• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.477-481
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• 2007

The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

• Environmental and Resource Economics Review
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• v.19 no.1
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• pp.81-100
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• 2010

This paper measures the impacts of the Korea-China Free Trade Agreement (FTA) on the emissions of carbon dioxide ($CO_2$) in Korean export industries. The Korean industrial exports were forecasted by employing Bayesian Kalman Filter Vector Auto-Regression (BVAR) model. The emissions of $CO_2$ were then estimated by applying the $CO_2$ emission coeffcients on the conditionally forecasted values of export by industries. Under the conditional scenario of the 50% reduction in current tariff rate through FTA between Korea and China, the total $CO_2$ emissions in Korea were expected to increase by 1.96% compared to the BAU (Non FT A) trend at the end of 2010. Another conditional scenario with no tariff after 2012 was also adopted. In this case, the total $CO_2$ emlssions were estimated to increase by 2.06% compared to the BAU up until the end of 2014. These facts imply that the FTA between Korea and China would not result in the significant increase of $CO_2$ emissions in Korea.

• Journal of Distribution Science
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• v.14 no.4
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• pp.47-53
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• 2016

Purpose - The objective of this study is to investigate the dynamic relationships among Advertising Cost (AD), Newly Registered Users(NRU), and Buying Users(BU) of Social Network Game(SNG). SNG is getting pervasive mainly due to the rapid growth of mobile game and Social Network Service(SNS). It would be helpful for marketing researchers interested in SNG and related practitioners to understand the changes in AD, NRU, and BU with time as well as the effects on one another in mutual and dynamic way. Research Design, Data, and Methodology - Necessary data were collected from Social Network Game(SNG) company. AD, NRU, and BU are endogenous variables, but new event such as launching (event) and holidays(holiday) are exogenous dummy variables. Vector Auto regression (VAR) model is generally used to examine and capture the dynamic relationships among endogenous variables. VAR model can easily capture dynamic and endogenous relationships among time-series variables. Vector Auto regression with Exogenous variables(VARX) is a model in which exogenous variables are added to VAR. To investigate this study, VARX is applied. Result - By estimating the VARX model, the author finds that the past periods' NRU affect negatively and significantly the present AD, and past periods' BU have a positive and significant impact on the increase of AD. In addition, the author shows that the past periods' AD and BU have a positive and significant effect on the increase of NRU, and the past periods' AD affect positively and significantly BU. While the impact of AD on NRU happens after 3 or 4 days (carryover effect), that of AD on BU comes about within just 1 or 2 days (immediate effect). The effect of BU on NRU can be considered as word of mouth (WOM effect). Therefore, SNG companies can obtain not only the growth of revenue but also the increase of NRU by increasing BU. Through those results, the author can also find that there are significant interactions between endogenous variables. Conclusion - This study intends to investigate endogenous and dynamic relationships between AD, NRU, and BU. They also give managerial implications to practitioners for SNS and SNG firms. Through this study, it is found that there exist significant interactions and dynamic relationships between those three endogenous variables. The results of this study can have meaningful implications for practitioners and researchers of SNG. This research is unique in that it deals with "actual" field data and intend to find "actual" relationships among variables unlike other related existing studies which intend to investigate psychological factors affecting the intention of game usage and the intention of purchasing game items. This study is also meaningful by showing that the increase of BU can be a good strategy for "killing birds with one stone" (i.e., revenue growth and NRU increase). Although there are some limitations related with future research topics, this research contributes to the current research on SNG marketing in the above mentioned ways.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.834-841
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• 2022

Recently, applying artificial intelligence technologies in various fields of production has drawn an upsurge of research interest due to the increase for smart factory and artificial intelligence technologies. A great deal of effort is being made to introduce artificial intelligence algorithms into the defect detection task. Particularly, detection of defects on the surface of metal has a higher level of research interest compared to other materials (wood, plastics, fibers, etc.). In this paper, we compare and analyze the speed and performance of defect classification by combining machine learning techniques (Support Vector Machine, Softmax Regression, Decision Tree) with dimensionality reduction algorithms (Principal Component Analysis, AutoEncoders) and two convolutional neural networks (proposed method, ResNet). To validate and compare the performance and speed of the algorithms, we have adopted two datasets ((i) public dataset, (ii) actual dataset), and on the basis of the results, the most efficient algorithm is determined.

• Economic Analysis
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• v.25 no.2
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• pp.132-176
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• 2019

We use a time-varying parameter vector auto regression (TVP-VAR) model to understand the impact of U.S. monetary policy normalization on Korean financial markets and capital accounts. The U.S. monetary policy is represented by the federal funds rate, term premium and credit spread. During the U.S. monetary contraction period of 2004 to 2006, changes in the federal funds rate presented negative pressure on Korean financial markets. The changes in federal funds rate also led to a simultaneous contraction in inward and outward capital flows. However, the effects of a federal funds rate shock has been reduced since 2015. On the other hand, the effects of U.S. term premiums is getting stronger after the period of quantitative easing (QE). The influence of the U.S. credit spread also significantly increased after the global financial crisis. Simulation results show that a rise in the U.S. credit spread, which can be triggered by a contractionary monetary policy, can pose a larger adverse impact on the Korean economy than a rise in the federal funds rate itself. As for capital flows, a U.S. monetary policy contraction causes an outflow of foreign investment, but the repatriation of overseas investment by Korean residents can offset this outflow.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.103-112
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• 2009

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. In this paper, principal component-based Auto-Associative support vector regression (PCSVR) was proposed for the sensor signal validation of the NPP. It utilizes the attractive merits of principal component analysis (PCA) for extracting predominant feature vectors and AASVR because it easily represents complicated processes that are difficult to model with analytical and mechanistic models. With the use of real plant startup data from the Kori Nuclear Power Plant Unit 3, SVR hyperparameters were optimized by the response surface methodology (RSM). Moreover the statistical techniques are integrated with PCSVR for the failure detection. The residuals between the estimated signals and the measured signals are tested by the Shewhart Control Chart, Exponentially Weighted Moving Average (EWMA), Cumulative Sum (CUSUM) and generalized likelihood ratio test (GLRT) to detect whether the sensors are failed or not. This study shows the GLRT can be a candidate for the detection of sensor drift.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.191-200
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• 2020

This research paper examines the causal relationship between India's economic growth and sectoral contribution to Gross Domestic Product (GDP) and vice versa, in the short-run and long-run, over a 10 years time period. Johansen's method of cointegration is used to study the cointegration between the sectoral contributions to Indian GDP vis-à-vis India's economic growth. Further, the route of interconnection between economic growth and sectoral contribution is tested by using Vector Auto Regression (VAR) model. Special attention was given for investigating impulse responses of economic growth depending on the innovations in sectoral contribution using time-series data from 1960 to 2015. This paper highlighted a dynamic co-relationship among industrial sector contribution and agricultural sector contribution and economic development. In the long run, one percent change in industrial sector contribution causes an increase of 3.42 percent in the economic growth and an increase of 1.12 percent in the primary sector contribution, while in the short run industrial and service sector contributions showed significant impact on economic development and agriculture sector. The changing composition of sector contribution is going to be an important activity for the policymakers to monitor and control where the technology and integration of sectors play a significant role in economic development.

• The Journal of Industrial Distribution & Business
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• v.8 no.5
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• pp.7-13
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• 2017

Purpose - The purpose of this paper is to analyze the relationship between the real exchange rate and the output, which is based on the macroeconomic equilibrium theory in China. Its aim will be to verify whether the change in the real exchange rate has a significant effect on the output or not. Research design, data, and methodology - This study endeavors tries to investigate the correlation among economic variables under the macroeconomic market (the commodity market and the money market) equilibrium. So, time-series data from 1990 to 2016 is applied to establish a vector auto-regression (VAR) model so as to perform an empirical analysis. Results - The empirical results reveal that an increase in the real exchange rate will result in an increase in the output in the short run. However, the empirical results also indicate that this kind of mechanism cannot work in the long run. Conclusions - The effect of a decrease of real exchange rate on output is significant in the short run. Also, this paper suggests that the total supply and the total demand can promote economic growth. The fiscal and money policy play a significant role in economic growth in China as well.

• The Journal of Industrial Distribution & Business
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• v.8 no.1
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• pp.5-13
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• 2017

Purpose - In this article, a dynamic model like a VAR is an appropriate choice for estimating the possible interrelationship between ownership structure and firm performance as a dynamic process. Research design, data, and methodology - Data of this work are collected from Chinese stock exchange including 350 Chinese-listed firms during the period of 1999-2012. We hypothesize that this interrelationship dynamically exists between ownership structure and firm performance. To examine the correlation, a panel Vector Auto-regression (PVAR) approach generated by GMM method is utilized to test the possible dynamic relation embedded in corporate governance. Another two dynamic analysis solutions such as orthogonalized impulse-response function and variance decomposition are also used simultaneously. Results - Findings of this study indicate the evidence that dynamically endogenous relationship exists between ownership structure and firm performance. Further, there is a dynamical correlation between investment and performance. Impulse response and variance decomposition illustrate that impact of a shock to variables themselves is the main source for their variability. Conclusions - The conclusion in this study is that there is a bidirectional and inter-temporal effect between proportion of ownership and corporate performance for a long run in accordance with impulse response function. Overall, our results suggest that corporate governance in China is more market oriented.

• The Journal of Fisheries Business Administration
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• v.46 no.3
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• pp.31-49
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• 2015

This study examines whether or not the South Korean major fishery product import markets; Frozen Pollock, Frozen Long Arm Octopus, and Frozen Hairtail are integrated. We are utilizing the Multivariate and Bivariate Johansen Co-integration test to see if the law of one price(LOP) holds in each market or not. The empirical results show that even though import prices from different countries affect each other in each South Korean major fishery product import market, there is no evidence of LOP in any fishery product import market, which means that none of the markets are integrated. Based on these results, we could expect that the three major fishery product import markets show monopolistic competition among import countries. we would also see whether or not any country plays the role of a price leader in any of the markets. Based on weak exogeneity test results, we might expect that the United States and Malaysia are price leaders in the South Korean Frozen Pollock Import Market and Frozen Long Arm Octopus Import Market, respectively; however, we need to study more on this in the future.