• 한국측량학회지
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• 제25권5호
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• pp.375-381
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• 2007

본 논문에서는 3차원 점군, 3차원 벡터 또는 3차원 곡면에 영상등록하는 새로운 방법을 제안 하였다. 제안한 방법은 카메라 위치와 3차원 직선, 2차원 영상 직선을 각각 지나는 평면의 법선벡터의 일치화를 통하여 카메라 외부표정을 추정하는 것이다. 법선벡터 일치화의 조건은 각 법선벡터 쌍의 사잇각이 제로가 되는 것이다. 이 조건은 벡터내적인 수학식으로 표현 된다. 시뮬례이션을 통하여 제안한 방법이 영상등록을 위한 외부표정 추정을 강인하게 하는 것을 증명하였다.

• Nuclear Engineering and Technology
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• 제54권5호
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• pp.1825-1834
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• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• Journal of applied mathematics & informatics
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• 제34권1_2호
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• pp.95-106
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• 2016

In this paper, according to the classical LSQR algorithm forsolving least squares (LS) problem, an iterative method is proposed for finding the minimum-norm pure imaginary solution of the quaternionic least squares (QLS) problem. By means of real representation of quaternion matrix, the QLS's correspongding vector algorithm is rewrited back to the matrix-form algorthm without Kronecker product and long vectors. Finally, numerical examples are reported that show the favorable numerical properties of the method.

• 한국독성학회:학술대회논문집
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• 한국독성학회 2003년도 추계학술대회
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• pp.86-86
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• 2003

Gene therapy is a medical intervention based on modification of the genetic material of living cells. Gene transfer usually conducted using bacterial plasmid DNA and/or virus vector to express a specific protein. Gene transfer medicinal products classified as naked nucleic acid, complexed nucleic acid or non-viral vectors, viral vector, and genetically modified cells according to biological origin.(omitted)

• Kyungpook Mathematical Journal
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• 제46권1호
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• pp.89-96
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• 2006

For a rank-1 matrix A, there is a factorization as $A=ab^t$, the product of two vectors a and b. We characterize the linear operators that preserve rank and some equivalent condition of rank-1 matrices over a chain semiring. We also obtain a linear operator T preserves the rank of rank-1 matrices if and only if it is a form (P, Q, B)-operator with appropriate permutation matrices P and Q, and a matrix B with all nonzero entries.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.821-824
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• 1999

In distributed arithmetic-based architecture for an inner product between two length-N vectors, the size of the ROM increases exponentially with N. Moreover, the ROMs are generally the bottleneck of speed, especially when their sire is large. In this paper, a ROM size reduction technique for DA (Distributed Arithmetic) is proposed. The proposed method is based on modified OBC (Offset Binary Coding) and control circuit reduction technique. By simulations, it is shown that the use of the proposed technique can result in reduction in the number of gates up to 50%.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.310-312
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• 1993

We present the discrete event systems modeled by finite state machines in this paper using the boolean matrices and vectors. We propose a supervisor synthesis method for such boolean discrete-event systems. The proposed supervisor synthesis algorithm is practically implementable, since the size of the state vector in the product system does not increase exponentially with the number of components.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• BMB Reports
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• 제38권4호
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• pp.414-419
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• 2005

The production of recombinant antibodies has been generally recognized as time-consuming and labor-intensive. The aim of our study is to construct mammalian expression vectors containing the cDNA encoding the human constant regions and murine variable regions to massively and cost-effectively produce full-length chimeric antibodies. Unique restriction sites flanking the Ig variable region were designed to allow for the replacement of variable regions generated by PCR. Western blot analysis of the chimeric antibodies revealed that the expressed products were of the predicted size, structure and specificity. The usefulness of the vectors was confirmed by construction of human-mouse chimeric antibody-HCAb which secretes murine antibody against the human colorectal cancer. Selected in medium containing gradually increasing methotrexate (MTX), clones with increased expression of the product gene can be efficiently generated. The secretion of recombinant chimeric antibody-HCAb yielded $30\;pg\;cell^{-1}\;day^{-1}$ at $10^{-6}\;M$ MTX. With this high-level expression from pools, the convenient and rapid production of over 100 milligram amounts per liter of recombinant antibodies may be achieved, which indicates the significant roles of pYR-GCEVH and pYR-GCEVL in the production of chimeric antibodies.

• 한국정보과학회논문지:소프트웨어및응용
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• 제33권10호
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• pp.836-850
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• 2006

오늘날 급속한 패키지 소프트웨어 제품의 증가 추세에 따라서, 소프트웨어 제품에 대한 품질 시험 요구 또한 증가하였다. 소프트웨어 제품 시험 시 중요한 요소는 무엇을 시험할지 기준이 되는 메트릭의 선정이다. 본 연구에서는 패키지 소프트웨어 종류를 특성 벡터들로 표현하여 메트릭들과의 연관 관계를 확률로서 세밀하게 표현한다. 특성 벡터란 소프트웨어의 형식 분류 지시자라고 할 수 있으며 특정한 패키지 소프트웨어가 다른 것들과 어떻게 구별되는지 나타낼 수 있다. 분류된 각각의 소프트웨어 형식별로 메트릭을 선정하기 위해서 과거 시험 데이타를 분석하여 활용한다. 베이지언망이 과거 데이타 분석에 이용되며 특성 벡터와 메트릭 간의 의존 관계 네트워크를 구축한다. 구축된 베이지언망은 새로운 패키지 소프트웨어 시험 작업에 적절한 메트릭을 찾아내는데 활용된다.