• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.107-117
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• 2004

Change point testing problem is considered. Kernel density estimators are used for constructing proposed change point test statistics. The proposed method can be used to the hypothesis testing of not only parameter change but also distributional change. Bootstrap method is applied to get the sampling distribution of proposed test statistic. Small sample Monte Carlo Simulation were also conducted in order to show the performance of proposed method.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.669-678
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• 2007

An algorithm to detect the number of discontinuity points of the variance function in regression model is proposed. The proposed algorithm is based on the left and right one-sided kernel estimators of the second moment function and test statistics of the existence of a discontinuity point coming from the asymptotic distribution of the estimated jump size. The finite sample performance is illustrated by simulated example.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.451-457
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• 2010

This paper considers the problem of nonparametric deconvolution density estimation when sample observa-tions are contaminated by double exponentially distributed errors. Three different deconvolution density estima-tors are introduced: a weighted kernel density estimator, a kernel density estimator based on the support vector regression method in a RKHS, and a classical kernel density estimator. The performance of these deconvolution density estimators is compared by means of a simulation study.

• Journal of Integrative Natural Science
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• v.14 no.3
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• pp.73-77
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• 2021

Robust design is an approach to reduce the performance variation of mutiple responses in products and processes. In fact, in many experimental designs require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

• The Journal of Korean Academic Society of Nursing Education
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• v.18 no.2
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• pp.293-302
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• 2012

Purpose: The purpose of this study was to investigate nursing students' awareness and performance on standard precautions and to provide meaningful information for nursing students' education regarding hospital infection control. Method: Four hundred forty seven nursing students at 6 universities in D-city participated in this study. Data collection was conducted from March to April 2011. Students' awareness and performance on standard precautions of infection control in hospitals were measured using the modified 2007 CDC standard precautions guidelines. Data analysis was performed using the SPSS WIN 18.0 program, descriptive statistics, t-test, and ANOVA. Results: The level of students' awareness in the standard precautions was higher than performance. The higher levels of students' awareness and performance on standard precautions included patient care equipment, safe injection practices, and worker safety. The lower levels of students' awareness and performance on standard precautions included hand hygiene and personal protective equipment. There was no difference in the students' awareness and performance of standard precautions according to their characteristics. Conclusions: Based on the findings of this study, hand hygiene and personal protective equipment need to be stressed more within the program to improve nursing students' infection control techniques.

• Journal of Information Management
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• v.40 no.1
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• pp.1-27
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• 2009

The study investigated the indicators for information service system performance measurement through the review on the related literatures, and developed 16 indicators for the performance measurement in 4 areas of library visit, lending, reference service and user instruction, and electronic service. And then with the indicators, the study surveyed 6 academic libraries including each 2 of large, middle, and small sized academic libraries. Based on the survey results, the study made a proposal for the application of performance indicator and the improvement of information service system performance.

• The Korean Journal of Rehabilitation Nursing
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• v.17 no.2
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• pp.90-96
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• 2014

Purpose: The purpose of this study was to determine the effects of simulation based training using a post-operating rehabilitation case on learning outcomes in nursing students. Methods: A quasi-experimental research design (one group pretest and posttest design) and a questionnaire for measuring learning outcomes were used in this study. The participants were 35 students in a college of nursing. Data were collected before the program and immediately after the program that applied simulation based training using a post-operating rehabilitation case consisted of 4th running and debriefing for 26 hours. With SAS 9.2 program, descriptive statistics and paired t-test were used to analyze the data. Results: There were statistically significant increases in necessity (p=.001) and performance of learning outcome (p<.001) of simulation based training using a post-operating rehabilitation case among students in a college of nursing. Conclusion: The findings of this study demonstrate that simulation based training using a post-operating rehabilitation case for nursing students may increase performance of learning outcomes on clinical reasoning and critical thinking.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.615-632
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• 2017

Unlike randomized trial, statistical strategies for inferring the unbiased causal relationship are required in the observational studies. The matching with the propensity score is one of the most popular methods to control the confounders in order to evaluate the effect of the treatment on the outcome variable. Recently, new methods for the causal inference in latent class analysis (LCA) have been proposed to estimate the average causal effect (ACE) of the treatment on the latent discrete variable. They have focused on the application study for the real dataset to estimate the ACE in LCA. In practice, however, the true values of the ACE are not known, and it is difficult to evaluate the performance of the estimated the ACE. In this study, we propose a method to generate a synthetic data using the propensity score in the framework of LCA, where treatment and outcome variables are latent. We then propose a new method for estimating the ACE in LCA and evaluate its performance via simulation studies. Furthermore we present an empirical analysis based on data form the 'National Longitudinal Study of Adolescents Health,' where puberty as a latent treatment and substance use as a latent outcome variable.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.126-134
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• 2009

This paper describes the vision-based system to track road signs from within a moving vehicle. The proposed system has the standard architecture with particle filter due to its robust tracking performance in complex environment. In the case of tracking road signs in real environment, it has a great difficulty in predicting time series data by reason of an occlusion due to an obstacle and the rapid change of objects on roads. To overcome this problem and improve the tracking performance, this paper proposes the algorithm using an autoregressive model as an state transition model which has affine parameters as states and using robust statistics for determining occlusion due to obstacles. The experiments of this paper show that the proposed method is efficient for real time tracking of road signs and performs well in road signs under occlusion due to obstacles.

• Journal of the Korea Society of Computer and Information
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• v.19 no.11
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• pp.43-52
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• 2014

In this paper, we propose the target detection method using image displacement, and classification method using SURF(Speeded Up Robust Features) feature points and BAS(Beam Angle Statistics) in infrared images. The SURF method that is a typical correspondence matching method in the area of image processing has been widely used, because it is significantly faster than the SIFT(Scale Invariant Feature Transform) method, and produces a similar performance. In addition, in most SURF based object recognition method, it consists of feature point extraction and matching process. In proposed method, it detects the target area using the displacement, and target classification is performed by using the geometry of SURF feature points. The proposed method was applied to the unmanned target detection/recognition system. The experimental results in virtual images and real images, we have approximately 73~85% of the classification performance.