• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1137-1149
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• 2014

Since the bifurcating autoregressive (BAR) model was developed by Cowan and Staudte (1986) to analyze cell lineage data, a lot of research has been directed to BAR and its generalizations. Based mainly on the author's works, this paper is concerned with a contemporary review on the BAR in terms of an overview and perspectives. Specifically, bifurcating structure is extended to multi-cast tree and to branching tree structure. The AR(1) time series model of Cowan and Staudte (1986) is generalized to tree structured random processes. Branching correlations between individuals sharing the same parent are introduced and discussed. Various methods for estimating parameters and related asymptotics are also reviewed. Consequently, the paper aims to give a contemporary overview on the BAR model, providing some perspectives to the future works in this area.

• Journal of Navigation and Port Research
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• v.45 no.2
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• pp.69-74
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• 2021

This study aims to investigate the lead-lag relationship between the agricultural produce import price in Korea and the corresponding shipping freight rate. Since the Korean economy has pursued an export-driven growth strategy, mainly based on the manufacturing sector, the country has to depend on the vast majority of its agricultural produce consumption after import from foreign countries. Moreover, compared with other high-value products, transportation cost occupies a substantial share of the agricultural commodity price, resulting in changes in the shipping freight rate being a pivotal determinant of agricultural produce import. In this respect, this study explores the possible association between agricultural produce import in Korea and shipping freight rate and the lead-lag relationship. Using a monthly dataset of agricultural produce import prices and freight rates for Handysize and Panamax dry-bulkers for the period between January 2010 and November 2020, this study determines that the shipping freight rate, in general, leads the agricultural commodity price.

• East Asian Economic Review
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• v.23 no.2
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• pp.203-223
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• 2019

This paper examines the interactions between financial conditions and business cycles in Mongolia, a small open economy, heavily depending on commodity exports. We construct two financial conditions indexes based on the reduced form IS model and the vector autoregression (VAR) model as surveillance tools to quantify the degree of the financial conditions. We find that real short-term interest rate and real effective exchange rate gap get a higher weight in the FCIs. Both business and financial cycles are often more pronounced in Mongolia, and financial condition is dependent of the financial and monetary policies in place. The analysis of the predictive power of the FCIs for business cycles shows that they have predictive information for the near-term economic activities. FCIs are also helpful in signaling inflation turning points.

• Proceedings of the KIPE Conference
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• 2020.08a
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• pp.215-217
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• 2020

본 논문은 배터리 팩 내부 셀 파라미터의 불균일도에 대한 분석을 실시하고 이를 기반으로 과방전을 사전에 진단할 수 있는 방법을 제안한다. 이를 위해서 배터리 팩 내부 셀간 편차가 발생하는 셀을 선정하여 두 셀간 특성 분석을 실시하였으며, 이를 기준으로 예측 모델을 구성하였다. 예측 성능을 통해 배터리 전압 예측 성능에 영향을 미치는 인자를 분석하였으며, 배터리 전기적 등가회로 모델을 기반으로 예측 모델을 제안한다. 예측 모델은 실제 과방전이 발생한 셀을 기준으로 실험데이터와 비교하여 예측 성능을 검증하였다.

• Information Systems Review
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• v.16 no.2
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• pp.77-95
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• 2014

From the success of TDX and CDMA to today's social media boom, Korea's ICT has achieved an amazing growth for the last couple of decades. However, in spite of ICT's role as an engine of growth in Korea, there have been concerns that ICT growth would negatively affect national employment due to the labor substitution effect. While some scholars insist that ICT would positively affect employment because it will enlarge the size of industry itself, many people blame ICT as a main culprit of rising unemployment rates. In this study, we try to empirically find the true effect of ICT growth on employment in Korea. We use the data of ICT productions, ICT investments, and various industries employments from 1995 to 2011. The methodologies we adopted for this study is Granger causality tests and impulse response functions based on vector autoregression (VAR) model. We find that ICT has negative impact on service industries, while it has positive impact on manufacturing industries. Meanwhile, ICT has no statistically significant impact on ICT industry itself. Since the impacts of ICT on employment are mixed, we can argue that ICT should not be blamed for the main cause of low employment. We suggest a direction of future policies to utilize ICT for vitalizing employments in Korea.

• Economic Analysis
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• v.26 no.2
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• pp.72-113
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• 2020

This study investigates the relationship between mineral exports to China, North Korea's most important source of foreign currency acquisition, and its imports of various items from China from the first quarter of 1995 through to the third quarter of 2019. The results from a cointegration analysis suggest that there exists a long-run equilibrium relationship between mineral exports and imports of food, fuel, and some intermediate goods, such as industrial supplies, parts, and accessories. The results from a vector autoregression using first-differenced variables indicate that the short-run relationship between mineral exports and imports is different between the period before and after the third quarter of 2010. Prior to structural changes, i.e., before the third quarter of 2010, import shocks affected mineral exports. However, after the third quarter of 2010, an increase in mineral exports led to an increase in the import of vehicles, intermediate goods, and luxury goods. This paper shows both the possibilities and the limits that mineral exports can contribute to North Korea's economic growth. The results, which show that mineral exports have a long-run relationship with intermediate goods, such as industrial supplies, parts and accessories, imply that mineral exports to China could have a positive effect on the North Korean economy. However, the fact that mineral exports do not have any significant effect on the import of machinery and equipment, which helps the accumulation of capital formation, shows that mineral exports have a limited effect on inducing long-term growth in the North Korean economy.

• Knowledge Management Research
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• v.19 no.2
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• pp.1-19
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• 2018

This study aims to identify the causal relationship among public technology transfer, technological performance, and research and development (R&D) productivity. Using the impulse-response function(IRF) of a panel vector autoregressive model (panel VAR), this study suggests the results of how long the factors such as technological performance (patent), public technology transfer, and R&D productivity takes and lasts if a one-unit shock of standard deviation occurs. As a result, first, the increase of public technology transfer activities has no power to increase the technology performance but improve the R&D productivity. If the public institute increases its technology transfer activities by one unit, the R&D productivity will increase within five years. Second, the impact of increasing technological performance on improvement of public technology transfer and R&D productivity is an insignificant. Third, the effect of R&D productivity on the public technology transfer creates a substantial reaction after a current time. Considering the structural relationships among public technology transfer, technological performance, and R&D productivity, if policy makers intend to construct the active R&D circumstance, technology suppliers should be motivated to run the active R&D mechanism because they achieve gains.

• Journal of Distribution Science
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• v.18 no.3
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• pp.25-36
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• 2020

Purpose: Based on previous researches on social factors of digital item purchase in digital contents distribution platforms such as SNS, we aim to develop the integrated model that accounts for the dynamic and interactive relationship between social structure indicators and digital item purchase. Research design, data and methodology: A PVAR model was used to capture endogenous and dynamic relationships between digital item purchase and network indicators. Results: We find that there exist considerable endogenous and dynamic relationships between digital item purchase and network structure variables. Not only lagged in-degree and out-degree but also in-closeness and out-closeness centrality have significant and positive impacts on digital item purchase. Lagged clustering has a significant and negative effect on digital item purchase. Lagged purchase has a significant and positive impact just on the present in-closeness and out-closeness centrality; but there is no significant effect of lagged purchase on the other two degree variables and clustering coefficient. We also find that both closeness centralities have much higher carryover effect on digital item purchase and that the elasticity of both closeness centralities on the purchase of digital items is even higher than that of other network structure variables. Conclusions: In-closeness and out-closeness are the most influential factors among social structure variables of this study on digital item purchase.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.239-252
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• 2004

It is known that the domestic and the U.S. stock prices tend to move together as those markets are closely interrelated. In this study, cointegration and causal relationships among the four stock price indexes of KOSPI, KOSDAQ, DOWJONES and NASDAQ are carefully investigated for the period of declining stock prices in the long run. When all indexes move in a similar fashion, cointegration does not exist and the causal linkages between the domestic and the U.S. stock prices appear relatively complex. On the other hand, when the domestic and the V.S. stock prices move in a different manner, cointegration exists and the causal relationships appear relatively simple. NASDAQ is apparently found to lead the domestic stock market in both periods, which is consistent with the actual market situation when the If industry is under recession.

• Computers and Concrete
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• v.20 no.5
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• pp.555-562
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• 2017

The accuracy and integrity of stress data acquired by bridge heath monitoring system is of significant importance for bridge safety assessment. However, the missing and abnormal data are inevitably existed in a realistic monitoring system. This paper presents a data reconstruction approach for bridge heath monitoring based on the wavelet multi-resolution analysis and support vector machine (SVM). The proposed method has been applied for data imputation based on the recorded data by the structural health monitoring (SHM) system instrumented on a prestressed concrete cable-stayed bridge. The effectiveness and accuracy of the proposed wavelet-based SVM prediction method is examined by comparing with the traditional autoregression moving average (ARMA) method and SVM prediction method without wavelet multi-resolution analysis in accordance with the prediction errors. The data reconstruction analysis based on 5-day and 1-day continuous stress history data with obvious preternatural signals is performed to examine the effect of sample size on the accuracy of data reconstruction. The results indicate that the proposed data reconstruction approach based on wavelet multi-resolution analysis and SVM is an effective tool for missing data imputation or preternatural signal replacement, which can serve as a solid foundation for the purpose of accurately evaluating the safety of bridge structures.