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Data Assessment for Electrical Surge Protective Devices (SpringerBriefs in Fire)
by Eddie Davis Nick Kooiman Kylash ViswanathanThis brief develops a data collection plan to assess loss related to electrical surges in homes, and explores the potential impact devices that prevent these surges could have in mitigating these losses. Key topics such as surge sources, surge effects and residential surge protection are clearly defined. Recent fire safety codes proposed a requirement that every dwelling unit be fitted with a surge protection device, as every year there is property damage to electrical and electronic equipment resulting from electrical surges. These proposals have not been implemented due to a lack of reliable data, which this brief seeks to change. The authors evaluate surge phenomena and their sources, surge protection methods, surge protection strategies and industry standards in order to present a data plan that can accurately assess loss related to electrical surges in homes.
Data Assimilation: Tools for Modelling the Ocean in a Global Change Perspective (Nato ASI Subseries I: #19)
by Jacques C. J.Nihoul Pierre P. BrasseurData assimilation is considered a key component of numerical ocean model development and new data acquisition strategies. The basic concept of data assimilation is to combine real observations via estimation theory with dynamic models. Related methodologies exist in meteorology, geophysics and engineering. Of growing importance in physical oceanography, data assimilation can also be exploited in biological and chemical oceanography. Such techniques are now recognized as essential to understand the role of the ocean in a global change perspective. The book focuses on data processing algorithms for assimilation, current methods for the assimilation of biogeochemical data, strategy of model development, and the design of observational data for assimilation.
Data Assimilation: Making Sense of Observations (Nato Science Series: Iv: Ser. #26)
by William Lahoz Boris Khattatov Richard MenardData assimilation methods were largely developed for operational weather forecasting, but in recent years have been applied to an increasing range of earth science disciplines. This book will set out the theoretical basis of data assimilation with contributions by top international experts in the field. Various aspects of data assimilation are discussed including: theory; observations; models; numerical weather prediction; evaluation of observations and models; assessment of future satellite missions; application to components of the Earth System. References are made to recent developments in data assimilation theory (e.g. Ensemble Kalman filter), and to novel applications of the data assimilation method (e.g. ionosphere, Mars data assimilation).
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications
by Seon Ki Park Liang XuData assimilation (DA) has been recognized as one of the core techniques for modern forecasting in various earth science disciplines including meteorology, oceanography, and hydrology. Since early 1990s DA has been an important s- sion topic in many academic meetings organized by leading societies such as the American Meteorological Society, American Geophysical Union, European G- physical Union, World Meteorological Organization, etc. nd Recently, the 2 Annual Meeting of the Asia Oceania Geosciences Society (AOGS), held in Singapore in June 2005, conducted a session on DA under the - tle of “Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications.” nd This rst DA session in the 2 AOGS was a great success with more than 30 papers presented and many great ideas exchanged among scientists from the three different disciplines. The scientists who participated in the meeting suggested making the DA session a biennial event. th Two years later, at the 4 AOGS Annual Meeting, Bangkok, Thailand, the DA session was of cially named “Sasaki Symposium on Data Assimilation for At- spheric, Oceanic and Hydrologic Applications,” to honor Prof. Yoshi K. Sasaki of the University of Oklahoma for his life-long contributions to DA in geosciences.
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. III)
by Seon Ki Park Liang XuThis book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including targeting observation, sensitivity analysis, and parameter estimation. The book will be useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)
by Liang Xu Seon Ki ParkThis book contains the most recent progress in data assimilation in meteorology, oceanography and hydrology including land surface. It spans both theoretical and applicative aspects with various methodologies such as variational, Kalman filter, ensemble, Monte Carlo and artificial intelligence methods. Besides data assimilation, other important topics are also covered including adaptive observations, sensitivity analysis, parameter estimation and AI applications. The book is useful to individual researchers as well as graduate students for a reference in the field of data assimilation.
Data Assimilation: Mathematical Concepts and Instructive Examples (SpringerBriefs in Earth Sciences)
by Rodolfo GuzziThis book endeavours to give a concise contribution to understanding the data assimilation and related methodologies. The mathematical concepts and related algorithms are fully presented, especially for those facing this theme for the first time. The first chapter gives a wide overview of the data assimilation steps starting from Gauss' first methods to the most recent as those developed under the Monte Carlo methods. The second chapter treats the representation of the physical system as an ontological basis of the problem. The third chapter deals with the classical Kalman filter, while the fourth chapter deals with the advanced methods based on recursive Bayesian Estimation. A special chapter, the fifth, deals with the possible applications, from the first Lorenz model, passing trough the biology and medicine up to planetary assimilation, mainly on Mars. This book serves both teachers and college students, and other interested parties providing the algorithms and formulas to manage the data assimilation everywhere a dynamic system is present.
Data Augmented Design: Embracing New Data for Sustainable Urban Planning and Design (Strategies for Sustainability)
by Ying Long Enjia ZhangThis book offers an essential introduction to a new urban planning and design methodology called Data Augmented Design (DAD) and its evolution and progresses, highlighting data driven methods, urban planning and design applications and related theories. The authors draw on many kinds of data, including big, open, and conventional data, and discuss cutting-edge technologies that illustrate DAD as a future oriented design framework in terms of its focus on multi-data, multi-method, multi-stage and multi-scale sustainable urban planning. In four sections and ten chapters, the book presents case studies to address the core concepts of DAD, the first type of applications of DAD that emerged in redevelopment-oriented planning and design, the second type committed to the planning and design for urban expansion, and the future-oriented applications of DAD to advance sustainable technologies and the future structural form of the built environment. The book is geared towards a broad readership, ranging from researchers and students of urban planning, urban design, urban geography, urban economics, and urban sociology, to practitioners in the areas of urban planning and design.
Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods (Synthesis Lectures on Materials and Optics)
by Ghanshyam Pilania Prasanna V. Balachandran James E. Gubernatis Turab LookmanMachine learning methods are changing the way we design and discover new materials. This book provides an overview of approaches successfully used in addressing materials problems (alloys, ferroelectrics, dielectrics) with a focus on probabilistic methods, such as Gaussian processes, to accurately estimate density functions. The authors, who have extensive experience in this interdisciplinary field, discuss generalizations where more than one competing material property is involved or data with differing degrees of precision/costs or fidelity/expense needs to be considered.
Data Book on Mechanical Properties of Living Cells, Tissues, and Organs
by Hiroyuki Abe Kozaburo Hayashi Masaaki SatoA research project entitled Biomechanics of Structure and Function of Living Cells, Tissues, and Organs was launched in Japan in 1992. This data book presents the original, up-to-date information resulting from the research project, supplemented by some of the important basic data published previously. The aim of collecting the information is to offer accurate and useful data on the mechanical properties of living materials to biomechanical scientists, biomedical engineers, medical scientists, and clinicians. The data are presented in graphs and tables (one type of data per page) arranged in an easily accessible manner, along with details of the origin of the material and the experimental method. Together with its two companion volumes, Biomechanics: Functional Adaptation and Remodeling and Computational Biomechanics, the Data Book on Mechanical Properties of Living Cells, Tissues, and Organs is a timely and valuable contribution to the rapidly growing field of biomechanics.
Data Breach Preparation and Response: Breaches are Certain, Impact is Not
by Kevvie FowlerData Breach Preparation and Response: Breaches are Certain, Impact is Not is the first book to provide 360 degree visibility and guidance on how to proactively prepare for and manage a data breach and limit impact. Data breaches are inevitable incidents that can disrupt business operations and carry severe reputational and financial impact, making them one of the largest risks facing organizations today. The effects of a breach can be felt across multiple departments within an organization, who will each play a role in effectively managing the breach. Kevvie Fowler has assembled a team of leading forensics, security, privacy, legal, public relations and cyber insurance experts to create the definitive breach management reference for the whole organization. Discusses the cyber criminals behind data breaches and the underground dark web forums they use to trade and sell stolen dataFeatures never-before published techniques to qualify and discount a suspected breach or to verify and precisely scope a confirmed breachHelps identify your sensitive data, and the commonly overlooked data sets that, if stolen, can result in a material breach Defines breach response plan requirements and describes how to develop a plan tailored for effectiveness within your organizationExplains strategies for proactively self-detecting a breach and simplifying a responseCovers critical first-responder steps and breach management practices, including containing a breach and getting the scope right, the first timeShows how to leverage threat intelligence to improve breach response and management effectivenessOffers guidance on how to manage internal and external breach communications, restore trust, and resume business operations after a breach, including the critical steps after the breach to reduce breach-related litigation and regulatory finesIllustrates how to define your cyber-defensible position to improve data protection and demonstrate proper due diligence practices
Data Cartels: The Companies That Control and Monopolize Our Information
by Sarah LamdanIn our digital world, data is power. Information hoarding businesses reign supreme, using intimidation, aggression, and force to maintain influence and control. Sarah Lamdan brings us into the unregulated underworld of these "data cartels", demonstrating how the entities mining, commodifying, and selling our data and informational resources perpetuate social inequalities and threaten the democratic sharing of knowledge. Just a few companies dominate most of our critical informational resources. Often self-identifying as "data analytics" or "business solutions" operations, they supply the digital lifeblood that flows through the circulatory system of the internet. With their control over data, they can prevent the free flow of information, masterfully exploiting outdated information and privacy laws and curating online information in a way that amplifies digital racism and targets marginalized communities. They can also distribute private information to predatory entities. Alarmingly, everything they're doing is perfectly legal. In this book, Lamdan contends that privatization and tech exceptionalism have prevented us from creating effective legal regulation. This in turn has allowed oversized information oligopolies to coalesce. In addition to specific legal and market-based solutions, Lamdan calls for treating information like a public good and creating digital infrastructure that supports our democratic ideals.
Data Cartels: The Companies That Control and Monopolize Our Information
by Sarah LamdanIn our digital world, data is power. Information hoarding businesses reign supreme, using intimidation, aggression, and force to maintain influence and control. Sarah Lamdan brings us into the unregulated underworld of these "data cartels", demonstrating how the entities mining, commodifying, and selling our data and informational resources perpetuate social inequalities and threaten the democratic sharing of knowledge. Just a few companies dominate most of our critical informational resources. Often self-identifying as "data analytics" or "business solutions" operations, they supply the digital lifeblood that flows through the circulatory system of the internet. With their control over data, they can prevent the free flow of information, masterfully exploiting outdated information and privacy laws and curating online information in a way that amplifies digital racism and targets marginalized communities. They can also distribute private information to predatory entities. Alarmingly, everything they're doing is perfectly legal. In this book, Lamdan contends that privatization and tech exceptionalism have prevented us from creating effective legal regulation. This in turn has allowed oversized information oligopolies to coalesce. In addition to specific legal and market-based solutions, Lamdan calls for treating information like a public good and creating digital infrastructure that supports our democratic ideals.
Data-Centric Biology: A Philosophical Study
by Sabina LeonelliIn recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.
Data-Centric Biology: A Philosophical Study
by Sabina LeonelliIn recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.
Data-Centric Biology: A Philosophical Study
by Sabina LeonelliIn recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.
Data-Centric Biology: A Philosophical Study
by Sabina LeonelliIn recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.
Data-Centric Biology: A Philosophical Study
by Sabina LeonelliIn recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.
Data-Centric Biology: A Philosophical Study
by Sabina LeonelliIn recent decades, there has been a major shift in the way researchers process and understand scientific data. Digital access to data has revolutionized ways of doing science in the biological and biomedical fields, leading to a data-intensive approach to research that uses innovative methods to produce, store, distribute, and interpret huge amounts of data. In Data-Centric Biology, Sabina Leonelli probes the implications of these advancements and confronts the questions they pose. Are we witnessing the rise of an entirely new scientific epistemology? If so, how does that alter the way we study and understand life—including ourselves? Leonelli is the first scholar to use a study of contemporary data-intensive science to provide a philosophical analysis of the epistemology of data. In analyzing the rise, internal dynamics, and potential impact of data-centric biology, she draws on scholarship across diverse fields of science and the humanities—as well as her own original empirical material—to pinpoint the conditions under which digitally available data can further our understanding of life. Bridging the divide between historians, sociologists, and philosophers of science, Data-Centric Biology offers a nuanced account of an issue that is of fundamental importance to our understanding of contemporary scientific practices.
Data-centric Living: Algorithms, Digitization and Regulation
by V. SridharThis book explores how data about our everyday online behaviour are collected and how they are processed in various ways by algorithms powered by Artificial Intelligence (AI) and Machine Learning (ML). The book investigates the socioeconomic effects of these technologies, and the evolving regulatory landscape that is aiming to nurture the positive effects of these technology evolutions while at the same time curbing possible negative practices. The volume scrutinizes growing concerns on how algorithmic decisions can sometimes be biased and discriminative; how autonomous systems can possibly disrupt and impact the labour markets, resulting in job losses in several traditional sectors while creating unprecedented opportunities in others; the rapid evolution of social media that can be addictive at times resulting in associated mental health issues; and the way digital Identities are evolving around the world and their impact on provisioning of government services. The book also provides an in-depth understanding of regulations around the world to protect privacy of data subjects in the online world; a glimpse of how data is used as a digital public good in combating Covid pandemic; and how ethical standards in autonomous systems are evolving in the digital world. A timely intervention in this fast-evolving field, this book will be useful for scholars and researchers of digital humanities, business and management, internet studies, data sciences, political studies, urban sociology, law, media and cultural studies, sociology, cultural anthropology, and science and technology studies. It will also be of immense interest to the general readers seeking insights on daily digital lives.
Data-centric Living: Algorithms, Digitization and Regulation
by Sridhar V.This book explores how data about our everyday online behaviour are collected and how they are processed in various ways by algorithms powered by Artificial Intelligence (AI) and Machine Learning (ML). The book investigates the socioeconomic effects of these technologies, and the evolving regulatory landscape that is aiming to nurture the positive effects of these technology evolutions while at the same time curbing possible negative practices. The volume scrutinizes growing concerns on how algorithmic decisions can sometimes be biased and discriminative; how autonomous systems can possibly disrupt and impact the labour markets, resulting in job losses in several traditional sectors while creating unprecedented opportunities in others; the rapid evolution of social media that can be addictive at times resulting in associated mental health issues; and the way digital Identities are evolving around the world and their impact on provisioning of government services. The book also provides an in-depth understanding of regulations around the world to protect privacy of data subjects in the online world; a glimpse of how data is used as a digital public good in combating Covid pandemic; and how ethical standards in autonomous systems are evolving in the digital world. A timely intervention in this fast-evolving field, this book will be useful for scholars and researchers of digital humanities, business and management, internet studies, data sciences, political studies, urban sociology, law, media and cultural studies, sociology, cultural anthropology, and science and technology studies. It will also be of immense interest to the general readers seeking insights on daily digital lives.
Data Converters
by Franco MalobertiThis book is the first graduate-level textbook presenting a comprehensive treatment of Data Converters. It provides comprehensive definition of the parameters used to specify data converters, and covers all the architectures used in Nyquist-rate data converters. The book uses Simulink and Matlab extensively in examples and problem sets. This is a textbook that is also essential for engineering professionals as it was written in response to a shortage of organically organized material on the topic. The book assumes a solid background in analog and digital circuits as well as a working knowledge of simulation tools for circuit and behavioral analysis.
Data Deduplication Approaches: Concepts, Strategies, and Challenges
by G. R. Sinha Tin Thein ThwelIn the age of data science, the rapidly increasing amount of data is a major concern in numerous applications of computing operations and data storage. Duplicated data or redundant data is a main challenge in the field of data science research. Data Deduplication Approaches: Concepts, Strategies, and Challenges shows readers the various methods that can be used to eliminate multiple copies of the same files as well as duplicated segments or chunks of data within the associated files. Due to ever-increasing data duplication, its deduplication has become an especially useful field of research for storage environments, in particular persistent data storage. Data Deduplication Approaches provides readers with an overview of the concepts and background of data deduplication approaches, then proceeds to demonstrate in technical detail the strategies and challenges of real-time implementations of handling big data, data science, data backup, and recovery. The book also includes future research directions, case studies, and real-world applications of data deduplication, focusing on reduced storage, backup, recovery, and reliability.Includes data deduplication methods for a wide variety of applicationsIncludes concepts and implementation strategies that will help the reader to use the suggested methodsProvides a robust set of methods that will help readers to appropriately and judiciously use the suitable methods for their applicationsFocuses on reduced storage, backup, recovery, and reliability, which are the most important aspects of implementing data deduplication approachesIncludes case studies
Data Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering
by Feras A. Batarseh Ruixin YangData Democracy: At the Nexus of Artificial Intelligence, Software Development, and Knowledge Engineering provides a manifesto to data democracy. After reading the chapters of this book, you are informed and suitably warned! You are already part of the data republic, and you (and all of us) need to ensure that our data fall in the right hands. Everything you click, buy, swipe, try, sell, drive, or fly is a data point. But who owns the data? At this point, not you! You do not even have access to most of it. The next best empire of our planet is one who owns and controls the world’s best dataset. If you consume or create data, if you are a citizen of the data republic (willingly or grudgingly), and if you are interested in making a decision or finding the truth through data-driven analysis, this book is for you. A group of experts, academics, data science researchers, and industry practitioners gathered to write this manifesto about data democracy.The future of the data republic, life within a data democracy, and our digital freedomsAn in-depth analysis of open science, open data, open source software, and their future challengesA comprehensive review of data democracy's implications within domains such as: healthcare, space exploration, earth sciences, business, and psychologyThe democratization of Artificial Intelligence (AI), and data issues such as: Bias, imbalance, context, and knowledge extractionA systematic review of AI methods applied to software engineering problems
Data-driven Analytics for Sustainable Buildings and Cities: From Theory to Application (Sustainable Development Goals Series)
by Xingxing ZhangThis book explores the interdisciplinary and transdisciplinary fields of energy systems, occupant behavior, thermal comfort, air quality and economic modelling across levels of building, communities and cities, through various data analytical approaches. It highlights the complex interplay of heating/cooling, ventilation and power systems in different processes, such as design, renovation and operation, for buildings, communities and cities. Methods from classical statistics, machine learning and artificial intelligence are applied into analyses for different building/urban components and systems. Knowledge from this book assists to accelerate sustainability of the society, which would contribute to a prospective improvement through data analysis in the liveability of both built and urban environment. This book targets a broad readership with specific experience and knowledge in data analysis, energy system, built environment and urban planning. As such, it appeals to researchers, graduate students, data scientists, engineers, consultants, urban scientists, investors and policymakers, with interests in energy flexibility, building/city resilience and climate neutrality.