• Food Science and Industry
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• v.54 no.4
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• pp.260-267
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• 2021

Nowadays kimchi is exported to 80 countries and can be easily found overseas, but the name "Korean Kimchi" has not been protected internationally. Korean kimchi need to be registered as a geographical indication and receive international protection in order to establish its status as the country of origin. With the revision of the Kimchi Industry Promotion Act in 2020, geographical indications were introduced for kimchi and a legal basis was in place to enable the geographical indication as "Korean Kimchi" or "Republic of Korea Kimchi." Although there are issues remaining between the current system and producers' associations, we should prioritize the geographical indication as a means of protecting the country's agricultural products. In addition, efforts should be made to improve the quality and product value of Korean kimchi so that it is also recognized as a global brand.

• Journal of Korea Multimedia Society
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• v.25 no.7
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• pp.945-952
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• 2022

In a market situation full of brands and products, packaging requires a differentiated design that reflects the needs and trends of the times, as well as the characteristics of the product. Therefore, in this study, through literature reviews, market research methods, questionnaire surveys, eye-tracking experiments, etc., we derived related research and current status of ramen package design, and visual expression elements that induce consumers' subjective perception and interest. As a result, the ramen package design was generally simplified and tended to visualize the spicy taste. Second, consumers buy bag ramen once a week on average at a large discount mart, consider the color of the ramen package design as important, and recognize that the aesthetics of the package design can improve quality. Finally, the spicy phrases and ramen illustrations were the first visual elements of the ramen package design, and for the longest time, attention was focused on the brand name.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2844-2853
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• 2023

A sophisticated Bayesian multilevel model for estimating group bias was developed to improve the utility of the ASTM E900-15 embrittlement trend curve (ETC) to assess the conditions of nuclear power plants (NPPs). For multilevel model development, the Baseline 22 surveillance dataset was basically classified into groups based on the NPP name, product form, and notch orientation. By including the notch direction in the grouping criteria, the developed model could account for TTS differences among NPP groups with different notch orientations, which have not been considered in previous ETCs. The parameters of the multilevel model and biases of the NPP groups were calculated using the Markov Chain Monte Carlo method. As the number of data points within a group increased, the group bias approached the mean residual, resulting in reduced credible intervals of the mean, and vice versa. Even when the number of surveillance test data points was less than three, the multilevel model could estimate appropriate biases without overfitting. The model also allowed for a quantitative estimate of the changes in the bias and prediction interval that occurred as a result of adding more surveillance test data. The biases estimated through the multilevel model significantly improved the performance of E900-15.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.1-6
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• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Information Systems Review
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• v.7 no.1
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• pp.97-113
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• 2005

This paper designed and implemented(programmed) a comparative shopping agent that helps consumers to shop at on-line shopping malls over Internet. At offline stores, as consumers usually tell a sales clerk about a manufacturer, functions and price range of an item they want to purchase, the sales clerk will show the products or relevant catalogues. Then the consumer will compare functions, design and prices of the product and buy it with the lowest price. PriceMeter, a comparative shopping agent, introduced in this paper, is designed best geared to this consumers' buying behavior. Basically, as consumers enter a manufacturer's name, price, features and etc. at a search window, PriceMeter will search the web and provide a list of product informations such as features and prices that meet the search conditions. Consumers can see the information in either a form of catalogue or a printing format. As consumers click specific items to examine closely, it will show prices and information about shopping malls that sell the requested items. Clicking a 'Buy' icon, the consumers will be transferred to the right web page at the linked shopping mall. The emergence of the comparative shopping agent will expedite a consumer-centered retailing economy in the age of e-commerce. As consumers are provided with a better set of product and shopping mall information, they can make better purchasing decisions and gain more bargaining power shifted from manufacturers(sellers). The presentation of this comparative shopping agent is intended to promote the consumer-centered B2C e-commerce.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.141-149
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• 2017

Numerous products are on the market every day and consumption is becoming increasingly polarized. Some products have been introduced to the market for the first time and others are the existing products that have upgraded performance. For companies, new products must be released constantly to prevent losing existing customers and to increase loyalty. However, when companies released new product, they communicate consumer brand name and core benefits of the new product. Moreover, if a new product fails, the amount that the company has to pay is bound to grow. So companies often use brand extension strategies that use the names of famous brands that are already loved by their customers for new products. In this study, the effect of extension similarity, time of release, and message type on brand extension was investigated. Result shows that using abstract messages rather than specific messages is more effective when similarities with existing brands are poor. In particular, the closer the release period is, the more effective these effects are. However, in case of extending the brand with high similarity products, it is effective to focus on concrete messages when the release time is near, and to communicate abstract messages when the release time is long. This result suggests that companies should take into consideration not only the similarity of extension but also the timing and characteristics of messages when extending the brand.

• Asia Marketing Journal
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• v.12 no.4
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• pp.183-201
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• 2011

In case of Aju capital, it adopted a strategy to use a single brand not two separate brands after M&A was completed. In order to implement this strategy, it has endeavored to effectively process the work of shifting existing marketing infrastructure of DAEWOO capital, the mergee, spending enough transition time for the brand migration. In the process of merging, Aju capital picked the strategy to use the brand of mergee first, which is the Daewoo Capital brand, and then took a transition time for a while to converge to the single brand of Aju capital. Putting another way, even if the M&A deal was completed back in 2005, it maximized the effect of launching its final brand "Aju capital" by capitalizing on the positive image of "Daewoo" during the transition time and changing its name just in the right moment. In a bid to implement this strategy successfully, it established a cautious but sophisticated brand migration strategy. 1) "Brand bridge" strategy through reinforcing brand power of "Naegeron", which is an individual product brand of Daewoo Capital 2) Establishing a good brand image through reinforcing customer satisfaction 3) It implemented and completed its brand transition initiative by going through the step of Aju Capital brand unification (from Sept 09 to present) Currently, the sales unit of Aju Capital is realizing quality growth through specialization. It's strategy is to construct a systematic sales portfolio in terms of both quality and quantity through product-by-product specialization where the existing practice was selling a variety of products in a single branch. Back in 2009, it opened a branch that specialize in imported cars and expanded its used car business to 6 specialized locations. Besides, the specialized locations for personal loan named "Naegeron" was expanded from 3 to 11 locations. Recently, it is expected that it will inject vigor to retail and corporate financing business alongside with its core business, which is auto financing.

• The Journal of the Korea Contents Association
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• v.19 no.11
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• pp.664-675
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• 2019

This study examined Korean sign Language of the linguistic form and the etymological forms about the origins of the Korean national sign languages. The general sign language has been shown through previous research all of place names from Chinese character except Seoul and Lmsil. And then, Sign language's form and origins which are current using in order to examine what kind of feature were analysed through interviews and publications in Korean association of the deaf people. As a result, it was analysed that was composed majority. indigenous sign language Korean place names were made and used by deaf than loan word character of Chinese characters, Hangul and loanword. When we consider that place names were correspond to a precious cultural heritage, representing the history with the culture and identity of the relevant area, we can worth of preservation and transmission to the abundant iconicity in the name of Sui. On the other hand the indigenous sign language korea place manes can worth deaf culture or korean sign language. Even lf geographical characteristics of area have been changed or local product was disappeared in this situation by The origin of sign language reach in modern time local specialty by geographical form lt continued over generation. This can be regarded as the Korean sign language of the form in the way of visual. lt will be very valuable heritage in the preservation deaf culture.

• Korean Journal of Food Science and Technology
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• v.30 no.4
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• pp.888-894
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• 1998

In order to investigate the radioprotective effect of Si-Wu-Tang (Korean name: Sa-Mul-Tang), a kind of traditional Oriental medicine as a blood-building decoction (Oriental medical concept: Bu-Xie), and Si-Jun-Zi-Tang (Korean name: Sa-Gun-Ja-Tang), one of the widely used Oriental herbal medicines as an energy tonic (Chinese medical concept: Bu-Qi). the jejunal crypt survival, endogenous spleen colony formation, and apoptosis in jejunal crypt cells were observed in irradiated mice. Jejunal crypts were protected by Si-Wu-Tang pretreated both per os (2 mg/mL of drinking water for 7 days, p<0.05) and intraperitoneally (1 mg/head, single injection at 24 hours before irradiation). Si-Wu-Tang adminstration before irradiation(1 mg/head, single injection at 24 hours before irradiation) resulted in an increase of the formation of endogenous spleen colony (p<0.005). The frequency of radiation-induced apoptosis in intestinal crypt cells was also reduced by pretreatment of Si-Wu-Tang (p<0.01). However, the radioprotective effect of Si-Jun-Zi-Tang was not as significant as that of Si-Wu-Tang. These results suggest that Si-Wu-Tang may be a useful radioprotective food, especially since it is a relatively nontoxic natural product.