• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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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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• v.16 no.3
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8C
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• pp.729-740
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• 2002

This paper studies the issues arising in the virtual topology reconfiguration phase of Multi-wavelength Routed Optical Networks. This reconfiguration process means to change the virtual topology in response to the changing traffic patterns in the higher layer. We formulate the optimal reconfiguration policy as a multi-stage decision-making problem to maximize the expected reward and cost function over an infinite horizon. Then we propose a new heuristic algorithm based on node-exchange to reconfigure the virtual topology to meet the traffic requirement. To counter the continual approximation problem brought by heuristic approach, we take the traffic prediction into consideration. We further propose a new heuristic reconfiguration algorithm called Prediction based Multi-stage Reconfiguration approach to realize the optimal reconfiguration policy based on predicted traffic. Simulation results show that our reconfiguration policy significantly outperforms the conventional one, while the required physical resources are limited.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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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.

• Journal of KIISE:Information Networking
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• v.30 no.1
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• pp.1-8
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• 2003

In this paper. we develop an analytical model to evaluate the virtual topology reconfiguration phase of optical Internet networks. To counter the continual approximation problem brought by traditional heuristic approach, we take the traffic prediction into consideration and propose a new heuristic reconfiguration algorithm called Prediction based Multi-stage Reconfiguration approach. We then use this analytical model to study the different configuration operation policies in response to the changing traffic patterns in the higher layer and the congestion level on the virtual topology. This algorithm persists to decide the optimal instant of reconfiguration easily based on the network state. Simulation results show that our virtual topology management Policy significantly outperforms the conventional one, while the required physical resources are limited.

• BMB Reports
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• v.42 no.11
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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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• v.11 no.2
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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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• v.14 no.5
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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.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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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.

• Computational Structural Engineering
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• v.11 no.4
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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.