A critical examination of node-similarity based graph matching algorithms

In this paper, we shall critically examine a special class of graph matching algorithms that follow the approach of node-similarity measurement. A high-level algorithm framework, namely node-similarity graph matching framework (NSGM framework), is proposed, from which, many existing graph matching algorithms can be subsumed, including the eigen-decomposition method of Umeyama, the polynomial-transformation method of Almohamad, the hubs and authorities method of Kleinberg, and the kronecker product successive projection methods of Wyk, etc. In addition, improved algorithms can be developed from the NSGM framework with respects to the corresponding results in graph theory. As the observation, it is pointed out that, in general, any algorithm which can be subsumed from NSGM framework fails to work well for graphs with non-trivial auto-isomorphism structure.

Environmental science and sustainability: some critical thoughts

Environmental science is often described as an interdisciplinary subject, but one firmly grounded in positivist science. Less well recognized is the idea that interdisciplinarity actually challenges fundamental conceptions concerning how reality is understood from an orthodox science perspective. Drawing on recent non-dualism (or post-natural) literature, it is suggested in this paper that there is a need for greater awareness and debate concerning the underlying challenges that ideas of interdisciplinarity and holism present for environmental science. It is argued by aligning environmental science more strongly with non-dualistic traditions (spanning the sciences, arts and religion), fundamental issues are raised concerning how reality is understood and what constitutes valid research methodologies. The concept of intrinsic value is used as one example of the way non-dualistic theory can open up new territories for exploring reality.