• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1825-1833
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• 1990

This paper proposes an efficient algorithm that constructs 3-dimensional solid object from 3 orthogonal views. This algorithm inputs vertex and edge information of 3 orthogonal views and generates 2 dimensional surfaces, 3 dimensional vertices, edges and surfaces and then compares 2 dimensional projections of 3 dimensional surfaces with surfaces from othorgonal views. This algorithm is useful for CAD system, 3 dimensional scene analysis system and object modeling for real-time animation and has been implemented in C language on IRIS workstation. The effectiveness of this algorithm is shown by examples of aircrafts' models.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.31-39
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• 2015

This paper deals with a method for estimating variance components on the basis of projections under the assumption of random effects model. It discusses how to use projections for getting sums of squares to estimate variance components. The use of projections makes the vector subspace generated by the model matrix to be decomposed into subspaces that are orthogonal each other. To partition the vector space by the model matrix stepwise procedure is used. It is shown that the suggested method is useful for obtaining Type I sum of squares requisite for the ANOVA method.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.423-429
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• 2014

This paper discusses a method for getting Type I sums of squares by projections under a two-way fixed-effects model when variances of errors are not equal. The method of weighted least squares is used to estimate the parameters of the assumed model. The model is fitted to the data in a sequential manner by using the model comparison technique. The vector space generated by the model matrix can be composed of orthogonal vector subspaces spanned by submatrices consisting of column vectors related to the parameters. It is discussed how to get the Type I sums of squares by using the projections into the orthogonal vector subspaces.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1207-1214
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• 2008

We give an elementary proof of one of the main results in [H.O. Kim, R.Y. Kim, J.K. Lim, The infimum cosine angle between two finitely generated shift-invariant spaces and its applications, Appl. Comput. Har-mon. Anal. 19 (2005) 253-281] concerning the existence of an oblique projection onto a finitely generated shift-invariant space along the orthogonal complement of another finitely generated shift-invariant space under the assumption that the generators generate Riesz bases.

• The Pure and Applied Mathematics
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• v.10 no.1
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• pp.49-56
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• 2003

For (equation omitted) be an ordered $\ell$(t)-tuple of numbers in｛1,2, …,$\ell$｝and let Tt be chosen from a finite composition of orthogonal projections (equation omitted) acting on the normed linear space $C_1$(X) to closed convex subset $S(fi_{j}\;^{t})$ respectively. In this paper, we study the convergence of the sequence (equation omitted) where (equation omitted).

• Communications of the Korean Mathematical Society
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• v.19 no.4
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• pp.691-700
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• 2004

Let X and Y be operators acting on a Hilbert space and let (equation omitted) be a subspace lattice of orthogonal projections on the space containing 0 and I. We investigate normal interpolation problems in Alg(equation omitted): Given operators X and Y acting on a Hilbert space, when does there exist a normal operator A in Alg(equation omitted) such that AX = Y?

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.69-72
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• 1991

This paper proposes an efficient algorithm that constructs 3 dimensional solid object from orthographic views. The 3D object construction algorithm inputs vertices and edges information of 3 orthogonal views, generates 2 dimensional surfaces of input views, 3 dimensional possible vertices, possible edges and possible surfaces, compares 2 dimensional projections of 3 dimensional possible surface with two dimensional surfaces from orthogonal views and then determines the solution. This algorithm has been proved to be efficient in reducing the time taken and is useful for CAD system, 3 dimensional scene analysis system and object modellings for 3D graphics. The algorithm has been implemented in C language on the IBM PC/AT.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.347-354
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• 2015

This paper deals with a method for intrablock anlaysis of balanced incomplete block designs on the basis of projections under the assumption of mixed effects model. It shows how to construct a model at each step by the stepwise procedure and discusses how to use projection for the analysis of intrablock. Projections are obtained in vector subspaces orthogonal to each other. So the estimates of the treatment effects are not affected by the block effects. The estimability of a parameter or a function of parameters is discussed and eigenvectors are dealt for the construction of estimable functions.

• ETRI Journal
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• v.43 no.1
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• pp.7-16
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• 2021

Noncontiguous orthogonal frequency division multiplexing (NC-OFDM)-based cognitive radio (CR) systems achieve highly efficient spectrum utilization by transmitting unlicensed users' data on subcarriers of licensed users' data when they are free. However, there are two disadvantages to the NC-OFDM system: out-of-band power (OBP) and a high peak-to-average power ratio (PAPR). OBP arises due to side lobes of an NC-OFDM signal in the frequency domain, and it interferes with the spectrum for unlicensed users. A high PAPR occurs due to the inverse fast Fourier transform (IFFT) block used in an NC-OFDM system, and it induces nonlinear effects in power amplifiers. In this study, we propose an algorithm called "Alternative Projections onto Convex and Non-Convex Sets" that reduces the OBP and PAPR simultaneously. The alternate projections are performed onto these sets to form an iteration, and it converges to the specified limits of in-band-power, peak amplitude, and OBP. Furthermore, simulations show that the bit error rate performance is not degraded while reducing OBP and PAPR.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.77-84
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• 2022

In this paper, we propose a novel unsupervised feature selection method. Conventional unsupervised feature selection method defines virtual label and uses a regression analysis that projects the given data to this label. However, since virtual labels are generated from data, they can be formed similarly in the space. Thus, in the conventional method, the features can be selected in only restricted space. To solve this problem, in this paper, features are selected using orthogonal projections and low-rank approximations. To solve this problem, in this paper, a virtual label is projected to orthogonal space and the given data set is also projected to this space. Through this process, effective features can be selected. In addition, projection matrix is restricted low-rank to allow more effective features to be selected in low-dimensional space. To achieve these objectives, a cost function is designed and an efficient optimization method is proposed. Experimental results for six data sets demonstrate that the proposed method outperforms existing conventional unsupervised feature selection methods in most cases.