We present a frame-invariant method for detecting coherent structures from Lagrangian flow trajectories that can be sparse in number, as is the case in many fluid mechanics applications of practical interest. The method, based on principles used in graph coloring and spectral graph drawing algorithms, examines a measure of the kinematic dissimilarity of all pairs of fluid trajectories, either m...

Recently, Borgatti [Borgatti, S.P., 2005. Centrality and network flow. Social Networks 27, 55–71] proposed a taxonomy of centrality measures based on the way that traffic flows through the network—whether over path, geodesic, trail, or walk, and whether by means of transfer, serial duplication, or parallel duplication. Most of the extant centrality measures assume that traffic propagates via pa...

This paper introduces a semantic representation for virtual prototyping in interactive virtual construction applications. The representation reflects semantic information about dynamic constraints to define objects’ modification and construction behavior as well as knowledge structures supporting multimodal interaction utilizing speech and gesture. It is conveniently defined using XML-based mar...

We present a frame-invariant method for detecting coherent structures from Lagrangian flow trajectories that can be sparse in number, as is the case in many fluid mechanics applications of practical interest. The method, based on principles used in graph colouring and spectral graph drawing algorithms, examines a measure of the kinematic dissimilarity of all pairs of fluid trajectories, measure...

In this paper we present the novel graph mining algorithm Edgar which is based on the well-known gSpan algorithm. The need for another subgraph miner results from procedural abstraction (an important technique to reduce code size in embedded systems). Assembler code is represented as a data flow graph and subgraph mining on this graph returns frequent code fragments that can be extracted into p...

In order to improve system performance efficiently, a number of systems choose to equip multi-core and many-core processors (such as GPUs). Due to their discrete memory these heterogeneous architectures comprise a distributed system within a computer. A data-flow programming model is attractive in this setting for its ease of expressing concurrency. Programmers only need to define task dependen...

Graph mining and management has become an important topic of research recently because of numerous applications to a wide variety of data mining problems in computational biology, chemical data analysis, drug discovery and communication networking. Traditional data mining and management algorithms such as clustering, classification, frequent pattern mining and indexing have now been extended to...

In recent years, privacy concerns about social network graph data publishing has increased due to the widespread use of such data for research purposes. This paper addresses the problem of identity disclosure risk of a node assuming that the adversary identifies one of its immediate neighbors in the published data. The related anonymity level of a graph is formulated and a mathematical model is...

Authority flow techniques like PageRank and ObjectRank can provide personalized ranking of typed entity-relationship graphs. There are two main ways to personalize authority flow ranking: Nodebased personalization, where authority originates from a set of userspecific nodes; Edge-based personalization, where the importance of different edge types is user-specific. We propose for the first time ...