926 resultados para Ontology matching
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Two types of ecological thresholds are now being widely used to develop conservation targets: breakpoint-based thresholds represent tipping points where system properties change dramatically, whereas classification thresholds identify groups of data points with contrasting properties. Both breakpoint-based and classification thresholds are useful tools in evidence-based conservation. However, it is critical that the type of threshold to be estimated corresponds with the question of interest and that appropriate statistical procedures are used to determine its location. On the basis of their statistical properties, we recommend using piecewise regression methods to identify breakpoint-based thresholds and discriminant analysis or classification and regression trees to identify classification thresholds.
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In all biological processes, protein molecules and other small molecules interact to function and form transient macromolecular complexes. This interaction of two or more molecules can be described by a docking event. Docking is an important phase for structure-based drug design strategies, as it can be used as a method to simulate protein-ligand interactions. Various docking programs exist that allow automated docking, but most of them have limited visualization and user interaction. It would be advantageous if scientists could visualize the molecules participating in the docking process, manipulate their structures and manually dock them before submitting the new conformations to an automated docking process in an immersive environment, which can help stimulate the design/docking process. This also could greatly reduce docking time and resources. To achieve this, we propose a new virtual modelling/docking program, whereby the advantages of virtual modelling programs and the efficiency of the algorithms in existing docking programs will be merged.
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The frequency responses of two 50 Hz and one 400 Hz induction machines have been measured experimentally over a frequency range of 1 kHz to 400 kHz. This study has shown that the stator impedances of the machines behave in a similar manner to a parallel resonant circuit, and hence have a resonant point at which the Input impedance of the machine is at a maximum. This maximum impedance point was found experimentally to be as low as 33 kHz, which is well within the switching frequency ranges of modern inverter drives. This paper investigates the possibility of exploiting the maximum impedance point of the machine, by taking it into consideration when designing an inverter, in order to minimize ripple currents due to the switching frequency. Minimization of the ripple currents would reduce torque pulsation and losses, increasing overall performance. A modified machine model was developed to take into account the resonant point, and this model was then simulated with an inverter to demonstrate the possible advantages of matching the inverter switching frequency to the resonant point. Finally, in order to experimentally verify the simulated results, a real inverter with a variable switching frequency was used to drive an induction machine. Experimental results are presented.
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Here we introduce a computer database that allows for the rapid retrieval of physicochemical properties, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes information about a protein or a list of proteins. We applied PIGOK analyzing Schizosaccharomyces pombe proteins displaying differential expression under oxidative stress and identified their biological functions and pathways. The database is available on the Internet at http://pc4-133.ludwig.ucl.ac.uk/pigok.html.
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An approach to the automatic generation of efficient Field Programmable Gate Arrays (FPGAs) circuits for the Regular Expression-based (RegEx) Pattern Matching problems is presented. Using a novel design strategy, as proposed, circuits that are highly area-and-time-efficient can be automatically generated for arbitrary sets of regular expressions. This makes the technique suitable for applications that must handle very large sets of patterns at high speed, such as in the network security and intrusion detection application domains. We have combined several existing techniques to optimise our solution for such domains and proposed the way the whole process of dynamic generation of FPGAs for RegEX pattern matching could be automated efficiently.
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This paper argues the need for the information communication technology (ICT), labor exchange (job boards), and Human Capital ontology engineers (ontoEngineers) to jointly design and socialize an upper level meta-ontology for people readiness and career portability. These enticing ontology research topics have yielded "independent" results, but have yet to meet the more broader or "universal" requirement that emerging frameworks demand. This paper will focus on the need to universally develop an upper level ontology and provide the reader concepts and models that can be transformed into marketable solutions.
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In this paper, we introduce two kinds of graphs: the generalized matching networks (GMNs) and the recursive generalized matching networks (RGMNs). The former generalize the hypercube-like networks (HLNs), while the latter include the generalized cubes and the star graphs. We prove that a GMN on a family of k-connected building graphs is -connected. We then prove that a GMN on a family of Hamiltonian-connected building graphs having at least three vertices each is Hamiltonian-connected. Our conclusions generalize some previously known results.
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It is problematic to use standard ontology tools when describing vague domains. Standard ontologies are designed to formally define one view of a domain, and although it is possible to define disagreeing statements, it is not advisable, as the resulting inferences could be incorrect. Two different solutions to the above problem in two different vague domains have been developed and are presented. The first domain is the knowledge base of conversational agents (chatbots). An ontological scripting language has been designed to access ontology data from within chatbot code. The solution developed is based on reifications of user statements. It enables a new layer of logics based on the different views of the users, enabling the body of knowledge to grow automatically. The second domain is competencies and competency frameworks. An ontological framework has been developed to model different competencies using the emergent standards. It enables comparison of competencies using a mix of linguistic logics and descriptive logics. The comparison results are non-binary, therefore not simple yes and no answers, highlighting the vague nature of the comparisons. The solution has been developed with small ontologies which can be added to and modified in order for the competency user to build a total picture that fits the user’s purpose. Finally these two approaches are viewed in the light of how they could aid future work in vague domains, further work in both domains is described and also in other domains such as the semantic web. This demonstrates two different approaches to achieve inferences using standard ontology tools in vague domains.