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E-raamat: Quantum Computing: The Future of Information Processing

Edited by , Edited by ((SCSE), Galgotias University, India), Edited by (National Forensic Sciences Univ., India)
  • Formaat: PDF+DRM
  • Ilmumisaeg: 17-Apr-2025
  • Kirjastus: Auerbach
  • Keel: eng
  • ISBN-13: 9781040321881
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Quantum Computing: The Future of Information ProcessingSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 17-Apr-2025
  • Kirjastus: Auerbach
  • Keel: eng
  • ISBN-13: 9781040321881
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Quantum computing and algorithms are set to revolutionize information processing. Covering such topics, Quantum Computing: The Future of Information Processing explains its principles, practical applications, and future implications in a clear and accessible manner. The book strives to simplify the essential concepts and practical applications of quantum computing. Its aim is to help students and researchers to apply quantum computing to advance AI and machine learning, cybersecurity, and blockchain. With its emphasis on practical applications, the book covers how quantum computing is changing such fields as:

  • Finance
  • Medicine
  • Built environment
  • Networking and communications

With extensive real-world case studies and practical implementation guidance, the book is a guide for those seeking to understand how quantum computing is applied in various industries. Its in-depth exploration of quantum computing covers both foundational principles and advanced applications in a single resource, saving readers the need to purchase multiple books. Finally, the book focuses on the future of information processing so that students and researchers can anticipate and prepare for the transformative impact of quantum computing.



Quantum computing is at the forefront of technological innovation. This book explains its principles, practical applications, and future implications in a clear and accessible manner. It takes readers on a journey from the fundamental principles of quantum mechanics to practical applications.

1. Quantum Computing: Evolution, Recent Advancements, Future Opportunities and Challenges for Future Generation
2. Application of Qubits in Artificial Intelligence and Machine Learning
3. Quantum Computing Applications
4. Qubit based Applications for Next Generation Society
5. Quantum Computing: Necessary Applications for the Future
6. Securing IoT: Advanced Algorithmic Approaches for Malware Detection
7. Advancing Drug Discovery with Quantum Machine Learning
8. Quantum Neural Networks: An Overview
9. Exploring the Intersection of Quantum Neural Networks and Classical Neural Networks for Early Cancer Identification
10. Cybersecurity Forensics with AI- A Comprehensive Review
11. Remote Sensing Imagery Classification Techniques Using Quantum Deep Learning
12. Mutation based Quantum Particle Swarm Optimization (MQPSO): A Novel Approach to Global Optimization
13. Decentralizing Trust: Innovating Social Media with Blockchain for Enhanced Authenticity and Fake News Mitigation
14. Quantum Computing Integration: Cutting-edge and Quantum Computing for Building a Smart and Sustainable Environment
15. Quantum Computing for Next-Generation Artificial Intelligence-Based Blockchain
16. Securing Patient Data in Healthcare with Quantum Cryptography in the Quantum Era
17. An Analysis of Security Threats in Quantum Computing Information Processing
18. Internet and Quantum Computing to find Collaboration Graphs of Certain Social Networks
19. XSS Vulnerability Detection Using the Black Box Approach
20. Fortifying Cyber Defenses with IDPS Implementation and Management Best Practices
21. Data Encryption in 6G Networks: A Zero Knowledge Proof Model

Amit Kumar Tyagi is an assistant professor, Department of Fashion Technology, National Institute of Fashion Technology, New Delhi. He earned a Ph.D. from Pondicherry Central University, India. He has worked as assistant professor, and senior researcher at the School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India.

Shrikant Tiwari is an associate professor in the School of Computing Science and Engineering (SCSE), Galgotias University, Greater Noida, India. He received a Ph.D. from the Department of Computer Science & Engineering at the Indian Institute of Technology (Banaras Hindu University), Varanasi, India. He has authored or co-authored more than 50 national and international journal publications, book chapters, and conference articles. He has five patents filed to his credit. His research interests include machine learning, deep learning, computer vision, medical image analysis, pattern recognition, and biometrics. Dr. Tiwari is a FIETE; a senior member of the IEEE; and member of ACM, IET, CSI, ISTE, IAENG, and SCIEI.

S. V. Nagaraj is currently a professor at Vellore Institute of Technology, Chennai. He obtained a bachelor of engineering in 1992 in computer science from the University of Madras. At the Institute of Mathematical Sciences, Chennai, he completed a master of science via the research program in theoretical computer science in 1994 and obtained a doctoral degree in the same field in 2000.
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