• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.1073-1084
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• 2009

For ordinal categorical $R{\times}R$ tables, a weighted measure of association, $H_{\omega}$, was proposed and its maximum likelihood estimator and asymptotic variance were drived. We redefined the last paradox of ${\kappa}$ and proved its relation to marginal distributions. We also introduced the new paradox of ${\kappa}$ and summaried the general relationships between ${\kappa}$ and marginal distributions.

• The Journal of Korean Society for School & Community Health Education
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• v.15 no.2
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• pp.91-101
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• 2014

Objectives: This study aimed to identify agreement between smartphone addiction (SA) and perceived SA among adolescents. Methods: This survey was done with 394 subjects conveniently sampled from elementary school (ES), middle school (MS), academic (AHS) and vocational (VHS) high school. The data were collected from June 20 to July 20, 2013 with self-administered questionnaire and analyzed by descriptive statistics, chi-square test and Cohen's kappa (${\kappa}$). Results: High risk of SA showed 2.8% in total, 1.0% in ES, 2.1% in MS, 4.1% in AHS, and 4.0% in VHS, which was statistically different by type of school (p<0.001). Perceived SA showed 22.6% in total, 9.0% in ES, 21.9% in MS, 33.7% in AHS, and 26.0% in VHS, which was statistically different by type of school (p=0.003). The agreement between SA and perceived SA was 82.0% (${\kappa}$=0.54) in total, 91.8% (${\kappa}$=0.53) in ES, 75.0% (${\kappa}$=0.33) in MS, 77.5% (${\kappa}$=0.53) in AHS, and 84.8% (${\kappa}$=0.65) in VHS. Conclusion: The agreement between SA and perceived SA showed moderate in general, but fair in MS. It is suggested to develop step-by-step activities to reduce the gap between SA and perceived SA among adolescen, in particular, middle school students.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.417-426
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• 2018

An alternative developmental toxicity test using mouse embryonic stem cell derived embryoid bodies has been developed. This alternative method is not to administer chemicals to animals, but to treat chemicals with cells. This study suggests the use of Discriminant Analysis, Support Vector Machine, Artificial Neural Network and k-Nearest Neighbor. Algorithm performance was compared with accuracy and a weighted Cohen's kappa coefficient. In application, various classification techniques were applied to cytotoxicity data to classify drug toxicity and compare the results.

• Communications for Statistical Applications and Methods
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• v.5 no.2
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• pp.277-285
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• 1998

The smoothing parameter $\lambda$ in smoothing spline regression is usually selected by minimizing cross-validation (CV) or generalized cross-validation (GCV). But, simple CV or GCV is poor candidate for estimating prediction error. We defined MGCV (Multifold Generalized Cross-validation) as a criterion for selecting smoothing parameter in smoothing spline regression. This is a version of cross-validation using $leave-\kappa-out$ method. Some numerical results comparing MGCV and GCV are done.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.285-294
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• 2005

This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. Method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, three dimensional nonlinear equations are simplified to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, L-ME (or MME) is recommended to use for small sample size( n$\le$100) while MLE is good for large sample size.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.233-242
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• 2009

This paper presents two different types of supervised classifiers such as support vector machine (SVM) and spectral angle mapper (SAM). The Compact Airborne Spectrographic Imager (CASI) high resolution aerial image was classified with the above two classifier. The image was classified into eight land use /land cover classes. Accuracy assessment and Kappa statistics were estimated for SVM and SAM separately. The overall classification accuracy and Kappa statistics value of the SAM were 69.0% and 0.62 respectively, which were higher than those of SVM (62.5%, 0.54).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2311-2318
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Korean Journal of Remote Sensing
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• v.23 no.3
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• pp.153-160
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• 2007

Forest cover density studies using high resolution satellite data and object oriented classification are limited in India. This article focuses on the potential use of QuickBird satellite data and object oriented classification in forest density mapping. In this study, the high-resolution satellite data was classified based on NDVI/pixel based and object oriented classification methods and results were compared. The QuickBird satellite data was found to be suitable in forest density mapping. Object oriented classification was superior than the NDVI/pixel based classification. The Object oriented classification method classified all the density classes of forest (dense, open, degraded and bare soil) with higher producer and user accuracies and with more kappa statistics value compared to pixel based method. The overall classification accuracy and Kappa statistics values of the object oriented classification were 83.33% and 0.77 respectively, which were higher than the pixel based classification (68%, 0.56 respectively). According to the Z statistics, the results of these two classifications were significantly different at 95% confidence level.

• Journal of Korean Neurosurgical Society
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• v.60 no.4
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• pp.465-470
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• 2017

Objective : Magnetic resonance imaging (MRI) grading systems using sagittal images are useful for evaluation of lumbar foraminal stenosis. We evaluated whether such a grading system is useful as a diagnostic tool for surgery. Methods : Between July 2014 and June 2015, 99 consecutive patients underwent unilateral lumbar foraminotomy for lumbar foraminal stenosis. Surgically confirmed foraminal stenosis and the contralateral, asymptomatic neuroforamen were assessed based on a 4-point MRI grading system. Two experienced researchers independently evaluated the MR sagittal images. Interobserver agreement and intraobserver agreement were analyzed using ${\kappa}$ statistics. Results : The mean age of patients (54 women, 45 men) was 62.5 years. A total of 101 levels (202 neuroforamens) were evaluated. MRI grades for operated neuroforamens were as follows : Grade 0 in 0.99%, Grade 1 in 5.28%, Grade 2 in 14.85%, and Grade 3 in 78.88%. Interobserver agreement was moderate for operated neuroforamens (${\kappa}=0.511$) and good for asymptomatic neuroforamens (${\kappa}=0.696$). Intraobserver agreement by reader 1 for operated neuroforamens was good (${\kappa}=0.776$) and that for asymptomatic neuroforamens was very good (${\kappa}=0.831$). In terms of lumbar level, interobserver agreement for L5-S1 (${\kappa}=0.313$, fair) was relatively lower than the other level (${\kappa}=0.804$, very good). Conclusion : MRI grading system for lumbar foraminal stenosis is thought to be useful as a diagnostic tool for surgery in the lumbar spine; however, it is less reliable for symptomatic L5-S1 foraminal stenosis than for other levels. Thus, various clinical factors as well as the MRI grading system are required for surgical decision-making.

• Honam Mathematical Journal
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• v.24 no.1
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• pp.131-142
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• 2002

A $1{\frac{1}{2}}$-starcompact space has one of the most curious properties among the spaces of starcompactness. It is not too far away from countably compact spaces and may be considered as the first candidate for extending theorems about countably compact spaces. Unfortunately, $1{\frac{1}{2}}$-starcompactness is not so easy to be recognized as 2-starcompactness which will follow from countable pracompactness. We investigate some properties around $1{\frac{1}{2}}$-starcompact spaces.