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Das Weltbild der Circular Economy und Bioökonomie: Vorbild Natur?
by Thomas Marzi Manfred RennerDies ist ein Open-Access-Buch. Bei der Suche nach neuen Wirtschaftsformen richten sich viele Hoffnungen auf die Circular Economy und Bioökonomie. Beiden wird das Potenzial zugesprochen, die Natur mit ihren Ressourcen zu schützen und gleichzeitig wirtschaftliches Wachstum zu ermöglichen. Welche Vorstellungen aber wirken in ihrem Hintergrund? Bei beiden Konzepten spielen die „Kreisläufe der Natur“ eine wesentliche Rolle. In manchen Denkschulen der Circular Economy sind sie ein Vorbild, nach dem Wirtschaftsprozesse gestaltet werden sollen. In der Bioökonomie sind sie „die“ Grundlage des Wirtschaftens. Dieses „Weltbild der Circular Economy und Bioökonomie“ ist Thema des vorliegenden Buches.
Das Weltbudget: Sichere und faire Ressourcennutzung als globale Überlebensstrategie
by Stefan BringezuDieses Buch beschreibt die zukunftsfähige Gestaltung der physischen Basis von Wirtschaft und Gesellschaft insgesamt durch eine gerechte Steuerung des weltweiten Ressourcenverbrauchs.Es erläutert Strategien, die die Entwicklung von Gesellschaften und Individuen auch bei begrenztem Güterverbrauch ermöglichen und gleichzeitig dem universellen Bedürfnis des Menschen nach Sicherheit und Unabhängigkeit entgegenkommen. Die Idee eines Weltbudgets der globalen Ressourcennutzung kann als wichtige Referenz für das Management auf der internationalen, nationalen und lokalen Ebene dienen und den Verbrauch weltweit auf eine sichere und faire Basis stellen. So lassen sich wirksame Hebel gezielt dort ansetzen, wo der Verbrauch wesentlich bestimmt wird: bei Art und Umfang von Produktion und Konsum sowie der Gestaltung der Infrastrukturen.Als Zielorientierung und Referenz dienen konkrete Obergrenzen für die Nutzung globaler Ressourcen, um ein gutes Leben für alle auf diesem Planeten zu sichern.
Das Zwillingsparadoxon (essentials)
by Helmut GüntherDie bewegte Uhr geht nach. – Zwei Zwillinge bewegen sich in entgegengesetzter Richtung. Beide beobachten, dass die Uhr des anderen nachgeht. Dann kommen sie wieder zusammen und stellen fest: Jünger ist, wer seine Geschwindigkeit geändert hat. Eine elementare Erklärung dafür folgt aus einer Kette von Ungleichungen auf der Basis der Zeitdilatation. Mit Hilfe der Definition einer absoluten Gleichzeitigkeit finden wir eine weitere, einfache Erklärung. Hierbei ist es wichtig, den definitorischen Charakter der Gleichzeitigkeit zu verstehen. Alternativ zu Einsteins Herleitung formulieren wir einen anschaulichen Zugang zur Speziellen Relativitätstheorie. Dabei können wir über die Gleichzeitigkeit frei verfügen und lösen das Paradoxon sowohl mit der Lorentz-Transformation als auch bei absoluter Gleichzeitigkeit.
Das Zwillingsparadoxon unter Berücksichtigung der Gravitation (essentials)
by Helmut GüntherDie bewegte Uhr und eine Uhr im Gravitationsfeld gehen nach. Das berühmte Paradoxon von den Zwillingen, die sich erst voneinander entfernen und dann wieder zusammenkommen, untersuchen wir zunächst im speziell-relativistischen Gedankenexperiment, also ohne Gravitation. Der Zwilling, der seinen Bruder mit einer höheren Geschwindigkeit wieder einholt, bleibt am Ende der jüngere, was sich mit der sog. Zwillingsungleichung einfach verifizieren lässt.Die Gravitation kann prinzipiell nicht abgeschirmt werden. Ihren Einfluss auf den Gang einer Uhr verstehen wir mit einem Gedankenexperiment von V. Müller. Während die Zwillinge betragsmäßig immer dieselbe Geschwindigkeit zueinander besitzen, gelangen sie aber bei ihrer Bewegung durch den Raum in die Nähe verschiedener Massen, so dass sie unterschiedlicher Gravitation ausgesetzt sind. Das kann dazu führen, dass am Ende der zurückkehrende Zwilling sogar der ältere ist.
Data: New Trajectories in Law (New Trajectories in Law)
by Robert HerianThis book explores the phenomenon of data – big and small – in the contemporary digital, informatic and legal-bureaucratic context. Challenging the way in which legal interest in data has focused on rights and privacy concerns, this book examines the contestable, multivocal and multifaceted figure of the contemporary data subject. The book analyses "data" and "personal data" as contemporary phenomena, addressing the data realms, such as stores, institutions, systems and networks, out of which they emerge. It interrogates the role of law, regulation and governance in structuring both formal and informal definitions of the data subject, and disciplining data subjects through compliance with normative standards of conduct. Focusing on the ‘personal’ in and of data, the book pursues a re-evaluation of the nature, role and place of the data subject qua legal subject in on and offline societies: one that does not begin and end with the inviolability of individual rights but returns to more fundamental legal principles suited to considerations of personhood, such as stewardship, trust, property and contract. The book’s concern with the production, use, abuse and alienation of personal data within the context of contemporary communicative capitalism will appeal to scholars and students of law, science and technology studies, and sociology; as well as those with broader political interests in this area.
Data Analysis and Classification: Methods and Applications (Studies in Classification, Data Analysis, and Knowledge Organization)
by Krzysztof Jajuga Krzysztof Najman Marek WalesiakThis volume gathers peer-reviewed contributions that address a wide range of recent developments in the methodology and applications of data analysis and classification tools in micro and macroeconomic problems. The papers were originally presented at the 29th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2020, held in Sopot, Poland, September 7–9, 2020. Providing a balance between methodological contributions and empirical papers, the book is divided into five parts focusing on methodology, finance, economics, social issues and applications dealing with COVID-19 data. It is aimed at a wide audience, including researchers at universities and research institutions, graduate and doctoral students, practitioners, data scientists and employees in public statistical institutions.
Data Analysis for Direct Numerical Simulations of Turbulent Combustion: From Equation-Based Analysis to Machine Learning
by Heinz Pitsch Antonio AttiliThis book presents methodologies for analysing large data sets produced by the direct numerical simulation (DNS) of turbulence and combustion. It describes the development of models that can be used to analyse large eddy simulations, and highlights both the most common techniques and newly emerging ones. The chapters, written by internationally respected experts, invite readers to consider DNS of turbulence and combustion from a formal, data-driven standpoint, rather than one led by experience and intuition. This perspective allows readers to recognise the shortcomings of existing models, with the ultimate goal of quantifying and reducing model-based uncertainty. In addition, recent advances in machine learning and statistical inferences offer new insights on the interpretation of DNS data. The book will especially benefit graduate-level students and researchers in mechanical and aerospace engineering, e.g. those with an interest in general fluid mechanics, applied mathematics, and the environmental and atmospheric sciences.
Data Analysis for Research Designs: Analysis of Variance and Multiple Regression/Correlation Approaches
by Geoffrey Keppel Sheldon ZedeckData Analysis for Research Designs covers the analytical techniques for the analysis of variance (ANOVA) and multiple regression/correlation (MRC), emphasizing single-degree-of-freedom comparisons so that students focus on clear research planning. This text is designed for advanced undergraduates and graduate students of the behavioral and social sciences who have an understanding of algebra and statistics.
Data Analysis for the Life Sciences with R
by Rafael A. Irizarry Michael I. LoveThis book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
Data Analysis in High Energy Physics
by Kevin Kröninger Olaf Behnke Thomas Schörner-Sadenius Grégory SchottThis practical guide covers the essential tasks in statistical data analysis encountered in high energy physics and provides comprehensive advice for typical questions and problems. The basic methods for inferring results from data are presented as well as tools for advanced tasks such as improving the signal-to-background ratio, correcting detector effects, determining systematics and many others. Concrete applications are discussed in analysis walkthroughs. Each chapter is supplemented by numerous examples and exercises and by a list of literature and relevant links. The book targets a broad readership at all career levels - from students to senior researchers. An accompanying website provides more algorithms as well as up-to-date information and links.* Free solutions manual available for lecturers at www.wiley-vch.de/supplements/
Data Analysis in Vegetation Ecology
by Otto WildiThe 3rd edition of this popular textbook introduces the reader to the investigation of vegetation systems with an emphasis on data analysis. The book succinctly illustrates the various paths leading to high quality data suitable for pattern recognition, pattern testing, static and dynamic modelling and model testing including spatial and temporal aspects of ecosystems. Step-by-step introductions using small examples lead to more demanding approaches illustrated by real world examples aimed at explaining interpretations. All data sets and examples described in the book are available online and are written using the freely available statistical package R. This book will be of particular value to beginning graduate students and postdoctoral researchers of vegetation ecology, ecological data analysis, and ecological modelling, and experienced researchers needing a guide to new methods. A completely revised and updated edition of this popular introduction to data analysis in vegetation ecology. Includes practical step-by-step examples using the freely available statistical package R. Complex concepts and operations are explained using clear illustrations and case studies relating to real world phenomena. Emphasizes method selection rather than just giving a set of recipes.
Data Analysis in Vegetation Ecology
by Otto WildiThe first edition of Data Analysis in Vegetation Ecology provided an accessible and thorough resource for evaluating plant ecology data, based on the author's extensive experience of research and analysis in this field. Now, the Second Edition expands on this by not only describing how to analyse data, but also enabling readers to follow the step-by-step case studies themselves using the freely available statistical package R. The addition of R in this new edition has allowed coverage of additional methods for classification and ordination, and also logistic regression, GLMs, GAMs, regression trees as well as multinomial regression to simulate vegetation types. A package of statistical functions, specifically written for the book, covers topics not found elsewhere, such as analysis and plot routines for handling synoptic tables. All data sets presented in the book are now also part of the R package 'dave', which is freely available online at the R Archive webpage. The book and data analysis tools combined provide a complete and comprehensive guide to carrying out data analysis students, researchers and practitioners in vegetation science and plant ecology.Summary:A completely revised and updated edition of this popular introduction to data analysis in vegetation ecologyNow includes practical examples using the freely available statistical package 'R'Written by a world renowned expert in the fieldComplex concepts and operations are explained using clear illustrations and case studies relating to real world phenomenaHighlights both the potential and limitations of the methods used, and the final interpretationsGives suggestions on the use of the most widely used statistical software in vegetation ecology and how to start analysing dataPraise for the first edition: "This book will be a valuable addition to the shelves of early postgraduate candidates and postdoctoral researchers. Through the excellent background material and use of real world examples, Wildi has taken the fear out of trying to understand these much needed data analysis techniques in vegetation ecology." Austral Ecology
Data Analysis in Vegetation Ecology, 3rd Edition
by Otto WildiThe third edition of this popular textbook introduces the reader to the investigation of vegetation systems with an emphasis on data analysis. The book succinctly illustrates the various paths leading to high quality data suitable for pattern recognition, pattern testing, static and dynamic modeling, and model testing, including spatial and temporal aspects of ecosystems. Step-by-step introductions using small examples lead to more demanding approaches illustrated by real world examples aimed at explaining interpretations. All data sets and examples described in the book are available online and are written using the freely available statistical package R. This book will be of particular value to beginning graduate students and postdoctoral researchers of vegetation ecology, ecological data analysis, and ecological modeling as well as to experienced researchers needing a guide to new methods. Features: - Completely revised and updated - Includes practical step-by-step examples using the freely available statistical package R - Complex concepts and operations are explained using clear illustrations and case studies relating to real world phenomena - Emphasizes method selection rather than just giving a set of recipes.
Data Analysis Techniques for Physical Scientists
by Claude A. PruneauA comprehensive guide to data analysis techniques for physical scientists, providing a valuable resource for advanced undergraduate and graduate students, as well as seasoned researchers. The book begins with an extensive discussion of the foundational concepts and methods of probability and statistics under both the frequentist and Bayesian interpretations of probability. It next presents basic concepts and techniques used for measurements of particle production cross-sections, correlation functions, and particle identification. Much attention is devoted to notions of statistical and systematic errors, beginning with intuitive discussions and progressively introducing the more formal concepts of confidence intervals, credible range, and hypothesis testing. The book also includes an in-depth discussion of the methods used to unfold or correct data for instrumental effects associated with measurement and process noise as well as particle and event losses, before ending with a presentation of elementary Monte Carlo techniques.
Data Analytics: Proceedings Of 4th Conference On Sustainable Urban Mobility (csum2018), 24 - 25 May, Skiathos Island, Greece (Advances In Intelligent Systems and Computing #879)
by Eftihia G. Nathanail Ioannis D. KarakikesThis book aims at showing how big data sources and data analytics can play an important role in sustainable mobility. It is especially intended to provide academicians, researchers, practitioners and decision makers with a snapshot of methods that can be effectively used to improve urban mobility. The different chapters, which report on contributions presented at the 4th Conference on Sustainable Urban Mobility, held on May 24-25, 2018, in Skiathos Island, Greece, cover different thematic areas, such as social networks and traveler behavior, applications of big data technologies in transportation and analytics, transport infrastructure and traffic management, transportation modeling, vehicle emissions and environmental impacts, public transport and demand responsive systems, intermodal interchanges, smart city logistics systems, data security and associated legal aspects. They show in particular how to apply big data in improving urban mobility, discuss important challenges in developing and implementing analytics methods and provide the reader with an up-to-date review of the most representative research on data management techniques for enabling sustainable urban mobility
Data Analytics and Learning: Proceedings of Dal 2018 (Lecture Notes in Networks and Systems #43)
by P. Nagabhushan D. S. Guru B. H. Shekar Y. H. Sharath KumarThis paper describes a method to localize and recognize seven-segment displays on digital energy meters. Color edge detection is first performed on a camera-captured image of the device which is then followed by a run-length technique to detect horizontal and vertical lines. The region of interest circumscribing the LCD panel is determined based on the attributes of intersecting horizontal and vertical lines. The extracted display region is preprocessed using the morphological black-hat operation to enhance the text strokes. Adaptive thresholding is then performed and the digits are segmented based on stroke features. Finally, the segmented digits are recognized using a support vector machine classifier trained on a set of syntactic rules defined for the seven-segment font. The proposed method can handle images exhibiting uneven illumination, the presence of shadows, poor contrast, and blur, and yields a recognition accuracy of 97% on a dataset of 175 images of digital energy meters captured using a mobile camera.
Data Analytics for Drilling Engineering: Theory, Algorithms, Experiments, Software (Information Fusion and Data Science)
by Qilong XueThis book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to overcome them. In drilling engineering, many signal processing technologies are required to solve practical problems, such as downhole information transmission, spatial attitude of drillstring, drillstring dynamics, seismic activity while drilling, among others. This title attempts to bridge the gap between the signal processing and data mining and oil and gas drilling engineering communities. There is an urgent need to summarize signal processing and data mining issues in drilling engineering so that practitioners in these fields can understand each other in order to enhance oil and gas drilling functions. In summary, this book shows the importance of signal processing and data mining to researchers and professional drilling engineers and open up a new area of application for signal processing and data mining scientists.
Data Analytics for Process Engineers: Prediction, Control and Optimization (Synthesis Lectures on Mechanical Engineering)
by Daniela Galatro Stephen DaweThis book provides an industry-oriented data analytics approach for process engineers, including data acquisition methods and sources, exploratory data analysis and sensitivity analysis, data-based modelling for prediction, data-based modelling for monitoring and control, and data-based optimization of processes. While many of the current data analytics books target business-related problems, the rationale for this book is a specific need to understand and select applicable data analytics approaches pragmatically to analyze process engineering–related problems; this tailored solution for engineers gets amalgamated with governing equations, and in several cases, with the physical understanding of the phenomenon being analyzed. We also consider this book strategically conceived to help map Education 4.0 with Industry 4.0 since it can support undergraduate and graduate students to gain valuable and applicable data analytics stills that can be further used in their workplace. Moreover, it can be used as a reference book for professionals, a quick reference to data analytics tools that can facilitate and/or optimize their process engineering tasks.
Data Analytics for Protein Crystallization
by Marc L. Pusey Ramazan Savaş AygünThis unique text/reference presents an overview of the computational aspects of protein crystallization, describing how to build robotic high-throughput and crystallization analysis systems. The coverage encompasses the complete data analysis cycle, including the set-up of screens by analyzing prior crystallization trials, the classification of crystallization trial images by effective feature extraction, the analysis of crystal growth in time series images, the segmentation of crystal regions in images, the application of focal stacking methods for crystallization images, and the visualization of trials.Topics and features: describes the fundamentals of protein crystallization, and the scoring and categorization of crystallization image trials; introduces a selection of computational methods for protein crystallization screening, and the hardware and software architecture for a basic high-throughput system; presents an overview of the image features used in protein crystallization classification, and a spatio-temporal analysis of protein crystal growth; examines focal stacking techniques to avoid blurred crystallization images, and different thresholding methods for binarization or segmentation; discusses visualization methods and software for protein crystallization analysis, and reviews alternative methods to X-ray diffraction for obtaining structural information; provides an overview of the current challenges and potential future trends in protein crystallization.This interdisciplinary work serves as an essential reference on the computational and data analytics components of protein crystallization for the structural biology community, in addition to computer scientists wishing to enter the field of protein crystallization.
Data Analytics for Renewable Energy Integration. Technologies, Systems and Society: 6th ECML PKDD Workshop, DARE 2018, Dublin, Ireland, September 10, 2018, Revised Selected Papers (Lecture Notes in Computer Science #11325)
by Wei Lee Woon Zeyar Aung Alejandro Catalina Feliú Stuart MadnickThis book constitutes the revised selected papers from the 6th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2018, held in Dublin, Ireland, in September 2018. The 9 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 Supply Chain Networks (Greening of Industry Networks Studies #11)
by Niamat Ullah Ibne HossainThe objective of the book is to adopt the application of data analytics to enhance the sustainability and resilience of the green supply chain networks. To demonstrate the applicability and usefulness of the method, the book adopts different data analytic models and approaches against the backdrop of case studies. In summary, this book attempts to address the question of methods, tools, and techniques that can be used to create resilient, anti-fragile, reliable, and invulnerable green supply chain networks.
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 Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV)
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 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 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.
The Data Book of Astronomy
by Patrick MooreFilled with data about the Earth, Moon, the planets, the stars, our Galaxy, and the myriad galaxies in deep space, this invaluable resource reveals the latest scientific discoveries about black holes, quasars, and the origins of the Universe. It includes maps supported by detailed tables of the names, positions, magnitudes, and spectra of the main stars in each constellation along with key data on galaxies, nebulae, and clusters. MNASSA wrote, "This book fills a niche � with detailed astronomical data and concise explanations, all at an accessible level � it is an excellent resource, and probably will be the first book I shall reach for.