Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022)
(Sprache: Englisch)
This book summarizes the research findings presented at the 2nd International Conference on Novel & Intelligent Digital Systems (NiDS 2022). NiDS 2022 was implemented virtually due to COVID-19 restrictions, on September 29-30, 2022, under the...
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This book summarizes the research findings presented at the 2nd International Conference on Novel & Intelligent Digital Systems (NiDS 2022). NiDS 2022 was implemented virtually due to COVID-19 restrictions, on September 29-30, 2022, under the auspices of the Institute of Intelligent Systems. NiDS lays special emphasis on the novelties of intelligent systems and on the interdisciplinary research which enables, supports, and enhances artificial intelligence (AI) in software development. It promotes high-quality research, creating a forum for the exploration of challenges and new advances in AI, and addresses experts, researchers, and scholars in the fields of artificial and computational intelligence in systems and in computer sciences in general, enabling them to learn more about pertinent, strongly related, and mutually complementary fields. The conference promotes an exchange of ideas, reinforcing and expanding the network of researchers, academics, and market representatives.
Inhaltsverzeichnis zu „Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022) “
Cross-Cutting Support of Decision Making for Forming Personalized Learning Spaces.- Personalized Learning in an Intelligent Educational System.- Electronic-Service Learning to Sustain Instruction with Civic Engagement during the COVID-19 Pandemic.- Evaluating E-Learning Process on Virtual Classroom Systems using an ISO-based model.- SERVE as instructional design for low-connectivity online self-directed modules.- From Threads to Textiles: Building an Ontology for the Indigenous Fabrics of the Ifugao.- TraCon: A novel dataset for real-time traffic cones detection using deep learning.- A Comparison of Machine Learning Methods for Modeling Dengue Incidence in Local Communities.
Bibliographische Angaben
- 2022, 1st ed. 2023, XVII, 402 Seiten, 136 farbige Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Akrivi Krouska, Christos Troussas, Jaime Caro
- Verlag: Springer, Berlin
- ISBN-10: 3031176006
- ISBN-13: 9783031176005
Sprache:
Englisch
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