• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2001년도 추계학술대회 논문집
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• pp.113-116
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• 2001

Finite element analysis programs have been for metal forming process design They will become more and more important in understanding forming process For large-scale forging analysis problems, the performance of a linear equation solver is very important for the overall efficiency of the analysis code. With problem size increased, the computation time needs to be reduced, which is spent on setting the system of algebraic equations associated with finite element model Many matrix solvers have been developed and used usefully in finite element program for this purpose.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2019년도 추계학술대회
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• pp.246-248
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• 2019

In the ongoing standardization of Versatile Video Coding (VVC), DCT-2, DST-7 and DCT-8 are accounted as the vital transform kernels. While storing all of those transform kernels, ROM memory storage is considered as the major problem. So, to deal with this scenario, a common sparse unified matrix concept is introduced in this paper. From the proposed matrix, any point transform kernels (DCT-2, DST-7, DCT-8, DST-4 and DCT-4) can be achieved after some mathematical computation. DCT-2, DST-7 and DCT-8 are the used major transform kernel in this paper.

• 경영과학
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• 제15권1호
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• pp.49-62
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• 1998

The purpose of this paper is to develope a large-scale simplex method program LPAKO. Various up-to-date techniques are argued and implemented. In LPAKO, basis matrices are stored in a LU factorized form, and Reid's method is used to update LU maintaining high sparsity and numerical stability, and further Markowitz's ordering is used in factorizing a basis matrix into a sparse LU form. As the data structures of basis matrix, Gustavson's data structure and row-column linked list structure are considered. The various criteria for reinversion are also discussed. The dynamic steepest-edge simplex algorithm is used for selection of an entering variable, and a new variation of the MINOS' perturbation technique is suggested for the resolution of degeneracy. Many preprocessing and scaling techniques are implemented. In addition, a new, effective initial basis construction method are suggested, and the criteria for optimality and infeasibility are suggested respectively. Finally, LPAKO is compared with MINOS by test results.

• Industrial Engineering and Management Systems
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• 제13권4호
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• pp.421-431
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• 2014

The market basket data in the form of a binary user-item matrix or a binary item-user matrix can be modelled as a binary classification problem. The binary logistic regression approach tackles the binary classification problem, where principal components are predictor variables. If users or items are sparse in the training data, the binary classification problem can be considered as a cold-start problem. The binary logistic regression approach may not function appropriately if the principal components are inefficient for the cold-start problem. Assuming that the market basket data can also be considered as a special regression problem whose response is either 0 or 1, we propose three supervised learning approaches: random forest regression, random forest classification, and elastic net to tackle the cold-start problem, comparing the performance in a variety of experimental settings. The experimental results show that the proposed supervised learning approaches outperform the conventional approaches.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권7호
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• pp.399-406
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• 2000

We propose an nonlinear demodulation algorithm for undersampled multicomponent AM(Amplitude Modulation), FM(Frequency Modulation) and AM-FM signals. First, we derive respectively undersampling frequency of the AM, FM and AM-FM using undersampling scheme, and separate respectively monocomponent signals from multicomponent signals using periodic algebraic separation algorithm. In this case augmented separation matrix is very regular and sparse, it has a special structure. The proposed demodulation algorithm detects respectively message signals of the IA(Instantaneous Amplitude) and IF(Instantaneous Frequency) from descrete monocomponent AM, FM and AM-FM signals with an undersampling frequency to be controllable. Verifying the RMS(Root Mean Squares) errors of the detected signals, we show that the performance is excellent.

• 전기학회논문지P
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• 제51권2호
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• pp.55-59
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• 2002

Parallel processing is able to be used effectively on computationally intense power system problems. But this technology is not still available is not only parallel computer but also parallel processing scheme. Testing these algorithms to ensure accuracy, and evaluation of their performance is also an issue. Although a significant amount of parallel algorithms of power system problem have been developed in last decade, actual testing on parallel computer architectures lies in the beginning stages because no clear cut paths. This paper presents Jacobian modeling method to supply the base being able to treat power flow by newton's method by the computer. This method is to assign and to compute teared blocks of sparse matrix at each parallel processors. The testing to insure accuracy of developed method have been done on serial computer by trying to simulate a parallel environment.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2017년도 추계학술대회
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• pp.202-203
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• 2017

비음수 행렬 인수분해(Non-negative Matrix Factorization, NMF)의 신호분리 성능을 개선하기 위해 희소조건을 인가한 방법이 희소 비음수 행렬 인수분해 알고리즘(Sparse NMF, SNMF)이다. 기존의 SNMF 알고리즘은 개별 음원의 희소성을 고려하지 않고 임의로 결정한 희소 조건을 사용한다. 본 논문에서는 음원의 특성에 따른 희소성을 추정하고 이를 SNMF 학습알고리즘에 적용하는 새로운 신호분리 기법을 제안한다. 혼합 신호에서의 잡음제거 실험을 통해, 제안한 방법이 기존의 NMF와 SNMF에 비해 성능이 더 우수함을 보였다.

• Wind and Structures
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• 제11권3호
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• pp.241-256
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• 2008

This paper adopts autoregressive (AR) model to simulate the wind velocity of spatial three-dimensional fields in accordance with the time and space dependent characteristics of the 3-D fields. Based on the built MATLAB programming, this paper discusses in detail the issues of the AR model deduced by matrix form in the simulation and proposes the corresponding solving methods: the over-relaxation iteration to solve the large sparse matrix equations produced by large number of degrees of freedom of structures; the improved Gauss formula to calculate the numerical integral equations which integral functions contain oscillating functions; the mixed congruence and central limit theorem of Lindberg-Levy to generate random numbers. This paper also develops a method of ascertaining the rank of the AR model. The numerical examples show that all those methods are stable and reliable, which can be used to simulate the wind velocity of all large span structures in civil engineering.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 학술대회 논문집 전문대학교육위원
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• pp.134-140
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• 2001

Parallel processing has the potential to be cost effectively used on computationally intense power system problems. But this technology is not still available is not only parallel computer but also parallel processing scheme. Testing these algorithms to ensure accuracy, and evaluation of their performance is also an issue. Although a significant amount of parallel algorithms of power system problem have been developed in last decade, actual testing on processor architectures lies in the beginning stages. This paper presents the parallel processing algorithm to supply the base being able to treat power flow by newton's method by the distributed memory type parallel computer. This method is to assign and to compute teared blocks of sparse matrix at each parallel processors. The testing to insure accuracy of developed method have been done on serial computer by trying to simulate a parallel environment.

• 물과 미래
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• 제29권1호
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• pp.141-150
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• 1996

상수관망에서의 압력과 유량의 정상상태 해석은 수공학에 있어서 매우 중요한 문제이다. 이 경우의 기본방정식은 유량을 미지값으로 하는 연속 방정식과 에너지 방정식으로 구성되는 비선형 연립방정식이다. 이 연립방정식을 풀기 위하여 선형화 기법을 도입하여 반복적으로 해석하였고 그 결과로 나타나는 선형 연립방정식의 효율적인 해석을 위해서 frontal기법을 사용하여 계산하였다. 이 기법은 계수 메트릭스의 '0'이 아닌 요소만을 모아 계산하므로 효과적으로 분산 메트릭스를 해석할 수 있었고, 기존의 band 해석기법보다 적은 앙의 계산 기억용량으로 계산시간을 크게 단축시켜 해석할 수 있었다. 본 연구에서 제시한 상수관망의 해석모형은 기존의 해석방법보다 정확하고 효율적인 계산기법으로서 제시하였다.