• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.775-783
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• 2017

In this paper, an impulsive rendezvous problem by using minimum energy of spacecraft in different orbits is addressed. In particular, the orbits considered in this paper are the general orbits including the elliptic orbit, while most of the orbits considered in the literature have been restricted within co-planar or circular orbits. The constraints for solving this optimization problem are the Kepler's equation formulated with the universal variable, and the final position and velocity of two spacecraft. Also, the Lagrange coefficients, sometimes called as f and g solution, are used to describe the orbit transfer. The proposed method technique is demonstrated through numerical simulation by considering the minimum energy, and both the minimum energy and the wait time, respectively. Finally, it is also verified by comparing with the Hohmann transfer known as the minimum energy trajectory. Although a closed-form solution cannot be obtained, it shows that the suggested technique can provide a new insight to solve various orbital transfer problems.

• Economic and Environmental Geology
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• v.14 no.2
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• pp.93-102
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• 1981

Studies of model potential fields continued upward and downward show differences depending on the method of continuation. Beginning with a magnetic field computed over a buried vertical cylinder, the field was continued to various levels by a method introduced by Henderson (Lagrangian interpolation) and by a spectral method (frequency domain analysis). Resultant fields show (1) no significant differences in upward continued values, (2) in downward continuation, accurate values are obtained with the spectral method over the central part of the anomaly, and (3) accurate values are obtained with Henderson's method on the flanks of the anomaly, while oscillations usually characterize the spectral method in this region. Essentially the same observations are made for derivative calculations. Field oscillations are empirically predicted at levels continued to approximately two-thirds of the depth of the source. Our spectral computer program output yields marked oscillations at one-half of the depth of the source. Henderson's method shows no oscillations at this depth and only minor oscillations at the top of the body (some negative values appear on the flanks of the anomaly). The Henderson output is a smooth field even if continued below the top of the body. These results suggest that the presence of oscillations cannot be used to identify the top of a buried source without careful consideration of the method used to continue the field. Use of the derivative to outline and isolate anomalies must similarly include consideration of the method of calculation.

• Korean small business review
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• v.31 no.4
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• pp.67-93
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• 2009

The purpose of this paper is to explore the relations between financial constraints and dividend smoothing of innovative small and medium sized enterprises(SMEs) listed on Korea Securities Market and Kosdaq Market of Korea Exchange. The innovative SMEs is defined as the firms with high level of R&D intensity which is measured by (R&D investment/total sales) ratio, according to Chauvin and Hirschey (1993). The R&D investment plays an important role as the innovative driver that can increase the future growth opportunity and profitability of the firms. Therefore, the R&D investment have large, positive, and consistent influences on the market value of the firm. In this point of view, we expect that the innovative SMEs can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. And also, we expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Aivazian et al.(2006) exert that the financial unconstrained firms with the high accessibility to capital market can adjust dividend payment faster than the financial constrained firms. We collect the sample firms among the total SMEs listed on Korea Securities Market and Kosdaq Market of Korea Exchange during the periods from January 1999 to December 2007 from the KIS Value Library database. The total number of firm-year observations of the total sample firms throughout the entire period is 5,544, the number of firm-year observations of the dividend firms is 2,919, and the number of firm-year observations of the non-dividend firms is 2,625. About 53%(or 2,919) of these total 5,544 observations involve firms that make a dividend payment. The dividend firms are divided into two groups according to the R&D intensity, such as the innovative SMEs with larger than median of R&D intensity and the noninnovative SMEs with smaller than median of R&D intensity. The number of firm-year observations of the innovative SMEs is 1,506, and the number of firm-year observations of the noninnovative SMEs is 1,413. Furthermore, the innovative SMEs are divided into two groups according to level of financial constraints, such as the financial unconstrained firms and the financial constrained firms. The number of firm-year observations of the former is 894, and the number of firm-year observations of the latter is 612. Although all available firm-year observations of the dividend firms are collected, deletions are made in the case of financial industries such as banks, securities company, insurance company, and other financial services company, because their capital structure and business style are widely different from the general manufacturing firms. The stock repurchase was involved in dividend payment because Grullon and Michaely (2002) examined the substitution hypothesis between dividends and stock repurchases. However, our data structure is an unbalanced panel data since there is no requirement that the firm-year observations data are all available for each firms during the entire periods from January 1999 to December 2007 from the KIS Value Library database. We firstly estimate the classic Lintner(1956) dividend adjustment model, where the decision to smooth dividend or to adopt a residual dividend policy depends on financial constraints measured by market accessibility. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between current payout rato and target payout ratio each year. In the Lintner model, dependent variable is the current dividend per share(DPS_t), and independent variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t). We hypothesized that firms adjust partially the gap between the current dividend per share(DPS_t) and the target payout ratio(Ω) each year, when the past dividend per share(DPS_t-1) deviate from the target payout ratio(Ω). We secondly estimate the expansion model that extend the Lintner model by including the determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory. In the expansion model, dependent variable is the current dividend per share(DPS_t), explanatory variables are the past dividend per share(DPS_t-1) and the current earnings per share(EPS_t), and control variables are the current capital expenditure ratio(CEA_t), the current leverage ratio(LEV_t), the current operating return on assets(ROA_t), the current business risk(RISK_t), the current trading volume turnover ratio(TURN_t), and the current dividend premium(DPREM_t). In these control variables, CEA_t, LEV_t, and ROA_t are the determinants suggested by the residual dividend theory and the agency theory, ROA_t and RISK_t are the determinants suggested by the dividend signaling theory, TURN_t is the determinant suggested by the transactions cost theory, and DPREM_t is the determinant suggested by the catering theory. Furthermore, we thirdly estimate the Lintner model and the expansion model by using the panel data of the financial unconstrained firms and the financial constrained firms, that are divided into two groups according to level of financial constraints. We expect that the financial unconstrained firms can adjust dividend payment faster than the financial constrained firms, because the former can finance more easily the investment funds through the market accessibility than the latter. We analyzed descriptive statistics such as mean, standard deviation, and median to delete the outliers from the panel data, conducted one way analysis of variance to check up the industry-specfic effects, and conducted difference test of firms characteristic variables between innovative SMEs and noninnovative SMEs as well as difference test of firms characteristic variables between financial unconstrained firms and financial constrained firms. We also conducted the correlation analysis and the variance inflation factors analysis to detect any multicollinearity among the independent variables. Both of the correlation coefficients and the variance inflation factors are roughly low to the extent that may be ignored the multicollinearity among the independent variables. Furthermore, we estimate both of the Lintner model and the expansion model using the panel regression analysis. We firstly test the time-specific effects and the firm-specific effects may be involved in our panel data through the Lagrange multiplier test that was proposed by Breusch and Pagan(1980), and secondly conduct Hausman test to prove that fixed effect model is fitter with our panel data than the random effect model. The main results of this study can be summarized as follows. The determinants suggested by the major theories of dividend, namely, residual dividend theory, dividend signaling theory, agency theory, catering theory, and transactions cost theory explain significantly the dividend policy of the innovative SMEs. Lintner model indicates that firms maintain stable and long run target payout ratio, and that firms adjust partially the gap between the current payout ratio and the target payout ratio each year. In the core variables of Lintner model, the past dividend per share has more effects to dividend smoothing than the current earnings per share. These results suggest that the innovative SMEs maintain stable and long run dividend policy which sustains the past dividend per share level without corporate special reasons. The main results show that dividend adjustment speed of the innovative SMEs is faster than that of the noninnovative SMEs. This means that the innovative SMEs with high level of R&D intensity can adjust dividend payment faster than the noninnovative SMEs, on the ground of their future growth opportunity and profitability. The other main results show that dividend adjustment speed of the financial unconstrained SMEs is faster than that of the financial constrained SMEs. This means that the financial unconstrained firms with high accessibility to capital market can adjust dividend payment faster than the financial constrained firms, on the ground of their financing ability of investment funds through the market accessibility. Futhermore, the other additional results show that dividend adjustment speed of the innovative SMEs classified by the Small and Medium Business Administration is faster than that of the unclassified SMEs. They are linked with various financial policies and services such as credit guaranteed service, policy fund for SMEs, venture investment fund, insurance program, and so on. In conclusion, the past dividend per share and the current earnings per share suggested by the Lintner model explain mainly dividend adjustment speed of the innovative SMEs, and also the financial constraints explain partially. Therefore, if managers can properly understand of the relations between financial constraints and dividend smoothing of innovative SMEs, they can maintain stable and long run dividend policy of the innovative SMEs through dividend smoothing. These are encouraging results for Korea government, that is, the Small and Medium Business Administration as it has implemented many policies to commit to the innovative SMEs. This paper may have a few limitations because it may be only early study about the relations between financial constraints and dividend smoothing of the innovative SMEs. Specifically, this paper may not adequately capture all of the subtle features of the innovative SMEs and the financial unconstrained SMEs. Therefore, we think that it is necessary to expand sample firms and control variables, and use more elaborate analysis methods in the future studies.