• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.955-959
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• 2009

In this paper, we propose a novel method for analyzing human interactions based on the walking trajectories of human subjects. Our principal assumption is that an interaction episode is composed of meaningful smaller unit interactions, which we call 'sub-interactions.' The whole interactions are represented by an ordered concatenation or a network of sub-interaction models. From the experiments, we could confirm the effectiveness and robustness of the proposed method by analyzing the inner workings of an interaction network and comparing the performance with other previous approaches.

• Journal of the Korean association of regional geographers
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• v.20 no.1
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• pp.30-48
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• 2014

Relying on the interaction indices - dominance index, relative strength index and entropy index, this paper analyzes the structural features of urban network in the Seoul metropolitan area with the flows of commuting, business, and freight. Analytical results show that the Seoul metropolitan urban system is vertical, size-dependent, one-way, and the highest city-dominant network rather than horizontal, size-neutral, two-way, complementary one. The network of freight flow is a little bit more symmetrical than the networks of commuting and business. However, the interaction with Seoul is still determinant in all aspects of hierarchical structure, relative strength, and symmetry of flow.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.397-397
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• 2015

The frequency of urban floods is recently increased as a consequence of climate change and haphazard development in urban area. To mitigate and prevent the flood damage, we generally utilized a numerical model to investigate the causes and risk of urban flood. Contrary to general flood inundation model simulating only the surface flow, the model needs to consider flow of the sewer network system like SWMM and ILLUDAS. However, this kind of model can not consider the interaction between the surface flow and drainage network. Therefore, we tried to evaluate the impact of bidirectional interaction between sewer and surface flow in urban flooding analysis based on simulations using the quasi-interacted model and the interacted model. As a general quasi-interacted model, SWMM5 and FLUMEN are utilized to analyze the flow of drainage network and simulate the inundation area, respectively. Then, FLO-2D is introduced to consider the interaction between the surface flow and sewer system. The two method applied to the biggest flood event occurred in July 2011 in Sadang area, South Korea. Based on the comparison with observation data, we confirmed that the model considering the interaction the sewer network and surface flow, showed a good agreement than the quasi-interacted model.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.563-573
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• 2012

Various methods of analysis have been proposed to understand the gene-disease relation and gene-gene interaction effect for a disease through comparison of genotype in case-control study. In this study, we proposed the method to detect a genetic association and gene-gene interaction through the use of a network graph and centrality measures that are used in social network analysis. The applicability of the proposed method was studied through an analysis of real genetic data.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2002.06a
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• pp.5-23
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• 2002

Motivation: Protein-protein interaction plays a critical role in the biological processes. The identification of interacting proteins by bioinformatical methods can provide new lead In the functional studies of uncharacterized proteins without performing extensive experiments. Results: Protein-protein interactions are predicted by a computational algorithm based on the weighted scoring system for domain interactions between interacting protein pairs. Here we propose potential interaction domain (PID) pairs can be extracted from a data set of experimentally identified interacting protein pairs. where one protein contains a domain and its interacting protein contains the other. Every combinations of PID are summarized in a matrix table termed the PID matrix, and this matrix has proposed to be used for prediction of interactions. The database of interacting proteins (DIP) has used as a source of interacting protein pairs and InterPro, an integrated database of protein families, domains and functional sites, has used for defining domains in interacting pairs. A statistical scoring system. named "PID matrix score" has designed and applied as a measure of interaction probability between domains. Cross-validation has been performed with subsets of DIP data to evaluate the prediction accuracy of PID matrix. The prediction system gives about 50% of sensitivity and 98% of specificity, Based on the PID matrix, we develop a system providing several interaction information-finding services in the Internet. The system, named PreDIN (Prediction-oriented Database of Interaction Network) provides interacting domain finding services and interacting protein finding services. It is demonstrated that mapping of the genome-wide interaction network can be achieved by using the PreDIN system. This system can be also used as a new tool for functional prediction of unknown proteins.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1189-1195
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• 2004

This paper investigates construction of gene (interaction) networks from gene expression time-series data based on evolutionary computation. To illustrate the proposed approach in a comprehensive way, we first assume an artificial gene network and then compare it with the reconstructed network from the gene expression time-series data generated by the artificial network. Next, we employ real gene expression time-series data (Spellman's yeast data) to construct a gene network by applying the proposed approach. From these experiments, we find that the proposed approach can be used as a useful tool for discovering the structure of a gene network as well as the corresponding relations among genes. The constructed gene network can further provide biologists with information to generate/test new hypotheses and ultimately to unravel the gene functions.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.837-840
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• 2014

Interactions between genes have long been recognized and studied by many researchers, and they formed a large-scale interaction networks. In systems biology, it has been a challenge to investigate the factors to determine network dynamics. Here, we create a new network called an effectiveness network by calculating thy dynamical effectiveness from a node to another node. We found that robust nodes tend to have smaller number of edges than non-robust nodes. This implies that hub nodes are likely to affect the network robustness.

• IE interfaces
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• v.23 no.1
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• pp.24-34
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• 2010

In the telecommunication system which is based on the existing PSTN(public switched telephone network), feature interaction has been an important research issue in order to provide seamless services to users. Recently, rapid proliferation of IP-based network and the various types of IP media supply services, the feature interaction from the perspective of application services has become a significant aspect. This paper presents conflict detection and resolution algorithms for designing and operating a variety of services that are provided through IP-based network. The algorithms use explicit service interactions to detect conflicts between a new service and registered services. They then apply various rules to reduce search space in resolving conflicts. The algorithms are applied to a wide range of realistic service provision scenarios to validate that it can detect conflicts between services and resolve in accordance with different rule sets. By applying the algorithms to various scenarios, it is observed that the proposed algorithms can be effectively used in operating an IP-based services network.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.13
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• pp.5325-5330
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• 2014

Background: Chronic myelocytic leukemia is a disease that threatens both adults and children. Great progress has been achieved in treatment but protein-protein interaction networks underlining chronic myelocytic leukemia are less known. Objective: To develop a protein-protein interaction network for chronic myelocytic leukemia based on gene expression and to predict biological pathways underlying molecular complexes in the network. Materials and Methods: Genes involved in chronic myelocytic leukemia were selected from OMIM database. Literature mining was performed by Agilent Literature Search plugin and a protein-protein interaction network of chronic myelocytic leukemia was established by Cytoscape. The molecular complexes in the network were detected by Clusterviz plugin and pathway enrichment of molecular complexes were performed by DAVID online. Results and Discussion: There are seventy-nine chronic myelocytic leukemia genes in the Mendelian Inheritance In Man Database. The protein-protein interaction network of chronic myelocytic leukemia contained 638 nodes, 1830 edges and perhaps 5 molecular complexes. Among them, complex 1 is involved in pathways that are related to cytokine secretion, cytokine-receptor binding, cytokine receptor signaling, while complex 3 is related to biological behavior of tumors which can provide the bioinformatic foundation for further understanding the mechanisms of chronic myelocytic leukemia.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.47-52
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• 2022

The current study investigates how student-teacher interaction can be developed through task-based teaching in undergraduate students' Saudi teaching and learning context. An experiment was conducted for five weeks on 85 male undergraduate students at a Saudi public university based in Jeddah, Saudi Arabia. The study investigated different types of student-teacher interaction through task-based teaching (speaking activities). The results revealed that the experimental group (43 students) evinced much more enthusiasm, willingness, engagement and readiness in their inclass participation than their peers in the control group (42 students). The student-teacher interaction also helped students to be more responsive to general and specific topics in speaking activities. The study recommends that decision-makers in education make student-teacher interaction part of the student's monthly assessment. It also recommends that more efforts be made to foster the awareness of students, teachers, and parents awareness of the academic and non-academic importance of interaction. One final recommendation of the research is that student-teacher interaction should be more emphasized and integrated into the school curriculum and adopted as a critical teaching strategy.