• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.237-248
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• 2018

The vertical distribution of hydrometeor before precipitation near the cloud base has been analyzed using a scanning lidar, rawinsonde data, and Cloud-Resolving Storm Simulator (CReSS). This study mostly focuses on 13 Desember 2016 only. The typical synoptic pattern of lake-effect snowstorm induced easterly in the Yeongdong region. Clouds generated due to high temperature difference between 850 hPa and sea surface (SST) penentrated in the Yeongdong region along with northerly and northeasterly, which eventually resulted precipitation. The cloud base height before the precipitation changed from 750 m to 1,280 m, which was in agreement with that from ceilometer at Sokcho. However, ceilometer tended to detect the cloud base 50 m ~ 100 m below strong signal of lidar backscattering coefficient. As a result, the depolarization ratio increased vertically while the backscattering coefficient decreased about 1,010 m~1,200 m above the ground. Lidar signal might be interpreted to be attenuated with the penetration depth of the cloud layer with of nonspherical hydrometeor (snow, ice cloud). An increase in backscattering signal and a decrease in depolarization ratio occured in the layer of 800 to 1,010 m, probably being associated with an increase in non-spherical particles. There seemed to be a shallow liquid layer with a low depolarization ratio (<0.1) in the layer of 850~900 m. As the altitude increases in the 680 m~850 m, the backscattering coefficient and depolarization ratio increase at the same time. In this range of height, the maximum value (0.6) is displayed. Such a result can be inferred that the nonspherical hydrometeor are distributed by a low density. At this time, the depolarization ratio and the backscattering coefficient did not increase under observed melting layer of 680 m. The lidar has a disadvantage that it is difficult for its beam to penetrate deep into clouds due to attenuation problem. However it is promising to distinguish hydrometeor morphology by utilizing the depolarization ratio and the backscattering coefficient, since its vertical high resolution (2.5 m) enable us to analyze detailed cloud microphysics. It would contribute to understanding cloud microphysics of cold clouds and snowfall when remote sensings including lidar, radar, and in-situ measurements could be timely utilized altogether.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.519-532
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• 2018

We investigated the effect of galactic plane toward molecular motion and kinematics in the northern filament (NF) of Orion Molecular Clouds Complex (OMC) using $^{12}CO$ (J=1-0) line. Observed data were from three areas including NF1, NF2, and NF3 in far-out order from galactic plane, for a total 270 hours by Seoul National University Radio Astronomy Observatory (SRAO) 6m telescope, with 2arcmin spatial resolution. galactic plane and OMC NF were connected to each other along the magnetic field at a density of 3% for $^{12}CO$ (J=2-1) and 9% for the case of dust. $^{12}CO$ (J=1-0), $^{12}CO$ (J=2-1), and interstellar dusts were distributed uniformly in NF3, but only in certain regions with relatively high density in NF1 and NF2. NF showed a single structure, partial shrinking motion in NF1, and rotational motion at the bottom of NF2, and spiral rotation associated with magnetic field only in NF3. The position-velocity analysis showed that the materials including $^{12}CO$ (J=1-0) could flow toward galactic plane along NF2 and NF3. However, there was no clear cause for the material to flow toward galactic plane in this result. Further detailed observation for rotational motion at the top of NF1 and NF2 might help to confirm it.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.139-145
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• 2006

The advantage of the lidar data is in fast acquisition and process time as well as in high accuracy and high point density. However lidar data itself is difficult to classify the earth surface because lidar data is in the form of irregularly distributed point clouds. In this study, we investigated land cover classification using both lidar data and optical image through a supervised classification method. Firstly, we generated 1m grid DSM and DEM image and then nDSM was produced by using DSM and DEM. In addition, we had made intensity image using the intensity value of lidar data. As for optical images, the red, blue, green band of CCD image are used. Moreover, a NDVI image using a red band of the CCD image and infrared band of IKONOS image is generated. The experimental results showed that land cover classification with lidar data and optical image together could reach to the accuracy of 74.0%. To improve classification accuracy, we further performed re-classification of shadow area and water body as well as forest and building area. The final classification accuracy was 81.8%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.51-56
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• 2014

Thesedays, there are many smart device applications developed, especially on the using various sensors included in the smart device. Smart devices have several sensors which are camera, GPS, mike, and communication module for collecting ubiquitous environment, and many applications are developed by using such sensors. In this paper, we developed the multimedia stream architecture and examined the smart device applications based on open source with front and back-end server clouds for developing the conceptual architecture. Also, we examined the back-end distributed servers, realtime multimedia stream transferring, multi-media store, and media relay for other server and smart devices. We test the examined architecture on the real target environment to collect the SIP initial setup time, media stream delay, and end-to-end play time. The test results show that there have good network operation environment to provide realtime multimedia services, and we need to improve the end-to-end play time by minimizing the initial setup time.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.28.3-29
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• 2015

$Ly{\alpha}$ nebulae, or "$Ly{\alpha}$ blobs", are extended (~100 kpc), bright (L[$Ly{\alpha}$] ~ 1044 erg/s) clouds of $Ly{\alpha}$-emitting gas. The origin of the $Ly{\alpha}$ emission remains unknown, but recent theoretical work suggests that measuring the polarization could discriminate among powering mechanisms. we will discuss current status of $Ly{\alpha}$ polarization observations at high-redshift and our on-going survey program. We will present the first narrow-band, imaging polarimetry of a $Ly{\alpha}$ blob, B3 J2330+3927 at z=3.09, with an embedded, radio-loud AGN (C. You et al. in prep.). The AGN lies near the blob's $Ly{\alpha}$ emission peak and its radio lobes align roughly with the blob's semi-major axis. With the SPOL polarimeter on the MMT telescope, we map the polarization in a grid of circular apertures of radius 0.6" (4.4 kpc), detecting a significant (>$2{\sigma}$) polarization fraction P% in 10 apertures and achieving strong upper-limits (as low as 2%) elsewhere. The degree of the polarization map increases from P% ~ 5% at ~5 kpc from the blob center to ~20% at the outer part (~30 kpc). The detections are distributed asymmetrically, roughly along the blob's major axis. The polarization angles (${\Theta}$) are mostly perpendicular to this axis. These results are consistent with the picture that $Ly{\alpha}$ photons produced at the AGN (or the host galaxy) are resonantly scattered away from the center. Higher polarization fraction on the radio jet suggests that the gas is more optically thin along the jet than the off-axis region.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.34.1-34.1
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• 2013

Interstellar ices (e.g., $H_2O$, $CO_2$, and CO ices) are formed on the surface of dust grains in dense molecular clouds. In a near-infrared spectrum, we can observe deep absorption features particularly due to $H_2O$ ice at $3.05{\mu}m$ and $CO_2$ ice at $4.27{\mu}m$. These interstellar ices have many pieces of information on the interstellar environment. Among various ices, $CO_2$ ice is one of the most important ones as a probe of the interstellar environment. That is because $CO_2$ ice is a secondary product unlike $H_2O$ and CO ices which are primarily formed on dust grains. Past studies for $CO_2$ ice in nearby galaxies were performed only for the galactic center in a few galaxies. In order to utilize the information from $CO_2$ ice effectively, it is valuable to perform mapping observations of ices on a galactic scale. With AKARI, we obtain the spatially-resolved near-infrared ($2.5-5.0{\mu}m$) spectra for the central ~1 kpc region of the nearby starburst galaxy M 82. These spectra clearly show the absorption features due to interstellar $H_2O$ and $CO_2$ ices, and we created their column density maps. As a result, we find that the spatial distribution of $H_2O$ ice is significantly different from that of $CO_2$ ice; $H_2O$ ice is widely distributed, while $CO_2$ ice is concentrated near the galactic center. Our result for the first time reveals spatial variations in $CO_2/H_2O$ ice abundance ratio on a galactic scale, suggesting that the ice-forming interstellar environment changes within a galaxy. In this presentation, we discuss the cause of the variations in the ice abundance ratio.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.1
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• pp.118-123
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• 1987

In relation to the dust detonatians which have imposed severe damages on the industry, the ignitability of various dusts has been investigated on a horizontal shock tube in this study. By using a newly designed air injector, very well-distributed clouds could be obtained. The proper reflected shock conditions have been generated by placing a reflector 1.5cm behind the air injector, which reflected the incident shock wave. The incident shock waves in the range of Mach number 2.8-3.3 created the postreflected shock temperature of 1200-1600K. Experimentally the ignition delay was defined as the time interval between the arrival of a reflected shock wave at dusts and the detection of visible light. Measured ignition delays of dusts investigated were located lower than 1msec under the above conditions. These values are one-order higher than those in the incident shock wave condition. In this type of ignitiion process the following three processes are considered to play important roles; heating of a particle, generation of volatile gas by endothermic devolatilization process, and its diffusion from the particle surface and the formation of stoichiometric mixture with oxidizer.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.59-67
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• 2005

Building information is primary source in many applications such as mapping, telecommunication, car navigation and virtual city modeling. While aerial CCD images which are captured by passive sensor(digital camera) provide horizontal positioning in high accuracy, it is far difficult to process them in automatic fashion due to their inherent properties such as perspective projection and occlusion. On the other hand, LIDAR system offers 3D information about each surface rapidly and accurately in the form of irregularly distributed point clouds. Contrary to the optical images, it is much difficult to obtain semantic information such as building boundary and object segmentation. Photogrammetry and LIDAR have their own major advantages and drawbacks for reconstructing earth surfaces. The purpose of this investigation is to automatically obtain spatial information of 3D buildings by fusing LIDAR data with aerial CCD image. The experimental results show that most of the complex buildings are efficiently extracted by the proposed method and signalize that fusing LIDAR data and aerial CCD image improves feasibility of the automatic detection and extraction of buildings in automatic fashion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2310-2345
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• 2017

With the emergence of the Internet of Things (IoT) the world is projecting towards a scenario where every object in the world (including humans) acts as a sender and receiver of data and if we were to see that concept mature we would soon be talking of billions more users of the cloud networks. The cloud technology is a very apt alternative to permanent storage when it comes to bulk storage and reporting. It has however shown weaknesses concerning real-time data accessibility and processing. The bandwidth availability of the cloud networks is limited and combined with the highly centralized storage structure and geographical vastness of the network in terms of distance from the end user the cloud just does not seem like a friendly environment for real-time IOT data. This paper aims at highlighting the importance of Flavio Bonomi's idea of Fog Computing which has been glamorized and marketed by Cisco but has not yet been given a proper service architecture that would explain how it would be used in terms of various service models i-e IaaS, PaaS and SaaS, of the Cloud. The main contribution of the paper would be models for IaaS, PaaS and SaaS for Fog environments. The paper would conclude by highlighting the importance of the presented models and giving a consolidated overview of how they would work. It would also calculate the respective latencies for fog and cloud to prove that our models would work. We have used CloudSim and iFogSim to show the effectiveness of the paradigm shift from traditional cloud architecture to our Fog architecture.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.479-493
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• 2016

LiDAR(Light Detection and Ranging) data acquired from ALS(Airborne Laser Scanner) has been intensively utilized to reconstruct object models. Especially, researches for 3D modeling from LiDAR data have been performed to establish high quality spatial information such as precise 3D city models and true orthoimages efficiently. To reconstruct object models from irregularly distributed LiDAR point clouds, sensor calibration, noise removal, filtering to separate objects from ground surfaces are required as pre-processing. Classification and segmentation based on geometric homogeneity of the features, grouping and representation of the segmented surfaces, topological analysis of the surface patches for modeling, and accuracy assessment are accompanied by modeling procedure. While many modeling methods are based on the segmentation process, this paper proposed to extract key points directly for building modeling without segmentation. The method was applied to simulated and real data sets with various roof shapes. The results demonstrate feasibility of the proposed method through the accuracy analysis.