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Castro H: AI in Emergency Medicine

AI in Emergency Medicine

What All Healthcare Professionals Can Learn from the Artificial Intelligence Revolution

With the rapid recent advances in the field of railway systems and infrastructure construction, and the evolution of AI tools that have enormous potential for application to railway design, maintenance and operations, industry professionals and researchers need an up-to-date resource on these developments. Artificial Intelligence Methods in Railway Infrastructure Systems: Application of Data Centric Engineering addresses this need. The book encapsulates the latest breakthroughs and contributions in these pivotal areas, providing readers with comprehensive insights into the cutting-edge methodologies and approaches shaping the field of railway infrastructure management. For engineers and researchers, the book provides a focused explanation of AI methodologies such as machine learning, computer vision and predictive analytics and their implementation to railway infrastructure development, tools that are new to this field. It combines theory with practical examples of the application of data centric engineering in structural health monitoring of monitoring of railway systems, thus enabling early anomaly detection and empowering infrastructure managers to address potential issues before they escalate. Given the expansive scope of research driving technological advancements in railway infrastructure management, this book serves as a reference for readers seeking to explore novel AI-based methodologies and harness their potential in the field. Readers will benefit from insights into how AI innovations can streamline their operations and enhance network safety across multiple dimensions. By providing a comprehensive overview of the subject matter, this book guides anticipatory strategies and shape future trends in railway infrastructure management.

Application of Data Centric Engineering

Artificial Intelligence Methods in Railway Infrastructure Systems

A Rebus Novel

The number one bestselling series that inspired BBC One’s REBUS

The Naming Of The Dead

How do we combat racism in a world determined to tell us it doesn't exist? To hold the line against racism, we need to know it when we see it. And as the dominant racial group in our society, White people must take up the charge. The problem is that White people haven't been socialised to detect racial bias in the way people of colour do. Racism is more than using racial slurs or overt, hateful speech, and it's more than unintentional slights; it's about an entire system that upholds Whiteness as the preferred standard. Fortunately, detecting it is a skill that can be learned. The Bias Gap is a re-education, call to action and practical guide, full of research-backed strategies including how to: · cultivate a growth mindset about bias · unlearn colourblindness and practice colour consciousness · talk to kids about race and racism - and bring others along for the journey At a time when diversity, equity and inclusion (DEI) is under coordinated attack, The Bias Gap is the essential toolkit for anyone who believes we all have a role to play in creating a more equitable world. Evelyn R. Carter, PhD, is a social psychologist and DEI expert, who has applied cutting-edge bias detection practices in a vast array of industries ranging from higher education to financial services, from technology to retail and professional sports, and at organisations like American Express, Burberry, Nike and Uber. Dr Carter's work has been featured in The Atlantic, Harvard Business Review and more.

How to Detect, Interrupt and Unlearn Bias in Everyday Life

Was That Racist?

Marty Moose

Funny animal friendship adventure stories for readers age 6, 7, 8

Marty Moose: The Great Stamp-ede

A Case Study Approach

Teaching Higher Education Administrators

A Introduction

Austrian Economics

BSAVA British Small Animal Veterinary Association

BSAVA Manual of Guinea Pigs

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

The brilliant and sometimes scandalous lives of twenty-one women who made French history.

A History of France in 21 Women

Digital Design using VerilogHDL: VLSI Modeling, Coding and Verification covers the concepts of digital logic design, including, logic simplification and optimization for digital circuit synthesis and implementation, design and integration of logics (combinational and sequential) in the building of digital circuits and systems, the practical aspects of number systems, the use of VerilogHDL in the logic design, testbench verification, and the synthesis of digital circuits and systems with HDL code examples. Users will find an approach to the design, integration, verification, and synthesizing of a digital logic circuit, complete with coding examples.

VLSI Modeling, Coding and Verification

Digital Design using VerilogHDL

Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains. It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.

Advanced Intelligence Methods for Data Science and Optimization

The Handbook of Infrastructure Communication

AI in Emergency Medicine

Bibliografische Angaben

Schlagworte

Bibliografische Angaben

Schlagworte

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