• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.263-274
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• 2020

In the Southeast Sea of Korea, a cold water mass is formed intensively in summer every year, causing frequent abnormal sea conditions. In order to analyze the spatial changes of sea surface temperature distribution in this area, ocean fields buoy data observed at Gori and Jeongja and reanalyzed sea surface temperature(SST) data from GHRSST Level 4 were used from June to September 2018. The buoy data were used to analyze the time-series water temperature changes at two stations, and the GHRSST data were used to calculate the daily SST variance and weighted mean center(WMC) across the study area. When the buoy's water temperature was lowered, the variance of SST in the study area trend to increase, but it did not appear consistently for the entire period. This is because GHRSST is a reanalysis data that does not reflect sensitive changes in water temperature along the coast. As such, there is a limit to grasping the local small-scale water temperature change in the coast or detecting the location and extent of the cold water zone only by the statistical variance representing the SST change in the entire sea area. Therefore, as a result of using WMC to quantitatively determine the spatial location of the cold water mass, when the cold water zone occurred, WMC was located in the northwest sea area from the mean center(MC) of the study area. This means that it is possible to quantitatively identify where and to what extent the distribution of cold surface water temperature appears through SST's WMC location information, and we could see the possibility of WMC's use in detecting the scale of cold water zones and the extent of regional spread in the future.

• Korean Journal of Biological Psychiatry
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• v.18 no.3
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• pp.141-147
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• 2011

Objectives The purpose of this study is to evaluate the relationship between the severity of white matter changes (WMC), risk factors and cognitive domains, including executive function profiles. Method Forty nine subjects over 55 years with subjective memory complaints were assessed with MRI and neuropsychological tests. The WMC were assessed by MRI T2-FLAIR images and divided into 3 groups of mild vs. moderate vs. severe and 2 groups of mild-moderate vs. severe by using Mantyla's criteria and Fazeka's criteria. The risk factors were examined in hypertension, heart disease history and chemistry Lab. Medical conditions which affect to cognitive dysfunction and definite dementia were also excluded. Results Comparing 3 groups, hypertension was identified as a risk factor of the WMC. Comparing 2 groups, total cholesterol and LDL were identified for as the risk factor of WMC. The severity of WMC was significantly associated with cognitive disturbances and their main effect on cognition was working memory and inhibition. Conclusion The risk factors of the WMC in the elderly were hypertension, hyperlipidemia. The severity of WMC appears to be associated with executive dysfunction in the elderly.

• Journal of Biomedical Engineering Research
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• v.26 no.6
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• pp.383-391
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• 2005

Age-related White Matter Changes (WMC) on Magnetic Resonance Imaging (MRI) are known to appear frequently in Multiple sclerosis (MS) and Alzheimer's disease and to be related to cognitive impairment. The characterization of these WMC is very important to the study of psychology and aging. These changes consist of periventricular and subcortical types, however it is difficult to detect and segment WMC using only intensity-based methods, because their intensity, level IS similar to th~t of the gray matter (GM). In this paper, we propose a new method of segmenting periventricular WMC using K-means clustering and morphological features.

• Korean Journal of Culture and Social Issue
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• v.22 no.1
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• pp.41-64
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• 2016

In two experiments, we compared envy with admiration in attentional and motivational benefits. In addition, we tested whether individual differences in working memory capacity (WMC) have consequences for emotion regulation. In Study 1, following WMC tasks, the participants were primed either with envy or with admiration through a recall task, in which they had to recall their own experiences about envy or admiration. The participants in the envy condition considered it more undeserved that another person had an advantage over them, than in the admiration condition. Additionally, in the envy condition, WMC was related to happiness, and anxiety was related to the motivation to study more. In contrast, there were no significant relationships between WMC, emotion and study hours in the admiration condition. Study 2 (N=43) found greater memory for the envy scenario in the envy condition than in the admiration and in the control condition. Additionally, there were significant relationships between WMC, anxiety and recall accuracy in the envy condition. However, these relations were not found in the admiration and in the control condition. Findings implicate that envy may play an important role in memory systems and that WMC is related to emotion regulation abilities.

• Proceedings of the KSMRM Conference
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• 2003.10a
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• pp.34-34
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• 2003

Age-related WMCs frequently appear in older subjects and are known to be associated with cognitive impairment and brain pathologies such as Alzheimer's disease and stroke. However, it is difficult to detect WMC correctly by using only intensity-based clustering scheme because the intensity levels of WC are similar to those of gray matter(GM). In this paper, we aimed to develop a fast and accurate scheme to detect and segment periventricular WMCs by using both k-means clustering method and morphological features.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.203-216
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• 2019

The nature of wireless transmission has made wireless sensor networks defenseless against various attacks. This paper presents warning message counter method (WMC) to detect blackhole attack, grayhole attack and sinkhole attack in wireless sensor networks. The objective of these attackers are, to draw the nearby network traffic by false routing information and disrupt the network operation through dropping all the received packets (blackhole attack), selectively dropping the received packets (grayhole and sinkhole attack) and modifying the content of the packet (sinkhole attack). We have also attempted light weighted symmetric key cryptography to find data modification by the sinkhole node. Simulation results shows that, WMC detects sinkhole attack, blackhole attack and grayhole attack with less false positive 8% and less false negative 6%.

• The KIPS Transactions:PartD
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• v.8D no.1
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• pp.71-80
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• 2001

Object-Oriented (OO) methodology to use the concept like encapsulation, inheritance, polymorphism, and message passing demands metrics that are different from structured methodology. There are many studies for OO software metrics such as program complexity or design metrics. But the metrics for the analysis class need to decrease the complexity in the analysis phase so that greatly reduce the effort and the cost of system development. In this paper, we propose new metrics to measure the complexity of analysis classes which draw out in the analysis phase based on Unified Process. By the collaboration complexity, is denoted by CC, we mean the maximum number of the collaborations can be achieved with each of the collaborator and detennine the potential complexity. And the interface complexity, is denoted by IC, shows the difficulty related to understand the interface of collaborators each other. We prove mathematically that the suggested metrics satisfy OO characteristics such as class size and inheritance. And we verify it theoretically for Weyuker' s nine properties. Moreover, we show the computation results for analysis classes of the system which automatically respond to questions of the it's user using the text mining technique. As we compared CC and IC to CBO and WMC, the complexity can be represented by CC and IC more than CBO and WMC. We expect to develop the cost-effective OO software by reviewing the complexity of analysis classes in the first stage of SDLC (Software Development Life Cycle).

• Journal of KIISE:Software and Applications
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• v.28 no.10
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• pp.720-731
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• 2001

Complexity metrics have been developed for the structured paradigm of software development are not suitable for use with the object-oriented(OO) paradigm, because they do not support key object-oriented concepts such as inheritance, polymorphism. message passing and encapsulation. There are many researches on OO software metrics such as program complexity or design metrics. But metrics measuring the complexity of classes at the OO analysis phase are needed because they provide earlier feedback to the development project. and earlier feedback means more effective developing and less costly maintenance. In this paper, we propose the new metrics to measure the complexity of analysis classes which draw out in the analysis based on RUP(Rational Unified Process). By the collaboration complexity, is denoted by CC, we mean the maximum number of the collaborations can be achieved with each of the collaborator and determine the potential complexity. And the interface complexity, is denoted by IC, shows the difficulty related to understand the interface of collaborators each other. We verify theoretically the suggested metrics for Weyuker's nine properties. Moreover, we show the computation results for analysis classes of the system which automatically respond to questions of the user using the text mining technique. As a result of the comparison of CC and CBO and WMC suggested by Chidamber and Kemerer, the class that have highly the proposed metric value maintain the high complexity at the design phase too. And the complexity can be represented by CC and IC more than CBO and WMC. We can expect that our metrics may provide us the earlier feedback and hence possible to predict the efforts, costs and time required to remainder processes. As a result, we expect to develop the cost-effective OO software by reviewing the complexity of analysis classes in the first stage of SDLC(Software Development Life Cycle).

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.493-503
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• 2018

The present study is a conceptual replication of O'Grady, Lee, and Choo's (2003) earlier study designed to investigate two hypotheses (linear distance hypothesis vs. structural distance hypothesis) in relation to L2 Korean learners' processing of Korean subject and object relative clauses (RCs) in a scholarly attempt to explicate Keenan and Comrie's (1977) Noun Phrase Accessibility Hierarchy (NPAH). In addition, the current study is intended to explore any potential role of working memory capacity (WMC) in the processing of Korean subject and/or object RCs. Chinese-speaking learners of Korean taking a language course offered at a local university in Korea participated in this experimental study. Among those recruited, only 23 learners completed the experimental tasks appropriately according to the specific instructions provided on each task, and thus, subsequent statistical analyses were conducted on their data. Fifteen Korean NSs were also recruited for the control group. Two experimental tasks were administerd to the participants: one picture selection task containing the same test items used in O'Grady et al.'s study to measure their processing of subject-object RCs and an operation span (OSPAN) task to measure their WMC. Somewhat differently from O'Grady et al.'s findings, the participating Chinese learners of Korean performed significantly better on object RCs than on subject RCs, seemingly lending support to the linear distance hypothesis. Further analyses, however, suggested that the results in favor of, or relative ease of processing, object relative clauses were due, most likely, to the learners' excessive use of the canonical sentence strategy, which also led to nonsignificant correlations between WMC and learner performance on the picture selection task.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.411-423
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• 2003

In this paper we develop a method for calculating a probability that a particular generalized variance is the smallest of all the K multivariate normal generalized variances. The method gives a way of comparing K multivariate populations in terms of their dispersion or spread, because the generalized variance is a scalar measure of the overall multivariate scatter. Fully parametric frequentist approach for the probability is intractable and thus a Bayesian method is pursued using a variant of weighted Monte Carlo (WMC) sampling based approach. Necessary theory involved in the method and computation is provided.