• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.287-294
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• 2022

The purpose of this study is to find out consumers' perceptions of "metaverse," a newly spotlighted technology, through big data analysis as a non-face-to-face society continues after the outbreak of COVID-19. This study conducted a big data analysis using text mining to analyze consumers' perceptions of metaverse before and after COVID-19. The top 30 keywords were extracted through word purification, and visualization was performed through network analysis and concor analysis between each keyword based on this. As a result of the analysis, it was confirmed that the non-face-to-face society continued and metaverse emerged as a trend. Previously, metaverse was focused on textual data such as SNS as a part of life logging, but after that, it began to pay attention to virtual reality space, creating many platforms and expanding industries. The limitation of this study is that since data was collected through the search frequency of portal sites, anonymity was guaranteed, so demographic characteristics were not reflected when data was collected.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.176-186
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• 2017

The subject of this study is to search for the improvements or solutions of problems in the field of the performing arts that relies on public support and faces economic difficulties. Considering the value chain for the performing arts industry is comprised of Creation-Distribution-Consumption is isolated relatively, this study aims to identify improvements for the distribution system. By examining the government's theater-oriented support policy, this study details methods of improvements in the distribution sector of the performing arts industry. Following the study of the performing arts industry and its value chain, the study analyzes the structure, factors and the present state in the performing arts industry, as well as the volume and type of public sector support for distribution. The study concludes by suggestingmagnifying government's Distribution sector supporting that was limited by only 2.7% in 2014, and fostering and specialty improvement of circulation agents such as production agencies.In addition, supporting distribution diversification, namely the extension of platforms like the Visualization of Performing Arts, is needed. These alternatives will contribute to balanced development and coevolution of each sector which comprises the performing arts industry's value chain.

• Nuclear Engineering and Technology
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• v.40 no.6
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• pp.451-458
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• 2008

After more than 10 years construction, KSTAR (Korea Superconducting Tokamak Advanced Research) had finally completed its assembly in June 2007, and then achieved the goal of first-plasma in July 2008 through the four month's commissioning. KSTAR was constructed with fully superconducting magnets with material of $Nb_3Sn$ and NbTi, and their operation temperatures are maintained below 4.5K by the help of Helium Refrigerator System. During the first-plasma operation, plasmas of maximum current of 133kA and maximum pulse width of 865ms were obtained. The KSTAR Integrated Control System (KICS) has successfully fulfilled its missions of surveillance, device operation, machine protection interlock, and data acquisition and management. These and more were all KSTAR commissioning requirements. For reliable and safe operation of KSTAR, 17 local control systems were developed. Those systems must be integrated into the logically single control system, and operate regardless of their platforms and location installed. In order to meet these requirements, KICS was developed as a network-based distributed system and adopted a new framework, named as EPICS (Experimental Physics and Industrial Control System). Also, KICS has some features in KSTAR operation. It performs not only 24 hour continuous plant operation, but the shot-based real-time feedback control by exchanging the initiatives of operation between a central controller and a plasma control system in accordance with the operation sequence. For the diagnosis and analysis of plasma, 11 types of diagnostic system were implemented in KSTAR, and the acquired data from them were archived using MDSpius (Model Driven System), which is widely used in data management of fusion control systems. This paper will cover the design and implementation of the KSTAR integrated control system and the data management and visualization systems. Commissioning results will be introduced in brief.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.71-89
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• 2019

In order to come up with satisfying product and improvement, firms use traditional marketing research methods to obtain consumers' opinions and further try to reflect them. Recently, gathering data from consumer communication platforms like internet and SNS has become popular methods. Meanwhile, with the development of information technology, mobile companies are launching new digital products for children to protect them from harmful content and provide them with necessary functions and information. Among these digital products, Kids Phone, which is a wearable device with safe functions that enable parents to learn childern's location. Kids phone is relatively cheaper and simpler than smartphone but it is noted that there are several problems such as some useless functions and frequent breakdowns. This study analyzes the reviews of Kids phones from domestic mobile companies, identifies the characteristics, strengths and weaknesses of the products, proposes improvement methods strategies for devices and services through SNS consumer analysis. In order to do that customer review data from online shopping malls was gathered and was further analyzed through text mining methods such as TF/IDF, Sentiment Analysis, and network analysis. Customer review data was gathered through crawling Online shopping Mall and Naver Blog/$Caf\acute{e}$. Data analysis and visualization was done using 'R', 'Textom', and 'Python'. Such analysis allowed us to figure out main issues and recent trends regarding kids phones and to suggest possible service improvement strategies based on sentiment analysis.

• Journal of Popular Narrative
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• v.25 no.4
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• pp.9-43
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• 2019

Web novels are one of the most actively adapted genre novels under a new medium called the Internet. Research on cultural content implemented on top of digital media is naturally closely related to environmental changes in digital media. The same goes for Web novels sparked by the identity of Web platforms. Especially in the case of web novels, the platform itself that provides them has triggered direct changes in genre code and reading patterns. From this perspective, this thesis wanted to examine the formation process and strategic features of web novels, which became content and products on the web platform environment. First of all, through the formation process ranging from communication novels to Internet novels and web novels, I arranged the transition to digital media and the change of genre novel market. This was an attempt to extract that Web novels not only have continuity as genre novels, but also have a turning point as digital content. Web novels are digital content that internalizes the values of the Web 2.0 era. It should also be a core product that grows the pie in the market in its own right. This paper noted that web novels are content that embodies these consumption values. So this thesis considered about what is the visualization and commercialization strategy of the web-based novels that is currently formed, and what is the current status of the web-based romance novels as the content and the product that is driving OSMU most actively in the process of commercialization. Through this process, I found that the greatest characteristic of web novels as genre novels that have evolved into digital content is their division and crack of genre.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.79-93
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• 2021

The size of the domestic art market has increased 21.9% over the past five years as of 2018 to KRW 448.2 billion and the number of transactions has also increased 31.6% to 39,367 points maintaining growth for the fifth consecutive year. Art distribution platforms are diversifying from galleries and auction-style offline to online auctions. The art market consists of three areas: production (creation), distribution (trade), and consumption (buying) of works and as the perception of artistic value as well as economic value spreads interest is also increasing as a means of investment. Consumers who purchase works and think of them as a means of investment technology have an increased need for objective information about their works, but there is a limit to collecting and analyzing objective and reliable statistics because information provision in the art market distribution area is closed and unbalanced. This paper identifies objective and reliable art distribution status and status through big data collection and structured and unstructured data analysis on art market distribution areas. Through this, we want to implement a system that can objectively provide analysis of authors in the current market. This study collected author information from art distribution sites and calculated the frequency of associated words by writer by collecting and analyzing the author's articles from Maeil Business, a daily newspaper. It aims to provide consumers with objective and reliable information.

• Korean Journal of Remote Sensing
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• v.36 no.2_2
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• pp.379-399
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• 2020

The detection of illegal ship is one of the key factors in building a marine surveillance system. Effective marine surveillance requires the means for continuous monitoring over a wide area. In this study, the possibility of ship detection monitoring based on satellite SAR, HF radar, UAV and AIS integration was investigated. Considering the characteristics of time and spatial resolution for each platform, the ship monitoring scenario consisted of a regular surveillance system using HFR data and AIS data, and an event monitoring system using satellites and UAVs. The regular surveillance system still has limitations in detecting a small ship and accuracy due to the low spatial resolution of HF radar data. However, the event monitoring system using satellite SAR data effectively detects illegal ships using AIS data, and the ship speed and heading direction estimated from SAR images or ship tracking information using HF radar data can be used as the main information for the transition to UAV monitoring. For the validation of monitoring scenario, a comprehensive field experiment was conducted from June 25 to June 26, 2019, at the west side of Hongwon Port in Seocheon. KOMPSAT-5 SAR images, UAV data, HF radar data and AIS data were successfully collected and analyzed by applying each developed algorithm. The developed system will be the basis for the regular and event ship monitoring scenarios as well as the visualization of data and analysis results collected from multiple platforms.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Korean Journal of Heritage: History & Science
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• v.46 no.2
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• pp.46-69
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• 2013

The results of study on the meaning landscape and environmental design techniques of the Byulup, Yoohoedang garden(Hageowon) based on the story in the collection of Kwon Yi-jin (Yoohoedangjip, 有懷堂集), are as below. First, Yoohoedang Kwon Yi-jin (有懷堂 權以鎭 : 1668~1734) constructed a Byulup garden consisting of ancestor grave, Byulup, garden, and a school, through 3 steps for 20 years in the back hill area of Moosoo-dong village, south of Mountain Bomun in Daejeon. In other words, he built the Byulup(別業, Yoohoedang) by placing his father's grave in the back hill of the village, and then constructed Yoegeongam(餘慶菴) and Geoupjae(居業齋) for protection of the pond(Napoji, 納汚池), garden(Banhwanwon, 盤桓園), and ancestor graves, and descendants' studying in the middle stage. He built an extension in Yoohoedang and finally completed the large-size garden (Hageowon) by extending the east area. Second, in terms of geomancy sense, Yoohoedang Byulup located in Moosoo-dong village area is the representative example including all space elements such as main living house (the head family house of Andong Kwon family), Byulup (Yoohoedang), ancestor graves, Hagoewon (garden) and Yoegeongam (cemetery management and school) which byulup type Byulseo should be equipped with. Thirdly, there are various meaning landscape elements combining the value system of Confucianism, Buddhism and Taoism value, including; (1) remembering parents, (2) harmonious family, (3) integrity, (4) virtue, (5) noble personality, (6) good luck, (7) hermit life, (8) family prosperity and learning development, (9) grace from ancestors, (10) fairyland, (11) guarding ancestor graves, and (12) living ever-young. Fourth, after he arranged ancestor graveyard in the back of the village, he used surrounding natural landscapes to construct Hagoewon garden with water garden consisting of 4 mountain streams and 3 ponds for 13 years, and finally completed a beautiful fairyland with 5 platforms, 3 bamboo forests, as well as the Seokgasan(石假山, artificial hill). Fifth, he adopted landscape plantation (28 kinds; pine, maple, royal azalea, azalea, persimmon tree, bamboo, willow, pomegranate tree, rose, chinensis, chaenomeles speciosa, Japanese azalea, peach tree, lotus, chrysanthemum, peony, and Paeonia suffruticosa, etc.) to apply romance from poetic affection, symbol and ideal from personification, as well as plantation plan considering seasonal landscapes. Landscape rocks were used by intact use of natural rocks, connecting with water elements, garden ornament method using Seokyeonji and flower steps, and mountain Seokga method showing the essence of landscape meanings. In addition, waterscape are characterized by active use of water considering natural streams and physio-graphic condition (eastern valley), ecological corridor role that rhythmically connects each space of the garden and waterways following routes, landscape meaning introduction connecting 'gaining knowledge by the study of things' values including Hwalsoodam(活水潭, pond), Mongjeong(蒙井, spring), Hosoo(濠水, stream), and Boksoo(?水, stream), and sensuous experience space construction with auditory and visualization using properties of landscape matters.