• Korean Journal of Heritage: History & Science
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• v.54 no.3
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• pp.204-227
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• 2021

This paper proposed the validity and necessity of establishing the Jungwon Historical and Cultural Area by reviewing the historical characteristics of the name Jungwon and its temporal and spatial range. We also explored ways to utilize the Jungwon historical and cultural Area under the Special Act on the Maintenance of Historical and Cultural Areas. Jungwon, which means the center of the country, has strategic value as a key area connecting the Korean Peninsula to the north and south through the Geripryeong and Jukryeong. It also includes Chungju, which connects the Namhan and Bukhan Rivers . From the Mahan period, the areas of Cheongju and Jincheon, the Miho Stream basin to the west, and Chungju to the east were closely connected to each other. Afterwards, Baekje, Koguryo, and Silla engaged in a fierce battle to occupy the Jungwon area. Jungwon culture was born through the negotiation and fusion of the cultures of the three kingdoms. In particular, Silla continued to value the Jungwon area, demonstrated by the installation of Seowongyeong in Cheongju and Bukwongyeong in Wonju, centering on the Jungwongyeong. Since we have a historical view with a focus on ancient kingdoms, we have overlooked the full value of the history and culture of Jungwon. We need to recognize the importance of Jungwon area and think about how to utilize it. Therefore, we suggested in this paper that there be more public information services on the cultural heritage of Jungwon, the historical heritage experience, and the education programs for local residents. The development and operation of Jungwon's history, culture, and tourism contents, as well as the various academic research papers should be used to reveal the identity of the Jungwon historical and cultural area.

• Journal of Korean Society of Rural Planning
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• v.24 no.3
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• pp.73-86
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• 2018

Agricultural or rural landscape provides various ecosystem services. However, the ecosystem services function is declining due to various environmental problems such as climate change, land use change, stream intensification, non-point pollution and garbage. The A1B scenario predicts that the mean air temperature of South Korea will rise $3.8^{\circ}C$ degrees celsius in 2100. Agricultural sector is very vulnerable to climate change, so it must be thoroughly predicted and managed. In Korea, the facility horticulture complex is 54,051ha in 2016 and is the 3rd largest in the world(MAFRA, 2014). Facilities of horticultural complexes are reported to cause problems such as groundwater decrease, vegetation and insects diversity reduction, landscapes damage and garbage increase, compared with the existing land use paddy fields. Heat island phenomenon associated with climate change is also accelerated by the high heat absorption of horticultural sites. Therefore, we analyzed the heat island phenomenon occurring in the facility of horticultural complex in Korea. As an improvement measurement, I examined how much air temperature is reduced by putting the channel and the open space. In the case of the Buyeo area, the Computational Fluid Dynamics (CFD) simulation was analyzed for the average summer temperature distribution in the current land use mode at $38.9^{\circ}C$. As an improvement measurement, CFD simulation after 10% of 6m water channel was found to have an effect of lowering the summer temperature of about $2.7^{\circ}C$ compared with the present average of $36.2^{\circ}C$. In addition, CFD simulations after analyzing 10% of the open space were analyzed at $34.7^{\circ}C$, which is $4.2^{\circ}C$ lower than the present. For the Jinju area, CFD simulations were analyzed for the average temperature of summer at $37.8^{\circ}C$ in the present land use pattern. As an improvement measure, CFD simulations after 10% of 6m water channel were found to have an effect of lowering the summer temperature of about $2.6^{\circ}C$ compared to the current average of $35.2^{\circ}C$. In addition, CFD simulations after analyzing 10% of the open space were analyzed at $33.9^{\circ}C$, which is $3.9^{\circ}C$ lower than the present. It can be said that the effect of summer temperature drop in open space and waterway has been proven. The results of this study are expected to be reflected in sustainable agriculture land use and used as basic data for government - level policy in land use planning for climate change.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of the Korean Society for Marine Environment & Energy
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• v.11 no.3
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• pp.150-159
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• 2008

The marine litter generated as by-products of human activities and economic development enters to the sea through rivers or stream Indirectly, and through sea-based activities directly. It is commonly comprised of materials that degrade very slowly, such as various plastic products, polystyrene, glass, rubber, metal, wood, derelict fishing nets, wire, rope and so on. Such litter is found in the water column and on the seafloor as well as coastal areas In the Northwest Pacific region. It causes injury or death of human and other living organisms and also accident or damage of the vessel. It is not only a problem of country but also regional and/or global problem because it is transported by currents and winds from one country to another. In this regard, Northwest Pacific Action Plan (NOWPAP) Marine Litter Activity (MALITA) project had been carried out during 2006-2007 biennium and NOWPAP Regional Action Plan on Marine Litter (RAP MALI) has been also continuously implemented in the 2008-2009 biennium as next phase step of MALITA. MERRAC, one of four Regional Activity Centres (RACs) of NOWPAP, has developed monitoring guidelines, sectoral guidelines, and brochures related to sea-based marine litter and port reception facilities and services through MALITA project. Based upon these output, MERRAC will continuously implement relevant activities of RAP MALI in order to help to establish and improve a regional mechanism to deal with the sea-based marine litter problem. This paper aims to introduce MERRAC activities under MALITA and RAP MALI, and to suggest several recommendations to reduce marine litter in the NOWPAP region.

• Korean Journal of Environmental Agriculture
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• v.40 no.4
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• pp.279-289
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• 2021

BACKGROUND: Recently, the golden apple snail, Pomacea canaliculata has been used as an environmentally-friendly weed-control agent in rice farming. Although effective for this particular style of farming, P. canaliculata can be destructive to other crops. The objective of this study was to identify overwintering as well as regional and seasonal distribution characteristics of P. canaliculata. Notably, winter is typically fatal for P. canaliculata. However, owing to increasing average global temperatures, we assessed the ability of P. canaliculata to survive through uncharacteristically warm winters. METHODS AND RESULTS: To examine the distribution and overwintering regions of P. canaliculata, We conducted a survey from April 2020 to May 2021 on environmentally-friendly rice fields, agricultural waterways, and streams in 23 cities belonging to 8 provinces. In addition, because air temperature may influence the distribution density of P. canaliculata, we analyzed the winter temperature data (http://weather.rda.go.kr). CONCLUSION(S): In 2021, overwintering of P. canaliculata (1-3 individuals/m²) was observed in the Goheung and Yeongam regions in Jeonnam. Overwintering of P. canaliculata was observed in fewer regions in 2021 than in 2020; this fact may be attributed to the lower minimum temperatures measured in 2021 (approximately 8℃ lower) than those in 2020. Our results suggest that overwintering occurs as long as overnight temperatures are ≥ -15℃, but can take place if temperatures are as low as -19℃.