• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.37-42
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• 2017

In order to estimate chaff RCS, we suggest here a novel method using the probability distribution. Normally, a chaff is assumed that it is a thin dipole antenna and the RCS can be calculated by the scattering wave theory. Most of the theoretical methods presented were mainly focusing on a single chaff cloud. In this paper, the RCS calculation was done for two or more chaff clouds and the changes of RCS with azimuth angle were observed. Matlab was used for presenting the probability distribution of chaff clouds and RCS calculation. A more accurate RCS estimation method is suggested by estimating the number of chaffs except the blocked elements.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.50.2-51
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• 2021

Stars form exclusively in cold and dense molecular clouds. To fully understand star formation processes, it is hence a key to investigate how molecular clouds form out of the surrounding diffuse atomic gas. With an aim of shedding light in the process of the atomic-to-molecular transition in the interstellar medium, we analyze Arecibo HI emission and absorption spectral pairs along with TRAO/PMO 12CO(1-0) emission spectra toward 58 lines of sight probing in and around molecular clouds in the solar neighborhood, i.e., Perseus, Taurus, and California. 12CO(1-0) is detected from 19 out of 58 lines of sight, and we report the physical properties of HI (e.g., central velocity, spin temperature, and column density) in the vicinity of CO. Our preliminary results show that the velocity difference between the cold HI (Cold Neutral Medium or CNM) and CO (median ~ 0.7 km/s) is on average more than a factor of two smaller than the velocity difference between the warm HI (Warm Neutral Medium or WNM) and CO (median ~ 1.7 km/s). In addition, we find that the CNM tends to become colder (median spin temperature ~ 43 K) and abundant (median CNM fraction ~ 0.55) as it gets closer to CO. These results hints at the evolution of the CNM in the vicinity of CO, implying a close association between the CNM and molecular gas. Finally, in order to examine the role of HI in the formation of molecular gas, we compare the observed CNM properties to the theoretical model by Bialy & Sternberg (2016), where the HI column density for the HI-to-H2 transition point is predicted as a function of density, metallicity, and UV radiation field. Our comparison shows that while the model reproduces the observations reasonably well on average, the observed CNM components with high column densities are much denser than the model prediction. Several sources of this discrepancy, e.g., missing physical and chemical ingredients in the model such as the multi-phase ISM, non-equilibrium chemistry, and turbulence, will be discussed.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.293-303
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• 2000

The typhoon Jelawat, which was formed over the tropical Pacific ocean on August 1, 2000 and made a landfall over China on August 10, 2000, was observed by Korea Multi-purpose Satellite (KOMPSAT-1) Ocean Scanning Multispectral Imager (OSMI), Tropical Rainfall Measuring Mission (TRMM)/Precipitation Radar(PR) and Quick Scatterometer (QuikSCAT). In spite of discontinuous observation, important mesoscale features of typhoon depending on life cycle were detected prominently. It is possible to distinguish on the OSMI photograph between the eye-wall convection and the stratiform and other convective clouds near the center of typhoon Jelawat. The TRMM/PR observations show quite clearly the eye-wall convection, stratiform regions, and convective bands. Vertical cross section of rainfall in the genesis stage of typhoon Jelawat exhibits circular ring of intense convection surrounding the eye. The mature stage of typhoon Jelawat consists of a strong rotational circulation with clouds which are well organized about a center of low pressure. The OSMI, TRMM/PR and QuikSCAT measurements presented here agree qualitatively with each other and provide a wealth of information on the structure of typhoon Jelawat.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.95-102
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• 2024

In distributed computing, accessible encryption strategy over Auditable data is a hot research field. Be that as it may, most existing system on encoded look and auditable over outsourced cloud information and disregard customized seek goal. Distributed storage space get to manage is imperative for the security of given information, where information security is executed just for the encoded content. It is a smaller amount secure in light of the fact that the Intruder has been endeavored to separate the scrambled records or Information. To determine this issue we have actualize (CBC) figure piece fastening. It is tied in with adding XOR each plaintext piece to the figure content square that was already delivered. We propose a novel heterogeneous structure to evaluate the issue of single-point execution bottleneck and give a more proficient access control plot with a reviewing component. In the interim, in our plan, a CA (Central Authority) is acquainted with create mystery keys for authenticity confirmed clients. Not at all like other multi specialist get to control plots, each of the experts in our plan deals with the entire trait set independently. Keywords: Cloud storage, Access control, Auditing, CBC.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.2
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• pp.135-150
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• 2023

The purpose of this study is to understand the formative characteristics of futuristic virtual fashion revealed in virtual fashion platforms targeting the human body. First, the current status of fashion in the metaverse and futurist fashion were reviewed and summarized by referring to prior research. Next, among the items posted on DRESSX, "futurism" was searched and those resturning a positive result were collected as research subjects. The characteristics were organized into design elements: colors, shapes, materials, and patterns. Futuristic aesthetic characteristics were derived from the characteristics of each design element. As a result, color showed the characteristics of achromatic, vivid and neon colors, multi-color and gradation, multi-color due to reflected light, and color conversion. As for the form, a body-concious look or exaggerated silhouettes, spatial expressions in geometric structures, forms imitating living things, and fluid silhouettes using clouds were prominent. Materials showed the digitization of universal clothing materials, application of industrial materials, use of metal materials, and unrealistic materials. In the patterns, geometric abstract patterns, patterns that reveal the digital world view, and moving fluid patterns appeared. The aesthetic characteristics of futurism in virtual fashion were revealed in four categories: visual dynamics, high-tech sensibility, variability, kineticisim. Visual dynamics were revealed in geometric forms, and intense neon colors. High-tech sensibility was prominent in the use of metal and industrial materials, light emission, and patterns of the digital world view. The expression of multiple colors by reflected light and the change showed the variability of futurism. The use of unrealistic materials, such as clouds and fire and fluid silhouettes expressed kineticisim. The infinite expressiveness of virtual fashion made it possible to actively express the aesthetic characteristics of futurism.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.39-52
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• 2005

In this paper, a registration method is presented to register partial 3D point clouds, acquired from a multi-view camera, for 3D reconstruction of an indoor environment. In general, conventional registration methods require a high computational complexity and much time for registration. Moreover, these methods are not robust for 3D point cloud which has comparatively low precision. To overcome these drawbacks, a projection-based registration method is proposed. First, depth images are refined based on temporal property by excluding 3D points with a large variation, and spatial property by filling up holes referring neighboring 3D points. Second, 3D point clouds acquired from two views are projected onto the same image plane, and two-step integer mapping is applied to enable modified KLT (Kanade-Lucas-Tomasi) to find correspondences. Then, fine registration is carried out through minimizing distance errors based on adaptive search range. Finally, we calculate a final color referring colors of corresponding points and reconstruct an indoor environment by applying the above procedure to consecutive scenes. The proposed method not only reduces computational complexity by searching for correspondences on a 2D image plane, but also enables effective registration even for 3D points which have low precision. Furthermore, only a few color and depth images are needed to reconstruct an indoor environment.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.75-94
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• 2021

The 4th industrial revolution needs a fusion of artificial intelligence, robotics, the Internet of Things (IoT), edge computing, and other technologies. For the fusion of technologies, cloud computing technology can provide flexible and high-performance computing resources so that cloud computing can be the foundation technology of new emerging services. The emerging services become a global-scale, and require much higher performance, availability, and reliability. Public cloud providers already provide global-scale services. However, their services, costs, performance, and policies are different. Enterprises/ developers to come out with a new inter-operable service are experiencing vendor lock-in problems. Therefore, multi-cloud technology that federatively resolves the limitations of single cloud providers is required. We propose a software platform, denoted as Cloud-Barista. Cloud-Barista is a multi-cloud service common platform for federating multiple clouds. It makes multiple cloud services as a single service. We explain the functional architecture of the proposed platform that consists of several frameworks, and then discuss the main design and implementation issues of each framework. To verify the feasibility of our proposal, we show a demonstration which is to create 18 virtual machines on several cloud providers, combine them as a single resource, and manage it.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.143-156
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• 2023

To precisely and reliably analyze the contents of the satellite imagery, recognizing the clouds which are the obstacle to gathering the useful information is essential. In recent times, deep learning yielded satisfactory results in various tasks, so many studies using deep neural networks have been conducted to improve the performance of cloud detection. However, existing methods for cloud detection have the limitation on increasing the performance due to the adopting the network models for semantic image segmentation without modification. To tackle this problem, we introduced the multi-branch neural architecture search to find optimal network structure for cloud detection. Additionally, the proposed method adopts the soft intersection over union (IoU) as loss function to mitigate the disagreement between the loss function and the evaluation metric and uses the various data augmentation methods. The experiments are conducted using the cloud detection dataset acquired by Arirang-3/3A satellite imagery. The experimental results showed that the proposed network which are searched network architecture using cloud dataset is 4% higher than the existing network model which are searched network structure using urban street scenes with regard to the IoU. Also, the experimental results showed that the soft IoU exhibits the best performance on cloud detection among the various loss functions. When comparing the proposed method with the state-of-the-art (SOTA) models in the field of semantic segmentation, the proposed method showed better performance than the SOTA models with regard to the mean IoU and overall accuracy.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.166-173
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• 2020

Multi-view images, which are widely used for providing free-viewpoint services, can enhance the quality of synthetic views when the number of views increases. However, there needs an efficient representation method because of the tremendous amount of data. In this paper, we propose a method for generating point cloud data for the efficient representation of multi-view color and depth images. The proposed method conducts sequential reconstruction of point clouds at each viewpoint as a method of deleting duplicate data. A 3D point of a point cloud is projected to a frame to be reconstructed, and the color and depth of the 3D point is compared with the pixel where it is projected. When the 3D point and the pixel are similar enough, then the pixel is not used for generating a 3D point. In this way, we can reduce the number of reconstructed 3D points. Experimental results show that the propose method generates a point cloud which can generate multi-view images while minimizing the number of 3D points.

• Journal of Energy Engineering
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• v.12 no.4
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• pp.259-266
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• 2003

Load reduction ring (LRR) was installed on the ABB-Atom sparger to reduce the oscillatory loadings due to the air bubble clouds in the water pool in case of safety relief system operations. In order to investigate the effect of LRR on the pressure field, a numerical simulation on the behavior of air bubble clouds discharging into a water pool through a ABB-Atom sparser without LRR was performed by using a commercial thermal hydraulic analysis code, FLUENT 4.5. Among the multi-phase models contained in the code, the VOF (Volume Of Fluid) model was used to simulate the interface of water, air and steam flows. By comparing the analysis results with the previous ones, the load reduction ring has an effect on reducing the oscillatory loads at the wall. It also includes the effect of air mass and inlet boundary conditions of the pipe on the pressure oscillations at the wall.