• KOREAN JOURNAL OF CROP SCIENCE
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• v.32 no.2
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• pp.234-242
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• 1987

Rough rice samples of four rice varieties were collected from twenty five locations through the country just after 1986 rice growing season. Various characteristics related to rice grain quality were observed to clarify the degree of locational variation of physico-chemical properties, and cooking and eating quality of rice grains. Grain weight, grain shape, degree of translucency and chalkiness of rice grain, amylogram properties of rice flour, water uptake during cooking, and cooked rice appearance were different between varieties tested. High degree of locational variation were found in following characteristics, degree of translucency and chalkiness of rice grain, water uptake during cooking, cooked rice appearance and amylogram properties. Eating quality of cooked rice indicated by sensory score showed different tendency of locational variation between rice varie-ties tested, and locations produced rice grains showing better eating quality were not coinside with among varieties tested. Grain weight, degree of translucency and chalkiness of rice grain, and cooked rice appearance of rice samples showing better eating quality were quite different to rice grains showing poor eating quality. Rice having better eating quality of a japonica variety, Chucheong, showed higher value of peak and final viscosity, viscosity after cooling, consistency and set back on amylograph compared with those of poor eating quality rices, and break down value of better rice was lower than that of poor rice. However, a Tongil type variety, Taebaek, did not show any consistent difference between better and poor rices. Rice samples from six locations in Chucheong and four locations in Taebaek showed special properties on amylogram compared with other rices collected in this study.

• Korean Journal of Food Science and Technology
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• v.42 no.1
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• pp.33-38
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• 2010

This study was conducted to compare the physicochemical properties of powdered green teas produced in Korea and Japan including particle size, color, chlorophyll, caffeine and theanine. The average particle size of Korean powered green tea ($14.63-25.39\;{\mu}m$) was similar to that of Japanese powdered green tea ($15.46-21.02\;{\mu}m$). The surface color of shade-cultivated Haenam Green Tea (HN-1) had the highest negative 'a' value, which represents 'green' color. When the TCD (total color difference value) was measured in the samples, HN-1 was most similar to the premium powdered green tea of Japan (JA-1). Domestic shade-cultivated powdered green teas had 1.5-2 times greater chlorophyll content than powdered green teas produced from plants that were not cultivated in the shade. The presence of chlorophyll a resulted in a higher intensity of green color than the presence of chlorophyll b. A significant negative correlation was also observed between the color and the chlorophyll a, chlorophyll b and total chlorophyll contents. Specifically, chlorophyll a had the greatest impact on the green color of powdered green tea. The content of catechins, caffeine and theanine in Korean powdered green teas ranged from 14.679-20.128, 1.496-3.237 and 0.926-1.977 g/100 g, respectively. The caffeine and theanine contents were high in shade-cultivated powdered green teas. Based on the above results, domestic powdered green teas cultivated under shaded conditions had a quality similar to that of medium-quality green teas produced in Japan, and the overall quality of Korean powdered green tea was poorer than that of Japanese powdered green tea.

• Food Science and Preservation
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• v.18 no.5
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• pp.729-738
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• 2011

This study was conducted to investigate the effect of extruded pellets (EP) containing different levels of protein (51%-55%) and lipid (9%-15%) on flesh quality of flounder (Paralichthys olivaceus) comparing with raw fish-based moist pellet (MP). Two replicate groups of 40 fish per each tank (initial mean weight 106 g) were fed one of three experimental EP (EP1, EP2 and EP3) containing different protein and lipid levels, a commercial EP (EP4) and MP for 16 weeks. Moisture content of fish fed MP was significantly higher than that of fish fed all EP. Significantly higher contents of 16:1n-7, 20:4n-6, 20:5n-3 and lower 18:2n-6 were observed in fish fed EP4 and MP compared with fish fed EP1, EP2, EP3. The 22:6n-3 content was not significantly different among all groups. Taurine content of fish fed MP was significantly higher than that of fish fed all EP. Asparagine content of fish fed EP1 was significantly higher than that of fish fed EP2, EP, EP4 and MP. Significant difference were observed in lysine and serine contents of fish fed experimental diets. In nucleotides and their related compounds, ATP and AMP content was not affected by diets. Significant difference were observed in IMP contents of fish fed experimental diets. Textural properties, no significant difference was observed among the fish groups fed different diets.

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.33-60
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• 2020

Along with the rapid advance in internet technologies, ubiquitous mobile device usage has enabled consumers to access real-time information and increased interaction with others through various social media. Consumers can now get information more easily when making purchase decisions, and these changes are affecting the brand landscape. In a digitally connected world, brand image is not communicated to the consumers one-sidedly. Rather, with consumers' growing influence, it is a result of co-creation where consumers have an active role in building brand image. This explains a reality where people no longer purchase products just because they know the brand or because it is a famous brand. However, there has been little discussion on the matter, and many practitioners still rely on the traditional measures of brand indicators. The goal of this research is to present the limitations of traditional definition and measurement of brand and brand image, and propose a more direct and adequate measure that reflects the nature of a connected world. Inspired by the proverb, "A man is known by the company he keeps," the proposed measurement offers insight to the position of brand (or brand image) through co-purchased product networks. This paper suggests a framework of network analysis that clusters brands of cosmetics by the frequency of other products purchased together. This is done by analyzing product networks of a brand extracted from actual purchase data on Amazon.com. This is a more direct approach, compared to past measures where consumers' intention or cognitive aspects are examined through survey. The practical implication is that our research attempts to close the gap between brand indicators and actual purchase behavior. From a theoretical standpoint, this paper extends the traditional conceptualization of brand image to a network perspective that reflects the nature of a digitally connected society.

• The Korean Journal of Food And Nutrition
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• v.10 no.4
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• pp.514-520
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• 1997

The study was carried out to investigate the changes of quality and to determine the optimal shelf-life of fried soybean curd under low temperature(8$\pm$2$^{\circ}C$) and room temperature(25-3$0^{\circ}C$), respectively. The quality criteria for fried soybean were acid value, peroxide value, fatty acid composition and microbial concentration, et al. The initial moisture content of fried soybean curd was 41.9%, it was rapidly decreased to 29.6% until the second days under low temperature. The pH value was 5.7 and 5.8 at the ninth days under 8$\pm$2$^{\circ}C$ and the sixth days under 25-3$0^{\circ}C$, respectively. Also, the acid value rised remarkly to 10.65 at the fifth days and the peroxide value was 12.20 at the sixth days under room temperature. The viable cell counts were 1.0$\times$1.0 at the initial storage, but they were increased to 6.1$\times$105 over at the second days of room temperature. Moreover, the mold colony counts were in 2.0$\times$10-6.0$\times$103 and 2.0$\times$10=8.5$\times$107 during all storage days under 8$\pm$2$^{\circ}C$ and 25-3$0^{\circ}C$, respectively.

• Food Science of Animal Resources
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• v.22 no.3
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• pp.240-246
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• 2002

The seasoned pork with soy sauce(SS) or Kochujang(SK) was manufactured using hind and fore leg as main raw material and the quality characteristics and shelf-life were investigated during storage at 5$\^{C}$ and 10$\^{C}$ after having packaged with air. The initial total aerobic plate counts(APC) of SS and SK were 5.24 and 5.75 log10 CFU/㎠, respectively. APC exceeded 7 log10CFU/cm2 after 10 days at 5$\^{C}$ and 6 days at 10$\^{C}$ far SS, and after 6 days at 5$\^{C}$ and 4 days at 10$\^{C}$ for SK, respectively. In the sensory test, the SS samples stored at 5$\^{C}$ and 10$\^{C}$ were assessed as lower than 3.0 points, the criterium of consumer acceptability, after 10 and 8 days, respectively. In the case of SK samples, the point of this time was at day 10 and 6, respectively when they were stored at 5$\^{C}$ and 10$\^{C}$. As storage time extended, pH and water content tended to decrease. Contrarily, the increase of TBA and VBN values was observed during storage and this was more pronounced at 10$\^{C}$ than at 5$\^{C}$ . The oxygen concentration in the package was 19.8 and 19.9% each for 55 and SK samples at the beginning but it was gradually decreased thereafter. On the other hand, the concentration of carbon dioxide was increased with the extension of storage. Based on the above results, the shelf-lives of seasoned pork were estimated to be 8 days for SS and SK stored at 5$\^{C}$ and 6 days for SS and 4 days for SK stored at 10$\^{C}$.

• Cartoon and Animation Studies
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• s.28
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• pp.155-180
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• 2012

This article is to propose a conceptual framework for the One Source Multi Use (OSMU) strategic model of culture content. In this study, OSMU is defined as a series of marketing activities to increase the value created by culture content. The framework of brand equity strategy is applied to develop the strategic model of OSMU, as both share the same goal - maximization of long term value created by brand or culture content. This article suggests the brand identity-based OSMU strategic model, in which the brand identity of culture content guides, integrates, and coordinates every decision-making of OSMU activities. For the maximization of brand equity value of culture content, the copyright holder of original content should decide the content's brand identity, which should provide the criteria of all decision makings regarding window strategy, adaptation of content to other genre, and merchandising. This brand identity-based OSMU strategic model can not only contribute to the sales of OSMU content, but also the creation of high equity culture content in the long run. Also, the model allows monitoring and evaluation of content's brand equity, which can be used for the strategic adjustment for the sake of long term value of the content. This study is differentiated from previous study on OSMU and expected to invigorate the further discussion on OSMU in several points. First, it broadens the scope of OSMU discussion as it views OSMU as a series of process including feedback. Second, this study points out the need for integration and coordination of various OSMU activities. Third, the strategic focus is laid on the value maximization of the original content, not 'multi used' content. Fourth, the suggested model emphasize the strategic role of copyright holder who takes the charge of the content brand management. Fifth, the model requires discussion on the components of marketing communication in addition to the content itself, which means the model includes the prospects, not only the content consumers, as the major future source for value creation.

• Restorative Dentistry and Endodontics
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• v.30 no.2
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• pp.128-137
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• 2005

In this study we measured the amount of light energy that was projected through the tooth material and analyzed the degree of polymerization by measuring the surface hardness of composites. For polymerization, Optilux 501 (Demetron, USA) with two types of light guide was used: a 12 mm diameter light guide with 840 nW/$cm^2$ light intensity and a 7 mm diameter turbo light guide with 1100 nW/$cm^2$. Specimens were divided into three groups according to thickness of penetrating tooth (1 mm, 2 mm, 0 mm). Each group was further divided into four subgroups according to type of light guide and curing time (20 seconds, 40 seconds). Vickers' hardness was measured by using a microhardness tester. In 0 mm and 1 mm penetrating tooth group, which were polymerized by a turbo light guide for 40 seconds, showed the highest hardness values. The specimens from 2 mm penetrating tooth group, which were polymerized for 20 seconds, demonstrated the lowest hardness regardless of the types of light guides (p < 0.05). The results of this study suggest that, when projecting tooth material over a specified thickness, the increase of polymerization will be limited even if light intensity or curing time is increased.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.195-211
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• 2010

An exhibition is defined as market events for specific duration to present exhibitors' main product range to either business or private visitors, and it also plays a key role as effective marketing channels. Especially, as the effect of the opinions of the visitors after the exhibition impacts directly on sales or the image of companies, exhibition organizers must consider various needs of visitors. To meet needs of visitors, ubiquitous technologies have been applied in some exhibitions. However, despite of the development of the ubiquitous technologies, their services cannot always reflect visitors' preferences as they only generate information when visitors request. As a result, they have reached their limit to meet needs of visitors, which consequently might lead them to loss of marketing opportunity. Recommendation systems can be the right type to overcome these limitations. They can recommend the booths to coincide with visitors' preferences, so that they help visitors who are in difficulty for choices in exhibition environment. One of the most successful and widely used technologies for building recommender systems is called Collaborative Filtering. Traditional recommender systems, however, only use neighbors' evaluations or behaviors for a personalized prediction. Therefore, they can not reflect visitors' dynamic preference, and also lack of accuracy in exhibition environment. Although there is much useful information to infer visitors' preference in ubiquitous environment (e.g., visitors' current location, booth visit path, and so on), they use only limited information for recommendation. In this study, we propose a booth recommendation methodology using Sequential Association Rule which considers the sequence of visiting. Recent studies of Sequential Association Rule use the constraints to improve the performance. However, since traditional Sequential Association Rule considers the whole rules to recommendation, they have a scalability problem when they are adapted to a large exhibition scale. To solve this problem, our methodology composes the confidence database before recommendation process. To compose the confidence database, we first search preceding rules which have the frequency above threshold. Next, we compute the confidences of each preceding rules to each booth which is not contained in preceding rules. Therefore, the confidence database has two kinds of information which are preceding rules and their confidence to each booth. In recommendation process, we just generate preceding rules of the target visitors based on the records of the visits, and recommend booths according to the confidence database. Throughout these steps, we expect reduction of time spent on recommendation process. To evaluate proposed methodology, we use real booth visit records which are collected by RFID technology in IT exhibition. Booth visit records also contain the visit sequence of each visitor. We compare the performance of proposed methodology with traditional Collaborative Filtering system. As a result, our proposed methodology generally shows higher performance than traditional Collaborative Filtering. We can also see some features of it in experimental results. First, it shows the highest performance at one booth recommendation. It detects preceding rules with some portions of visitors. Therefore, if there is a visitor who moved with very a different pattern compared to the whole visitors, it cannot give a correct recommendation for him/her even though we increase the number of recommendation. Trained by the whole visitors, it cannot correctly give recommendation to visitors who have a unique path. Second, the performance of general recommendation systems increase as time expands. However, our methodology shows higher performance with limited information like one or two time periods. Therefore, not only can it recommend even if there is not much information of the target visitors' booth visit records, but also it uses only small amount of information in recommendation process. We expect that it can give real?time recommendations in exhibition environment. Overall, our methodology shows higher performance ability than traditional Collaborative Filtering systems, we expect it could be applied in booth recommendation system to satisfy visitors in exhibition environment.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.