption depth) with both filter systems. We will present and discuss the results of our newly proposed three-dimensional color taxonomy for asteroids using the whole dataset (Roh et al., to be submitted).

• KIEAE Journal
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• v.5 no.4
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• pp.25-32
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• 2005

In apartment complexes of Korea shared space becomes more and more important since it promotes social relationship among neighbors and also as a ecological point of view. After the Green Building system was introduced in the society, it attracted more attentive as an essential component for sustainable community. Now, it's expected the shared space plan or the community center plan will be a hot issue in the society. Therefore, we could see an aspect of the gradual change related to housing culture in Korea and make a prediction how to develop the shared space as researching domestic leading studies about the 'shared space'. The purpose of this study is to identify the trend of academic achievement as shared spaces. 14 books and 43 studies are searched and each of them are divided into according to the subject. The concept of the shared space was introduced in a holistic moment and the design plans were presented in books in the early 1990's, and total community center it was introduced. The studies are naturally divided into 4 parts as time passed that are characteristics of the block planning in the complex, the needs of the shared space, the actual condition of the using shared space, and the case studies of the shared space. The shared spaces under the structure of the community center are expected to be developed in a more elaborate way to cope with increasingly well-being needs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.1946-1953
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• 2006

Because the embedded watermark of luminance component guarantees the extraction of ownership information when the color image is converted to gray scale image, the information of ownership right as to the luminance component is embedded in the luminance-chrominance color space such as YCbCr. Therefore, this paper proposes watermark embedding, extraction and authentication algorithm of color image. which considers the device and performance of multimedia contents service by focusing on the robustness and invisibility of watermark. The color image is converted from RGB color space to YCbCr color space, and then the properties of each component of Y(Luminance), Cb(Color Differences) and Cr(Color Differences) are considered in order to embed, extract and certify multi-level watermark in the frequency domain based on the wavelet. As a result, it can guaranteed the robustness for the JPEG compression and invisibility of watermark for multi-level.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.687-696
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• 2015

JCT-VC (Joint Collaborative Team on Video Coding) continues developing HEVC/Screen Content Coding (HEVC/SCC) as an extension for efficiently coding screen content videos, including computer animations, graphics, and electrical documents, based on HEVC/Range extension (HEVC/RExt.). Color space conversion from RGB space being captured from CCD sensors is popular in natural video coding. However, the conversion is often undesired for screen contents because of a significant loss in perceptual quality. Therefore, several coding tools including cross-component prediction (CCP) and in-loop adaptive color space transform (ACST) have been developed for an efficient screen content video coding in order to reduce the redundancies between color spaces while maintaining the original color space. In this paper, we review the two coding tools, i.e., CCP and ACST exploiting the correlation in the RGB color space and conduct the performance analysis of the coding tools. In our simulation results, CCP and ACST provide 11.7% BD-rate saving and 16.4% BD-rate saving, respectively, while the two coding tools provide 18.2% BD-rate saving in total. Following this idea, if the two coding tools are exclusively selected, we provide 93% encoding measurement time with a 0.3% coding loss.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.22.1-22.1
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• 2011

Two dominant components of polar motion are the Chandler and the annual components. Recently, the existence of 500-day period component in the Earth's polar motion has been manifested. But its existence is not clear on Fourier spectrum. One cause of difficulty involved here is that the amplitudes of the two main components are slightly variable in time by certain amounts (Chandler: 0.15~0.28 arcsec, annual: 0.09~0.15 arcsec). A residual polar motion time series excluding the two main components for a time span between 1962 Jan and 2010 Nov from IERS C04 time series dataset was constructed by least square fitting. For faithful fitting, 43 time segments of 6.8 year length (each starts on January 1st of successive years) were separately acquired and later combined together. The period of dominant peak in the spectrum of this residual polar motion time series is 490 days. Next peaks have their periods as semi-annual, 300~330 days, ~560 days, 670 days, and 1360 days.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.175-177
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• 2003

This paper addresses a problem of classifying human breast cancer into its subtypes. A main ingredient in our approach is kernel machines such as support vector machine (SVM). kernel principal component analysis (KPCA). and kernel partial least squares (KPLS). In the task of breast cancer classification, we employ both SVM and KPLS and compare their results. In addition to this classification. we also analyze the patterns of clinical outcomes in the feature space. In order to visualize the clinical outcomes in low-dimensional space, both KPCA and KPLS are used. It turns out that these methods are useful to identify correlations between clinical outcomes and the nonlinearly protected expression profiles in low-dimensional feature space.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.29.2-29.2
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• 2008

The CCD photometric observations of the W UMa type contact binary GX Aur were performed for 33 nights from 2004 to 2008 using a 2K CCD camera and Johnson BVRI filter system attached to the 61cm reflector at Sobaeksan Optical Astronomy Observatory (SOAO). From our observations, the first BVRI light curves of GX Aur were completed and eight new times of minima (primary: 4, secondary: 4) were obtained. All the times of minima including our timings were collected and analyzed to see the dynamical behavior of GX Aur system. Intensive analysis of our BVRI lightcurves with the recent Wilson-Devinney binary model shows that GX Aur is an over-contact binary whose component stars have equal mass and time-variable spots.