• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.93-94
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• 1996

The Galaxy and the Large and Small Magellanic Clouds (LMC and SMC respectively) form a triple system of mutually interacting galaxies. We have carried out a set of N-body simulations on the gravitational interaction of the SMC with the Galaxy and the LMC in order to model prominent features such as the Magellanic Stream, the inter-Cloud Bridge, and the large depth of the SMC which are thought to be products of the tidal interactions among the members of this system.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2001.11a
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• pp.83-84
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• 2001

액적화학은 SO4$^{-2}$ 생성에 중요한 역할을 할 뿐만 아니라 OH와 HO$_2$ 라디칼 생성에도 영향을 미친다. 따라서 기존 기상 광화학반응에 액적화학을 추가하여 산성비 모사를 하여왔다. 그러나 액적화학을 추가하기 위해서는 기액간의 물질전달을 포함하여야 하고 액적화학반응속도와 기상화학반응속도가 크게 다름으로써 수치적 풀이의 어려움이 가중되는 문제가 있다. 따라서 기존 연구에서는 기액간의 평형 및 시간 분리 등의 가정을 사용하여 액적화학 반응 추가에 따른 문제를 해결하여 왔다. 본 논문은 이러한 수치단순화의 정확도를 평가하려 한다. (중략)

• Journal of Advanced Technology Convergence
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• v.1 no.2
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• pp.01-09
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• 2022

Recently, safety issues in companies and public institutions are no longer a task that can be postponed, and when a major safety accident occurs, not only direct financial loss, but also indirect loss of social trust in the company and public institution is greatly increased. In particular, in the case of a fatal accident, the damage is even more serious. Accordingly, as companies and public institutions expand their investments in industrial safety education and prevention, open AI learning model creation technology that enables safety management services without being affected by user behavior in industrial sites where high-risk situations exist, edge terminals System development using inter-AI collaboration technology, cloud-edge terminal linkage technology, multi-modal risk situation determination technology, and AI model learning support technology is underway. In particular, with the development and spread of artificial intelligence technology, research to apply the technology to safety issues is becoming active. Therefore, in this paper, an open cloud platform design method that can support AI model learning for high-risk site safety management is presented.

• Atmosphere
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• v.21 no.3
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• pp.311-317
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• 2011

Aerosol optical properties from the radiation measurements by SKYNET PREDE skyradiometers, POM-01 and POM-02 were compared during the inter-calibration campaign at Seoul in February 2009. The monochromatic solar flux at the top of the atmosphere ($F_0$) gave a relative standard deviation (RSD) of 9-10% for both instruments. This comparatively high value of RSD was probably because $F_0$ was determined at short time intervals, in the morning and afternoon, using the measurements made in the polluted environment of Seoul. Although POM-02 was more effective in tracking the solar radiation, aerosol optical depths (AODs) from the two instruments were very similar after the cloud screening procedure. The squared correlation coefficients ($R^2$) of single scattering albedo (SSA) and real and imaginary refractive indices between the two instruments was around 0.5 but increased to 0.7-0.8 when only using AOD greater than 0.4. Nevertheless, mean values of the Angstrom exponent, SSA, and the imaginary refractive index of POM-02 were higher than those of POM-01.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.49-54
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• 2000

Conventional methods for measuring winds provide wind velocity observations over limited area and time period. The use of satellite imagery for measuring wind velocity overcomes some of these limitations by providing wide area and near condinuous coverage. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP models. GMS-5 provides full disk images at hourly intervals. At four times each day - 0500, 1100, 1700, 2300 hours UTC-a series of three images is received, separated by thirty minutes, centered at the four times. The current wind system generates winds from sets of 3 infrared(IR) images, separated by an hour, four times a day. It also produces visible(VIS) and water vapor(WV) image-based winds from half-hourly imagery four times a day. The derivation of wind from satellite imagery involves the identification of suitable cloud targets. tracking the targets on sequential images, associating a pressure height with the derived wind vector, and quality control. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.1054-1064
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• 2017

With the development of cloud computing, internet technology and Internet of Things(IoT), most of applications are being smarter and changing from native application to SaaS (Software as a Service) application. New versatile SaaS applications are being released through various app portals (e.g. appstore, googleplay, T-Store, and so on). However, a user has a difficulty in searching, choosing an suitable application to him. It is also hard for him to know what functions of each SaaS application are useful. He wants to be recommended something inter-operated SaaS service according to his personality and his situation. Therefore, this paper presents a way of making mash-up of SaaS applications in order to provide the most convenient inter-operated SaaS service to user. This paper also presents SaaS Application Mash-up Framework (SAMF), complex context and rule matrix. The proposed SAMF is a main system that totally manage SaaS application mash-up service. Complex context and rule matrix are key components in order to recommend what SaaS applications are needed and how those SaaS applications are inter-operated. The SAMF collects complex contexts (User Description, Status Description, SaaS Service Description) in order to choose which SaaS applications are useful, analyze what functions to use, how to mash-up.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.135-139
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• 1999

Wind velocity is one of the primary variables for describing atmospheric state from GMS-5. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP(Numerical Weather Prediction) models. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images. Multi spectral imagery from GMS-5 was used for this purpose and applied to Korean region with together BoM(Bureau of Meteorology). The derivation of wind velocity estimates from low and high resolution visible, split window infrared, and water vapor images, resulted in improvements in the amount and quality of wind data available for forecasting.

• Electronics and Telecommunications Trends
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• v.37 no.2
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• pp.42-52
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• 2022

Intra- and inter- datacenter data traffic is rapidly increasing due to the spread of smart devices, cloud computing, and non-face-to-face services. Recently, 400-Gbps optical transceivers based on 100-Gbps/channel have been released primarily by major overseas companies. Various solutions for next-generation datacenter interconnect are being proposed by international standardization and multiple source agreement groups. Following this trend, ETRI has developed a 400-Gbps optical transmission/reception engine using 100-Gbps/channel light sources and photodetectors as well as a silica-based AWG. In the future, technologies of optical devices and components for intra-datacenter communication are expected to be developed based on a data rate of 200-Gbps/channel. Thus, 1.6-Tbps class optical transceivers will be released.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.279-282
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• 2021

포인트 클라우드는 3 차원 물체를 표현하기 위한 점들의 집합으로, 동적인 3 차원 데이터를 정밀하게 획득할 수 있기에 이의 효율적인 압축의 필요성이 대두되고 있다. 기존 3D DCT(3D Discrete Cosine Transform)를 이용한 동적 객체의 포인트 클라우드 압축 방식은 Inter 프레임 압축을 고려하지 않아 압축시의 데이터 압축률에 한계가 있다. 따라서 본 논문은 이러한 문제점을 개선하기 위해 3D DCT 를 이용한 움직임 예측을 통하여 포인트 클라우드 영상의 I 프레임 및 P 프레임을 압축하는 방식을 제안한다.

• Atmosphere
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• v.27 no.2
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• pp.235-249
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• 2017

This paper describes methodology verifying near-surface predictability of numerical weather prediction models against the surface synoptic weather station network (SYNOP) observation. As verification variables, temperature, wind, humidity-related variables, total cloud cover, and surface pressure are included in this tool. Quality controlled SYNOP observation through the pre-processing for data assimilation is used. To consider the difference of topographic height between observation and model grid points, vertical inter/extrapolation is applied for temperature, humidity, and surface pressure verification. This verification algorithm is applied for verifying medium-range forecasts by a global forecasting model developed by Korea Institute of Atmospheric Prediction Systems to measure the near-surface predictability of the model and to evaluate the capability of the developed verification tool. It is found that the verification of near-surface prediction against SYNOP observation shows consistency with verification of upper atmosphere against global radiosonde observation, suggesting reliability of those data and demonstrating importance of verification against in-situ measurement as well. Although verifying modeled total cloud cover with observation might have limitation due to the different definition between the model and observation, it is also capable to diagnose the relative bias of model predictability such as a regional reliability and diurnal evolution of the bias.