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Titlebook: Databases and Information Systems; 13th International B Audrone Lupeikiene,Olegas Vasilecas,Gintautas Dzem Conference proceedings 2018 Spri

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51#
發(fā)表于 2025-3-30 09:34:57 | 只看該作者
Environmental Management in China and Taiwanto explore discrepancy between (a) the high degree of availability of e-services in Latvia, and (b) low usage of these e-services among population. We aim to find the regularities regarding color preferences that could be useful in the development of e-services and that could support the rise of the
52#
發(fā)表于 2025-3-30 15:33:47 | 只看該作者
https://doi.org/10.1057/9780230514225. An algorithm allowing to decrease a number of calls to failed provider nodes is proposed. It is designed for a clustered client and is based on an asynchronous communication. A formal specification of the algorithm is formulated in the TLA. language and was used to investigate the correctness of t
53#
發(fā)表于 2025-3-30 18:23:14 | 只看該作者
54#
發(fā)表于 2025-3-30 23:27:39 | 只看該作者
https://doi.org/10.1007/978-3-540-70818-6 that may not be suitably addressed by traditional centralized test architectures. In this paper, a distributed test framework for testing distributed real-time systems is presented, where online monitors (executable code as annotations) are integrated to systems to record relevant events. The propo
55#
發(fā)表于 2025-3-31 01:32:00 | 只看該作者
Walther Ch Zimmerli,Michael S. Assl?nderhe expression of the product variant knowledge and its validation very important. In this paper, we express knowledge of product variants as domain ontology in order to capture the product knowledge in the way that is consistent and shareable between humans and machines. Using Ontology Web Language
56#
發(fā)表于 2025-3-31 06:22:55 | 只看該作者
57#
發(fā)表于 2025-3-31 12:58:35 | 只看該作者
https://doi.org/10.1007/978-3-319-97571-9artificial intelligence; big data; clustering; cognitive computing; databases; data mining; information sy
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