• Journal of Digital Convergence
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• v.16 no.4
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• pp.95-105
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• 2018

This study empirically test the roles of network closure and structural hole on radical innovation in technological knowledge exchange network in Gumi cluster. In doing so, we build 2,550 firm network, transforming association*firm(2-mode) to firm*firm(1-mode) network data. In addition, in order to investigate firms' attributes, we conduct survey for 101 firms in Gumi cluster using random sampling, and finally collect 86 firm samples. For analysis, we use ridge regression since network density and efficiency, indices of network closure and structural hole respectively, has a high level of multicollinearity. The findings show that structural hole has a significant and positive impact on radical innovation, but network closure has a significant and negative impact on radical innovation. This study contributes to present an empirical evidence of debate on network closure and structural hole based on past conceptual discussions and literature review and further goes a long way towards strategy formulation to establish social capital in accomplishing radical innovation. Further research is required that pays closer attention to features of technological knowledge, innovation types and interaction between network closure and structural hole, directing efforts to structural characteristics of various networks.

• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.75-85
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• 2017

Personalization recommendations have already proven in many areas of the e-commerce industry. For personalization recommendations, additional work such as reclassifying items is generally necessary, which requires personal information. In this study, we propose a recommendation technique that neither exploit personal information nor reclassify items. We focus on music recommendation and performed experiments with actual music listening data. Experimental analysis shows that the proposed method may result in meaningful recommendations albeit it exploits less amount of data. We analyze the appropriate number of items and present future considerations for contextual recommendation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2020-2028
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• 2013

In this paper, we propose a novel analysis and design methodology based on complex network theory for wireless large-scale ad hoc networks. We also enhance the conventional analysis methods which does not sufficiently consider the effect of the wireless communication channels and extend the existing random graph theory by reflecting the wireless communication environments. As a main result, the effect of the network topology such as average degree of each communication node on the network capacity through extensive computer simulations.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.1-6
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• 2005

In the Markov network which models disparity map with the Markov Random Fields(MRF), the belief propagation algorithm is operated by message passing between nodes corresponding to each pixel. The initial message value is converged by iterations of the algorithm and the algorithm requires many iterations to get converged messages. In this paper, we simplify the algorithm by regarding the objects in the disparity map as combinations of lines with same message valued nodes to reduce iterations of the algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.68-75
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• 2013

Recently, there has been introduced various types of pairing computations to implement ID based cryptosystem for mobile ad hoc network. According to spreading the applications of pairing computations, various fault attacks have been proposed. Among them, a counter fault attack has been considered the strongest threat. Thus this paper proposes a new countermeasure to prevent the counter fault attack on Miller's algorithm. The proposed method is able to reduce the possibility of fault propagation by a random index of intermediate values. Additionally, it is difficult to challenge fault attacks on the proposed method since a simple side channel leakage of 'if' branch is eliminated.

• The Journal of Korea Robotics Society
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• v.9 no.1
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• pp.11-19
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• 2014

In this paper, an external torque estimation problem in one-degree-of-freedom (1-DOF) flexible-joint robot equipped with a joint-torque sensor is revisited. Since a sensor torque from the joint-torque sensor is distorted by two dynamics having a spring connection, i.e., motor dynamics and link dynamics of a flexible-joint robot, a model-based estimation, rather than a simple linear spring model, should be required to extract external torques accurately. In this paper, an external torque estimation algorithm for a 1-DOF flexible-joint robot is proposed. This algorithm estimates both an actuating motor torque from the motor dynamics and an external link torque from the link dynamics simultaneously by utilizing the flexible-joint robot model and the Kalman filter estimation based on random-walk model. The basic structure of the proposed algorithm is explained, and the performance is investigated through a custom-designed experimental testbed for a vertical situation under gravity.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.9
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• pp.30-38
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• 2008

The traditional TCP was designed assuming wired networks. Thus, if it is used networks consisting of both wired and wireless networks, all packet losses including random losses in wireless links are regarded as network congestion losses. Misclassification of packet losses causes unnecessary reduction of transmission rate, and results in waste of bandwidth. In this paper, we present WTCP(wireless TCP) congestion control algorithm that differentiates the random losses more accurately, and adopts improved congestion control which results in better network throughput. To evaluate the performance of proposed scheme, we compared the proposed algorithm with TCP Westwood and TCP Veno via simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10A
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• pp.830-838
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• 2011

Recently, studies for the network coding in the wireless network to achieve improvement of the network capacity are conducted. In this paper, we analysis considerations to apply RLNC in the wireless network. First of all, we verify whether the RLNC method in multicast is applied to distributed wireless network. In simulation results, the decoding failure can occur in the original manner of multicast. In RLNC which conducts encoding and decoding in X topology to gets rid of the decoding failure, the RLNC gain is insignificant. In this paper we also discuss considerations such as the hidden node problem, the occurrence of coding opportunity, and the RLNC overhead which are practical issues in the wireless network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.222-228
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• 2016

We provide an aggressive spatial reuse scheme exploiting the space sensed busy when neighboring 802.11 stations radiate radio wave in omni-directions. For this purpose, we develop four strategies, i.e., disruptive RTS, busy random backoff, zero padding, and unavailable pair management. The simulation results show that the proposed scheme can improve the aggregate network throughput from 14% to 50% while the station adopting the proposed scheme coexists with the legacy stations.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.1-8
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• 2015

Security has become an issue due to the rapid increases in internet traffic data network. Especially P2P traffic data poses a great challenge to network systems administrators. Preemptive measures are necessary for network quality of service(QoS) and efficient resource management like blocking suspicious traffic data. Deep packet inspection(DPI) is the most exact way to detect an intrusion but it may pose a private security problem that requires time. We used several machine learning methods to compare the performance in classifying network traffic data accurately over time. The Random Forest method shows an excellent performance in both accuracy and time.