• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.100-102
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• 1999

We have analyzed AVHRR global data set for obtaining aerosol and cloud microphysical parameters, i. e., optical thickness and size index of particle polydispersions. From the results, it is found that the cloud optical thickness increases with increasing aerosol column number, which seems to be caused mainly by decreasing cloud particle radius, The cloud liquid water path was observed to be relatively constant without a significant dependence on the aerosol number. Further comparison of the satellite results with a general circulation model simulation.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.E2
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• pp.78-88
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• 2006

In order to study the characteristics of cloud, a real-scale experiment for cloud generation was carried out using an extinct vertical mine (430 m height) located in the northeastern Honshu, Japan. The dry particles generated from the three-step concentrations of NaCl solutions were used for cloud generation. The number size distributions of initial dry particles and cloud droplets were monitored by Scanning Mobility Particle Sizer (SMPS) and Forward Scattering Spectrometer Probe (FSSP) at bottom and upper sites of pit, respectively. The polymeric water absorbent film (PWAF) method was employed to measure liquid water content ($W_L$) as a function of droplet size. Moreover the chemical properties of individual droplet replicas were determined by micro-PIXE. The CCN number concentration shows the lognormal form in dependence of the particle size, while the number size distributions of droplets are bimodal showing the peaks around $9{\mu}m$ and $20{\mu}m$ for every case. In comparison to background mineral particles, right shifting of size distribution line for NaCl particles was occurred. When NaCl solutions with three-step different concentrations were neulized, $W_L$ shows the strong droplet size dependence. It varied from $10.0mg\;m^{-3}$ up to $13.6mg\;m^{-3}$ with average $11.6mg\;m^{-3}$. A good relationship between $W_L$ and cloud droplet number concentration was obtained. Both chemical inhomogeneities (mixed components with mineral and C1) and homogeneities (only mineral components or C1) in individual droplet replicas were obviously observed from micro-PIXE elemental images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2914-2935
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• 2016

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.

• Journal of the Korean Society of Combustion
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• v.4 no.2
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• pp.1-10
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• 1999

Pulverized coal is widely used as the source of electrical power generation and industrial processes. Numerical analysis on the transient ignition process of the cloud of pulverized coal particles in various cases is carried out. Particle radius, initial particle temperature, number density are chosen as major parameters that influence the characteristics of ignition and combustion. The result can be summarized as follow. The ignition occurs at the position that is closed to the surface of the cloud. Maximum temperature and velocity appear at ignition point, and the concentrations of gaseous fuel and oxidizer decrease rapidly near the ignition point. The chemical reaction takes place in wider zone as number density and particle radius decrease. The ignition delay is shortest when particle radius is about $50\;{\mu}m$, and tends to be shorter as number density and initial ambient temperature increase.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.68.3-68.3
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• 2019

We present the preliminary results on the formation of star clusters by cloud-cloud collision. For this purpose, we perform sub-parsec scale, radiation-hydrodynamic simulations of giant molecular clouds using a sink particle algorithm. The simulations include photo-ionization, direct radiation pressure, and non-thermal radiation pressure from infrared and Lyman alpha photons. We confirm that radiation feedback from massive stars suppresses accretion onto sink particles. We examine the collision-induced star formation and discuss the possibility on the formation of a globular cluster.

• Korean Journal of Remote Sensing
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• v.29 no.3
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• pp.293-306
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• 2013

Hydrometeor type and Drop Size Distribution (DSD) in cloud are the fundamental properties that may help explain the rain formation processes and determine the parameters of radar meteorology. This study presents a preliminary analysis of hydrometeor types and DSD data of cloud measured with a PARSIVEL (PARticle SIze and VELocity) optical disdrometer at the site of Cloud Physics Observation System (CPOS, $37^{\circ}41^{\prime}N$, $128^{\circ}45^{\prime}E$, 843 m from sea level) in Daegwallyeong mountainside of Korea. The method has been validated by comparing the observed rainfall rates with the computed ones from the fitted distribution, using the physical data such as DSD, terminal velocity, and rain intensity which were measured by a Micro-Rain Radar (MRR) and a PARSIVEL optical disdrometer. The analysis period started in three cases: on rainy days with light rain (15.5 mm), moderate rain (76 mm), and heavy rain (121 mm), from March to November 2007, respectively.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.45-49
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• 2022

The fourth industrial revolution, internet of things, and the expansion of online web services have increased an exponential growth and deployment in the number of cloud data centers (CDC). The cloud is emerging as new paradigm for delivering the Internet-based computing services. Due to the dynamic and non-linear workload and availability of the resources is a critical problem for efficient workload and resource management. In this paper, we propose the particle swarm optimization (PSO) based gated recurrent unit (GRU) neural network for efficient prediction the future value of the CPU and memory usage in the cloud data centers. We investigate the hyper-parameters of the GRU for better model to effectively predict the cloud resources. We use the Google Cluster traces to evaluate the aforementioned PSO-GRU prediction. The experimental shows the effectiveness of the proposed algorithm.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.71-87
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• 2007

In this study, 14 heavy snow events in Yeongdong area which are local phenomena are analyzed using MODIS cloud products provided from NASA/GSFC. The clouds of Yeongdong area at observed at specific time by MODIS are classified into A, B, C Types, based on the characteristic of cloud properties: cloud top temperature, cloud optical thickness, Effective Particle Radius, and Cloud Particle Phase. The analysis of relations between cloud properties and precipitation amount for each cloud type show that there are statistically significant correlations between Cloud Optical Thickness and precipitation amount for both A and B type and also significant correlation is found between Cloud Top Temperature and precipitation amount for A type. However, for C type there is not any significant correlations between cloud properties and precipitation amount. A-type clouds are mainly lower stratus clouds with small-size droplet, which may be formed under the low level cold advection derived synoptically in the East sea. B-type clouds are developed cumuliform clouds, which are closely related to the low pressure center developing over the East sea. On the other hand, C-type clouds are likely multi-layer clouds, which make satellite observation difficult due to covering of high clouds over low level clouds directly related with Yeongdong heavy snow. It is, therefore, concluded that MODIS cloud products may be useful except the multi-layer clouds for understanding the mechanism of heavy snow and estimating the precipitation amount from satellite data in the case of Yeongdong heavy snow.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.48.3-49
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• 2017

Interplanetary space of the solar system contains a large number of dust particles, referred to as Interplanetary Dust Particles (IDPs) cloud complex. They are observable through meteors and zodiacal lights. The relative contribution of possible sources to the IDPs cloud complex was an controversial topic, however, recent research (Yang & Ishiguro, 2015 and references therein) suggested a dominance of cometary origin. In this study, we numerically investigated the orbital evolution of cometary dust particles, with special concerns on different evolutionary tracks and its consequences according to initial orbits, size and particle shape. The effect of dust particle density and initial size-frequency distribution (SFD) were not decisive in total cloud complex mass and mass supply rate, when these physical quantities are confined by observed zodiacal light brightness and dust particle SFD at 1 au. We noticed that, if we assume the existence of fluffy aggregates discovered in the Earth's stratosphere and the coma of 67P/Churyumov-Gerasimenko, the required mass supply rate decreases significantly. We also found out that close encounters with planets (mostly Jupiter) are the dominating factor of the orbital evolution of dust particles, as the result, the lifetime of cometary dust particles are shorter than Poynting-Robertson lifetime (around 250 thousand years). As another consequence of severe close encounters, only a small fraction of cometary dust particles can be transferred into the orbit < 1 au. This effect is significant for large size particles of ${\beta}$ < 0.01. The exceptional cases are dust particles ejected from 2P/Encke and active asteroids. Because they rarely encounter with Jupiter, most dust particles ejected from those objects are governed by Poynting-Robertson effect and well transferred into the orbits of small semimajor axis. In consideration of the above effects, we directly estimated probability of mutual collisions between dust particles and concluded that mutual collisions in the IDPs cloud complex is mostly ignorable, except for the case of large sized particles from active asteroids.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2006.04a
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• pp.55-56
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• 2006

This thesis describes the use of measured aerosol size distributions and size-resolved hygroscopic growth to examine the physical and chemical properties of several particle classes. The primary objective of this work was to investigate the optical and cloud forming properties of a range of ambient aerosol types measured in a number of different locations. The tool used for most of these analyses is a differential mobility analyzer / tandem differential mobility analyzer (DMA / TDMA) system developed in our research group. To collect the data described in two of the chapters of this thesis, an aircraft-based version of the DMA / TDMA was deployed to Japan and California. The data described in two other chapters were conveniently collected during a period when the aerosol of interest came to us. The unique aspect of this analysis is the use of these data to isolate the size distributions of distinct aerosol types in order to quantify their optical and cloud forming properties. I used collected data during the Asian Aerosol Characterization Experiment (ACE-Asia) to examine the composition and homogeneity of a complex aerosol generated in the deserts and urban regions of China and other Asian countries. An aircraft-based tandem differential mobility analyzer was used for the first time during this campaign to examine the size-resolved hygroscopic properties of particles having diameters between 40 and 586 nm. Asian Dust Above Monterey (ADAM-2003) study was designed both to evaluate the degree to which models can predict the long-range transport of Asian dust, and to examine the physical and optical properties of that aged dust upon reaching the California coast. Aerosol size distributions and hygroscopic growth are measured in College Station, TX to investigate the cloud nucleating and optical properties of a biomass burning aerosol generated from fires on the Yucatan Peninsula. Measured aerosol size distributions and size-resolved hygroscopicity and volatility were used to infer critical supersaturation distributions of the distinct particle types that were observed during this period. The predicted CCN concentrations were used in a cloud model to determine the impact of the different aerosol types on the expected cloud droplet concentration. RH-dependent aerosol extinction coefficients are calculated at a wavelength of 550 nm.