• Journal of the Korean Magnetics Society
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• v.23 no.1
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• pp.26-30
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• 2013

This article is experimentally to investigate thermal-flow characteristics of the magnetic fluid for concentric annuli under externally fixed magnetic fields using visualization technique. Temperatures of the inner tube and outer tube in the tested concentric annuli were constantly maintained at both $30^{\circ}C$ and $25^{\circ}C$ and the middle tube was filled with the magnetic fluid. Magnetic field was uniformly applied using 4 permanent magnets at 4 directions of the concentric annuli. As a result, the thermal-flow characteristics of the magnetic fluid for concentric annuli could be controlled by directions of the external magnetic fields.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.111-118
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• 2015

Entity linking is to link entity's name mentions occurring in text to corresponding entities within knowledge bases. Since the same entity mention may refer to different entities according to their context, entity linking needs to deal with entity disambiguation. Most recent works on entity disambiguation focus on semantic relatedness between entities and attempt to integrate semantic relatedness with entity prior probabilities and term co-occurrence. To the best of my knowledge, however, it is hard to find studies that analyze and present the pure effects of semantic relatedness on entity disambiguation. From the experimentation on Korean Wikipedia data set, this article empirically evaluates entity disambiguation approaches using semantic relatedness in terms of the following aspects: (1) the difference among semantic relatedness measures such as NGD, PMI, Jaccard, Dice, Simpson, (2) the influence of ambiguities in co-occurring entity mentions' set, and (3) the difference between individual and collective disambiguation approaches.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1039-1055
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• 2014

The distribution of a test statistic under a null hypothesis depends on the unknown distribution of the data and thus is unknown as well. Conditional tests replace the unknown null distribution by the conditional null distribution, that is, the distribution of the test statistic given the observed data. This approach is known as permutation tests and was developed by Fisher (Fisher, 1935). Theoretical framework for permutation tests was given by Strasser and Weber(1999). The coin package developed by Hothon et al. (2006, 2008) implements a unified approach for conditional inference via the generic independence test. Because convenient functions for the most prominent problems are available, users will not have to use the extremely flexible procedure. In this article we briefly review the underlying theory from Strasser and Weber (1999) and explain how to transform the data to perform the generic function independence test. Finally it was illustrated with a few real data sets.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.971-986
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• 2014

When thousands of hypotheses are tested simultaneously, the probability of rejecting any true hypotheses increases, and large multiplicity problems are generated. To solve these problems, researchers have proposed different approaches to multiple testing methods, considering family-wise error rate (FWER), false discovery rate (FDR) or false nondiscovery rate (FNR) as a type I error and some test statistics. In this article, we discuss Bonferroni (1960), Holm (1979), Benjamini and Hochberg (1995) and Benjamini and Yekutieli (2001) procedures based on T statistics, modified T statistics or local-pooled-error (LPE) statistics. We also consider Sun and Cai (2007) procedure based on Z statistics. These procedures are compared in the simulation and applied to Arabidopsis microarray gene expression data to identify differentially expressed genes.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1293-1300
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• 2014

The temperature data influences on various policies of the country. In this article, the autoregressive error (ARE) model has been considered for analyzing the monthly and seasonal temperature data at the northern part of the Chungcheong Namdo, Seosan monitoring site in Korea. In the ARE model, five meteorological variables, four greenhouse gas variables and five pollution variables are used as the explanatory variables for the temperature data set. The five meteorological variables are wind speed, rainfall, radiation, amount of cloud, and relative humidity. The four greenhouse gas variables are carbon dioxide ($CO_2$), methane ($CH_4$), nitrous oxide ($N_2O$), and chlorofluorocarbon ($CFC_{11}$). And the five air pollution explanatory variables are particulate matter ($PM_{10}$), sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), ozone ($O_3$), and carbon monoxide (CO). The result showed that the monthly ARE model explained about 39-63% for describing the temperature. However, the ARE model will be expected better when we add the more explanatory variables in the model.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1371-1383
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• 2014

Classification ensemble technique is a method to combine diverse classifiers to enhance the accuracy of the classification. It is known that an ensemble method is successful when the classifiers that participate in the ensemble are accurate and diverse. However, it is common that an ensemble includes less accurate and similar classifiers as well as accurate and diverse ones. Ensemble pruning method is developed to construct an ensemble of classifiers by choosing accurate and diverse classifiers only. In this article, we proposed an ensemble pruning method called WAVE-bagging. We also compared the results of WAVE-bagging with that of the existing pruning method called Lasso-bagging. We showed that WAVE-bagging method performed better than Lasso-bagging by the extensive empirical comparison using 26 real dataset.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1315-1331
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• 2014

Replacement rates which shows the ratio of retirement income relative to preretirement income is used for a valuable evaluation measures while discussing social security benefit levels or the adequacy of retirement income. However, replacement rates has been only used for an index for evaluating benefit level at the time of retirement or specific retirement period in advanced research projects. This article analyzes how much the uncertainty of survival has an influence on retirement income, and shows replacement rates in conformity with the period of survival as an index. The researchers named this index lifetime income replacement rates. Analysis based on this index shows both life replacement income rates of 38.3% in men's case and of 41.1% in women's case while enrolled for 20years in three pension plans - national pension, retirement pension and individual annuity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1199-1205
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• 2021

In the era of big data, not only structured data well organized in databases, but also the Internet, social network services, it is very important to effectively analyze unstructured big data such as web documents, e-mails, and social data generated in real time in mobile environment. Big data analysis is the process of creating new value by discovering meaningful new correlations, patterns, and trends in big data stored in data storage. We intend to summarize and visualize the analysis results through frequency analysis of unstructured article data using R language, a big data analysis tool. The data used in this study was analyzed for total 104 papers in the Mon-May 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 1,538 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Journal of Korea Trade
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• v.25 no.1
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• pp.89-111
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• 2021

Purpose - The U.S. Trade Preference Expansion Act (TPEA) of 2015 enables the US Department of Commerce (DOC) to inflate dumping margin when the particular market situation (PMS) exists in the exporter's home market. DOC applied PMS provisions to the steel products from Korea. This paper analyzes whether DOC's calculation by using the regression analysis is consistent with WTO rules. Design/methodology - This paper analyzes the PMS application in law and regression analysis that extends the data period from 10 years to 18 years using the same economic model with DOC, and changes the country group according to the quantities of steelmaking capacity. Findings - Results show that DOC's argument conflating the sales-based with cost-based PMS designed to inflate dumping margins might not be consistent with WTO Antidumping Agreement Article 2.2 and 2.2.1.1 in which costs shall normally be calculated on the basis of records kept by the exporter, providing generally accepted accounting principles and reasonably reflection of the costs and PMS that exists in the Korean steel product markets. Even if it will be consistent, DOC's calculated margin by the regression analysis using a 10-year data is a big gap (5 times) compared with an 18-year data projection and different countries' data through the same methodology, which is a huge gap of regression coefficient. It means that dumping margin would be very wide range from 7.8% to 38.54% and unstable to calculate. Inflating dumping margin by DOC using regression analysis would not only be inconsistent with WTO rules, but also projection result is unreliable. Originality/value - Literature papers have mainly analyzed WTO law itself. This paper however, would be the first attempt to analyze the DOC's new way of dumping margin calculation in both manners of law and an empirical methodology perspective at the same time.

• Korean Journal of Heritage: History & Science
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• v.48 no.1
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• pp.132-147
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• 2015

In this article, the research trends regarding the analysis and restoration of the pigments applied on colored cultural properties during past 25 years are reviewed and the future research direction in this field of study is proposed. There are over 100 different pieces of the colored cultural property samples that have been analyzed in Korea during the time and are increasing numbers of studies on comparative investigations as well. In addition, new analysis techniques have been introduced to surpass the limitation of the current analysis techniques and the database construction has been developed tremendously, which will enhance the analysis reliability, indicating fast growth in the related research areas. There are also studies on finding new materials to replace the traditional ingredients for producing color pigments and related other materials to overcome the limitation of the traditional ingredients on top of the steady number of studies on reproduction and restoration of the traditional pigments. These various research efforts will bring much development in this area of research. One suggestion to be made is that there need to be long term planned research works for certain type of studies. For instance, the effect to the colored cultural properties due to the environmental change is one of important research topics that should be carefully studied, which requires longer time period and also more patience than the research works in the current and past trends.