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Jugulum Rajesh: Big Data Management and
Analytics

Big Data Management and Analytics

Concepts, Tools, and Applications

ForewordPreface and AcknowledgementsAuthorsChapter 1 - The Management of BIG Data OverviewChapter 2 - Big Data, Hadoop Distro, Data Triad, and Enterprise Data LakesChapter 3 - The Data Supply ChainChapter 4 - Data Quality - Measurement and Its ImpactChapter 5 - Analytics Landscape, Execution, and EvaluationChapter 6 - Big Data and Cloud SolutionsChapter 7 - Structuring Unstructured Data and NoSQLChapter 8 - Design and Development of Multivariate Diagnostic SystemsChapter 9 - Big Data and Artificial Intelligence (AI)Chapter 10 - Aligning Big Data and AI Strategy with Business GoalsChapter 11 - Facets of Responsible AIReferencesAppendixes

A Design Oriented Approach using MATLAB

Elements of Mechatronic Systems

Principles and Practice of Forensic Mechanical Engineering

Strategic guide for implementing and developing digital twin products, with real-world case studies from different industries Infrastructure Digital Twins is an instructive and practical guide that offers tools on incorporating digital twins into existing processes, illustrated by real-world case studies across diverse sectors. Emphasizing the intersections of digital twin technology, sustainability, and cutting-edge software inventions, this book uncovers the potential to accelerate the global journey toward carbon neutrality and the United Nations Sustainable Development Goals. Written by a an esteemed author, Infrastructure Digital Twins approaches the topic by discussing: <ul> <li>Ground-breaking applications of digital twin technology demonstrated through real-world examples in transportation, construction, aviation, manufacturing, and healthcare sectors, bringing to light the transformative potential of emerging tech in these industries. </li> <li>Advantages offered by the confluence of digital twin technology and modern software engineering tools, including generative Artificial Intelligence (AI), enhanced interoperability and sophisticated relationship mapping between static and dynamic entities. </li> <li>Advanced semantics to leverage AI and data analytics, thus enabling accurate predictions of future scenarios, illuminating the path towards smarter, sustainable cities and infrastructure.</li> <li>Current challenges and future solutions for digital twin adoption in sustainable asset maintenance and management, focusing on innovative strategies to seamlessly develop digital twin products </li></ul>Diving into a subject of growing significance across industries, Infrastructure Digital Twins serves as an essential guide for practicing professionals and executive engineering leaders. It is also applicable for technologists and entrepreneurs, as well as it can serve as a textbook for graduate-level courses focusing on digital twin applications, machine learning, and the emerging landscape of tech innovation in infrastructure sustainability.

Applications in Engineering, Aviation, and Facilities Management

Infrastructure Digital Twins

Complexity, Risk Modeling, and Systems

The Science of Resilience

How AI Learned to Talk and What It Means

These Strange New Minds

Manage Less, Empower More

Let Them Lead

Cybersecurity for Healthcare Systems in the Internet of Medical Things Era

Microsoft Power BI For Dummies

Design, Science and Engineering of How Things are Made

Manufacturing

Building a Program for Strategy and Oversight

Practical AI Governance

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

Fueling Blockchain Innovation and DApp Expansion

Consensus

Big Data Management and Analytics

Bibliografische Angaben

Inhaltsverzeichnis

Schlagworte

Bibliografische Angaben

Inhaltsverzeichnis

Schlagworte

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