• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.815-824
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• 2013

Traditional Pearson chi-squared test is not appropriate for the data collected by the complex sample design. When one uses the traditional Pearson chi-squared test to the complex sample categorical data, it may give wrong test results, and the error may occur not only due to the biased variance estimators but also due to the biased point estimators of cell proportions. In this study, the design based consistent Wald test statistics was derived for k-population homogeneity test, and the traditional Pearson chi-squared test statistics was partitioned into three parts according to the causes of error; the error due to the bias of variance estimator, the error due to the bias of cell proportion estimator, and the unseparated error due to the both bias of variance estimator and bias of cell proportion estimator. An analysis was conducted for empirical results of the relative size of each error component to the Pearson chi-squared test statistics. The second year data from the fourth Korean national health and nutrition examination survey (KNHANES, IV-2) was used for the analysis. The empirical results show that the relative size of error from the bias of variance estimator was relatively larger than the size of error from the bias of cell proportion estimator, but its degrees were different variable by variable.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.459-461
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• 2012

본 논문에서는 식물재배기에 유입되는 조도 정보를 자동 센싱하여 대상 식물의 생육에 적합한 목표조도와 비교과정을 거쳐 LED의 밝기를 지능적으로 제어하기 위한 상황인식기반의 식물재배용 LED 제어 시스템을 구현하고자 한다. 먼저 식물 생육 환경 모니터링을 위해 조도, 온도, 습도, CO2 등의 이기종 센서들을 ZigBee 기반의 통합센서 형태로 설계 및 제작하고, GUI기반의 모니터링 시스템을 구현하여 실시간으로 식물 생육 환경 정보를 수집한다. 데이터베이스에 저장되어 있는 재배대상식물의 표본데이터 중 광보상과 광포화 정보를 기준으로 상황에 따라 변화하는 외부 조도정보와 비교하여 LED 인공광의 밝기를 시스템에 의한 자율 처리에 의해 지능적으로 제어함으로써 불필요한 조명 에너지 소비를 절감하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.163-167
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• 2012

이 연구는 실무능력이 중시되는 맥락에서 유용한 능력기반 학습환경의 구축방안을 모색해보고, 그 효과성을 실증적으로 탐색하는데 목적이 있다. 이를 위해 기존의 교수설계 패러다임의 발전동향을 토대로 능력기반 학습환경 구축원리를 도출하고, 이른 토대로 일반대학의 교직과목의 하나를 선정하여 구체적인 교수학습 환경을 개발하고, 기본적 실험설계의 틀에 그 효과성을 분석해 보았다. 그 결과 원래 해당 과목이 지향한 3개의 능력 중 2개 능력에서 실험집단이 비교집단보다 향상의 가능성을 보였다. 후속 연구에서는 이 학습환경 모형의 정련화와 아울러 효과검증 방법론을 보다 정련화하고, 표본수 증대를 통한 통계학적 검증이 요청된다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.21-28
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• 2017

This study aims to identify individual and familial factors associated with youth sexual experience by using the nationally representative sample data in South Korea. Specifically, we select 68,043 students in middle and high schools participating in the 2015 Korea Youth Risk Behavior Web-based Survey. Considering the complex survey design, we conduct a descriptive analysis and multiple logistic regression for sexual experience. The main results identify factors on sexual experience such as age, type of school, stress level, drinking, smoking, economic status, and cohabiting parents. In particular, the drinking and smoking behaviors are positively associated with sexual experience and the youth living with neither parent is more likely to have a sexual experience than those who lived two parents. In conclusion, the plan of sex education should consider the risk factors and the quality of sex education should be enhanced in order to build more appropriate sexual culture and behaviors among the youth.

• Journal of Korean Society of Forest Science
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• v.107 no.4
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• pp.402-411
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• 2018

This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.

• Journal of Internet Computing and Services
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• v.19 no.2
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• pp.17-26
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• 2018

Recently, through the emergence and convergence of Internet services, the unified Internet of thing(IoT) service platform have been researched. Currently, the IoT service is constructed as an independent system according to the purpose of the service provider, so information exchange and module reuse are impossible among similar services. In this paper, we propose a operation based service classification algorithm for various services in order to provide an environment of unfied Internet platform. In implementation, we classify and cluster more than 100 commercial IoT services. Based on this, we evaluated the performance of the proposed algorithm compared with the K-means algorithm. In order to prevent a single clustering due to the lack of sample groups, we re-cluster them using K-means algorithm. In future study, we will expand existing service sample groups and use the currently implemented classification system on Apache Spark for faster and more massive data processing.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.464-475
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• 2003

few sample objects and compressed histogram information of image databases. The histogram information is used to estimate the selectivity of spherical range queries and a small number of sample objects is used to compensate the selectivity error due to the difference of the similarity measures between meta server and local image databases. An extensive experiment on a large number of image data demonstrates that our proposed method performs well in the distributed heterogeneous environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.29-36
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• 2012

In Wireless Sensor Network(WSN)s, the detection of precise location of each node is essential for utilizing sensing data acquired from sensor nodes effectively. Among various location methods, the received signal strength(RSS) based localization scheme is mostly preferable in many applications because it can be easily implemented without any additional hardware cost. Since a RSS-based localization scheme is mainly affected by radio channel or obstacles such as building and mountain between two nodes, the localization error can be inevitable. To enhance the accuracy of localization in RSS-based localization scheme, a number of RSS measurements are needed, which results in the energy consumption. In this paper, a RSS based localization using Bayesian Compressive Sensing(BSS) with path-loss exponent estimation is proposed to improve the accuracy of localization in the energy-efficient way. In the propose scheme, we can increase the adaptative, reliability and accuracy of localization by estimating the path-loss exponents between nodes, and further we can enhance the energy efficiency by the compressive sensing. Through the simulation, it is shown that the proposed scheme can enhance the location accuracy of multiple unknown nodes with fewer RSS measurements and is robust against the channel variation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.42-50
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• 2021

The purpose of this study was to identify and analyze the communication behavior styles of hemodialysis nurses based on the structured Q-methodology. The Q-population was formulated based on literature reviews and in-depth interviews with 10 hemodialysis nurses who were working in hospitals in Seoul and Anyang-si, Gyeonggi Province. A total of 50 Q-samples, which were believed to best represent the communication behavior styles of hemodialysis nurses, were selected from the Q-population by the author and a professor majoring in nursing. 30 P-samples were selected from hemodialysis nurses who were working in primary, secondary, and tertiary hospitals in Seoul. Q-sorting was performed by P-samples and data was analyzed through the pc-QUANL program. The results suggested that there are four types of communication behavior styles of hemodialysis nurses, namely: "type I: listening and speaking courteously with an active mind", "type II: listening and speaking courteously with a receptive mind", "type III: advising with an explanation" and "type IV: super-reasonable with a defensive mind". It is expected that the analytical results described here may provide basic information that can be used to develop educational material for hemodialysis nurses.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.809-818
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• 2014

Multivariate skew-normal distribution(distribution that includes multivariate normal distribution) has been recently applied to many application areas. We consider saddlepoint approximation for a statistic of linear combination based on a multivariate skew-normal distribution. This approach can be regarded as an extension of Na and Yu (2013) that dealt saddlepoint approximation for the distribution of a skew-normal sample mean for a linear statistic and multivariate version. Simulations results and examples with real data verify the accuracy and applicability of suggested approximations.