• Journal of Conservation Science
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• v.28 no.1
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• pp.87-94
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• 2012

This study was focused on digital restoration and surface depth modeling applying the three-dimensional laser scanning system of the Haeundae Stone Inscription. Firstly, the three-dimensional digital restoration carried out acquiring of point cloud using wide range and precision scanner, thereafter registering, merging, filtering, polygon mesh and surveyed map drawing. In particular, stroke of letters, inscribed depth and definition appearing the precision scanning polygon was outstanding compared with ones of the wide range polygon. The surface depth modeling completed through separation from polygon, establishment of datum axis, selection of datum point, contour mapping and polygon merging. Also, relative inscribed depth (5~17mm) and outline by the depth modeling was well-defined compared with photograph and polygon image of the inscription stone. The digital restoration technology merging wide range and precision scanning restored the total and detailed shape of the Stone Inscription quickly and accurately. In addition, the surface depth modeling visibly showed unclear parts from naked eye and photograph. In the future, various deteriorations and surrounding environment change of the Stone Inscription will be numerically analyze by periodic monitoring.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2641-2654
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• 2014

In the smart media environment, magazine industry has been experiencing a transition to ecosystem of value network, which includes high complexity and ambiguity. Using case study method, this article conducts research on digital convergence, the model of magazine ecosystem and adaptation strategy of global magazine companies. Research findings have it that the way of contents production of global magazines has been based on collaborative production system within communities, expert communities, creative users, media contents companies and magazine platform. The system shows different patterns and characteristics depending on magazine-driven platform, Platform-driven platform or user-driven platform. Collaboration system has been confirmed in various cases: Huffington Post and Zinio which collaborate with media contents companies, Amazon magazines and Bookish with magazine companies, Huffington Post and Wired with expert communities, and Flipboard with creative users and communities. Foreign magazine contents diverge into (paper, electronic, app and web magazine) as they start the lively trades of their contents on the magazine platform. In the area of contents uses, readers employ smart media technology effectively such as cloud computing, artificial intelligence and module individualization, making it possible for the virtuous cycle to remain in the relationship within communities, expert communities and creative users.

• Journal of Korea Multimedia Society
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• v.10 no.2
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• pp.209-217
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• 2007

This paper proposed to a detection scheme of weather information that is a part of CCTV Images Weather Detection System using CCTV images and Temperature, Humidity. The previous Partial Weather Detection System uses how to acquire weather information using images on the Road. In the system the contrast and RGB Values using clear images are gained. This information is distributed a input images to cloud, rain, snow and fog images. That is, this information is compared the snow and the fog images for acquisition more correctness information us ing difference images and binary images. Currently, We use to environment sense system, but we suggest a new Weather Detection Algorithm to detect weather information using CCTV images. Our algorithm is designed simply and systematically to detect and separate special characteristics of images from CCTV images. and using temperature & humidity in formation. This algorithm, there is more complex to implement than how to use DB with high overhead of time and space in the previous system. But our algorithm can be implement with low cost' and can be use the system in real work right away. Also, our algorithm can detect the exact information of weather with adding in formation including temperature, humidity, date, and time. At last, this paper s how the usefulness of our algorithm.

• 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.

• Convergence Security Journal
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• v.18 no.1
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• pp.19-31
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• 2018

As the ICT technologies advance, the unprecedently large amount of digital data is created, transferred, stored, and utilized in every industry. With the data scale extension and the applying technologies advancement, the new services emerging from the use of large scale data make our living more convenient and useful. But the cybercrimes such as data forgery and/or change of data generation time are also increasing. For the data security against the cybercrimes, the technology for data integrity and the time verification are necessary. Today, public key based signature technology is the most commonly used. But a lot of costly system resources and the additional infra to manage the certificates and keys for using it make it impractical to use in the large-scale data environment. In this research, a new and far less system resources consuming signature technology for large scale data, based on the Hash Function and Merkle tree, is introduced. An improved method for processing the distributed hash trees is also suggested to mitigate the disruptions by server failures. The prototype system was implemented, and its performance was evaluated. The results show that the technology can be effectively used in a variety of areas like cloud computing, IoT, big data, fin-tech, etc., which produce a large-scale data.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.401-407
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• 2019

SDN(Softeware Defined Networking) has emerged to address the rapidly growing demand for cloud computing and to support network virtualization services. Therefor many companies and organizations have taken SDN as a next-generation network technology. However, unlike the wired network where the SDN is originally designed, the SDN in the wireless network has a restriction that it can not provide the mobility of the node. In this paper, we extended existing openflow protocol of SDN and developed SDN-based network platform, which enables the SDN controller to manage the radio resources of its network and support the mobility of the nodes. The mobility support function of this paper has the advantage that a node in the network can move using its two or more wireless interfaces by using the radio resource management function of the SDN controller. In order to test the functions implemented in this paper, we measured parameters related to various transmission performance according to various mobile experiments, and compared parameters related to performance using one wireless interface and two interfaces. The SDN-based network platform proposed in this paper is expected to be able to monitor the resources of wireless networks and support the mobility of nodes in the SDN environment.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.1-12
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• 2021

With the recent 4th Industrial Revolution, the growth and value of big data are continuously increasing, and the government is also actively making efforts to open and utilize public data. However, the situation still does not reach the level of demand for public data use by citizens, At this point, it is necessary to identify research trends in the public data field and seek directions for development. In this study, in order to understand the research trends related to public data, the analysis was performed using topic modeling, which is mainly used in text mining techniques. To this end, we collected papers containing keywords of 'Public data' among domestic and foreign research papers (1,437 domestically, 9,607 overseas) and performed topic modeling based on the LDA algorithm, and compared domestic and foreign public data research trends. After analysis, policy implications were presented. Looking at the time series by topic, research in the fields of 'personal information protection', 'public data management', and 'urban environment' has increased in Korea. Overseas, it was confirmed that research in the fields of 'urban policy', 'cell biology', 'deep learning', and 'cloud·security' is active.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.115-126
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• 2021

Central banks communicate with the market through a statement on the direction of monetary policy while implementing monetary policy. The rapid contraction of the global economy due to the recent Covid-19 pandemic could be compared to the crisis situation during the 2008 global financial crisis. In this paper, we analyzed the text data from the monetary policy statements of the Bank of Korea and Fed reflecting monetary policy directions focusing on how they were affected in the face of a global crisis. For analysis, we collected the text data of the two countries' monetary policy direction reports published from October 1999 to September 2020. We examined the semantic features using word cloud and word embedding, and analyzed the trend of the similarity between two countries' documents through a piecewise regression tree model. The visualization result shows that both the Bank of Korea and the US Fed have published the statements with refined words of clear meaning for transparent and effective communication with the market. The analysis of the dissimilarity trend of documents in both countries also shows that there exists a sense of synchronization between them as the rapid changes in the global economic environment affect monetary policy.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.89-92
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• 2020

According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.53-61
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• 2022

Recent years have drawn a great attention to generation MZ and Metaverse, due to 4th industrial revolution and the development of digital environment that blurs the boundary between reality and virtual reality. Generation MZ approaches the information very differently from the existing generations and uses distinguished communication methods. In terms of learning, they have different motivations, types, skills and build relationships differently. Meanwhile, Metaverse is drawing a great attention as a teaching method that fits traits of gen MZ. Thus, the current research aimed to investigate how to increase the use of Metaverse in Educational Technology. Specifically, this research examined the antecedents of popularity of Gather Town, a platform of Metaverse. Big data of news articles have been collected and analyzed using the Bigkinds system provided by Korea Press Foundation. The analysis revealed, first, a rapid increasing trend of media exposure of Gather Town since July 2021. This suggests a greater utilization of Gather Town in the field of education after the COVID-19 pandemic. Second, Word Association Analysis and Word Cloud Analysis showed high weights on education related words such as 'remote', 'university', and 'freshman', while words like 'Metaverse', 'Metaverse platform', 'Covid19', and 'Avatar' were also emphasized. Third, Network Analysis extracted 'COVID19', 'Avatar', 'University student', 'career', 'YouTube' as keywords. The findings also suggest potential value of Gather Town as an educational tool under COVID19 pandemic. Therefore, this research will contribute to the application and utilization of Gather Town in the field of education.