• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.1-14
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• 2023

The objective of the study was to examine the associations of dietary carbohydrate and fat intake with the prevalence of metabolic syndrome in Korean women. A cross-sectional study was employed based on data from the Korea National Health and Nutrition Examination (2007-2016). A total of 22,850 women aged 19 to 69 years were studied after excluding responses from pregnant or lactating women and those with missing metabolic values. Dietary intake data were collected with a 24-hour recall method. Dietary carbohydrate and fat intakes were divided into quintiles. After controlling for confounding variables, a multivariable logistic regression and general linear model were used. The findings indicated that HDL cholesterol levels were lower (p for trend<0.01), while triglyceride levels (p for trend=0.04), waist circumference (p for trend<0.01), and systolic blood pressure (p for trend<0.01) were higher among participants in the highest quintile of carbohydrate intake compared to those in the lowest quintile. Participants in the highest quintile of fat intake had lower waist circumference (p for trend=0.02), triglyceride level (p for trend<0.01), and systolic blood pressure (p for trend<0.01), while higher HDL cholesterol level (p for trend<0.01) compared to those in the lowest fat intake quintile. Metabolic syndrome was more likely to be present in the highest quintile of carbohydrates intake than in the lowest quintile (5^th quintile vs. 1^st quintile, OR: 1.32; 95% CI: 1.11 to 1.57). However, metabolic syndrome was less likely to be present in the highest quintile of fat intake than in the lowest quintile (5^th quintile vs. 1^st quintile, OR: 0.73; 95% CI: 0.61 to 0.86). This study revealed that high dietary carbohydrate intake and low dietary fat intake were associated with metabolic syndrome in Korean women.

• Knowledge Management Research
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• v.24 no.2
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• pp.241-262
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• 2023

The phenomena and game records that occur in sports matches are being analyzed in the field of sports game analysis, utilizing advanced technologies and various scientific analysis methods. Among these methods, social network analysis is actively employed in analyzing pass networks. As football is a representative sport in which the game unfolds through player interactions, efforts are being made to provide new insights into the game using social network analysis, which were previously unattainable. Consequently, this study aims to analyze the changes in pass networks over time for a specific football team and compare them in different scenarios, including variations in the game's nature (Qatar World Cup games vs. A match games) and alterations in the opposing team (higher FIFA rankers vs. lower FIFA rankers). To elaborate, we selected ten matches from the games of the Korean national football team following Coach Bento's appointment, extracted network indicators for these matches, and applied four indicators (efficiency, cohesion, vulnerability, and activity/leadership) from a football team's performance evaluation model to the extracted data for analysis under different circumstances. The research findings revealed a significant increase in cohesion and a substantial decrease in vulnerability during the analysis of game performance over time. In the comparative analysis based on changes in the game's nature, Qatar World Cup matches exhibited superior performance across all aspects of the evaluation model compared to A matches. Lastly, in the comparative analysis considering the variations in the opposing team, matches against lower FIFA rankers displayed superior performance in all aspects of the evaluation model in comparison to matches against top FIFA rankers. We hope that the outcomes of this study can serve as essential foundational data for the selection of football team coaches and the development of game strategies, thereby contributing to the enhancement of the team's performance.

• Health Policy and Management
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• v.34 no.2
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• pp.196-210
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• 2024

Background: In January 2018, revised elderly fixed outpatient copayment for the elderly were implemented. When people ages 65 years and older receive outpatient treatment at clinic-level medical institutions (clinic, dental clinic, Korean medicine clinic), with medical expenses exceeding 15,000 won but not exceeding 25,000 won, their copayment rates have decreased differentially from 30%. This study aimed to examine the changes of health utilization of elderly after revised elderly fixed outpatient copayment. Methods: We used Korea health panel data from 2016 to 2018. The time period is divided into before and after the revised elderly fixed outpatient copayment. We conducted Poisson segmented regression to estimate the changes in outpatient utilization and inpatient utilization and conducted segmented regression to estimate the changes in medical expenses. Results: Immediately after the revised policy, the number of clinic and Korean medicine outpatient visits of medical expenses under 15,000 won decreased. But the number of clinic outpatient visits in the range of 15,000 to 20,000 won and Korean medicine clinic in the range of 20,000 to 25,000 won increased. Copayment in outpatient temporarily decreased. The inpatient admission rates and total medical expenses temporarily decreased but increased again. Conclusion: We confirmed the temporary increase in outpatient utilization in the medical expense segment with reduced copayment rates. And a temporary decrease in medical expenses followed by an increase again. To reduce the burden of medical expense among elderly in the long run, efforts to establish chronic disease management policies aimed at preventing disease occurrence and deterioration in advance need to continue.

• Journal of Digestive Cancer Research
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• v.8 no.2
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• pp.102-108
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• 2020

Background: This study was performed to evaluate the effect of gastric cancer screening through analysis of screening-related data. Methods: We investigated claims data of gastric cancer from 2009 to 2015. We evaluated whether the screening was performed to prior to registration as patients with gastric cancer. The effect of gastric cancer screening was also analyzed by gender. Results: We collected total 196,293 patients with gastric cancer. 74% of them had previous experience of gastric cancer screening. In patients with screening, early gastric cancer was 33.4% and advanced gastric cancer was 17.3%. 22,548 (15.5%) patients were diagnosed with gastric cancer within 2 years after screening. In the case of patients without screening, early gastric cancer was 15.1% and advanced gastric cancer was 25.3%. In case of men, 76% of them confirmed gastric cancer through screening, and 70.2% of women confirmed the gastric cancer. In both men and women, the rate of early gastric cancer was higher among those with screening than those without screening. Conclusion: In this study, we were able to indirectly confirm the stage shift of gastric cancer screening. However, within 2 years after screening, not a few patients with gastric cancer were diagnosed. Therefore, more studies are warranted to in the future.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.481-491
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• 2024

Recent droughts make hydroelectric power generation (HPG) decreasing. Due to climate change in the future, the frequency and intensity of drought are expected to increase, which will increase uncertainty of HPG in multi-purpose dams. Therefore, it is necessary to estimate the amount of HPG according to climate change scenarios and analyze the effect of drought on the amount of HPG. This study analyzed the future HPG of the Soyanggang Dam and Chungju Dam according to the SSP2-4.5 and SSP5-8.5 scenarios. Regression equations for HPG were developed based on the observed data of power generation discharge and HPG in the past provided by My Water, and future HPGs were estimated according to the SSP scenarios. The effect of drought on the amount of HPG was investigated based on the drought severity calculated using the standardized precipitation index (SPI). In this study, the future SPIs were calculated using precipitation data based on four GCM models (CanESM5, ACCESS-ESM1-5, INM-CM4-8, IPSL-CM6A) provided through the environmental big data platform. Overall results show that climate change had significant effects on the amount of HPG. In the case of Soyanggang Dam, the amount of HPG decreased in the SSP2-4.5 and SSP5-8.5 scenarios. Under the SSP2-4.5 scenario the CanESM model showed a 65% reduction in 2031, and under the SSP5-8.5 scenario the ACCESS-ESM1-5 model showed a 54% reduction in 2029. In the case of Chungju Dam, under the SSP2-4.5 and SSP5-8.5 scenarios the average monthly HPG compared to the reference period showed a decreasing trend except for INM-CM4 model.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.125-148
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• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.197-218
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• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

• Korean Journal of Human Ecology
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• v.14 no.2
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• pp.313-319
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• 2005

This survey was conducted in order to obtain the basic data for desirable consumption habits through investigation and analysis of university students' fast food consumption behaviors. Questionnaires were collected from a total of 374 male and female students living in big or small and medium-sized cities in August, 2004. The contents surveyed were utilization and expenses of fast foods, choice of fast foods, relationship between fast foods and a diet, and characteristics of fast food restaurants. The results obtained are summarized as follows: 1. The ratio of the surveyees varied according to gender, residence, and the size of a city they're living in. For example, males took up 48.66% of the surveyees, while females did 51.34%. The ratio of residents in apartments and stand-alone houses was 54.81% and 45.19% each. 47.33% of the respondents were living in big cities, while 52.67% of them in small and medium-sized cities. 2. 70.1% of the surveyees responded that they are with friends when having fast foods. There was a highly significant difference between male and female in the type of eating companions (p<0.001). The average number of days that they eat fast foods was 1 to 2 times a week, which accounted for 63.7% of the respondents. However, in the case of eating foods, there was no significant differences between two sexes. 3. 64.2% of the surveyees paid more than 20,000 won to buy fast foods for a week, which showed no significant differences between genders. They tend to split a bill, rather than one person pays all. There was a highly significant difference between genders in paying method (p<0.001). 4. 52.1 % of the respondents chose a menu themselves. Their most favored food was chickens (26.5%), which showed a statistically significant difference between genders (p<0.001). 46.8% of them preferred coke as a drink, which had no significant difference between genders. 42.2% of the surveyees had fast foods between lunch and dinner, which also had no significant difference between genders. The most important factor in choosing a menu was its taste (62.8%), which indicated a significant difference between males and females (p<0.05). 5. The preference to fast foods was due to the influence of western culture (36.4%) and eating-out habits (29.1%), which was significantly different between genders (p<0.05). Those who eat fast foods answered they have normal weight and normal body type (49.5%). 24.3% of them were relatively fat with significant difference between genders (p<0.05). 63.4% of the surveyees thought themselves not picky with foods, and there was a significant difference between genders (p<0.05). 78.3% of them mostly preferred franchise restaurants because they are convenient and cheap.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.20-28
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• 2013

The purpose of this study was to compare the ultra-violet(UV) radiation under the landscaping shade facilities and tree with natural solar UV of the outdoor space at summer middays. The UVA+B and UVB were recorded every minute from the $20^{th}$ of June to the $26^{th}$ of September 2012 at a height of 1.1m above in the four different shading conditions, with fours same measuring system consisting of two couple of analog UVA+B sensor(220~370nm, Genicom's GUVA-T21GH) and UVB sensor(220~320nm, Genicom's GUVA-T21GH) and data acquisition systems(Comfile Tech.'s Moacon). Four different shading conditions were under an wooden shelter($W4.2m{\times}L4.2m{\times}H2.5m$), a polyester membrane structure ($W4.9m{\times}L4.9m{\times}H2.6m$), a Salix koreensis($H11{\times}B30$), and a brick-paved plot without any shading material. Based on the 648 records of 17 sunny days, the time serial difference of natural solar UVA+B and UVB for midday periods were analysed and compared, and statistical analysis about the difference between the four shading conditions was done based on the 2,052 records of daytime period from 10 A.M. to 4 P.M.. The major findings were as follows; 1. The average UVA+B under the wooden shelter, the membrane and the tree were $39{\mu}W/cm^2$(3.4%), $74{\mu}W/cm^2$(6.4%), $87{\mu}W/cm^2$(7.6%) respectively, while the solar UVA+B was $1.148{\mu}W/cm^2$. Which means those facilities and tree screened at least 93% of solar UV+B. 2. The average UVB under the wooden shelter, the membrane and the tree were $12{\mu}W/cm^2$(5.8%), $26{\mu}W/cm^2$(13%), $17{\mu}W/cm^2$(8.2%) respectively, while the solar UVB was $207{\mu}W/cm^2$. The membrane showed the highest level and the wooden shelter lowest. 3. According to the results of time serial analysis, the difference between the three shaded conditions around noon was very small, but the differences of early morning and late afternoon were apparently big. Which seems caused by the matter of the formal and structural characteristics of the shading facilities and tree, not by the shading materials itself. In summary, the performance of the four landscaping shade facilities and tree were very good at screening the solar UV at outdoor of summer middays, but poor at screening the lateral UV during early morning and late afternoon. Therefore, it can be apparently said that the more delicate design of shading facilities and big tree or forest to block the additional lateral UV, the more effective in conditioning the outdoor space reducing the useless or even harmful radiation for human activities.