• Journal of the Korean Society of Industry Convergence
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• v.3 no.1
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• pp.17-27
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• 2000

A factorization is an extremely important part of multi-level logic synthesis. The number of literals in a factored form is a good estimate of the complexity of a logic function. and can be translated directly into the number of transistors required for implementation. Factored forms are described as either algebraic or Boolean, according to the trade-off between run-time and optimization. A Boolean factored form contains fewer number of literals than an algebraic factored form. In this paper, we present a new method for a Boolean factorization. The key idea is to build an extended co-kernel cube matrix using co-kernel/kernel pairs and kernel/kernel pairs together. The extended co-kernel cube matrix makes it possible to yield a Boolean factored form. We also propose a heuristic method for covering of the extended co-kernel cube matrix. Experimental results on various benchmark circuits show the improvements in literal counts over the algebraic factorization based on Brayton's co-kernel cube matrix.

• Journal of Biomedical Engineering Research
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• v.27 no.6
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• pp.310-317
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• 2006

Extensive research with polarimetry and Mueller matrix has been done for chemical measurements and possible cancer detection. However, the effect of thermally denatured biological tissue on polarization changes is not well known. The purpose of this study is to characterize polarization changes in collagen due to thermal denaturation. The variations in polarized state caused by thermal damage were investigated by obtaining the Mueller matrix elements of collagen sample at multiple thermal damage levels. The changes in birefringence of denatured collagen were also investigated. This information could be used to determine the extent of thermal damage level of clinically heat treated tissues.

• Journal of Korea Foundry Society
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• v.2 no.2
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• pp.2-9
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• 1982

This paper is concerned with the improvement of impact and tensile Properties of spheroidal graphite cast iron of the following duplex matricess which were heat treated in the eutectic transformation temperature range (that is, $({\alpha}+{\gamma})$ coexisting range) ; ferrite-martensite, ferrite-bainite and ferrite-pearlite. The absorbed energy and maximum load was measured by recording the load-deflection curve with instrumented Charpy impact testing machine in the temperature range from $+100^{\circ}C$ to $-196^{\circ}C$. It was found the ferrite-bainite duplex matrix showed the highest toughness among the above matrices in the room temperature and the low temperature range. Comparison of this matrix to ferrite-pearlite matrix(that is, as cast) showed a lowering of $27^{\circ}C$ in the nil-ductility transition temperature (NDT) and a lowering of $40^{\circ}C$ in the ductile-brittle transition temperature (TrE), Which seems to result from the finner dimple pattern observed using miorofractography.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.10a
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• pp.27-30
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• 2004

Carbon nanotube reinforced alumina matrix nanocomposite was fabricated by sol-gel process and followed by spark plasma sintering process. Homogeneous distribution of carbon nanotubes within alumina matrix can be obtained by mixing the carbon nanotubes with alumina sol and followed by condensation into gel. The mixed gel, consisting of alumina and carbon nanotubes, was dried and calcinated into carbon nanotube/alumina composite powders. The composite powders were spark plasma sintered into carbon nanotube reinforced alumina matrix nanocomposite. The hardness of carbon nanotube reinforced alumina matrix nanocomposite was enhanced due to an enhanced load sharing of homogeneously distributed carbon nanotubes. At the same time, the fracture toughness of carbon nanotube reinforced alumina matrix nanocomposite was enhanced due to a bridging effect of carbon nanotubes during crack propagation.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1493-1499
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• 2009

Let $A_1$ and $A_2$ be nonzero complex idempotent and tripotent matrix, respectively. Denote a linear combination of the two matrices by A = $c_1A_1$ + $c_2A_2$, where $c_1,\;c_2$ are nonzero complex scalars. In this paper, under an assumption of $A_1A_2$ = $A_2A_1$, we characterize all situations in which the linear combination is tripotent. A statistical interpretation of this tripotent problem is also pointed out. Moreover, In [2], Baksalary characterized all situations in which the above linear combination is idem-potent by using the property of decomposition of a tripotent matrix, i.e. if $A_2$ is tripotent, then $A_2$ = $B_1-B_2$, where $B^2_i=B_i$, i = 1, 2 and $B_1B_2=B_2B_1=0$. While in this paper, by utilizing a method different from the one used by Baksalary in [2], we prove the theorem 1 in [2] again.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.923-932
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• 2014

The Hurdle model can to analyze zero-inflated count data. This model is a mixed model of the logit model for a binary component and a truncated Poisson model of a truncated count component. We propose a new hurdle model with a general heterogeneous random effects covariance matrix to analyze longitudinal zero-inflated count data using modified Cholesky decomposition. This decomposition factors the random effects covariance matrix into generalized autoregressive parameters and innovation variance. The parameters are modeled using (generalized) linear models and estimated with a Bayesian method. We use these methods to carefully analyze a real dataset.

• Structural Engineering and Mechanics
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• v.27 no.2
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• pp.135-148
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• 2007

A new finite shear wall element model and a method for calculation of 3D multi-storied only shear walled or shear walled - framed structures using finite shear wall elements assumed ideal elasto - plastic material are developed. The collapse load of the system subjected to factored constant gravity loads and proportionally increasing lateral loads is calculated with a method of load increments. The shape functions over the element are determined as a cubic variation along the story height and a linear variation in horizontal direction because of the rigid behavior of the floor slab. In case shear walls are chosen as only one element in every floor, correct solutions are obtained by using this developed element. Because of the rigid behavior of the floor slabs, the number of unknowns are reduced substantially. While in framed structures, classical plastic hinge hypothesis is used, in nodes of shear wall elements when vertical deformation parameter is exceeded ${\varepsilon}_e$, this node is accepted as a plastic node. While the system is calculated with matrix displacement method, for determination of collapse safety, plastic displacements and plastic deformations are taken as additional unknowns. Rows and columns are added to the system stiffness matrix for additional unknowns.

• Journal of IKEEE
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• v.27 no.1
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• pp.38-44
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• 2023

Performance of a STAP(space-time adaptive processing) algorithm highly depends on how closely the estimated covariance matrix(CM) resembles the actual CM by the interference in CUT(cell under test). A STAP has 2 dimensional data structure determined by the number of array elements and the number of transmitting pulses and both numbers are generally not small. Thus, to meet the degree of freedom(DOF) of the CM, a huge amount of training data is required. This paper presents an algorithm to generate virtual training data from small received data, via converting them into the data in spatial frequency-Doppler plane. We theoretically derive where the clutter exist in the plane and present the procedure to implement the proposed algorithm. Finally, with the simulated scenario of small received data, we show the proposed algorithm can improve STAP performance.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.129-140
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• 2020

In this paper, we introduce an efficient algorithm for the non-convex penalized multinomial logistic regression that can be uniformly applied to a class of non-convex penalties. The class includes most non-convex penalties such as the smoothly clipped absolute deviation, minimax concave and bridge penalties. The algorithm is developed based on the concave-convex procedure and modified local quadratic approximation algorithm. However, usual quadratic approximation may slow down computational speed since the dimension of the Hessian matrix depends on the number of categories of the output variable. For this issue, we use a uniform bound of the Hessian matrix in the quadratic approximation. The algorithm is available from the R package ncpen developed by the authors. Numerical studies via simulations and real data sets are provided for illustration.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.619-627
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• 2014

Distances or dissimilarities among units are assumed to be symmetric in most cases of multidimensional scaling(MDS); consequently, it is not an easy task to deal with asymmetric distances. Current asymmetric MDS still face difficulties in the interpretation of results. This study proposes a simpler asymmetric MDS that utilizes the order statistic of an asymmetric matrix. The proposed Web method demonstrates that some influences among objects are visualized by direction, size and shape of arrow to ease the interpretability of users.