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Titlebook: Enterprise Information Systems; 24th International C Joaquim Filipe,Michał Śmiałek,Slimane Hammoudi Conference proceedings 2023 The Editor(

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https://doi.org/10.1007/978-3-319-29899-3ualize large data sets, do not support all common sensor data forms and offer little support for efficient labeling of large data volumes. In this paper, we build on our previously presented visual interactive labeling tool Gideon-TS that is designed for handling large data sets of industrial sensor
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https://doi.org/10.1007/978-1-4684-2502-4area. To create dataset Microsoft Azure Translation was chosen as the reference translation with manual translation verification for grammar. Translations produced by each model were compared with the reference translation using two metrics: BLEU and METEOR. The possibility of fast fine-tuning of mo
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Sanford B. Krantz,S. Donald Zaentzspecifications, (3) requirements specifications, (4) virtual thing search, as a constraint satisfaction problem, (5) compositions of virtual things that are mutually consistent, Pareto-optimal against requirements specifications, and optimal against customer utility function expressed in terms of cu
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Alessandra Diazzi,Alvise Sforza Tarabochiaity of its semantic constructs. The results showed a very good user performance in explaining and creating task models using SERIES. These results were reflected in the feedback of the participants and the activities that they performed using SERIES.
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