• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.1019-1031
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• 2004

This paper describes a new modeling method for the prediction of transmembrane protein topology. The structural regions of the transmembrane protein have been modeled by means of a multiple state hidden Markov model that has provided for the detailed modeling of the heterogeneous amino acid distributions of each structural region. Grammatical constraints have been incorporated to the prediction method in order to capture the biological order of membrane protein topology. The proposed method correctly predicted 76% of all membrane spanning regions and 92% sidedness of the integration when all membrane spanning regions were found correctly.

• Journal of the Korean Data and Information Science Society
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• 제16권3호
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• pp.683-693
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• 2005

This paper presents a new transmembrane Protein topology prediction method which is an attempt to model the topological rules governing the topogenesis of transmembrane proteins. Context-dependent structural regions of the transmembrane protein are used as basic modeling units in order to effectively represent their topogenic roles during transmembrane protein assembly. These modeling units are modeled by means of a tied-state hidden Markov model, which can express the position-specific effect of amino acids during ransmembrane protein assembly. The performance of prediction improves with these modeling approaches. In particular, marked improvement of orientation prediction shows the validity of the proposed modeling. The proposed method is available at http://bioroutine.com/TRAPTOP.

• 한국통신학회논문지
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• 제27권8C호
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• pp.729-740
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• 2002

본 논문에서는 광 인터넷 망의 가상망 재구성을 위하여 최적의 망 재구성 정책을 고려한 보상-비용 함수를 최대화하는 다단계 결정 문제로 정의 하였다. 그리고 트래픽 요구사항을 만족하기 위해서 노드 교환 기법에 근거한 새로운 휴리스틱 알고리즘을 제안하였다. 또한 트래픽 예측 기법을 사용하여 휴리스틱 알고리즘에 의해 발생하는 근사 문제를 해결 하고, 이를 바탕으로 트래픽 예측 다단계 재구성 정책을 제안하였다. 실험결과 다단계 재구성 정책은 물리적 자원이 제한된 환경에서 기존의 방법에 비해 뛰어난 성능을 보였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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• pp.3-10
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• 1998

Optimization problems may be devided into geometry optimization problems and topology optimization problems. In this paper, a method using tile equivalent material properties prediction techniques of a particulate-reinforced composites is proposed for the topology optimization. This method makes use of penalty factor in order that regions with intermediate value of design variables can be penalized. The computational results being obtained from PLBA algorithm of some values of penalty factor are presented.

• 한국정보과학회논문지:정보통신
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• 제30권1호
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• pp.1-8
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• 2003

본 논문에서는 광 인터넷의 가상 토폴로지 재구성을 효과적으로 관리하는 정책을 제시한다. 기존의 휴리스틱 기법의 근사 문제를 해결하기 위해 트래픽 예측 기반 다단계 재구성 알고리즘을 바탕으로 트래픽 패턴과 망 혼잡 정도의 변화에 따라 적응적인 토폴로지 재구성 기법을 제시한다. 이 알고리즘은 네트워크의 상태를 고려하여 적정 재구성 시기를 결정함으로써 가상망의 관리를 단순화한다. 시뮬레이션 결과, 제안된 가상망 관리 정책이 물리적인 자원 사용이 제한될 때 기존의 방법에 비해 좋은 성능을 보인다.

• BMB Reports
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• 제42권11호
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• pp.697-704
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• 2009

Membrane proteins play important roles in the biology of the cell, including intercellular communication and molecular transport. Their well-established importance notwithstanding, the high-resolution structures of membrane proteins remain elusive due to difficulties in protein expression, purification and crystallization. Thus, accurate prediction of membrane protein topology can increase the understanding of membrane protein function. Here, we provide a brief review of the diverse computational methods for predicting membrane protein structure and function, including recent progress and essential bioinformatics tools. Our hope is that this review will be instructive to users studying membrane protein biology in their choice of appropriate bioinformatics methods.

• Journal of Information Technology Applications and Management
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• 제11권2호
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• pp.205-214
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• 2004

Internet evolves into the huge network with new nodes inserted or deleted depending on specific situations. A new model of network topology is needed in order to analyze time-varying Internet more realistically and effectively. In this study the non-monotony models are proposed which can describe topological changes of Internet such as node insertion and deletion, and can be used for predicting its future topology. Simulation is performed to analyze the topology generated by our model. Simulation results show that our proposed model conform the power law of realistic Internet better than conventional ones. The non-monotony model can be utilized for designing Internet protocols and networks with better security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.1909-1928
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• 2020

Predicting human mobility has always been an important task in Location-based Social Network. Previous efforts fail to capture spatial dependence effectively, mainly reflected in weakening the location topology information. In this paper, we propose a neural network-based method which can capture spatial-temporal dependence to predict the next location of a person. Specifically, we involve a graph convolutional network (GCN) based on a seq2seq framework to capture the location topology information and temporal dependence, respectively. The encoder of the seq2seq framework first generates the hidden state and cell state of the historical trajectories. The GCN is then used to generate graph embeddings of the location topology graph. Finally, we predict future trajectories by aggregated temporal dependence and graph embeddings in the decoder. For evaluation, we leverage two real-world datasets, Foursquare and Gowalla. The experimental results demonstrate that our model has a better performance than the compared models.

• 천문학회보
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• 제39권2호
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• pp.43.2-43.2
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• 2014

We present the three-dimensional genus topology of large-scale structure using the CMASS sample of the Final SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) data. To estimate the uncertainties in the measured genus, we very carefully construct mock CMASS surveys along the past light cone from the Horizon Run 3. We find that the shape of the observed genus curve agrees very well with the prediction of perturbation theory and with the mean topology of the mock surveys. However, comparison with simulations show that the observed genus curve slightly deviates from the theoretical Gaussian expectation. From the deviation, we further quantify the primordial non-Gaussian contribution.

• 전산구조공학
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• 제11권4호
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• pp.267-274
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• 1998

본 연구에서는 기지개와 미시구멍으로 구성된 복합재료에 입자보강 복합재료의 등가 재료상수 예측기법인 평균장 근사이론과 등가원리를 적용하여 위상 최적화에 필요한 등가 재료상수와 설계변수와의 상관관계식을 유도하였다. 또한, 유도된 관계식에 중간값을 갖는 설계변수의 수를 줄이기 위하여 벌칙인자를 도입하였다. 그리고 본 연구의 타당성을 검증하기 위하여 벌칙인자가 도입된 위상 최적화문제를 순차이차계획법인 PLBA 알고리즘을 이용하여 해석하였다.