• Proceedings of the Zoological Society Korea Conference
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• 1998.10b
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• pp.338.1-338
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• 1998

No Abstract, See Full Text

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.118-119
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• 2008

• Proceedings of the Zoological Society Korea Conference
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• 2000.10a
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• pp.92-92
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• 2000

No Abstract, See Full Text

• Proceedings of the Zoological Society Korea Conference
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• 1999.10b
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• pp.285.1-285
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• 1999

No Abstract, See Full Text

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.6
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• pp.89-96
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• 2001

This paper presents a decision making technique of reasonable $O_2$quantity needed to resolve organic matter via microbe in wastewater treatment. Decision making system of inferring reasonable $O_2$quantity consists of three parts. The first part is to compute reasonable $O_2$quantity with given process data. The second part is to find output features of processed wastewater using process model when $O_2$quantity is changed to a value inferred from decision making system. The third part is to show the results of decision making system. In order to verify performance of proposed decision making system computer simulation was done with process data gathered during 40 days. Simulation result shows that $O_2$quantity can be reduced over 10% under the condition of satisfying the specifications for processed wastewater.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.202-205
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• 2005

Cell phenotypes are determined by the concerted activity of thousands of genes and their products. This activity is coordinated by a complex network that regulates the expression of genes. Understanding this organization is crucial to elucidate cellular activities, and many researches have tried to construct gene regulatory networks from mRNA expression data which are nowadays the most available and have a lot of information for cellular processes. Several computational tools, such as Boolean network, Qualitative network, Bayesian network, and so on, have been applied to infer these networks. Among them, Bayesian networks that we chose as the inference tool have been often used in this field recently due to their well-established theoretical foundation and statistical robustness. However, the relative insufficiency of experiments with respect to the number of genes leads to many false positive inferences. To alleviate this problem, we had developed the algorithm of MONET(MOdularized NETwork learning), which is a new method for inferring modularized gene networks by utilizing two complementary sources of information: biological annotations and gene expression. Afterward, we have packaged and improved MONET by combining dispersed functional blocks, extending species which can be inputted in this system, reducing the time complexities by improving algorithms, and simplifying input/output formats and parameters so that it can be utilized in actual fields. In this paper, we present the architecture of MONET system that we have improved.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.47-75
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• 2010

Two experiments were conducted to explore whether the Or structure works as a default causal model in inferring the causal structure from the contingency data. The contingencies of three unfamiliar variables were used in Experiment 1. Participants inferred the Or structure quite well from the OR data, but incorrectly inferred the Or structure from the And data for about a little less than half of the time, and almost always inferred the Or structure from the chain data. The results suggested that the Or interpretation can be the default causal model. The prevalence of the Or interpretation from the contingency data was reported even when the three variables were familiar ones in Experiment 2. Multinomial modeling performed on the results of the two experiments strongly suggested that the Or interpretation work as a default causal model.

• Korean Journal of Ecology and Environment
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• v.36 no.3 s.104
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• pp.221-234
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• 2003

Phylogenetic studies would clarify the diversity of fishes if the morphological analysis based on plesimorphy characters combined with new genetic analysis on molecular level, inferring more accurate and objective phylogeny and the taxonomy. Current molecular phylogenetic approach using mitochondrial genome provides the framework for a new hypothesis not only inferring the relationships between ancestor descendants but raveling the intra-, interspecies variation.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.75-82
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• 2008

The times of service commencement and service completion had been used for inferring the queueing systems. However, the service commencement times are difficult to measure because of unobservable nature in queueing systems. In this paper, for inferring queueing systems, the service commencement times are replaced for arrival times which can be easily observed. Determining the service commencement time is very important in our methods. The methods for first come first served(FCFS), last come first served(LCFS) queueing discipline are already developed in our previous work. In this paper, we extend to random selection for service(RSS) queueing discipline. The performance measures we used are mean queueing time and mean service time, the variances of two. The simulation results verify our proposed methods to infer queueing systems under RSS discipline.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.49-56
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• 2019

The purpose of this study is to analyze the characteristics and meanings of Instagram hashtags related to the exhibitions as a online communication platform of museums. At the same time, it focuses on efficiency of hashtags as a reference framework of inferring viewing experiences. We collect and visualize Instagram hashtags of exhibitions held in Korea for the past two years including 'Paper Present (2017)', 'YOUTH (2017)', 'Monet, Draw Light Exhibition (2018)', 'Van Gogh Inside (2016)', 'Drawn by the Wind: Shin yun-bok & Jeong Seon'. To sum up, significant data related to viewing experiences are not derived, and hashtags as a reference framework of inferring viewing experiences are turned out to be inefficient. Meanwhile, we conclude that potential for distributing information about the exhibitions is inherent in hashtags. In terms of informational characteristics, we notice that the influence of hashtags related to regional information is presented more than the response toward the viewing experiences. This result shows that Instagram users in the exhibitions are worthy of place making rather than viewing experiences.