• Title/Summary/Keyword: Value Network

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Network Perspectives in Innovation Research: Looking Back and Moving Forward

  • HYUN, Eunjung;RHEE, Seung-Yoon
    • Asian Journal of Business Environment
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    • v.11 no.1
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    • pp.27-37
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    • 2021
  • Purpose: This article aims to provide a balanced understanding of the structural conditions and social processes involved in the creation and diffusion of innovation. Research design, data and methodology: Drawing on organizational and economic sociology and strategic management literature, this article offers a conceptual framework that highlights the two dimensions of network structures: the vertical dimension focusing on power and legitimacy vs. the horizontal dimension highlighting information value. By organizing the literature on the functions and consequences of network, this paper advances a theoretical perspective in understanding the vast array of empirical studies on innovation involving network analysis. Results: Using the proposed framework, this article explains how the mechanisms of power, legitimacy, and information value work together with social structural factors, thus enriching our understanding of innovation. This study reveals that the information mechanism (horizontal dimension) has been most important in innovation creation and diffusion, and that trust, credibility, and legitimacy are operative in innovation diffusion. Conclusions: This paper contributes to the literature by responding to calls to extend existing frameworks to better account for the dynamics between innovation and network. In addition, this article highlights how conceptualizing innovation within the horizontal-vertical dimensions of network structures, creates new opportunities for future research.

Detection and Trust Evaluation of the SGN Malicious node

  • Al Yahmadi, Faisal;Ahmed, Muhammad R
    • International Journal of Computer Science & Network Security
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    • v.21 no.6
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    • pp.89-100
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    • 2021
  • Smart Grid Network (SGN) is a next generation electrical power network which digitizes the power distribution grid and achieves smart, efficient, safe and secure operations of the electricity. The backbone of the SGN is information communication technology that enables the SGN to get full control of network station monitoring and analysis. In any network where communication is involved security is essential. It has been observed from several recent incidents that an adversary causes an interruption to the operation of the networks which lead to the electricity theft. In order to reduce the number of electricity theft cases, companies need to develop preventive and protective methods to minimize the losses from this issue. In this paper, we have introduced a machine learning based SVM method that detects malicious nodes in a smart grid network. The algorithm collects data (electricity consumption/electric bill) from the nodes and compares it with previously obtained data. Support Vector Machine (SVM) classifies nodes into Normal or malicious nodes giving the statues of 1 for normal nodes and status of -1 for malicious -abnormal-nodes. Once the malicious nodes have been detected, we have done a trust evaluation based on the nodes history and recorded data. In the simulation, we have observed that our detection rate is almost 98% where the false alarm rate is only 2%. Moreover, a Trust value of 50 was achieved. As a future work, countermeasures based on the trust value will be developed to solve the problem remotely.

Resource Allocation Strategy of Internet of Vehicles Using Reinforcement Learning

  • Xi, Hongqi;Sun, Huijuan
    • Journal of Information Processing Systems
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    • v.18 no.3
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    • pp.443-456
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    • 2022
  • An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.

Generation of Collaboration Network and Analysis of Researcher's Role in National Cancer Center (협업네트워크 구축과 연구자 역할 분석 -국립암센터 사례 중심으로-)

  • Jang, Hae-Lan
    • The Journal of the Korea Contents Association
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    • v.15 no.10
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    • pp.387-399
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    • 2015
  • Recently collaboration network is generated to find out experts in their field as potential collaborators in health care sector. In this paper, the co-author network of a National Cancer Center researcher was generated for identifying each researcher's role and collaborative research pattern. The co-author network of 2,437 authors was extracted from 1,194 SCI(E) publications from 2000 to 2010 and author's role was analyzed by author's centrality value. Centrality reflecting only the number of papers and centrality weighted by the paper number, impact factor, and authorship contribution was evaluated. On the comparison with simple degree centrality value and the weighted degree centrality, difference of value was statistically significant(t=11.66, p=0.00). Co-author network considering various variables of the paper provides more objective figure of researcher's role. This suggests that co-author network could be more effective in identifying potential collaborators.

A Exploratory Study on Analyzing the Multi-Dimensional Effectiveness of Broadband Network of Korea (국내 초고속정보통신망의 파급효과분석에 관한 탐색적 연구)

  • Jeong, Yong-Gwan;Kim, Yoo-Jung
    • Information Systems Review
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    • v.6 no.2
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    • pp.1-24
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    • 2004
  • This paper develops a framework for analyzing the effectiveness of broadband network from the value chain view. The value chain of broadband network is composed of activities such as broadband network building, application/equipments development, information systems utilization. The effectiveness from the interaction between these activities are defined as the effectiveness of informatization(private and public sector) and the effectiveness of IT Industry(effects on production on inducement of broadband carriers, IT equipments and service market creation, online digital contents market creation). For testing its real-world applicability, a case study is performed on the broadband network of Korea and the effectiveness of the framework for analyzing the effectiveness of broadband network is demonstrated.

Analysis on Continuous Usage Intention of Chinese Mobile Games from the Perspective of Experiential Marketing and Network Externality

  • Lei, Bo;Lee, Jungmann
    • Journal of Information Technology Applications and Management
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    • v.27 no.6
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    • pp.197-224
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    • 2020
  • Mobile games have become one of the most important driving forces of the game industry. We focus on the continuous intention to use Chinese mobile games from the perspective of experiential marketing and network externalities. We integrate user experience, network externalities and flow theory into expectation confirmation model and explore the influencing factors of continuous usage intention of Chinese mobile game and propose a research model. Game experience, service experience, perceived enjoyment, social interaction, challenge, perceived number of users and perceived number of peers were employed as independent variables, while flow, perceived value and satisfaction as mediating variables and continuous intention as the dependent variable. After surveying 426 samples, the model is tested with structural equation model. The results reveal that perceived enjoyment significantly positively influences perceived value, flow, satisfaction, and continuous intention. The greater the enjoyment of the game, the greater the satisfaction of the game and the greater the willingness to use it continuously. Game experience has a significant direct effect on continuous intention, which indicates that a better game experience can retain more users. Service experience and perceive number of peers positively influence satisfaction. Another finding is that social interaction and perceived number of users positively influence perceived value and flow, which indicate that social attributes are critical roles for retaining users. Game challenge also positively influences flow. The proper level of challenge is more likely to cause users to enter the state of flow. Flow indirectly influences continuous usage intention through the satisfaction of the game, which indicates that satisfaction is driven by flow experience and further retaining users. Empirical results implied that mobile game companies need to focus on improving user experience, expectation satisfaction and extending network externalities to improve the continuous intention of using mobile game.

Classification of ECG arrhythmia using Discrete Cosine Transform, Discrete Wavelet Transform and Neural Network (DCT, DWT와 신경망을 이용한 심전도 부정맥 분류)

  • Yoon, Seok-Joo;Kim, Gwang-Jun;Jang, Chang-Soo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.4
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    • pp.727-732
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    • 2012
  • This paper presents an approach to classify normal and arrhythmia from the MIT-BIH Arrhythmia Database using Discrete Cosine Transform(DCT), Discrete Wavelet Transform(DWT) and neural network. In the first step, Discrete Cosine Transform is used to obtain the representative 15 coefficients for input features of neural network. In the second step, Discrete Wavelet Transform are used to extract maximum value, minimum value, mean value, variance, and standard deviation of detail coefficients. Neural network classifies normal and arrhythmia beats using 55 numbers of input features, and then the accuracy rate is 98.8%.

Social Network Services and Performing Arts: Value and potential of its application (소셜 네트워크 서비스와 공연예술: 활용가치와 가능성)

  • Choi, Hyun Ju;Ahn, Byung Ju
    • Knowledge Management Research
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    • v.12 no.5
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    • pp.59-69
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    • 2011
  • The popularity of the social media has enabled growth of the social network, which has a big impact on culture and arts sector. The impact is based on the fact that news and evaluation of performances are communicated actively through the use of on-line community, and that the advent of social commerce makes more people see better performance at a lower price. Besides, collaboration programs called Social Sourcing are springing up in the arts sector, and there is Crowd Funding for culture & arts which is a desirable form of social funding. In this way social media and social network service (SNS) have huge social influence not only on the performing arts sector but also on the whole culture and arts sector, and are expected to have growing dominance. With SNS - which opened new marketing, publicity and donation system not only for the whole society but also for the culture and arts sector - in mind, this paper handles the topics on understanding of close relationship between SNS and performing arts, and on its current usage, value and endless possibilities. By presenting the practical value and the possibilities, this paper will help in making smooth the communication between stakeholders and audience of performing arts, in making effective the means of performance delivery, and in making enlarged the mutual understanding between performers and audience. This paper will also be the basis of an alternative means, which presents the performing arts sector with possibilities to get out of the chronic deficit.

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A Study on the Optimum Mix Design Model of 100MPa Class Ultra High Strength Concrete using Neural Network (신경망 이론을 이용한 100MPa급 초고강도 콘크리트의 최적 배합설계모델에 관한 연구)

  • Kim, Young-Soo;Shin, Sang-Yeop;Jeong, Euy-Chang
    • Journal of the Regional Association of Architectural Institute of Korea
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    • v.20 no.6
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    • pp.17-23
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    • 2018
  • The purpose of this study is to suggest 100MPa class ultra high strength concrete mix design model applying neural network theory, in order to minimize an effort wasted by trials and errors method until now. Mix design model was applied to each of the 70 data using binary binder, ternary binder and quaternary binder. Then being repeatedly applied to back-propagation algorithm in neural network model, optimized connection weight was gained. The completed mix design model was proved, by analyzing and comparing to value predicted from mix design model and value measured from actual compressive strength test. According to the results of this study, more accurate value could be gained through the mix design model, if error rate decreases with the test condition and environment. Also if content of water and binder, slump flow, and air content of concrete apply to mix design model, more accurate and resonable mix design could be gained.

Application of the Recursive Contract Net Protocol for the Threshold Value Determination in Wireless Sensor Networks (무선 센서 네트워크에서 경계값 결정을 위한 재귀적 계약망 프로토콜의 적용)

  • Seo, Hee-Suk
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.19 no.4
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    • pp.41-49
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    • 2009
  • In ubiquitous sensor networks, sensor nodes can be compromised by an adversary since they are deployed in hostile environments. False sensing reports can be injected into the network through these compromised nodes, which may cause not only false alarms but also the depletion of limited energy resource in the network. In the security solutions for the filtering of false reports, the choice of a security threshold value which determines the security level is important. In the existing adaptive solutions, a newly determined threshold value is broadcasted to the whole nodes, so that extra energy resource may be consumed unnecessarily. In this paper, we propose an application of the recursive contract net protocol to determine the threshold value which can provide both energy efficiency and sufficient security level. To manage the network more efficiently, the network is hierarchically grouped, and the contract net protocol is applied to each group. Through the protocol, the threshold value determined by the base station using a fuzzy logic is applied only where the security attack occurs on.