• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.62-77
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• 2019

Open Data Cube(ODC) has been emerging and developing as the open source platform in the Committee on Earth Observation Satellites(CEOS) for the Global Earth Observation System of Systems(GEOSS) deployed by the Group on Earth Observations (GEO), ODC can be applied to the deployment of scalable and large amounts of free and open satellite images in a cloud computing environment, and ODC-based country or regional application services have been provided for public users on the high performance. This study first summarizes the status of ODC, and then presents concepts and some considering points for linking this platform with Korea Multi-Purpose Satellite (KOMPSAT) images. For the reference, the main contents of ODC with the Google Earth Engine(GEE) were compared. Application procedures of KOMPSAT satellite image to implement ODC service were explained, and an intermediate process related to data ingestion using actual data was demonstrated. As well, it suggested some practical schemes to utilize KOMPSAT satellite images for the ODC application service from the perspective of open data licensing. Policy and technical products for KOMPSAT images to ODC are expected to provide important references for GEOSS in GEO to apply new satellite images of other countries and organizations in the future.

• International journal of advanced smart convergence
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• v.6 no.4
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• pp.88-95
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• 2017

The conventional scan methods are based on a laser scanner and a depth camera, which requires high cost and complicated post-processing. Whereas in photometric scanning method, the 3D modeling data is acquired through multi-view images. This is advantageous compared to the other methods. The quality of a photometric 3D model depends on the environmental conditions or the object characteristics, but the quality is lower as compared to other methods. Therefore, various methods for improving the quality of photometric scanning are being studied. In this paper, we aim to investigate the effect of illumination conditions on the quality of photometric scanning data. To do this, 'Moai' statue is 3D printed with a size of $600(H){\times}1,000(V){\times}600(D)$. The printed object is photographed under the hard light and soft light environments. We obtained the modeling data by photometric scanning method and compared it with the ground truth of 'Moai'. The 'Point-to-Point' method used to analyseanalyze the modeling data using open source tool 'CloudCompare'. As a result of comparison, it is confirmed that the standard deviation value of the 3D model generated under the soft light is 0.090686 and the standard deviation value of the 3D model generated under the hard light is 0.039954. This proves that the higher quality 3D modeling data can be obtained in a hard light environment. The results of this paper are expected to be applied for the acquisition of high-quality data.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.113-124
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• 2015

Unlike structured data which are gathered and saved in a predefined structure, unstructured text data which are mostly written in natural language have larger applications recently due to the emergence of web 2.0. Text mining is one of the most important big data analysis techniques that extracts meaningful information in the text because it has not only increased in the amount of text data but also human being's emotion is expressed directly. In this study, we used R program, an open source software for statistical analysis, and studied algorithm implementation to conduct analyses (such as Frequency Analysis, Cluster Analysis, Word Cloud, Social Network Analysis). Especially, to focus on our research scope, we used keyword extract method based on a Data Dictionary. By applying in real cases, we could find that R is very useful as a statistical analysis software working on variety of OS and with other languages interface.

• KIISE Transactions on Computing Practices
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• v.22 no.3
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• pp.151-156
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• 2016

Cloud computing systems require a huge number of storage servers due to the growing implications of power bills, carbon emissions, and logistics of data centers. These considerations have motivated researchers to improve the energy efficiency of storage servers. Most servers use a lot of power irrespective of the amount of computing that they are doing, and one important goal is to redesign servers to be power-proportional. However, Research on large-scale storage systems is hampered by their cost. It is therefore desirable to develop a scalable test-bed for evaluating the power consumption of large-scale storage systems. We are building on open-source projects to construct a test-bed which will contribute to the assessment of power consumption in tiered storage systems. Integrating the cloud application platform can easily extend the proposed testbed laying a foundation for the design and evaluation of low-power storage servers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.1-7
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• 2013

Big data management is becoming increasingly important in both industry and academia of information science community. One of the important categories of big data generated from software systems is log data. Log data is generally used for better services in various service providers and can also be used as information for qualification. This paper presents a big data management architecture specialized for log data. Specifically, it provides the aggregation of log messages sent from multiple clients and provides intelligent functionalities such as analyzing log data. The proposed architecture supports an asynchronous process in client-server architectures to prevent the potential bottleneck of accessing data. Accordingly, it does not affect the client performance although using remote data store. We implement the proposed architecture and show that it works well for processing big log data. All components are implemented based on open source software and the developed prototypes are now publicly available.

• Journal of The Korean Astronomical Society
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• v.37 no.4
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• pp.285-288
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• 2004

Near-infrared imaging photometry supplemented by optical spectroscopy and narrow-band imaging of the H II region Sh 2-128 and its environment are presented. This region contains a developed H II region and the neighboring compact H II region S 128N associated with a pair of water maser sources. Midway between these, the core of a CO cloud is located. The principal ionizing source of Sh 2-128 is an 07 star close to its center. A new spectroscopic distance of 9.4 kpc is derived, very similar to the kinematic distance to the nebula. This implies a galactocentric distance of 13.5 kpc and z = 550 pc. The region is optically thin with abundances close to those predicted by galactocentric gradients. The $JHK_s$ images show that S 128N contains several infrared point sources and nebular emission knots with large near-infrared excesses. One of the three red Ks knots coincides with the compact H II region. A few of the infrared-excess objects are close to known mid- and far-infrared emission peaks. Star counts in J and $K_s$ show the presence of a small cluster of B-type stars, mainly associated with S 128N. The $JHK_s$ photometric properties together with the characteristics of the other objects in the vicinity suggest that Sh 2-128 and S 128N constitute a single complex formed from the same molecular cloud, with ages ${\~}10^6$ and < $3 {\times} 10^5$ years respectively. No molecular hydrogen emission was detected at 2.12 ${\mu}m$. The origin of this remote star forming region is an open problem.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.913-921
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• 2012

The current PC-based desktop environment is being converted into server-based virtual desktop environment due to security, mobility, and low upgrade cost. In this paper, a desktop virtualization system is implemented using an open source-based cloud computing platform and hypervisor. The implemented system is applied to the virtualziation of computer in university. In order to reduce the image transfer time, we propose a solution using HDFS. In addition, an image management structure needed for desktop virtualization is designed and implemented, and applied to a real computer lab which accommodates 30 PCs. The performance of the proposed system is evaluated in various aspects including implementation cost, power saving rate, reduction rate of license cost, and management cost. The experimental results showed that the proposed system considerably reduced the image transfer time for desktop service.

• Smart Media Journal
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• v.6 no.1
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• pp.9-15
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• 2017

The trends in ICT are concentrated in IoT, Bigdata, and Cloud Computing. These mega-trends do not operate independently, and mass storage technology is essential as large computing technology is needed in the background to support them. In order to evaluate the performance of high-capacity storage based on open source Ceph, we carry out the demonstration test of Abyss Storage with domestic and overseas sites using educational network KOREN. In addition, storage media and network bonding are tested to evaluate the performance of the storage itself. Although there is a substantial difference in aspect of the physical speed among storage medias, there is no significant performance difference in the storage media test performed. As a solution to this problem, we could get performance improvement through network acceleration. In addition, we conducted actual performance test of Abyss Storage internal and external network by connecting domestic and overseas sites using KOREN network.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.1-9
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• 2023

In this paper, we identify the factors that hinder the application of quantum computing technology to solve meaningful real-world problems, and suggest related research trends and directions. To this end, we summarize the basic knowledge of quantum mechanics from the perspective of computer science, which is necessary to understand the difficulties in applying quantum computing technology, and analyze the currently commercialized quantum computers and quantum programming layers from the literature. Through an analysis of the current status and utilization of cloud-based commercial quantum computing services, we identify four factors that currently hinder the practical application of quantum computing: high barriers to entry for quantum computer programming, constraints on noisy intermediate-scale quantum computers, a still-growing open source ecosystem, and difficulties in simulating realistic problem sizes, and suggest trends and directions for related research. In doing so, it is expected to contribute to laying the groundwork for practical applications of quantum computing technology.

• Smart Media Journal
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• v.11 no.2
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• pp.70-76
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• 2022

IoT application development using a cloud server causes problems such as data transmission and reception delay, network traffic, and cost for real-time processing support in network connected hardware. To solve this problem, edge cloud-based platforms can use neuromorphic hardware to enable fast data transfer. In this paper, we propose a model optimization method for supporting spiking neural networks on FPGA hardware. We focused on auto-adjusting network model parameters optimized for neuromorphic hardware. The proposed method performs optimization to show higher performance based on user requirements for accuracy. As a result of performance analysis, it satisfies all requirements of accuracy and showed higher performance in terms of expected execution time, unlike the naive method supported by the existing open source framework.