• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.928-935
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• 2009

Ontology schema reasoning is used to maintain consistency of concepts and build concept hierarchy automatically. For the purpose, the search of concepts must be inevitably performed. Ontology schema reasoning performs the test of subsumption relationships of all the concepts delivered in the test set. The result of subsumption tests is determined based on the creation of complete graphs, which seriously weighs with the performance of reasoning. In general, the process of creating complete graph has been known as expressive procedure. This process is essential in improving the leading performance. In this paper, we propose a method enhancing the classification performance by identifying unnecessary subsumption test supported by optimized searching method on subsumption relationship test among concepts. It is achieved by propagating subsumption tests results into other concept.

• Genomics & Informatics
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• v.16 no.4
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• pp.23.1-23.5
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• 2018

Virus taxonomy was initially determined by clinical experiments based on phenotype. However, with the development of sequence analysis methods, genotype-based classification was also applied. With the development of genome sequence analysis technology, there is an increasing demand for virus taxonomy to be extended from in vivo and in vitro to in silico. In this study, we verified the consistency of the current International Committee on Taxonomy of Viruses taxonomy using an in silico approach, aiming to identify the specific sequence for each virus. We applied this approach to norovirus in Caliciviridae, which causes 90% of gastroenteritis cases worldwide. First, based on the dogma "protein structure determines its function," we hypothesized that the specific sequence can be identified by the specific structure. Firstly, we extracted the coding region (CDS). Secondly, the CDS protein sequences of each genus were annotated by the conserved domain database (CDD) search. Finally, the conserved domains of each genus in Caliciviridae are classified by RPS-BLAST with CDD. The analysis result is that Caliciviridae has sequences including RNA helicase in common. In case of Norovirus, Calicivirus coat protein C terminal and viral polyprotein N-terminal appears as a specific domain in Caliciviridae. It does not include in the other genera in Caliciviridae. If this method is utilized to detect specific conserved domains, it can be used as classification keywords based on protein functional structure. After determining the specific protein domains, the specific protein domain sequences would be converted to gene sequences. This sequences would be re-used one of viral bio-marks.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.102-116
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• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.

• Journal of Preventive Medicine and Public Health
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• v.33 no.1
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• pp.125-133
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• 2000

Objectives : This study uses meta-analysis methodology to examine the statistical consistency and importance of random variation among results of epidemiologic studies of occupational electromagnetic field exposure and leukemia. Methods : Studies for this meta-analysis were identified from previous reviews and by asking researcher active in this field for recommendations. Overall, 27 studies of occupational electromagnetic field exposures and leukemia were reviewed. A variety of meta-analysis statistical methods have been used to assess combined effects, to identify heterogeneity, and to provide a single summary risk estimate based on a set of simiar epidemiologic studies. In this study, classification of exposure metircs on occupational epidemiologic studies are reported for (1) job classification (20 individual studies); (2) leukemia subtypes (13 individual studies); and (3) country (27 individual studies). Results : Results of this study, an inverse-variance weighted pooling of all the data leads to a small but significant elevation in risk of f 1% (OR=1.11, 95% CI : $1.06\sim1.16$) among 27 occupational epidemiologic studies. Publication bias was assessed by the 'fail-safe n' that may be not influence for all combined results exception a few categories, ie, 'power station operators' and 'electric utility workers' by job classification on occupational study. And ail combined odds ratio results were similar for fixed-effects models and random-effects models, with slightly higher risk estimates for the random-effects model in situations where there was significant heterogeneity, ie, Q-statistic significant (p<.05). Conclusions : We found a small elevation in risk of leukemia, but the ubiquitous nature of exposure to electromagnetic fields from workplace makes even a weak association a public health issue of substantial power to influence the present overall conclusion about relationship between electromagnetic fields exposure and leukemia.

• Journal of Energy Engineering
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• v.11 no.4
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• pp.359-369
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• 2002

Nuclear power plant is a huge system with multidisciplinary technology. So, R & D prioritization is a not a simple task and the relative importance of each prioritization criterion is not well established. This study built a technology classification chart for nuclear power plant operation and maintenace, established the relative importance of prioritization criteria and assigned the relative importance of each technology at each level. Analytical Hierarchy Process was used for the prioritization and the result was validated with Consistency Index and outcomes of fields interview.

• Journal of the Korean Society for information Management
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• v.13 no.1
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• pp.227-241
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• 1996

We present development results for a Hangul thesaurus which was provided to improve performance of the intelligent information retrieval system. The important stages and methods in the process of term acquisition, classification, creation of the consistency-effectiveness relationship using HiTEL menu and text of dictionary are described. To cany out our study we have built a thesaurus management system and also describe its utility functions.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.77-86
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• 1989

A fully automated cost estimation system(FACES) has been developed. Since speed, accuracy, and consistency are essential factors in automating a cost estimation, the use of computers in cost estimation system(CES) has grown rapidly in the last few years. FACES is a micro computer based cost estimation system that employs a manufacturing knowledge base. A Group Technology(GT) based part classification and coding(C&C) scheme is used to automate the process planning aspects of cost estimation. Variant process planning methods are employed to generate workstation routings from form features of the part. The system has been tested for an assembly of six machined parts. Results indicate that the system could provide a substantial improvement in accuracy, productivity, and performance over the more traditional full dialog approach to cost estimation. It also provides a good foundation for a factory automation by using a common GT based database through design to production.

• Proceedings of the Korean Association for Survey Research Conference
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• 2001.11a
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• pp.33-45
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• 2001

Korean standard industrial/occupational classification has been the basis of producing accurate statistical data related with our industrial structure and distribution of industry and occupation since 1960. But coding over several million records not only requires high cost in the aspects of time and manpower but also has many problems in accuracy and consistency. Therefore, we got to develop the automatic coding system in order to work out these problems of manual coding. This paper shows the structure of our system and the result of experiment over survey data of 2,000 Census.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.14 no.1
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• pp.15-22
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• 2008

The excitement over radio frequency identification (RFID) technology has gained momentum in the last five years, with a diversification in the range of applications. Besides academic research into radio frequency identification (RFID) has proliferated over the last few years, however there is much to be desired on Packaging industry. In this paper, we present a literature reviews of researches of RFID system on Packaging, especially focused on RFID system standardization into packaging. There is not any packaging standard or guidance about tag locations, classification with the materials and so on. Therefore it hampers reduction of the distribution costs on political and corporate sides, and lack consistency of applying RFID system. The main focus of this review paper is to establish a constituency about legislating RFID system standard on packaging. It is hoped that the review will be a good resource for future research in order to applly RFID system to Packaging industry effectively.

• Journal of Korean Academy of Nursing
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• v.46 no.1
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• pp.149-158
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• 2016

Purpose: This study was done to develop of the Korean intensive care delirium screening tool (KICDST). Methods: The KICDST was developed in 5 steps: Configuration of conceptual frame, development of preliminary tool, pilot study, reliability and validity test, development of final KICDST. Reliability tests were done using degree of agreement between evaluators and internal consistency. For validity tests, CVI (Content Validity Index), ROC (Receiver Operating Characteristics) analysis, known group technique and factor analysis were used. Results: In the reliability test, the degree of agreement between evaluators showed .80~1.00 and the internal consistency was KR-20=.84. The CVI was .83~1.00. In ROC analysis, the AUC (Area Under the ROC Curve) was .98. Assessment score was 4 points. The values for sensitivity, specificity, correct classification rate, positive predictive value, and negative predictive value were found to be 95.0%, 93.7%, 94.4%, 95.0% and 93.7%, respectively. In the known group technique, the average delirium screening tool score of the non-delirium group was $1.25{\pm}0.99$ while that of delirium group was $5.07{\pm}1.89$ (t= - 16.33, p <.001). The factors were classified into 3 factors (cognitive change, symptom fluctuation, psychomotor retardation), which explained 67.4% of total variance. Conclusion: Findings show that the KICDST has high sensitivity and specificity. Therefore, this screening tool is recommended for early identification of delirium in intensive care patients.