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TABLE I RESILIENCE PROVISIONING MODELS IN VIRTUAL NETWORKS

in Resilience-Differentiation in Programmable Virtual Networks
by Filip Rosenbaum, Sanjay Jha, et al.

Table 12: Perturbing relationships: improved resilience.

in ABSTRACT Internet Routing Resilience to Failures: Analysis and Implications
by Jian Wu, Ying Zhang, Z. Morley, Mao Kang, G. Shin
"... In PAGE 10: ... We focus on min-cut analysis under BGP policy restrictions. Table12 presents the min-cut analysis results for 4 rela- tionship perturbation scenarios. Changing peer-peer links to customer-provider/provider-customer links improves the overall network resilience as the perturbed links provides ASes extra flexibility in choosing paths to other networks.... ..."

Table 12: Perturbing relationships: improved resilience.

in ABSTRACT Internet Routing Resilience to Failures: Analysis and Implications
by Jian Wu, Ying Zhang, Z. Morley, Mao Kang, G. Shin
"... In PAGE 10: ... We focus on min-cut analysis under BGP policy restrictions. Table12 presents the min-cut analysis results for 4 rela- tionship perturbation scenarios. Changing peer-peer links to customer-provider/provider-customer links improves the overall network resilience as the perturbed links provides ASes extra flexibility in choosing paths to other networks.... ..."

Table 3. Performance of the Best Neural Network Training Function (Resilient Back Propagation)

in Intrusion Detection Systems Using Adaptive Regression Splines
by Srinivas Mukkamala, Andrew H. Sung, Ajith Abraham, Vitorino Ramos 2004
Cited by 2

Table 3. Performance of the Best Neural Network Training Function (Resilient Back Propagation)

in Intrusion Detection Systems Using Adaptive Regression Splines
by Srinivas Mukkamala, Andrew H. Sung, Ajith Abraham, Vitorino Ramos 2004
Cited by 2

Table 2. SSE values for the SCG and resilient backpropagation learning approaches, varying the training epochs, in the double network

in A Neural Architecture for Segmentation and Modelling of Range Data
by Roberto Pirrone, Antonio Chella

Table 2: Comparison of Distributed Index Structures Range Query Support Interval Representation Re-balancing Resilience Small Networks Large Networks

in Tsar: A two tier sensor storage architecture using interval skip graphs
by Peter Desnoyers, Deepak Ganesan, Prashant Shenoy 2005
Cited by 16

Table 2: Comparison of Distributed Index Structures Range Query Support Interval Representation Re-balancing Resilience Small Networks Large Networks

in Tsar: A two tier sensor storage architecture using interval skip graphs
by Peter Desnoyers, Deepak Ganesan, Prashant Shenoy 2005
Cited by 16

Table 7 ICM Asphalt Material Property Inputs Input Value Coarse aggregate content in asphalt (%) 80 Air content asphalt layer (%) 4 Gravimetric water content of asphalt layer (%) 2 (def) Resilient Modulus: Temperature (F)/Stiffness (psi)

in TABLE OF CONTENTS TABLE OF CONTENTS...............................................................................................................iii LIST OF FIGURES..........................................................................................
by John Harvey, Aimee Chong, Jeffrey Roesler 2000

Table 3.4: Results for the recognition of the numeral from the NIST data set using the resilient back-propagation neural network.

in THE FORMER MEMBERS OF THE VISIELAB
by Complexe Systemen, Promotor Prof, Dr. Dirk, Van Dyck Antwerpen, Frie Van Rossen, Prof Dr, Dirk Van Dyck, Dr. Paul Scheunders, Prof Dr, Marcelo A. F. Gomes, Bart De Boeck, Steve De Backer, Greg Tisson, Jos Rozema, Elke Van De Casteele, Shixin Yu, Eva Bettens, Erik Claes, João Garcia, Piotr Jedrasik, Stefan Livens, Dirk Meersman, Gert Van De Wouwer, Brigitte Debroey, Frie Van Rossen, Isabelle Plassais, Inton Tsang
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