Results 51 to 60 of about 7,824,399 (323)
Identification of nodes influence based on global structure model in complex networks
Scientific Reports, 2021 Identification of Influential nodes in complex networks is challenging due to the largely scaled data and network sizes, and frequently changing behaviors of the current topologies. Various application scenarios like disease transmission and immunization,
Aman Ullah +5 more
doaj +1 more source
Fast Shortest Path Distance Estimation in Large Networks [PDF]
, 2009 We study the problem of preprocessing a large graph so that point-to-point shortest-path queries can be answered very fast. Computing shortest paths is a well studied problem, but exact algorithms do not scale to huge graphs encountered on the web ...
Castillo, Carlos +3 more
core +2 more sources
The von Neumann Theil index: characterizing graph centralization using the von Neumann index [PDF]
Journal of Complex Networks, 2018 We show that the von Neumann entropy (from herein referred to as the von Neumann index) of a graph’s trace normalized combinatorial Laplacian provides structural information about the level of centralization across a graph. This is done by considering the Theil index, which is an established statistical measure used to determine levels of inequality ...
Simmons, D, Coon, J, Datta, A
openaire +3 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The Improving Population Outcomes for Renal Tumours of childhood (IMPORT) is a prospective clinical observational study capturing detailed demographic and outcome data on children and young people diagnosed with renal tumours in the United Kingdom and the Republic of Ireland.
Naomi Ssenyonga +56 more
wiley +1 more source
InsectsLand maxing in cultivated ecosystems can improve upon other agroecological approaches because in this approach social, economic and ecological benefits are maximized within the available land, in part through the careful selection of plant species with ...
Valerie E. Peters, Elijah Cruz Cardona
doaj +1 more source
Fast computing betweenness centrality with virtual nodes on large sparse networks. [PDF]
PLoS ONE, 2011 Betweenness centrality is an essential index for analysis of complex networks. However, the calculation of betweenness centrality is quite time-consuming and the fastest known algorithm uses O(N(M + N log N)) time and O(N + M) space for weighted networks,
Jing Yang, Yingwu Chen
doaj +1 more source
A faster algorithm for betweenness centrality
, 2001 Motivated by the fast‐growing need to compute centrality indices on large, yet very sparse, networks, new algorithms for betweenness are introduced in this paper.
U. Brandes
semanticscholar +1 more source
Cancer Medicine, 2021 To parallelly compare the applicability of the radius, exophytic/endophytic, nearness, anterior/posterior, location nephrometry score (R.E.N.A.L.), the Preoperative Aspects and Dimensions Used for an Anatomical (PADUA), and the centrality index (C‐index)
Can Hu +7 more
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction We developed MedSupport, a multilevel medication adherence intervention designed to address root barriers to medication adherence. This study sought to explore the feasibility and acceptability of the MedSupport intervention strategies to support a future full‐scale randomized controlled trial.
Elizabeth G. Bouchard +8 more
wiley +1 more source
Identifying influential spreaders in complex networks by an improved gravity model
Scientific Reports, 2021 Identification of influential spreaders is still a challenging issue in network science. Therefore, it attracts increasing attention from both computer science and physical societies, and many algorithms to identify influential spreaders have been ...
Zhe Li, Xinyu Huang
doaj +1 more source