• 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.

• Geomechanics and Engineering
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• v.17 no.4
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• pp.367-374
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• 2019

This study concluded the results of a research on the features of cement based permeation grout, based on some important grout parameters, such as the rheological properties (yield stress and viscosity), coefficient of permeability to grout ($k_G$) and the inject ability of cement grout (N and $N_c$ assessment), which govern the performance of cement based permeation grouting in porous media. Due to the limited knowledge of these important grout parameters and other influencing factors (filtration pressure, rate and time of injection and the grout volume) used in the field work, the application of cement based permeation grouting is still largely a trial and error process in the current practice, especially in the local construction industry. It is seen possible to use simple formulas in order to select the injection parameters and to evaluate their inter-relationship, as well as to optimize injection spacing and times with respect to injection source dimensions and in-situ permeability. The validity of spherical and cylindrical flow model was not verified by any past research works covered in the literature review. Therefore, a theoretical investigation including grout flow models and significant grout parameters for the design of permeation grouting was conducted in this study. This two grout flow models were applied for three grout mixes prepared for w/c=0.75, w/c=1.00 and w/c=1.25 in this study. The relations between injection times, radius, pump pressure and flow rate for both flow models were investigated and the results were presented. Furthermore, in order to investigate these two flow model, some rheological properties of the grout mixes, particle size distribution of the cement used in this study and some geotechnical properties of the sand used in this work were defined and presented.

• Smart Structures and Systems
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• v.24 no.3
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• pp.303-317
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• 2019

Magneto-rheological fluid (MRF) rotatory dampers are normally used for controlling the constant rotation of machines and engines. In this research, such a device is proposed to act as variable stiffness device to alleviate the rotational oscillation existing in the many engineering applications, such as motor. Under such thought, the main purpose of this work is to characterize the nonlinear torque-angular displacement/angular velocity responses of an MRF based variable stiffness device in oscillatory motion. A rotational hysteresis model, consisting of a rotatory spring, a rotatory viscous damping element and an error function-based hysteresis element, is proposed, which is capable of describing the unique dynamical characteristics of this smart device. To estimate the optimal model parameters, a modified whale optimization algorithm (MWOA) is employed on the captured experimental data of torque, angular displacement and angular velocity under various excitation conditions. In MWOA, a nonlinear algorithm parameter updating mechanism is adopted to replace the traditional linear one, enhancing the global search ability initially and the local search ability at the later stage of the algorithm evolution. Additionally, the immune operation is introduced in the whale individual selection, improving the identification accuracy of solution. Finally, the dynamic testing results are used to validate the performance of the proposed model and the effectiveness of the proposed optimization algorithm.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.440-449
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• 2018

Purpose: This study aims to design and verify an onsite EEWS that extracts the P-wave from a single seismic station and deduce the PGV. Method: The P-wave properties of Pd, Pv, and Pa were calculated by using 12 seismic waveform data extracted from historic seismic records in Korea, and the PGVs were computed using empirical equation on the P properties - PGV relationship and compared with the observed values. Results: Comparison of the observed and estimated PGVs within the alarm level shows the error rate of 86.7% as minimum. By reducing the PTW to 2 seconds, the alarm time can be shortened by 1 second and the seismic blind zone near the epicenter can be shortened by 6 Km. Conclusion: Through this study, we confirmed the availability of the on-site EEWS in Korea. For practical use, it is necessary to develop regression formula and algorithm reflect local effect in Korea by increasing the number of seismic waveform data through continuous observation, and to eliminate the noise from the site.

• Journal of Environmental Science International
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• v.30 no.12
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• pp.1053-1065
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• 2021

In this study, the prediction technology of Hydrological Quantitative Precipitation Forecast (HQPF) was improved by optimizing the weather predictors used as input data for machine learning. Results comparison was conducted using bias and Root Mean Square Error (RMSE), which are predictive accuracy verification indicators, based on the heavy rain case on August 21, 2021. By comparing the rainfall simulated using the improved HQPF and the observed accumulated rainfall, it was revealed that all HQPFs (conventional HQPF and improved HQPF 1 and HQPF 2) showed a decrease in rainfall as the lead time increased for the entire grid region. Hence, the difference from the observed rainfall increased. In the accumulated rainfall evaluation due to the reduction of input factors, compared to the existing HQPF, improved HQPF 1 and 2 predicted a larger accumulated rainfall. Furthermore, HQPF 2 used the lowest number of input factors and simulated more accumulated rainfall than that projected by conventional HQPF and HQPF 1. By improving the performance of conventional machine learning despite using lesser variables, the preprocessing period and model execution time can be reduced, thereby contributing to model optimization. As an additional advanced method of HQPF 1 and 2 mentioned above, a simulated analysis of the Local ENsemble prediction System (LENS) ensemble member and low pressure, one of the observed meteorological factors, was analyzed. Based on the results of this study, if we select for the positively performing ensemble members based on the heavy rain characteristics of Korea or apply additional weights differently for each ensemble member, the prediction accuracy is expected to increase.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.18 no.3
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• pp.1-6
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• 2022

Ground source heat pump (GSHP) system is highly efficient and environment-friendly and supplies heating, cooling and hot water to buildings. For an optimal design of the GSHP system, the ground thermal properties should be determined to estimate the heat exchange rate between ground and borehole heat exchangers (BHE) and the system performance during long-term operating periods. However, the process increases the initial cost and construction period, which causes the system to be hindered in distribution. On the other hand, much research has been applied to the artificial neural network (ANN) to solve problems based on data efficiently and stably. This research proposes the predictive performance model utilizing ANN considering local characteristics and weather data for the predictive performance model. The ANN model predicts the entering water temperature (EWT) from the GHEs to the heat pump for the modular GHEs, which were developed to reduce the cost and spatial disadvantages of the vertical-type GHEs. As a result, the temperature error between the data and predicted results was 3.52%. The proposed approach was validated to predict the system performance and EWT of the GSHP system.

• Journal of Environmental Health Sciences
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• v.48 no.3
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• pp.151-158
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• 2022

Background: Chemical emissions in the environment have rapidly increased with the accelerated industrialization taking place in recent decades. Residents of industrial complexes are concerned about the health risks posed by chemical exposure. Objectives: This study was performed to suggest modeling methods that take into account multimedia and multi-pathways in human exposure and risk assessment. Methods: The concentration of benzene emitted at industrial complexes in Daesan, South Korea and the exposure of local residents was estimated using the Caltox model. The amount of human exposure based on inhalation rate was stochastically predicted for various activity stages such as resting, normal walking, and fast walking. Results: The coefficient of determination (R²) for the CalTOX model efficiency was 0.9676 and the root-mean-square error (RMSE) was 0.0035, indicating good agreement between predictions and measurements. However, the efficiency index (EI) appeared to be a negative value at -1094.4997. This can be explained as the atmospheric concentration being calculated only from the emissions from industrial facilities in the study area. In the human exposure assessment, the higher the inhalation rate percentile value, the higher the inhalation rate and lifetime average daily dose (LADD) at each activity step. Conclusions: Prediction using the Caltox model might be appropriate for comparing with actual measurements. The LADD of females was higher ratio with an increase in inhalation rate than those of males. This finding would imply that females may be more susceptible to benzene as their inhalation rate increases.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.119-125
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• 2010

In ad-hoc networks, dynamically reconfigurable and temporary wireless networks, all mobile devices cooperatively maintain network connectivity with no assistance of base stations while they have limited amounts of energy that is used in different rates depending on the power level. Since every node has to perform the functions of a router, if some nodes die early due to lack of energy, it will not be possible for other nodes to communicate with each other and network lifetime will be shortened. Consequently, it is very important to develop a technique to efficiently consume the limited amounts of energy resources so that the network lifetime is maximized. In this paper, geographical localized routing is proposed to help making smarter routing decision using only local information and reduce the routing overhead. The proposed localized routing algorithm selects energy-aware neighbors considering the transmission energy and error rate over the wireless link, and the residual energy of the node, which enables nodes to achieve balanced energy-consumption and the network lifetime to prolong.

• Journal of Practical Agriculture & Fisheries Research
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• v.6 no.1
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• pp.143-154
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• 2004

The value of daily heating degree hour(described as DH hereafter) is essential for calculating the heating load of a greenhouse during the winter months. Many researchers have so for proposed different models for estimating DH value. Models for estimating DH have been investigated DH(unit, ℃·h·year^-1) in this paper. The comparisons of standard and existed DH values were made to know the estimation error of each model proposed so far. The standard DH values and other proposed DH values have were obtained for the inside setpoint temperatures of 9, 13, 16 and 20℃ in greenhouse, estimated based on meterological data from 1961 to 2000 according to locals, and standard DH values were independent and existed DH values were dependent. Among the various model, the one developed theoretically by Mihara modified to author was the best fitting for standard DH values. The DH values were obtained for the inside setpoint temperature of 9, 13, 16 and 20℃ by Modified Mihara's model. A new DH contour line graph was proposed using Modified Mihara's model. Using the DH contour line graph, the DH values can be obtained easily for any setpoint according to local.

• Korean Journal of Construction Engineering and Management
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• v.24 no.2
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• pp.70-78
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• 2023

Inclinometer has several problems of 1)difficulty installing inclinometer casing, 2) measuring 2D local lateral displacement of retaining wall, 3) measurement by manpower. To solve such problems, a 2D LiDAR sensor-based retaining wall displacement measurement system was developed in previous studies. The purpose of this study is to select a displacement analysis algorithm to be applied in the retaining wall displacement measurement system. As a result of the displacement analysis algorithm selection, the M3C2 (Multiple Model to Model Cloud Comparison) algorithm with a displacement estimation error of 2mm was selected as the displacement analysis algorithm. If the M3C2 algorithm is applied in the system and the reliability of the displacement analysis result is secured through several field experiments. Convenient management of the displacement for the retaining wall is possible in comparison with the current measurement management.