| ISBN13: | 9781774911464 |
| ISBN10: | 1774911469 |
| Kötéstípus: | Keménykötés |
| Terjedelem: | 502 oldal |
| Méret: | 234x156 mm |
| Súly: | 1088 g |
| Nyelv: | angol |
| Illusztrációk: | 141 Illustrations, black & white; 12 Illustrations, color; 11 Halftones, black & white; 130 Line drawings, black & white; 12 Line drawings, color; 48 Tables, black & white |
| 636 |
A természettudományok általános kérdései, tudománytörténet, tudományfilozófia
A biológia általános kérdései
A számítástudomány elmélete, a számítástechnika általában
A számítástudomány matematikai elmélete
Adatkezelés a számítógépes rendszerekben
Számítógép architektúrák, logikai tervezés
Szuperszámítógépek
Operációs rendszerek és grafikus felhasználói felületek
Szoftverfejlesztés
Adatbázis kezelő szoftverek
Természettudományok
A természettudományok általános kérdései, tudománytörténet, tudományfilozófia (karitatív célú kampány)
A biológia általános kérdései (karitatív célú kampány)
A számítástudomány elmélete, a számítástechnika általában (karitatív célú kampány)
A számítástudomány matematikai elmélete (karitatív célú kampány)
Adatkezelés a számítógépes rendszerekben (karitatív célú kampány)
Számítógép architektúrák, logikai tervezés (karitatív célú kampány)
Szuperszámítógépek (karitatív célú kampány)
Operációs rendszerek és grafikus felhasználói felületek (karitatív célú kampány)
Szoftverfejlesztés (karitatív célú kampány)
Adatbázis kezelő szoftverek (karitatív célú kampány)
Természettudományok (karitatív célú kampány)
Computational Intelligence in Analytics and Information Systems
GBP 147.00
Kattintson ide a feliratkozáshoz
A Prosperónál jelenleg nincsen raktáron.
Presents state-of-the-art advancements in IoT, network technologies, and software engineering. It focuses on smart technologies and computational intelligence in network technologies and in software engineering, such as cryptography mechanisms, internet privacy protection, satellite communication technology, etc.
This new volume presents a selection of state-of-the-art technological advancements in IoT, network technologies, and software engineering that address unsolved issues in computational intelligence. The volume focuses on empirical, theoretical, and application perspectives on smart technologies and computational intelligence, identifying the advantages and limitations of each.
The chapters on smart technologies address their application in communication services, healthcare and assistive technology, urban waste management, vehicle pollution and accident detection, and more. The technologies encompass the use of machine learning, blockchain, fog computing, etc. The volume goes on to discuss computational intelligence in network technologies as well as cryptography mechanisms, internet privacy protection, satellite communication technology, ant colony optimization algorithms, etc. The topics on computational intelligence in software engineering include security optimization via software-defined networking, education-based interactive automated agent, data warehouse requirement engineering, and more.
Together with Volume 1: Data Science and AI, Selected Papers from CIAIS-2021, this 2-volume set offers and abundance of valuable information on emerging technologies in computational intelligence.
PART I: SMART TECHNOLOGIES 1. Communication Services for Social Connection: A Proposed Market for Wipro 2. Assistive Technology as a Potential Aid for Disability and Health: A Critical Analysis 3. A Study on a Water-Body-Based Robotics Waste Management System 4. An Analysis of City Command Centers of Indian Smart Cities 5. Design of a Vehicle Pollution Detection System Using IoT 6. Fog Computing: The Next Generation Computing Paradigm 7. Logical Study of Predictions and Gathering Methodologies to Enhance Co-Clustering Formulation from a Period of Change Information in Machine Learning 8. A Review on Machine Learning Techniques for Recognition of Human Actions 9. Proposed Intelligent Vehicular Accident Detection and Alerting Based on the Internet of Things 10. Intelligent Spectacles for Accident Prevention 11. Impact of Co-Doping on Armchair Silicene Nanoribbon Using AI and P: A Potential Material for Efficient Computing 12. DOIFCM: An Outlier Efficient IFCM 13. Assessment of Document Clustering and Topic Modelling of Blockchain Adoption by the E-Sports Community 14. A Novel Hybrid Sampling Algorithm to Deal with Imbalanced Datasets 15. A Study on Analysis of E-Commerce Application on Online Healthcare 16. A Computational Approach to Detect the Incipient Cracks of Bearing in the Magnetic Particle Inspection Process PART II: COMPUTATIONAL INTELLIGENCE IN NETWORK TECHNOLOGIES 17. Comparison of Novel STE-AMM and EDES-ACM Frameworks with a Standard Cryptography Mechanism 18. Privacy Protection in Personalized Web Searches Using Anonymity 19. Performance Study of Various Routing Protocols in Opportunistic IoT Networks 20. On AES S-Boxes with Variable Modulus and Translation Polynomials 21. On Demand Link and Energy-Aware Dynamic Multipath Routing for Mobile Nodes in a Wireless Sensor Network 22. An Optimized Multi-Server Queuing Model for Transportation Problems 23. Forming the Cluster in the RFID Network for Improve the Efficiency and Investigation of Unkind Attacks 24. Traffic-Aware Quality of Service Routing in SDIoT Using Ant Colony Optimization Algorithm 25. ML-BBFT: ML-Based Bonding-Based Forwarding Technique for Social OppIoT Networks 26. Eff-MANet: A Systematic Approach for Feature Extraction in Unstructured Road Scene Scenarios 27. Quantum Error Correction Technique for Quantum-Based Satellite Communication PART III: COMPUTATIONAL INTELLIGENCE IN SOFTWARE ENGINEERING 28. A Study on an Education-Based Interactive Automated Agent 29. Issues in Retrieving Research Data from Open Source Software Projects: A Case Study 30. Proposed Model for Data Warehouse Requirement Engineering 31. Random Cloudlet Priority Scheduling: An Enhanced Approach 32. RAFI: Parallel Dynamic Test-Suite Reduction for Software 33. Security Optimization through Programmability and Flexibility in Software-Defined Networking: A Novel Approach 34. Test Case Optimization Using Genetic Algorithm
