• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1404-1417
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• 1998

Currently, there exists two different methods for database retrieval in the internet. First is to use the search engine and the second is to use the plug-in or ActiveX technology, If a search engine, which makes use of indices built from keywords of simple text data in order to do a search, is used when accessing a database, first it is not possible to access more than one database at a time, second it is also not possible to support various conditional retrievals as in using query language, and third the set of data received might include many unwanted data, in other words, precision rate might be relatively low. Plug in or Active technology make use of Web browset to execute chents' query in order to do a database retrieval. Problems associated with this is that it is not possible to activate more than one DBMS simultaneously even if they are of the same data model. sefond it is not possible to execute a user query other than the ones thai arc previou sly defined by the client program In this paper, to resolve those aforementioned problems we design and implement database retrieval system using a virtual database, which makes it possible to provide direct query jntertacc through the conventional Web browser. We assume that the virtual database is designed and aggregated from more than one relational database using the same data model.

• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.607-617
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• 2020

Human bio-monitoring (HBM) data is a very important resource for tracking total exposure and concentrations of a parent chemical or its metabolites in human biomarkers. However, until now, it was difficult to execute the integration of different types of HBM data due to incompatibility problems caused by gaps in study design, chemical description and coding system between different sources in Korea. In this study, we presented a standardized code system and HBM knowledge model (KM) based on relational database modeling methodology. For this purpose, we used 11 raw datasets collected from the Ministry of Food and Drug Safety (MFDS) between 2006 and 2018. We then constructed the HBM database (DB) using a total of 205,491 concentration-related data points for 18,870 participants and 86 chemicals. In addition, we developed a summary report-type statistical analysis program to verify the inputted HBM datasets. This study will contribute to promoting the sustainable creation and versatile utilization of big-data for HBM results at the MFDS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.81-86
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• 2022

In this work, we propose a method for automatically determining the domain of columns of file data structured by csv format. New data can be generated through convergence between data and data, and the consistency of the joined columns must be maintained in order for these new data to become an important resource. One of the methods for measuring data quality is a domain-based quality diagnosis method. Domain is the broadest indicator that defines the nature of each column, so a method of automatically determining it is necessary. Although previous studies mainly studied domain automatic discrimination of relational databases, this study developed a model that can automate domains using the characteristics of file data. In order to specialize in the domain discrimination of file data, the data were simplified and patterned using a regular expression, and the contents of the data header corresponding to the column name were analyzed, and the suffix used was used as a derived variable. When derivatives of regular expressions and suffixes were added, the result of automatically determining the domain with an accuracy of 95% greater than the existing method of 87% was derived. This study is expected to reduce the quality measurement period and number of people by presenting an automation methodology to the quality diagnosis of public data.

• Journal of KIISE:Databases
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• v.35 no.3
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• pp.231-242
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• 2008

W3C has selected OWL as a standard for Web ontology description and a necessity of research on storage models that can store OWL ontologies effectively has been issued. Until now, relational model-based storage systems such as Jena, Sesame, and DLDB, have been developed, but there still remain several issues. Especially, they lead inefficient query processing performance. The structural problems of their low query processing performance are as follow: Jena has a simple structure which is not normalized and also stores most information in a single table. It exponentially decreases the performance because of comparison with unnecessary information for processing queries requiring join operations as well as simple search. The structures of storages(e.g., Sesame) have been completely normalized. Therefore it executes many join operations for query processing. The storages require many join operations to find simply a specific class. This paper proposes a storage model to resolve the problems that the query processing performance is decreased because of non-normalization or complete normalization of the existing storages. To achieve this goal, we analyze the problems of existing storage models as well as relations of OWL elements and query patterns. The proposed model, defined with the analysis results, provides an optimal normalized structure to minimize join operations or unnecessary information comparison. For the experiment of query processing performance, a LUBM data sets are used and query patterns are defined considering search targets and their hierarchical relations. In addition, this paper conducts experiments on correctness and completeness of query results to verify data loss of the proposed model, and the results are described. With the comparative evaluation results, our proposal showed a better performance than the existing storage models.

• Journal of muscle and joint health
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• v.5 no.2
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• pp.191-205
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• 1998

This study was conducted to identify the relations between the factors influencing syndrome and physical disability of fibromyalgia patients. The subjects of this study were 125 outpatients selected at H. Rheumatism clinic from February to July in 1997, The Collected data were analyzed by Frequency, Pearson correlation using SPSS Windows and Path analysis using LISREL 7.16. The results were as follows. 1. General characteristics of subjects About 2/3 of subjects were over 40years of age and most of them were graduated from high school. The Christian were over a half (54.0%) of subjects. 2. Correlation between Family support, knowledge, Self-efficacy, Syndrome and physical disability. As knowledge was positively related to self-efficacy(r=.306), the family support was positively related to self-efficacy(r=.217), and family support was negatively to syndrome. Self-efficacy showed negative relation with syndrome and Physical disability. Syndrome as physical disability represent positive relation. Therefore all hypotheses were supported. 3. Causal relations between research variables. Family support influenced on syndrome, as syndrome on physical activity, as well as knowledge on self-efficacy & physical disability. The model also showed a good fit to the data[$X^2$=1.21 df=1(p=.546), GFI=.996, AGFI=.971, RMSR=.023]. 4. Correlation between symptoms of Fibromyalyia. Having analyzed the relations between tender point, pain, stiffness, functional disturbance, sleep disturbance, depression, fatigue, anxiety, the results were as follows ; All relations show statistically positive correlation, which means close relationship between symptoms, except between pain and depression, pain and anxiety. As a result, symptoms of Fibromyalgia had close relation. Therefore, these were common, rather than individual symptoms. This syndrome influenced on physical disability, and self-efficacy on the both, as knowledge on self-efficacy. In conclusion, to improve syndrome relief and physical disability of fibromyalgia, nursing interventions such as education, self-efficacy increasing stratagy, and family counseling are needed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.611-623
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• 2017

The purpose of this study is to develop and validate the Korean Job Crafting Scale. First, previous studies on the concept and measurement of job crafting were reviewed, and items were developed based on this review. The content validity of the scale was examined using a focus group interview consisting of 10 HRM professionals. Following modification of the items, the measurements were administered to 305 employees from 8 Korean firms, and exploratory factor analysis was conducted in order to examine the factorial validity of the scale. Subsequently, confirmatory factor analysis was implemented concerning data collected from 295 employees who work in 7 Korean firms. Results indicated that the measurement model sufficiently explained the data at an appropriate level, and the subscales featured convergent and discriminant validity. If the scale developed in this study is validated in further studies, it can be employed to conduct research regarding job crafting in Korean organizations.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.9-21
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• 2020

With the proliferation of RDF knowledge graphs(KGs), there arose a need of a standardized schema representation of the graph model for effective data interchangeability and interoperability. The need resulted in the development of SHACL specification to describe and validate RDF graph's structure by W3C. Relational databases(RDBs) are one of major sources for acquiring structured knowledge. The standard for automatic generation of RDF KGs from RDBs is R2RML, which is also developed by W3C. Since R2RML is designed to generate only RDF data graphs from RDBs, additional manual tasks are required to create the schemas for the graphs. In this paper we propose an approach to automatically generate SHACL schemas for RDF KGs populated by R2RML mappings. The key of our approach is that the SHACL shemas are built only from R2RML documents. We describe an implementation of our appraoch. Then, we show the validity of our approach with R2RML test cases designed by W3C.

• Survey Research
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• v.12 no.2
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• pp.1-26
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• 2011

Mortality for oldest-old age (aged 80 or over) in Korea has never been studied mainly due to lack of data leaving its quality aside. The rapid aging recently occurring in Korea, which no other country has never experienced, must introduce a drastic change in the structure of future population pyramid, requring a careful investigation on mortality level, pattern, and trend for the oldest-old age in Korea. For mortality trend, we need to extend the past mortality data, which has provided only an open-ended age interval 80 or 85 years and over, to age-specific mortality up to 115 years old. A prerequisite for such an extension is constructing a Korean standard mortality by which one can figure out the mortality level and pattern of the oldest-old age. A Korean standard mortality is proposed by applying one relational model and eleven functions from which we select best models for each sex in terms of three measures of fits and three consistencies of mortality. Then we extend the mortality of the open-ended age intervals by providing a method to avoid the longitudinal consistency of mortality.

• The Korean Journal of Franchise Management
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• v.12 no.1
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• pp.35-44
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• 2021

Purpose: This study examines the opportunism moderating effect by the startup experience in the relationship between franchisor and franchisees. In the case of a franchise system that has a continuous relational exchange transaction, relationship management is a very important activity because the relationship management between franchisor and franchisees improves the quality of the relationship. Nevertheless, there is insufficient of research on opportunism, which is a negative factor in managing the relationship between franchisor and franchisees in continuous relationship. Research design, data and methodology: This study, we explore the cause of opportunism based on transaction cost theory through prior research and establish a research model based by goal incongruity, uncertainty, information asymmetry, transaction specific assets, the relevance to determinant of opportunism and the startup experienced which is a moderating variable. To verify several hypotheses, the data were collected from 300 out of 1,760 domestic franchisees and analyzed using multiple regression analysis with SPSS program. Results: The findings are as follows. Goal incongruity did not affect opportunism. Opportunism increased as uncertainty increased, and as information asymmetry increased, opportunism increased. An opportunism decreased as transaction specific assets increased. Moreover, the findings show that startup experience only plays a moderating role in the relationship between information asymmetry and opportunism. Therefore, 4 out of 8 hypotheses were supported. Conclusions: The findings show that uncertainty, information asymmetry, and transaction specific assets are the determinants of opportunism. In addition, the results of the analysis of the moderating role of startup experience show that the less entrepreneurial experience, the greater the influence of information asymmetry on opportunism. Our findings mean that maintaining a successful relationship between franchisors and franchisees is possible when franchisors provide knowledge sharing, goal sharing, environmental sharing, and management information sharing to franchisees. In addition, the findings of this study shows that the contract content and management should be changed according to the entrepreneurial experience. In other words, the franchisors must share and integrate the accumulated franchisees' and franchisors' experience with the franchisees to create a synergy that can lead to successful bilateral relationship maintenance, which in turn reduces opportunism.

• International Commerce and Information Review
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• v.16 no.4
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• pp.3-34
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• 2014

Nowadays to thrive on the intensively competitive environments based on drastic and rapid technical evolutions, exporting manufacturing companies need to keep very stable relationship with suppliers. Thus, analyzing key factors of strengthening relationship with suppliers in a B2B environment is important. In this regard, this study develops a research model to deeply understand key antecedents of relationship strength between B2B companies. Relationship quality was considered as the key factor affecting to the relationship strength. This study considers relationship satisfaction, trust, and relationship commitment as the factors of relationship quality. Moreover, technical service quality and relational service quality were considered to be the antecedents of relationship satisfaction, while communication and information exchange, relationship policies and practices, and opportunistic behavior were regarded as the antecedents of trust. The PLS method was applied for the empirical analysis of 107 companies data. The results indicated that the relationship commitment has a significant impact on relationship strength. Moreover, relationship satisfaction and trust had indirectly impact on relationship strength through relationship commitment. Although the quality of technical service quality had a significant impact on relationship satisfaction, relational service quality did not have a significant impact. While communication and information exchange, relationship policies, and practices had positively significant impacts, opportunistic behavior had a negative impact.