• Knowledge Management Research
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• v.15 no.2
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• pp.1-21
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• 2014

In this study we adopted Interpersonal Process Model of Intimacy to study SNS use intention. First, we investigated the effects of personal identity, social identity and intimacy. Second, we tested the influences of self-disclosure, partner disclosure on perceived partner responsiveness. Third, we measured the relationship between perceived partner responsiveness and intimacy. Lastly, we investigated the effects of intimacy, perceived partner responsiveness and use intention. A total of 232 final respondents were collected from users of Social Network Services in 2011. The results revealed several important findings. First, we found that social identity had a significant and positive effect on intimacy. However, personal identity showed insignificant effect toward intimacy. Moreover, self-disclosure and partner disclosure had a positive effects on perceived partner responsiveness. perceived partner responsiveness showed a positive effect on both intimacy and use intention. Lastly, intimacy had significant effect on use intention.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.1
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• pp.108-114
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• 2015

The purpose of this study is to find the relationships among communication competency, social network centrality(trust centrality and knowledge sharing centrality), discussion performance, and online boarding activity in the team based learning situation. For investigating this topic, 44 students are participated in the classes of educational technology. In order to find out the relationships among communication competency, social network centrality, discussion performance, and online boarding activity, compared t-test and path analysis are used. Followings are the results of the research: (a) Communication competency is improved significantly after team based learning. (b) Trust centrality effects significantly on the knowledge sharing centrality. (c) Knowledge sharing effects significantly on discussion performance. (d) Trust centrality effects on the online boarding activity in the team based learning.

• ETRI Journal
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• v.41 no.5
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• pp.560-573
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• 2019

Two supervised learning algorithms, a basic neural network and a long short-term memory recurrent neural network, are applied to traffic including DDoS attacks. The joint effects of preprocessing methods and hyperparameters for machine learning on performance are investigated. Values representing attack characteristics are extracted from datasets and preprocessed by two methods. Binary classification and two optimizers are used. Some hyperparameters are obtained exhaustively for fast and accurate detection, while others are fixed with constants to account for performance and data characteristics. An experiment is performed via TensorFlow on three traffic datasets. Three scenarios are considered to investigate the effects of learning former traffic on sequential traffic analysis and the effects of learning one dataset on application to another dataset, and determine whether the algorithms can be used for recent attack traffic. Experimental results show that the used preprocessing methods, neural network architectures and hyperparameters, and the optimizers are appropriate for DDoS attack detection. The obtained results provide a criterion for the detection accuracy of attacks.

• Structural Engineering and Mechanics
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• v.39 no.2
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• pp.267-285
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• 2011

There can be a significant amount of moment redistribution in composite frames consisting of steel columns and composite beams, due to cracking, creep and shrinkage of concrete. Considerable amount of computational effort is required for taking into account these effects for large composite frames. A methodology has been presented in this paper for taking into account these effects. In the methodology that has been demonstrated for moderately high frames, neural network models are developed for rapid prediction of the inelastic moments (typically for 20 years, considering instantaneous cracking, and time effects, i.e., creep and shrinkage, in concrete) at a joint in a frame from the elastic moments (neglecting instantaneous cracking and time effects). The proposed models predict the inelastic moment ratios (ratio of elastic moment to inelastic moment) using eleven input parameters for interior joints and seven input parameters for exterior joints. The training and testing data sets are generated using a hybrid procedure developed by the authors. The neural network models have been validated for frames of different number of spans and storeys. The models drastically reduce the computational effort and predict the inelastic moments, with reasonable accuracy for practical purposes, from the elastic moments, that can be obtained from any of the readily available software.

• Journal of Service Research and Studies
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• v.6 no.4
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• pp.15-34
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• 2016

The purpose of this study is to examine the effects of social entrepreneurship on organizational performance and to identify network moderating effects on social entrepreneurship and organizational performance. Data collected from 189 employees working in social enterprises were analyzed by using SPSS 18.0 program. Results are as follows: First, innovativeness, proactiveness, and social value orientation which were sub-factors of social entrepreneurship had positive effects on social performance. Second, proactiveness, risk-taking, and social value orientation which were sub-factors of social entrepreneurship had positive effects on economic performance. Third, the network significantly moderated the effects on innovativeness, proactiveness, social value orientation which were sub-factors of social entrepreneurship, and social performance. Fourth, the network significantly moderated the effects on proactiveness which was a sub-factor of social entrepreneurship, and economic performance. These results exhibited that the social entrepreneurship was effective to increase the organizational performance by activating the network and proposed a useful approach for further studies as an investigation method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.138-141
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• 1997

In this study, a simulation model is developed to analyze the effects of routing and scale-economy of transmission facilities on the traffic network topology and investment cost changes in a metropolitan telephone network. Computational experiments showed that the wide deployment of bifurcated routing in a dual-homing configuration reduces significantly the traffic network connectivity and the investment cost. Its enhanced version, when combined with the subscriber network cost model, can be used as a prototype cost proxy model for figuring out the access charges in a multi-operator environment.

• ETRI Journal
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• v.25 no.5
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• pp.369-378
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• 2003

Using the general switch management protocol on a multi-protocol label switching network, we present an efficient method for handling handovers. The proposed method directly changes an established path into a new path for supporting a handover. Our investigation reveals the effects of the proposed scheme and demonstrates that this method significantly reduces signaling costs and delays.

• Asia pacific journal of information systems
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• v.26 no.4
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• pp.477-488
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• 2016

New technology development capability plays a key role in making small- and medium-sized enterprises (SMEs) increase their innovation performance, such as in product or process innovation. To examine the influencing factors of SMEs' new technology development capability, this study empirically analyzes the mediating effects of SMEs' process design capability and product interior design capability on the positive association between their external information network diversity and new technology development capability. This study performs the ordinary least squares regression on a sample of 2,000 South Korean SMEs. Results reveal that SMEs' process design capability fully mediates, and product interior design capability partially mediates the positive association between the external information network diversity and new technology development capability.

• Journal of Digital Convergence
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• v.1 no.1
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• pp.147-164
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• 2003

The use of electronic mail and messenger software tools has been increased rapidly over a decade. Compared to the variety of research related to the relationship between personal psychological traits and communication modes, effects of human psychology on online activities have only recently become a focus of interest. This research analyzed the relationship between personal psychological type and online connectivity. We employed network analysis methodology and collected and analyzed data from 146 subjects. Significant differences in network measures were found among groups with different psychological style. Findings of the research can provide several implications for managerial activities regarding social connectivity.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.7
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• pp.337-343
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• 2015

This paper investigates the ventilation characteristics in a two-dimensional underground network junction composed of four main lines interconnected by eight ramps. Simple one-dimensional models cannot be applied to network junctions since there are interferences of traffic piston effects in the main lines and at the ramps. A numerical algorithm was developed to analyze the pressure and airflow distributions iteratively. The Darcy-Weisbach equation was used to calculate the piston effects by traffic flows, and a Hardy Cross iteration was conducted for network analysis at the interconnected junction. The results show interesting ventilation characteristics and CO concentration distributions depending on system parameters such as vehicle speed, tunnel diameter, and other junction configurations.