• Korea journal of population studies
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• v.12 no.2
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• pp.56-68
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• 1989

The methodology in historical demography comprises the three core areas the family reconstitution method at the Institut National d' Ftudes Demographiques(I.N.E.D), the back projection at the Cambridge Group for the History of PopuJation and Social Struc-ture(HPSS). and the household-pattern analysis at the Cambridge Group and at the California Institute of Technology. The paper presents an outline of the family reconstitu-tion method and discusses the problems, both theoretical and methodological, arising from the problematic back projection vis-a-vis the usual inverse projection developed by Ronald D. Lee at Berkeley. Recent developments in the tield of the generalized inverse projection method designed 10 supplement the defects in the back projection and the inverse projection are presented. and for ease of explanation of the parish register data for the family reconstitution form (FRE). pre-modern Korean household register data are presented along with the parish register data of England and Wales that constitute the backbone of historical demography in pre-modern Europe. Possibilities of exploring the household pattern analysis method based on the Laslett-Hammel classification scheme for the mid-eighteenth-century Korean household register data are suggested.

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.205-215
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• 2021

Sufficient dimension reduction is useful dimension reduction tool in regression, and sliced inverse regression (Li, 1991) is one of the most popular sufficient dimension reduction methodologies. In spite of its popularity, it is known to be sensitive to the number of slices. To overcome this shortcoming, the so-called fused sliced inverse regression is proposed by Cook and Zhang (2014). Unfortunately, the two existing methods do not have the direction application to large p-small n regression, in which the dimension reduction is desperately needed. In this paper, we newly propose seeded sliced inverse regression and seeded fused sliced inverse regression to overcome this deficit by adopting iterative projection approach (Cook et al., 2007). Numerical studies are presented to study their asymptotic estimation behaviors, and real data analysis confirms their practical usefulness in high-dimensional data analysis.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.29-36
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• 2004

In this paper, a study of damage detection for 2-Dimensional Truss Structures using the parametric projection filter theory is presented. Many researchers are interested in inverse problem and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In filtering algorithm, the Kalman filtering algorithm is well known and have been applied to many kind of inverse problems. In this paper, the Parametric projection filtering in conjunction with structural analysis is applied to the identification of damages in 2-D truss structures. The natural frequency and modes of damaged truss model are adopted as the measurement data. The effectiveness of proposed method is verified through the numerical examples.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.4
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• pp.195-201
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• 2005

In this paper, a study of damage measures for truss structures using the Extended Projection filter theory is presented. Many researchers are interested in inverse problems and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In this paper, the projection filtering in conjunction with structural analysis is applied to the identification of damages in truss structures. And, the effectiveness of proposed method is verified through the numerical examples of a free vibrating structure.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.73-80
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• 2004

In this paper, a study of damage detection for 2-Dimensional Truss Structures using the parametric projection filter theorr is presented. Many researchers are interested in inverse problem and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In filtering algorithm, the Kalman filtering algorithm is well known and have been applied to many kind of inverse problems. In this paper, the Parametric projection filtering in conjunction with structural analysis is applied to the identification of damages in 2-D truss structures. The natural frequency and modes of damaged truss model are adopted as the measurement data. The effectiveness of proposed method is verified through the numerical examples.

• Bulletin of the Korean Mathematical Society
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• v.46 no.5
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• pp.885-894
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• 2009

In this paper, we consider a hybrid projection algorithm for a pair of inverse-strongly monotone mappings and a quasi-$\phi4-nonexpansive mapping. Strong convergence theorems are established in the framework of Banach spaces.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.9
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• pp.550-556
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• 2003

Price-based unit commitment is one of bidding strategies which a Genco may take in a practical manner. For that purpose, it is required for a Genco to decide output levels of its generators at each trade period. In this paper, an economic dispatch of thermal units is proposed considering the quantity of reserve contracts. A gradient projection algorithm is adopted as an optimization tool. A direct form of a projection matrix without any calculation of matrix inverse and multiplications is induced. Besides, it is proved that there is no need to check one of the two optimality conditions in the gradient projection method, which also requires matrix inverse and multiplications.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.1
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• pp.170-176
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• 1998

In this paper, the column space and null space of the Jacobian matrix were obtained by using the pseudo-inverse method and projection matrix. The equations of motion of the system were replaced by independent acceleration components using the null space matrix. The proposed method has the following advantages. (1) It is simple to derive the null space. (2) The efficiency is improved by getting rid of constrained force terms. (3) Neither null space updating nor coordinate partitioning method is required. The suggested algorithm is applied to a three-dimensional vehicle model to show the efficiency.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.396-401
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• 2003

Electrical impedance tomography(EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents and measured voltages on the surface of the object. In this paper, an effective dynamic EIT imaging scheme is presented based on the projection filtering to estimate the unknown resistivity distribution. In particular, pre-integration (pre-grouping) technique is employed to stabilize the inverse algorithm. We carried out computer simulations with synthetic data to illustrate the reconstruction performance of the proposed algorithm.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.73-86
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• 2007

The general stereographic projection which maps a point on a sphere with arbitrary radius to a point on a plane stereographically and its inverse projection have the pythagorean-hodograph (PH) preserving property in the sense that they map a PH curve to another PH curve. Upon this fact, for given spatial $C^1$ Hermite data, we construct a spatial PH curve on a sphere that is a $C^1$ Hermite interpolant of the given data as follows: First, we solve $C^1$ Hermite interpolation problem for the stereographically projected planar data of the given data in $\mathbb{R}^3$ with planar PH curves expressed in the complex representation. Second, we construct spherical PH curves which are interpolants for the given data in $\mathbb{R}^3$ using the inverse general stereographic projection.