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The current reprint presents studies of uncertain variational problems. It aims to develop the research in this field by formulating and demonstrating some characterization results of well-posedness and robust efficient solutions in new classes of (multiobjective) variational (control) problems governed by multiple and/or path-independent curvilinear integral cost functionals and robust mixed and/or isoperimetric constraints involving first- and second-order partial differential equation.
Electronic data processing. --- Computer science. --- Informatics --- Science --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Automation
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Electronic data processing. --- Punched card systems. --- Codes for punched card systems --- Data processing --- Perforated card systems --- Punch-card systems --- Punched card systems --- Card system in business --- Computer input-output equipment --- Computer storage devices --- Indexing --- Information storage and retrieval systems --- Information theory --- Tabulating machines --- ADP (Data processing) --- Automatic data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Business --- Automation
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The use of data to guide action is growing. Even the public uses data to guide everyday decisions! How do we develop data acumen across a broad range of fields and varying levels of expertise? How do we foster the development of effective data translators? This book explores these questions, presenting an interdisciplinary collection of edited contributions across fields such as education, health sciences, natural sciences, politics, economics, business and management studies, social sciences, and humanities. Authors illustrate how to use data within a discipline, including visualization and analysis, translating and communicating results, and pedagogical considerations. This book is of interest to scholars and anyone looking to understand the use of data science across disciplines. It is ideal in a course for non-data science majors exploring how data translation occurs in various contexts and for professionals looking to engage in roles requiring data translation.
Big data. --- Electronic data processing. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Data sets, Large --- Large data sets --- Data sets --- Automation --- Engineering—Data processing. --- Computational intelligence. --- Data Engineering. --- Computational Intelligence. --- Big Data. --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Mathematics
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This book explores the most recent Edge and Distributed Cloud computing research and industrial advances, settling the basis for Advanced Swarm Computing developments. It features the Swarm computing concepts and realizes it as an Ad-hoc Edge Cloud architecture. Unlike current techniques in Edge and Cloud computing that solely view IoT connected devices as sources of data, Swarm computing aims at using the compute capabilities of IoT connected devices in coordination with current Edge and Cloud computing innovations. In addition to being more widely available, IoT-connected devices are also quickly becoming more sophisticated in terms of their ability to carry considerable compute and storage resources. Swarm computing and Ad-hoc Edge Cloud take full advantage of this trend to create on-demand, autonomic and decentralized self-managed computing infrastructures. Focusing on cognitive resource and service, the book examines the specific research challenges of the Swarm computing approach, related to the characteristics of IoT connected devices that form the infrastructure. It also offers academics and practitioners insights for future research in the fields of Edge and Swarm computing.
Cloud Computing. --- Mobile computing. --- Internet of things. --- Mobile Computing. --- Internet of Things. --- IoT (Computer networks) --- Things, Internet of --- Computer networks --- Embedded Internet devices --- Machine-to-machine communications --- Electronic data processing --- Context-aware computing --- Portable computers --- Web services --- Distributed processing --- Cloud computing. --- Swarm intelligence. --- Technological innovations. --- Collective intelligence --- Cellular automata --- Distributed artificial intelligence --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Automation --- Processament de dades --- Intel·ligència col·lectiva --- Computació en núvol
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In smart cities, the indispensable devices used in people’s daily lives, such as smartphones, smartwatches, vehicles, and smart buildings, are equipped with more and more sensors. For example, most smartphones now have cameras, GPS, acceleration and light sensors. Leveraging the massive sensing data produced by users’ common devices for large-scale, fine-grained sensing in smart cities is referred to as the urban crowdsensing. It can enable applications that are beneficial to a broad range of urban services, including traffic, wireless communication service (4G/5G), and environmental protection. In this book, we provide an overview of our recent research progress on urban crowdsensing. Unlike the extant literature, we focus on multi-dimensional urban sensing using crowdsensing data. Specifically, the book explores how to utilize crowdsensing to see smart cities in terms of three-dimensional fundamental issues, including how to incentivize users’ participation, how to recommend tasks, and how to transmit the massive sensing data. We propose a number of mechanisms and algorithms to address these important issues, which are key to utilizing the crowdsensing data for realizing urban applications. Moreover, we present how to exploit this available crowdsensing data to see smart cities through three-dimensional applications, including urban pollution monitoring, traffic volume prediction, and urban airborne sensing. More importantly, this book explores using buildings’ sensing data for urban traffic sensing, thus establishing connections between smart buildings and intelligent transportation. Given its scope, the book will be of particular interest to researchers, students, practicing professionals, and urban planners. Furthermore, it can serve as a primer, introducing beginners to mobile crowdsensing in smart cities and helping them understand how to collect and exploit crowdsensing data for various urban applications.
Mobile computing. --- Computer networks. --- Cloud Computing. --- Mobile Computing. --- Computer Communication Networks. --- Electronic data processing --- Web services --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Context-aware computing --- Portable computers --- Distributed processing --- Electronic data processing. --- Remote sensing. --- Smart cities. --- Cities and towns --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Remote-sensing imagery --- Remote sensing systems --- Remote terrain sensing --- Sensing, Remote --- Terrain sensing, Remote --- Aerial photogrammetry --- Aerospace telemetry --- Detectors --- Space optics --- Automation
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This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown. The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers. The Content Introduction to Data Science Systems, tools and methods Applications The target groups IT consultants and management consultants Project managers and project staff Students and teachers of business informatics, computer science and business administration The editors Prof. Dr Thomas Barton is a professor at Worms University of Applied Sciences. His focus is on the development of operational applications, e-business, cloud computing and data science. Prof. Dr Christian Müller is a professor at the Technical University of Wildau. His focus is on operations research, simulation of business processes and internet technologies.
Big data. --- Data mining. --- Electronic data processing. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data sets, Large --- Large data sets --- Data sets --- Automation --- Artificial intelligence—Data processing. --- Information storage and retrieval systems. --- Business information services. --- Business—Data processing. --- Data Science. --- Information Storage and Retrieval. --- Data Mining and Knowledge Discovery. --- IT in Business. --- Business Informatics. --- Big Data. --- Business --- Business enterprises --- Information services --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data centers --- Digital libraries --- Information organization --- Information retrieval --- Dades massives --- Processament de dades --- Aprenentatge automàtic --- Mineria de dades
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This study companion helps you prepare for the SnowPro Core Certification exam. The author guides your studies so you will not have to tackle the exam by yourself. To help you track your progress, chapters in this book correspond to the exam domains as described on Snowflake’s website. Upon studying the material in this book, you will have solid knowledge that should give you the best shot possible at taking and passing the exam and earning the certification you deserve. Each chapter provides explanations, instructions, guidance, tips, and other information with the level of detail that you need to prepare for the exam. You will not waste your time with unneeded detail and advanced content which is out of scope of the exam. Focus is kept on reviewing the materials and helping you become familiar with the content of the exam that is recommended by Snowflake. This Book Helps You Review the domains that Snowflake specifically recommends you study in preparation for Exam COF-C02 Identify gaps in your knowledge that you can study and fill in to increase your chances of passing Exam COF-C02 Level up your knowledge even if not taking the exam, so you know the same material as someone who has taken the exam Learn how to set up a Snowflake account and configure access according to recommended security best practices Be capable of loading structured and unstructured data into Snowflake as well as unloading data from Snowflake Understand how to apply Snowflake data protection features such as cloning, time travel, and fail safe Review Snowflake’s data sharing capabilities, including data marketplace and data exchange.
Database management. --- Big data. --- Quantitative research. --- Data mining. --- Database Management. --- Big Data. --- Data Analysis and Big Data. --- Data Mining and Knowledge Discovery. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data analysis (Quantitative research) --- Exploratory data analysis (Quantitative research) --- Quantitative analysis (Research) --- Quantitative methods (Research) --- Research --- Data sets, Large --- Large data sets --- Data sets --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- Electronic data processing personnel --- Certification. --- Examinations --- Certification --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Automation
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This book constitutes the refereed proceedings of the 19th International Conference on Economics of Grids, Clouds, Systems, and Services, GECON 2022, held in Izola, Slovenia, in September 2022. The 4 full papers presented in this book were carefully reviewed and selected from 22 submissions. In addition, this book includes 6 work-in-progress papers, 4 new ideas paper, and two invited papers. This series of conferences serves as a meeting place to bring together distributed systems expertise (e.g., in resource allocation, quality of service management, and energy consumption) with economics expertise (focusing on both micro- and macro-economic modelling and analysis) for creating effective solutions in this space. .
Computer networks. --- Computers, Special purpose. --- Computer systems. --- Programming languages (Electronic computers). --- Operating systems (Computers). --- Artificial intelligence. --- Computer Communication Networks. --- Special Purpose and Application-Based Systems. --- Computer System Implementation. --- Programming Language. --- Operating Systems. --- Artificial Intelligence. --- Computer languages --- Computer program languages --- Computer programming languages --- Machine language --- Electronic data processing --- Languages, Artificial --- ADP systems (Computer systems) --- Computing systems --- Systems, Computer --- Electronic systems --- Cyberinfrastructure --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Computer operating systems --- Computers --- Disk operating systems --- Systems software --- Special purpose computers --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Information networks --- Telecommunication --- Network computers --- Operating systems --- Distributed processing --- Cloud computing --- Computational grids (Computer systems) --- Economic aspects --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Office practice --- Web services --- Automation --- Processament distribuït de dades --- Condicions econòmiques --- Computació distribuïda --- Computació en núvol
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