• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.476-484
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• 2012

Family member network of kings in Chosun dynasty shows scale free network properties as if most social networks do. One of distinct topological properties of the network is relatively high diameter that reflects dataset composed of the one generation continuously falling to next one. When k-core algorithm as a useful tool for obtaining a core network from the complex family member network was employed, it is possible to obtain hidden and valuable information from a complex network. Unfortunately, it is found that k-core algorithm is not useful tool for applying narrow and deep structural network. The family member network is composed of kings, queens, princes, and princesses. It is possible to separate sub-family members and to construct sub-family member networks such as queen-centered, prince-centered, and princess-centered networks. Sub-family member networks provide an useful and hidden information. These results provide new insight that is analyzed by network-based approaches for the family member of the kings in the Chosun dynasty.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.191-195
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• 2007

Recently, landslides frequently happen at a natural slope during period of intensive rainfall. With rapidly increasing population of steep terrain in Korea, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is developed. The system is focused to debris flows which happen frequently during periods of intensive rainfall at steep slopes in Kangwondo. This system is based on the wireless sensor network that is composed of sensor nodes, gateway, and server system. Sensor nodes that are composed of sensing part and communication part are newly developed to detect sensitive ground movement. Sensing part is designed to measure tilt angle and acceleration accurately, and communication part is deployed with Bluetooth (IEEE 802.15. I) module to transmit the data to the gateway. To verify the feasibility of this landslide prediction system, a series of laboratory tests is performed at a small-scale earth slope supplying rainfall by artificial rainfall dropping device. It is found that sensing nodes installed at slope can detect the ground motion when the slope failure starts. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs, and can be applied to ubiquitous computing city (U-City) that is characterized by disaster free.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.519-526
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• 2012

Human-human interaction network derived from Roman-fleuve, Togi was constructed. The network has a scale free properties as if most social networks do. The Togi is excellent model system for analyzing network dynamics because it has various characters and complex their interactions. The novel is composed of well-separated 5 sections. I constructed 5 different sub-netwotks from each section. As employing k-core algorithm as a useful tool for obtaining a core network from the complex networks, it is possible to obtain hidden and valuable information from a complex network. As gradually extending one section to another one, I constructed 4 different extended networks. The final one is whole network from the Togi. These results provide new insight that is analyzed by network-based approaches for network dynamics from literature, Togi.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.5-19
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• 2015

Literatures on open innovation have two major limitations. First, either on a firm level or on an industry level did they analyze the open innovation issues. The results of a firm's innovation can be diffused through the whole network and the firm can learn back from the network knowledge. Prior literatures did not consider the feedback loop among firms and network in which the firms are involved. Second, most open innovation research had a static perspective on firm's innovation performance. Since the diffusion, spill-over and learning among network members are involved over time, the open innovation is intrinsically dynamic. From the dynamic perspective, we can appreciate the fundamental attributes of the open innovation network which involves diverse firms, research institutes, and universities. In order to overcome the limitations, we suggest a dynamic model for open innovation network. We build an agent-based model which consists of heterogeneous firms. The firms are connected through a scale-free network which is formed by preferential attachment. Through the diverse scenario of simulation, we collect massive data on the firm level and analyze them both on firm and industry level. From the analysis, we found that, on industry level, the overall performance of open innovation increases as the internal research capability, absorptive capacity, and learning curve coefficient increase. Noticeably, as the deprecation rate of knowledge increases, the variability of knowledge increases. From the firm level analysis, we found that the industry-level variables had a significant effect on the firm's innovation performance lasting through all the time, whereas the firm-level variables had only on the early phase of innovation.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.259-271
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• 2008

We propose a protein function finding algorithm that is able to predict specific molecular function for unannotated proteins through domain analysis from protein-protein network. To do this, we first construct protein-protein interaction(PPI) network in Saccharomyces cerevisiae from MIPS databases. The PPI network(proteins; 3,637, interactions; 10,391) shows the characteristics of a scale-free network and a hierarchical network that proteins with a number of interactions occur in small and the inherent modularity of protein clusters. Protein-protein interaction databases obtained from a Y2H(Yeast Two Hybrid) screen or a composite data set include random false positives. To filter the database, we reconstruct the PPI networks based on the cellular localization. And then we analyze Hub proteins and the network structure in the reconstructed network and define structural modules from the network. We analyze protein domains from the structural modules and derive functional modules from them. From the derived functional modules with high certainty, we find tentative functions for unannotated proteins.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.438-447
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• 2012

This study was to explore the social network structure of professional volleyball players and analyze network variables and resource exchange. This study selected 127 players of Korean professional volleyball in ten team of male and female using the purposive sampling method. The research method utilized general social survey of NGQ(Name Generator Question) and interview. To analyze data, NetMiner 3.0 and SNA(social network analysis) were used. The conclusion based on above study method and the result of material analysis are here below. First, social network of professional volleyball players is scale-free network following power law. Centrality and herb of club members' network show up richer-get-richer and poor-get-poor by collecting links of back of beyond. Second, social network structure of professional volleyball players influence resource exchange.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.427-435
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• 2010

We extracted core terms by constructing scientific item networks from textbooks, analyzing their structures, and investigating the connected information and their relationships. For this research, we chose three high-school textbooks from different publishers for each three subjects, i.e, Science, Biology I and Biology II, to construct networks by linking scientific items in each sentence, where used items were regarded as nodes. Scientific item networks from all textbooks showed scare-free character. When core networks were established by applying k-core algorithm which is one of generally used methods for removing lesser weighted nodes and links from complex network, they showed the modular structure. Science textbooks formed four main modules of physics, chemistry, biology and earth science, while Biology I and Biology II textbooks revealed core networks composed of more detailed specific items in each field. These findings demonstrate the structural characteristics of networks in textbooks, and suggest core scientific items helpful for students' understanding of concept in Science and Biology.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.364-371
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• 2009

We analyzed romance of the three kingdoms written by Luo Guanzhong by using complex network to compare its properties with those of social network. The three kingdom network has a scale free and hierarchical network properties. Human-human interaction networks are dramatically changing in response to time and space. Due to lack of the dynamic interacting data, the researches only focus to analysis for properties of the statical networks. The romance of the three kingdoms is a Chinese historical novel based upon events from the end of the Han Dynasty, the Three Kingdoms era of China, and the reunification of the land. There are over a thousand characters, over a three thousand human-human interactions, and the dynamic changed in human-human interactions in the historical novel. Here, we introduce that a possible method for analyzing about dynamic changing of the complex network.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.127-135
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• 2016

We identified a competition network which has never been studied before and investigated the relationship between centrality of participants in singing competition and their winning percentage within the competition network. We collected competition data from 'Immortal Songs: Singing the Legend', which is a Korean television music competition program, and constructed a competition network. We calculated centrality and winning percentage and analyzed their relationship using correlation analysis, regression analysis, and visualization. There are four main findings in this research. First, a competition network is a scale-free network whose degree distribution follows a power law. Second, there is a logarithmic relationship between the count of competition and closeness. Third, winning percentage converges to approximately 60% for players who have participated in more than 20 competitions. Lastly, a strength of opponents affects approximately 23% of winning percentage for players with less than 20 competitions. The academic significance of this study is that we pioneered the definition of the competition network and applied social network analysis method. Another significant contribution of this paper is that we found explicit patterns between the centrality and winning percentage, suggesting ways to improve social relationship in competition network and to increase winning percentage.

• Journal of Korean Elementary Science Education
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• v.39 no.2
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• pp.255-267
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• 2020

Students' engagement is important for meaningful learning and it has multifaceted aspects for their science learning. This study investigated elementary students' perceptions of science learning engagement. The subjects of this study were 341 4^th to 6^th elementary students. The survey questionnaires were 5-Likert scale questions and free response questions on science learning engagement. The results showed that elementary students' perceptions of behavioral engagement were higher than emotional and cognitive engagement. Keyword network analysis with NetMiner program showed that the frequent key words of science learning engagement were 'experiment', 'listening', and 'teachers' explanation', which were mostly the behavioral types of engagement. The degree centrality and eigenvector centrality of these key words appeared high. 'Interest', which is emotional engagement, were also one of the frequent key words, but the centralities of this word were relatively low. The Frequent key words of science learning disengagement were mostly related with off-tasks, not doing expected behaviors and negative emotions about science and science learning. Educational implications on science learning engagement were discussed.