• Proceedings of the Korean DIstribution Association Conference
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• 2005.05a
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• pp.383-405
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• 2005

The traditional market is foremost a regionally positioned place, wherein the market directly represents regional and cultural centered traits while it plays an important role in the circulation of facilities through reciprocal, informative and cultural exchanges while sewing to form local communities. The traditional market in Korea is one of representative retail businesses and premodern marketing techniques by family owned business of less than five members such as product management, purchase method, and marketing patterns etc. Since the 1990s, the appearance of new circulation-type businesses and large discount convenience stores escalated the loss of traditional competitiveness, increased the living standard of customers, changed purchasing patterns, and expanded the ubiquity of the Internet. All of these changes in external circulation circumstances have led the traditional markets to lose their place in the economy. The traditional market should revive on a regional site basis through the formation of a community of regional neighbors and through knowledge-sharing that leads to the creation of wealth. For the purpose of creating a wealth in a place, the following components are necessary: 1) a facility suitable for the spatial place of the present, 2)trust built through exchanges within the changing market environment, which would simultaneously satisfy customer's desires, 3) international bench marking on cases such as regionally centered TCM (England), BID (USA), and TMO (Japan) so that the market unit of store placement transfers from a spot policy to a line policy, 4)conversion of communicative conception through a surface policy approach centered around a macro-region perspective. The budget of the traditional market funding policy was operational between 2001 and 2004, serving as a counter move to solve the problem of the old traditional market through government intervention in regional economies to promote national economic strength. This national treasury funding project was centered on environmental improvement, research corps, and business modernization through the expenditure of 3,853 hundred million won (Korean currency). However, the effectiveness of this project has yet to be to proven through investigation. Furthermore, in promoting this funding support project, a lack of professionalism among merchants in the market led to constant limitations in comprehensive striving strategies, reduced capabilities in middle-and long-term plan setup, and created reductions in voluntary merchant agreement solutions. The traditional market should go beyond mere physical place and ordinary products creative site strategies employing the communicative approach must accompany these strategies to make the market a new regional and spatial living place. Thus, regarding recent paradigm changes and the introduction of region-based site functions into the traditional market, acquiring a conversion of direction into the newly developed project is essential to reinvestigate the traditional market composed of cultural and economic meanings, for the purpose of the research. Excavating social policy demands through the comparative analysis of domestic and international cases as well as innovative and expert management leadership development for NPO or NGO civil entrepreneurs through advanced case research on present promotion methods is extremely important. Discovering the seeds of the cultural contents industry cored around regional resource usages, commercializing regionally reknowned products, and constructing complex cultural living places for regional networks are especially important. In order to accelerate these solutions, a comprehensive and systemized approach research operated within a mentor academy system is required, as research will reveal distinctive traits of the traditional market in the aging society.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Molecules and Cells
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• v.26 no.5
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• pp.443-453
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• 2008

The Bric-a-brac, Tramtrack, Broad-complex (BTB) domain is a protein-protein interaction domain that is found in many zinc finger transcription factors. BTB containing proteins play important roles in a variety of cellular functions including regulation of transcription, regulation of the cytoskeleton, protein ubiquitination, angiogenesis, and apoptosis. Here, we report the cloning and characterization of a novel human gene, KLHL31, from a human embryonic heart cDNA library. The cDNA of KLHL31 is 5743 bp long, encoding a protein product of 634 amino acids containing a BTB domain. The protein is highly conserved across different species. Western blot analysis indicates that the KLHL31 protein is abundantly expressed in both embryonic skeletal and heart tissue. In COS-7 cells, KLHL31 proteins are localized to both the nucleus and the cytoplasm. In primary cultures of nascent mouse cardiomyocytes, the majority of endogenous KLHL31 proteins are localized to the cytoplasm. KLHL31 acts as a transcription repressor when fused to GAL4 DNA-binding domain and deletion analysis indicates that the BTB domain is the main region responsible for this repression. Overexpression of KLHL31 in COS-7 cells inhibits the transcriptional activities of both the TPA-response element (TRE) and serum response element (SRE). KLHL31 also significantly reduces JNK activation leading to decreased phosphorylation and protein levels of the JNK target c-Jun in both COS-7 and Hela cells. These results suggest that KLHL31 protein may act as a new transcriptional repressor in MAPK/JNK signaling pathway to regulate cellular functions.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.8
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• pp.1165-1171
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• 2015

In this study, we examined the effects of cultivation adaptability and product quality of aronia (fruit of Aronia melanocarpa) cultivated in various domestic regions. Extracts of aronia cultivated in various domestic regions and Poland were measured for their total sugar contents, acidities, total polyphenol contents, anthocyanin contents, and antioxidant activities using 1,1-diphenyl-2-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays. Our results showed that aronia extracts from the two countries had similar sugar contents, acidities, and anthocyanin contents. Anthocyanin is an important functional component of Aronia melanocarpa. Extracts of aronia from the two countries contained cyanidin-3-galactoside (65.5~69.1%) as the major anthocyanin compound. Aronia cultivated in C region showed higher polyphenol content (121.5%) than Poland aronia and we measured of antioxidant activities by DPPH ($IC_{50}$) and FRAP assay. Aronia cultivated in C region showed the highest antioxidant activity and polyphenol contents. Cultivation conditions of C region had sufficient sunshine and soil with pH of 6.5. From the above results, Korean aronia had similar activities with Poland aronia, which suggests that it can be a new potential development source and high technological foods.

• Cartoon and Animation Studies
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• s.33
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• pp.293-315
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• 2013

The number of French movies imported to and released in S. Korea is constantly increasing. All French movies released in Korean theatres, however, are not a great success. For the domestic film market and audiences, the idea French cinema is generally equivalent to 'diversity cinema' or 'arthouse films' is common notion. In this respect, French movies introduced throughout the country would be culture product into which one can read other cultural significances different from that of domestic cinema, and also serve significant cultural value to understand diversity in cinema, for domestic audiences. However, it could be said that French movies, in common with Hollywood films, obey rules in the film industry and needs for audience trends. In this content, what the researchers want to do is to analysis the tendency of the domestic audience reception and main causes of commercial success in the domestic film market, analysing Taken produced in France. The analysis, most of all, suggests the consideration for the film industry beside the notion of cultural diversity in cinema, as imported films are released in the domestic theatre. For this, the study examines the promotional strategy the french cinema perceived generally as the arthouse film applies extensively, analysing on Taken, and inquires into factors of commercial success, using SWOT Analysis. This study, the first of all, (briefly) examines what audiences consider when they choose a film to watch, articulating (generally) the choice-and-consume modality of the domestic audience. And then, it examines dominant factors Taken was a commercial success in domestic film market, even though the film is a french film, using SWOT Analysis. On the basis of SWOT Analysis, finally, this study draws up promotional plan for Taken, and shed new light on dominant preconditions, when the foreign cinema would be imported from the now on.

• Cartoon and Animation Studies
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• s.33
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• pp.597-616
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• 2013

Character industry is not only knowledge-based industry chiefly with copyrights but also motive power for creative economy to take a role functionally over the fields of industries because it has industrial characteristic as complement product to promote sale value in manufacturing industry and service industry and increase profit on sales. Since 2003, the national policy related to character has aimed to maximize effect among connected industries, extend its business abroad, enforce copyrights through the improvement of marketing system, develop industrial infrastructure through raising quality of character products. With the result of this policy, the successful cases of connected contents have been crystallized and domestic character industry has stepped up methodically since 2007. It is needed to reset the scales of character industry and industrial stats because there are more know-how of self industry promotion and more related characters through strategy of market departmentalization starting with cartoon, animation, games, novels, movies and musicals. Especially, The Korea government set our target for 'Global Top Five Character Power' since 2009 and has started to carry out to find global star characters, support to establish network among connected industries, diversify promotion channels, and develop licensing business. Particularly, since 2013, There have been prospered the indoor character theme park with time management just like character experimental marketing or Kids cafes using characters, the demand market of digital character focusing on SNS emoticon, and the performance market for character musical consistently. Moreover, The domestic and foreign illegal black markets on off-line have been enlarged, so we need another policy alternative. To prepare for the era of exploding character demand market and diversifying platform, it is needed to set up a solid strategy that is required the elements of policy changes in character industry to vitalize character industry and support new character design and connected contents. the following shows that the elements of policy changes related to the existing policy, the current position of market. Nowadays, the elements of policy changes in domestic character industry are that variety of consumers in the digital character market according to platform diversification, Convergence contents of character goods for the Korean waves, legalization of the illegal black contents market, and controling the tendency of consumers in departmentalized market. This can help find the policy issue entirely deferent with the existing character powers like US, Japan or Europe. In its final analysis, the alternatives are the promotion of models with contract copyrights of domestic and foreign connected contents, the diversification of profit models of platform economy, the additive development of target market related to enlarging the Korean waves, and the strategy of character market for the age-specific tendency according to developing character demand market.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.297-302
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• 2017

Recently, building materials and air purification filters with eco-friendly charcoal are actively studying to reduce the concentration of radon gas in indoor air. In this study, radon reduction performance was assessed by designing and producing new panel-type activated carbon filter that can be handled more efficiently than conventional charcoal filters, which can reduce radon gas. For the fabrication of our panel-type activated carbon filter, first the pressed molding product after mixing activated carbon powder and polyurethane. Then, through diamond cutting, the activated carbon filter of 2 mm, 4 mm and 6 mm thickness were fabricated. To investigate the physical characteristics of the fabricated activated carbon filter, a surface area and flexural strength measurement was performed. In addition, to evaluate the reduction performance of radon gas in indoor, the radon concentration of before and after the filter passes from a constant amount of air flow using three acrylic chambers was measured, respectively. As a result, the surface area of the fabricated activated carbon was approximately $1,008m^2/g$ showing similar value to conventional products. Also, the flexural load was found to have three times higher value than the gypsum board with 435 N. Finally, the radon reduction efficiency from indoor gas improved as the thickness of the activated carbon increases, resulting in an excellent radon removal rate of more than 90 % in the 6 mm thick filter. From the experimental results, the panel-type activated carbon is considered to be available as an eco-friendly building material to reduce radon gas in an enclosed indoor environment.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• Journal of Life Science
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• v.18 no.8
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• pp.1090-1095
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• 2008

Marbling (intramuscular fat) is an important factor in determining meat quality in Korean beef market. A grain based finishing system for improving marbling leads to inefficient meat production due to an excessive fat production. Identification of intramuscular fat-specific gene might be achieved more targeted meat production through alternative genetic improvement program such as marker assisted selection (MAS). We carried out ddRT-PCR in 12 and 27 month old Hanwoo steers and detected 300 bp PCR product of the inducible cAMP early repressor (ICER) gene, showing highly gene expression in 27 months old. A 1.5 kb sequence was re-sequenced using primer designed base on the Hanwoo EST sequence. We then predicted the open reading frame (ORF) of ICER gene in ORF finder web program. Tissue distribution of ICER gene expression was analysed in eight Hanwoo tissue using realtime PCR analysis. The highest ICER gene expression showed in Small intestine followed by Longissimus dorsi. Interestingly, the ICER gene expressed 2.5 time higher in longissimus dorsi than in same muscle type, Rump. For gene expression analysis in high- and low marbled individuals, we selected 4 and 3 animal based on the muscle crude fat contents (high is 17-32%, low is 6-7% of crude fat contents). The ICER gene expression was analysed using ANOVA model. Marbling (muscle crude fat contents) was affected by ICER gene (P=0.012). Particularly, the ICER gene expression was 4 times higher in high group (n=4) than low group (n=3). Therefore, ICER gene might be a functional candidate gene related to marbling in Hanwoo.