• Journal of Wetlands Research
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• v.21 no.spc
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• pp.61-68
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• 2019

Recently, climate indices represented by quantifying atmospheric-ocean circulation patterns have been widely used to predict hydrologic variables for considering long-term climate variability. Hydrologic forecasting models based on artificial neural networks have been developed to provide accurate and stable forecasting performance. Forecasts of hydrologic variables considering climate variability can be effectively used for long-term management of water resources and environmental preservation. Therefore, identifying significant indicators for hydrologic variables and applying forecasting models still remains as a challenge. In this study, we selected representative climate indices that have significant relationships with dam inflow time series in the Han-River basin, South Korea for applying the dam inflow forecasting model. For this purpose, the ensemble empirical mode decomposition(EEMD) method was used to identify a significance between dam inflow and climate indices and an artificial neural network(ANN) ensemble model was applied to overcome the limitation of a single ANN model. As a result, the forecasting performances showed that the mean correlation coefficient of the five dams in the training period is 0.88, and the test period is 0.68. It can be expected to come out various applications using the relationship between hydrologic variables and climate variability in South Korea.

• Journal of Korea Port Economic Association
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• v.26 no.1
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• pp.61-82
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• 2010

The purpose of this study is to examine the causuality among export and import trading volume of port of Busan, Kwangyang, Incheon and to induce policy implications. In order to test whether time series data is stationary and the model is fitness or not, we put in operation unit root test, cointegration test. And We apply Granger causality and impulse response and variance decomposition based on VECM. The results indicate that the trading volume of port of Busan is not largely influenced by that of port of Kawangyang and Incheon, but the trading volume of port of Kawangyang and Incheon is largely influenced by other ports including port of Busan. The result suggest that government has to focus on policy that the port of Kawangyang and Incheon can raise its own competitiveness in the world market.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.1
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• pp.29-39
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• 2020

A series of struvite (MgNH₄PO₄·6H₂O) was synthesized and dried at various temperatures (15-60℃). Crystallization of struvite and its structural properties were significantly influenced by synthetic and drying temperature. Struvite was favorably formed at synthetic temperatures ≤30℃ with an inverse relationship between the crystallinity and synthetic temperature. The crystallinity of struvite was also significantly reduced by an increase in drying temperature from 45℃ to 60℃ due to the loss of structural water molecules and ammonium ions by the facilitated thermal decomposition. However, struvite formed at lower synthetic temperature showed higher crystallinity, and its amorphization by thermal decomposition was inhibited. These results demonstrate that struvite formed at low temperature with an stable condition thermodynamically through favorable crystallization shows high crystallinity and stability with respect to the structural and thermal resistance.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.889-900
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• 2006

Even though sensor networks are different in user requests and data characteristics depending on each application area, the existing researches on stream data transmission problem focus on the performance improvement of their methods rather than considering the original characteristic of stream data. In this paper, we introduce a hierarchical or distributed sensor network architecture and data model, and then evaluate the multivariate data reduction methods suitable for user requirements and data features so as to apply reduction methods alternatively. To assess the relative performance of the proposed multivariate data reduction methods, we used the conventional techniques, such as Wavelet, HCL(Hierarchical Clustering), Sampling and SVD (Singular Value Decomposition) as well as the experimental data sets, such as multivariate time series, synthetic data and robot execution failure data. The experimental results shows that SVD and Sampling method are superior to Wavelet and HCL ia respect to the relative error ratio and execution time. Especially, since relative error ratio of each data reduction method is different according to data characteristic, it shows a good performance using the selective data reduction method for the experimental data set. The findings reported in this paper can serve as a useful guideline for sensor network application design and construction including multivariate stream data.

• Journal of Korean Society of Forest Science
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• v.88 no.1
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• pp.1-10
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• 1999

The dynamic relationships among import prices of roundwood are analyzed using the time series approach. A vector autoregression(VAR) model is estimated for six import prices(New Zealand, Chile, Russia, U.S.A., PNG, and Malaysia). Then Granger's causality test, variance decomposition analysis, and impulse response function analysis are also conducted. The major results are summarized as follows : (1) The prices of New Zealand and Russia are caused by only own lagged prices. (2) The prices of Chile and PNG are effected by New Zealand, the price of PNG is effected by New Zealand and Russia, and the price of U.S.A. is effected by those of Chile and PNG, respectively. (3) An exogenous shock in New Zealand will affect the prices of New Zealand, PNG, U.S.A., Chile, Russia. (4) An exogenous shock in Chile may also affect the prices of Chile, U.S.A., Russia.

• Bulletin of the Korean Chemical Society
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• v.31 no.4
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• pp.976-980
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• 2010

A series of arylacetylene resins with siloxane units were synthesized by the condensation reactions of m-diethynylbenzene magnesium reagents with various $\alpha,\omega$-bis(chloro)dimethylsiloxanes. These resins are liquids and are miscible with common organic solvents at room temperature. The structures of the resins were characterized by FT-IR, $^1H$ NMR, $^{13}C$ NMR, $^{29}Si$ NMR, and gel permeation chromatography (GPC). The thermal behaviors of the resins were examined with differential scanning calorimetry (DSC). These resins have good processability. They can be thermally cross-linked through the ethynyl groups to produce cured resins. The thermal and thermooxidative stabilities of the cured resins were studied by thermogravimetric analysis (TGA). The cured resins possess high thermal and thermooxidative stability. Their decomposition occurs at above $500^{\circ}C$ in both $N_2$ and air. With increasing the length of siloxane units in the resins, the thermal stability of the cured resins decreases in $N_2$. When the cured resins were sintered above $1450^{\circ}C$ under argon, hard and glassy SiOC ceramics were obtained. These SiOC ceramics have the decomposition temperatures at 5% weight loss above $800^{\circ}C$ in air.

• International Area Studies Review
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• v.13 no.1
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• pp.55-79
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• 2009

This papers studies the causalities and effects on the relationship between international trade and economic growth in China for the period of 1950-2007, using the unit root test, the Granger causality test, the cointegration test, VAR model, and VECM. The results of this study are as follows: Firstly, in the unit root test, I found that each time series was unstable one that has unit root. Secondly, in the Granger Causality test, this papers shows that variable dlexp and dlinp influence on dlgdp and dlgdd, while bilateral causality relation between dlexp and dlgdp, dlexp and dlgdd for the whole period, for the whole period, pre-reform period and post-reform period. Thirdly, there is no cointegraion relation between lgdp(or dlgdp, lgdd, dlgdd) and lexp, linp for lgdd-limp in the whole period, and pre-reform period, while no cointegration relation for the post-reform period. Finally, in the impulse-response test, it was proved that lgdp represents (-) correlation with lexp for the whole period. Thorough the variance decomposition test, it was proved that linp(or dlinp) is the most affected variable of the each data and relation between linp(or dlinp) and lexp(or dlexp) has become bigger recently.

• Journal of Korea Trade
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• v.27 no.5
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• pp.113-136
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• 2023

Purpose - Global production chains and their impacts on economic growth have drawn extensive attention from researchers. Close relationships among global production chains, export and economic growth have been illuminated, as evidenced by the fast and stable economic growth of East Asian economies. These economies perform various roles within global production chains using offshoring, in which the impact of import on domestic gross output is as strong as that of export. The impact of import on economic growth would depend on whether imported inputs substitute or complement domestic inputs production, which is likely to vary according to individual countries' functions within global production chains. The economic growth of concerned countries would also be diverse. However, little attention has been paid to the impact brought by imports compared to its significance. Design/methodology - The principal methodology used in this paper is structural decomposition analysis (SDA), widely chosen to elucidate the impact of various factors on domestic gross output using input-output tables. This paper extracts trade data of six Asian economies from the World Input-Output Database (WIOD) 2016 release that covers 43 countries for the period 2000-2014. The extracted data is then categorised into 37 sectors. First, this paper calculates the Feenstra-Hanson Offshoring Index (OSI) of each country. It then applies SDA to measure the changes in each economy's gross output, export, import input coefficients, and domestic input coefficients. Finally, after taking the first difference from pooled time-series data, it estimates the correlations between imported input coefficients and OSI using the ordinary least square (OLS) method. Findings - The main findings of this paper can be summarised as follows. Firstly, all six countries have increasingly engaged in global production chains, as evidenced by the growing size of OSI. Secondly, there are negative correlations in five countries except Japan, with sectoral differences. Thirdly, changes in import input coefficients are not negative in all six countries, indicating that offshoring does not necessarily substitute for domestic inputs production but does complement it and, therefore, fosters their economic growth. This is observed in China, Indonesia, Korea and Taiwan. Offshoring has led to an increase in the use of imported inputs, which has, in turn, stimulated domestic inputs production in these countries. Originality/value - While existing studies focus on the role of export in evaluating the impact of participating global production chains, this paper explicitly examines the unexplored impact of import on domestic gross output by considering both the substitution and the complementary effect, using the WIOD. The findings of this paper suggest that Asian economies have achieved fast and stable economic growth not only through successful export management but also through effective import management within global production chains. This paper recommends that the Korean government and enterprises carefully choose offshoring strategies to minimise disruption to domestic production chains or foster them.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.

• Health Policy and Management
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• v.4 no.2
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• pp.77-110
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• 1994

This study is an empiriacl analysis of effects of government intervention on the health care delivery system in Korea. The purposes of this study are to find out the effects of government intervention on the per capita national health expenditure(per capita NHE), crude mortality rate(CMR), and institutional efficiency. Here, the institutional efficiency is defined as a formula shown below: log$\frac{100-curde mortality rate }{per capita NHE}$$\times$100. The formula indicates that the instiutional efficiency increases if the CMR and/or per capita NHE goes down. In the meantime the government intervention is measured by six independent variables: I) the degree of social developments, ii) the numberr of physicians per 100, 000 population, iii) the proportion of specialists among the total physicians, iv) the proportion of public expenditure among the NHE, v) the proportion of public beds to the total number of beds, vi) the proportion of physicians working at the public sector to the total number of physicians. In the above six independent variables iv), v) and vi) are the ones that reflect the degree of government intervention. In actual calculation, the two independent variables v) and vi) are integrated into a new variable based on one to one correspondence. The materials used are the time-series data from 1970 through 1990 in Korea. A path analysis and the time-series regression analysis were adopted to estimate and examine the causal relationship between variables involved. And decomposition of the effect of causal relationship is made to find net effect, direct and indirect effect. The major findings are as follows; 1. The effect of public expenditure, number of physicians per 100, 000 population, the proportion of specialists among the total physicians and social development shows a positive relationship with per capita NHE. Only if the government intervention would be counted, the effects of the number of physicians and the proportion of specialists succeed in containing per capita NHE. 2. In additionn to the above four variables, one additional variable, per capita NHE, was also responsible for the reduction of CMR. The factor of social development found to be the most potent predictor of the CMR reduction. However, the CMR reduction due to government intervention was negligible. 3. Meanwhile, the above four variables were found to was have negative effects on the institutional efficiency. The reverse is true when the government intervention is counted. For example, the number of physicians and the proportion of specialists have played a positive role in raising institutional efficiency via goverment intervention. This comes from the factual effect that the increment of institutional efficiency via the reduction of per capita NHE is bigger than via the reduction of CMR.