• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.151-154
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• 2008

Dramatic price increases of fossil fuels and the economic development of emerging nations accelerates the transformation of forest lands into monocultures, e.g. for biofuel production. On this account, cost efficient methods to enable the monitoring of land resources has become a vital ambition. The application of remote sensing techniques has become an integral part of forest attribute estimation and mapping. The aim of this study was to evaluate the potentials of the kNN method by combining terrestrial with remotely sensed data for the development of a pixel-based monitoring system for the small scaled mosaic of different land use types of the off-reserve forests of the Goaso forest district in Ghana, West Africa. For this reason, occurrence and distribution of land use types like cocoa and non-timber forest resources, such as bamboo and raphia palms, were estimated, applying the kNN method to ASTER satellite data. Averaged overall accuracies, ranging from 79% for plantain, to 83% for oil palms, were found for single-attribute classifications, whereas a multi-attribute approach showed overall accuracies of up to 70%. Values of k between 3 and 6 seem appropriate for mapping bamboo. Optimisation of spectral bands improves results considerably.

• Journal of Korean Society of Water and Wastewater
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• v.30 no.3
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• pp.299-312
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• 2016

The main objective of this paper is to develop computer simulation program for performance evaluation and cost estimation of a reverse osmosis (RO) and pressure-retarded osmosis (PRO) hybrid process to propose guidelines for its economic competitiveness use in the field. A solution-diffusion model modified with film theory and a simple cost model was applied to the simulation program. Using the simulation program, the effects of various factors, including the Operating conditions, membrane properties, and cost parameters on the RO and RO-PRO hybrid process performance and cost were examined. The simulation results showed that the RO-PRO hybrid process can be economically competitive with the RO process when electricity cost is more than 0.2 $/kWh, the PRO membrane cost is same as RO membrane cost, the power density is more than $8W/m^2$ and PRO recovery is same as 1/(1-RO recovery).

• Proceedings of the Korean Geotechical Society Conference
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• 1993.06b
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• pp.19-44
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• 1993

The purpose of this paper is to study the design and the construction for the most economic and safe slope stability analysis. The approach to the purpose Iies in analyzing the characteristic on direction and distance by the sample value for the geotechnical parameters using the semi-variogram concept. Based on the result, we derive the Kriging system equation from the stochastical concept and solve the equation to find the weighting factor which is applied both the point estimation and the block estimation in the particular position. Comparing and analyzing the various methods. we find the best reliability, which is more accurate than any other.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.269-276
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• 2020

As we become an aging society, the number of elderly patients continues to increase. Pressure sores that can easily occur in patients with trauma cause serious socio-economic problems. In general, prevention of bedsores through predicting the patient's posture is being developed. Developed method usually use artificial intelligence techniques to estimate the patient's posture by measured pressure images in the mattress. In this method, it has a problem the reduction of estimation accuracy when posture of patient is changed. Therefore, it is necessary to use the filter of pressure images in the position transition of patient. In this paper, we propose an algorithm to predict the patient's posture, and an algorithm to reduce the ambiguity that can occur in the patient's posture transition section. By obtaining stable data through this algorithm, learning/prediction stability of the neural network can be expected, and prediction performance is improved accordingly. Through experiments, the effectiveness of the algorithm was verified.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.23-31
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• 2020

This paper investigates the impact of monetary policy independence shock on bond yield by allowing for heterogeneous coefficients in the model based on panel data for 19 developing countries using quarterly data from 1991 to 2016. First, we estimate the model using conventional panel VAR estimation with the assumption of homogeneous coefficients across countries. Second, by performing Chow and Roy-Zellner tests to check the homogeneity assumption, we find that the assumption does not hold in the model. Third, we apply a mean-group estimation for panel VAR as a solution for heterogeneity panel model. The results reveal that central bank independence is effective in reducing bond yield with the maximum at period 6 after the shock. Shock one standard deviation bond yield has a negative effect on consumption and investment. We determine that central bank independence has a contradictory effect on real activity; a negative effect on consumption but a positive influence on investment for the first two years after the shock. Additionally, we split our sample into three groups to make the subgroups pool. Our empirical result shows that monetary policy independence shock reduces bond yield. Meanwhile, the response of economic activity to bond yield varies for all three groups.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.627-637
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• 2005

Small area estimation has been studied using various methods such as direct, indirect, synthetic and based on regression or time series model . In this paper we investigate a motel-based small area estimation which takes into account the spare time autoregressive model. The Economic Active Population Surveys in 2001 are used for analysis and the results from space-time autoregressive(STAR) and simultaneous autoregressive(SAR) model are compared with using MSE, MAE and MB.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.11a
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• pp.191-192
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• 2017

In response to the economic depression, the demand for fixed rent income has increased according to the easing construction regulations. it caused indiscriminated investment to stakeholders. This leads to oversupply in the multi-family Housing market and increases unsold housing and vacancy rates except specific area such as Gangnam-gu.In order to solve this issue, although studies on the optimization price of apartment houses has been conducted, the study is insufficient regarding on residential officetel. Therefore, the objective is to suggest a basic study on optimal price estimation model development by using probabilistic forecasting method in planning phase. To achieve the objective, first, variables are defined such as expenses, financial costs, income, etc. Second, causal loop diagram is suggested. Third, basic optimization prices estimation model is developed. In the future, this study can be used as one of decision making tools in planning phase of officetel development projects.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.1
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• pp.22-30
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• 1999

This paper presents an efficient algorithm to estimate the maximum load level for heavily loaded power systems with the load-generation vector obtained by ELD (Economic Load Dispach) and/or short term load forecasting while utilizing the elliptic pattern of the P-e curve. It is well known the power flow equation in the rectangular corrdinate is jully quadratic. However, the coupling between e and f makes it difficult to take advantage of this quadratic characteristic. In this paper, the elliptic characteristics of P-e curve are illustrated and a simple technique is proposed to reflect the e-f coupling effects on the estimation of maximum loadability with theoretical analysis. An efficient estimation algorithm has been developed with the use of the elliptic properties of the P-e curve. The proposed algorithm is tested on IEEE 14 bus system, New England 39 bus system and IEEE 118 bus system, which shows that the maximum load level can be efficiently estimated with remarkable improvement in accuracy.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.61-65
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• 2008

Urban flooding with surcharges in sewer system was investigated because of unexpected torrential storm events these days, causing significant amounts of human and economic damages. Although there are limitations in forecasting and preventing natural disasters, integrated urban flooding management system using the SWMM engine and Web technology will be an effective tool in securing safety in operating Bi-modal transportation system. In addition, the integrated urban flooding management system can be linked with general and transportation-related disaster management system in the future. In this study, With simulated values by the SWMM, which is a core engine of the Bi-modal disaster management system, flash flooding area estimation module was developed. Thus, the SWMM system codes were modified and new module was developed and integrated with the existing SWMM interface using the Delphi programming language. The flash flooding area estimation module is fully integrated with the SWMM interface, thus the area is estimated on-the-fly inside the system.

• Journal of the Korean Geotechnical Society
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• v.37 no.12
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• pp.7-23
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• 2021

Underground utility tunnels, which contribute to supply of electricity, communication, water and heat, are critical lifelines of an urban area. In case service is discontinued or functional disruption happens, there will be a huge socio-economic impact. For the improved seismic design and evaluation of underground structures, this study proposes a ground displacement measure when the site is subjected to a scenario earthquake based on hazard-consistent source spectra and site amplification/attenuation. This measure provides a rational estimation of ground displacement and can be an alternative to existing response displacement methods.