Computational Intelligence and Efficiency in Engineering by Grzegorz Borowik, Zenon Chaczko, Witold Jacak, Tadeusz Łuba

By Grzegorz Borowik, Zenon Chaczko, Witold Jacak, Tadeusz Łuba

This rigorously edited and reviewed quantity addresses the more and more well known call for for looking extra readability within the facts that we're immersed in. It bargains first-class examples of the clever ubiquitous computation, in addition to contemporary advances in platforms engineering and informatics. The content material represents state of the art foundations for researchers within the area of contemporary computation, desktop technology, approach engineering and networking, with many examples which are set in commercial program context. The ebook comprises the rigorously chosen most sensible contributions to APCASE 2014, the second Asia-Pacific convention on machine Aided method Engineering, held February 10-12, 2014 in South Kuta, Bali, Indonesia. The ebook contains 4 major elements that disguise data-oriented engineering technological know-how examine in a variety of purposes: computational versions and data discovery; communications networks and cloud computing; computer-based structures; and data-oriented and software-intensive structures.

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Keywords Knowledge representation · Description logics · Knowledge cartography · Logic synthesis · Boolean function complement G. pl D. com © Springer International Publishing Switzerland 2015 G. Borowik et al. 1007/978-3-319-15720-7_3 33 34 G. Borowik and D. 1 Introduction Knowledge Representation (KR) is a field of Artificial Intelligence which focuses on inventing and developing of languages and formalisms that allow capturing knowledge about the world. It typically depicts objects, object relations, types of objects, and rules/axioms that describe laws and constraints existing within the world.

Therefore, the powerful algorithm of the previous subsection can be implemented using OpenCL. The execution of both the CUDA and the OpenCL implementation of the same algorithm on the same GPU allows a comparison of the influence of these APIs to the needed runtime. Using Algorithm 2 to realize the main step 6 of Algorithm 1, an OpenCL program was implemented in [7]. The advantage of this OpenCL implementation is that it 26 B. Steinbach and M. Werner can be used for different GPUs and even for multi-core CPUs.

However, non-recursive procedure cannot handle large taxonomies (depends on division factor) and some way of divideand-conquer procedure is required. • Similarly to TreeFusion algorithm [23], the recursive procedure applying the Complement algorithm benefits from good scalability (for large taxonomical ontologies). It’s due to the fact that both methods use similar partitioning procedure with fast graph partitioning. • It has been confirmed that Knowledge Cartography using Complement algorithm manifests itself as a good method for ontologies that are taxonomies.

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