Robust network flow against attackers with knowledge of routing method

Suppakitpaisarn, Vorapong; Dai, Wenkai; Baffier, Jean-François

doi:10.1109/hpsr.2015.7483079

Cited by 4 publications

(1 citation statement)

References 25 publications

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“…In response to policy guidance, colleges and universities have established various CIL platforms to help students improve their innovation ability and realize the agglomeration and accumulation of innovation resources [1][2][3][4][5][6][7]. The knowledge stored on CIL platforms is an important component of CIL resources for college students, and the knowledge flow is a kind of explicit behavior of college students during their CIL process [8][9][10][11][12][13][14][15][16]. However, existing CIL platforms for college students generally have unsolved issues such as the cooperation of CIL only stays at a low level, the inefficient knowledge flow, and the unsmooth communication between innovation participants [17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

The Multi-Factor Action Mechanism of Knowledge Flow on Collaborative Innovative Learning Platforms for College Students

Shi¹

2022

Int. J. Emerg. Technol. Learn.

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Knowledge flow is an explicit behavior of college students during their Collaborative Innovative Learning (CIL). Existing studies on the management mechanism of knowledge flow on CIL platforms generally lack a systematic theoretical analysis on the action mechanism of the influencing factors, few scholars have viewed the problems of the management mechanism of knowledge flow, the action mechanisms of the influencing factors of knowledge flow, the efficiency of knowledge flow, and the relationship among them from the perspective of the platform, and few studies have discussed the impact of the management mechanism of CIL platforms on the knowledge flow from a dynamic angle. To fill in these research blanks, this paper aims to analyze the multi-factor action mechanism of knowledge flow on CIL platforms for college students. At first, this paper elaborated on the formation mechanism of the CIL network, and measured model variables of the proposed network; then, it analyzed the robustness of the functions of the proposed network based on knowledge flow; at last, this paper gave the multi-factor variable analysis results of the model.

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