• Knowledge Management Research
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• v.10 no.2
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• pp.35-48
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• 2009

The paper proposes a quantitative causal ordering map (QCOM) to combine qualitative and quantitative methods in a framework. The procedures for developing QCOM consist of three phases. The first phase is to collect partially known causal dependencies from experts and to convert them into relations and causal nodes of a model graph. The second phase is to find the global causal structure by tracing causality among relation and causal nodes and to represent it in causal ordering graph with signed coefficient. Causal ordering graph is converted into QCOM by assigning regression coefficient estimated from path analysis in the third phase. Experiments with the prediction model of Korea stock price show results as following; First, the QCOM can support the design of qualitative and quantitative model by finding the global causal structure from partially known causal dependencies. Second, the QCOM can be used as an integration tool of qualitative and quantitative model to offerhigher explanatory capability and quantitative measurability. The QCOM with static and dynamic analysis is applied to investigate the changes in factors involved in the model at present as well discrete times in the future.

• Bulletin of the Korean Chemical Society
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• v.27 no.7
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• pp.972-973
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• 2006

• East Asian Economic Review
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• v.22 no.4
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• pp.507-529
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• 2018

This paper evaluates the whole impact of quantitative easing on inflation in Korea implemented by the central banks in four major advanced economies, the U.S., Euro Area, U.K. and Japan. According to the analysis employing a VAR-X model with the security holdings of those central banks an exogenous variable, quantitative easing is estimated to exert downward pressures on inflation in Korea. Considering the impulse responses of Korean macroeconomic variables to a quantitative easing shock, the spillover effect is transmitted through exchange rate channel while trade channel turns out to be ineffective. In an additional analysis assessing the impact of each quantitative easing program of the central banks, only those of the Fed and European Central Bank are estimated to be significant. The empirical results prove to be robust even if using long-term interest rates as an alternative indicator of quantitative easing.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1057-1064
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• 2007

From the view of natural language process, quantitative linguistic analysis is a linguistic study relying on statistical methods, and is a mathematical linguistics in an attempt to discover various linguistic characters by interpreting linguistic facts quantitatively through statistical methods. In this study, I would like to introduce a quantitative linguistic analysis method utilizing a computer and statistical methods on literary works. I also try to introduce a use of SynKDP, a synthesized Korean data process, and show the relations between distribution of linguistic unit elements which are used by the hero in a novel #Sassinamjunggi# and theme analysis on literary works.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.115-125
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• 2018

In order to examine the ways to improve the efficiency of R&D investment, this paper presents analysis on both quantitative and qualitative efficiency of R&D projects. As Korea's R&D investment has significantly increased in recent years, the efficiency of R&D investment has attracted attention. In this paper, a Data Envelopment Analysis(DEA) method is used to construct models for quantitative efficiency and qualitative efficiency analysis. Based on a cases of agricultural R&D projects of Korea, the efficiency of national R&D projects were analyzed and their quantitative and qualitative efficiencies are compared. As a result, statistically significant difference between quantitative and qualitative efficiency was found. Also, characteristics of Decision Making Units(DMUs) which can influence both quantitative and qualitative efficiency were identified. In particular, the stage of a R&D project has significant impact on R&D efficiency. This study suggests that in order to enhance R&D efficiency both quantitative and qualitative nature of outputs should be considered when measuring R&D efficiency.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.118-127
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• 2020

The paper introduces trends and methodological challenges of quantitative Korean text analysis by using the case studies of academic and news media articles on "migration" and "immigration" within the periods of 2017-2019. The quantitative text analysis based on natural language processing technology (NLP) and this became an essential tool for social science. It is a part of data science that converts documents into structured data and performs hypothesis discovery and verification as the data and visualize data. Furthermore, we examed the commonly applied social scientific statistical models of quantitative text analysis by using Natural Language Processing (NLP) with R programming and Quanteda.

• Bulletin of the Korean Chemical Society
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• v.30 no.5
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• pp.1026-1030
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• 2009

A novel Schiff base ligand (N, O system) 5-methoxy-2-phenyliminomethylphenol ($5-CH_3O-PMP$) was synthesized. Using the synthesized ligand as a fluorescent reagent, a fluorometric method was developed for the quantitative analysis of Al(III) ion. The quantitative analysis of Al(III) ion was performed by making the complex compound between Al(III) ion and $5-CH_3O-PMP$ in ethanol-water solution (85/15, v/v, pH 6.2). The excitation wavelength (${\lambda}em$) of the complex compound was 397 nm while the emmision wavelength (${\lambda}em$) was 498 nm. The quantitative analysis of Al(III) ion was carried out by estimating the fluorescence intensity. The various calibration curves were used for the quantitative analysis in the range of 0.27$\sim$27 ng/mL Al(III) ion concentrations. The detection limit was 0.027 ng/mL. Using the fluorometric method developed in this study, satisfying results were obtained from various samples such as tap water, hot spring water, river water, sea water and waste water, which contained considerable amounts of interfering ions.

• Journal of the Korean Magnetic Resonance Society
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• v.20 no.1
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• pp.7-12
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• 2016

PTMEG(Polytetramethylene ether glycol) is a polymer compound widely used as a wide range of applications in the textile industry. PTMEG substance carrying various 1,800~2,000 molecular weight are mainly used as the raw material of the spandex production. Molecular weight and degree of polymerization value for 4 different PTMEG samples under pilot plant scale synthetic process were determined by a new quantitative NMR method. In NMR experiments, p-toluenesulfonic acid(TSOH) was used for external standard material of PTMEG quantitative analysis. were measuring The concentration of the primary standard TSOH was measured by UV/Vis spectroscopy. By using NMR peak assignments and the integral values of designated proton NMR peaks, We were able to measure the % composition of the synthetic PTMEG polymers, concentrations, molecular weight and the degree of polymerization that show the synthetic process of each manufacturing pilot plant. By utilizing a newly developed quantitative NMR method were able to obtain the molecular weight of PTMEG samples within 0.08 error % range.

• 대한핵의학회:학술대회논문집
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• 2001.05a
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• pp.60-65
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• 2001

The positron emission tomography (PET) has been used for the evaluation of the characteristics of various tumors. The role of PET in oncology has been evolved from a pure research tool to a methodology of enormous clinical potential. The unique characteristics of PET imaging make sophisticated quantitation possible. Several quantitative methods, such as standardized uptake values (SUV), simplified quantitative method, Patlak graphical analysis, and Sokoloff's glucose metabolism measurement, have been used in the field of oncology. However, each quantitative method has limitations of its own. For example, the SUV has been used as a quantitative index of glucose metabolism for tumor classification and monitoring response to treatment, even though it depends on blood glucose level, body configuration of patient, and scanning time. The quantitative methods of PET are reviewed and strategy for implementing these methods are presented.

• The Korean Journal of Malacology
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• v.28 no.4
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• pp.363-375
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• 2012

The gametogenic cycle, the number of spawning seasons per year and first sexual maturiity of the pen shell, Atrina (Servatrina) pectinata, were investigated by quantitative statistical analysis using an Image Analyzer System. Compared two previous results (the spawning periods in the reproductive cycles in 1998 and 2006) by qualitative histological analysis with the present results by quantitative statistical analysis, there are some differences in the spawning periods: the spawning period (June to September) by quantitative statistical analysis was one month longer than those of two previous reports (June to July or June to August) by qualitative histological analysis. However, the number of spawning seasons studied by the qualitative and quatitative analyses occurred once per year. In quantitative statistical analysis using an image analyzer system, the patterns of monthly changes in the percent (%) of the areas occupied by follicles to the ovary area in females (or that of the areas occupied by spermatogenic stages to the testis area in males) showed a maximum in May, and then sharply droped from June to September, 2006. From these data, it is apparent that the spawning season of A. (S.) pectinata occurred once a year from June to September, indicating a unimodal gametogenic cycle during the year. Shell heights of sexually mature pen shells (size at 50% of group sexual maturity, $GM_{50}$) that were fitted to an exponential equation were 15.81 cm in females and 15.72 cm in males (considered to be one year old).