• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.4_1
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• pp.121-128
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• 1992

This study aims to define the algorithm for self-calibration bundle adjustment with additional parameters, which is fit for the correction systematic errors in the SPOT satellite imagery, and to present a suitable term of additional parameters for the data form of SPOT satellite imagrery. As a result, an algorithm of self-calibration bundle adjustment for SPOT satellite imagery was settles, and the computer program was developed. Also, the suitable term of additional parameters to correct the systematic errors for each data form was defined through examination for determination effect of additional parameters and significance test. The algorithm of self-calibration bundle adjustment for SPOT satellite imagery according to this study could improve the accuracy of positioning.

• Transactions of Materials Processing
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• v.32 no.2
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• pp.74-80
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• 2023

A deformation behavior of commercially pure titanium (CP-Ti) is highly dependent on material and processing parameters, such as deformation temperature, deformation direction, and strain rate. This study aims to predict the multivariable and nonlinear tensile behavior of CP-Ti using machine learning based on three algorithms: artificial neural network (ANN), light gradient boosting machine (LGBM), and long short-term memory (LSTM). The predictivity for tensile behaviors at the cryogenic temperature was lower than those in the room temperature due to the larger data scattering in the train dataset used in the machine learning. Although LGBM showed the lowest value of root mean squared error, it was not the best strategy owing to the overfitting and step-function morphology different from the actual data. LSTM performed the best as it effectively learned the continuous characteristics of a flow curve as well as it spent the reduced time for machine learning, even without sufficient database and hyperparameter tuning.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.7-17
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• 2018

This paper examines short-run and long-run dynamic relationships between selected macroeconomic variables and stock prices in the Korea Stock Exchange. The data is restricted to the period for which monthly data are available from January 1986 to October 2016 (370 observations) retrieved from the Economic Statistics System database sponsored by the Bank of Korea. The study employs unit root test, cointegration test, vector error correction estimates, impulse response test, and structural break test. The results of the Johansen cointegration test indicate at least three cointegrating equations exist at the 0.05 level in the model, confirming that there is a long-run equilibrium relationship between stock prices and macroeconomic variables in Korea. The results of vector error correction model (VECM) estimates indicate that money supply and short-term interest rate are not related to stock prices in the short-run. However, exchange rate is positively related to stock prices while the industrial production index and inflation are negatively related to stock prices in the short-run. Furthermore, the VECM estimates indicate that the external shock, such as regional and global financial crisis shocks, neither affects changes in the endogenous variables nor causes instability in the cointegrating vector. This study finds that the endogenous variables are determined by their own dynamics in the model.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.953-963
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.

• Journal of Korea Foundry Society
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• v.13 no.4
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• pp.323-332
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• 1993

An implicit finite difference formulation with three methods of latent heat treatment, such as equivalent specific heat method, temperature recovery method and enthalpy method, was applied to solidification analysis. The Neumann problem was solved to compare the numerical results with the exact solution. The implicit solutions with the equivalent specific heat method and the temperature recovery method were comparatively consistent with the Neumann exact solution for smaller time steps, but its error increased with increasing time step, especially in predicting the solidification beginning time. Although the computing time to solve energy equation using temperature recovery method was shorter than using enthalpy method, the method of releasing latent heat is not realistic and causes error. The implicit formulation of phase change problem requires enthalpy method to treat the release of latent heat reasonably. We have modified the enthalpy formulation in such a way that the enthalpy gradient term is not needed, and as a result of this modification, the computation stability and the computing time were improved.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.12
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• pp.921-928
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• 2002

Main sources of the nitration of a gear-pair system are backlash and transmission error, the difference between required and actual rotation during gear meshing. This paper presents the nonlinear dynamic characteristics of gear motions due to the existence of backlash and periodic variation of meshing stiffness, which is assumed as a one-term harmonic component. Gear motions are classified as three types with the consideration of backlash. Each response is calculated using the harmonic balance method and confirmed by numerical integration. The responses with the increase of the rotating speed show abrupt changes in its magnitude for the variation of the preload, exciting force, and damping coefficient. The result also shows that there is a chaotic motion with some specific design parameters and operating conditions In gear diving system. Consequently the design of gear driving system with low nitration and noise requires the study on the effects of nonlinear dynamic characteristics due to stiffness variation and backlash.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.2
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• pp.69-77
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• 2001

An artificial neural network model was developed to analyze and forecast daily steamflow flow a small watershed. Error Back propagation neural networks (EBPN) of daily rainfall and runoff data were found to have a high performance in simulating stremflow. The model adopts a gradient descent method where the momentum and adaptive learning rate concepts were employed to minimize local minima value problems and speed up the convergence of EBP method. The number of hidden nodes was optimized using Bayesian information criterion. The resulting optimal EBPN model for forecasting daily streamflow consists of three rainfall and four runoff data (Model34), and the best number of the hidden nodes were found to be 13. The proposed model simulates the daily streamflow satisfactorily by comparison compared to the observed data at the HS#3 watershed of the Baran watershed project, which is 391.8 ha and has relatively steep topography and complex land use.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.8
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• pp.874-883
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• 1988

A complete form of physical optics solution to the diffraction of electromagnetic waves by a dielectric wedge with arbitrary dielectric constant and general wedge angle is obtained for an incident plane wave with any angle. Based on the formulation of dual integral equation in the spectral domain, the physical optics solution is constructed by sum of geometrical optics term including multiple reflection inside the wedge and the edge diffracted field, of which diffraction functions are represented in a quite simple form as series of cotangent functions weighted by the Fresnel reflection coefficients. Since diffraction patterns of physical optics are discontinous at dielectric interfaces, Part II and III of these three companion papers will be concerned with correction to the error of the physical optics approximation.

• Korean Management Science Review
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• v.30 no.2
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• pp.1-10
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• 2013

Case studies are made to investigate the relationship between the accuracy of energy production estimation and project feasibility indicators such as rate of return on equity (ROE) and debt service coverage ratio (DSCR) for three wind farm projects. It is found out that 1% improvement in the accuracy of energy production estimation may enhance the ROE by more than 0.5% in the case of P95, thanks to improved financing terms. AHP survey shows that MCP correlation of measured in situ wind data with long term wind speed distribution and hands-on experiences of flow analysis are more important than other factors for more precise annual energy production estimation.

• Journal of Korean Society of Transportation
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• v.24 no.4 s.90
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• pp.117-127
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• 2006

Many large cities in Korea have implemented or planed to implement a bus information system(BIS) to improve service quality for bus Passengers, mainly by Providing bus arrival time at bus stations. In those systems, similar systematic errors to estimate the bus arrival time occur, which are caused by the cycle time to identify each bus location, the information processing time of the center system, and the cycle time to update the bus arrival information on each terminal. This paper investigated each cause sequentially and estimated three expectations related to the above three causes, respectively using the random incidence concept. Through a validation using real data from a BIS in a city in Korea, fairly amount of improvements on the bus arrival time estimation have been observed.