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Applied Machine Learning in Chemical
Process Engineering

Applied Machine Learning in Chemical Process Engineering

A Practical Approach

Quantum Computing and Machine Learning for 6G

Understand How to Use Artificial Intelligence in Your HR Role

AI for People Professionals

Triangulating AI Security

How AI Learned to Talk and What It Means

These Strange New Minds

Life Cycle Assessment of Waste and Water Systems

The Complete Step-by-Step Guide to Agile Project Management with Kanban

Kanban

Integration of Federated Learning and Blockchain for Smart Cities

Vital information on AI, ML, and 5G, and implementing these topics for cellular network design and optimization AI for Design and Optimization of Cellular Networks focuses on the intersection of cellular communications and AI, discussing current advances, key concepts, challenges, opportunities, and lifecycle management. Divided into two parts, the first part provides the background of AI and cellular communications, exploring the challenges that are associated with creation, deployment, operation, and maintenance of systems for the design and optimization of cellular networks. The second part explains the process of network planning, design, and optimization of cellular networks, including examples and use cases in each area. The second part also discusses the application of AI to energy saving, the challenges that operators face, and a glimpse of future trends for AI, cellular networks, and their related NDO (Network Design and Optimization) activities. The book also includes coverage of AI-powered design technologies, performance characterization of advanced antenna systems, propagation predictions, and more. With heavy contribution from industry professionals at Ericsson, AI for Design and Optimization of Cellular Networks includes detailed information on: Evolution of cellular communications from the early GSM days until today, with special emphasis on the arrival of 5G and its implications compared with LTESupervised, unsupervised, semi-supervised, and reinforcement learning with an intuitive focus, covering their distinctive characteristicsDifferent types of digital twins, their fundamental properties, their suitability for design and optimization of cellular networks, and using them together with AI techniquesTransition from traditional network performance management and operations towards an AI-driven combination of control loops An informed and timely exploration of key developments and challenges by those who work on the frontline, AI for Design and Optimization of Cellular Networks is an essential resource for professionals working in cellular communications and AI, providing a one-of-a-kind blend of practical and theoretical information.

AI for Design and Optimization of Cellular Networks

Green Protocols

Ionic Liquids in Biomass Processing

Cybersecurity for Healthcare Systems in the Internet of Medical Things Era

Understanding failures and disasters using case studies and simple engineering techniques Decoding Disasters provides illustrated failure case histories on a multitude of technologies and shows how engineering analysis can explain and help professionals understand them. For each case, the analysis technique is included so that the reader can adapt and apply it to their own situation. Different techniques are developed to show how the methods can be applied in various disciplines. This book guides readers to determine what likely occurred in each case with a minimum amount of data and without speculating. Each example in this book states the problem, theorizes a conceptual cause, verifies the cause by analysis (i.e. a mathematical model) and actual data, shows the use of the various engineering equations, and documents a solution. In this comprehensive guide, readers will learn about: <ul> <li>Viewing disasters not solely as a matter of emergency response, but also more holistically as social constructs between natural extremes, human populations, and the built environment</li> <li>Economic, environmental, and human impacts of disasters</li> <li>How growth calculations can evaluate the past and present and be applied to likely future events</li> <li>Disasters stemming from shortcuts in the design process to meet the demands and needs of society</li> </ul> This book is an excellent learning resource not only for practicing engineers, but also government and regulatory officials who can enact changes to prevent future repeat failures.

An Engineering Approach to Understanding Technical Failures and Natural Catastrophes

Decoding Disasters

The Blueprint for AI Adoption and Societal Transformation

Applied Machine Learning in Chemical Process Engineering

Informations bibliographiques

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