• 대기
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• 제31권5호
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• pp.489-510
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• 2021

In this paper, we propose an algorithm for detecting convective initiation (CI) using GEO-KOMPSAT-2A/advanced meteorological imager data. The algorithm identifies clouds that are likely to grow into convective clouds with radar reflectivity greater than 35 dBZ within the next two hours. This algorithm is developed using statistical and qualitative analysis of cloud characteristics, such as atmospheric instability, cloud top height, and phase, for convective clouds that occurred on the Korean Peninsula from June to September 2019. The CI algorithm consists of four steps: 1) convective cloud mask, 2) cloud object clustering and tracking, 3) interest field tests, and 4) post-processing tests to remove non-convective objects. Validation, performed using 14 CI events that occurred in the summer of 2020 in Korean Peninsula, shows a total probability of detection of 0.89, false-alarm ratio of 0.46, and mean lead-time of 39 minutes. This algorithm can be useful warnings of rapidly developing convective clouds in future by providing information about CI that is otherwise difficult to predict from radar or a numerical prediction model. This CI information will be provided in short-term forecasts to help predict severe weather events such as localized torrential rainfall and hail.

• 한국환경과학회지
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• 제30권12호
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• pp.1027-1039
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• 2021

In this study, we investigated the optimal meteorological conditions for cloud seeding using aircraft over the Korean Peninsula. The weather conditions were analyzed using various data sources such as a weather chart, upper air observation, aircraft observation, and a numerical model for cloud seeding experiments conducted from 2018 to 2019 by the National Institute of Meteorological Sciences, Korea Meteorological Administration. Cloud seeding experiments were performed in the seasons of autumn (37.0%) and winter (40.7%) in the West Sea and Gangwon-do. Silver iodide (70.4%) and calcium chloride (29.6%) were used as cloud seeding materials for the experiments. The cloud seeding experiments used silver iodide in cold clouds. Aircraft observation revealed relatively low temperatures, low liquid water content, and strong wind speeds in clouds with a weak updraft. In warm clouds, the cloud seeding experiments used calcium chloride. Observations included relatively high temperatures, high liquid water content, and weak wind speeds in clouds with a weak updraft. Based upon these results, we determined the comprehensive meteorological conditions for cloud seeding experiments using aircraft over the Korean Peninsula. The understanding of optimal weather conditions for cloud seeding gained from this study provide information critical for performing successful cloud seeding and rain enhancement.

• 천문학회보
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• 제44권2호
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• pp.68.1-68.1
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• 2019

Turbulence plays a crucial role in controlling star formation as it produces density fluctuation as well as non-thermal pressure against gravity. Therefore, turbulence controls the mode and tempo of star formation. However, despite a plenty of previous studies, the properties of turbulence remain poorly understood. As part of the Taeduk Radio Astronomy Observatory (TRAO) Key Science Program (KSP), "mapping Turbulent properties In star-forming MolEcular clouds down to the Sonic scale (TIMES; PI: Jeong-Eun Lee)", we mapped the Orion A and the Ophiuchus clouds, in three sets of lines (13CO 1-0/C18O 1-0, HCN 1-0/HCO+ 1-0, and CS 2-1/N2H+ 1-0) with a high-velocity resolution (~0.1 km/s) using the TRAO 14-m telescope. The mean Trms for the observed maps are less than 0.25 K, and all these maps show uniform Trms values throughout the observed area. These homogeneous and high signal-to-noise ratio data provide the best chance to probe the nature of turbulence in two different star-forming clouds, the Orion A and Ophiuchus clouds. We present comparisons between the line intensities of different molecular tracers as well as the results of a Principal Component Analysis (PCA).

• International Journal of Computer Science & Network Security
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• 제24권6호
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• pp.207-215
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• 2024

Cloud computing is now used by most companies, business centres and academic institutions to embrace new computer technology. Cloud Service Providers (CSPs) are limited to certain services, missing some of the assets requested by their customers, it means that different clouds need to interconnect to share resources and interoperate between them. The clouds may be interconnected in different characteristics and systems, and the network may be vulnerable to volatility or interference. While information technology and cloud computing are also advancing to accommodate the growing worldwide application, criminals use cyberspace to perform cybercrimes. Cloud services deployment is becoming highly prone to threats and intrusions. The unauthorised access or destruction of records yields significant catastrophic losses to organisations or agencies. Human intervention and Physical devices are not enough for protection and monitoring of cloud services; therefore, there is a need for more efficient design for cyber defence that is adaptable, flexible, robust and able to detect dangerous cybercrime such as a Denial of Service (DOS) and Distributed Denial of Service (DDOS) in heterogeneous cloud computing platforms and make essential real-time decisions for forensic investigation. This paper aims to develop a framework for digital forensic for the detection of cybercrime in a joined heterogeneous cloud setup. We developed a Digital Forensics model in this paper that can function in heterogeneous joint clouds. We used Unified Modeling Language (UML) specifically activity diagram in designing the proposed framework, then for deployment, we used an architectural modelling system in developing a framework. We developed an activity diagram that can accommodate the variability and complexities of the clouds when handling inter-cloud resources.

• International Journal of CAD/CAM
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• 제5권1호
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• pp.19-27
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• 2005

As three-dimensional range scanners make large point clouds a more common initial representation of real world objects, a need arises for algorithms that can efficiently process point sets. In this paper, we present a method for extracting smooth surfaces from dense point clouds. Given an unorganized set of points in space as input, our algorithm first uses principal component analysis to estimate the surface variation at each point. After defining conditions for determining the geometric compatibility of a point and a surface, we examine the points in order of increasing surface variation to find points whose neighborhoods can be closely approximated by a single surface. These neighborhoods become seed regions for region growing. The region growing step clusters points that are geometrically compatible with the approximating surface and refines the surface as the region grows to obtain the best approximation of the largest number of points. When no more points can be added to a region, the algorithm stores the extracted surface. Our algorithm works quickly with little user interaction and requires a fraction of the memory needed for a standard mesh data structure. To demonstrate its usefulness, we show results on large point clouds acquired from real-world objects.

• 천문학회지
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• 제38권2호
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• pp.253-256
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• 2005

We have constructed the Mount Fuji submillimeter-wave telescope at Nishiyasugawara (alt. 3725 m) near the summit of Mt. Fuji (alt. 3774 m). Thanks to the excellent condition of Mt. Fuji, we have successfully carried out the [CI] survey toward more than 40 square degrees of sky, including qrion MC, Taurus MC, Rosetta MC, DR 15, DR 21, NGC 1333, NGC 2264, W 3, W 44, W 51, L 134, p-Oph. Our [CI] survey have revealed that the [CI] 492 GHz emission widely extends to the molecular clouds. The spatial and velocity structures of the [CI] 492 GHz emission resemble those of 13CO J=l-0 in many molecular clouds, implying that [CI] 492 GHz and $^{13}CO$ J=1-0 are emitted from the same gas. The column density of $C^o$ linearly correlates with that of CO up to high Av, suggesting that $C^o$ exist in the deep interior of molecular clouds. In several regions, we have found that the distributions of $C^o$ and CO are different from each other. The $C^o$-rich area is found in the Hieles' cloud 2. The C+/CO/$C^o$ configuration is found in DR 15, p-Oph, M 17, Orion KL, and NGC 1333. These results indicate that an origin of $C^o$ is unrelated with the photodissociation process. We discuss the observed $C^o$ distributions in relation to the non-equilibrium chemistry.

• 천문학회지
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• 제30권1호
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• pp.71-81
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• 1997

We have studied the IR properties of molecular clouds in the region of the supershell GS234-02 using IRAS and COBE data. The mean values of dust color temperature and optical depth at $240{\mu}m$ are derived to be $15.4\pm1.5K\; and\;9.0\pm5.7\times10^{-4}$, respectively, which agree well with those determined by Sodroski et al.(1994) for the outer Galaxy. Mean IRAS colors, $R_{12}/100= 0.074,\; R_{25}/100= 0.052,\; R_{60/100}= 0.219$, indicate that the abundance of PAHs is enhanced but other particles are nearly the same as those of the solar neighborhood. We found the anticorrelation between $R_{100/140}\;and\;R_{140/240}$. It cannot be explained by the thermal emission of traditional big grains. The anticorrelation implies that, at high ISRF, $T_{100/140}$ underestimates the equilibrium temperature, while $T_{140/240}$ overestimates it and, at low ISRF, vice versa. Therefore we propose to use the intensity ratio, $R_{100/240}$ as a dust thermometer.

• 대기
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• 제20권4호
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• pp.427-436
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• 2010

The single-scattering optical properties of ice crystals in cirrus clouds by the aircraft measurement data were investigated, and the radiative equilibrium temperatures and radiative fluxes were calculated and analyzed by radiative convective model with the variations of ice crystal habits and sizes in cirrus clouds. The homogeneous cloud is assumed to be in the layer 200~260 hPa with an ice crystal content of $10gm^{-2}$ for the flux calculation. The profiles of temperature, humidity, and ozone typical of mid-latitude summer are used. The surface albedo is assumed to be 0.2 for all spectral bands and the cosine of solar zenith angles is 0.5. The result of radiative equilibrium temperature at surface was less than surface temperature of the standard atmosphere data in case of smaller effective ice crystal size and larger optical thickness. The column, aggregation and plate in 6 ice crystal habits were the most effective in positive greenhouse effect and bullet-4 was the worst in it. At the surface, the maximum difference of equilibrium temperature by 6 kinds of ice crystal habits were about 3~15 K with 30 sample aircraft measurement data.

• 대기
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• 제20권4호
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• pp.519-530
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• 2010

In this paper we review current research on Atmospheric Brown Clouds (ABCs) with lightweight Unmanned Aerial Vehicles (UAVs) and miniaturized instruments. The UAV technology for in-situ measurements, including aerosol concentration, aerosol size distribution, aerosol absorption, cloud drop size distribution, solar radiation fluxes (visible and broadband), and spectral radiative fluxes, is a leading-edge technology for cost-effective atmospheric sounding, which can fill the gap between the ground measurement and satellite observation. The first experimental observation with UAVs in Korea, Cheju ABC Plume Monsoon Experiment (CAPMEX), conducted during summer 2008 revealed that the Beijing plumes exerted a strong positive influence on the net warming and fossil-fuel-dominated black-carbon plumes were approximately 100% more efficient warming agents than biomass-burning-dominated plumes. Long-term sustainable routine UAV measurements will eventually provide truly three-dimensional data of ABCs, which is necessary for the better understanding of their climate impacts and for the improvement of numerical models for air pollution, weather forecast and climate change.

• 로봇학회논문지
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• 제10권1호
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.