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Omylska B: Ultrasonic Measurement and
Characterization of Liquid-Particle Flo

Ultrasonic Measurement and Characterization of Liquid-Particle Flow

Petroleum Production Engineering with Data Science

Big Data Management

This book demystifies the core principles and architectural design of spatiotemporal big data systems, offering incisive analysis of the unique attributes of spatiotemporal data and its broad applicability in real-world scenarios, aiming to impart a profound understanding of the intrinsic value of spatiotemporal big data and its far-reaching impact across various fields.In the core technology section, particular emphasis is placed on the pivotal role of GIS (Geographic Information Systems) technology in the processing of spatiotemporal big data, comprehensively covering the entire process from data collection, pre-processing, in-depth analysis to final visualization. Through carefully selected real-world cases and detailed technical explanations, readers will gain proficiency in leveraging GIS technology to uncover the latent value of spatiotemporal big data.The book also delves into the essential techniques and algorithms required for building efficient spatiotemporal big data systems, such as efficient data storage and management, intelligent data mining and analysis, alongside specific application cases under the smart city framework, including advanced practices in urban planning optimization, traffic management innovation, and environmental monitoring upgrades. Rich in content and blending theoretical depth with practical guidance, it serves as a valuable resource and reference guide for both academic experts and practitioners in the field, as well as a quality read for those intrigued by spatiotemporal big data systems.The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.

Concepts, Principles and Applications

Spatiotemporal Big Data Systems

Dieses Handbuch setzt dort an, wo die meisten Einführungstexte zur angewandten Statistik aufhören: Anerkannte Expertinnen und Experten führen in fortgeschrittene Methoden, Modelle und Konzepte der angewandten Statistik ein und geben Hinweise zur tiefergehenden Lektüre. Schwerpunkte sind dabei zum einen flexible Methoden und Modellklassen für Regressionsprobleme, die unterschiedliche Aspekte adressieren, welche im klassischen linearen Modell nicht adäquat abgebildet bzw. berücksichtigt werden können. Zu nennen sind hier beispielhaft die Verteilungsregression, generalisierte additive Modelle, Überlebenszeitanalysen und maschinelle Lernverfahren. Zum anderen werden zahlreiche Methoden der modernen statistischen Inferenz behandelt, wie etwa Bayesianische Ansätze, Bootstrap- und Permutationstests, kausale Inferenz oder Tests bei hochdimensionalen Daten. Abgerundet wird das Buch durch übergreifende Kapitel zu fehlenden Daten und reproduzierbarer bzw. replizierbarer Forschung. Die einzelnen Beiträge sind dabei unabhängig von den anderen Kapiteln lesbar. Das Handbuch wendet sich zum einen an Anwenderinnen und Anwender aus der Praxis sowie Promovierende und PostDocs mit soliden Grundkenntnissen der Statistik, die sich anhand kompakter Darstellungen von jeweils etwa 30 Seiten über weiterführende Themen der angewandten Statistik informieren möchten. Zum anderen ist das Buch geeignet für Studierende aus höheren Semestern in Studiengängen, in denen die adäquate und tiefergehende Analyse empirischer Daten von zentraler Bedeutung ist.Die HerausgeberJan Gertheiss ist Professor für Statistik und Data Science an der Fakultät für Wirtschafts- und Sozialwissenschaften der Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg. Seine Forschungsschwerpunkte liegen im anwendungsorientierten und -motivierten statistischen Lernen.Matthias Schmid ist Professor für Medizinische Biometrie, Informatik und Epidemiologie an der Medizinischen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn. Seine Forschungsschwerpunkte liegen im Bereich der Regressionsmodellierung, der Analyse von Überlebenszeiten und des statistischen Lernens.Martin Spindler ist Professor für Statistik an der Universität Hamburg. Seine Forschungsschwerpunkte liegen sowohl in&nbsp;der Theorie als auch der Anwendung non maschinellem Lernen, Deep Learning und Causal Machine Learning.

Handbuch fortgeschrittener Modelle, Methoden und Konzepte

Moderne Verfahren der Angewandten Statistik

The SAS ecosystem is evolving. Whether you work with SAS Viya or SAS 9, there's never been a better time to dive in and master its full potential. This bookguides you through the technologies and environments that make SAS a powerful asset in data analytics, revealing the surprising depth and rich capabilities that SAS offers.This comprehensive guide is tailored for consultants and operations teams, covering everything from strategic analysis and architecture to implementation, administration, and best practices. You'll explore the analytics landscape across both commercial and open-source systems, learning how to design, deploy, and manage SAS environments effectively.By the end of this book, you'll be equipped to confidently implement and operate SAS technology turning raw data into real insights and business value.You will:·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Understand Consulting, Operations and Process activities associated with SAS technologies·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Support SAS data sourcing and reporting deliveries·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Establish best practices and guidelines for usage of the SAS platform&nbsp;&nbsp;

Mastering SAS Consulting: Design, Deploy, and Manage Analytics Environments

A Practitioners' Guide to SAS

This book allows us to compare the strategies used by different economies in the world regarding implementing digital currencies in the monetary system and their impact on the green economy. It evaluates the effectiveness of such strategies concerning the sustainability model of the economy (green economy, circulated economy, doughnut economy). It offers case studies from Asia, Europe, and other regions from different sectors focusing on how the government operates under its policy in the given countries to fulfil the SDGs. Although the sustainable development policy is not new, this book brings together academicians and experts from different parts of the world to share their views and knowledge on this subject with a focus on case studies and regional perspectives.&nbsp; The range of problems analysed in this book has multiple layers namely macroeconomics, management, finance, technology focused on digital currencies, and public policies of local authorities &amp; Government.
Ranjan Aneja, Ph.D., is a Professor Economics at Central University of Haryana, India. His areas of interest are Economic Modelling and Policy Analysis and Macroeconomic stability.
Robert Dygas, Ph.D., is an assistant professor at SGH Warsaw School of Economics, East Asian Economic Studies Department in The World Economy Research Institute. His academic interests are geoeconomics, economies of Asian countries and International Business.

Opportunities and Challenges in Achieving Sustainable Development Goals (SDGs)

Digital Currencies and the Green Economy

Business Analytics in Practice

This book offers a comprehensive guide to blockchain analytics, from foundational concepts to advanced applications, crafted for professionals, academics, policymakers, and students. It begins with an introduction to blockchain technology and analytics, highlighting the unique structure of blockchain data, collection methods, and distinctions from traditional databases. Analytical techniques are covered in depth, including statistical and machine learning methods, real-time analysis, and predictive modeling.
It contains numerous practical industry use cases that demonstrate how blockchain analytics transforms finance, supply chain, and healthcare, enhancing fraud detection, data security, and product verification. Sections on security and privacy address tools to protect blockchain data and manage risks, while global regulatory insights emphasize transparency and policy development. It provides actionable insights on emerging integrations with AI, IoT, and quantum computing.
As such, industry leaders will discover frameworks for integrating blockchain into business, while academics gain insights into the analytic methodologies that underpin blockchain technology. Policymakers and government officials can use this resource to develop policies promoting transparency and security. For students and educators, the book serves as an essential foundation in blockchain, data analytics, and fintech.

Bridging Theory and Practice

Blockchain Analytics for Practitioners

Key Technologies on New Energy Vehicles

This book focuses on the current advanced technology field of battery operation big data and comprehensively describes the frontier technology of big data analysis and intelligent control of battery safe operation. The content systematically introduces the coupling mechanism of battery system safety and consistency, battery SOH estimation and prediction, battery safety state prediction, battery fault diagnosis, battery system risk pre-warning, and safety control strategy research.This book is suitable for teachers and students of universities and colleges in the automotive and related industries, engineers and technicians in the R&amp;D departments of enterprises or automotive enthusiasts to read and refer.The basis of English translation of this book, originally in Chinese, was facilitated by artificial intelligence. The content was later revised by the author for accuracy.

Big Data Analysis and Application of Power Battery Operation Safety

Reliable and Sustainable Electric Power and Energy Systems Management

This book discusses various aspects of future intelligent power grids, covering key topics including the operation of smart grids and microgrids, resource optimization, and energy management. Over the last few decades, the use of solar photovoltaics (PVs) and wind turbine generators has increased significantly in an effort to make future power systems sustainable. However, the intensive integration of renewables in existing electrical networks has raised several control and operational issues due to their limited dispatch capability and intermittent generation. In addition, integrating new electrical loads, such as those produced by electric vehicles, heat pumps, and electric water heaters, in existing distribution networks negatively impacts the power-balance scenario. As such, these developments present both challenges and opportunities for the research community.

Against this backdrop, the book not only discusses the challenges and their potential solutions, but also outlines future research directions that could help make future power grids intelligent, adaptive, and resilient. It presents insights from academia, industry, and research institutions on understanding, modeling, and analyzing the control and operation of intelligent power grids of the future.

Modeling, Planning, Control and Operation

Intelligent Power Grids of Tomorrow

Math for Data Science

Is your company struggling to get real value from data? Problem solved. This book is your guide to transforming an organization from one that treats data as an afterthought or merely a support function into one that makes data a key driver of product development and business innovation. In doing so, you’ll be able to measure outcomes that matter, rather than just tracking features shipped.In a world where products are increasingly driven by data and AI, traditional approaches to product development and data management have become barriers to growth rather than enablers of success. At its core, this book establishes two fundamental principles for success: autonomous, outcome/data-driven product teams and the need for data assets to be managed as products. These principles are then expanded into practical frameworks, step-by-step implementation guides, and maturity models, that cross-functional teams in any industry can incorporate in their decision-making.Whether you're a product manager wanting to become more data-fluent, a data professional aiming to increase your product impact, or a leader trying to break down silos in your organization, Data as a Product Driver provides practical steps to transform how your company uses data. What You Will Learn:<ul><li>Reorganize your teams around business problems instead of technical disciplines.</li><li>Manage the transition from centralized data teams to domain-driven decentralized data ownership.</li><li>Build effective data platform teams that enable product teams while maintaining consistent standards across your data ecosystem.</li><li>Create data assets that provide lasting value across your organization.</li><li>Implement the right operating model for your company's size and maturity level.</li></ul>

Strategies for Aligning Data and Product Teams to Transform Organizations

Data as a Product Driver

Universitext

This textbook provides a thorough-yet-accessible introduction to function spaces, through the central concepts of integrability, weakly differentiability and fractionally differentiability.In an essentially self-contained treatment the reader is introduced to Lebesgue, Sobolev and BV-spaces, before being guided through various generalisations such as Bessel-potential spaces, fractional Sobolev spaces and Besov spaces. Written with the student in mind, the book gradually proceeds from elementary properties to more advanced topics such as lower dimensional trace embeddings, fine properties and approximate differentiability, incorporating recent approaches. Throughout, the authors provide careful motivation for the underlying concepts, which they illustrate with selected applications from partial differential equations, demonstrating the relevance and practical use of function spaces.Assuming only multivariable calculus and elementary functional analysis, as conveniently summarised in the opening chapters,&nbsp;A Course in Function Spaces&nbsp;is designed for lecture courses at the graduate level and will also be a valuable companion for young researchers in analysis.

I: Spaces of continuous and integrable functions

A Course on Function Spaces

Produktentwicklung und Konstruktionstechnik

Forschungsergebnisse und -projekte der Jahre 2021 bis 2025

In der Kunststofftechnik gewinnt der Silikonkautschuk immer mehr an Bedeutung, da er aufgrund seiner hervorragenden Eigenschaften für eine Vielzahl an Anwendungen geeignet ist. In der Medizintechnik wird Silikonkautschuk unter anderem wegen seiner guten Verarbeitbarkeit und physiologischen Unbedenklichkeit anderen Kunststoffen vorgezogen; Im Bereich Automotive prädestiniert der breite Gebrauchstemperaturbereich von -50°C bis +200°C die Silikonkautschuke für Anwendungen im motornahen Bereich. Die hervorragenden Dämpfungs- und Haptikeigenschaften machen Silikonkautschuk für den Wachstumsmarkt der Consumer-Elektronikbranche interessant. Ziel ist es im Rahmen des Buches den Lesern einen fundierten Einblick in die Verarbeitung von Silikonkautschuk zu geben: Neben der heutigen Prüftechnik zur umfassenden Charakterisierung der mechanischen und physikalischen Eigenschaften, werden den Lesern diverse Möglichkeiten der Verarbeitung von Fest- und Flüssigsilikonkautschuk vorgestellt. Durch aktuelle Anwendungsbeispiele aus Industrie und Forschung werden die Zukunftspotentiale von Silikonkautschuk, auch in Verbindung mit anderen Werkstoffen, aufgezeigt.

Verarbeitung von Fest- und Flüssigsilikonkautschuken

Ultrasonic Measurement and Characterization of Liquid-Particle Flow

Autres titres sur ce thème