• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.413-419
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• 2002

본 연구의 목적은 품질경영시스템의 ISO 9000:2000/KS A 9000:2001 개정 규격 내용 및 요구사항을 살펴보는 한편, 우리나라 중소기업이 전환규격을 적용하는데 있어서 ERP PACKAGE를 이용하여 효과적인 품질경영시스템 구축 방안을 제시하기 위함이다. 본 연구에서는 업무 PROCESS와 품질 기록을 중심으로 ISO 9000:2000/KS A 9000:2001 개정 규격을 ERP PACKAGE에 접목하는 방법을 도출하였으며, 적용 사례로서 기계 제조업체의 구매업무를 중심으로 품질경영시스템 구축방안을 제시하였다. 본 연구의 결과는 다음과 같다. 첫째, 정형화된 업무 체계를 갖추어 업무 담당자간 혹은 부서간의 업무 마찰을 줄이고 여러부서에서 발생하는 업부 DATA를 중앙집중식으로 공유하여 동일한 DATA의 수집과 작성에 중복성을 최소화하는 등에서 업무의 효과가 있는 것을 볼 수 있다. 둘째, ERP PACKAGE를 이용한 품질경영시스템(ISO 9000:2000/KS A 9000:2001)의 효과적인 추진 방안은 다음과 같다 1) 전환 규격의 충분한 이해가 요구된다. 2) 현재의 업무 프로세스를 파악한 후 ERP PACKAGE에서 제공하는 개선된 업무프로세스를 적용하는 것이 필요하다. 3) 개선된 업무 프로세스의 실행 결과를 ERP PACKAGE 모듈에서 품질기록으로 유지한다. 4) 새로운 품질경영 정보 시스템을 업무 전반에 적용하기 위한 기업인프라 구축과 프로세스에 대한 지속적인 개선이 요구된다. 본 연구에서는 ISO 9000:2000/KS A 9000:2001 개정 규격요구사항을 이해하고 ERP PACKAGE를 이용하여 최초로 개정규격을 적용하거나, 전환규격으로 품질경영시스템을 구축 시 좀더 효과적이고 효율적인 품질경영시스템을 구축하는데 업무지침으로 활용될 수 있을 것이다.의 수와 생존율면에서 볼 때 가장 적합한 것으로 사료되었다./TEX>개월 투여하게 되면 HDL 콜레스테롤 양이 현저히 증가하였으며, 총 콜레스테롤 양, 동맥경화지표, 중성지방, 유리지방산, 과산화지방은 현 저히 감소하였다.- 결론 - 홍삼과 진세노사이드는 사람과 흰쥐에 있어 과지혈증을 호전시켰다. 실험적으로 과지혈증을 유발시킨 흰쥐에서, 혈중 아포단백질, 지방단백질 및 프로스타글란딘 상호성을 개선시켰다.었다.xA_{2}$ synthetase 억제제인 imidazole의 효과와 유사하였다. 4. G-Re는 $1{\times}10^{-5}g/ml$ 이하의 농도에서는 효과가 없으나 $1{\times}10^{-4}g/ml$ 이상의 농도에서 농도의존적으로 유의성 있는 $PGE_{2},\;PGF_{2}{\alpha},\;TXB_{2}$의 생성억제와 함께 6-keto-$PGF_{1}{\alpha}$ 증가를 보였다. 이는 prostacyclin synthetase를 자극하는 serotonin의 효과와 같은 작용으로서 prostacyclin synthetase 억제제인 tranylcypromine에 대하여 길항효과를 보였다. 5. $TxB_{2}$생성억제 작용을 나타내는 ginsenoside들의 효과를 뒷받침하기 위하여 인삼 saponin 성분을 전처치한 patelet rich plasma에서 혈소판 응집시험 결과, ADP로 유도된 혈소판 응집반응에는 모든 인삼 saponin 성분들이 효과가 없었으나 arachidonic acid로 유도된 혈소판 응집반응에는 $G-Rb_{2}$, G-Rc, G-Re의 순으로 농도 의존적인 억제현상을 보였다. 이상의 결과와 같이 인삼 saponin 성분들은

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.31-39
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• 2021

Obtaining delivery addresses from calls is one of the most important processes in TV home shopping business. By automating this process, the operational efficiency of TV home shopping can be increased. In this paper, a method of recognizing and validating road name address, which is the address system of South Korea, from speech oriented text is proposed. The speech oriented text has three challenges. The first is that the numbers are represented in the form of pronunciation. The second is that the recorded address has noises that are made from repeated pronunciation of the same address, or unordered address. The third is that the readability of the resulted address. For resolving these problems, the proposed method enhances the existing address databases provided by the Korea Post and Ministry of the Interior and Safety. Various types of pronouncing address are added, and heuristic rules for dividing ambiguous pronunciations are employed. And the processed address is validated by checking the existence in the official address database. Even though, this proposed method is for the STT result of the address pronunciation, this also can be used for any 3^rd party services that need to validate road name address. The proposed method works robustly on noises such as positions change or omission of elements.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.1-18
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• 2019

Due to the great advances in e-Marketplace and changes in type of items purchased from the online market, it has been dramatically increased the demand of the storage and transportation under the special conditions such as restricted temperature. Especially, the cold chain needs the way to transparently measure and monitor the entire network in realtime because it has a very complicated structure and requires totally different criteria at the every different steps and items. In this research, it has been presented the performance evaluation metrics to make contract using service level agreement (SLA), the way to apply the smart contract based on blockchain, the structure of blocks, service platform and application in order to build cold chain which can prevent the risk factors by measuring and sharing information in realtime using block chain technology. In addition, we have proposed the way to store the measured performance and reputation of each player in the block using smart contract based on SLA. With the presented framework, all players including service providers as well as users can secure the information for making the rational decisions. When the service platform is actually built and operated, it seems possible to secure the information in transparently and realtime. Also, it is possible to prevent the risk factors or prepare the preemptive plans to react on them.

• 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.

• Culinary science and hospitality research
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• v.19 no.4
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• pp.161-175
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• 2013

This study investigates the impact of the attributes of the eco-friendly agricultural products traceability system on perceived value and behavioral intention. Empirical subjects are those who live in Seoul and Gyeonggi province, over the age of 20 and have experience of buying eco-friendly agricultural products though department stores, discount stores and specialized eco-friendly product stores. After distributing 550 copies of questionnaire from April 10th, 2013 to May 9th, 2013, 470 copies(85.5%) are used for a final statistical analysis of the survey after excluding the copies with biased opinions or missing values. The results of this study show sufficient theoretical base for future research by verifying a causal relationships between the attributes of eco-friendly agricultural products traceability system such as reliability, safety and innovation, and consumers' perceived value and behavioral intention. Therefore, producers should correctly record producing history base so that consumers can continue to use the system. The traceability system can not only satisfy consumers by enhancing transparent management and producing systems for eco-friendly products but also guarantee us to eat all products we get without worries.

• Information Systems Review
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• v.22 no.3
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• pp.143-156
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• 2020

Price promotion is one of the most frequently marketing strategies with a long history. According to various studies, the effect of price promotion is controversial. Some studies have argued that price promotion has a positive effect, while others have found that it has no effect or rather has a negative effect. This study aims to examine the effect of price promotion in a subscription-based service. First, we check the effect of price promotion on the repurchase of the consumer. And we investigate how this effect varies depending on the characteristics of the consumer. Using the data from one of the music streaming service in South Korea, the effect of consumers' price promotion experience, demographic characteristics, and behavioral characteristics on their repurchase is analyzed through logistic regression analysis. As a result of the study, it is found that consumers' experience of price promotion has a positive effect on repurchase. In addition, the positive effect of price promotion is relatively greater in younger and female consumers. This study has implications in that it not only confirmed the positive effect of price promotion in a subscription-based environment but also empirically confirmed that the characteristics of consumers should be considered when performing price promotion.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.27-34
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• 2011

In this paper, it was presented a design on the dynamic multimedia fingerprinting code for anti-collusion code(ACC) in the protection of multimedia content. Multimedia fingerprinting code for the conventional ACC, is designed with a mathematical method to increase k to k+1 by transform from BIBD's an incidence matrix to a complement matrix. A codevector of the complement matrix is allowanced fingerprinting code to a user' authority and embedded into a content. In the proposed algorithm, the feature points were drawing from a content which user bought, with based on these to design the dynamical multimedia fingerprinting code. The candidate codes of ACC which satisfied BIBD's v and k+1 condition is registered in the codebook, and then a matrix is generated(Below that it calls "Rhee matrix") with ${\lambda}+1$ condition. In the experimental results, the codevector of Rhee matrix based on a feature point of the content is generated to exist k in the confidence interval at the significance level ($1-{\alpha}$). Euclidean distances between row and row and column and column each other of Rhee matrix is working out same k value as like the compliment matrices based on BIBD and Graph. Moreover, first row and column of Rhee matrix are an initial firing vector and to be a forensic mark of content protection. Because of the connection of the rest codevectors is reported in the codebook, when trace a colluded code, it isn't necessity to solve a correlation coefficient between original fingerprinting code and the colluded code but only search the codebook then a trace of the colluder is easy. Thus, the generated Rhee matrix in this paper has an excellent robustness and fidelity more than the mathematically generated matrix based on BIBD as ACC.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.161-173
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• 2020

In-depth interview in the field of hospitality industry services was conducted in COVID- 19. Introduction of kiosks for non-face-to-face services using untact technology, reservation, pay systems, self-service, service improvement using room service should be carried out. It is also necessary to implement Instagram, Facebook, YouTube, P-blogs, online broadcasting and live commerce through the establishment of m-channel system through untact marketing sales channels in the hospitality industry now that the product composition to solve the pro -blem of untact marketing is drawing attention due to diversification of online sales channe -ls. Now, the recognition of important elements of service education and a establishment of differentiated system of untact marketing, expansion of untact sale channel, implementation of non-face-to-face counseling service and introduction of pre-booking, telecommuting were recognized as urgent parts. In particular, a service differentiation and importance of human services, which were recognized free of charge, have re-recognized as premium, and quality service aspect of the hospitality industry in untact and the direction to diversify marketing channels are presented.