• Korean Journal of Culture and Social Issue
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• v.17 no.4
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• pp.435-459
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• 2011

The present study explored Korean parents' perceptions of and behavior toward game use among teenagers in Korea. A total of 600 Korean mothers of teenagers residing in Seoul and five other metropolitan areas participated in the survey. The survey was constructed based on five categories of variables, including the overall perception of games and game use, specific attitudes toward game use, cognitions about and attitudes toward game addiction, factors predicting parental monitoring of children's game use, and views and opinions about what needs to be done to promote healthy game cultures as well as to prevent problematic game use among teenagers in Korea. Results indicate that the respondents' overall perceptions of and attitudes toward games and game use are negative. In contrast, attitudes toward game use of the respondent's own child are contingent upon various comparison standards. Results also indicate that the respondents tend to overestimate the possibility that their own child is addicted to games, and their perceptions of game addiction are based on a narrow range of behavioral symptoms. Additional analyses indicate that parental monitoring of teenagers' game use can be predicted by the theoretical model driven from Ajzen(1991)'s theory of planned behavior. Finally, results also indicate that, in order to deal with the problems associated with teenagers' game use, proactive approaches to promote healthy game cultures as well as various initiatives to prevent problematic game use are necessary. Implications of the findings and future direction were discussed.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.1-23
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• 2023

The purpose of this study is to analyze the characteristics of the integrated search services for integrated libraries operated by local governments in Korea. The target of analysis was integrated libraries operated by 25 local governments in Seoul, and the analysis elements were selected from service functions in 12 areas related to integrated search. The results of the study are as follows. First, the integrated library is an association of public libraries and small libraries in autonomous districts and provides integrated search services. The provided integrated search service function, types of bibliographic information, and facets are not diverse. Second, the records in the search results were mostly item types, not title types. Third, enrichment information supplementing book information consists of book introductions, related information, book-related keywords, and loan-related information. Fourth, integrated search shows the form of integrated OPAC based on integrated catalog DB rather than discovery-type search. It concentrates on providing an integrated search for catalog DBs distributed in public libraries or small libraries in the autonomous district. Fifth, most integrated libraries provide similar service types. Based on these results, improvement plans were proposed for domestic public libraries to expect discovery-type integrated search services.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.50-60
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• 2022

In this study, habitat suitability was analyzed for three major honey tree species, namely Kalopanax septemlobus, Tilia amurensis, and Styrax obassis, in the Baekdudaegan Mountains using MaxEnt models. The AUC values indicating the prediction accuracies of the models were 0.747, 0.790, and 0.755 for K. septemlobus, T. amurensis, and S. obassis, respectively. The most important variables for K. septemlobus and T. amurensis were elevation, mean annual temperature, and slope, whereas mean annual temperature, elevation, and mean annual precipitation were the most important predictors for S. obassis. For all three studied species, elevation and mean annual temperature were the most important topographic and climatic factors, respectively, indicating that such variables are crucial for explaining species distribution. Honey tree species are essential resources in forest beekeeping, a high value-added process for improving forest income, and this study identified sites with the potential for management of such species in the Baekdudaegan Mountains, where it may be possible to establish a honey forest. However, the accuracy of the models should be improved through comprehensive analysis with abiotic variables, such as soil properties and aridity, which affect the distribution of honey tree species, as well as biotic variables, such as interspecific competition.

• Journal of Korea Entertainment Industry Association
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• v.6 no.4
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• pp.82-92
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• 2012

Recently people who enjoy social game via mobile devices significantly are increasing depending on the rapid adoption of smart phones and the development of the network such as LTE. Most of them are enjoying the casual gaming mobile social games that you are able to play easily, but social issues like health problems due to long play time are emerging. The users, however, do not last long because of the simplicity of the game, and there are few people who actually buy game items even though they play it long time. This study has been conducted aiming to overcome such difficulties. This study suggests ways to generate constantly revenue avoiding short-term box-office after the release of mobile social games based on the analysis for market trend and profitability of the mobile social game. In addition, by applying profitability model analyzed to Japan's most successful game practices, this paper suggests the concrete methods about the commitment of the users. For summarizing the main achievements of this paper, providing the latest market information about mobile social games, analysis of profitability, practical implications for the commitment of the users are presented.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.19-31
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• 2021

This study tried to identify the characteristics of college students' entrepreneurial intentions in the entertainment industry, focusing on existing literature studies. Based on this, it was intended to suggest realistic educational alternatives for university student start-ups and implications for start-up management to university start-up officials and those in charge of national start-up support policy. Therefore, the implications of this study are as follows. First, technology(item) for idea creation education, which is an essential element in the entertainment industry, how to connect ideas and products, technology methods that can increase content value, and user characteristics education within the entertainment industry will need to be continued. In addition, along with the idea education, it is necessary to increase the understanding of start-up business management such as financing, human resource management, marketing, and operation management, and furthermore, confidence education should be provided so that the possibility of success in an entertainment start-up and a sense of adventure in a new job can be developed. Second, the space and equipment necessary for start-up (club room, student start-up room, entertainment-related equipment, etc.) should be provided centering on the opinion survey of students who are interested in starting a business, and various regulations of universities and government for student start-up should be relaxed. will have to In addition, education for the formation of entrepreneurial knowledge inside and outside of the school, special lectures and consultations by experts, and on-the-spot education, etc., should be made to create more practical entrepreneurial knowledge. something to do. Third, for students wishing to start a business in the entertainment industry, it is necessary to inform their families about the field situation of the entertainment industry accurately so that their children can develop a positive perception rather than a negative perception when choosing a business field. In addition, by promoting various successful cases of college students to their families after starting a business, families should be encouraged so that their children can develop a challenging spirit about starting a business. Fourth, it should be possible to form continuous clubs or gatherings with friends who wish to start a business in the entertainment industry, and furthermore, an opportunity to listen to the opinions of friends who actually started a business through these meetings should be provided. In addition, the meeting and the formation of friends should create a place for discussion about writing a business plan, how to succeed in starting a business, and management of startups, and psychological stimulation activities should be conducted so that each other's will to start a business arises. Fifth, various knowledge related to start-up (methods for securing funds, management of start-up organizations, grasping information about the market in which they want to start a business, etc.) should be cultivated, and how to write a business plan for the various entertainment industry fields they want to start up. You will also need to train them to be practical. Also, based on this knowledge formation, students themselves should be able to respond to risks and changes that may occur in entrepreneurship. Lastly, it is necessary to increase the understanding of business start-up management, and various psychological stimulation activities are needed to make the confidence and fear of starting a business disappear.

• Science of Emotion and Sensibility
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• v.9 no.1
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• pp.49-61
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• 2006

The present mobile phone industry has significant effect on the domestic economy and has taken root as the core item that has the responsibility to lead the Korean economy for a considerable period of time. As the mobile phone market becomes gigantic, the mobile phone is being used by people in broader age bracket, and functions or designs preferred by people of various age are getting more diverse. Like that, as the mobile phone has greater effect on and meaning in our daily lives, consumers of mobile phone have growing expectation of the mobile phone Now, the core function of voice communication via the mobile phone is not a great concern to consumers. But the function, such as more convenient and friendly information input and output, processing and storage, and the design, which is more sophisticated and optimized for the user environment, are being demanded, not just the simple voice communication. And as the modern design is getting more similar to the objects of traditional high art consumed by consumers every day, the aesthetic aspect of design can play an important role, as the factor that differentiates the product, in creating new value which forms the spiritual and emotional value of human beings to improve the quality of living, and in addition, the willingness of consumers to buy is determined by the design that they prefer the most. Like that, a new design of mobile phone based on a new dimension and preferred by the consumers the most is urgently required to be developed by shedding light on the factors related to the preference of consumers on the basis of the analysis on the aesthetic aspect, which can be said to be the most critical factor in the design process. Therefore, this study aims to identity the common preference and different factors of aesthetic aspects through the analysis on the aesthetic aspects of the mobile phone preferred by users among countries, and figure out the formative artistic factors of aesthetic aspects that are considered to be important, in order to propose the guideline on the aesthetic aspect of mobile phone that can be applied to the design of mobile phone practically.

• Journal of Dairy Science and Biotechnology
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• v.27 no.2
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• pp.7-16
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• 2009

Appenzeller cheese samples were prepared by addition of 0.5, 1.0, and 2.0% green tea (Camellia sinensis, CS) powder and control cheese. We examined various quality characteristics of the novel cheese, such as viable-cell counts, pH, water-soluble nitrogen (WSN), non-casein nitrogen (NCN), non-protein nitrogen (NPN), and catechin level during maturation for 16 weeks at $14^{\circ}C$. To develop a Korean natural cheese containing green tea powder, we also analyzed the changes in the polyacrylamide gel electrophoresis pattern, chemical composition, and sensory qualities. The viable cell counts of the samples were not significantly different. Until the $3^{rd}$ week, the pH of the CS cheese decreased with an increase in the maturation time. However, the pH gradually increased by the $12^{th}$ week, while WSN, NCN, NPN also increased. The WSN, NCN, NPN, and catechin values for the CS cheese samples were significantly higher than the values for the control cheese. The polyacrylamide gel electrophoretic pattern of caseins for the CS cheese indicated that this cheese degraded more rapidly than the control cheese did. In the sensory evaluation, cheese with 1.0% CS powder showed the highest scores in taste and appearance and good scores in flavor and texture. These results indicate that 1.0% CS is the optimal value for addition to cheese, and cheese containing 1.0% CS shows good physiological properties and reasonably high overall sensory acceptability.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.3
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• pp.318-332
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• 2015

The maize production in South-eastern Asian countries showed a continuous increase with increasing poultry-livestock from the beginning of the 1990s to early 2010. Also the need for a new variety development of each contries was increased rapidly in the same period. Single-Cross hybrid varieties have been developed and supplied from 2001 instead of multi-cross maize varieties since 1992 in Indonesia. In Cambodia, CP group is mainly manufacturing feeds with most of the forage maize from farmers who are growing its seeds from the company. Cambodian main cultivars are varieties of multinational corporations such as DK8868 from Monsanto, NK6326, NK7328 from Syngenta and CP333 from CP group including local business company. Vietnam is the main maze importing country in South-Eastern Asia which had imported 13 times scale of amount compared to exports in average from 1990 to 2011. Vietnamese government has developed a range of varieties for improving their efficiency in production, such as the LVN-10 with political investments. Their production has been reached to 80% of the total. According to the 2012 MIFAFF (Ministry for Food, Agriculture, Forestry and Fisheries) data in Korea, domestic edible maize cultivation area was approximately 15,000ha. It showed 74,399 tons of production, 3.8% of food self-sufficiency in maize and around 0.9% of grain self-sufficiency rate. The consumption of grain is mostly rely on imports in Korea. To overcome the limit of the domestic seed market and increase maize self-sufficiency, the need to develop maze varieties for world-class is increasing at present through analyzing the market trend and prospect of the seed industry in South-eastern Asia.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.1-16
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• 2015

Traffic accident is one of the major cause of death worldwide for the last several decades. According to the statistics of world health organization, approximately 1.24 million deaths occurred on the world's roads in 2010. In order to reduce future traffic accident, multipronged approaches have been adopted including traffic regulations, injury-reducing technologies, driving training program and so on. Records on traffic accidents are generated and maintained for this purpose. To make these records meaningful and effective, it is necessary to analyze relationship between traffic accident and related factors including vehicle design, road design, weather, driver behavior etc. Insight derived from these analysis can be used for accident prevention approaches. Traffic accident data mining is an activity to find useful knowledges about such relationship that is not well-known and user may interested in it. Many studies about mining accident data have been reported over the past two decades. Most of studies mainly focused on predict risk of accident using accident related factors. Supervised learning methods like decision tree, logistic regression, k-nearest neighbor, neural network are used for these prediction. However, derived prediction model from these algorithms are too complex to understand for human itself because the main purpose of these algorithms are prediction, not explanation of the data. Some of studies use unsupervised clustering algorithm to dividing the data into several groups, but derived group itself is still not easy to understand for human, so it is necessary to do some additional analytic works. Rule based learning methods are adequate when we want to derive comprehensive form of knowledge about the target domain. It derives a set of if-then rules that represent relationship between the target feature with other features. Rules are fairly easy for human to understand its meaning therefore it can help provide insight and comprehensible results for human. Association rule learning methods and subgroup discovery methods are representing rule based learning methods for descriptive task. These two algorithms have been used in a wide range of area from transaction analysis, accident data analysis, detection of statistically significant patient risk groups, discovering key person in social communities and so on. We use both the association rule learning method and the subgroup discovery method to discover useful patterns from a traffic accident dataset consisting of many features including profile of driver, location of accident, types of accident, information of vehicle, violation of regulation and so on. The association rule learning method, which is one of the unsupervised learning methods, searches for frequent item sets from the data and translates them into rules. In contrast, the subgroup discovery method is a kind of supervised learning method that discovers rules of user specified concepts satisfying certain degree of generality and unusualness. Depending on what aspect of the data we are focusing our attention to, we may combine different multiple relevant features of interest to make a synthetic target feature, and give it to the rule learning algorithms. After a set of rules is derived, some postprocessing steps are taken to make the ruleset more compact and easier to understand by removing some uninteresting or redundant rules. We conducted a set of experiments of mining our traffic accident data in both unsupervised mode and supervised mode for comparison of these rule based learning algorithms. Experiments with the traffic accident data reveals that the association rule learning, in its pure unsupervised mode, can discover some hidden relationship among the features. Under supervised learning setting with combinatorial target feature, however, the subgroup discovery method finds good rules much more easily than the association rule learning method that requires a lot of efforts to tune the parameters.