• 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.

• Cartoon and Animation Studies
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• s.50
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• pp.327-347
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• 2018

From the end of the 18th century to the end of the 19th century, the late 19th century was a genre of a new art that was in contrast to the distribution between social class and low class, and it was also a popular culture that attempted to transform the late Joseon Dynasty's social class. It is no exaggeration to say that it is the origin of the Korean folk art, started as popular art concepts, use colorful techniques and decorations which doesn't yield to ordinary iconography. But, because of the attempt of this technique was used by lower class, the meaning of the idea was lowered from iconography to secular picture. Ethics character picture, passed on to the present from going through the upheaval cultural time, was started from secular picture and transformed into hyukpil time illustration, and it represented popular arts until now. This thesis aims to reflect the meaning, various visual expressions and the lifestyle of Ethics Character Picture of filial piety and brotherly love, which is a unique genre of popular arts. Also, propose to suggest about the kinetic typography using video media, and how the traditional ethics character picture, which are combined with video technology, effects to the advertisements. These kind of attempts will show the world about the korea's traditional contents, and through the various media information it can be recreated as national symbolic key words. Furthermore, its meaningful to pass down the noble and cultural Ethics Character Picture of filial piety and brotherly love to younger generations. And by realigning to modern expression, it is predicted that it will be significantly meaningful to pass down and make the younger generations to understand to spirit of the ancestors. This will allow various attempts to reconstruct various items of contents from Korea's traditional contents to new media content that merged with video media.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.3
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• pp.426-434
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• 2011

In order to increase the use of rice, ginseng Garaedduks and Topokki were made and the physicochemical and sensory properties were investigated. Topokki and Garaedduks were added with 0, 1, 3 and 5% ginseng powder and stored at $20^{\circ}C$ for 48 hours. The moisture contents were not different to the increasing amount of ginseng powder and increasing storage time for 48 hours. The moisture content of Garaedduks for control and 5% added ginseng powder were 48.08% and 49.62%, respectively. The L value in color of uncooked ginseng Garaedduk decreased according to the added amount of ginseng powder, and the b value in color increased significantly according to the added amount of ginseng powder and during 48 hours storage at $20^{\circ}C$. Textural analysis, measured using a texture analyzer, of Garaedduk revealed that hardness, cohesiveness, chewiness decreased significantly and adhesiveness increased according to the added amount of ginseng powder. In sensory evaluation, 5% ginseng Garaedduk (uncooked, cooked) scored higher in overall acceptability than those of the other samples. In cooking properties, water absorption and solid contents increased according to the added amount of ginseng powder. Therefore, Garaedduk containing 5% ginseng powder was the most preferable. These results implied that the degree of retrogradation of ginseng Garaedduk might be low due to its high dietary fiber content.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.31-43
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• 2022

Startups are recognized as the vitality of the economy, and countries are competing to attract competitive overseas entrepreneurs and startups to their own startup ecosystem. In this global trend, entrepreneurs cross the border without hesitation, expecting abundant available resources and a startup friendly environment. Despite the increasing frequency of start-up migration between countries, studies related to this are very rare. Therefore, this study has chosen the cross-border migration of startups between countries as a research topic, and those who have been involved in the cross-border entrepreneurial migration to South Korea as a research sample. This study consists of two stages. The first research stage hires a Delphi method to collect expert opinions and find major factors related to the global startup migration. Drawing on the prior literature on the regional startup ecosystem at the national level, this stage is to conduct expert interviews in order to discover underlying factors and subfactors important for global migration of startups. The second stage measures the importance of the factors and subfactors using the AHP model. The priorities of factors and factors were identified hiring the overseas entrepreneurs who moved to Korea as the AHP survey samples. The results of this study suggest some interesting implications. First, a group of entrepreneurs with nomadic tendencies was found in the trend of global migration of entrepreneurs. They had already started their own businesses with the same business ideas in multiple countries before settling down in Korea. Second, important unique factors and subfactors in the context of global start-up migration were identified. A good example is the government's support package, including start-up visas. Third, it was possible to know the priority of the factors and subfactors that influence the global migration of startups This study is meaningful in that it preemptively conducted exploratory research focusing on a relatively new phenomenon of global startup migration, which recently catches attention in the global startup ecosystem. At the same time, it has a limitation in that it is difficult to generalize the meanings found in this study because the research was conducted based on the case of South Korea

• Journal of the East Asian Society of Dietary Life
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• v.22 no.6
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• pp.744-757
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• 2012

This study was designed to obtain basic data for the globalization of Korean food and the expansion of food exports through contract foodservices. A survey of dietary habits and attitudes toward school foodservices was given to students in three American international schools served by a domestic contract foodservice management company located in Seoul and Gyeonggi area. The results showed an average of three meals taken daily 3.39 times for male students and 2.95 times for female students and the time required for a meal was about 24~26 minutes. The average breakfast frequency was 5.10 times(4.59 times for male students and 5.35 times for female students) and many students reported skipping breakfast due to a lack of time. The average weekly frequency of dining out was 1.78 times(2.15 times for male students and 1.60 times for female students). In all schools, irrespective of gender and grade, students responded that a desire for snacking was 'why they want to have cookies', and snacking hours were frequently listed as 'between noon and evening'. Many also responded that an unbalanced diet is the reason some snacks are 'not to their taste'. Overall, students were highly satisfied with the foodservice menu, although there was a significant difference in what was considered proper food temperature, proper food seasoning, suitable amounts of food, and freshness of food. Male and female students were specifically highly satisfied with the 'freshness of food materials' and 'variety of menu' respectively. Overall, all students were highly satisfied with the foodservice, including the 'cleanliness of tables and trays'.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.1
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• pp.119-132
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• 2014

This study analyzed the failure prediction model of the firms listed on the KOSDAQ by considering whether there are embezzlement, malpractice and the largest shareholder changes or not. This study composed a total of 166 firms by using two-paired sampling method. For sample of failed firm, 83 manufacturing firms which delisted on KOSDAQ market for 4 years from 2009 to 2012 are selected. For sample of normal firm, 83 firms (with same item or same business as failed firm) that are listed on KOSDAQ market and perform normal business activities during the same period (from 2009 to 2012) are selected. This study selected 80 financial ratios for 5 years immediately preceding from delisting of sample firm above and conducted T-test to derive 19 of them which emerged for five consecutive years among significant variables and used forward selection to estimate logistic regression model. While the precedent studies only analyzed the data of three years immediately preceding the delisting, this study analyzes data of five years immediately preceding the delisting. This study is distinct from existing previous studies that it researches which significant financial characteristic influences the insolvency from the initial phase of insolvent firm with time lag and it also empirically analyzes the usefulness of data by building a firm's fail prediction model which considered embezzlement/malpractice and the largest shareholder changes as dummy variable(non-financial characteristics). The accuracy of classification of the prediction model with dummy variable appeared 95.2% in year T-1, 88.0% in year T-2, 81.3% in year T-3, 79.5% in year T-4, and 74.7% in year T-5. It increased as year of delisting approaches and showed generally higher the accuracy of classification than the results of existing previous studies. This study expects to reduce the damage of not only the firm but also investors, financial institutions and other stakeholders by finding the firm with high potential to fail in advance.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.12
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• pp.1956-1964
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• 2009

Understanding ethical fashion consumers in Korea is essential for the expansion of the ethical fashion market. This study analyzed ethical consumers in Korea in an examination of the factors that influence ethical purchase behavior and attitudes. The differences between ethical fashion consumers and non-ethical fashion consumers were investigated using eight variables (perceived consumer effectiveness (PCE), self-direction, benevolence, universalism, social responsibility, perceived behavioral control, face saving, and group conformity). Data were collected by means of a questionnaire through both on-line and off-line surveys from April 20 to June 7, 2009. Only the respondents knowledgeable of ethical products or ethical consumption were asked to complete the questionnaire. A total of 494 samples were used for analyses. Using independent samples t-test, the differences in each variable between two groups were examined. There were significant differences between ethical fashion consumers and non-ethical fashion consumers in attitudes toward ethical consumption behavior, behavioral intention, PCE, self-direction, universalism, social responsibility, and face saving variables. The factors influencing attitude and behavior intention were investigated by step-wise regression analyses. For ethical fashion consumers, the attitudes to ethical consumption behavior were largely influenced by PCE and benevolence. Social responsibility was the most predictable variable in guiding behavioral intention. Behavioral intention was also influenced by benevolence and attitude. Group conformity was found to be negatively correlated with behavioral intention. The findings of this study provide significant guidance for marketers of ethical fashion products. This study is the start of ethical fashion consumer research in Korea and can develop into variable subfields in the future.