• Journal of Biosystems Engineering
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• v.33 no.4
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• pp.260-268
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• 2008

Optical diffuse reflectance sensing has potential for rapid and reliable on-site estimation of soil properties. For good results, proper calibration to measured soil properties is required. One issue is whether it is necessary to develop calibrations using samples from the specific area or areas (e.g., field, soil series) in which the sensor will be applied, or whether a general "factory" calibration is sufficient. A further question is if specific calibration is required, how many sample points are needed. In this study, these issues were addressed using data from 42 paddy fields representing 14 distinct soil series accounting for 74% of the total Korean paddy field area. Partial least squares (PLS) regression was used to develop calibrations between soil properties and reflectance spectra. Model evaluation was based on coefficient of determination ($R^2$) root mean square error of prediction (RMSEP), and RPD, the ratio of standard deviation to RMSEP. When sample data from a soil series were included in the calibration stage (full information calibration), RPD values of prediction models were increased by 0.03 to 3.32, compared with results from calibration models not including data from the test soil series (calibration without site-specific information). Higher $R^2$ values were also obtained in most cases. Including some samples from the test soil series (hybrid calibration) generally increased RPD rapidly up to a certain number of sample points. A large portion of the potential improvement could be obtained by adding about 8 to 22 points, depending on the soil properties to be estimated, where the numbers were 10 to 18 for pH, 18-22 for EC, and 8 to 22 for total C. These results provide guidance on sampling and calibration requirements for NIR soil property estimation.

• Journal of Energy Engineering
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• v.21 no.3
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• pp.301-308
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• 2012

This paper attempts to estimate the demand function for the transport LPG and to analyze long-run and short-run price and income elasticities. In addition, the paper measures consumer surplus and economic value ensuing from the transport LPG consumption by utilizing the estimated long-run price elasticity. The price and the income data are the monthly real transport LPG price and the monthly composite index adjusted by real transport LPG price from 2003 to 2012. Unit root test, co-integration test and error correction model are to take the procedure of estimation of demand curve. The demand for transport LPG is considered to be inelastic and the long-run demand is more elasticity than that of short-run. Price elasticity of demand estimate here is -0.422, and the estimated consumer surplus and economic value in 2010/03 are 966 and 1,781 billion won, respectively.

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.59-78
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• 2010

This paper tries to apply the asymmetrical price transmission(APT) behavior observed in the agricultural industry to supply chains of the domestic fishery industry by a statistical manner. The fore mentioned asymmetrical price transmission refers to when price movements in the later stage of the supply chain do not move in a normal or symmetrical manner corresponding to price movements in the earlier stage of the supply chain. Therefore, when the earlier stage price increase and the later stage price increases to a larger degree, it is called positive(+) asymmetry and the opposite behavior is called negative(-) asymmetry. The study examines the data from domestic producers of three fresh fish types, hairtail, mackerel, and cuttlefish, and tries to examine the price asymmetry between the producer or farm, wholesaler, and retail prices via an APT test utilizing unit root, cointegration, and error correction model. The study found, hairtail wholesale and retail pricing bas a negative asymmetric relationship while mackerel has a negative asymmetric pricing relationship at the producer and retail levels of the supply chain. In the case of cuttlefish, all levels of the supply chain showed negative asymmetrical behavior in the supply chain price transmission, meaning the earlier stage price changes are more rapidly and greatly inputted in the later stage of the supply chain pricing. We believe that the reason why the analysis results show negative price asymmetry is due to the uniqueness of fishery products having an important variable such as freshness. If price increases are greater and quicker than price decreases, then consumer demand, which is sensitive to price increases will decrease and subsequently result in the increase of inventory levels, reducing profits for retailers. Also, frozen hairtail, mackerel, and cuttlefish will act as substitute goods to fresh fishery products. Therefore, fresh fishery products have a high demand of price elasticity. When prices increase, demand quickly decreases. Therefore the profit of wholesalers and retailers to decrease, I think this is the main reason of APT in the supply chain of Korea' s fisheries industry.

• International Commerce and Information Review
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• v.14 no.4
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• pp.27-47
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• 2012

The study aims to analyze how the variables for Korea, such as the exports, imports, FDI(Inward) and FDI(Outward), influence the economic growth and how they affect each other. For the purpose of empirical analysis, this paper used the quarterly time series data from 1980 to 2010, dividing the period before and after 1997(IMF). The variables used in this study were log-transformation from the original variables. This study empirically tests the relationship among variables by using VECM with considering the time-series properties of each variable. The results found from the study are as followings. Causality analysis using VECM proved that no causality between GDP and exports existed, whereas causality between GDP and FDI(Inward) existed, in which GDP affected FDI(Inward) since IMF. However, it was found that other periods and FDI(Inward) did not affect GDF and had no causality among them.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2B
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• pp.154-163
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• 2006

The importance of R & D investment has dramatically been increased as industrial paradigm rapidly changes to knowledge-based economy. In order to preserve recent economic growth and reinforce competitive advantage, government policy and regulatory framework needs to be reshaped in ways that minimize the distorted use of limited resources and maximize the efficiency of R & D investment. In this regards, this paper aims to investigate the influence of R & D investment in national economic growth and to compare the effectiveness of IT R & D investment with other industries, in respect to the time lag.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.47-53
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• 2019

The purpose of the study was to utilize VECM(Vector Error Correction Model) and detect causal relationships among shipping freight rates. Shipping freight rates used in this study were BDI(Baltic Dry Index), HRCI(Howe Robinson Containership Index), WS(World Scale rate) and SCFI(Shanghai Containerized Freight Index). Using weekly data published since August 2nd, 2013 to September 6th, 2019, it was discovered that BDI and WS were heavily influenced by past week's BDI and WS respectively. VECM also found that one percent increase in WS resulted in 0.022% increase in following week's HRCI data. One percent increase in HRCI affects SCFI by 0.77% on the following week. This study believes that finding may help each shipping market of shipping freight rates estimates, thereby encouraging decision markers to exercise discretion and establish best interest decision.

• Asia-Pacific Journal of Business
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• v.12 no.1
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• pp.209-223
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• 2021

Purpose - The purpose of this study was to investigate the relationship between Korea agricultural productions and Greenhouse Gas (GHG) emissions based on Environmental Kuznets Curve (EKC) hypothesis. Design/methodology/approach - This study utilized time series data of economic growth, greenhouse gas, agricultural productions, trade dependency, and energy usages. In order to econometric procedure of EKC hypothesis, this study utilized unit root test and cointegration test to check staionarity of each variable and also adopted Vector Error Correction Model (VECM) and Ordinary Least Square (OLS) to analyze the short and long run relationships. Findings - In the short run, greenhouse gas emissions resulting from economic growth show an inverse U-shape relationship, and an increase in agricultural production and energy consumption led to increase in greenhouse gas emission. In the long run, total GHG emissions and CO2 emissions show an N-shaped relationship with economic growth, and an increase in agricultural production has resulted in a decrease in total GHG and CO2 emissions. However, methane (CH4) and nitrous oxide (N2O) emissions showed an inverse U-shape relationship with economic growth, which indicated the environment and production process of agricultural production. Research implications or Originality - Korea agricultural production has different effects on the GHG emission sources, and in particular, methane (CH4) and nitrous oxide (N2O) emissions show to increase as the agricultural production expansions, so policy or technological development in related sector is required. Especially, in the context of the 2030 GHG reduction road-map, if GHG-related reduction technologies or policies are spread, national GHG emission reduction targets can be achieved and this is possible to predict the decline in production in the sector and damage to the related industries.

• International Area Studies Review
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• v.16 no.3
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• pp.77-97
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• 2012

Estimated coefficients has serious problems including inconsistency, biasness, etc. because many researches about the effect of fiscal decentralization on a country's economic growth use the traditional OLS method. Researches use the data intactly so that so called "spurious regression" phenomenon exists. This causes fundamental fallacy. This research tries unit root test, cointegration test, and then estimates the United States' economic time series by using VECM. The analysis of the effect of the state level-fiscal decentralization on economic growth shows two long term-equilibriums. During short term-dynamic adjustment, fiscal decentralization and economic growth move the same or different directions. In case of prediction GDP increases steeply and then from 2015 gently; and fiscal decentralization index shows a general reduction trend and then decreases slowly. At local level it shows two long term-equilibriums. During short term-dynamic adjustment, fiscal decentralization and economic growth also move the same or different directions. Impulse response analysis shows the very negative effect of fiscal decentralization on economic growth.

• International Area Studies Review
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• v.16 no.1
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• pp.3-27
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• 2012

This paper adopts recently developed panel unit root test that is cross-sectionally robust. Cointegration test is also used to find whether regional house prices are in line with gross regional domestic production (GRDP) in the long run in Korea during 1989-2009. Based on the panel VECM and the panel ARDL models, we examine causal relationships among the variables and estimate the long-run elasticity. We find evidence of cointegration and bidirectional causal relationships between regional house prices and GRDP. The results of long-run estimates, using both fixed effect and ARDL models, show that house prices positively and significantly influence on the GRDP and vice versa. Together with these results, the findings of ARDL-ECM imply that there exists a long-run equilibrium relationship between house prices and regional economic variables even if there is a possibility of short-run deviation from its long-run path.

• Geomechanics and Engineering
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• v.34 no.6
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• pp.697-726
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• 2023

Brittleness as an important property of rock plays a crucial role both in the failure process of intact rock and rock mass response to excavation in engineering geological and geotechnical projects. Generally, rock brittleness indices are calculated from the mechanical properties of rocks such as uniaxial compressive strength, tensile strength and modulus of elasticity. These properties are generally determined from complicated, expensive and time-consuming tests in laboratory. For this reason, in the present research, an attempt has been made to predict the rock brittleness indices from simple, inexpensive, and quick laboratory test results namely dry unit weight, porosity, slake-durability index, P-wave velocity, Schmidt rebound hardness, and point load strength index using multiple linear regression, exponential regression, support vector machine (SVM) with various kernels, generating fuzzy inference system, and regression tree ensemble (RTE) with boosting framework. So, this could be considered as an innovation for the present research. For this purpose, the number of 39 rock samples including five igneous, twenty-six sedimentary, and eight metamorphic were collected from different regions of Iran. Mineralogical, physical and mechanical properties as well as five well known rock brittleness indices (i.e., B₁, B₂, B₃, B₄, and B₅) were measured for the selected rock samples before application of the above-mentioned machine learning techniques. The performance of the developed models was evaluated based on several statistical metrics such as mean square error, relative absolute error, root relative absolute error, determination coefficients, variance account for, mean absolute percentage error and standard deviation of the error. The comparison of the obtained results revealed that among the studied methods, SVM is the most suitable one for predicting B₁, B₂ and B₅, while RTE predicts B₃ and B₄ better than other methods.