• Journal of IKEEE
• /
• v.4 no.2 s.7
• /
• pp.249-256
• /
• 2000

In EIT(electrical impedance tomography), the internal resistivity(or conductivity) distribution of the unknown object is estimated using the boundary voltage data induced by different current patterns using various reconstruction algorithms. In this paper, we present a regularized modified Newton-Raphson(mNR) scheme which employs additional a priori information in the cost functional as soft constraint and the weighting matrices in the cost functional are selected based on the exponentially weighted least square criterion. The computer simulation for the 32 channels synthetic data shows that the reconstruction performance of the proposed scheme is improved compared to that of the conventional regularized mNR at the expense of slightly increased computational burden.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.24 no.1
• /
• pp.1-22
• /
• 2020

An accurate and efficient gradient estimation method on unstructured grid is presented by proposing a switching process between two Least-Square methods. Diverse test cases show that the gradient estimation by Least-Square methods exhibit better characteristics compared to Green-Gauss approach. Based on the investigation, switching between the two Least-Square methods, whose merit complements each other, is pursued. The condition number of the Least-Square matrix is adopted as the switching criterion, because it shows clear correlation with the gradient error, and it can be easily calculated from the geometric information of the grid. To illustrate switching process on general grid, condition number is analyzed using stencil vectors and trigonometric relations. Then, the threshold of switching criterion is established. Finally, the capability of Switching Weighted Least-Square method is demonstrated through various two- and three-dimensional applications.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.10
• /
• pp.175-185
• /
• 1998

In this paper, we studied some design methodologies of typical FIR filters based on the peak-error constrained least square criterion which was first introducedd by Adams in 1991. This method is a mixed type of the classical least squared error method(LSM) and the so-called min-max error method (MMM). And by considering both the least squared error as well as the maximum error, the solution, i.e. the impulse response of the filter, can be found only when the restrictions on maximum gain, transition bandwidth, and the squared error are satisfied simultaneously under some trade-off conditions. We used the multiple exchange algorithms for optimization procedure and applied the design methodology to the cases of the multiband filter, the differentiator, and the Hilbert transformer by taking the balance of two design criteria into account. The results show that the peak-error constrained least weighted square error design method(PLEM) is superior in performance to the existing LSM and MMM from both the squared error and the maximum error standpoints. And it is verified that PLEM can be applied to not only the case of simple low pass filter, but also to various types of FIR filters.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.3C
• /
• pp.338-347
• /
• 2007

In this paper, a weighted block adaptive channel estimation (WBA-CE) for a space-time block-coded (STBC) single-carrier transmission with a cyclic-prefix is proposed. In operation of the WBA-CE, a STBC matrix-wise block for filter input symbols is first formulated. Applying a weighted a posteriori error vector-based least-square (LS) criterion for this block, the coefficient correction terms of the WBA-CE are then computed. An approximate steady-state excess mean-square error (EMSE) of the WBA-CE for the stationary optimal coefficient is also analyzed. Simulation results show in a time-varying typical urban (TU) channel that the proposed channel estimator provides better bit-error-rate (BER) performances than conventional algorithms such as the NLMS and RLS channel estimators.

• Journal of Korea Trade
• /
• v.26 no.7
• /
• pp.1-18
• /
• 2022

Purpose - Recent international studies have largely focused on measuring the welfare gains from increased trade varieties. To adequately capture the variety gains, it is of importance to estimate the elasticity of substitution between varieties of trade goods because it is one of the key parameters to determine the magnitude of the variety gains. Using the import data of South Korea, this paper shows that the elasticities vary substantially across the estimators, which affects the magnitude of the gains from trade. Design/methodology - Empirical studies working on the gains from trade variety have heavily depended on the estimation methods for the elasticity of substitution between trade varieties, developed by Feenstra (1994) and refined by Broda and Weinstein (2006). We estimate and compare the estimated elasticities for 8,945 HS 10 goods of South Korea, obtained from the three estimation methods: Feenstra's weighted least square (F-WLS), Feenstra's feasible generalized least square (F-FGLS), and Broda and Weinstein's feasible generalized least square (BW-FGLS). Findings - Using the estimated elasticities from the F-FGLS, considered as a suitable estimator, A typical Korean consumer saved 228 dollars per year by the greater access to new import varieties. This leads to gains from imported variety of 2.06% of GDP. In 2017, a typical Korean consumer would gain by 611 dollars, compared with 2000. China is the country with the largest contribution (28.4%), followed by Japan and USA. About 50% of all the welfare gains come from the imports from the three main trade partners. The Southern Asian countries are more important to the South Korean welfare gain than the Western European countries. Originality/value - Existing studies have chosen one of the methods without any criterion for the choice and then estimated the elasticities of substitution between varieties of trade goods. This paper focuses on the estimation specifications and methods as the cause of the disparity in estimated elasticities and welfare gains from trade variety. According to the Ramsey RESET and White tests, the F-FGLS estimates are relatively better compared to the F-WLS and BW-FGLS estimates. As another contribution, this paper provides the first measure of the welfare gains from trade variety for South Korea, using the estimated elasticities of substitution between trade varieties.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.1
• /
• pp.31-39
• /
• 2017

The goal of this study was to efficiently analyze the relationships of the number of thefts with related factors, considering the spatial patterns of theft crimes. Theft crime data for a 5-year period (2009-2013) were collected from Haeundae Police Station. A logarithmic transformation was performed to ensure an effective statistical analysis and the number of theft crimes was used as the dependent variable. Related factors were selected through a literature review and divided into social, environmental, and defensive factors. Seven factors, were selected as independent variables: the numbers of foreigners, aged persons, single households, companies, entertainment venues, community security centers, and CCTV (Closed-Circuit Television) systems. OLS (Ordinary Least Squares) and GWR (Geographically Weighted Regression) were used to analyze the relationship between the dependent variable and independent variables. In the GWR results, each independent variable had regression coefficients that differed by location over the study area. The GWR model calculated local values for, and could explain the relationships between, variables more efficiently than the OLS model. Additionally, the adjusted R square value of the GWR model was 10% higher than that of the OLS model, and the GWR model produced a AICc (Corrected Akaike Information Criterion) value that was lower by 230, as well as lower Moran's I values. From these results, it was concluded that the GWR model was more robust in explaining the relationship between the number of thefts and the factors related to theft crime.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2393-2398
• /
• 2003

In this paper, we proposes a new fuzzy inference system for modeling nonlinear systems given input and output data. In the suggested fuzzy inference system, the number of fuzzy rules and parameter values of membership functions are automatically decided by using the kernel-based method. The kernel-based method individually performs linear transformation and kernel mapping. Linear transformation projects input space into linearly transformed input space. Kernel mapping projects linearly transformed input space into high dimensional feature space. The structure of the proposed fuzzy inference system is equal to a Takagi-Sugeno fuzzy model whose input variables are weighted linear combinations of input variables. In addition, the number of fuzzy rules can be reduced under the condition of optimizing a given criterion by adjusting linear transformation matrix and parameter values of kernel functions using the gradient descent method. Once a structure is selected, coefficients in consequent part are determined by the least square method. Simulated result illustrates the effectiveness of the proposed technique.

• The Korean Journal of Applied Statistics
• /
• v.31 no.4
• /
• pp.463-473
• /
• 2018

Variable selection algorithms for linear regression models of large data are considered. Many algorithms are proposed focusing on the speed and the robustness of algorithms. Among them variance inflation factor (VIF) regression is fast and accurate due to the use of a streamwise regression approach. But a VIF regression is susceptible to outliers because it estimates a model by a least-square method. A robust criterion using a weighted estimator has been proposed for the robustness of algorithm; in addition, a robust VIF regression has also been proposed for the same purpose. In this article a fast and robust variable selection method is suggested via a VIF regression with detecting and removing potential outliers. A simulation study and an analysis of a dataset are conducted to compare the suggested method with other methods.

• Nuclear Engineering and Technology
• /
• v.54 no.3
• /
• pp.940-947
• /
• 2022

Meta-heuristic algorithms have found their place in optimization problems. Henry gas solubility optimization (HGSO) is one of the newest population-based algorithms. This algorithm is inspired by Henry's law of physics. To evaluate the performance of a new algorithm, it must be used in various problems. On the other hand, the optimization of the proportional-integral-derivative (PID) gains for load-following of a nuclear power plant (NPP) is a good challenge to assess the performance of HGSO. Accordingly, the power control of a pressurized water reactor (PWR) is targeted, based on the point kinetics model with six groups of delayed-neutron precursors. In any optimization problem based on meta-heuristic algorithms, an efficient objective function is required. Therefore, the integral of the time-weighted square error (ITSE) performance index is utilized as the objective (cost) function of HGSO, which is constrained by a stability criterion in steady-state operations. A Lyapunov approach guarantees this stability. The results show that this method provides superior results compared to an empirically tuned PID controller with the least error. It also achieves good accuracy compared to an established GA-tuned PID controller.

• Health Policy and Management
• /
• v.30 no.1
• /
• pp.26-36
• /
• 2020

Background: The purpose of this study was to analyze the relationship between the regional characteristics and the age-adjusted cardio-cerebrovascular disease mortality rates (SCDMR) in 229 si·gun·gu administrative regions. Methods: SCDMR of man and woman was used as a dependent variable using the statistical data of death cause in 2017. As a representative index of regional characteristics, health behavior factors, socio-demographic and economic factors, physical environment factors, and health care factors were selected as independent variables. Ordinary least square (OLS) regression and geographically weighted regression (GWR) were performed to identify their relationship. Results: OLS analysis showed significant factors affecting the mortality rates of cardio-cerebrovascular disease as follows: high-risk drinking rates, the ratio of elderly living alone, financial independence, and walking practice rates. GWR analysis showed that the regression coefficients were varied by regions and the influence directions of the independent variables on the dependent variable were mixed. GWR showed higher adjusted R² and Akaike information criterion values than those of OLS. Conclusion: If there is a spatial heterogeneity problem as Korea, it is appropriate to use the GWR model to estimate the influence of regional characteristics. Therefore, results using the GWR model suggest that it needs to establish customized health policies and projects for each region considering the socio-economic characteristics of each region.