• Journal of KIBIM
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• v.6 no.3
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• pp.49-56
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• 2016

As project opportunities for the Architecture, Engineering and Construction (AEC) industry have grown more complex and larger, the utilization of Building Information Modeling (BIM) technologies for three-dimensional (3D) design and simulation practices has been increasing significantly; the typical applications of the BIM technologies include clash detection and design alternative based on 3D planning, which have been expanded over to the technology of construction management in the AEC industry for virtual design and construction. As for now, commercial BIM software has been operated under a single-user environment, which is why initial costs for its introduction are very high. Cloud computing, one of the most promising next-generation Internet technologies, enables simple Internet devices to use services and resources provided with BIM software. Recently in Korea, studies to link between BIM and cloud computing technologies have been directed toward saving costs to build BIM-related infrastructure, and providing various BIM services for small- and medium-sized enterprises (SMEs). This study addressed development of the usage metering functions of BIM software under cloud computing architecture in order to archive and use BIM data and create an optimal revenue structure so that the BIM services may grow spontaneously, considering a demand for cloud resources. For the reason, we surveyed relevant cases, and then analyzed needs and requirements from AEC industry. Based on the relevant cases, customizing for cloud BIM and design for the development was performed. We also surveyed any related-law to support cloud computing-based BIM service. Finally, we proposed herein how to optimally design and develop the usage metering functions of cloud BIM software.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.282-304
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• 2014

Each cloud service has numerous owners and tenants, so it is necessary to construct a privacy preserving identity management and access control mechanism for cloud computing. On one hand, cloud service providers (CSP) depend on tenant's identity information to enforce appropriate access control so that cloud resources are only accessed by the authorized tenants who are willing to pay. On the other hand, tenants wish to protect their personalized service access patterns, identity privacy information and accessing newfangled cloud services by on-demand ways within the scope of their permissions. There are many identity authentication and access control schemes to address these challenges to some degree, however, there are still some limitations. In this paper, we propose a new comprehensive approach, called Privacy pReserving Identity and Access Management scheme, referred to as PRIAM, which is able to satisfy all the desirable security requirements in cloud computing. The main contributions of the proposed PRIAM scheme are threefold. First, it leverages blind signature and hash chain to protect tenant's identity privacy and implement secure mutual authentication. Second, it employs the service-level agreements to provide flexible and on-demand access control for both tenants and cloud services. Third, it makes use of the BAN logic to formally verify the correctness of the proposed protocols. As a result, our proposed PRIAM scheme is suitable to cloud computing thanks to its simplicity, correctness, low overhead, and efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2952-2971
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• 2016

Outsourcing jobs to a public cloud is a cost-effective way to address the problem of satisfying the peak resource demand when the local cloud has insufficient resources. In this paper, we studied the management of deadline-constrained bag-of-tasks jobs on hybrid clouds. We presented a binary nonlinear programming (BNP) problem to model the hybrid cloud management which minimizes rent cost from the public cloud while completes the jobs within their respective deadlines. To solve this BNP problem in polynomial time, we proposed a heuristic algorithm. The main idea is assigning the task closest to its deadline to current core until the core cannot finish any task within its deadline. When there is no available core, the algorithm adds an available physical machine (PM) with most capacity or rents a new virtual machine (VM) with highest cost-performance ratio. As there may be a workload imbalance between/among cores on a PM/VM after task assigning, we propose a task reassigning algorithm to balance them. Extensive experimental results show that our heuristic algorithm saves 16.2%-76% rent cost and improves 47.3%-182.8% resource utilizations satisfying deadline constraints, compared with first fit decreasing algorithm, and that our task reassigning algorithm improves the makespan of tasks up to 47.6%.

• Journal of the Korean earth science society
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• v.40 no.4
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• pp.406-413
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• 2019

Red-Green-Blue (RGB) imagery techniques are useful for both forecasters and public users because they are intuitively understood, have advantageous visualization, and do not lose observational information. This study presents a novel RGB convective cloud product and its application to tropical cyclone analysis using Communication, Oceanography, and Meteorology (COMS) satellite observations. The RGB convective cloud product was developed using the brightness temperature differences between WV ($6.75{\mu}m$) and IR1 ($10.8{\mu}m$), and IR2 ($12.0{\mu}m$) and IR1 ($10.8{\mu}m$) as well as the brightness temperature in the IR1 bands of the COMS, with the threshold values estimated from the Korea Meteorological Administration (KMA) radar observations and the EUMETSAT RGB recipe. To verify the accuracy of the convective cloud RGB product, the product was applied to the center positions analysis of two typhoons in 2013. Thus, the convective cloud RGB product threshold values were estimated for WV-IR1 (-20 K to 15 K), IR1 (210 K to 300 K), and IR1-IR2 (-4 K to 2 K). The product application in typhoon analysis shows relatively low bias and root mean square errors (RMSE)s of 23 and 28 km for DANAS in 2013, and 17 and 22 km for FRANCISCO in 2013, as compared to the best tracks data from the Regional Specialized Meteorological Center (RSMC) in Tokyo. Consequently, our proposed RGB convective cloud product has the advantages of high accuracy and excellent visualization for a variety of meteorological applications.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.60-66
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• 2024

Host's data during transmission. Data tempering results in loss of host's sensitive information, which includes number of VM, storage availability, and other information. In the distributed cloud environment, each server (computing server (CS)) configured with Local Resource Monitors (LRMs) which runs independently and performs Virtual Machine (VM) migrations to nearby servers. Approaches like predictive VM migration [21] [22] by each server considering nearby server's CPU usage, roatative decision making capacity [21] among the servers in distributed cloud environment has been proposed. This approaches usage underlying server's computing power for predicting own server's future resource utilization and nearby server's resource usage computation. It results in running VM and its running application to remain in waiting state for computing power. In order to reduce this, a decentralized decision making hybrid model for VM migration need to be proposed where servers in decentralized cloud receives, future resource usage by analytical computing system and takes decision for migrating VM to its neighbor servers. Host's in the decentralized cloud shares, their detail with peer servers after fixed interval, this results in chance to tempering messages that would be exchanged in between HC and CH. At the same time, it reduces chance of over utilization of peer servers, caused due to compromised host. This paper discusses, an roatative decisive (RD) approach for VM migration among peer computing servers (CS) in decentralized cloud environment, preserving confidentiality and integrity of the host's data. Experimental result shows that, the proposed predictive VM migration approach reduces extra VM migration caused due over utilization of identified servers and reduces number of active servers in greater extent, and ensures confidentiality and integrity of peer host's data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.81-87
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• 2013

In this paper, we propose a music search algorithm for automotive infotainment system. The proposed method extracts fingerprints using the high peaks based on log-spectrum of the music signal, and the extracted music fingerprints store in cloud server applying a hash value. In the cloud server, the most similar music is retrieved by comparing the user's query music with the fingerprints stored in hash table of cloud server. To evaluate the performance of the proposed music search algorithm, we measure an accuracy of the retrieved results according to various length of the query music and measure a retrieval time according to the number of stored music database in hash table.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.42.2-42.2
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• 2017

The Large Magellanic Cloud (LMC) is a unique target to study the detail structures of molecular clouds and star-forming regions, due to its proximity and face-on orientation from us. Most part of the astrophysical subjects for the LMC have been investigated, but the magnetic field is still veiling despite its role in the evolution of the interstellar medium (ISM) and in the main force to influence the star formation process. Measuring polarization of the background stars behind interstellar medium allows us to describe the existence of magnetic fields through the polarization vector map. In this presentation, I introduce the near-infrared polarimetric results for the $39^{\prime}{\times}69^{\prime}$ field of the northeastern region of the LMC and the N159/N160 star-forming complex therein. The polarimetric observations were conducted at IRSF/SIRPOL 1.4 m telescope. These results allow us to examine both the global geometry of the large-scale magnetic field in the northeastern region and the close structure of the magnetic field in the complex. Prominent patterns of polarization vectors mainly follow dust emission features in the mid-infrared bands, which imply that the large-scale magnetic fields are highly involved in the structure of the dust cloud in the LMC. In addition, local magnetic field structures in the N159/N160 star-forming complex are investigated with the comparison between polarization vectors and molecular cloud emissions, suggesting that the magnetic fields are resulted from the sequential formation history of this complex. I propose that ionizing radiation from massive stellar clusters and the expanding bubble of the ionized gas and dust in this complex probably affect the nascent magnetic field structure.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.5
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• pp.29-36
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• 2012

Cloud computing has gained great popularity because users don't need to install any softwares as well as maintain hardwares and service providers also can utilize its resources through virtualization of servers. As workflows feature variableness and servers are heterogenous, efficient scheduling of workflows in cloud computing is important factor in view of responsibility and resource utilization. In this paper, we propose a new workflow scheduling named 2-step scheduling which prioritizes each workflow through its significance degree and allocates resources to workflows through decision table. The goal of this 2-step scheduling is to improve responsibility as well as availability versus cost. Simulation results show that the proposed scheme in contrast of counterparts can improve the responsibility as well as availability of resource.

• Journal of The Korean Astronomical Society
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• v.31 no.2
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• pp.117-125
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• 1998

We have observed the 10-9 transitions of $HC_3N$ and its $^{13}C$ substitutes ($H^{13}CCCN,\;HC^{13}CCN$, and $HCC^{13}CN$), and the vibration ally excited 12-11 ($v_r=1$) $HC_3N$ transition toward the Sgr B2 molecular cloud. The observed $HC_3N$ emission shows an elongated shape around the Principal Cloud ($\~$4.5 pc in R.A. $\times$ 7.4 pc in Decl.). The optically thin $H^{13}CCCN$ line peaks around the (N) core and we derive the total column density $N(H^{13}CCCN) = 4 {\times}10^{13} cm^{-2}$ at this position. Toward the 2' N cloud which shows the peculiar chemistry, the $HC_3N$ lines show enhancements compared to the extended envelope. The shocks of the 2' N may have resulted in the enhancement of $HC_3N$. The hot component of $HC_3N$ is strongly concentrated around the (N) core and its HPW is $\~$0.9 pc in diameter. We derive the lower limit of the abundance ratio $N(HC_3N)/N(H^{13}CCCN)$ to be larger than 40 in most regions except the (M) and (N) cores. The fractionation processes of $^{13}C $at this region may not be as effective as previously reported.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.1-8
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• 2012

Cloud computing has got great popularity in recent times because users can easily access its resources as well as service providers can use efficiently use its resources. By the way, cloud computing are composed of heterogeneous resources and workflows of user application have various characteristics. So, the main goal of this paper is to design new efficient workflow scheduling algorithm, which classifies workflows through their importance degree and allocates resources to each workflow based on QoS metrics such as responsibility, cost and load balancing. Simulation results show that the proposed scheme can improve the responsibility as well as availability of resource.