• 한국항공운항학회지
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• 제25권4호
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• pp.124-129
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• 2017

Clouds are an important factor in aircraft flight. In particular, a significant impact on small aircraft flying at low altitude. Therefore, we have verified and characterized the low level cloud prediction data of the Unified Model(UM) - based Local Data Assimilation and Prediction System(LDAPS) operated by KMA in order to develop cloud forecasting service and contents important for safety of low-altitude aircraft flight. As a result of the low level cloud test for seven airports in Korea, a high correlation coefficient of 0.4 ~ 0.7 was obtained for 0-36 leading time. Also, we found that the prediction performance does not decrease as the lead time increases. Based on the results of this study, it is expected that model-based forecasting data for low-altitude aviation meteorology services can be produced.

• 대한원격탐사학회지
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• 제28권3호
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• pp.287-296
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• 2012

Although low spatial resolution satellite images like MODIS and GOCI can be important to observe land surface, it is often difficult to visually interpret the imagery because of the low contrast by prevailing cloud covers. We proposed a simple and adaptive stretching algorithm to enhance image contrast over land areas in cloudy images. The proposed method is basically a linear algorithm that stretches only non-cloud pixels. The adaptive linear stretch method uses two values: the low limit (L) from image statistics and upper limit (U) from low boundary value of cloud pixels. The cloud pixel value was automatically determined by pre-developed empirical function for each spectral band. We used MODIS and GOCI images having various types of cloud distributions and coverage. The adaptive contrast stretching method was evaluated by both visual interpretation and statistical distribution of displayed brightness values.

• 대기
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• 제17권2호
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• pp.195-205
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• 2007

The influences of ice microphysical processes on urban heat island-induced convection and precipitation are numerically investigated using a cloud-resolving model (ARPS). Both warm- and cold-cloud simulations show that the downwind upward motion forced by specified low-level heating, which is regarded as representing an urban heat island, initiates moist convection and results in downwind precipitation. The surface precipitation in the cold-cloud simulation is produced earlier than that in the warm-cloud simulation. The maximum updraft is stronger in the cold-cloud simulation than in the warm-cloud simulation due to the latent heat release by freezing and deposition. The outflow formed in the boundary layer is cooler and propagates faster in the cold-cloud simulation due mainly to the additional cooling by the melting of falling hail particles. The removal of the specified low-level heating after the onset of surface precipitation results in cooler and faster propagating outflow in both the warm- and cold-cloud simulations.

• 스마트미디어저널
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• 제5권2호
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• pp.65-76
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• 2016

최근 클라우드 컴퓨팅이 새로운 공격 대상으로 부상하기 시작했으며, 클라우드의 다양한 서비스를 지연 및 방해하기 위한 악의적인 DDoS 공격이 진행되고 있다. 본 논문에서는 허니팟 보안 기술과 클라우드 컴퓨팅의 자원을 이용한 호넷 클라우드를 제안하며, 간략하게 사이버 탄력성에 의한 능동 상호동작의 프레임워크에 의한 보안 기능들을 정의 및 설계한다. 더불어 가상 허니팟 서비스를 위한 사이버 탄력성을 이용한 Low-Interaction vHonyepot의 기능들을 시뮬레이션하여 가능성을 검증한다.

• 대한원격탐사학회지
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• 제11권1호
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• pp.31-45
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• 1995

The values of brightness temperature difference (BTD) between 11um and 12um infrared channels may reflect amounts of low-level water vapor and cloud types due to the different absorptivity for water vapor between two channels. A simple method of classifying cloud types at night was proposed. Two-dimensional histograms of brightness temperature of the 11um channel and the BTD between the split window data over subareas around characteristic clouds such as Cb(cumulonimbus), Ci(cirrus), and Sc(stratocumulus) was constructed. Cb, Ci and Sc can be classified by seleting appropriate thresholds in the two-dimensional histograms. And we can see amounts of low-level water vapor in clear area as well as cloud types in cloudy area in the BTD image. The map of cloud types and low-level water vapor generated by this method was compared with 850hPa and 1000hPa relative humidity(%) of numerical analysis data and nephanalysis chart. The comparisons showed reasonable agreement.

• 대한임베디드공학회논문지
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• 제14권2호
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• pp.103-111
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• 2019

The IoT-driven large-scaled systems consist of connected things with on-chip executable embedded software. These light-weighted embedded things have limited hardware space, especially small size of on-chip flash memory. In addition, on-chip embedded software in flash memory is not easy to update in runtime to equip with latest services in IoT-driven applications. It is becoming important to develop light-weighted IoT devices with various software in the limited on-chip flash memory. The remote instruction execution in cloud via IoT connectivity enables to provide high performance software execution with unlimited software instruction in cloud and low-power streaming of instruction execution in IoT edge devices. In this paper, we propose a Cloud-IoT asymmetric structure for providing high performance instruction execution in cloud, still low power code executable thing in light-weighted IoT edge environment using remote instruction execution. We propose a simulated approach to determine efficient partitioning of software runtime in cloud and IoT edge. We evaluated the instruction cloudification using remote instruction by determining the execution time by the proposed structure. The cloud-connected instruction set simulator is newly introduced to emulate the behavior of the processor. Experimental results of the cloud-IoT connected software execution using remote instruction showed the feasibility of cloudification of on-chip code flash memory. The simulation environment for cloud-connected code execution successfully emulates architectural operations of on-chip flash memory in cloud so that the various software services in IoT can be accelerated and performed in low-power by cloudification of remote instruction execution. The execution time of the program is reduced by 50% and the memory space is reduced by 24% when the cloud-connected code execution is used.

• 한국항공운항학회지
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• 제15권3호
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• pp.57-62
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• 2007

In this paper, we attempted to produce the cloud forecast that use the numerical weather prediction(NWP) MM5 for objective cloud forecast. We presented two methods for cloud forecast. One of them used total cloud mixing ratio registered to sum(synthesis) of cloud-water and cloud-ice grain mixing ratio those are variables related to cloud among NWP result data and the other method that used relative humidity. An experiment was carried out period from 23th to 24th July 2004. According to the sequence of comparing the derived cloud forecast data with the observed value, it was indicated that both of those have a practical use possibility as cloud forecast method. Specially in this Case study, cloud forecast method that use total cloud mixing ratio indicated good forecast availability to forecast of the low level clouds as well as middle and high level clouds.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 추계학술대회
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• pp.350-353
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• 2014

클라우드 기반의 주식 체결 시스템에서는 대규모의 데이터가 운영되고 있다. 그러나 주식 체결 시스템에서 클라우드 기반으로 데이터 상호운용은 쉽지 않은 기술이다. 또한 시스템상의 최적의 전송속도와 데이터 적시성을 만족하기에는 어려움이 따른다. 그로 인한 저지연 최소화 문제와 처리 속도 향상을 위한 다양한 기술이 도입되고 있다. 하지만 Socket Direct Protocol, TCP/IP Offload Engine과 같은 하드웨어로는 속도 개선의 한계가 있으며, 도입 효과 또한 낮다는 것이 현실이다. 본 논문에서는 클라우드 환경의 XMDR-DAI 기반 주식 체결 시스템 제안하여 데이터 적시성을 만족하고, 최적의 전송 속도와 신뢰성을 만족하기 위해 Safe Proper Time 방식을 제안한다.

• 대한원격탐사학회지
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• 제23권2호
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• pp.71-87
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• 2007

본 연구는 NASA/GSFC에서 제공하는 MODIS 구름 산출물 자료를 활용하여 국지적 현상으로 나타난 영동지역의 14개 대설 사례를 분석하였다. MODIS에 의해 특정시간에 관측된 영동지역의 구름은 운정 온도(CTT), 광학 두께(COT), 유효 입자 반경$(r_e)$, 입자상(CP)과 같이 구름 내 속성의 특징에 따라 A, B, C 형으로 분류하였다. 각각의 구름 형태에 대한 강수량과 구름의 속성 사이의 연관성 분석에서 COT는 A와 B형에서 상당히 높은 통계적으로 유의한 관계성을 보였으며, CTT는 A형에서만 높은 상관성을 보였다. 그렇지만, C형에서는 통계적으로 유의한 관계성이 구름의 특성물에 대해 나타나지 않았다. A형 구름은 작은 크기의 물방울과 함께 주로 낮은 층운형 구름으로 구성되어 있으며, 동해에서 종관적으로 유도된 하층 한기 이류 하에서 발생할 수 있다. B형 구름은 발달하는 적운형 구름과 관련되어 있으며, 이러한 구름은 동해상에서 발달하는 저기압 중심과 밀접하게 관련되어 있다. 그렇지만, C형 구름은 다층 구름들로써 영동대설과 직접적으로 관련된 하층 구름을 상층구름이 덮고 있어 위성 관측이 어렵다. 따라서 MODIS 구름 산출물은 영동대설의 경우에 다층 구름을 제외하고 위성 자료로부터 강수량 추정과 대설 기작을 이해하는데 도움이 될 수 있다고 결론지을 수 있다.

• 대기
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• 제25권1호
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• pp.117-127
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• 2015

The presences of clouds significantly influence the accuracy of ozone retrievals from satellite measurements. This study focuses on the influence of clouds on Ozone Monitoring instrument (OMI) ozone profile retrieval based on an optimal estimation. There are two operational OMI cloud products; OMCLDO2, based on absorption in $O_2-O_2$ at 477 nm, and OMCLDRR, based on filling in Fraunhofer lines by rotational Raman scattering (RRS) at 350 nm. Firstly, we characterize differences between $O_2-O_2$ and RRS effective cloud pressures using MODIS cloud optical thickness (COT), and then compare ozone profile retrievals with different cloud input data. $O_2-O_2$ cloud pressures are significantly smaller than RRS by ~200 hPa in thin clouds, which corresponds to either low COT or cloud fraction (CF). On the other hand, the effect of Optical centroid pressure (OCP) on ozone retrievals becomes significant at high CF. Tropospheric ozone retrievals could differ by up to ${\pm}10$ DU with the different cloud inputs. The layer column ozone below 300 hPa shows the cloud-induced ozone retrieval error of more than 20%. Finally, OMI total ozone is validated with respect to Brewer ground-based total ozone. A better agreement is observed when $O_2-O_2$ cloud data are used in OMI ozone profile retrieval algorithm. This is distinctly observed at low OCP and high CF.