• Clinical and Experimental Pediatrics
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• v.51 no.5
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• pp.523-527
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• 2008

Purpose : Several cytokines play important roles in the inflammatory process of Henoch-$Sch\ddot{o}lein$ Purpura (HSP). It is likely that transforming growth $factor-{\beta}$ ($TGF-{\beta}$) is involved in the pathogenesis of HSP. The purpose of this study is to investigate whether $TGF-{\beta}$ promoter polymorphism is associated with the renal involvement of childhood HSP. Methods : Thirty-four patients younger than 15 years, who had been diagnosed with HSP, as well as 27 controls, were examined. Patients and controls were genotyped for $TGF-{\beta}$ C-509T by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Results : The T allelic frequencies in patients and controls showed no difference (45% vs. 48.8%). No allele or genotype differences between the group of HSP group and control group were observed. The frequencies of $TGF-{\beta}$ 509 genotypes TT, TC, and CC were no different between patients and controls (26% vs. 22%). The TT genotype of polymorphism of the $TGF-{\beta}$ C-509T gene had no relation to the susceptibility of children to HSP and renal involvement in HSP. Conclusion : $TGF-{\beta}$ T allele may not be related to the susceptibility of children to HSP. The TT genotype of polymorphism of the $TGF-{\beta}$ C 509T gene does not appear to have an influence on renal involvement in childhood HSP.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.1
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• pp.115-137
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• 2020

This study aims to examine the limitations of status that describe archives based on the Archival rules, and to propose a new method using the Records in Context - Conceptual model (RiC-CM) as a solution. Given this, the study conducted literature reviews and case studies. The solutions based on RiC-CM and its effects on the limitations of the existing environment are as follows. First, RiC-CM can describe multiple provenances about archives. This can be solved by defining individual records and provenances as "entity" and expressing their associations as relationships. The interrelation of entities alone can more accurately represent the information of provenances associated with a particular archive, making it easier to identify the overall context that makes records. Second, RiC-CM can link related files. Those that belong to a specific records group (fonds) can be resolved by assigning them to individual entities and making interrelation according to the context that makes records. This method makes it possible to serve information about the context that makes records. From the user's point of view, more options are available for searching records. Third, RiC-CM can link all relevant producer-made records related to a specific production organization. If organizations are related to each other, they can be defined as "entity," and their relationship can be expressed as "associated with." It helps to comprehensively examine the context of provenances. The findings of this study are expected to be used as a basis for future research on RiC-CM, in response to the paradigm shift for electronic records management systems.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.616-631
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• 2007

Residential differentiation is an academic theme which has been given enormous attention in urban studies. This is due to the fact that residential segregation can be seen as one of the best indicators for socio-spatial dialectics occurring on urban space. Measuring how one population group is differentiated from the other group in terms of residential space has been a focal point in the residential segregation studies. The index of dissimilarity has been the most extensively used one. Despite its popularity, however, it has been accused of inability to capture the degree of spatial clustering that unevenly distributed population groups usually display. Further, the spatial indices of segregation which have been introduced to edify the problems of the index of dissimilarity also have some drawbacks: significance testing methods have never been provided; recent advances in spatial statistics have not been extensively exploited. Thus, the main purpose of the research is to devise a spatial separation measure which is expected to gauge not only how unevenly two population groups are distributed over urban space, but also how much the uneven distributions are spatially clustered (spatial dependence). The main results are as follows. First, a new measure is developed by integrating spatial association measures and spatial chi-square statistics. A significance testing method based on the generalized randomization test is also provided. Second, a case study of residential differentiation among groups by educational attainment in major Korean metropolitan cities clearly shows the applicability of the analytical framework presented in the paper.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.797-804
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• 2017

A social network is a typical social science environment with both network and iteration characteristics. This research presents a reaction analysis model of how each node responds to social networks when given input such as promotions or incentives. In addition, the setting value of a specific node is changed while examining the response of each node. And we try to understand the reactions of the nodes involved. The reaction analysis model is constructed by applying various techniques such as unidirectional, fuzzy set, weighting, and cyclic feedback, so it can accommodate the complicated environment of practice. Finally, the implementation model is implemented using Vensim rather than NetLogo because it requires repetitive input, change of setting value in real time, and analysis of association between nodes.

• Information Systems Review
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• v.8 no.2
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• pp.119-138
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• 2006

Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.197-206
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• 2012

A exisiting recommedation system using association rules has the problem, such as delay of processing speed from a cause of frequent scanning a large data, scalability and accuracy as well. In this paper, using a Implicit method which is not used user's profile for rating, we propose the personalized recommendation system which is a new method using the FP-tree mining based on RFM. It is necessary for us to keep the analysis of RFM method and FP-tree mining to be able to reflect attributes of customers and items based on the whole customers' data and purchased data in order to find the items with high purchasability. The proposed makes frequent items and creates association rule by using the FP-tree mining based on RFM without occurrence of candidate set. We can recommend the items with efficiency, are used to generate the recommendable item according to the basic threshold for association rules with support, confidence and lift. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.213-219
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• 2020

The purpose of this study was to investigate the characteristics of error types in naming task for 8 questionable demeatia groups, 9 definite dementia groups, and 10 normal groups. The items of naming error analysis were classified into visual perception errors, semantic association errors, semantic non-correlation errors, phoneme errors, Don't Know, and No Response. For the analysis, descriptive statistics analysis, analysis of variance, and multivariate analysis of variance were conducted using SPSS 21.0. As a result, there was a significant difference in the error rate between groups according to the error type. The errors that showed significant differences between the normal group and the other two groups were visual perception errors and semantic non-related errors. The error of non-response was different from the dementia confirmation group, but there was no significant difference from the dementia suspicion group. These results showed that Alzheimer's patients had a defect in confrontation naming ability. Also, it was found that it is appropriate to provid other clues when the defects caused by the degeneration of a specific step during the information processing process become severe.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3855-3865
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• 2000

The automatic indexing is a compulsory part for the text retrieval system. However it is impossible to rank the appropriate texts at top. Furthermore, it is more difficult to prevent to rank the inappropriate texts having homonyms at top by only the automatic indexing. In this paper, we proposed the two-level retrieval system to enhance the retrieval efficiency, in which Automatic Keyword Network (AKN) is used at the second-level process. The firsHevel search is carried out with an inverted index file generated by the automatic indexing. On the other hand the second-level search exploits AKN based on the degree of asslxiation between terms. We have developed several formulas for rearranging the rank of texts at second-level search, and evaluated the performance of the effects of them on resolving the word sense ambiguities.

• Journal of Applied Reliability
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• v.15 no.2
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• pp.131-138
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• 2015

In modern warfare, the number of unmanned systems grow faster than any other weapon systems. Therefore, it is very important to predict and measure the combat effectiveness (CE) of unmanned weapon systems in battlefield for deciding defense budget to acquire those systems. In general, quantitative calculation of weapon effectiveness under complicated battlefield is difficult based on the future network centric warfare. Hence, many papers studied how to measure the combat effectiveness and tried to study a lot of related issues about it. However, there are few papers dealing with the relationship between the UGV (Unmanned Ground Vehicle)'s performance and CE in a ground battlefield. In this paper, we do the sensitivity analysis based on a given scenario in a small unit battle. In order to do that, we developed simulation model using AnyLogic and changed the input parameters such as detection and hitting probabilities. We also assess the simulation outputs according to the variation of input parameters. The MOE used in this simulation model output is survival ratio for Blue force. We hope that this paper will be useful to find which input variable is more effective to increase combat effectiveness in a small unit ground battlefield.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.843-848
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• 2002

It is studied on the relationship between the occurrence of red tide and the meteorological factors(precipitation, air temperature, sunshine and winds) in the middle coastal area in the South Sea of Korea. In summer and early-fall which frequently occurred the red tide, the precipitation had directly influence on the occurrence of red tide because it carried the nutritive substances which originated from the land into the coastal areas. Then air temperature kept up generally high values, and sunshine and winds showed not directly the relationship on the occurrence of red tide.