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Titlebook: Model Driven Engineering and Ontology Development; Vladan Deved?ic,Dragan Djuric,Dragan Ga?evic Book 2009Latest edition Springer-Verlag Be

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21#
發(fā)表于 2025-3-25 03:54:07 | 只看該作者
Miroslava Kulkovadifferent classes of dynamic distillation models and various approaches to solving these models will be presented. The author hopes to dispel the myth that modelling and simulation of distillation dynamics must be difficult and complex..Dynamic modelling and simulation has proven to be an insightful
22#
發(fā)表于 2025-3-25 08:42:50 | 只看該作者
Perfect Sampling of Phase-Type Servers Using Bounding Envelopesnetworks. However, the corresponding Markov chains are in most cases very large and hard to solve without the help of an efficient simulation model. A simulation framework, based on perfect sampling, had already been developed to address the evaluation of large queueing models. Perfect sampling enab
23#
發(fā)表于 2025-3-25 14:11:47 | 只看該作者
24#
發(fā)表于 2025-3-25 18:33:05 | 只看該作者
Conducting Creativity Brainstorming Sessions in Small and Medium-Sized Enterprises Using Computer-Mese tools invariably incorporate chat systems that facilitate simultaneous input in synchronous electronic meeting environments, allowing what is referred to as “electronic brainstorming.” Although prior research in information systems (IS) has established that electronic brainstorming can be superio
25#
發(fā)表于 2025-3-25 20:26:46 | 只看該作者
26#
發(fā)表于 2025-3-26 00:20:45 | 只看該作者
27#
發(fā)表于 2025-3-26 05:49:35 | 只看該作者
Andrew Bush MD, FRCP, FRCPCH, FERS, FAPSRfor CTL model update cannot deal with all kinds of model changes. We introduce the concept of CTL model revision: an approach based on belief revision to handle system inconsistency in a static context. We relate our proposal to classical works in belief revision and give an algorithm sketch.
28#
發(fā)表于 2025-3-26 09:13:23 | 只看該作者
29#
發(fā)表于 2025-3-26 13:16:01 | 只看該作者
30#
發(fā)表于 2025-3-26 18:20:57 | 只看該作者
https://doi.org/10.1007/978-3-030-18696-8nts have been conducted on AR database. The preliminary experiment results shows that . is a very robust approach which maintains high recognition performance, and deserves to be investigated with larger dataset.
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