• Journal of Korean Academy of Nursing
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• v.36 no.5
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• pp.770-781
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• 2006

Purpose: This study was designed to create a job description for Korean geriatric care managers and examine performance frequency, importance, and difficulty of task elements. Method: The sample consisted of 38 geriatric care managers and professors who performed duties related to geriatric care management at community based-facilities in Korea. A survey method was used, and the questionnaire included frequency, importance, and difficulty of task elements in job descriptions using the DACUM method. Using SPSS WIN 10.0, descriptive statistics such as frequency distribution, means, and standard deviation were conducted to examine the subject's general characteristics, frequency, importance, and difficulties of task performance. Result: The Job description of geriatric care managers revealed 10 duties, 34 tasks, and 105 task elements. On all ten duties, the average performance frequency, importance, and difficulty was 2.55, 2.21 and 2.43 respectively. Conclusion: The job description of geriatric care managers includes duty, task, and task elements and the definition of a completed job. Thus we recommend a data based trial to confirm and validate the information gathered.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.80-83
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• 2006

The purpose of this paper is to build a pronunciation lexicon with estimated likelihoods of the phonetic rules based on the phonetic realizations and therefore to improve the performance of CSR using the dictionary. In the baseline system, the phonetic rules and their application probabilities are defined with the knowledge of Korean phonology and experimental tuning. The advantage of this approach is to implement the phonetic rules easily and to get stable results on general domains. However, a possible drawback of this method is that it is hard to reflect characteristics of the phonetic realizations on a specific domain. In order to make the system reflect phonetic realizations, the likelihood of phonetic rules is reestimated based on the statistics of the realized phonemes using a forced-alignment method. In our experiment, we generates new lexica which include pronunciation variants created by reestimated phonetic rules and its performance is tested with 12 Gaussian mixture HMMs and back-off bigrams. The proposed method reduced the WER by 0.42%.

• Korean Journal of Human Ecology
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• v.9 no.4
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• pp.55-66
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• 2006

The purpose of this study was to identify the effect on the evaluation or a female teachers' role-performance based on appearance according to backgrounds of students and their parents. For this study, data was collected between October 19 and 29, 2005 by means of a questionnaire designed to gauge a subject's evaluation of a teacher's abilities in learning guidance, living guidance, and human relations. The researchers selected two middle schools and four high schools in the city of Gwang-ju. The 398 surveys completed were analyzed using factor analysis, one-way ANOVA, Duncan's multiple range test, t-test and descriptive statistics. According to the study, the evaluation of a female teacher's abilities varies with the backgrounds of both students and their parents. Among the students tested perceptions were affected by gender, grade level and type of school attended. For mothers there were differences based on age, occupation and family income.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.411-424
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• 2021

Inference following two-stage adaptive designs (also known as two-stage randomization designs) with survival endpoints usually focuses on estimating and comparing survival distributions for the different treatment strategies. The aim is to identify the treatment strategy(ies) that leads to better survival of the patients. The objectives of this study were to assess the performance three commonly cited methods for estimating survival distributions in two-stage randomization designs. We review three non-parametric methods for estimating survival distributions in two-stage adaptive designs and compare their performance using simulation studies. The simulation studies show that the method based on the marginal mean model is badly affected by high censoring rates and response rate. The other two methods which are natural extensions of the Nelson-Aalen estimator and the Kaplan-Meier estimator have similar performance. These two methods yield survival estimates which have less bias and more precise than the marginal mean model even in cases of small sample sizes. The weighted versions of the Nelson-Aalen and the Kaplan-Meier estimators are less affected by high censoring rates and low response rates. The bias of the method based on the marginal mean model increases rapidly with increase in censoring rate compared to the other two methods. We apply the three methods to a leukemia clinical trial dataset and also compare the results.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1487-1498
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• 2016

In monitoring a process, in-control process parameters must be estimated from the Phase I data. When we design the control chart based on the estimated process parameters, the control limits are usually chosen to satisfy a specific in-control average run length (ARL). However, as the run length distribution is skewed when the process is either in-control or out-of-control, the median run length (MRL) can be used as alternative measure instead of the ARL. In this paper, we evaluate the performance of Shewhart $\bar{X}$ chart with estimated parameters in terms of the average of median run length (AMRL) and the standard deviation of MRL (SDMRL) metrics. In simualtion study, the grand sample mean is used as a process mean estimator, and several competing process standard deviation estimators are used to evaluate the in-control performance for various amounts of Phase I data.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1079-1094
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• 2014

In this paper, we study efficient gene selection methods by using conditional mutual information. We suggest gene selection methods using conditional mutual information based on semiparametric methods utilizing multivariate normal distribution and Edgeworth approximation. We compare our suggested methods with other methods such as mutual information filter, SVM-RFE, Cai et al. (2009)'s gene selection (MIGS-original) in SVM classification. By these experiments, we show that gene selection methods using conditional mutual information based on semiparametric methods have better performance than mutual information filter. Furthermore, we show that they take far less computing time than Cai et al. (2009)'s gene selection but have similar performance.

• Journal of Distribution Science
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• v.14 no.6
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• pp.99-106
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• 2016

Purpose - The antecedent to the relationship between the effect of the characteristics of strategic alliances and the performance of container liner shipping companies has been investigated in this study as container liner shipping companies' strategic alliances. It affects positively and negatively home, partner, and the third parties' performance in container liner shipping companies. Extensive literature reviews on shipper's strategic alliances reveal that strategic alliances in financial and non-financial performance of container liner shipping companies show the performance such as economic effects, business performance, global supply chain management performance, customer satisfaction, and forward integration and backward integration performance. The purpose of this study is to test empirically that the relationship between the characteristics of strategic alliances and financial and non-financial performance in container liner shipping companies. Structured equation modeling and confirmatory factor analysis were used to test the hypothesis using AMOS statistics program. Most previous researches focused on the relationship between the characteristics of strategic alliances and alliance types. There are few empirical studies that focus on business performance data because it is difficult to collect data in container liner shipping companies. However, this research measures financial and non-financial performance differently compared with the previous researches focusing on the characteristics of strategic alliances and alliance types measurements. Research design, data, and methodology - The conceptual model for the study is based on the studies of Lim (2010), Chen & Zhen (2009), and Wang & Meng (2014). The model is built around the factors of characteristics of strategic alliances and business performance. Cost, marketing, and service factors are regarded as proxy for the characteristics of strategic alliances. The financial and non-financial performance are regarded as proxy for the performance of strategic alliances. Based on the analysis of one hundred cases such as forwarder, shipper, and liner shipping companies, this study uses structural equation modeling to verify the effects of the characteristics of strategic alliances on business performance. Conclusions - This study provides container liner shipping companies to get some policy and practical implications in terms of the characteristics of strategic alliances and business performance. First, the cost factor for alliances characteristics has a positively significant influence on the financial and non-financial performance of strategic alliances. The cost factor relationship between high and low performance group does not have a significant difference on the performance of strategic alliances. Second, the marketing factor of alliances characteristics has a positively significant influence on the financial and non-financial performance of strategic alliances. The high performance group's marketing factor has a great non-financial performance than low performance group, but the low performance group's marketing factor has a grater financial performance than high performance group factor does. Third, the service factor of alliances characteristics has a negative influence on the non-financial performance of strategic alliances. The high performance group's service factor has a great non-financial performance than low performance group. Based on the findings from this study, related implications and future avenues deserve to be discussed.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.327-340
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• 2008

This paper derives joint and conditional Lagrange multiplier tests based on information matrix for testing functional form and/or the presence of autocorrelation in a regression model. Small sample properties of these tests are assessed by Monte Carlo study and comparisons are made with LM tests based on Hessian matrix. The results show that the proposed $LM_E$ tests have the most appropriate finite sample performance.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.717-729
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• 2014

Projection pursuit classification tree uses a 1-dimensional projection with the view of the most separating classes in each node. These projection coefficients contain information distinguishing two groups of classes from each other and can be used to calculate the importance measure of classification in each variable. This paper reviews the variable importance measure with increasing interest in line with growing data size. We compared the performances of projection pursuit classification tree with those of classification and regression tree(CART) and random forest. Projection pursuit classification tree are found to produce better performance in most cases, particularly with highly correlated variables. The importance measure of projection pursuit classification tree performs slightly better than the importance measure of random forest.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.591-601
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• 2020

The self-organizing map (SOM) is a unsupervised learning method projecting high-dimensional data into low-dimensional nodes. It can visualize data in 2 or 3 dimensional space using the nodes and it is available to explore characteristics of data through the nodes. To understand the structure of data, cluster analysis is often used for nodes obtained from SOM. In cluster analysis, the optimal number of clusters is one of important issues. To help to determine it, various cluster validity indexes have been developed and they can be applied to clustering outcomes for nodes from SOM. However, while SOM has an advantage in that it reflects the topological properties of original data in the low-dimensional space, these indexes do not consider it. Thus, we propose a new cluster validity index for SOM based on connectivity between nodes which considers topological properties of data. The performance of the proposed index is evaluated through simulations and it is compared with various existing cluster validity indexes.