• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.481-484
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• 2005

Inherent opportunities on research for restoring high resolution image from low resolution images are increasing in these days. Super resolution image reconstruction is the process of combining multiple low resolution images to form a higher resolution one. To achieve super resolution reconstruction, proper observation model which is based on subpixel shift information is required. In this context, the importance of the subpixel registration cannot be estimated because subpixel shift information cannot be obtained from original image. This paper presents a regularized adaptive super resolution reconstruction method based on phase correlated subpixel registration, where the Constrained Least Squares(CLS) Restoration is adopted as a post process.

• Microbiology and Biotechnology Letters
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• v.21 no.6
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• pp.615-621
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• 1993

In order to maximize the riboflavin production by a mutant strain Ashbya gosspyii, the optimization of medium and fed-batch fermentation were performed. As carbon sources, glucose and soybean oil were necessary for the riboflavin overproduction. Optimal concentrations of glucose and soybean oil in the flask cultures were found to be 3.0% and 0.5%, respectively, in a complex medium containing corn steep liquor(CLS) 1%. Among the various organic nitrogen sources tested, CSL was the most effective one both for the cell growth and riboflavin overproduction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.12
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• pp.3132-3143
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• 1996

In the evaluation of Broadband-ISDN, the main issue is to interconnect existing LANs and MANs to B-ISDN based on Asynchrous Transfer Mode. However, LANs provide connectionless services, whereas the ATM network provides connection-oriented services. So some problem arises from accessing ATM switchs to transparently transmit connectionless data via B-ISDN. Two methods then were recommended by ITU-TS to support the connectionaless services. In the paper, we do the numerical analysis, using the stochastic fluid flow method, of dynamic bandwidth allocation sheme with two class traffics in the virtual path established between Interworking Units(JWUS) interconnecting LANs to an ATM network and Connectionless Servers(CLSs). The loss mechanism of each traffic is controlled by the contents of buffer. The vandwidth which the IWU requests the CLS is estimated by the number of On-Off sources in the On state. We use the stochsastic fluide flow method which is to find the steady-state joint probability in each level of the IWU buffer. The length of the IWU buffer as the real random variable is changed by traffics entering the IWU.

• Journal of Ginseng Research
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• v.15 no.1
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• pp.1-5
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• 1991

For the quality control of crude drug drink preparations, methods for identification of cinnamon components and quantitative determination of cinnamic acid were established. Cinnamon components were identified by TLC with benzene/ethyl acetate (1:1, v/v) on silica gel plate by spraying p-anisaldehyde-sulfuric acid. Cinnamic acid contents were determined at UV 280 nm by HPLC on $\mu$-Bondapak Cls column with acetonitrile/water/acetic acid (40:60:2, v/v). Recoveries of cinnamic acid in three crude drug drink preparations were between 84.1-90.2% compared to the content of the cinnamon extract.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.271-276
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• 2000

본 논문은 칼라 성분들간의 차분 영상과 휘도 영상을 이용하여 산출한 색차 휘도합 영상을 대상으로 블록에 기반한 영상 분할을 수행하여 객체의 형상 정보를 추출함으로써 분할 특성을 개선한 블록 기반 칼라 영상 분할 기법에 관한 것이다. 우선, R, G, B 영상들 간의 차분 성분들을 구하여 합산한 후, 이를 정규화하여 색차합 영상을 구한다. 다음으로 화소 단위로 휘도 영상의 상위 2비트와 정하화된 색차합 영상의 하위 6비트를 결합하여 색차 휘도합 영상을 얻는다. 이후, 기설정된 크기의 블록으로 분할된 색차 휘도합 영상의 각 블록을 질감 블록과 단순 블록 및 에지 블록으로 분류하고 각 유형의 블록별로 병합한 후, 기설정된 마커 배정 규칙에 따라 선택적으로 마커를 부여한다. 마지막으로, 마커가 부여되지 않은 블록을 대상으로 화소 단위의 워터쉐드 알고리즘을 적용함으로써 자연스러운 형상 정보를 얻을 수 있다. 컴퓨터 시뮬레이션 결과를 통해 고찰할 때, 제안된 방범은 질감 영역에서의 과분할의 문제와 과도한 연산량의 부담을 효과적으로 경감시킬 수 있으나, 더불어, 영상 분할용 파라미터들의 민감도가 낮아 서로 다른 화소 분포 특성온 갖는 영상들에 전역적인 파라미터들사용할 수 있을 뿐만 아니라 특히, 색차 휘도합 영상에 반영된 색차 성분에 힘입어 저대조 경계면에서의 분할 특성을 현저히 개선시킬 수 있는 이점이 있다.

• Journal of Embryo Transfer
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• v.27 no.4
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• pp.205-209
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• 2012

Transgenic rats and mice are useful experimental animal models for medical research including human disease model studies. Somatic cell nuclear transfer (SCNT) technology is successfully applied in most mammalian species including cattle, sheep, pig and mouse. SCNT is also considered to increase the efficacy of transgenic/knockout mouse and rat production. However, in the area of reproductive biotechnology, the rodent model is inadequate because of technical obstacles in manipulating the oocytes including intracytoplasmic sperm injection and SCNT. In particular, success of rat SCNT is very limited so far. In this review, the history of rodent cloning is described.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.51-61
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• 1999

A cell scheduling method of Queue for the ATM switch is proposed and simulated. In this paper, we present the cell scheduling method proper to the proposed queue and the improved queue with Queue Sharing(QS) structure for CBR, VBR, ABR traffic. The proposed QS structure minimizes the CLS(Cell Loss Ratio) of ABR traffic and decreases the CLR of bursty VBR traffic. Also we propose a cell scheduling method using VRR(Variable Round Robin) scheme proper to the high-speed(ATM) switch. The VRR scheme provides a fairness in terms of service chance for the queues in the ATM switch as well as QOS of their cell delay characteristic of CBR and VBR traffic, QOS of ABR CLR. The simulation results show the proposed method achieves excellent CLR and average cell delay performance for the various ATM traffic services in the Queue Sharing structure.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.415-424
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• 2005

The rapid growth of blog has caused information overload where bloggers in the virtual community space are no longer able to effectively choose the blogs they are exposed to. Recommender systems have been widely advocated as a way of coping with the problem of information overload in e-business environment. Collaborative Filtering (CF) is the most successful recommendation method to date and used in many of the recommender systems. Therefore, we propose a CF-based recommender system for bloggers in the virtual community space. Our proposed methodology consists of three main phases: In the first phase, we apply the "Interest Value" to a recommender system. The Interest Value is a quantity value about user preference in virtual community, and can measure the opinion of users accurately. Next phase, we generate the neighborhood group based on the Interest Value. In the final phase, we use the Community Likeness Score (CLS) to generate the top-n recommendation list. The methodology is explained step by step with an illustrative example and is verified with real data of a blog service provider.

• Bulletin of the Korean Mathematical Society
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• v.59 no.2
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• pp.453-468
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• 2022

In this article, we define a module M to be G^z-extending if and only if for each z-closed submodule X of M there exists a direct summand D of M such that X ∩ D is essential in both X and D. We investigate structural properties of G^z-extending modules and locate the implications between the other extending properties. We deal with decomposition theory as well as ring and module extensions for G^z-extending modules. We obtain that if a ring is right G^z-extending, then so is its essential overring. Also it is shown that the G^z-extending property is inherited by its rational hull. Furthermore it is provided some applications including matrix rings over a right G^z-extending ring.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.124-127
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• 2020

관계 추출은 문장에서 두 개의 엔티티가 주어졌을 때 두 개의 엔티티에 대한 의미적 이해를 통해 관계를 분류하는 작업이다. 이와 같이 관계 추출에서 관계를 분류하기 위해서는 두 개의 엔티티에 대한 정보가 필요하다. 본 연구에서는 관계 추출을 하기 위해 문장에서 엔티티들의 표현을 다르게하여 관계 추출의 성능을 비교 실험하였다. 첫번째로는 문장에서 [CLS] 토큰(Token)으로 관계를 분류하는 Standard 엔티티 정보 표현과 두번째로는 엔티티의 앞과 뒤에 Special Token을 추가하여 관계를 분류하는 Entity-Markers 엔티티 정보 표현했다. 이를 기반으로 문장의 문맥 정보를 학습한 사전 학습(Pre-trained)모델인 BERT-Large와 ALBERT-Large를 적용하여 실험을 진행하였다. 실험 결과 Special Token을 추가한 Entity-Markers의 성능이 높았으며, BERT-Large에서 더 높은 성능 결과를 확인하였다.