• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of the Korean Geosynthetics Society
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• v.19 no.1
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• pp.93-101
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• 2020

In order to predict the nonlinear behaviour of the soil, the elasto-plastic hyperbolic model was selected, which was considered to be relatively simple and highly predictable. The soil parameter determination and the behavior analysis program were developed by formalizing the functions related to the constitutive model. Each soil parameter was determined from the results of the drained triaxial compression tests of Baekma river sand with the change of relative density. The stress-strain behavior was predicted using the soil parameters determined under each condition. As a result, the deviator stress for the axial strain is verified to have a good match between the measured value and predicted value at each relative density. In the relationship between the volumetric stain and the axial strain, when the relative density is loose, the measured value and predicted value tend to match, and when relative density is dense, the predicted value of the volumetric strain appears somewhat smaller than the measured value due to the limitation of the constitutive model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7754-7760
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• 2015

The outer tie rod is one of the part of steering system, the optimization process was executed to find the lightweight design. The inner tie rod was considered in the optimum design of an outer tie rod. it could be closer to the test condition than in the case of considering outer tie rod only. The aluminum forging material was considered as a weight reduction proposal. The target of optimization was the shape of the minimum weight to resist at the load of buckling. RSM and Kriging interpolation method were applied as a optimization method to consider the nonlinear shape optimization problem. Then, 16.3%, 16.6% of weight reduction was obtained from the result comparing with that of the initial model. The results of meta model optimization was compared with that of finite element method. The error values of buckling load estimation were 2.6%, 2.04%. and those of weight estimation were 0.17%, 0.13%. Therefore, it seemed that the result of Kriging model could be obtained closer to optimum value than that of RSM model.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1905-1919
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process (ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of wastewater, the change in influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains are adjusted by the expert who has much experience in the ASP. The ASP model based on $Matlab^{(R)}5.3/Simulink^{(R)}3.0$ is developed in this paper. The performance of the model is tested by IWA(International Water Association) and COST(European Cooperation in the field of Scientific and Technical Research) data that include steady-state results during 14 days. The advantage of the developed model is that the user can easily modify or change the controller by the help of the graphical user interface. The ASP model as a typical nonlinear system can be used to simulate and test the proposed controller for an educational purpose. Various control methods are applied to the ASP model and the control results are compared to apply the proposed intelligent control strategy to a real ASP. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method. The proposed setpoints changer based on the fuzzy logic shows a better performance and robustness under disturbances. The objective function can be defined and included in the proposed control strategy to improve the effluent water quality and to reduce the operating cost in a real ASP.

• Journal of the Korea Concrete Institute
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• v.22 no.3
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• pp.381-388
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• 2010

In this study, characteristics of the seismic response of the non-earthquake resistant reinforced concrete (RC) frame were identified. The test building is designed to withstand only gravity loads and not in compliance with modern seismic codes. Smooth bars were utilized for the reinforcement. Members are provided with minimal amount of stirrups to withstand low levels of shear forces and the core concrete is virtually not confined. Columns are slender and more flexible than beams, and beam-column connections were built without stirrups. Through the modeling of an example RC frame, the feasibility of the fiber elementbased 3D nonlinear analysis method was investigated. Since the torsion is governed by the fundamental mode shape of the structure under dynamic loading, pushover analysis cannot predict torsional response accurately. Hence, dynamic response history analysis is a more appropriate analysis method to estimate the response of an asymmetric building. The latter method was shown to be accurate in representing global responses by the comparison of the analytical and experimental results. Analytical models without rigid links provided a good estimation of reduced stiffness and strength of the test structure due to bond-slip, by forming plastic hinges closer to the column ends. However, the absence of a proper model to represent the bond-slip poased the limitations on the current inelastic analysis schemes for the seismic analysis of buildings especially for those with round steel reinforcements. Thus, development of the appropriate bond-slip model is in need to achieve more accurate analysis.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.139-149
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• 2004

As the expansion of road capacity has become impractical in many urban areas, congestion pricing has been widely considered as an effective method to reduce urban traffic congestion in recent years. The principal reason is that the congestion pricing may lead the user equilibrium (UE) flow pattern to system optimum (SO) pattern in road network. In the context of network equilibrium, the link tolls according to the marginal cost pricing principle can user an UE flow to a SO pattern. Thus, the pricing method offers an efficient tool for moving toward system optimal traffic conditions on the network. This paper proposes a continuous network design program (CNDP) in network equilibrium condition, in order to find optimal congestion toll for maximizing net economic benefit (NEB). The model could be formulated as a bi-level program with continuous variable(congestion toll) such that the upper level problem is for maximizing the NEB in elastic demand, while the lower level is for describing route choice of road users. The bi-level CNDP is intrinsically nonlinear, non-convex, and hence it might be difficult to solve. So, we suggest a heuristic solution algorithm, which adopt derivative information of link flow with respect to design parameter, or congestion toll. Two example networks are used for test of the model proposed in the paper.

• Journal of Pharmaceutical Investigation
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• v.39 no.3
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• pp.185-199
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• 2009

Using a strain-controlled rheometer [Advanced Rheometric Expansion System (ARES)], the steady shear flow properties and the dynamic viscoelastic properties of $Antiphlamine-S^{(R)}$ lotion have been measured at $20^{\circ}C$ (storage temperature) and $37^{\circ}C$ (body temperature). In this article, the temperature dependence of the linear viscoelastic behavior was firstly reported from the experimental data obtained from a temperature-sweep test. The steady shear flow behavior was secondly reported and then the effect of shear rate on this behavior was discussed in detail. In addition, several inelastic-viscoplastic flow models including a yield stress parameter were employed to make a quantitative evaluation of the steady shear flow behavior, and then the applicability of these models was examined by calculating the various material parameters. The angular frequency dependence of the linear viscoelastic behavior was nextly explained and quantitatively predicted using a fractional derivative model. Finally, the strain amplitude dependence of the dynamic viscoelastic behavior was discussed in full to elucidate a nonlinear rheological behavior in large amplitude oscillatory shear flow fields. Main findings obtained from this study can be summarized as follows : (1) The linear viscoelastic behavior is almostly independent of temperature over a temperature range of $15{\sim}40^{circ}C$. (2) The steady shear viscosity is sharply decreased as an increase in shear rate, demonstrating a pronounced Non-Newtonian shear-thinning flow behavior. (3) The shear stress tends to approach a limiting constant value as a decrease in shear rate, exhibiting an existence of a yield stress. (4) The Herschel-Bulkley, Mizrahi-Berk and Heinz-Casson models are all applicable and have an equivalent validity to quantitatively describe the steady shear flow behavior of $Antiphlamine-S^{(R)}$ lotion whereas both the Bingham and Casson models do not give a good applicability. (5) In small amplitude oscillatory shear flow fields, the storage modulus is always greater than the loss modulus over an entire range of angular frequencies tested and both moduli show a slight dependence on angular frequency. This means that the linear viscoelastic behavior of $Antiphlamine-S^{(R)}$ lotion is dominated by an elastic nature rather than a viscous feature and that a gel-like structure is present in this system. (6) In large amplitude oscillatory shear flow fields, the storage modulus shows a nonlinear strain-thinning behavior at strain amplitude range larger than 10 % while the loss modulus exhibits a weak strain-overshoot behavior up to a strain amplitude of 50 % beyond which followed by a decrease in loss modulus with an increase in strain amplitude. (7) At sufficiently large strain amplitude range (${\gamma}_0$>100 %), the loss modulus is found to be greater than the storage modulus, indicating that a viscous property becomes superior to an elastic character in large shear deformations.

• Journal of Environmental Science International
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• v.17 no.8
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• pp.891-898
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• 2008

This study was conducted to develop the effects of site environmental factors on estimation of site index function for Chamaecyparis obtusa Endlicher stands. We derived nonlinear growth equation and the draw site index curves by applying this estimated equation. This study with Chapman-Richards function showed significant P-value which was less then 0.0001 and $R^2$ value 0.5947. This study was conducted to develop the feasible site index equation of Chamaecyparis obtusa Endlicher. For the table, the data of 82 sample areas that were thought to be without errors among the data of Chamaecyparis obtusa Endlicher sample area located on the value-oriented forest location chart were used and estimated. After analyzing the quantification method I based on 13 environmental factors to develop the score table for the site-index estimation of Chamaecyparis obtusa Endlicher, $R^2$ value of the model was 0.7555. It has been analyzed that the scope value of Soil moisture in horizon A was 7.5045, that of total soil depth was 6.3896, that of topography was 5.3471, that of slope was 4.7000 and that of aspect was 3.2038. After analyzing the partial correlation to examine the factors that affected most the site-index of Chamaecyparis obtusa Endlicher, it has been noted that the partial correlation of climatic zone was 0.4987, which was highest, and it was followed by Soil moisture in horizon A (0.4592), slope (0.4537), topography (0.3299) and total soil depth (0.1035). As a result of conducting the significance test for partial correlation, it has been found that topography, climatic zone, parent rock, slope, altitude, aspect, Soil moisture in horizon A, soil hardness in horizon A and total soil depth were recognized significant with 1% of significance level and sedimentary type and soil texture in horizon A were recognized significant with 5% of significance level.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.372-379
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• 2023

International oil prices are expected to increase from $85 a barrel this year to up to $100 a barrel in the second half of the year; this is likely to increase orders for offshore plants in the global market. One main characteristic of offshore plants is that a large helideck is located on the top side, and aluminum alloys are used as the basic material of the structure for weight reduction and corrosion resistance. Shipowners are increasing the size of helicopters to quickly evacuate lives in the event of an emergency, and the safety use load of devices that can stably secure helicopters to the deck is also required to increase. Owing to the nature of the aluminum material, the structural strength caused by welding is greatly reduced; therefore, the fixing device must be designed by embedding it in the deck and fixing it with bolts. In this study, a model applying aluminum alloy 6082-T6 was developed to develop a helicopter fastening device that can be used for large helidecks (diameter = 28 m). The developed item was verified through nonlinear structural strength calculation to satisfy the load used for the actual fastening condition. The load condition with a 45° showed a lower ultimate strength than the 90° case owing to local plastic collapse. The nonlinear structural collapse behavior showed a result similar to that of the experimental test. The main contents derived from this study are considered to be reference materials when evaluating the structural strength of similar aluminum equipment.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1115-1123
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• 2008

When constructing projects such as road embankments, bridge approaches, dikes or buildings on soft, compressible soils, significant settlements may occur due to the consolidation of these soils under the superimposed loads. The compressibility of the soil skeleton of a soft clay is influenced by such factors as structure and fabric, stress path, temperature and loading rate. Although it is possible to determine appropriate relations and the corresponding material parameters in the laboratory, it is well known that sample disturbance due to stress release, temperature change and moisture content change can have a profound effect on the compressibility of a clay. The early research of Tezaghi and Casagrande has had a lasting influence on our interpretation of consolidation data. The 24 hour, incremental load, oedometer test has become, more or less, the standard procedure for determining the one-dimensional, stress-strain behavior of clays. An important notion relates to the interpretation of the data is the ore-consolidation pressure ${\sigma}_p$, which is located approximately at the break in the slope on the curve. From a practical point of view, this pressure is usually viewed as corresponding to the maximum past effective stress supported by the soil. Researchers have shown, however, that the value of ${\sigma}_p$ depends on the test procedure. furthermore, owing to sampling disturbance, the results of the laboratory consolidation test must be corrected to better capture the in-situ compressibility characteristics. The corrections apply, strictly speaking, to soils where the relation between strain and effective stress is time independent. An important assumption in Terzaghi's one-dimensional theory of consolidation is that the soil skeleton behaves elastically. On the other hand, Buisman recognized that creep deformations in settlement analysis can be important. this has led to extensions to Terzaghi's theory by various investigators, including the applicant and coworkers. The main object of this study is to suggestion the modified compression index value to predict settlements by back calculating the $C_c$ from different numerical models, which are giving best prediction settlements for multi layers including very thick soft clay.