• Journal of Navigation and Port Research
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• v.39 no.1
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• pp.69-75
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• 2015

The concrete purpose of this study is to suggest actually a debt ratio to optimize the capital structure providing a kind of approach to estimate the proper debt ratio with an analytical model and empirical data in Korean shipping industry. The mathematical and analytical model is started from the first equation about ROE, return of net operating income on equity, with an independent variable, debt ratio. It is constructed with several parameters, ROS(return of operating income on sales), TAT(total assets turnover), and NFCL(net finance cost to liabilities). There could not be a certain relationship between debt ratio and ROS or TAT, while some correlation or causality between debt ratio and NFCL. In other words, most of firms with high debt ratio is likely to burden higher finance cost than others with low one. In this case, there is a linearity relationship between debt ratio and NFCL, so then the second equation considering this relation could be included within the analytical approach of this paper. To be short, if the criteria of adequate debt ratio has to be defined as some level of debt ratio to optimize ROE, the ROE could be illustrated as a quadratic equation to debt ratio from two equations. Next, this research estimated those parameters' numbers through the single regression method with data over 12 years of Korean shipping industry, and identified empirically the fact that optimal debt ratio would be approximately 400%. To conclude, if that industry's sales and operating incomes are stable, the debt ratio could be accepted until twice of 200% had forced in order to guarantee its financial safety in past time.

• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1155-1163
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• 2014

The complementary relationship-based evapotranspiration models, namely, AA model of Brutsaert and Stricker (1979) and the CRAE model of Morton (1983) was applied to two permanent stream watersheds Jeju island for the first time, and their major optimal parameters were suggested in this study. The representative watersheds for model calibration and validation were selected as the Hancheon watershed located in the northern part of the Jeju island and and the Kangjeongcheon watershed in southern Jeju island, respectively. The estimated actual evapotranspiration for the Hancheon watershed was compared with the result by the hydrological model, and the major parameters of the AA and CRAE models were calibrated until their results match the hydrological simulations. Through the iterative estimations, the optimal parameters were determined as ${\alpha}=1.00$, $M=30.0Wm^{-2}$ of the AA model, and $b_1=33.0Wm^{-2}$, $b_2=1.02$ of the CRAE model. The calibrated AA and CRAE models were applied to the Kangjeongcheon watershed for model validation, and it was found out that both models can accurately produce the actual evaporation on annual and semiannual bases.

• Journal of the Korean Society for Heat Treatment
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• v.25 no.1
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• pp.6-13
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• 2012

HVOF thermal spray coating of 80%WC-CoFe powder is one of the most promising candidate for the replacement of the traditional hard chrome plating and hard ceramics coating because of the environmental problem of the very toxic $Cr^{6+}$ known as carcinogen by chrome plating and the brittleness of ceramics coatings. 80%WC-CoFe powder was coated by HVOF thermal spraying for the study of durability improvement of the high speed spindle such as air bearing spindle. The coating procedure was designed by the Taguchi program, including 4 parameters of hydrogen and oxygen flow rates, powder feed rate and spray distance. The surface properties of the 80%WC-CoFe powder coating were investigated roughness, hardness and porosity. The optimal condition for thermal spray has been ensured by the relationship between the spary parameters and the hardness of the coatings. The optimal coating process obtained by Taguchi program is the process of oxygen flow rate 34 FRM, hydrogen flow rate 57 FRM, powder feed rate 35 g/min and spray distance 8 inch. The coating cross-sectional structure was observed scanning electron microscope before chemical etching. Estimation of coating porosity was performed using metallugical image analysis. The Friction and wear behaviors of HVOF WC-CoFe coating prepared by OCP are investigated by reciprocating sliding wear test at $25^{\circ}C$ and $450^{\circ}C$. Friction coefficients (FC) of coating decreases as sliding surface temperature increases from $25^{\circ}C$ to $450^{\circ}C$.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.733-745
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• 2017

Local composite quantile regression is a useful non-parametric regression method widely used for its high efficiency. Data smoothing methods using kernel are typically used in the estimation process with performances that rely largely on the smoothing parameter rather than the kernel. However, $L_2$-norm is generally used as criterion to estimate the performance of the regression function. In addition, many studies have been conducted on the selection of smoothing parameters that minimize mean square error (MSE) or mean integrated square error (MISE). In this paper, we explored the optimality of selecting smoothing parameters that determine the performance of non-parametric regression models using local linear composite quantile regression. As evaluation criteria for the choice of smoothing parameter, we used mean absolute error (MAE) and mean integrated absolute error (MIAE), which have not been researched extensively due to mathematical difficulties. We proved the uniqueness of the optimal smoothing parameter based on MAE and MIAE. Furthermore, we compared the optimal smoothing parameter based on the proposed criteria (MAE and MIAE) with existing criteria (MSE and MISE). In this process, the properties of the proposed method were investigated through simulation studies in various situations.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.205-214
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• 2020

In this study, we performed to evaluate the water balance during the cultivation of Chinese cabbage and maize according to the soil type and water management method using weighable lysimeters, and to estimate the crop water stress coefficient and minimal water requirement by considering crop productivity and water deficiency. In 2018, Chinese cabbage cultivation period was not irrigated due to frequent rainfall two weeks after planting, so there was no difference in irrigation amount between the non-irrigated and the irrigated and little difference in crop yield. Excluding the Chinese cabbage cultivation in 2018, in the cultivation of Chinese cabbage and maize, the crop yield of irrigated plots was higher than that of non-irrigated plots. The evapotranspiration of irrigated plots was also generally higher than non-irrigated plots. Crop yield and evapotranspiration are closely related, and transpiration is active as biomass increases. The crop water stress coefficients in the middle and the late stage were 0.8 and 0.8 for Chinese cabbage and 0.8 and 0.5 for maize, respectively. The minimal water requirements for Chinese cabbage and maize were 82.0% and 68.8%, respectively, compared to the optimal water requirements (239.4 mm for Chinese cabbage and 466.9 mm for maize). These results can be used as basic data for water management for crop cultivation by securing the minimum amount of irrigation in case of water deficiency.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.3
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• pp.1-10
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• 2008

The seismic performance of a structure designed without consideration of seismic loading can be effectively enhanced through seismic rehabilitation. The appropriate level of rehabilitation should be determined based on the decision criteria that minimize the anticipated earthquake-related losses. To estimate the anticipated losses, seismic risk analysis should be performed considering the probabilistic characteristics of the hazard and the structural damage. This study presents the decision procedure in which the probabilistic seismic demand model is utilized for the effective estimation and minimization of the total seismic losses through seismic rehabilitation. The probability density function and the cumulative distribution function of the structural damage for a specified time period are established in a closed form, and are combined with the loss functions to derive the expected seismic loss. The procedure presented in this study could be effectively used for making decisions on the seismic rehabilitation of structural systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.80-92
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• 2008

Many predominant video coding tools in terms of coding efficiency were adopted in the latest video coding standard, H.264/AVC. Regardless of development of these predominant video coding tools such as the variable block-size motion estimation/compensation, intra prediction based on various directions, and so on, the discrete cosine transform has been continuously used starting from the early video coding standards. Generally, the correlation coefficient of the residual signal is usually less than 0.5 when this residual signal is actually encoded. In this interval of correlation coefficient, the discrete cosine transform does not show the optimal coding gain, and the discrete sine transform which is a sub-optimal transform when the correlation coefficient is in the interval from -0.5 to 0.5 can be used in conjunction with the discrete cosine transform in the video coding. In this paper, an alternative transform that alternatively uses the discrete sine transform and integer cosine transform in H.264/AVC by using rate-distortion optimization is proposed. The proposed method achieves a BD-PSNR gain of up to 0.71 dB compared to H.264/AVC JM 10.2 at relatively high bitrates.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.183-190
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• 2018

This paper presents optimization of the main spar of Human-Powered Aircraft (HPA) wing. Mass minimization was attempted, while considering large torsional deformation of the beam. Sequential Quadratic Programming (SQP) method was adopted as a relevant tool to conduct structural optimization algorithm. An inner diameter and ply thicknesses of the main spar were selected as the design variables. The objective function includes factors such as mass minimization, constant tip bending displacement, and constant tip twist of the beam. For estimation of bending and torsional deformation, the geometrically exact beam model, which is appropriate for large deflection, was adopted. Properties of the cross sectional area which the geometrically exact beam model requires were obtained by Variational Asymptotic Beam Sectional Analysis (VABS), which is a cross sectional analysis program. As a result, maintaining tip bending displacement and tip twist within 1.45%, optimal design that accomplished 7.88% of the mass reduction was acquired. By the stress and strain recovery, structural integrity of the optimal design and validity of the present optimization procedure were authenticated.

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.363-373
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• 2010

The existing QoS mechanisms for video streaming are short of the consideration for various user environments and the characteristic of streaming applying programs. In order to overwhelm this problem, studies on the video streaming protocols exploiting scalable video coding (SVC), which provide spatial, temporal, and qualitative scalability in video coding, are progressing actively. However, these protocols also have the problem to deepen network congestion situation, and to lower fairness between other traffics, as they are not equipped with congestion control mechanisms. SVC based streaming protocols also have the problem to overlook the property of videos encoded in SVC, as the protocols transmit the streaming simply by extracting the bitstream which has the maximum bit rate within available bandwidth of a network. To solve these problems, this study suggests TCP-friendly network adaptive SVC streaming(T-NASS) protocol which considers both network status and SVC bitstream property. T-NASS protocol extracts the optimal SVC bitstream by calculating TCP-friendly transmission rate, and by perceiving the network status on the basis of packet loss rate and explicit congestion notification(ECN). Through the performance estimation using an ns-2 network simulator, this study identified T-NASS protocol extracts the optimal bitstream as it uses TCP-friendly transmission property and perceives the network status, and also identified the video image quality transmitted through T-NASS protocol is improved.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.5
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• pp.574-583
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• 2021

Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.