Analysis of robustness of urban bus network

任涛,; 王一帆,; 刘苗苗,; 徐艳杰,

doi:10.1088/1674-1056/25/2/020101

Cited by 41 publications

(16 citation statements)

References 37 publications

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“…In Figure 3, we show an example for a DEG-based attack to a network. Some of the studies [76,77] only evaluate DEG of nodes for designing a targeted attack, e.g., stating that "for the selective attack strategy, we remove some nodes with higher degrees according to their degree order from high to low" [77]. Others compare a set of few static network metrics, but without considering interactive/iterative/dynamic metrics sufficiently for much stronger attacks [26,[78][79][80][81][82] (see Section 4.2 for further discussion).…”

Section: Common Pitfalls and Misleading Interpretationsmentioning

confidence: 99%

Studying the Topology of Transportation Systems through Complex Networks: Handle with Care

Zanin

Sun

Wandelt

2018

Journal of Advanced Transportation

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The introduction of complex network concepts in the study of transportation systems has supposed a paradigm shift and has allowed understanding different transport phenomena as the emergent result of the interactions between the elements composing them. In spite of several notable achievements, lurking pitfalls are undermining our understanding of the topological characteristics of transportation systems. In this study, we analyse four of the most common ones, specifically related to the assessment of the scale-freeness of networks, the interpretation and comparison of topological metrics, the definition of a node ranking, and the analysis of the resilience against random failures and targeted attacks. For each topic we present the problem from both a theoretical and operational perspective, for then reviewing how it has been tackled in the literature and finally proposing a set of solutions. We further use six real-world transportation networks as case studies and discuss the implications of these four pitfalls in their analysis. We present some future lines of work that are stemming from these pitfalls and that will allow a deeper understanding of transportation systems from a complex network perspective.

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Section: Common Pitfalls and Misleading Interpretationsmentioning

confidence: 99%

Studying the Topology of Transportation Systems through Complex Networks: Handle with Care

Zanin

Sun

Wandelt

2018

Journal of Advanced Transportation

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Section: Introductionmentioning

confidence: 99%

“…Diffusion weighted imaging (DWI) has been applied to diagnosis of diseases, including HAE, in abdominal organs [ 6 – 9 ]. In a comparative study between DWI and histopathological features of HAE, Ren et al, found a significant negative correlation between apparent diffusion coefficient (ADC) values and percentage of HAE fibrosis in the peripheral area [ 9 ]. In recent years, intravoxel incoherent motion diffusion weighted magnetic resonance imaging (IVIM DW MRI), which was first described by Le Bihan et al [ 10 ], has been applied in the clinical diagnosis of HAE.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance (MR) Imaging to T1 Mapping in Characterization of Hepatic Alveolar Echinococcosis

2017

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BackgroundThe aim of this study was to compare intravoxel incoherent motion diffusion-weighted magnetic resonance imaging (IVIM DW MRI) to T1 mapping for characterization of hepatic alveolar echinococcosis (HAE).Material/MethodsEighteen HAE patients confirmed by surgery were examined with conventional MRI, IVIM DWI MRI with 10 b values (range: 0–1,000 sec/mm2), and longitudinal relaxation time (T1) mapping. Diffusion coefficient (D), perfusion fraction (f), pseudo-diffusion coefficient (D*), and T1 relaxation time were calculated in solid components, perilesional components, and background liver parenchyma of HAE patients. The correlation between T1 relaxation time and IVIM-derived parameters was assessed by using the Pearson correlation test.ResultsT1 relaxation times were significantly higher in solid components (820.58±331.24 ms) compared to background components (551.52±182.93 ms) of HAE patients (p<0.05). IVIM-derived D values were significantly higher in solid components (1.30±0.28×10−3 mm2/sec) compared to perilesional components (0.88±0.28×10−3 mm2/sec) and background liver parenchyma (0.97±0.27×10−3 mm2/sec) of liver parenchyma. There were significant differences in f values between solid components (13.70±7.66%), perilesional components (23.59±10.73%) and background liver parenchyma (30.78±10.18%). IVIM derived D* values were significantly lower in solid components (14.32±10.85×10−3 mm2/sec) than in background liver parenchyma (30.06±15.68×10−3 mm2/sec). Importantly, IVIM-derived f values were significantly correlated with T1 relaxation time: r=−0.337 (p<0.05).ConclusionsBased on our image comparison, IVIM DWI MRI might be better than T1 mapping, and IVIM-derived f values might be a valuable index for characterization of HAE.

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“…Introduction. Complex network are widely used in the real world, like music field [11], urban transport field [12]. In recent years, a variety of online social networks grow rapidly, such as Facebook, weibo and WeChat [17].…”

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confidence: 99%

Rumor propagation controlling based on finding important nodes in complex network

Jia¹,

Liu²,

Zhang³

et al. 2020

Journal of Industrial &Amp; Management Optimization

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The rumor propagation analysis and important nodes detection is a hot topic in complex network under crisis situation. The traditional propagation model does not consider enough states, so it cannot intact reflect the real world. In this paper, a new rumor propagation model which considers the Wiseman and the Truth Spreader is proposed based on the Graph Theory. Then, 3 new methods are proposed to find important nodes in the new model. These methods consider the differences between nodes to evaluate the importance of the nodes. Finally, 4 networks are demonstrated to show that the 3 proposed methods are useful to control rumor propagation.

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Analysis of robustness of urban bus network

Cited by 41 publications

References 37 publications

Studying the Topology of Transportation Systems through Complex Networks: Handle with Care

Studying the Topology of Transportation Systems through Complex Networks: Handle with Care

Comparison of Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance (MR) Imaging to T1 Mapping in Characterization of Hepatic Alveolar Echinococcosis

Rumor propagation controlling based on finding important nodes in complex network

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