• Textile Coloration and Finishing
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• v.17 no.2 s.81
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• pp.10-18
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• 2005

Silk fabrics mordanted with $Fe^{2+},\;Ni^{2+},\;and\;Cu^{2+}$ were dyed with the aqueous extract of Cassia tora L. seed which was known to include water soluble colorant kaempferol, one of flavonol compounds. Kaempferol can react with free radicals and chelate transition metal ions, which is thought to catalyze processes leading to the appearance of free radicals and have antioxidant activity. In relation to the coordinating and chelating mechanism of the ions with the silk protein and kaempferol, reasonable conclusions should be made on the colorant uptake and the water fastness of the fabric. The amount of the colorant on the fabric was in the order of $Fe^{2+}>Ni^{2+}>Cu^{2+}$. In case of dyeing through coordinaiton bonds between transition metal ions and silk protein and colorants, it was thought that the ions with the smaller secondary hydration shell, the higher preference to the atoms of the ligand coordinated, and the suitable bonding stability for the substitution of primarily hydrated water molecules for colorants led to the higher colorant uptake. The water fastnsess of the fabric was in the order of $Fe^{2+}>Cu^{2+}>Ni^{2+}$. It should be reasonable to choose transition metal ions with weak and strong tendency to the ionic and the coordination bond, respectively, to the carboxylate anion of the silk protein. Although further research needs to be done, the conclusions above may be generally applied to the natural dyeing through the coordination bond mechanism between transition metal ions and colorants and substrates.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.125-144
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• 2006

The development of mobile applications is fast in recent years. However, nearly all applications are for messaging, financial, locating services based on simple interactions with mobile users because of the limited screen size, narrow network bandwidth, and low computing power. Processing an algorithm for supporting a group decision process on mobile devices becomes impossible. In this paper, we introduce the mobile-oriented simple interactive procedure for support a group decision making process. The interactive procedure is developed for multiple objective linear programming problems to help the group select a compromising solution in the mobile Internet environment. Our procedure lessens the burden of group decision makers, which is one of necessary conditions of the mobile environment. Only the partial weak order preferences of variables and objectives from group decision makers are enough for searching the best compromising solution. The methodology is designed to avoid any assumption about the shape or existence of the decision makers' utility function. For the purpose of the experimental study of the procedure, we developed a group decision support system in the mobile Internet environment, MOBIGSS and applied to an allocation problem of investor assets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.285-292
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• 2020

Despite the government's constant exertions on making a win-win environment through positive discrimination for small and medium-sized companies and local companies, they are suffering from order polarization, weak competitiveness to win a project, and low profitability in highly competitive market situations resulting from the contraction of the construction market. This study examined the U.S. policy and regulations on protecting the relatively weak entities in the construction industry, focused on a goaling program, setting aside the bid preference for small and middle-sized companies and local companies. From benchmarking, some implications were drawn to reconsider the goal of policy and regulations for small and medium-sized companies and local companies. In conclusion, unlike domestic positive discrimination regulations, which are based on the concept of market sharing that can allow a paper company to survive, those of the U.S. are based on the principle of fair competitiveness, and also provide a certain degree of advantage for small and medium-sized companies and local companies. Therefore, the domestic positive discrimination policy and regulations for small and medium-sized companies and local companies need to be reconsidered toward the direction of not only protecting them but also to strengthen their competitiveness in the market.

• Cross-Cultural Studies
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• v.22
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• pp.203-221
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• 2011

With the beginning of systemized research on Latin American region as a part of the third world in the mid-60s, Latin American regional studies in Korea acquired a steppingstone for development through the establishment of Hankook University of Foreign Studies Central & South American Regional Study, the creation of Central & South America Research Center, and Latin American Society established in the mid-80s. Latin American regional studies achieved quantitative and qualitative growth with the natioal globalization policy in the 90s, and research centers related to Latin America in Seoul National University, Pusan University of Foreign Studies, Dankook University, and Sunmoon University have contributed to the activation of regional studies. In spite of such achievements, Latin American regional studies, which have developed with 40 years of history, still possess problems that need to be solved. This study achieves qualitative analysis on theses published from 2000 to March 2001 in main Latin America regional study academic journals in Korea to analyze Latin American regional study trend of the recent 10 years in order to search measures for activating Latin American regional studies. Academic journals used in analysis include "Ibero America Research" of Seoul National University Research Center of Central & South America, Spain, "Central & South America Research" of Hankook University of Foreign Studies Research Center of Central & South America, "Ibero America Research" of Pusan University of Foreign Studies Central & South America Center, and "Latin America Research" published by Latin American Society. According to analysis on publication ratio of published theses according to field, it was presented that culture and politics fields occupied the highest ratio. Social and cultural fields, the elementary studies of regional research which have previously presented a weak research tendency, have achieved noticeable development during the past 10 years. According to analysis on researched nations, Latin America regional study was weighted in particular nations, and nations of economic size and political influence within region were selected as main subjects of research. Furthermore, several nations were not researched at all. For the last 10 years, the depth and width of the Latin America regional study had been decided by the degree of political, economic, social, and cultural significance occupied by the nation. It can be said that studies based on overall understanding on regional countries of Latin America have been relatively weak in individual nation study. Furthermore, studies that separate issues to achieve analysis based on the awareness theory of individual branches can be regarded dominant among studies based on entire Latin America. These studies still possess limitations in failing to deviate from the outline of particular region and topic.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.669-675
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• 2002

In recent years most of personalized recommender systems in electronic commerce utilize collaborative filtering algorithm in order to recommend more appropriate items. User-based collaborative filtering is based on the ratings of other users who have similar preferences to a user in order to predict the rating of an item that the user hasn't seen yet. This nay decrease the accuracy of prediction because the similarity between two users is computed with respect to the two users and only when an item has been rated by the users. In item-based collaborative filtering, the preference of an item is predicted based on the similarity between the item and each of other items that have rated by users. This method, however, uses the ratings of users who are not the neighbors of a user for computing the similarity between a pair of items. Hence item-based collaborative filtering may degrade the accuracy of a recommender system. In this paper, we present a new approach that a user's neighborhood is used when we compute the similarity between the items in traditional item-based collaborative filtering in order to compensate the weak points of the current item-based collaborative filtering and to improve the prediction accuracy. We empirically evaluate the accuracy of our approach to compare with several different collaborative filtering approaches using the EachMovie collaborative filtering data set. The experimental results show that our approach provides better quality in prediction and recommendation list than other collaborative filtering approaches.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Korean Journal of Food Science and Technology
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• v.48 no.5
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• pp.461-465
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• 2016

In order to prevent the blackening and texture softening of heated shrimp, the pH was adjusted by soaking shrimps in acidic and alkali solutions, and their qualities were evaluated. The lightness of shrimps pretreated with 0.2% (w/w) citric acid and 0.05% (w/w) ascorbic acid solution increased by 20% compared to that of the control. The strength of mechanical hardness of shrimps soaked in acetic acid and phosphate solution (pH 6.0) was significantly higher ($1209g_f$) compared to that of untreated shrimp ($801g_f$; p<0.05), and the overall preference of texture was 0.4 points higher than that of the control in the descriptive sensory evaluation (p<0.05). In contrast, soaking in solution of pH 8 exhibited a weak texture hardening effect ($855g_f$). Additionally, the hardness of the heated shrimp after soaking at an adjusted pH of 4.0 increased to $4046g_f$, but the yield based on weight decreased to 38% compared to that of untreated shrimp (70%; p<0.05).