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Books on the topic 'Critical infrastructure Machine Learning'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Al-Turjman, Fadi, and Anand Nayyar, eds. Machine Learning for Critical Internet of Medical Things. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-80928-7.

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2

John, Ruediger, ed. book - an object-oriented definition of an infrastructure. [sic!], 1991.

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3

Trevor, Hastie, Tibshirani Robert, and SpringerLink (Online service), eds. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer-Verlag New York, 2009.

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4

Blanutsa, Viktor. Public geography after 2030: outlines of new directions. INFRA-M Academic Publishing LLC., 2024. https://doi.org/10.12737/2137881.

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The monograph is devoted to the prospects for the development of social geography. After about 2030, new technologies capable of transforming the territorial organization of society will begin to be introduced. This is the sixth generation wireless communication, ubiquitous artificial intelligence, the Internet of everything and the tactile Internet. In order to understand the consequences of the deployment of these technologies, new scientific directions will have to be formed. As a first attempt, about forty directions have been proposed related to the study of linear nodal structure, critic

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5

Gaivoronski, Alexei A., Pavel S. Knopov, Vladimir I. Norkin, and Volodymyr A. Zaslavskyi. Stochastic Modeling and Optimization Methods for Critical Infrastructure Protection 2: Methods and Tools. ISTE-Wiley, 2025. https://doi.org/10.1115/1.862smo.

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Stochastic Modeling and Optimization Methods for Critical Infrastructure Protection is a thorough exploration of mathematical models and tools that are designed to strengthen critical infrastructures against threats – both natural and adversarial. Divided into two volumes, this first volume examines stochastic modeling across key economic sectors and their interconnections, while the second volume focuses on advanced mathematical methods for enhancing infrastructure protection. The book covers a range of themes, including risk assessment techniques that account for systemic interdependencies w

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6

Dobson, James E. Critical Digital Humanities. University of Illinois Press, 2019. http://dx.doi.org/10.5622/illinois/9780252042270.001.0001.

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This book seeks to develop an answer to the major question arising from the adoption of sophisticated data-science approaches within humanities research: are existing humanities methods compatible with computational thinking? Data-based and algorithmically powered methods present both new opportunities and new complications for humanists. This book takes as its founding assumption that the exploration and investigation of texts and data with sophisticated computational tools can serve the interpretative goals of humanists. At the same time, it assumes that these approaches cannot and will not

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7

Deep Learning for Internet of Things Infrastructure. CRC Press, 2021.

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8

Pathan, Al-Sakib Khan, Mamoun Alazab, Uttam Ghosh, and Ali Kashif Bashir. Deep Learning for Internet of Things Infrastructure. Taylor & Francis Group, 2021.

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9

Pathan, Al-Sakib Khan, Mamoun Alazab, Uttam Ghosh, and Ali Kashif Bashir. Deep Learning for Internet of Things Infrastructure. Taylor & Francis Group, 2021.

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10

Feyzkhanov, Rustem. Hands-On Serverless Deep Learning with TensorFlow and AWS Lambda: Training Serverless Deep Learning Models Using the AWS Infrastructure. Packt Publishing, Limited, 2019.

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11

If Machine, 2nd Edition: 30 Lesson Plans for Teaching Philosophy. Bloomsbury Publishing Plc, 2019.

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12

Castelle, Michael, and Jonathan Roberge. Cultural Life of Machine Learning: An Incursion into Critical AI Studies. Springer International Publishing AG, 2021.

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13

Castelle, Michael, and Jonathan Roberge. Cultural Life of Machine Learning: An Incursion into Critical AI Studies. Springer International Publishing AG, 2020.

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14

Machine Learning Infrastructure and Best Practices for Software Engineers: Take Your Machine Learning Software from a Prototype to a Fully Fledged Software System. Packt Publishing, Limited, 2024.

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15

Baggett, Ryan K., and Brian K. Simpkins. Homeland Security and Critical Infrastructure Protection. Praeger, 2018. http://dx.doi.org/10.5040/9798400666155.

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A compelling overview of systems and strategies implemented to safeguard U.S. resources from a plethora of threats, the vulnerabilities and security gaps in these infrastructure systems, and options to enable the future security of the homeland. Since the first edition of this book was published in 2009, significant changes have occurred in the security landscape, both domestically and internationally. This second edition is thoroughly updated to reflect those changes, offering a complete review of the various security and resilience measures currently in place and potential strategies to safe

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16

Al-Turjman, Fadi, and Anand Nayyar. Machine Learning for Critical Internet of Medical Things: Applications and Use Cases. Springer International Publishing AG, 2021.

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17

Machine Learning for Critical Internet of Medical Things: Applications and Use Cases. Springer International Publishing AG, 2023.

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18

Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure. Elsevier Science & Technology, 2023.

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19

Kehrer, Kristen, and Caleb Kaiser. Machine Learning Upgrade : a Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure. Wiley & Sons, Limited, John, 2024.

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20

Kehrer, Kristen, and Caleb Kaiser. Machine Learning Upgrade : a Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure. Wiley & Sons, Incorporated, John, 2024.

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21

Kehrer, Kristen, and Caleb Kaiser. Machine Learning Upgrade : a Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure. Wiley & Sons, Incorporated, John, 2024.

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22

Chang, Ni-Bin, and Kaixu Bai. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. Taylor & Francis Group, 2018.

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23

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. Taylor & Francis Group, 2018.

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24

Cordesman, Anthony H. Cyber-threats, Information Warfare, and Critical Infrastructure Protection. Praeger, 2001. http://dx.doi.org/10.5040/9798400636509.

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During the last two decades, the infrastructure of the U.S. economy has undergone a fundamental set of changes. It has steadily increased its reliance on its service sector and high-technology economy. The U.S. has come to depend on computers, electronic data storage and transfers, and highly integrated communications networks. The result is the rapid development of a new form of critical infrastructure--and one that is exceedingly vulnerable to a new family of threats, loosely grouped together as information warfare. This detailed volume examines these threats and the evolving U.S. policy res

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25

Khuat, Thanh Tung, and David Jacob Kedziora. Roles and Modes of Human Interactions with Automated Machine Learning Systems: A Critical Review and Perspectives. Now Publishers, 2023.

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26

Machine Learning for Quote-to-Cash: Powering Your Most Critical Business Process with Artificial Intelligence, Bots, and Data-Driven Insights. Apttus, 2017.

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27

Peng, Weiwen. Intelligent Reliability and Maintainability of Energy Infrastructure Assets: Approaches, Case Studies, Mathematical Modelling, Advanced-Decision-Making Tools, Operation Research, Progressive Machine Learning and Artificial Intelligence Methods. Springer, 2023.

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28

Trepulė, Elena, Airina Volungevičienė, Margarita Teresevičienė, et al. Guidelines for open and online learning assessment and recognition with reference to the National and European qualification framework: micro-credentials as a proposal for tuning and transparency. Vytauto Didžiojo universitetas, 2021. http://dx.doi.org/10.7220/9786094674792.

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These Guidelines are one of the results of the four-year research project “Open Online Learning for Digital and Networked Society” (2017-2021). The project objective was to enable university teachers to design open and online learning through open and online learning curriculum and environment applying learning analytics as a metacognitive tool and creating open and online learning assessment and recognition practices, responding to the needs of digital and networked society. The research of the project resulted in 10 scientific publications and 2 studies prepared by Vytautas Magnus university

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29

Bhushan, Megha, Sailesh Iyer, Ashok Kumar, Tanupriya Choudhury, and Arun Negi, eds. Artificial Intelligence for Smart Cities and Villages: Advanced Technologies, Development, and Challenges. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150492511220101.

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Smart cities and villages have enhanced the quality of lives of residents. Various computer-assisted technologies have been harnessed for the development of smart cities and villages in order to provide solutions for common and niche urban problems. The development of smart environments has been possible due to advances in computing power and artificial intelligence (AI) that have allowed the deployment of scalable technologies. Artificial Intelligence for Smart Cities and Villages: Advanced Technologies, Development, and Challenges summarizes the role of AI in planning and designing smart sol

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30

Lam, W. Hiu, and J. Robert Sneyd. Teaching in anaesthesia. Edited by Philip M. Hopkins. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0037.

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Anaesthesia education is uniquely placed to allow safe and supervised workplace teaching and training delivered in a personalized, contextual one-to-one basis. Trainers and trainees need to manage their expectations in training, enabling flexible and opportunistic capturing of these learning episodes, as well as structured learning. Structured planning of individualized training is imperative to facilitate learning in trainees with different learning styles. Role modelling of trainers in the workplace is an essential component of both clinical and professional teaching. Critical reflection and

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31

Mossberger, Karen, Eric W. Welch, and Yonghong Wu, eds. Transforming Everything? Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190082871.001.0001.

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Broadband, or high-speed internet, has been called the most important infrastructure challenge of the century by the National Broadband Plan. It has the potential to connect remote communities, help coordinate and streamline healthcare services, enable our children with unparalleled access to learning opportunities, promote government transparency and civic participation, and spark and support innovation in the economy and across numerous fields. But businesses and government agencies must be prepared to take advantage of new technologies, and individuals must have the connections and skills t

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32

Hardt, Heidi. NATO's Lessons in Crisis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190672171.001.0001.

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In crisis management operations, strategic errors can cost lives. Some international organizations (IOs) learn from these failures, whereas, others tend to repeat them. Given high rates of turnover and shorter job contracts, how do IOs such as NATO retain any knowledge about past errors? Institutional memory enhances prospects for reforms that can prevent future failures. The book provides an explanation for how and why IOs develop institutional memory in international crisis management. Evidence indicates that the design of an IO’s learning infrastructure (e.g. lessons learned offices and dat

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33

Smith, Gary, and Jay Cordes. The 9 Pitfalls of Data Science. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198844396.001.0001.

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Scientific rigor and critical thinking skills are indispensable in this age of big data because machine learning and artificial intelligence are often led astray by meaningless patterns. The 9 Pitfalls of Data Science is loaded with entertaining real-world examples of both successful and misguided approaches to interpreting data, both grand successes and epic failures. Anyone can learn to distinguish between good data science and nonsense. We are confident that readers will learn how to avoid being duped by data, and make better, more informed decisions. Whether they want to be effective creat

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34

Kubek, Maria M., and Zhong Li, eds. Autonomous Systems 2018. VDI Verlag, 2018. http://dx.doi.org/10.51202/9783186862105.

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To meet the expectations raised by the terms Industry 4.0, Industrial Internet and Internet of Things, real innovations are necessary, which can be brought about by information processing systems working autonomously. Owing to their growing complexity and their embedding in ever-changing environments, their design becomes increasingly critical. Thus, the many topics addressed in this book range from data integration on hardware level to methods for security and safety of data and to stochastic methods, data interferences as well as machine learning and search in decentralised systems. Their va

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35

Asokan, Dr N. Empowering Educators: Mastering Curriculum Decision Making. Jupiter Publications Consortium, 2024. https://doi.org/10.47715/978-93-86388-86-5.

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Curriculum Decisions Matters Effective curriculum decision making is the backbone of exceptional education. It has the power to inspire, engage, and transform students, teachers, and entire learning communities. Yet, for many educators and educational leaders, curriculum development and implementation can be a daunting and complex task. The ever-changing educational landscape, diverse student needs, and competing stakeholder demands can make it challenging to create and implement a curriculum that truly supports student success for their life and career. “Empowering Educators: Mastering Curric

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36

Baecker, Ronald M. Computers and Society. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198827085.001.0001.

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The last century has seen enormous leaps in the development of digital technologies, and most aspects of modern life have changed significantly with their widespread availability and use. Technology at various scales - supercomputers, corporate networks, desktop and laptop computers, the internet, tablets, mobile phones, and processors that are hidden in everyday devices and are so small you can barely see them with the naked eye - all pervade our world in a major way. Computers and Society: Modern Perspectives is a wide-ranging and comprehensive textbook that critically assesses the global te

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37

Graham, S. Scott. The Doctor and the Algorithm. Oxford University PressNew York, 2022. http://dx.doi.org/10.1093/oso/9780197644461.001.0001.

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Abstract The Doctor and the Algorithm combines insights from science and technology studies, critical algorithm studies, and public interest informatics to better understand how health artificial intelligence (AI) is made, promoted, regulated, and justified. It reviews the enthusiastic promises of health AI marketing communication and medical futurism as well as concerns about the dangerous and inequitable effects of AI that have been raised in critical algorithm studies and bioethics. In so doing, The Doctor and the Algorithm investigates promising new applications for health AI, as well as h

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38

Fridlund, Mats, Mila Oiva, and Petri Paju, eds. Digital Histories: Emergent Approaches within the New Digital History. Helsinki University Press, 2020. http://dx.doi.org/10.33134/hup-5.

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Historical scholarship is currently undergoing a digital turn. All historians have experienced this change in one way or another, by writing on word processors, applying quantitative methods on digitalized source materials, or using internet resources and digital tools. Digital Histories showcases this emerging wave of digital history research. It presents work by historians who – on their own or through collaborations with e.g. information technology specialists – have uncovered new, empirical historical knowledge through digital and computational methods. The topics of the volume range from

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39

Riley, Richard D., Danielle van der Windt, Peter Croft, and Karel G. M. Moons, eds. Prognosis Research in Health Care. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780198796619.001.0001.

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What is going to happen to me, doctor?’ ‘What outcomes am I likely to experience?’ ‘Will this treatment work for me?’ Prognosis—forecasting the future—has always been a part of medical practice and caring for the sick. In modern healthcare it now has a new importance, with large financial investments being made to personalize clinical decisions and tailor treatment strategies to improve individual health outcomes based on prognostic information. Prognosis research—the study of future outcomes in people with a particular health condition—provides the critical evidence for obtaining, evaluating,

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