• Korean Association of Arts Management
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• no.52
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• pp.75-105
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• 2019

In studying culture consumption today, it is essential to understand and analyze the actual visitors' experiences in detail. This is deeply related to the fact that we can utilize subjective experience records that were previously inaccessible as data since plenty of people actually record many performance experiences in the media space such as social media. This study attempts to examine what elements actually consists of people's performance experience based on actual expression of the performance experience that exists online. For this, we collected two types of data. First, we collected posts which required performance recommendation on online platforms such as Jisik-In and Cafes to see how people describe what they want and analyzed data focusing on the modifiers. Results show that people mainly use modifiers that reflect the specific situation of the individual such as companion or age. In addition we analyzed how the experience was described after the show through the review posts of ticket booking site. Results show how expressions are centered around companions, revisit intentions, and viewing experiences besides elements such as story and music, which have been known as main satisfaction elements of performance experience in previous studies. In addition, we discussed the practical implications and limitations of the study as well as the theoretical discussion.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.167-181
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• 2023

This study utilized TEXTOM, a social network analysis program to analyze changes in current tourism behavior after travel restrictions were eased after the outbreak of COVID-19. Data on the keywords 'domestic travel' and 'overseas travel' were collected from blogs, cafes, and news provided by Naver, Google, and Daum. The collection period was set from April to December 2022 when social distancing was lifted, and 2019 and 2020 were each set as one year and compared and analyzed with 2022. A total of 80 key words were extracted through text mining and centrality analysis was performed using NetDraw. Finally, through the CONCOR, the correlated keywords were clustered into 4. As a result of the study, tourism behavior in 2022 shows tourism recovery before the outbreak of COVID-19, segmentation of travel based on each person's preferred theme, prioritization of each country's corona mitigation policy, and then selecting a tourist destination. It is expected to provide basic data for the development of tourism marketing strategies and tourism products for the newly emerging tourism ecosystem after COVID-19.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.97-109
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• 2024

In the field of domestic tourism, tourism trend analysis of tourism consumers, both international tourists and domestic tourists, is essential not only for the Korean tourism market but also for local and governmental tourism policy makers. e will explore the keywords and sentiment analysis on social media to establish a marketing strategy plan and revitalize the domestic tourism industry through communication and information from tourism consumers. This study utilized TEXTOM 6.0 to analyze recent trends in Korean tourism. Data was collected from September 31, 2022, to August 31, 2023, using 'Korean tourism' and 'domestic tourism' as keywords, targeting blogs, cafes, and news provided by Naver, Daum, and Google. Through text mining, 100 key words and TF-IDF were extracted in order of frequency, and then CONCOR analysis and sentiment analysis were conducted. For Korean tourism keywords, words related to tourist destinations, travel companions and behaviors, tourism motivations and experiences, accommodation types, tourist information, and emotional connections ranked high. The results of the CONCOR analysis were categorized into five clusters related to tourist destinations, tourist information, tourist activities/experiences, tourism motivation/content, and inbound related. Finally, the sentiment analysis showed a high level of positive documents and vocabulary. This study analyzes the rapidly changing trends of Korean tourism through text mining on Korean tourism and is expected to provide meaningful data to promote domestic tourism not only for Koreans but also for foreigners visiting Korea.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.511-521
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• 2022

Cloud detection and removal from satellite images is an essential process for topographic observation and analysis. Threshold-based cloud detection techniques show stable performance because they detect using the physical characteristics of clouds, but they have the disadvantage of requiring all channels' images and long computational time. Cloud detection techniques using deep learning, which have been studied recently, show short computational time and excellent performance even using only four or less channel (RGB, NIR) images. In this paper, we confirm the performance dependence of the deep learning network according to the heterogeneous learning dataset with different resolutions. The DeepLabV3+ network was improved so that channel features of cloud detection were extracted and learned with two published heterogeneous datasets and mixed data respectively. As a result of the experiment, clouds' Jaccard index was low in a network that learned with different kind of images from test images. However, clouds' Jaccard index was high in a network learned with mixed data that added some of the same kind of test data. Clouds are not structured in a shape, so reflecting channel features in learning is more effective in cloud detection than spatial features. It is necessary to learn channel features of each satellite sensors for cloud detection. Therefore, cloud detection of heterogeneous sensors with different resolutions is very dependent on the learning dataset.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.33-41
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• 2021

Ammonia emission from the agricultural sector contributes almost 78% of total ammonia emission in Korea. The current ammonia emission estimation method from fertilizer application has high uncertainty and needs to be improved. In this study, we propose an improvement method for estimating the amount of ammonia emission from agricultural land with improved spatiotemporal resolution using Farm Manager Registration Information System and criteria for the fertilizer. We calculated ammonia emissions by utilizing the 2020 cultivation area provided by Farm Manager Registration Information System for 55 kinds of upland crops cultivated in the field area of the farmland. As a result, soybeans were the most cultivated field crop in 2020, and the area of cultivated land was surveyed at about 77,021 ha, followed by sweet potatoes 22,057 ha, garlic 20004 ha, potatoes 17,512 ha, and corn 16,636 ha. The month with the highest ammonia emissions throughout the year was calculated by emitting 590.01 ton yr-1 in May, followed by 486.55 ton yr-1 in March. Hallim-eup in Jeju showed the highest ammonia emission at 117.50 ton yr-1.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.80-83
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• 2007

Entering 21st century, various natural disasters have been caused by the scorching heat wave, earthquake, tsunami, typhoon and so on. The casuality and damages have been drastically increased in terms of the frequency and magnitude. Therefore, 50 nations around the world agreed to build up the GEO(Global Earth Observation) in charge of the earth observation for the understanding of the earth system changes, monitoring and prediction and it is on operation. To keep the pace with GEOSS for the cooperation of Science & Technology and to successfully achieve the GEOSS project, KGEO office was established and has been on its duty. Moreover, for more prosperous building of the GEOSS, in cooperation with KGEO and KISTI(Korea Institute of Science and Technology Information), we've conducted the survey of the domestic situation about 9 societal benefit areas of the GEOSS. This survey consists of 5 sections as follows: the standardization, the information system management, the raw data and metadata, the infrastructure, and the others. This survey results will be used as the basic material for establishing the National Global Earth Observation System.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.9
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• pp.27-35
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• 2016

Today, with the advance of Information and communication technology, 'Smart, connected' toys, which apply technologies related to IoT (Internet of Things) to traditional toys, are emerging and rapidly growing. This research aims to analyze the tendencies and limitations of smart, connected toys through exploring the representative cases of smart, connected toys based on characteristics of ICBM (Internet of Things, Cloud, Big-data, and Mobile) technology. For this study, we begin by understanding literature research about smart, connected toys and ICBM technology. Then, we extracted the characteristics of ICBM technology for connecting physical and digital environments through investigating cases to which ICBM technologies are applied. Based on the extracted characteristics, the case studies of smart, connected toys were conducted. In this research, we explore the level of ICBM technology application and limitation to smart, connected toys. We expect this research will contribute to providing guidelines for developing smart, connected toys based on the characteristics of the latest technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.382-390
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• 2019

As there is severe competition in the global foldable display market, strategic technology planning is required. Patent analysis as a tool for technology planning has frequently been used due to data characteristics such as openness, formality, and detailed information. However, traditional patent analysis has various limitations such as quantitative approaches are limited in evaluating contents of patents and identifying core technologies of firms as they rely on number of patents, and qualitative approaches have time and cost problems as researchers have to investigate each patent on a case-by-case basis. In this research, we analyze core technologies of firms in the foldable display sector analyzing patent co-classification Network. Results show that the number of patent applications has rapidly increased since 2014, and 92% of these patents are held by two panel manufacturers, SDC and LGD, and two device manufacturers, SEC and LGE. Network analysis shows that the two panel manufacturers' core technologies are similar and two device manufacturers are notably different. This research provides implications to the sector. Moreover, this study provides unique results drawn from co-classification network analysis, and therefore, our research suggests patent co-classification analysis as an effective tool for technology planning.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.59-69
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• 2010

The research on protein for the diseases analysis and the new medicines development is one of the most important themes in biotechnology. Since the analysis on diseases and protein needs to handle a large scale of data, we don't use the way to approach it by the experiments anymore. In recent, we have accelerated the research on diseases and protein analysis by sharing and connecting the various experimental data by combining the biotechnology with the IT technology. However, many biotechnology researchers have difficulty in handling the protein analysis tools based on the IT knowledge. In order to solve such problems, data analysis tools through the cooperation between IT researchers and biologists have been developed. However, the existing data analysis tools still have the problems that it is very hard for biologists to extend their functions and to use them. In this paper, we design and implement an effective analysis system for diseases and protein based on components that alleviates the problems of the existing data analysis systems.

• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.151-155
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• 2021

The application of environmental DNA in the domestic ecosystem is also accelerating, but the processing and analysis of the produced data is limited, and doubts are raised about the reliability of the analyzed and produced biological taxa identification data, and the sample medium (target sample, water, air, sediment, Gastric contents, feces, etc.) and quantification and improvement of analysis methods are also needed. Therefore, in order to secure the reliability and accuracy of biodiversity research using the environmental DNA of the domestic ecosystem, it is a process of actively using the database accumulated through ecological taxonomy and undergoing verification procedures, and experts verifying the resolution of the data increased by gene sequence analysis. This is absolutely necessary. Environmental DNA research cannot be solved only by applying molecular biology technology, and interdisciplinary research cooperation such as ecology-taxa identification-genetics-informatics is important to secure the reliability of the produced data, and researchers dealing with various media can approach it together. It is an area in desperate need of an information sharing platform that can do this, and the speed of development will proceed rapidly, and the accumulated data is expected to grow as big data within a few years.