• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.201-210
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• 2004

The peakedness ordering is closely related to dispersive ordering. In this paper we consider the statistical inference concerning peakedness ordering between two arbitrary symmetric distributions. Nonparametric maximum likelihood estimates of two distribution functions under symmetry and peakedness ordering are given. The likelihood ratio test for equality of two symmetric discrete distributions in the sense of peakedness ordering is studied.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.63-74
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• 1996

Ordering plays an important role in solving an LP problem with sparse matrix by the interior point method. Since ordering is NP-complete, we try to find an efficient method. The objective of this paper is to present an efficient heuristic ordering method for implementation of the minimum deficiency method. Both the ordering method and the data structure play important roles in implementation. First we define a new heuristic pseudo-deficiency ordering method and a data structure for the method-quotient graph and cliqued storage. Next we show an experimental result in terms of time and nonzero numbers by NETLIB problems.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.10
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• pp.544-555
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• 2003

Since the result data from DNA microarray experiments contain a lot of gene expression information, adequate analysis methods are required. Hierarchical clustering is widely used for analysis of gene expression profiles. In this paper, we study leaf-ordering, which is a post-processing for the dendrograms output by hierarchical clusterings to improve the efficiency of DNA microarray data analysis. At first, we analyze existing leaf-ordering algorithms and then present new approaches for leaf-ordering. And we introduce a software HCLO(Hierarchical Clustering ＆ Leaf-Ordering Tool) that is our implementation of hierarchical clustering, some of existing leaf-ordering algorithms and those presented in this paper.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.205-216
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• 2019

Diagnostic tests in medical fields detect or diagnose a disease with results measured by continuous or discrete ordinal data. The performance of a diagnostic test is summarized using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The diagnostic test is considered clinically useful if the outcomes in actually-positive cases are higher than actually-negative cases and the ROC curve is concave. In this study, we apply the stochastic ordering method in a Bayesian hierarchical model to estimate the proper ROC curve and AUC when the diagnostic test results are measured in discrete ordinal data. We compare the conventional binormal model and binormal model under stochastic ordering. The simulation results and real data analysis for breast cancer indicate that the binormal model under stochastic ordering can be used to estimate the proper ROC curve with a small bias even though the sample sizes were small or the sample size of actually-negative cases varied from actually-positive cases. Therefore, it is appropriate to consider the binormal model under stochastic ordering in the presence of large differences for a sample size between actually-negative and actually-positive groups.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.413-428
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• 2003

If a restriction is imposed only to a (proper) subset of parameters of interest, we call it a local restriction. Statistical inference under a local restriction in multinomial setting is studied. The maximum likelihood estimation under a local restriction and likelihood ratio tests for and against a local restriction are discussed. A real data is analyzed for illustrative purpose.

• Korean Management Science Review
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• v.12 no.2
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• pp.31-42
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• 1995

The ordering method is used to reduce the fill-ins in interior point methods. In ordering, the data structure plays an important role. In this paper, first, we compare the efficiency and the memory storage requirement of the quotient graph structure and the clique storage. Next, we propose a method of reducing the number of cliques and a data structure for clique storage. Finally, we apply a method of merging rows and absorbing cliques and show the experimental results.

• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.134-141
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• 2012

It is difficult to find an appropriate ordering policy for a many types of items. One of the reasons for this difficulty is that each item has a different demand trend. We will classify items by shipment trend and then decide the ordering policy for each item category. In this study, we indicate that categorizing items from their statistical characteristics leads to an ordering policy suitable for that category. We analyze the ordering policy and shipment trend and propose a new method for selecting the ordering policy which is based on finding the strongest relation between the classification of the items and the ordering policy. In our numerical experiment, from actual shipment data of about 5,000 items over the past year, we calculated many statistics that represent the trend of each item. Next, we applied the canonical correlation analysis between the evaluations of ordering policies and the various statistics. Furthermore, we applied the cluster analysis on the statistics concerning the performance of ordering policies. Finally, we separate items into several categories and show that the appropriate ordering policies are different for each category.

• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.1-14
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• 2015

The purpose of this paper is to reveal two problems in the existing inventory systems in retail market, and to suggest a Two-Bin System under Automatic Ordering System considering only base-stock. Large retailers already have a sophisticated inventory system based on an automatic ordering principle. However, why does the out-of-stock (OOS) happen in large discount stores in spite of having a good inventory system? This paper suggests two systems after finding the root causes concerning the previous question. For evaluating the performance of each system, the random 200 data set in each sample group was generated from MINITAB 16 and obeyed the Poisson distribution. The existing inventory system in retail market cannot help generating OOS due to indwelling contradiction in itself. The reasons are the ordering deadline and the relationship between ordering quantity and base stock. This paper also demonstrates that these previous studies on inventory fall into the closed loop. Also the paper shows that the performance of the replenishment policy was better than traditional methods dealing with ordering quantity and base stock.

• English Language & Literature Teaching
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• v.15 no.2
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• pp.121-150
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• 2009

This paper deals with contrastive analysis and interlanguage with respect to adjective ordering. It aimed to investigate how similar and different the orders of descriptive adjectives are in English and Korean, and how Korean EFL learners perceive the sequences of English descriptive adjectives. Data were collected from native English speakers and native Korean speakers and Korean EFL learners. The contrastive analysis showed that the order of English adjectives was size, opinion, condition, age, color, shape, material, and origin, whereas the Korean order was condition, age, opinion, color, size, shape, material, and origin. The relative order of the interlanguage was shown to be age, size, opinion, shape, condition, color, origin, and material, with the exceptions of the order of condition preceding age and that of size being the same position as condition. The interlanguage data manifested different aspects of ordering when compared with English and Korean: Some adjective combinations were similar to both English and Korean; Some were different from English or Korean; Some were different from both English and Korean. These ordering patterns are discussed in terms of such principles as the nouniness principle, the subjectivity/objectivity principle, the iconic principle, etc. On the basis of these results, some helpful suggestions are made.

• Proceedings of the IEEK Conference
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• 2003.11c
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• pp.302-305
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• 2003

3GPP RLC protocol specification adopted an error control scheme based on selective repeat ARQ. In the 3GPP ARQ, distinctive windows are provided at transmitting and receiving stations so that those stations are prohibited to send or receive data PDU's out of window. An increase in window size enhances delay performance. Such an increase, however, raises the occupancy at re-ordering buffer, which results in a long re-ordering time. Aiming at suppressing the occupancy at re-ordering buffer, we propose partial go back N scheme in this paper In the partial go back N scheme, the receiving station regards all data PDU's between the first (lowest sequence numbered) error-detected PDU and last (highest sequence numbered) error-detected PDU. By the employment of the partial go back N scheme, the occupancy at the re-ordering buffer is apparently reduced, while the delay and throughput performance may be degraded due to the remaining properties of go back N. We thus consider peak occupancy of re-ordering buffer, mean sojourn time at re-ordering buffer, mean delay time, and maximum throughput as measures to evaluate tile proposed scheme and investigate such performance by using a simulation method. From numerical examples, we observe a trade-off among performance measures and conclude that the partial go back N scheme is able to effectively reduce the occupancy of re-ordering buffer.