• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.25-34
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• 2015

In this research, we applied a procedure of quality control (QC) to the agro-meteorological data measured at the Suwon weather station of Korea Meteorological Administration (KMA). The QC was conducted through six steps based on the KMA Real-time Quality control system for Meteorological Observation Data (RQMOD) and four steps based on the International Soil Moisture Network (ISMN) QC modules. In addition, we set up our own empirical method to remove erroneous data which could not be filtered by the RQMOD and ISMN methods. After all these QC procedures, a well-refined agro-meteorological dataset was complied at both air and soil temperatures. Our research suggests that soil moisture requires more detailed and reliable grounds to remove doubtful data, especially in winter with its abnormal variations. The raw data and the data after QC are now available at the NCAM website (http://ncam.kr/page/req/agri_weather.php).

• Information Systems Review
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• v.21 no.4
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• pp.1-29
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• 2019

The knowledge resources take a role in promoting the sustainable growth of organization. Therefore, it is important for the members of organization to acquire knowledge consistently so that the company can continue to grow. Knowledge service is the field that provides information and infrastructure which enable the members of organization to acquire new knowledge. As we recognized the importance of knowledge services, we analyzed the level of knowledge service management and development through the impact of knowledge quality on user capabilities. First, the matrix of knowledge patterns was presented based on the type of information and the level of customer interaction. According to patterns, the knowledge service was classified into three types of information providing, information analysis, and infrastructure, and then the results of structural model analysis were presented for each type. It found that the impact of knowledge service quality on user competence was different according to the type of service. The results suggested new indicators for measuring the performance of knowledge services, and provided information for reconstructing services based on the user considering the integrated operation of knowledge service and organizational designing knowledge service.

• Journal of Service Research and Studies
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• v.7 no.4
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• pp.151-164
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• 2017

This study aims to explore the effect of quality factors and learning styles on users' satisfaction in the use of business simulation tools in business education. For this purpose, statistical methods such as reliability test, factor analysis, ANOVA, regression analysis were carried out using the survey data from university students. The quality factors of education using simulation were classified into contents, education environment, interpersonal activities, and instructor support while learning styles were classified into proactive, self-directed, environmental-dependent, and passive styles. The results showed that each quality factors of education using business simulation had a strong positive effect on user satisfaction. Proactive and environment-dependent group had higher satisfaction than other groups. Learning styles had moderating effects on the quality-satisfaction relationship, and the direction and degree varied depending on the quality factors and learning styles. Theoretical and practical implications were drawn from these findings.

• Korean Business Review
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• v.19 no.2
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• pp.261-274
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• 2006

Airline business operates in the 21st century within fast changing market environment and fierce competition. Management of airline companies has faced the need for vast adaptation to new trends in the growth of world economy that are cardinal changes in marketing environment due to quick development of Internet and IT, transport price competition and, as a consequence, low profit margin, diversified customer wants and needs, lack of investment needed for new aircraft equipped with the latest high tech innovations, unpredictable oil price changes, and exchange rate fluctuations. This study is aimed to evaluate the quality performance of cabin service, to analyse, further, the issues that appeared to be the most significant among customers' answers to questionnaire, to explore the relationships between these issues and customer satisfaction, to highlight the essential questions to address, and to provide some practical suggestions. The five dimensions (such as tangible, reliability, responsiveness, assurance, and empathy) were adopted to examine the relationship between the service quality and customer satisfaction of Mongolian and non-Mongolian passengers travelling by the MIAT. According to findings of analysis made with use of the SERVPERF model, it can be concluded that Mongolian travellers' satisfaction was effected by 'Tangible' and 'Responsiveness' dimensions of service quality, whereas the 'Empathy' dimension has more impact on the satisfaction of non-Mongolian.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.39-57
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• 2004

Many dairy producers periodically receive information about their bulk tank milk with reference to bulk tank somatic cell counts, standard plate counts, and preliminary incubation counts. This information, when collected over a period of time, in combination with bulk tank mastitis culture reports can become a significant knowledge base. Several guidelines have been proposed to interpret farm bulk tank milk bacterial counts. However many of the suggested interpretive criteria lack validation, and provide little insight to the interrelationship between different groups of bacteria found in bulk tank milk. Also the linguistic terms describing bulk tank milk quality or herd management status are rather vague or fuzzy such as excellent, good or unsatisfactory. The objective of this paper was to develop a set of fuzzy descriptors to evaluate bulk tank milk quality and herd's milking practice based on bulk tank milk microbiology test results. Thus, fuzzy logic based reasoning methodologies were developed based on fuzzy inference engine. Input parameters were bulk tank somatic cell counts, standard plate counts, preliminary incubation counts, laboratory pasteurization counts, non agalactiae-Streptococci and Streptococci like organisms, and Staphylococcus aureus. Based on the input data, bulk tank milk quality was classified as excellent, good, milk cooling problem, cleaning problem, environmental mastitis, or mixed with mastitis and cleaning problems. The results from fuzzy reasoning would provide a reference regarding a good management practice for milk producers, dairy health consultants, and veterinarians.

• Journal of KIISE:Information Networking
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• v.37 no.3
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• pp.175-186
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• 2010

Due to the emergence of new application programs and the fast growth of Internet users, Internet routers are required to provide the quality of services according to the class of input packets, which is identified by wire-speed packet classification. For a pre-defined rule set, by performing multi-dimensional search using various header fields of an input packet, packet classification determines the highest priority rule matching to the input packet. Efficient packet classification algorithms have been widely studied. Tuple pruning algorithm provides fast classification performance using hash-based search against the candidate tuples that may include matching rules. Bloom filter is an efficient data structure composed of a bit vector which represents the membership information of each element included in a given set. It is used as a pre-filter determining whether a specific input is a member of a set or not. This paper proposes new tuple pruning algorithms using Bloom filters, which effectively remove unnecessary tuples which do not include matching rules. Using the database known to be similar to actual rule sets used in Internet routers, simulation results show that the proposed tuple pruning algorithm provides faster packet classification as well as consumes smaller memory amount compared with the previous tuple pruning algorithm.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.4
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• pp.67-88
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• 2021

The National Science and Technology Standard Classification System is established and operated for the purpose of efficiently managing science and technology related information, manpower, and R&D projects. The revision cycle for the classification system is five years, and 2022 is the first year of the next revision procedures. The main purpose of the next revision is to turn the third level categories into the keywords in the current classification system. It is to solve the problems about not reflecting the latest terms, and the difficulty in linking with the relevant other classifications caused by the rigid structure of the current classification system. In this study, the method was proposed by changing the existing classification system into the term management system as to improve the quality and usability of keywords related with the current third level categories. For this method, SKOS, the international standard terminology management system, and ISO/IEC 11179 standards were offered as basic models. In addition, the related metadata standards used in overseas scientific and technological glossaries were investigated, and compared with the current National Science and Technology Standard Classification System. And then essential metadata elements from the terminology management as point of view was derived. As a result, 11 standard metadata elements that can be immediately modified and applied in the current system were recommended, and five elements that can be applied after the revision of the classification system were offered.

• The Journal of Bigdata
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• v.7 no.2
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• pp.1-9
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• 2022

In the global era, the importance of imported food safety management is increasing. Address information of overseas food companies is key information for imported food safety management, and must be verified for prompt response and follow-up management in the event of a food risk. However, because each country's address system is different, one verification system cannot verify the addresses of all countries. Also, the purpose of address verification may be different depending on the field used. In this paper, we deal with the problem of classifying a given overseas food business address into the administrative district level of the country. This is because, in the event of harm to imported food, it is necessary to find the administrative district level from the address of the relevant company, and based on this trace the food distribution route or take measures to ban imports. However, in some countries the administrative district level name is omitted from the address, and the same place name is used repeatedly in several administrative district levels, so it is not easy to accurately classify the administrative district level from the address. In this study we propose a deep learning-based administrative district level classification model suitable for this case, and verify the actual address data of overseas food companies. Specifically, a method of training using a label powerset in a multi-label classification model is used. To verify the proposed method, the accuracy was verified for the addresses of overseas manufacturing companies in Ecuador and Vietnam registered with the Ministry of Food and Drug Safety, and the accuracy was improved by 28.1% and 13%, respectively, compared to the existing classification model.

• Radiation Oncology Journal
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• v.24 no.3
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• pp.185-191
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• 2006

[ $\underline{Purpose}$ ]: Standardization quality assurance (QA) program of CyberKnife for suitable circumstances in Korea has not been established. In this research, we investigated the development of QA program for CyberKnife and evaluation of the feasibility under applications. $\underline{Materials\;and\;Methods}$: Considering the feature of constitution for systems and the therapeutic methodology of CyberKnife, the list of quality control (QC) was established and divided dependent on the each period of operations. And then all these developed QC lists were categorized into three groups such as basic QC, delivery specific QC, and patient specific QC based on the each purpose of QA. In order to verify the validity of the established QA program, this QC lists was applied to two CyberKnife centers. The acceptable tolerance was based on the undertaking inspection list from the CyberKnife manufacturer and the QC results during last three years of two CyberKnife centers in Korea. The acquired measurement results were evaluated for the analysis of the current QA status and the verification of the propriety for the developed QA program. $\underline{Results}$: The current QA status of two CyberKnife centers was evaluated from the accuracy of all measurements in relation with application of the established QA program. Each measurement result was verified having a good agreement within the acceptable tolerance limit of the developed QA program. $\underline{Conclusion}$: It is considered that the developed QA program in this research could be established the standardization of QC methods for CyberKnife and confirmed the accuracy and stability for the image-guided stereotactic radiotherapy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.51-55
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• 2010

Tele-marketing service has been provided through voice media in a several places such as modern call centers. In modern call centers, they are trying to measure their service quality, and one of the measuring method is a extracting speaker's feeling information in their voice. In this study, it is proposed to analyze speaker's voice in order to extract their feeling information. For this purpose, a person's feeling is categorized by analyzing several types of signal parameters in the voice signal. A person's feeling can be categorized in four different states: joy, sorrow, excitement, and normality. In a normal condition, excited or angry state can be major factor of service quality. In this paper, it is proposed to select a conversation with problems by extracting the speaker's feeling information based on pitches and amplitudes of voice.