• 제목/요약/키워드: Network NAT

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Linking Social Network to Education: The Potentials and Challenges

  • RHA, Ilju;BYUN, Hyunjung;KIM, Younyoung;HONG, Seoyon
    • Educational Technology International
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    • 제13권1호
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    • pp.1-25
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    • 2012
  • Despite the relatively short history of Social Network Sites or Services (SNS), it has quickly gained popularity with more than seven hundred million users all over the globe. The SNS emerged as one of the strongest cultural influences for the contemporary society. The SNS would provide both chances and challenges for Education. The main purpose of the article was to explore the way education react and adapt to the emergence of social network and SNS. It tried to provide major theoretical grounds that bridge education and social network. In the due process, the researchers have examined the curriculum and instructional design process of education from the perspective of disruptive and sustainable aspect of SNS technology. Consequently, four major theoretical grounds were identified and reviewed: Gibson's theory of affordance, Vygotsky's social constructivism, Rha's human visual intelligence theory, and the network theory. By investigating these theories, the educational potentials of social network and SNS were emerged. The SNS was viewed as a new medium with abundant potentials of expanding the learning space, empowering the affective aspects of learning, and facilitating the formation of group intelligence. Finally, some future implications and challenges of SNS were suggested.

Dissolved Gas Analysis of Power Transformer Using Fuzzy Clustering and Radial Basis Function Neural Network

  • Lee, J.P.;Lee, D.J.;Kim, S.S.;Ji, P.S.;Lim, J.Y.
    • Journal of Electrical Engineering and Technology
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    • 제2권2호
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    • pp.157-164
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    • 2007
  • Diagnosis techniques based on the dissolved gas analysis(DGA) have been developed to detect incipient faults in power transformers. Various methods exist based on DGA such as IEC, Roger, Dornenburg, and etc. However, these methods have been applied to different problems with different standards. Furthermore, it is difficult to achieve an accurate diagnosis by DGA without experienced experts. In order to resolve these drawbacks, this paper proposes a novel diagnosis method using fuzzy clustering and a radial basis neural network(RBFNN). In the neural network, fuzzy clustering is effective for selecting the efficient training data and reducing learning process time. After fuzzy clustering, the RBF neural network is developed to analyze and diagnose the state of the transformer. The proposed method measures the possibility and degree of aging as well as the faults occurred in the transformer. To demonstrate the validity of the proposed method, various experiments are performed and their results are presented.

농촌관광개발 이해당사자 분석 방법론 - 사회연결망분석 사례 연구 - (An Alternative Methodology for Stakeholder Analysis in Rural Tourism Development - A Case Study of Social Network Analysis -)

  • 이주연;이영주;이동호
    • 농촌계획
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    • 제11권3호
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    • pp.29-42
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    • 2005
  • This study aimed to apply a methodological approach, 'social network analysis' to a case study for the understanding of relational structure among stakeholders related to green tourism development. By doing so, this study argued that it is important to identify stakeholder's network structure to help green tourism planners develop collaborative relationship among stakeholders. This study identified the stakeholders regarding a community-based festival development in the southern area of Korea, and investigated two types of networks among them: decision-making power relational and intimate network. Interviewer-administrated survey and in-depth interview were employed for data collection. The data was analyzed by SPSS (version 10.0) and Net-MinerII (version 2.5.0), and by constant comparison method. The result revealed that low different groups of the stakeholders were separated in the intimate networt and that the festival organizational body was not connected with other stakeholders in the decision-making power relational network. The existence of separated groups and weak relationship among the stakeholders appeared to relate to age-group differences, and different views on the festival between the stakeholders.

이스트 프로테옴에 대한 단백질-단백질 네트워크의 생물학적 및 물리학적 정보인식 : 라플라스 행렬에 대한 고유치와 섭동분석 (Identifying the biological and physical essence of protein-protein network for yeast proteome : Eigenvalue and perturbation analysis of Laplacian matrix)

  • Chang, Ik-Soo;Cheon, Moo-Kyung;Moon, Eun-Joung;Kim, Choong-Rak
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2004년도 The 3rd Annual Conference for The Korean Society for Bioinformatics Association of Asian Societies for Bioinformatics 2004 Symposium
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    • pp.265-271
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    • 2004
  • The interaction network of protein -protein plays an important role to understand the various biological functions of cells. Currently, the high -throughput experimental techniques (two -dimensional gel electrophoresis, mass spectroscopy, yeast two -hybrid assay) provide us with the vast amount of data for protein-protein interaction at the proteome scale. In order to recognize the role of each protein in their network, the efficient bioinformatical and computational analysis methods are required. We propose a systematic and mathematical method which can analyze the protein -protein interaction network rigorously and enable us to capture the biological and physical essence of a topological character and stability of protein -protein network, and sensitivity of each protein along the biological pathway of their network. We set up a Laplacian matrix of spectral graph theory based on the protein-protein network of yeast proteome, and perform an eigenvalue analysis and apply a perturbation method on a Laplacian matrix, which result in recognizing the center of protein cluster, the identity of hub proteins around it and their relative sensitivities. Identifying the topology of protein -protein network via a Laplacian matrix, we can recognize the important relation between the biological pathway of yeast proteome and the formalism of master equation. The results of our systematic and mathematical analysis agree well with the experimental findings of yeast proteome. The biological function and meaning of each protein cluster can be explained easily. Our rigorous analysis method is robust for understanding various kinds of networks whether they are biological, social, economical...etc

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비선형 신경회로망보상기를 이용한 시변파라미터 적응추정의 자동이득조정 앨고리즘 (A gain self-tuneing algorithm for adaptive estimating or time-varying parameter using nonlinear neural network compansator)

  • 서보혁;전순용
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1992년도 하계학술대회 논문집 A
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    • pp.236-238
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    • 1992
  • This paper proposes a new algorithm to estimate time-varying parameters by combining KFSM(Kalman Filter with Shift Matrix) with neural network compansator. While the time varying parameters are estimated from KFSM, the error coverence of system, R(k) are compansated by neural network concurrently. The casestudy using computer simulation proves the usefullness and advantages of the proposed algorithm in this paper.

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다중고장에 대한 전기 네트워크 구심성 척도 (A Measure of Electric Network Centrality Due to Multiple Contingencies)

  • 로델 도사노;송화창;이병준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.286-287
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    • 2008
  • This paper proposes a power system blackout model and devises a method of identification and selection of higher-order contingencies that may threaten power system security. To study how failures spread in power grids, network observability based on topological concept is utilized which provide a means of monitoring network evolutions due to multiple contingencies. The simulations and results are presented using the IEEE 118-bus test system.

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Fast Color Classifier Using Neural Networks in RGB and YUV Color-Space

  • Lee, Seonghoon;Lee, Minjung;Park, Youngkiu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.109.3-109
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    • 2002
  • 1. Introduction 2. Vision system 3. Effect of brightness variations 4. Color classifier using multi-layer neural network 5. Experimental result of color classifier 6. Applications for robot soccer system 7. Conclusion

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A Navigation Algorithm for Autonomous Mobile Robots Using Artificial Immune Networks and Neural Networks

  • Kim, Insic;Lee, Minjung;Park, Youngkiu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.106.5-106
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    • 2002
  • 1. Introduction 2. Artificial Immune Networks and Navigation Algorithm 3. Obstacle Avoidance and Goal Approach Behavior 4. Weights Adjustment Using Neural Network 5. Velocity Control and Local Minimum Avoidance 6. Simulation 7. Conclusion

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MLP 층을 갖는 CNN의 설계 (Design of CNN with MLP Layer)

  • 박진현;황광복;최영규
    • 한국기계기술학회지
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    • 제20권6호
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    • pp.776-782
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    • 2018
  • After CNN basic structure was introduced by LeCun in 1989, there has not been a major structure change except for more deep network until recently. The deep network enhances the expression power due to improve the abstraction ability of the network, and can learn complex problems by increasing non linearity. However, the learning of a deep network means that it has vanishing gradient or longer learning time. In this study, we proposes a CNN structure with MLP layer. The proposed CNNs are superior to the general CNN in their classification performance. It is confirmed that classification accuracy is high due to include MLP layer which improves non linearity by experiment. In order to increase the performance without making a deep network, it is confirmed that the performance is improved by increasing the non linearity of the network.