74 resultados para KNOWLEDGE REPRESENTATION AND REASONING
Resumo:
This paper highlights the importance of design expertise, for designing liquid retaining structures, including subjective judgments and professional experience. Design of liquid retaining structures has special features different from the others. Being more vulnerable to corrosion problem, they have stringent requirements against serviceability limit state of crack. It is the premise of the study to transferring expert knowledge in a computerized blackboard system. Hybrid knowledge representation schemes, including production rules, object-oriented programming, and procedural methods, are employed to express engineering heuristics and standard design knowledge during the development of the knowledge-based system (KBS) for design of liquid retaining structures. This approach renders it possible to take advantages of the characteristics of each method. The system can provide the user with advice on preliminary design, loading specification, optimized configuration selection and detailed design analysis of liquid retaining structure. It would be beneficial to the field of retaining structure design by focusing on the acquisition and organization of expert knowledge through the development of recent artificial intelligence technology. (C) 2003 Elsevier Ltd. All rights reserved.
Resumo:
The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.
Resumo:
After providing some brief background on Dendrolagus species in Australia, two consecutive surveys of Brisbane’s residents are used to assess public knowledge of tree-kangaroos and the stated degree of support for their conservation in Australia. The responses of participants in Survey I are based on their pre-survey knowledge of wildlife. The same additional set of participants completed Survey II after being provided with information on all the wildlife species mentioned in Survey I. Changes in the attitudes of respondents and their degree of support for the protection and conservation of Australia’s tree-kangaroos are measured, including changes in their contingent valuations and stated willingness to provide financial support for such conservation. Reasons for wanting to protect tree-kangaroos are specified and analyzed. Furthermore, changes that occur in the relative importance of these reasons with increased knowledge are also examined. Support for the conservation of tree-kangaroos is found to increase with the additional knowledge supplied. Furthermore, support for the conservation of Australia’s less well-known tropical mammals is shown to increase relative to better known mammals (icons) present in temperate areas, such as koalas and red kangaroos with this increased knowledge. Possible implications of the results for government conservation policies in Australia are examined.
Resumo:
Motivated by application of twisted current algebra in description of the entropy of Ads(3) black hole, we investigate the simplest twisted current algebra sl(3, c)(k)((2)). Free field representation of the twisted algebra, and the corresponding twisted Sugawara energy-momentum tensor are obtained by using three (beta, gamma) pairs and two scalar fields. Primary fields and two screening currents of the first kind are presented. (C) 2001 Published by Elsevier Science B.V.
Resumo:
We compare the performance of two different low-storage filter diagonalisation (LSFD) strategies in the calculation of complex resonance energies of the HO2, radical. The first is carried out within a complex-symmetric Lanczos subspace representation [H. Zhang, S.C. Smith, Phys. Chem. Chem. Phys. 3 (2001) 2281]. The second involves harmonic inversion of a real autocorrelation function obtained via a damped Chebychev recursion [V.A. Mandelshtam, H.S. Taylor, J. Chem. Phys. 107 (1997) 6756]. We find that while the Chebychev approach has the advantage of utilizing real algebra in the time-consuming process of generating the vector recursion, the Lanczos, method (using complex vectors) requires fewer iterations, especially for low-energy part of the spectrum. The overall efficiency in calculating resonances for these two methods is comparable for this challenging system. (C) 2001 Elsevier Science B.V. All rights reserved.
Resumo:
Groupers (Epinephelinae) are prominent marine fishes distributed in the warmer waters of the world. Review of the literature suggests that trematodes are known from only 62 of the 159 species and only 9 of 15 genera; nearly 90% of host-parasite combinations have been reported only once or twice. All 20 families and all but 7 of 76 genera of trematodes found in epinephelines also occur in non-epihephelines. Only 12 genera of trematodes are reported from both the Atlantic-Eastern Pacific and the Indo-West Pacific. Few (perhaps no) species are credibly cosmopolitan but some have wide distributions across the Indo-West Pacific. The hierarchical 'relatedness' of epinephelines as suggested by how they share trematode taxa (families, genera, species) shows little congruence with what is known of their phylogeny. The major determinant of relatedness appears to be geographical proximity. Together these attributes suggest that host-parasite coevolution has contributed little to the evolution of trematode communities of epinephelines. Instead, they appear to have arisen through localized episodes of host-switching, presumably both into and out of the epinephelines. The Epinephelinae may well be typical of most groups of marine fishes both in the extent to which their trematode parasites are known and in that, apparently, co-evolution has contributed little to the evolution of their communities of trematodes.
Resumo:
The long short-term memory (LSTM) is not the only neural network which learns a context sensitive language. Second-order sequential cascaded networks (SCNs) are able to induce means from a finite fragment of a context-sensitive language for processing strings outside the training set. The dynamical behavior of the SCN is qualitatively distinct from that observed in LSTM networks. Differences in performance and dynamics are discussed.