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Data Analytics for Renewable Energy Integration: 5th ECML PKDD Workshop, DARE 2017, Skopje, Macedonia, September 22, 2017, Revised Selected Papers (Lecture Notes in Computer Science #10691)
by Wei Lee Woon, Zeyar Aung, Oliver Kramer and Stuart MadnickThis book constitutes revised selected papers from the 5th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2017, held in Skopje, Macedonia, in September 2017. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response and many others.
Data Analytics for Renewable Energy Integration: Third ECML PKDD Workshop, DARE 2015, Porto, Portugal, September 11, 2015. Revised Selected Papers (Lecture Notes in Computer Science #9518)
by Wei Lee Woon Zeyar Aung Stuart MadnickThis book constitutes revised selected papers from the second ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2014, held in Nancy, France, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book.
Data Analytics for Smart Cities (Data Analytics Applications)
by Amir Alavi William G. ButtlarThe development of smart cities is one of the most important challenges over the next few decades. Governments and companies are leveraging billions of dollars in public and private funds for smart cities. Next generation smart cities are heavily dependent on distributed smart sensing systems and devices to monitor the urban infrastructure. The smart sensor networks serve as autonomous intelligent nodes to measure a variety of physical or environmental parameters. They should react in time, establish automated control, and collect information for intelligent decision-making. In this context, one of the major tasks is to develop advanced frameworks for the interpretation of the huge amount of information provided by the emerging testing and monitoring systems. Data Analytics for Smart Cities brings together some of the most exciting new developments in the area of integrating advanced data analytics systems into smart cities along with complementary technological paradigms such as cloud computing and Internet of Things (IoT). The book serves as a reference for researchers and engineers in domains of advanced computation, optimization, and data mining for smart civil infrastructure condition assessment, dynamic visualization, intelligent transportation systems (ITS), cyber-physical systems, and smart construction technologies. The chapters are presented in a hands-on manner to facilitate researchers in tackling applications. Arguably, data analytics technologies play a key role in tackling the challenge of creating smart cities. Data analytics applications involve collecting, integrating, and preparing time- and space-dependent data produced by sensors, complex engineered systems, and physical assets, followed by developing and testing analytical models to verify the accuracy of results. This book covers this multidisciplinary field and examines multiple paradigms such as machine learning, pattern recognition, statistics, intelligent databases, knowledge acquisition, data visualization, high performance computing, and expert systems. The book explores new territory by discussing the cutting-edge concept of Big Data analytics for interpreting massive amounts of data in smart city applications.
Data Analytics for Smart Grids Applications—A Key to Smart City Development (Intelligent Systems Reference Library #247)
by Devendra Kumar Sharma Rohit Sharma Gwanggil Jeon Raghvendra KumarThis book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.
Data Analytics in e-Learning: Approaches and Applications (Intelligent Systems Reference Library #220)
by Marian Cristian MihăescuThis book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications. This book represents a guideline for building a data analysis workflow from scratch. Each chapter presents a step of the entire workflow, starting from an available dataset and continuing with building interpretable models, enhancing models, and tackling aspects of evaluating engagement and usability. The related work shows that many papers have focused on machine learning usage and advancement within e-learning systems. However, limited discussions have been found on presenting a detailed complete roadmap from the raw dataset up to the engagement and usability issues. Practical examples and guidelines are provided for designing and implementing new algorithms that address specific problems or functionalities. This roadmap represents a potential resource for various advances of researchers and practitioners in educational data mining and learning analytics.
Data Analytics in Power Markets
by Yi Wang Qixin Chen Hongye Guo Kedi ZhengThis book aims to solve some key problems in the decision and optimization procedure for power market organizers and participants in data-driven approaches. It begins with an overview of the power market data and analyzes on their characteristics and importance for market clearing. Then, the first part of the book discusses the essential problem of bus load forecasting from the perspective of market organizers. The related works include load uncertainty modeling, bus load bad data correction, and monthly load forecasting. The following part of the book answers how much information can be obtained from public data in locational marginal price (LMP)-based markets. It introduces topics such as congestion identification, componential price forecasting, quantifying the impact of forecasting error, and financial transmission right investment. The final part of the book answers how to model the complex market bidding behaviors. Specific works include pattern extraction, aggregated supply curve forecasting, market simulation, and reward function identification in bidding. These methods are especially useful for market organizers to understand the bidding behaviors of market participants and make essential policies. It will benefit and inspire researchers, graduate students, and engineers in the related fields.
Data Analytics in System Engineering: Proceedings of 7th Computational Methods in Systems and Software 2023, Vol. 3 (Lecture Notes in Networks and Systems #910)
by Radek Silhavy Petr SilhavyThese proceedings offer an insightful exploration of integrating data analytics in system engineering. This book highlights the essential role of data in driving innovation, optimizing processes, and solving complex challenges in the field. Targeted at industry professionals, researchers, and enthusiasts, this book serves as a comprehensive resource, providing actionable insights and showcasing transformative applications of data in engineering. It is a must-read for anyone keen on understanding and participating in the ongoing evolution of system engineering in our data-centric world.
Data Analytics in System Engineering: Proceedings of 7th Computational Methods in Systems and Software 2023, Vol. 4 (Lecture Notes in Networks and Systems #935)
by Radek Silhavy Petr SilhavyThese proceedings offer an insightful exploration of integrating data analytics in system engineering. This book highlights the essential role of data in driving innovation, optimizing processes, and solving complex challenges in the field. Targeted at industry professionals, researchers, and enthusiasts, this book serves as a comprehensive resource, providing actionable insights and showcasing transformative applications of data in engineering. It is a must-read for anyone keen on understanding and participating in the ongoing evolution of system engineering in our data-centric world.
Data Analytics in the Era of the Industrial Internet of Things
by Aldo DagninoThis book presents the characteristics and benefits industrial organizations can reap from the Industrial Internet of Things (IIoT). These characteristics and benefits include enhanced competitiveness, increased proactive decision-making, improved creativity and innovation, augmented job creation, heightened agility to respond to continuously changing challenges, and intensified data-driven decision making. In a straightforward fashion, the book also helps readers understand complex concepts that are core to IIoT enterprises, such as Big Data, analytic architecture platforms, machine learning (ML) and data science algorithms, and the power of visualization to enrich the domains experts’ decision making. The book also guides the reader on how to think about ways to define new business paradigms that the IIoT facilitates, as well how to increase the probability of success in managing analytic projects that are the core engine of decision-making in the IIoT enterprise. The book starts by defining an IIoT enterprise and the framework used to efficiently operate. A description of the concepts of industrial analytics, which is a major engine for decision making in the IIoT enterprise, is provided. It then discusses how data and machine learning (ML) play an important role in increasing the competitiveness of industrial enterprises that operate using the IIoT technology and business concepts. Real world examples of data driven IIoT enterprises and various business models are presented and a discussion on how the use of ML and data science help address complex decision-making problems and generate new job opportunities. The book presents in an easy-to-understand manner how ML algorithms work and operate on data generated in the IIoT enterprise. Useful for any industry professional interested in advanced industrial software applications, including business managers and professionals interested in how data analytics can help industries and to develop innovative business solutions, as well as data and computer scientists who wish to bridge the analytics and computer science fields with the industrial world, and project managers interested in managing advanced analytic projects.
Data and AI Driving Smart Cities (Studies in Big Data #128)
by Pedro Ponce Therese Peffer Juana Isabel Mendez Garduno Ursula Eicker Arturo Molina Troy McDaniel Edgard D. Musafiri Mimo Ramanunni Parakkal Menon Kathryn Kaspar Sadam HussainThis book illustrates how the advanced technology developed for smart cities requires increasing interaction with citizens to motivate and incentive them. Megacities' needs have been encouraging for the creation of smart cities in which the needs of inhabitants are collected using virtualization and digitalization systems. On the other hand, machine learning algorithms have been implemented to provide better solutions for diverse areas in smart cities, such as transportation and health. Besides, conventional electric grids have transformed into smart grids, improving energy quality. Gamification, serious games, machine learning, dynamic interfaces, and social networks are some elements integrated holistically to provide novel solutions to design and develop smart cities. Also, this book presents in a friendly way the concept of social devices that are incorporated into smart homes and buildings. This book is used to understand and design smart cities where citizens are strongly interconnected so the demand response time can be reduced.
Data and Applications Security and Privacy XXXII: 32nd Annual IFIP WG 11.3 Conference, DBSec 2018, Bergamo, Italy, July 16–18, 2018, Proceedings (Lecture Notes in Computer Science #10980)
by Florian Kerschbaum Stefano ParaboschiThis book constitutes the refereed proceedings of the 32nd Annual IFIP WG 11.3 International Working Conference on Data and Applications Security and Privacy, DBSec 2018, held in Bergamo, Italy, in July 2018. The 16 full papers and 5 short papers presented were carefully reviewed and selected from 50 submissions. The papers present high-quality original research from academia, industry, and government on theoretical and practical aspects of information security. They are organized in topical sections on administration, access control policies, privacy-preserving access and computation, integrity and user interaction, security analysis and private evaluation, fixing vulnerabilities, and networked systems.
Data and Decision Sciences in Action 2: Proceedings of the ASOR/DORS Conference 2018 (Lecture Notes in Management and Industrial Engineering)
by Andreas T. Ernst Simon Dunstall Rodolfo García-Flores Marthie Grobler David MarlowThis book constitutes the proceedings of the Joint 2018 National Conferences of the Australian Society for Operations Research (ASOR) and the Defence Operations Research Symposium (DORS). Offering a fascinating insight into the state of the art in Australian operations research, this book is of great interest to academics and other professional researchers working in operations research and analytics, as well as practitioners addressing strategic planning, operations management, and other data-driven decision-making challenges in the domains of commerce, industry, defence, the environment, humanitarianism, and agriculture. The book comprises 21 papers on topics ranging from methodological advances to case studies, and addresses application domains including supply chains, government services, defence, cybersecurity, healthcare, mining and material processing, agriculture, natural hazards, telecommunications and transportation.ASOR is the premier professional organization for Australian academics and practitioners working in optimization and other disciplines related to operations research. The conference was held in Melbourne, Australia, in December 2018.
Data and Energy Integrated Communication Networks: A Brief Introduction (SpringerBriefs in Computer Science)
by Jie Hu Kun YangThe book discusses data and energy integrated communication networking technologies, including the latest research contributions in this promising area. It firstly provides an overview of data and energy integrated communication networks (DEINs) and introduces the key techniques for enabling integrated wireless energy transfer (WET) and wireless information transfer (WIT) in the radio frequency (RF) band. It then describes the ubiquitous architecture of DEINs and demonstrates the typical DEIN system and investigates the core issues in both the physical layer and the medium-access-control (MAC) layer in order to coordinate both the WIT and WET in the same RF band. Lastly, the book addresses a number of emerging research topics in the field of DEINs. It promotes joint efforts from both academia and industry to push DEIN a step closer to practical implementation. It is also a valuable resource for students interested in studying cutting-edge techniques in this field.
Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World
by Bruce SchneierYou are under surveillance right now.<P><P> Your cell phone provider tracks your location and knows who’s with you. Your online and in-store purchasing patterns are recorded, and reveal if you're unemployed, sick, or pregnant. Your e-mails and texts expose your intimate and casual friends. Google knows what you’re thinking because it saves your private searches. Facebook can determine your sexual orientation without you ever mentioning it.<P> The powers that surveil us do more than simply store this information. Corporations use surveillance to manipulate not only the news articles and advertisements we each see, but also the prices we’re offered. Governments use surveillance to discriminate, censor, chill free speech, and put people in danger worldwide. And both sides share this information with each other or, even worse, lose it to cybercriminals in huge data breaches.<P> Much of this is voluntary: we cooperate with corporate surveillance because it promises us convenience, and we submit to government surveillance because it promises us protection. The result is a mass surveillance society of our own making. But have we given up more than we’ve gained? In Data and Goliath, security expert Bruce Schneier offers another path, one that values both security and privacy. He shows us exactly what we can do to reform our government surveillance programs and shake up surveillance-based business models, while also providing tips for you to protect your privacy every day. You'll never look at your phone, your computer, your credit cards, or even your car in the same way again.
Data and the Built Environment: A Practical Guide to Building a Better World Using Data (Digital Innovations in Architecture, Engineering and Construction)
by Ian Gordon Neil ThompsonThis book takes a data-first approach to framing the built environment sector’s unique challenges and how industry can address them through better use of data. It describes how the sector has failed to derive value from data, and the common causes underlying this failure. It then provides practical guidance on how to use data to construct and operate built environment assets in a manner that better meets society’s needs. The book examines how industry norms, organizational culture, and our personal behaviours contribute to the successful use of data. It sets out a philosophy and vision for the use of data in the built environment, and how this in turn might help the sector realise better outcomes in terms of cost, schedule, quality, and sustainability. Data is a valuable asset, one that the built environment sector must generate, protect, manage, and exploit. The book works as a holistic primer to data and the built environment, written both for those who are new to data or the built environment, and including deep-dive material that will provide insight to experienced professionals.
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: 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 Baby: My Life in a Psychological Experiment
by Susannah BreslinA Belletrist Book Pick for December 2023Lab Girl meets Brain on Fire in this provocative and poignant memoir delving into a woman's formative experiences as a veritable "lab rat" in a lifelong psychological study, and her pursuit to reclaim autonomy and her identity as a adult. What if your parents turn you into a human lab rat when you&’re a child? Will that change the story of your life? Will that change who you are? When Susannah Breslin is a toddler, her parents enroll her in an exclusive laboratory preschool at the University of California, Berkeley, where she becomes one of over a hundred children who are research subjects in an unprecedented thirty-year study of personality development that predicts who she and her cohort will grow up to be. Decades later, trapped in what she feels is an abusive marriage and battling breast cancer, she starts to wonder how growing up under a microscope shaped her identity and life choices. Already a successful journalist, she makes her own curious history the subject of her next investigation. From experiment rooms with one-way mirrors, to children&’s puzzles with no solutions, to condemned basement laboratories, her life-changing journey uncovers the long-buried secrets hidden behind the renowned study. The question at the gnarled heart of her quest: Did the study know her better than she knew herself? At once bravely honest and sharply witty, Data Baby is a compelling and provocative account of a woman&’s quest to find her true self, and an unblinking exploration of why we turn out as we do. Few people in all of history have been studied from such a young age and for as long as this author, but the message of her book is universal. In an era when so many of us are looking to technology to tell us who to be, it&’s up to us to discover who we actually are.
Data Borders: How Silicon Valley Is Building an Industry around Immigrants
by Melissa Villa-NicholasData Borders investigates entrenched and emerging borderland technology that ensnares all people in an intimate web of surveillance where data resides and defines citizenship. Detailing the new trend of biologically mapping undocumented people through biotechnologies, Melissa Villa-Nicholas shows how surreptitious monitoring of Latinx immigrants is the focus of and driving force behind Silicon Valley's growing industry within defense technology manufacturing. Villa-Nicholas reveals a murky network that gathers data on marginalized communities for purposes of exploitation and control that implicates law enforcement, border patrol, and ICE, but that also pulls in public workers and the general public, often without their knowledge or consent. Enriched by interviews of Latinx immigrants living in the borderlands who describe their daily use of technology and their caution around surveillance, this book argues that in order to move beyond a heavily surveilled state that dehumanizes both immigrants and citizens, we must first understand how our data is being collected, aggregated, correlated, and weaponized with artificial intelligence and then push for immigrant and citizen information privacy rights along the border and throughout the United States.
Data Breach at Equifax
by Suraj Srinivasan Quinn PitcherExamining the cause of and response to the 2017 data breach at Equifax that exposed the information of over 145 million consumers.
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 Centre Essentials: Design, Construction, and Operation of Data Centres for the Non-expert
by Vincent Fogarty Sophia FluckerData Centre Essentials Understand the design, construction and operation of data centres with this easy-to-use reference Data centres are spaces where computer systems, physical network technology and associated components are housed, operated and monitored, and any industry or business that employs computer systems or networked systems at any scale will interact with data centres. Data centres are complex and expensive to build and operate, and successful project delivery requires a wide range of specialised knowledge and skills. This accessible reference lays out the requirements for creating these essential facilities. Data Centre Essentials is a comprehensive survey of the essential principles of data centre design, construction and operation. It is designed to provide those involved in a data centre project or providing professional service deliverables to the data centre industry but do not have a technical background or deep sector experience with the understanding required to participate in such projects. The non-technical language and thorough engagement with key considerations make it ideal for anyone looking to understand one of the pillars of a digital society. Data Centre Essentials readers will also find: An authorial team with decades of combined experience in engineering and construction consultancy Detailed information about every stage in the process, including securing investment and the building process Working lexicon of key data centre terminology Data Centre Essentials is a must-own for contractors, engineers and construction project managers involved in data centre projects and will be invaluable for professionals such as lawyers, financial and insurance advisors, surveyors, engineers and architects who do not necessarily have deep domain experience but find themselves involved in or are interested in engaging in, data centre projects.
Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem
by Alex Khang Geeta Rana R. K. Tailor Vugar AbdullayevThe book offers insight into the healthcare system by exploring emerging technologies and AI-based applications and implementation strategies. It includes current developments for future directions as well as covering the concept of the healthcare system along with its ecosystem. Data-Centric AI Solutions and Emerging Technologies in the Healthcare Ecosystem focuses on the mechanisms of proposing and incorporating solutions along with architectural concepts, design principles, smart solutions, decision-making process, and intelligent predictions. It offers state-of-the-art approaches for overall innovations, developments, and implementation of the smart healthcare ecosystem and highlights medical signal and image processing algorithms, healthcare-based computer vision systems, and discusses explainable AI (XAI) techniques for healthcare. This book will be useful to researchers involved in AI, IoT, Data, and emerging technologies in the medical industry. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.
A Data-Centric Approach to Breaking the FDI Trap Through Integration in Global Value Chains: A Case Study from Clothing Manufacturing Enterprises in Albania (Lecture Notes on Data Engineering and Communications Technologies #50)
by Jolta KacaniThis book reveals the hidden potential of emerging economies to become the new industrial hubs in existing global value chains. Pursuing a data-centric approach, it investigates the presence of foreign direct investment as an instrument for emerging economies to promote active participation in global value chains. This approach is based on time series analyses conducted at the national and industry level, and on datasets retrieved from international databases such as EORA, ICIO, and World Integrated Solutions. The outcomes of robust statistical models indicate that export-related innovations can improve trade openness and transform emerging economies into active players in global value chains. Researchers, developers, and professionals in the field will find a comprehensive and self-contained guide to the topic.
Data Centric Artificial Intelligence: A Beginner’s Guide (Data-Intensive Research)
by Parikshit N. Mahalle Gitanjali R. Shinde Yashwant S. Ingle Namrata N. WasatkarThis book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.