• Journal of Radiation Protection and Research
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• v.26 no.2
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• pp.59-66
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• 2001

It is a hot issue to determine the spatial location and shape of tumor boundary in fractionated stereotactic radiotherapy (FSRT). We could get consecutive transaxial plane images from the phantom (paraffin) and 4 patients with brain tumor using helical computed tomography(HCT). K-means classification algorithm was adjusted to change raw data pixel value in CT images into classified average pixel value. The classified images consists of 5 regions that ate tumor region (TR), normal region (NR), combination region (CR), uncommitted region (UR) and artifact region (AR). The major concern was how to separate the normal region from tumor region in the combination area. Relative average deviation analysis was adjusted to alter average pixel values of 5 regions into 2 regions of normal and tumor region to define maximum point among average deviation pixel values. And then we drawn gross tumor volume (GTV) boundary by connecting maximum points in images using semi-automatic contour method by IDL(Interactive Data Language) program. The error limit of the ROI boundary in homogeneous phantom is estimated within ${\pm}1%$. In case of 4 patients, we could confirm that the tumor lesions described by physician and the lesions described automatically by the K-mean classification algorithm and relative average deviation analyses were similar. These methods can make uncertain boundary between normal and tumor region into clear boundary. Therefore it will be useful in the CT images-based treatment planning especially to use above procedure apply prescribed method when CT images intermittently fail to visualize tumor volume comparing to MRI images.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.127-138
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• 2011

The core service of most research portal sites is providing relevant research papers to various researchers that match their research interests. This kind of service may only be effective and easy to use when a user can provide correct and concrete information about a paper such as the title, authors, and keywords. However, unfortunately, most users of this service are not acquainted with concrete bibliographic information. It implies that most users inevitably experience repeated trial and error attempts of keyword-based search. Especially, retrieving a relevant research paper is more difficult when a user is novice in the research domain and does not know appropriate keywords. In this case, a user should perform iterative searches as follows : i) perform an initial search with an arbitrary keyword, ii) acquire related keywords from the retrieved papers, and iii) perform another search again with the acquired keywords. This usage pattern implies that the level of service quality and user satisfaction of a portal site are strongly affected by the level of keyword management and searching mechanism. To overcome this kind of inefficiency, some leading research portal sites adopt the association rule mining-based keyword recommendation service that is similar to the product recommendation of online shopping malls. However, keyword recommendation only based on association analysis has limitation that it can show only a simple and direct relationship between two keywords. In other words, the association analysis itself is unable to present the complex relationships among many keywords in some adjacent research areas. To overcome this limitation, we propose the hybrid approach for establishing association network among keywords used in research papers. The keyword association network can be established by the following phases : i) a set of keywords specified in a certain paper are regarded as co-purchased items, ii) perform association analysis for the keywords and extract frequent patterns of keywords that satisfy predefined thresholds of confidence, support, and lift, and iii) schematize the frequent keyword patterns as a network to show the core keywords of each research area and connecting keywords among two or more research areas. To estimate the practical application of our approach, we performed a simple experiment with 600 keywords. The keywords are extracted from 131 research papers published in five prominent Korean journals in 2009. In the experiment, we used the SAS Enterprise Miner for association analysis and the R software for social network analysis. As the final outcome, we presented a network diagram and a cluster dendrogram for the keyword association network. We summarized the results in Section 4 of this paper. The main contribution of our proposed approach can be found in the following aspects : i) the keyword network can provide an initial roadmap of a research area to researchers who are novice in the domain, ii) a researcher can grasp the distribution of many keywords neighboring to a certain keyword, and iii) researchers can get some idea for converging different research areas by observing connecting keywords in the keyword association network. Further studies should include the following. First, the current version of our approach does not implement a standard meta-dictionary. For practical use, homonyms, synonyms, and multilingual problems should be resolved with a standard meta-dictionary. Additionally, more clear guidelines for clustering research areas and defining core and connecting keywords should be provided. Finally, intensive experiments not only on Korean research papers but also on international papers should be performed in further studies.

• Cartoon and Animation Studies
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• s.29
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• pp.129-149
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• 2012

The purpose of this study was to investigate the clustering and Big Five Personality domains in discriminating groups by level of school-related adjustment, as experienced by Social Sims game users. Social Games are based on web that has simple rules to play in fictional time and space background. This paper is to analyze the relationships between social networks and user behaviors through the social games . In general, characteristics of social games are simple, fun and easy to play, popular to the public, and based on personal connections in reality. These features of social games make themselves different from video games with one player or MMORPG with many unspecific players. Especially Social Game show a noticeable characteristic related to social learning. The object of this research is to provide a possibility that game that its social perspective can be strengthened in social game environment and analyze whether it actually influences on problem solving of real life problems, therefore suggesting its direction of alternative play means and positive simulation game. Data was collected by administering 4 questionnaires (the short version of BFI, Satisfaction with life, Career Decision-.Making Self-.Efficacy, Depression) to the participants who were 20 people in Seoul and Daejeon. For the purposes of the data analysis, both Stepwise Discriminant analysis and Cluster analysis was employed. Neuroticism, Openness, Conscientiousness within the Big Five Personality domains were seen to be significant variables when it came to discriminating the groups. These findings indicated that the short version of the BFI may be useful in understanding for game user behaviors When it comes to cultural research, digital game takes up a significant role. We can see that from the fact that game, which has only been considered as a leisure activity or commercial means, is being actively research for its methodological, social role and function. Among digital game's several meanings, one of the most noticeable ones is the research on its critical, social participating function. According to Jame Paul gee, the most important merit of game is 'projected identity'. This means that experiences from various perspectives is possible.[1] In his recent autobiography , he described gamer as an active problem solver. In addition, Gonzalo Francesca also suggested an alternative game developing method through 'game that conveys critical messages by strengthening critical reasons'. [2] They all provided evidences showing game can be a strong academic tool. Not only does a genre called social game exist in the field of media and Social Network Game, but there are also some efforts to positively evaluate its value Through these kinds of researches, we can study how game can give positive influence along with the change in its general perception, which would eventually lead to spreading healthy game culture and enabling fresh life experience. This would better bring out the educative side of the game and become a social communicative tool. The object of this game is to provide a possibility that the social aspect can be strengthened within the game environment and analyze whether it actually influences the problem solving of real life problems. Therefore suggesting it's direction of alternative play means positive game simulation.

• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.53-67
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• 2009

For the last decades, service quality has been studied as one of the most important tools for a service company to compete with the other companies. Based on these past researches, it has been agreed that the service quality is a basic and powerful tool to create the competitive advantage. Due to similar reason, many service marketing practitioners have been also focused on the service quality to retain the existing consumers and collect the new consumers. However, service quality is subjectively perceived by individual consumers. Consumer evaluation of service quality can be different from each other. Especially consumers with one life-style may evaluate the service quality differently from the consumers with the other life-styles. Therefore we need to know whether there are differences in service quality perception on the categories of life-style. Life-style refers to a distinctive mode of living in its aggregate and broadest sense. It embodies the patterns that were developed and emerged from the dynamics of living in a society. Since the concept of life-style and its relationship to marketing was introduced in 1963 by William Lazer, methods of measuring the life-style and their application have been developed. Life-style has been usually used to segment the marketplace because it offers marketers a unique and important view of the market. When Life-style is combined with clustering methods, life-style segmentation can generate identifiable whole persons rather than isolated fragment. Life-style segmentation begins with people instead of products and classifies them into different life-style types, each characterized by a unique style of living based on a wide range of activities, interests, and opinions(Plummer, 1974). In this study we applies the life-style segmentation based on the AIO(Activities, Interests, and Opinions) to the consumers of the large discount stores. In Korea, the large discount store market has entered into maturity stage so that the market differentiation strategy is becoming a more critical issue to the marketing practitioners. One of the most important tools to differentiate from the competitors in large discount store market is continuously to provide service of better quality than competitors. This study tries to find answers about the following questions: 1) How can we categorize the consumer life-styles in the large discount store? 2) What are the characteristics of the categorized groups? 3) Are there any differences in service quality perception among the consumers with different life-styles 4) Are there any differences in consumer behavior among them in the large discount store? For the purpose, we collected survey data from consumers and analyzed the data with the SPSS package where we had $X^2$-test, factor analysis, ANOVA, MANOVA, and cluster analysis. The survey was made during one month in the April of 2008. Among the collected 306 copies of questionnaires, 281 copies were chosen as the effective samples for empirical analysis except 25 copies with wrong responses. To identify the life-style patterns, we used the measures employed by Kim and Kwon(1999), where 44 items on a seven-point scale were used to measure factors of the life-style patterns. The Principal Component Method was used for factor extraction, and the VARIMAX orthogonal factor rotation was employed. The 7 items showing low factor loading were eliminated. The results of the factor analysis suggested that nine factors of the life-style patterns were identified as follows: 1) the equality-of-sexes and pursuit-of-independence tendency 2) self-management tendency 3) sociable tendency 4) self-display tendency 5) degree of a dilettante life 6) pursuit-of-information tendency 7) bargain hunter tendency 8) TV preference tendency 9) pursuit-of-leisure tendency. Next, after the K-means cluster analysis was performed with nine factors of the life-style patterns, the life-styles of the respondents were classified into four groups which are named as the 'progressive practicality-oriented group', 'positive success-oriented group', 'sociable ostentation-oriented group', 'stable conservation-oriented group'. The analysis results for usage behavior between the market segments showed statistically significant differences in the frequency of usage, duration time in the store, consumer satisfaction, and loyalty. Also, we tried to investigate whether the large discount store consumers differently perceive the quality of service based upon the types of life-style. To measure the service quality of large discount store, we adapted several measurement models measuring the service quality such as SERVPERF, BCP, R-SERVPERF, R-BCP. MANOVA and One-Way ANOVA were performed to confirm the difference in service quality perception based on the market segments. The results have also shown significant differences between life-style types in service quality perception. These findings show that the large discount store marketers should consider consumer life-style as one of the most important market segments for marketing and understand the difference in service quality perception between life-style types. Our findings give important implications to marketers of large discount stores as well as life-style researchers. First, this study showed there were significant differences in consumer's service quality perception and usage behavior between the types of life-style. It provides evidence that the life-style approach can be a important basis in segmenting the large discount store market and will make consumers perceive the service quality high. Second, most previous researches on service quality have been in aggregate level. However, our results imply that the future research on service quality have to focus on segment level.

• Journal of Nutrition and Health
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• v.50 no.4
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• pp.325-335
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• 2017

Purpose: The purpose of this study was to investigate the consumption behaviors of sugar-sweetened beverages and blood lipid profiles according to food-related lifestyles of adults in Incheon. Methods: Subjects were recruited from 19 to 64 year old adults residing in Incheon who visited for the purpose of a health examination at D hospital. A total of 110 subjects consented to participate in this study and to allow their health examination records to be used at D hospital. Data were collected using self-administered questionnaires and anthropometric data, and blood lipid profiles were collected from health examination records. Statistical analysis was performed using the SPSS 20.0 program. Results: In the factor analysis, food-related lifestyles were categorized into four factors: planned purchase seeking, taste seeking, well-being seeking, and convenience seeking. Using the K-average clustering method, food-related lifestyles of subjects were categorized into two groups: health and rationality-oriented group (HRG) and convenience purchase-oriented group (CPG). Average total scores of sugar-related nutrition knowledge in the HRG were significantly higher compared to the CPG, and average scores of consumption habits regarding sugar-containing foods in the HRG were significantly lower compared to the HRG. When subjects chose sugar-sweetened beverages, the CPG showed a significantly higher frequency of checking food labeling and considering nutrition compared to the CPG. Drinking frequency of carbonated beverages in the CPG was significantly higher compared to the HRG. Conclusion: There were significant differences in sugar-related nutrition knowledge and consumption habits of sugar-sweetened beverages between the two food-related lifestyle groups. These results could be useful for establishing guidelines for reducing consumption of sugar-sweetened beverages. In addition, it is necessary to continue sugar-related nutrition education by considering the food-related lifestyles of adults.

• Korean Journal of Weed Science
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• v.9 no.1
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• pp.1-15
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• 1989

The seventeen barnyardgrass [Echinochloa crus-galli (L.) Beauv.] accessions, which were collected national-widely in 1986 and selected two times through 1987, were experimented at 1988. To identify the ecological properties of the collected accessions of native barnyardgrass species as a weed, the experiment was conducted with Wagner pots in size of I/500a and under PE film house. 1. Accessions were classified into 5 specific groups in plant type properties by use of data from plant height, number of maximum tillers, erectness, culm length and panicle type, among others. 2. As for species identification, they were clustered into 3 similar groups and 2 individual species by use of data from color, first-glumer type, and erectness. 3. Four groups were identified for elongational properties by plant height of 22 days old seedling, length of culm, panical, leaf length and width, and inter-node and spikelet, among others. 4. Properties on quanititative growth were classified into 4 groups and 1 individual accession corresponding to differential plant height of 22 days old seedling, length of culm, panical, inter-node, leaf-sheath, spikelet, first-glumes length, grain, number of tillers, spike, and grain weight. 5. Due to different daily increasing rate in seedling height, dry weight, number of tillers and ratio in dry weight to plant height, the growth rate properties were clustered into 4 groups and one individual accession. 6. Properties on seedling growth were classified into 4 groups by use of differential date in length and width of first-leaf, plant height, number of tillers, and dry weight of young and medium aged seedling. 7. Responding to heading date, the accessions were classified into 3 groups : temperative sensitive, medium, and short-day length sensitive types, respectively. 8. By integrating of all quanititative and attributable characters, the seventeen accessions were clustered into 4 groups and 2 individual accessions.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.57-66
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• 2015

Considerable research efforts are being directed towards analyzing unstructured data such as text files and log files using commercial and noncommercial analytical tools. In particular, researchers are trying to extract meaningful knowledge through text mining in not only business but also many other areas such as politics, economics, and cultural studies. For instance, several studies have examined national pending issues by analyzing large volumes of text on various social issues. However, it is difficult to provide successful information services that can identify R&D documents on specific national pending issues. While users may specify certain keywords relating to national pending issues, they usually fail to retrieve appropriate R&D information primarily due to discrepancies between these terms and the corresponding terms actually used in the R&D documents. Thus, we need an intermediate logic to overcome these discrepancies, also to identify and package appropriate R&D information on specific national pending issues. To address this requirement, three methodologies are proposed in this study-a hybrid methodology for extracting and integrating keywords pertaining to national pending issues, a methodology for packaging R&D information that corresponds to national pending issues, and a methodology for constructing an associative issue network based on relevant R&D information. Data analysis techniques such as text mining, social network analysis, and association rules mining are utilized for establishing these methodologies. As the experiment result, the keyword enhancement rate by the proposed integration methodology reveals to be about 42.8%. For the second objective, three key analyses were conducted and a number of association rules between national pending issue keywords and R&D keywords were derived. The experiment regarding to the third objective, which is issue clustering based on R&D keywords is still in progress and expected to give tangible results in the future.

• 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.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.199-209
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• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.