• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.33-40
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• 2020

This work tackles the problem of conventional reinforcement learning scheme which has a relatively long training time to reduce energy consumption in underwater network. The enhanced scheme adjusts the learning range of reinforcement learning based on distance estimation. It can be reduce the scope of learning. To take account the fact that the distance estimation may not be accurate due to the underwater wireless network characteristics. this research added noise in consideration of the underwater environment. In simulation result, the proposed AQ-NAV scheme has completed learning much faster than existing method. AQ-NAV can finish the training process within less than 40 episodes. But the existing method requires more than 120 episodes. The result show that learning is possible with fewer attempts than the previous one. If AQ-NAV will be applied in Underwater Networks, It will affect energy efficiency. and It will be expected to relieved existing problem and increase network efficiency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4780-4785
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• 2012

As many mobile devices such as smart phones and tablets are widely spread, optimized mobile video encoder used during video recording application is needed. In this paper, we implemented H.264/AVC base profile video encoder on a mobile device and empirically optimized control parameters of the encoder. As the experiment, we more than 100 test cases were designed with varying Lagrangian optimization, Hadamard Transform, search range, I-frame period, and reference frames. During the experiment, we measured picture quality, bit-rate, encoding time, motion estimation time, and power consumption. From the result, we can determine optimal values for the H.264 control parameters.

• Journal of Energy Engineering
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• v.22 no.4
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• pp.370-375
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• 2013

This paper attempts to estimate the city gas demand function in Korea over the period 1981-2012. As the city gas demand function provides us information on the pattern of consumer's city gas consumption, it can be usefully utilized in predicting the impact of policy variables such as city gas price and forecasting the demand for city gas. We apply lagged dependent variable model and ordinary least square method as a robust approach to estimating the parameters of the city gas demand function. The results show that short-run price and income elasticities of the city gas demand are estimated to be -0.522 and 0.874, respectively. They are statistically significant at the 1% level. The short-run price and income elasticities portray that demand for city gas is price- and income-inelastic. This implies that the city gas is indispensable goods to human-being's life, thus the city gas demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for city gas is price- and income-elastic in the long-run.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.703-720
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• 2019

The influence of temperature on electricity demand is increasing due to extreme weather and climate change, and the climate impacts involves nonlinearity, asymmetry and complexity. Considering changes in government energy policy and the development of the fourth industrial revolution, it is important to assess the climate effect more accurately for stable management of electricity supply and demand. This study aims to analyze the effect of temperature change on electricity demand using the partial linear model. The main results obtained using the time-unit high frequency data for meteorological variables and electricity consumption are as follows. Estimation results show that the relationship between temperature change and electricity demand involves complexity, nonlinearity and asymmetry, which reflects the nonlinear effect of extreme weather. The prediction accuracy of in-sample and out-of-sample electricity forecasting using the partial linear model evidences better predictive accuracy than the conventional model based on the heating and cooling degree days. Diebold-Mariano test confirms significance of the predictive accuracy of the partial linear model.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.7
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• pp.757-766
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• 2014

In this paper, economic loss due to high power electromagnetic pulse is estimated and the methodology used for calculating its impacts is suggested using a macro approach. In order to investigate the most critical infrastructure for the high power electromagnetic pulse assault, the vulnerability assessment that provides information on the threats of concern is conducted. As a result, this study concentrates on the electric power networks. The presented assessment model is considered with gross domestic product (GDP) and energy consumption when the electric power networks are damaged due to high power electromagnetic pulse. In addition, economic losses are calculated by the extent of damages considering different types of the high power electromagnetic pulse assault generated by nuclear and man-made weapon. Through the estimation of these damages, the resulted economic loss will be compared with the protection cost. Consequently, protection of the vulnerable infrastructures can be prepared against electromagnetic pulse attack.

• The KSFM Journal of Fluid Machinery
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• v.17 no.2
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• pp.24-29
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• 2014

In general, a large-capacity axial flow fan is used for industrial processes or ventilation in a social overhead capital infrastructure. The main characteristics of the large axial-flow fan need a lot of electrical power consumption and operate 24 hours a day, 365 days a year. Since the large axial flow fan consumes several hundreds to thousands kW per hour, both manufacturer and consumer are struggling to select high efficiency products for saving energy and reducing operation cost. Therefore, the performance testing should be accurately conducted in experimental equipments. The performance estimation and uncertainty of measurement of the axial-flow fan gathered from the result from nozzle shaped testing equipments certified with ANSI/AMCA standard and duct shaped testing equipment under the same experimental condition. The experimental results from both facilities have maximum 17% differences in performance evaluation and uncertainty of measurement. As considering that the differences, it is doubt about the reliability of testing result. The test was repeated with the specific term during 12 months because it is important to fully reflect the real conditions and to decide the repeatability of data. The evaluation of duct type testing facilities was failed to get an uncertainty measure. Testing results were previously published. As a series of previous paper, axial fan (∅1690 mm) and duct type testing facilities were fabricated. The purpose of fabricating testing equipment was testing an uncertainty measurement under the controlled environments.

• Environmental and Resource Economics Review
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• v.23 no.2
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• pp.225-248
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• 2014

The purpose of this study is to estimate the optimal tax rate for gasoline in Korea, by utilizing both the parameters for the estimation of the optimal fuel taxes and the theoretical model considering externalities proposed by Parry and Small (2005). The result of simulation shows that the optimum fuel taxes in Korea is calculated in 382 korean won per liter, which is lower than fuel tax rate(529 korean won per liter) currently being imposed. The fuel tax is composed of two types of tax. First is Pigouvian tax caused by negative externality such as traffic congestion and accidents etc. And second is Ramsey tax for optimal commodity sales taxes. We find that Pigouvian tax in Korea is higher than one of U.S. and U.K and Ramsey tax is very small due to the inelastic labor supply comparing to consumption elasticity of fuel. When adjusting the elasticity of labor supply to the UK level, the optimal fuel tax in Korea is very close to the current level of 480 korean won per liter. This paper contributes to suggest the reasonable estimation and discussion in the social optimum fuel tax rates by utilizing the theory and simulation and improve the possibility of the derivation of optimum fuel taxes through both securing the exact parameters and modifying the theoretical model suitable for Korea.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.571-573
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• 2018

Wireless sensor networks have unbalanced energy consumption due to the convergence structure in which data is concentrated to sink nodes. To solve this problem, in the previous research, the relay node was placed between the source node and the sink node to merge the data before being concentrated to the sink node. However, selecting a relay node that does not consider the link quality causes packet loss according to the link quality of the reconfigured routing path. Therefore, in this paper, we propose a link cost calculation method for data reliability in routing path reconfiguration for relay node selection. We propose a link cost estimation formula considering the number of hops and RSSI as the routing metric value and select the RSSI threshold value through the packet transmission experiment between the sensor modules.

• Environmental and Resource Economics Review
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• v.29 no.1
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• pp.23-45
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• 2020

The rapid economic growth has brought tremendous pressure on the environment and caused severe air pollution in China. This study empirically examines causes of air pollution in China. Panel-corrected standard errors procedure (PCSE) was used to analyze major determinants of increasing or reducing emissions of sulfur dioxide (SO₂) and nitrogen oxides (NO_X) in 30 Chinese provinces. The estimation results show that SO₂ emission is mitigated as per capita regional GDP increases, but the relation between emission of NO_X and per capita regional GDP is found to have an inverse N-shaped curve, which implies that emission of NO_X is ultimately expected to decline with economic growth. As for increasing factors of air pollutants, electricity consumption is a significant common source of SO₂ and NO_X emissions. Moreover, the results show that increment of coal consumption significantly affects emission of SO₂ while increase of natural gas consumption reduce emission of SO₂. On the other side, investment in energy industry, and investment on treatment of waste gases are determinants of mitigating emissions of SO₂, but have no impact on NO_X. Consumption of diesel, truck ratio and number of vehicles increase emission of NO_X. Meanwhile, higher precipitation rate is a common determinant of mitigating emissions of SO₂ and NO_X. Policy implications are suggested in the conclusion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2338-2356
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• 2013

In cognitive radio networks, acquiring the position information of the primary user is critical to the communication of the secondary user. Localization of primary users can help improve the efficiency with which the spectrum is reused, because the information can be used to avoid harmful interference to the network while simultaneity is exploited to improve the spectrum utilization. Despite its inherent inaccuracy, received signal strength based on range has been used as the standard tool for distance measurements in the location detection process. Most previous works have employed the path-loss propagation model with a fixed value of the path loss exponent. However, in actual environments, the path loss exponent for each channel is different. Moreover, due to the complexity of the radio channel, when the number of channel increases, a larger number of RSS measurements are needed, and this results in additional energy consumption. In this paper, to overcome this problem, we propose using the Bayesian compressive sensing method with a calibrated path loss exponent to improve the performance of the PU localization method.