• Knowledge Management Research
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• v.14 no.5
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• pp.101-120
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• 2013

The effective management of knowledge has become one of the critical success factors in current organizations. In spite of the extensive use of Knowledge Management System (KMS), useful information and knowledge resources are still transmitted through personal networks among people in organizations. Thus, social network theory which focuses on social relationships in organization can be a fruitful theoretical resource for enhancing Knowledge Management (KM) performances. In this study, we investigate the effects of intra-team network characteristics (i.e., group density and degree of centralization) and external boundary spanning activities on knowledge management performances of a team. We also acknowledge that all group members do not necessarily agree on the team goal and actively disseminate useful information and knowledge. Drawing on the political perspective on KM which emphasizes the role of trust among group members, we examine the mediating effects of team trust between internal/external network characteristics and KM performances. From the data of 220 teams in financial companies in Korea, we found that: (1) group density had positive effects on KM performances (i.e., knowledge creation, sharing, and use). (2) However, centralization was not significantly associated with KM performances. (3) Team trust was found to be an important factor mediating the relationship between intra-team network characteristics, boundary spanning activities, and KM performances. Based on these results, we discuss and suggest possible implications of the findings when designing and implementing KM practices.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.4
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• pp.87-97
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• 2009

Internet network routing system is used to prevent spread and distribution of malicious data traffic. This study is based on analysis of diagnostic weakness structure in the network security domain. We propose an improved integrated multi-level protection domain for in the internal route of groupware. This paper's protection domain is designed to handle the malicious data traffic in the groupware and finally leads to lighten the load of data traffic and improve network security in the groupware. Infrastructure of protection domain is transformed into five-stage blocking domain from two or three-stage blocking. Filtering and protections are executed for the entire server at the gateway level and internet traffic route ensures differentiated protection by dividing into five-stage. Five-stage multi-level network security domain's malicious data traffic protection performance is better than former one. In this paper, we use a trust evaluation metric for measuring the security domain's performance and suggested algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1717-1724
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• 2012

Information of social relationship of users on online is useful information for other services such as recommend information of commercial activity. So, there is a lot of studies analysis with connection to visualization of social network. Most of the previous works of visualization focus on representing user's relationship on social network by a complex multi dimension graph. However, this method is difficult to identify the important of relationship to focus on personal user intuitively. In order to resolve above problem, this paper proposes a new visualization method using the user's correlation and user relationship of network node. The proposed method visualizes the hierarchy relationship of users using the internal relation of network reflecting user's message and external relation of network nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.853-873
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• 2021

In recent years, deep reinforcement learning (DRL) models are enjoying great interest as their success in a variety of challenging tasks. Deep Q-Network (DQN) is a widely used deep reinforcement learning model, which trains an intelligent agent that executes optimal actions while interacting with an environment. This model is well known for its ability to surpass skilled human players across many Atari 2600 games. Although DQN has achieved excellent performance in practice, there lacks a clear understanding of why the model works. In this paper, we present a visual analytics system for understanding deep Q-network in a non-blind matter. Based on the stored data generated from the training and testing process, four coordinated views are designed to expose the internal execution mechanism of DQN from different perspectives. We report the system performance and demonstrate its effectiveness through two case studies. By using our system, users can learn the relationship between states and Q-values, the function of convolutional layers, the strategies learned by DQN and the rationality of decisions made by the agent.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.41-46
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• 2022

In the fourth industrial era, when various technologies are fused and combined, new and advanced technologies from other industries are used extensively in the maritime industry field. New security threats are also increasing along with the development of new technologies. In addition, in incorporating convergence technologies into the maritime industry, various problems, such as communication definitions and procedures between technologies and customer-customized delays, occur. In this paper, for the problems mentioned above, research results on the network configuration of safer autonomous vessels by supplementing and fusing existing solutions rather than developing new technologies are proposed. In conclusion, the entire network consists of VDI and presents additional configurations to ensure confidentiality, integrity, and availability, which are the three security elements. According to the composition of such a convergence network, it is intended to help prepare countermeasures to protect internal data from external threats.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.461-463
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• 2021

With the recent increase in remote access due to network expansion, cloud infrastructure expansion, and telecommuting, the need to be vigilant not only from external access but also from internal access is increasing. Because of this, a new network security model called zero trust is attracting attention. In this paper, we will briefly introduce the concept of zero trust and examine strategies for applying zero trust according to various business environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2359-2376
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• 2022

With the exponential growth of medical image big data represented by high-resolution CT images(CTI), the high-resolution CTI data is of great importance for clinical research and diagnosis. The paper takes lung CTI as an example to study. Retrieving answer CTIs similar to the input one from the large-scale lung CTI database can effectively assist physicians to diagnose. Compared with the conventional content-based image retrieval(CBIR) methods, the CBIR for lung CTIs demands higher retrieval accuracy in both the contour shape and the internal details of the organ. In traditional supervised deep learning networks, the learning of the network relies on the labeling of CTIs which is a very time-consuming task. To address this issue, the paper proposes a Weakly Supervised Similarity Evaluation Network (WSSENet) for efficiently support similarity analysis of lung CTIs. We conducted extensive experiments to verify the effectiveness of the WSSENet based on which the CBIR is performed.

• The Journal of Korean Association of Computer Education
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• v.5 no.3
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• pp.27-35
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• 2002

This paper is presented a model of management and application of PC, one of the most important computer resources and software and a model for optimal speed of network to organize information budget of University. I propose strategies to promote utilization degree of existing PCs, problems and strategies to maintain PC, effective strategies to expand PC and change into new models, and strategies to utilize effectively and purchase softwares. Also, I propose an optimal model for network environment and management, which is core to establish master plan of information system. Network is divided into internal and external network and formula model is proposed to calculate optimal speed of these. And strategy is proposed to maintain security of University preserving its characteristics.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2923-2925
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• 1999

The objective of camera calibration is to determine the internal optical characteristics of camera and 3D position and orientation of camera with respect to the real world. Calibration procedure applicable to general purpose cameras and lenses. The general method to revise the accuracy rate of calibration is using mathematical distortion of lens. The effective og calibration show big difference in proportion to distortion of camera lens. In this paper, we propose the method which calibration distortion model by using neural network. The neural network model implicity contains all the distortion model. We can predict the high accuracy of calibration method proposed in this paper. Neural network can set properly the distortion model which has difficulty to estimate exactly in general method. The performance of the proposed neural network approach is compared with the well-known Tsai's two stage method in terms of calibration errors. The results show that the proposed approach gives much more stable and acceptabke calibration error over Tsai's two stage method regardless of camera resolution and camera angle.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.27-35
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• 1998

In this paper we will develope the immunized recurrent neural network control system with high robustness in dynamically changing environmental conditions. The variation of internal parameters of a system and external(or internal) disturbances can be considered as antigen, and the control input which can be regarded as antibody can be generated against uncertainties. The antibody will be generated from previous control informations and if a antibody for an antigen can not be generated from the corresponding information. the immune system produces another antibody by genetic operations. We apply this concept to a robot manipulator and evaluate the effectiveness of the above proposed system.