• Journal of the Korean housing association
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• v.7 no.2
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• pp.1-7
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• 1996

This study was designed to examine the effects of housing values on housing satisfaction model. The empirical model of this study was based on the Goulart(1982). Data were collected through questionnaire survey, and the sample consisted of 285 households in Kimhae. Housing values were grouped into four clusters : the health and convenience value, the personal and social value, the location value, and the economic value. The major findings were that 1) the concordance between values and the actual housing conditions contributes significantly to the prediction of housing astisfaction, and 2) the control variables including sociodemographic and economic characteristics and housing values themselves did not directly influence on housing satisfaction.

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.62-67
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• 2021

Selective catalytic reduction(SCR) is an exhaust gas reduction device to remove nitro oxides (NOx). SCR operation of ship can be controlled through valves for minimizing economic loss from SCR. Valve in SCR-high pressure (HP) system is directly connected to engine exhaust and operates in high temperature and high pressure. Long-term thermal deformation induced by engine heat weakens the sealing of the valve, which can lead to unexpected failures during ship sailing. In order to prevent the unexpected failures due to long-term valve thermal deformation, a failure prediction system using autoregressive integrated moving average (ARIMA) was proposed. Based on the heating experiment, virtual data mimicking temperature range around the SCR-HP valve were produced. By detecting abnormal temperature rise and fall based on the short-term ARIMA prediction, an algorithm determines whether present temperature data is required for failure prediction. The signal processed by the data collection algorithm was interpolated for the failure prediction. By comparing mean average error (MAE) and root mean square error (RMSE), ARIMA model and suitable prediction instant were determined.

• Economic and Environmental Geology
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• v.51 no.4
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• pp.393-400
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• 2018

Despite some skeptical views on the possibility of earthquake prediction, observation and evaluation of precursory changes have been continued throughout the world. In Korea, the public concern on the earthquake prediction has been increased after 2016 $M_L5.8$ and 2017 $M_L5.4$ earthquakes occurred in Gyeongju and Pohang, the southeastern part in Korea, respectively. In this study, the abnormal increase of groundwater level was observed before the 2016 $M_L5.8$ Gyeongju earthquake in a borehole located in 52 km away from the epicenter. The well was installed in the Yangsan fault zone, and equipped for the earthquake surveillance. The abnormal change in the well would seem to be a precursor, considering the hydrogeological condition and the observations from previous studies. It is necessary to set up a specialized council to support and evaluate the earthquake prediction and related researches for the preparation of future earthquake hazards.

• Journal of Korea Port Economic Association
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• v.17 no.1
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• pp.53-72
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• 2001

This study focuses on analyzing the economic effects and probes the necessity of establishing a customs free zone at the Port of Busan. It first considers the economic effects of establishing a customs free zone at the Port of Busan, then suggests policy prescriptions for introducing and operating the free zone system and improving the logistics functions of the Port. The timeline of this study is focused on 2007, when all of Busan Port will operate as a customs free zone and the first stage of the New Busan Port and distribution parks will be built and opened for operation. The regression analysis, which was conducted using the inter-industry relations table(input-output table data), provided a quantitative prediction on the effects of making Busan Port into a customs free zone. Regarding the impact of a free zone system on the domestic and regional economy, this research found that the impact of a customs free zone on domestic industries and the regional economy once the customs free zone is established throughout all of Busan Port would be highly positive. The positive economic effects on the domestic and Busan regional economy might be further strengthened if the value-added logistics function of Busan Port could be supplemented by effective linking to the hinterlands.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1581-1587
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• 2014

Two-lalyered quiet asphalt pavements are well known for their noise reduction capabilities compared to the conventional ones. This study was conducted to analyze the economic effects on two-layered quiet asphalt pavement rather than on one-layered. Noise prediction was performed on the data surveyed from the two-layered quiet asphalt pavement. In addition, the economic analysis was executed considering cost benefits using the noise prediction result. The permeability test was also investigated to evaluate the clogging recovery of two-layered quiet asphalt pavement. Analysis results revealed that the construction cost of two-layered quiet asphalt pavements was cheaper than that of the conventional soundproof walls. The two-layered quiet asphalt pavement with simulated clogging conditions was satisfied the permeability requirements of the permeable asphalt pavements. The permeability test results showed that the permeable time was recorded as 6.77 seconds for one cycle of cleaning job with 400 mL of water.

• Research in Plant Disease
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• v.19 no.3
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• pp.196-200
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• 2013

This study was carried out to investigate yield loss due to soybean leaf spot disease caused by Cercospora sojina Hara and to determine the economic threshold level. The investigations revealed highly significant correlations between disease severity (diseased leaf area) and yield components (pod number per plant, total grain number per plant, total grain weight per plant, percent of ripened grain, weight of hundred seed, and yield). The correlation coefficients between leaf spot severity and each component were -0.90, -0.90, -0.92, -0.99, -0.90 and -0.94, respectively. The yield was inversely proportional to the diseased leaf area increased. The regression equation, yield prediction model, between disease severity (x) and yield (y) was obtained as y = -3.7213x + 354.99 ($R^2$ = 0.9047). Based on the yield prediction model, economic injury level and economic threshold level could be set as 3.3% and 2.6% of diseased leaf area of soybean.

• Economic Analysis
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• v.26 no.3
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• pp.1-47
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• 2020

This paper surveys research since the 1990s on the ability of the yield spread and its components (i.e., expectation spread and term premium components) for future economic activity, and also conducts an empirical analysis of their forecasting ability using the yield data of Korean government bonds. This paper's survey, particularly for the US, shows that the yield spread has significant predictive power for some macroeconomic variables, but since the mid-1980s, its predictive power seems to have declined, possibly due to stronger inflation targeting. Next, this paper's empirical analysis using Korean data indicates that the yield spread, and the term premium component in particular, has significant predictive power for industrial production (IP) growth, consumer price index growth, and the IP gap. An out-of-sample analysis shows that the prediction equations are unstable over time, and that in predicting IP growth, the yield spread decomposition makes a significant contribution to the prediction of IP growth.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.8
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• pp.1503-1512
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• 1992

The strength evaluation and life prediction on the corrosion part of structure is one of the most important subjects, as a viewpoint of reducing economic loss by regular inspection, maintenance, repair and replace. For this purpose, it has been difficult to obtain the available data on growth of pit depth or growth rate of each pit which depends on time. In this paper, the life prediction and strength evaluation method was suggested for the structure with irregular stress concentration part by surface corrosion. The statistical distribution pattern of corrosion depth and the degree of fatigue strength decline were confirmed according to corrosion period by artificial corrosion of SS41 steel. The life prediction and the fatigue strength evaluation of materials with consideration of the corrosion period on the extreme value statistic analysis by the data of maximum depth of corrosion and on random variable was studied.

• Environmental Engineering Research
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• v.22 no.2
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• pp.175-185
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• 2017

As the energy and environmental problems are increasingly severe, researches about carbon dioxide emissions has aroused widespread concern. The accurate prediction of carbon dioxide emissions is essential for carbon emissions controlling. In this paper, we analyze the relationship between carbon dioxide emissions and influencing factors in a comprehensive way through correlation analysis and regression analysis, achieving the effective screening of key factors from 16 preliminary selected factors including GDP, total population, total energy consumption, power generation, steel production coal consumption, private owned automobile quantity, etc. Then fruit fly algorithm is used to optimize the parameters of least squares support vector machine. And the optimized model is used for prediction, overcoming the blindness of parameter selection in least squares support vector machine and maximizing the training speed and global searching ability accordingly. The results show that the prediction accuracy of carbon dioxide emissions is improved effectively. Besides, we conclude economic and environmental policy implications on the basis of analysis and calculation.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.778-783
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• 2006

Price prediction is essential to decisions of investment and shipment in oak mushroom cultivation. But predicting the prices of oak mushroom is very difficult because there are so many uncertain factors affecting the demand and the supply in the market. The Box-Jenkins methodology is one of strong tools in price prediction especially for the short-term using historical observations of time series. In this paper, the Box-Jenkins methodology is applied to find a model to forecast future oak mushroom prices. And out-of-sample test was conducted to check out the prediction accuracy. The result shows the high accuracy except for market disturbance period affected by unexpected weather change and reveals the usefulness of the model.