• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.75-82
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• 2017

Correct prediction of emotion is essential for developing advanced health devices. For this purpose, neural network has been successfully used. However, interpretation of how a certain emotion is predicted through the emotion prediction neural network is very tough. When interpreting mechanism about how emotion is predicted by using the emotion prediction neural network can be developed, such mechanism can be effectively embedded into highly advanced health-care devices. In this sense, this study proposes a novel approach to interpreting how the emotion prediction neural network yields emotion. Our proposed mechanism is based on HRV (heart rate variability) measurements, which is based on calculating physiological data out of ECG (electrocardiogram) measurements. Experiment dataset with 23 qualified participants were used to obtain the seven HRV measurement such as Mean RR, SDNN, RMSSD, VLF, LF, HF, LF/HF. Then emotion prediction neural network was modelled by using the HRV dataset. By applying the proposed mechanism, a set of explicit mathematical functions could be derived, which are clearly and explicitly interpretable. The proposed mechanism was compared with conventional neural network to show validity.

• Journal of Korea Trade
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• v.26 no.4
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• pp.39-62
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• 2022

Purpose - Along with the growing awareness of environmental sustainability, international green entrepreneurship is expected to realize international sustainable development (ISD) by introducing ecological innovation results, using fewer resources consumption, and reducing negative environmental impacts. Building upon contingency theory and social network theory, this paper attempts to explore the role of home country-based networks (technology ties and business ties) as contingent factors that might impact the effectiveness of entrepreneurial orientation (EO) in promoting ISD among green ventures. Design/methodology - Original data were collected from 127 green ventures in China based on the random sampling technique. These green ventures mainly focus on the lower use of energy or materials, lower CO2 emissions, and higher ecological benefits located in the Fujian province, which highlights green economic growth and economic cooperation with international markets. Moderated hierarchical linear regression analysis was conducted to test our hypotheses concerning the main relationship between EO (innovativeness, proactiveness, and risk-taking) and ISD as well as the moderating effects of home country-based networks (technology ties and business ties) on the main relationship. Findings - Empirical results indicate that: first, both innovativeness and proactiveness positively affect ISD; second, both technology ties and business ties at home might significantly strengthen the positive relationship between innovativeness (or proactiveness) and ISD. However, this study did not find significant moderating effects of technology ties or business ties at home on the relationship between risk-taking and ISD. Originality/value - Since previous literature often gives more focus on the host country context of social networks, this study shifts to a home country-based network context. Therefore, our research might enrich the international green entrepreneurship literature by empirically investigating the contingent value of home country-based networks in the relationship between EO and ISD in the context of an emerging economy such as China.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.374-374
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• 2006

• Journal of Communications and Networks
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• v.16 no.5
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• pp.534-547
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• 2014

Large-scale failures resulting from natural disasters or intentional attacks are now causing serious concerns for communication network infrastructure, as the impact of large-scale network connection disruptions may cause significant costs for service providers and subscribers. In this paper, we propose a new framework for the analysis and prevention of network service disruptions in large-scale failure scenarios. We build dynamic deterministic and probabilistic models to capture the impact of regional failures as they evolve with time. A probabilistic failure model is proposed based on wave energy behaviour. Then, we develop a novel approach for preventive protection of the network in such probabilistic large-scale failure scenarios. We show that our method significantly improves uninterrupted delivery of data in the network and reduces service disruption times in large-scale regional failure scenarios.

• Asia pacific journal of information systems
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• v.32 no.1
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• pp.168-190
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• 2022

This review aims to synthesize social network theories by drawing on the importance of social network perspectives in understanding knowledge management with technology in organizations. I provide an overview of prior social network research with the following core ideas: the primacy of relations between organizational actors, the utility of actors' embeddedness in social fields, the social utility of network connections, and the structural patterning of social life. On top of that, I summarize critical social perspectives (the social capital theory, the structural hole theory, the embeddedness perspective, the social exchange theory, the organizational learning theory, and the innovation diffusion theory) to suggest potential research questions for future studies in social network research in the knowledge management discipline.

• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.93-105
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• 2013

Much Interest has focused on social network services such as Facebook and Twitter. Previous research conducted on social network often emphasized the architecture of the social network that is the existence of path between any objects on network and the centrality of the object in the network. However, studies on the semantic association in the network are rare. Studies on searching semantic associations between entities are necessary for future business enhancements. In this research, the ontology based social network analysis is performed. A new method to search and rank relation sequences that consist of several relations between entities is proposed. In addition, several heuristics to measure the strength of the relation sequences are proposed. To evaluate the proposed method, an experiment was performed. A group of social relationships among the university and organizations are constructed. Some social connections are searched using the proposed ranking method. The proposed method is expected to be used to search the association among entities in ontology based knowledge base.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• Journal of Distribution Science
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• v.11 no.10
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• pp.37-45
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• 2013

Purpose - Appropriate response to the fast changing economic environment determines SMEs' competiveness in the era of globalization and open market and, therefore, government policies to strengthen SME's competitiveness will be very important in the future. It is time to investigate the element of strategic orientation that is necessary for strengthening the competitiveness of SMEs, and its effect on the success of a business start-up. This study analyzes the network orientation in addition to existing strategic orientation, and focuses on price and quality management capability as mediators for strategic orientation and outcomes of business start-ups. Research design/data/methodology - The orientations of technology-based business founders were classified into market, technology, network, and entrepreneurial orientation. We then investigated the effect of these orientations on product price and quality management capability, as well as the influence of price and quality management capability on the outcome of a business start-up. This study is based on the nation-wide survey of the founders and members of technology-based business establishments. The survey was administered to 300 selected companies via email for a period of one month, at the end of which 175 companies replied with valid answers. Further, for effective and objective research, we used SPSS 14.0 and Amos 7.0 for structural equation modeling assumptions and hypothesis verification. Results - Except for entrepreneurial orientation, the other three orientations, namely, technology, market, and network orientations, affect the price management capability according to our results. The price management capability relates significantly with the sales and customer satisfaction. Especially, technology orientation is the core competency of start-ups that affects price and quality management capabilities. However, technology and entrepreneurial orientation do not influence the outcome of business start-ups, but affect their quality management capabilities. Conclusions - This study confirms that the strategic orientation affects product price as well as quality management capabilities, to introduce new products and achieve successful outcomes. In conclusion, new business founders face the dilemma of trade-off between price and quality in the planning stage of new product development. In particular, price management capability directly affects the outcome. Therefore, price management is more important for a successful start-up than quality management. Especially, during the initial stages of starting up a new business, price management capability entails following the market-leading company, or price penetration strategy. In this stage, price management is dependent on the information from outside rather than on the founder's decision, and it directly affects sales performance and customer satisfaction. In contrast, quality management capability is directly related to the technology capability and market experience of founders. In this case, subjective and proactive decision making is required for differentiation and development of demand in the niche market, which does not directly influence the sales performance and customer satisfaction.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.53-62
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• 2023

Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary's network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

• The Journal of Society for e-Business Studies
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• v.9 no.3
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• pp.277-288
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• 2004

The purpose of multimedia contents transmission is to resolve the large size and nonformal issues. Various multicasting technologies have been researched to support these issues. This paper suggests a technique to build multicast routing for safe and reliable transmission of multimedia contents. Network server nodes have their own weight with respect to communication loads. The weight is computed by a server's communication load with others. This suggests low delay routing with two or more edge server of content delivery network. We will show the weighted inter-server routing technique and analyze the network performance improvement caused by lower network traffic and delay.