Trustworthy Autonomic Computing by Thaddeus Eze
This book covers challenges and solutions of autonomic computing trustworthiness from methods and techniques to achieve consistent and reliable system self-management. This is an ideal tutorial guide for independent study with simple and well documented diagrams to explain techniques and processes.-
UML for Systems Engineering
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Generative AI for Multimedia Content Processing, Security and Privacy
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The Power of Large Language Models and AI in the Digital Age
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Modelling Enterprise Architectures
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Knowledge Discovery and Data Mining
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Generative AI for Sign Language Recognition and Translation
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Managing Complexity in Software Engineering
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Semi-custom IC Design and VLSI
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Ultrascale Computing Systems
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The Digital Twin Handbook
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Matrix Factorization for Multimedia Clustering
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AIoT Technologies and Applications for Smart Environments
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Intelligent Network Design Driven by Big Data Analytics, IoT, AI and Cloud Computing
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Demystifying Graph Data Science
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Energy Optimization and Security in Federated Learning for IoT Environments
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Big Data Recommender Systems
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Blockchains for Network Security
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Network Classification for Traffic Management
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Intelligent Distributed Video Surveillance Systems
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AI for Emerging Verticals
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Big Data and Software Defined Networks
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Security and Privacy for Big Data, Cloud Computing and Applications
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Intelligent Multimedia Technologies for Financial Risk Management
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E-learning Methodologies
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Many-Core Computing
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Big Data-Enabled Internet of Things
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Generative AI Unleashed
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Explainable Artificial Intelligence for Trustworthy Internet of Things
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Streaming Analytics
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Edge Computing
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ReRAM-based Machine Learning
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Nature-inspired Optimization Algorithms and Soft Computing
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Advanced Networking Technologies
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Virtual Reality and Light Field Immersive Video Technologies for Real-World Applications
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Federated Learning for Multimedia Data Processing and Security in Industry 5.0
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Engineering the Metaverse
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Personal Knowledge Graphs (PKGs)
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Trusted Platform Modules
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Explainable Artificial Intelligence (XAI)
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Earth Observation Data Analytics Using Machine and Deep Learning
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Graphical Programming Using LabVIEW
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Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches
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Managing Internet of Things Applications across Edge and Cloud Data Centres
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Enabling Technologies for Smart Fog Computing
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Intelligent Multimedia Processing and Computer Vision
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Access Control and Security Monitoring of Multimedia Information Processing and Transmission
Thaddeus Eze is a cybersecurity senior lecturer and researcher at the Computer Science Department, University of Chester, UK. He is the programme leader for MSc Cybersecurity (Conversion) and the postgraduate assessment officer for the Computer Science department. His research interests include cybersecurity awareness and training, trustworthy autonomic computing, ethical hacking, cryptography, and digital forensics. He is a member of CIISec and was the Vice Chair of the IEEE Young Professionals, UK & Ireland Section from 2014 to 2022. He's the Convener and organiser of the IEEE UK & Ireland YP Postgraduate STEM Research Symposium (three successful editions already organised). He was actively involved in organising the first ever UK Pitch Bootcamp and the IEEE Professional Development Networking Workshop 2017. He is a 2004 graduate of Anambra State University, Nigeria, with BSc (Upper 2nd Class) in Computer Science. He holds an MSc (with Distinction, 2010) in Mobile Computing and Communications and a PhD in Trustworthy Autonomics from the University of Greenwich, London, UK.
| SKU | Unavailable |
| ISBN 13 | 9781785618833 |
| ISBN 10 | 1785618830 |
| Title | Trustworthy Autonomic Computing |
| Author | Thaddeus Eze |
| Series | Computing And Networks |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Institution of Engineering and Technology |
| Year published | 2023-01-30 |
| Number of pages | 264 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |