Buch, Englisch, Band 1243, 539 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1091 g
Proceedings of ICCDN 2024, Volume 1
Buch, Englisch, Band 1243, 539 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1091 g
Reihe: Lecture Notes in Electrical Engineering
ISBN: 978-981-97-6464-8
Verlag: Springer Nature Singapore
This book covers recent trends in the field of devices, wireless communication and networking. It gathers selected papers presented at the 7th International Conference on Communication, Devices and Networking (ICCDN 2024), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on January 19–20, 2024. Gathering cutting-edge research papers prepared by researchers, engineers and industry professionals, it helps young and experienced scientists and developers alike to explore new perspectives and offers them inspirations on how to address real-world problems in the areas of electronics, communication, devices and networking.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde
Weitere Infos & Material
1. High Speed Congestion Aware Routing Algorithm for Network on Chip Architecture.- 2. Impact of Technology Node on Low Power Analog Performance of AU TFET.- 3. Comparative Analysis of the Electrical and Dielectric Characteristics of a Novel Glassy Ceramic and Its Crystalline Analogue.- 4. DFT Investigation of Fe Doped ZnO Monolayer for Adsorption of Toxic Gases.- 5. Printed Circuit Board Assembly Welding Process Based on Computer Aided Design.- 6. Enhancing Endangered Animal Conservation through Deep Learning-Powered Monitoring.- 7. Direct Approach for Modelling a Class of Fractional Order System Using Two Generating Functions.- 8. Classification of Parkinson’s and Control Subjects with Machine Learning.