• Journal of the Korean Regional Science Association
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• v.39 no.1
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• pp.53-66
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• 2023

Due to COVID-19, the external activities of urban residents have greatly shrunk, causing a lot of damage to the commercial district, such as a decrease in population and sales. The downturn in commercial districts means the collapse of the infrastructure of the national economy, and can have serious side effects on the local economy and individual lives. Therefore, it is necessary to look at the alley commercial area, which is closely related to the national local economy, and pay attention to the damage and stagnation of the alley commercial area where small business owners are concentrated. The purpose of this study is to classify alley commercial districts into growth commercial districts and decline commercial districts by using commercial sales time series data and DTW time series group analysis for the pre- and post-COVID-19 period. The main findings of the study are as follows. First, using the time series data on commercial sales before and after COVID-19, the alley commercial districts were divided into growth commercial districts and decline commercial districts, and it was confirmed that the distribution of growth commercial districts and decline commercial districts was regionally different. Therefore, it is necessary to actively manage commercial districts in areas where many declining commercial districts are distributed, and it is required to prepare policies for each region in consideration of the spatial distribution of declining commercial districts. Second, during the COVID-19 period, face-to-face essential industries, density of guest facilities, and population density negatively affected the sustainability of commercial districts, which is the opposite of previous studies. This is the result of empirically confirming the specificity of the COVID-19 period and the negative effects of the integrated economy, and can be used as basic data for effective commercial district management and policy preparation in the event of a national disaster in the future. Third, the characteristics of the background of the commercial district had a significant effect on the sustainability of the commercial district, and the negative effect of the attracting facilities inducing population concentration in the background area was found. This suggests that it is necessary to consider the characteristics of the background as well as the inside of the commercial district when establishing policies to revitalize the commercial district and support small business owners in a national disaster situation.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.710-713
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• 2007

This paper presents the findings obtained from several series of analysis on the fatal accident, which are maintained by Korean Production Household Mascot Safety Industrial Complex, relative to fall. The fall accidents occurred in 5 years, from 2002 to 2006, were analyzed. The statistic relative to the fatal accidents analyzed according to different classifications such as accident rate, project amount, project type, cause, type of occupation. years of experience, and time in a day. This research would contribute to ensure the effectiveness of safety policy so as to enhance worker safety. In addition, cluster analysis was applied to find the major contributors on the fall accidents. Cross referencing between occupation and type of work, and occupation and cause were established so that the occurrence statistics of fall accidents were investigated.

• Journal of Digital Convergence
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• v.15 no.11
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• pp.567-579
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• 2017

The purpose of this study was conducted to clarify physical activity university students on time perspective in leisure constraints and leisure flow. To achieve this purpose, subjects of this study were sampled 295 Physical Activity University Students participant using purposeful sampling method for 2 months from May to June of 2017. Using questionnaires stratified cluster random sampling in university students in D city and C city. The analysis method was used t-test, one-way ANOVA, multiple regression analysis, correlation analysis methods in order to solve problems of the study. According to the study Result, First, studies show that female have high levels of leisure constraints than males. Males have higher levels of leisure flow than females. The first grader show high level of individual constraints and past negation were also high. In the series of majors, natural affiliates and humanities are high in the past negation, present destiny, the service major currently high in pleasure and of leisure, autotelic experience of leisure flow. In the rhythmic type of Activity type, the past negation, present destiny and leisure constraints are highly likely to be higher. In the competitive have shown that is high. Second, leisure constraints on students' participation in physical activities have been found to have negative influence on their students. Third, leisure flow have shown that they have a positive effect on past affirmation and present pleasure.

• Journal of the Korean Society for information Management
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• v.35 no.1
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• pp.231-250
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• 2018

In this paper, we propose a new methodology for extracting and formalizing subjective topics at a specific time using a set of keywords extracted automatically from online news articles. To do this, we first extracted a set of keywords by applying TF-IDF methods selected by a series of comparative experiments on various statistical weighting schemes that can measure the importance of individual words in a large set of texts. In order to effectively calculate the semantic relation between extracted keywords, a set of word embedding vectors was constructed by using about 1,000,000 news articles collected separately. Individual keywords extracted were quantified in the form of numerical vectors and clustered by K-means algorithm. As a result of qualitative in-depth analysis of each keyword cluster finally obtained, we witnessed that most of the clusters were evaluated as appropriate topics with sufficient semantic concentration for us to easily assign labels to them.

• 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 Korean Society for Atmospheric Environment
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• v.34 no.2
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• pp.321-330
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• 2018

Concentrations of the atmospheric radon and gaseous pollutants were measured at the Gosan site on Jeju Island from 2010 to 2015, in order to observe their time-series variation characteristics and examine the concentration change related to the airflow transport pathways. Based on the realtime monitoring of the atmospheric radon and gaseous pollutants, the daily mean concentrations of radon ($^{222}Rn$) and gaseous pollutants($SO_2$, CO, $O_3$, $NO_x$) were $2,400mBq\;m^{-3}$ and 1.3, 377.6, 41.1, 3.9 ppb, respectively. On monthly variations of radon, the mean concentration in October was the highest as $3,033mBq\;m^{-3}$, almost twice as that in July ($1,452mBq\;m^{-3}$). The diurnal variation of radon concentration shows bimodal curves at early morning (around 7 a.m.) and near midnight, whereas its lowest concentration was recorded at around 3 p.m. Several gaseous pollutants($SO_2$, CO, $NO_x$) showed a similar seasonal variation with radon concentration as high in winter and low in summer, whereas the $O_3$ concentrations had a bit different seasonal trend. According to the cluster back trajectory analysis, the frequencies of airflow pathways moving from continental North China, East China, Japan and the East Sea, the Korean Peninsula, and North Pacific Ocean routes were 36, 37, 10, 13, and 4%, respectively. When the airflow were moved to Jeju Island from continental China, the concentrations of radon and gaseous pollutants were relatively high. On the other hand, when the airflows were moved from North Pacific Ocean and East Sea, their concentrations were much lower than those from continental China.

• Publications of The Korean Astronomical Society
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• v.30 no.3
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• pp.821-832
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• 2015

As a part of the short-period variability survey (SPVS) at Bohyunsan Optical Astronomy Observatory, we obtained time-series BV CCD images in the region of the open cluster NGC 1039 (M34). The observations were performed for 22 nights from July 29, 2008 to September 26, 2010. We also made LOAO observations for 10 days from September 18, 2009 to October 30, 2010 to confirm the small variabilties of ${\delta}$ Scuti-type variable stars. In this paper we presented the observational properties of 28 variable stars found in the region. They are seven ${\delta}$ Scuti-type variable stars, two ${\gamma}$ Doradus-type variable stars, four-teen eclipsing binary stars and five semi-long periodic or slow irregular variables, respectively. Only three variables were listed in the GCVS and the rest are newly discovered ones. We have performed multiple-frequency analysis to determine pulsation frequencies of the ${\delta}$ Scuti-type and ${\gamma}$ Doradus-type variable stars, using the discrete Fourier transform and linear least-square fitting methods. We also have derived the periods and amplitudes of 12 eclipsing binaries from the phase fitting method, and presented the light curves of all variable stars.

• Publications of The Korean Astronomical Society
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• v.27 no.5
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• pp.399-409
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• 2012

As a part of the short-period variability survey (SPVS) at Bohyunsan Optical Astronomy Observatory, we obtained time-series BV CCD images in the region of Cyg OB3 association centered on the open cluster NGC 6871. The observations were performed for 18 nights from September 5, 2008 to September 1, 2009. We found 15 short-period variable stars in the region. They are ${\delta}$ Scuti type stars belonging to the local spiral arm, Orion spur. Among them, only two stars were previously known, and the rest are newly discovered ones. In this paper, we have performed a multiple-frequency analysis to determine frequencies of the 15 ${\delta}$ Scuti type stars, using the discrete Fourier transform and linear least-square fitting methods. One of the newly discovered variable stars is a double-mode ${\delta}$ Scuti type star with the fundamental and the first overtone modes, and two are high amplitude ${\delta}$ Scuti stars.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Journal of the Korean association of regional geographers
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• v.22 no.4
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• pp.792-808
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• 2016

Due to the high importance of foreign trade in the national economy, Korea has a lot of ports designated as trade ports compared to the small land size. However, because of the poor utilization results, some small trade ports have been criticized for wasteful financing due to redundant investment in SOC. This is because the characteristics and comparative advantage of foreign trade in trade ports have not been analyzed in detail by region. Therefore, this study analyzes the patterns and types of change in the size of trade, number of cargo items handled, and the number of trade target countries in the past 20 years for 19 domestic small trade ports using the time-series cluster analysis technique. As a result of analysis, Korean small trade ports were classified into five growth pattern types according to the analysis index, and characteristics and implications for each type could be derived. Today, as the foreign trade environment changes drastically and the importance of balanced regional development is emphasized, it is very important to study the growth types and implications of small trade ports and the results of this study are expected to provide meaningful implications for regional port development and operation in the future.