Computer Networks and Inventive Communication Technologies : Proceedings of Fifth ICCNCT 2022 (Lecture Notes on Data Engineering and Communications Technologies)

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Computer Networks and Inventive Communication Technologies : Proceedings of Fifth ICCNCT 2022 (Lecture Notes on Data Engineering and Communications Technologies)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 920 p.
  • 言語 ENG
  • 商品コード 9789811930348
  • DDC分類 004.6

Full Description

This book is a collection of peer-reviewed best selected research papers presented at 5th International Conference on Computer Networks and Inventive Communication Technologies (ICCNCT 2022). The book covers new results in theory, methodology, and applications of computer networks and data communications. It includes original papers on computer networks, network protocols and wireless networks, data communication technologies, and network security. The proceedings of this conference is a valuable resource, dealing with both the important core and the specialized issues in the areas of next generation wireless network design, control, and management, as well as in the areas of protection, assurance, and trust in information security practice. It is a reference for researchers, instructors, students, scientists, engineers, managers, and industry practitioners for advance work in the area.

Contents

Cluster Head Selection based on Mapping-based Cuttlefish Optimization Algorithm for Multipath Routing in MANET.- Opinion Mining of Movie Reviews Using Hybrid Deep Learning Technique.- Hybrid Approach to Predict The Death Rate Of Covid-19 Patients.- A Study on Reinforcement Learning based Traffic Engineering in Software Defined Networks.- Enhancing the Performance of Heterogeneous Networks Using Optimized Cluster-based Algorithm.- An Efficient Machine Learning Classifier for Sarcasm Detection.- A Delicate Authentication Mechanism for IoT Devices with Lower Overhead Issues.- A Comprehensive Study on Crop Disease Prediction Using Learning Approaches.- Design of Various SRAM attainment for FINFET.- A Novel Channel Estimation Technique for Intelligent Reflecting Surface (IRS)-aided mmWave systems based on Sparse-Kalman Filter (S-KF).

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