Advanced Computing Techniques in Engineering and Technology
First International Conference, ACTET 2023, Jaipur, India, December 18-19, 2023, Proceedings
Published on 1. March 2024
Book
Paperback/Softback
XIII, 107 pages
978-3-031-54161-2 (ISBN)
Description
This CCIS conference volume constitutes the proceedings of the 24th International Conference, ACTET 2023, in Jaipur, India, December 2023. The 7 full papers together in this volume were carefully reviewed and selected from 89 submissions.
The conference addresses fundamentals of advanced scientific computing and specific mechanisms and algorithms for particular and to exchange their innovative ideas, knowledge, expertise, and experience in advance computing techniques in various domains of engineering and technology.
More details
Series
Edition
2024 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
12 s/w Abbildungen, 33 farbige Abbildungen
XIII, 107 p. 45 illus., 33 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 8 mm
Weight
201 gr
ISBN-13
978-3-031-54161-2 (9783031541612)
DOI
10.1007/978-3-031-54162-9
Schweitzer Classification
Other editions
Additional editions
Ramesh C. Bansal | Margarita N. Favorskaya | Shahbaz Ahmed Siddiqui
Advanced Computing Techniques in Engineering and Technology
First International Conference, ACTET 2023, Jaipur, India, December 18-19, 2023, Proceedings
E-Book
02/2024
Springer
€117.69
Available for download
Content
Real time Pattern Recognition with Support Vector Machines and Local Binary Patterns.- Adversarial Attacks and Defenses in Capsule Networks: A Critical Review of Robustness Challenges and Mitigation Strategies.- Control Schemes for Hybrid AC-DC Microgrid.- Design of Low Power and Energy Efficient Write Driver with Bitline Leakage Compensation for SRAM.- Review of Synergistic Integration of Microstrip Patch Antennas in Biomedical and Artificial Intelligence Domains.- An optimal design of an MLFNN coupled with genetic algorithm for prediction of MIG-CO2 welding process.- Stochastic Model for Estimation of Aggregated EV Charging Load Demand.