Model Management And Analytics For Large Scale Systems

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• Author : Bedir Tekinerdogan,Önder Babur,Loek Cleophas,Mark van den Brand,Mehmet Aksit
• Publisher : Academic Press
• Release Date : 2019-09-14
• Total pages : 344
• ISBN : 9780128166505
• File Size : 55,7 Mb
• Total Download : 291
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Download Model Management and Analytics for Large Scale Systems in PDF, Epub, and Kindle

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions

• Author : Boris Shishkov
• Publisher : Springer Nature
• Release Date : 2020-07-06
• Total pages : 395
• ISBN : 9783030523060
• File Size : 53,9 Mb
• Total Download : 868
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Download Business Modeling and Software Design in PDF, Epub, and Kindle

This book constitutes the refereed proceedings of the 10th International Symposium on Business Modeling and Software Design, BMSD 2020, which took place in Berlin, Germany, in July 2020. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling and Software Development; Blockchain-Based Business Models and Information Systems; IoT and Implications for Enterprise Information Systems. The theme of BMSD 2020 was: Towards Knowledge-Driven Enterprise Information Systems.

• Author : Ivan Mistrik,Matthias Galster,Bruce R. Maxim,Bedir Tekinerdogan
• Publisher : CRC Press
• Release Date : 2021-06-15
• Total pages : 342
• ISBN : 9781000387414
• File Size : 28,7 Mb
• Total Download : 167
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Download Knowledge Management in the Development of Data-Intensive Systems in PDF, Epub, and Kindle

Data-intensive systems are software applications that process and generate Big Data. Data-intensive systems support the use of large amounts of data strategically and efficiently to provide intelligence. For example, examining industrial sensor data or business process data can enhance production, guide proactive improvements of development processes, or optimize supply chain systems. Designing data-intensive software systems is difficult because distribution of knowledge across stakeholders creates a symmetry of ignorance, because a shared vision of the future requires the development of new knowledge that extends and synthesizes existing knowledge. Knowledge Management in the Development of Data-Intensive Systems addresses new challenges arising from knowledge management in the development of data-intensive software systems. These challenges concern requirements, architectural design, detailed design, implementation and maintenance. The book covers the current state and future directions of knowledge management in development of data-intensive software systems. The book features both academic and industrial contributions which discuss the role software engineering can play for addressing challenges that confront developing, maintaining and evolving systems;data-intensive software systems of cloud and mobile services; and the scalability requirements they imply. The book features software engineering approaches that can efficiently deal with data-intensive systems as well as applications and use cases benefiting from data-intensive systems. Providing a comprehensive reference on the notion of data-intensive systems from a technical and non-technical perspective, the book focuses uniquely on software engineering and knowledge management in the design and maintenance of data-intensive systems. The book covers constructing, deploying, and maintaining high quality software products and software engineering in and for dynamic and flexible environments. This book provides a holistic guide for those who need to understand the impact of variability on all aspects of the software life cycle. It leverages practical experience and evidence to look ahead at the challenges faced by organizations in a fast-moving world with increasingly fast-changing customer requirements and expectations.

• Author : Ananieva, Sofia
• Publisher : KIT Scientific Publishing
• Release Date : 2022-12-06
• Total pages : 310
• ISBN : 9783731512417
• File Size : 28,5 Mb
• Total Download : 756
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Download Consistent View-Based Management of Variability in Space and Time in PDF, Epub, and Kindle

Developing variable systems faces many challenges. Dependencies between interrelated artifacts within a product variant, such as code or diagrams, across product variants and across their revisions quickly lead to inconsistencies during evolution. This work provides a unification of common concepts and operations for variability management, identifies variability-related inconsistencies and presents an approach for view-based consistency preservation of variable systems.

• Author : Silvia Chiusano,Tania Cerquitelli,Robert Wrembel,Kjetil Nørvåg,Barbara Catania,Genoveva Vargas-Solar,Ester Zumpano
• Publisher : Springer Nature
• Release Date : 2022-08-29
• Total pages : 675
• ISBN : 9783031157431
• File Size : 55,8 Mb
• Total Download : 825
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Download New Trends in Database and Information Systems in PDF, Epub, and Kindle

This book constitutes the proceedings of the 26th European Conference on Advances in Databases and Information Systems, ADBIS 2022, held in Turin, Italy, in September 2022. The 29 short papers presented were carefully reviewed and selected from 90 submissions. The selected short papers are organized in the following sections: data understanding, modeling and visualization; fairness in data processing; data management pipeline, information and process retrieval; data access optimization; data pre-processing and cleaning; data science and machine learning. Further, papers from the following workshops and satellite events are provided in the volume: DOING: 3rd Workshop on Intelligent Data – From Data to Knowledge; K-GALS: 1st Workshop on Knowledge Graphs Analysis on a Large Scale; MADEISD: 4th Workshop on Modern Approaches in Data Engineering and Information System Design; MegaData: 2nd Workshop on Advanced Data Systems Management, Engineering, and Analytics; SWODCH: 2nd Workshop on Semantic Web and Ontology Design for Cultural Heritage; Doctoral Consortium.

• Author : Ashish Kumar Luhach,Dharm Singh Jat,Kamarul Hawari Bin Ghazali,Xiao-Zhi Gao,Pawan Lingras
• Publisher : Springer Nature
• Release Date : 2021-06-19
• Total pages : 683
• ISBN : 9789811636608
• File Size : 40,9 Mb
• Total Download : 578
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Download Advanced Informatics for Computing Research in PDF, Epub, and Kindle

This two-volume set (CCIS 1393 and CCIS 1394) constitutes selected and revised papers of the 4th International Conference on Advanced Informatics for Computing Research, ICAICR 2020, held in Gurugram, India, in December 2020. The 34 revised full papers and 51 short papers presented were carefully reviewed and selected from 306 submissions. The papers are organized in topical sections on computing methodologies; hardware; networks; security and privacy.

• Author : M. A. Jabbar,Fernando Ortiz-Rodríguez,Sanju Tiwari,Patrick Siarry
• Publisher : Springer Nature
• Release Date : 2023-05-26
• Total pages : 252
• ISBN : 9783031342226
• File Size : 54,8 Mb
• Total Download : 233
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Download Applied Machine Learning and Data Analytics in PDF, Epub, and Kindle

This book constitutes the refereed proceedings of the 5th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2022, held in Reynosa, Tamaulipas, Mexico, during December 22–23, 2022. The 16 full papers and 4 short papers included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: Machine learning, Healthcare and medical imaging informatics; biometrics; forensics; precision agriculture; risk management; robotics and satellite imaging.

• Author : Önder Babur,Joachim Denil,Birgit Vogel-Heuser
• Publisher : Springer Nature
• Release Date : 2020-10-16
• Total pages : 197
• ISBN : 9783030581671
• File Size : 35,6 Mb
• Total Download : 146
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Download Systems Modelling and Management in PDF, Epub, and Kindle

This book constitutes the refereed proceedings of the First International Conference on Systems Modelling and Management, ICSMM 2020, planned to be held in Bergen, Norway, in June 2020. Due to the COVID-19 pandemic the conference did not take place physically or virtually. The 10 full papers and 3 short papers were thoroughly reviewed and selected from 19 qualified submissions. The papers are organized according to the following topical sections: verification and validation; applications; methods, techniques and tools.

• Author : Danilo Ardagna,Li Zhang
• Publisher : Springer Science & Business Media
• Release Date : 2010-11-15
• Total pages : 185
• ISBN : 9783034604338
• File Size : 32,7 Mb
• Total Download : 840
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Download Run-time Models for Self-managing Systems and Applications in PDF, Epub, and Kindle

The complexity of Information Technology (IT) systems has been steadily incre- ing in the past decades. In October 2001, IBM released the “Autonomic Computing Manifesto” observing that current applications have reached the size of millions of lines of code, while physical infrastructures include thousands of heterogeneous servers requiring skilled IT professionals to install, con?gure, tune, and maintain. System complexity has been recognized as the main obstacle to the further advan- ment of IT technology. The basic idea of Autonomic Computing is to develop IT systems that are able to manage themselves, as the human autonomic nervous system governs basic body functions such as heart rate or body temperature, thus freeing the conscious brain— IT administrators—from the burden of dealing with low-level vital functions. Autonomic Computing systems can be implemented by introducing autonomic controllers which continuously monitor, analyze, plan, and execute (the famous MAPE cycle) recon?guration actions on the system components. Monitoring acti- ties are deployed to measure the workload and performance metrics of each running component so as to identify system faults. The goal of the analysis activities is to determine the status of components from the monitoring data, and to forecast - ture conditions based on historical observations. Finally, plan and execute activities aim at deciding and actuating the next system con?guration, for example, deciding whether to accept or reject new requests, determining the best application to servers assignment, in order to the achieve the self-optimization goals.

• Author : Stefanos Vrochidis,Benoit Huet,Edward Y. Chang,Ioannis Kompatsiaris
• Publisher : John Wiley & Sons
• Release Date : 2019-05-28
• Total pages : 372
• ISBN : 9781119376972
• File Size : 15,7 Mb
• Total Download : 290
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Download Big Data Analytics for Large-Scale Multimedia Search in PDF, Epub, and Kindle

A timely overview of cutting edge technologies for multimedia retrieval with a special emphasis on scalability The amount of multimedia data available every day is enormous and is growing at an exponential rate, creating a great need for new and more efficient approaches for large scale multimedia search. This book addresses that need, covering the area of multimedia retrieval and placing a special emphasis on scalability. It reports the recent works in large scale multimedia search, including research methods and applications, and is structured so that readers with basic knowledge can grasp the core message while still allowing experts and specialists to drill further down into the analytical sections. Big Data Analytics for Large-Scale Multimedia Search covers: representation learning, concept and event-based video search in large collections; big data multimedia mining, large scale video understanding, big multimedia data fusion, large-scale social multimedia analysis, privacy and audiovisual content, data storage and management for big multimedia, large scale multimedia search, multimedia tagging using deep learning, interactive interfaces for big multimedia and medical decision support applications using large multimodal data. Addresses the area of multimedia retrieval and pays close attention to the issue of scalability Presents problem driven techniques with solutions that are demonstrated through realistic case studies and user scenarios Includes tables, illustrations, and figures Offers a Wiley-hosted BCS that features links to open source algorithms, data sets and tools Big Data Analytics for Large-Scale Multimedia Search is an excellent book for academics, industrial researchers, and developers interested in big multimedia data search retrieval. It will also appeal to consultants in computer science problems and professionals in the multimedia industry.

• Author : Goundar, Sam,Rayani, Praveen Kumar
• Publisher : IGI Global
• Release Date : 2021-01-15
• Total pages : 377
• ISBN : 9781799866756
• File Size : 33,7 Mb
• Total Download : 892
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Download Applications of Big Data in Large- and Small-Scale Systems in PDF, Epub, and Kindle

With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

• Author : Matthias Boehm,Arun Kumar,Jun Yang
• Publisher : Springer Nature
• Release Date : 2022-05-31
• Total pages : 157
• ISBN : 9783031018695
• File Size : 46,5 Mb
• Total Download : 327
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Download Data Management in Machine Learning Systems in PDF, Epub, and Kindle

Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scalable manner. Data management is at the heart of many ML systems due to data-driven application characteristics, data-centric workload characteristics, and system architectures inspired by classical data management techniques. In this book, we follow this data-centric view of ML systems and aim to provide a comprehensive overview of data management in ML systems for the end-to-end data science or ML lifecycle. We review multiple interconnected lines of work: (1) ML support in database (DB) systems, (2) DB-inspired ML systems, and (3) ML lifecycle systems. Covered topics include: in-database analytics via query generation and user-defined functions, factorized and statistical-relational learning; optimizing compilers for ML workloads; execution strategies and hardware accelerators; data access methods such as compression, partitioning and indexing; resource elasticity and cloud markets; as well as systems for data preparation for ML, model selection, model management, model debugging, and model serving. Given the rapidly evolving field, we strive for a balance between an up-to-date survey of ML systems, an overview of the underlying concepts and techniques, as well as pointers to open research questions. Hence, this book might serve as a starting point for both systems researchers and developers.

• Author : Kannan, Rajkumar
• Publisher : IGI Global
• Release Date : 2016-01-07
• Total pages : 307
• ISBN : 9781466697683
• File Size : 17,6 Mb
• Total Download : 479
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Download Managing and Processing Big Data in Cloud Computing in PDF, Epub, and Kindle

Big data has presented a number of opportunities across industries. With these opportunities come a number of challenges associated with handling, analyzing, and storing large data sets. One solution to this challenge is cloud computing, which supports a massive storage and computation facility in order to accommodate big data processing. Managing and Processing Big Data in Cloud Computing explores the challenges of supporting big data processing and cloud-based platforms as a proposed solution. Emphasizing a number of crucial topics such as data analytics, wireless networks, mobile clouds, and machine learning, this publication meets the research needs of data analysts, IT professionals, researchers, graduate students, and educators in the areas of data science, computer programming, and IT development.

• Author : David G. Collings,Kamel Mellahi,Wayne F. Cascio
• Publisher : Oxford University Press
• Release Date : 2017
• Total pages : 609
• ISBN : 9780198758273
• File Size : 38,8 Mb
• Total Download : 169
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Download The Oxford Handbook of Talent Management in PDF, Epub, and Kindle

The Oxford Handbook of Talent Management offers academic researchers, advanced postgraduate students, and reflective practitioners a state-of-the-art overview of the key themes, topics, and debates in talent management. The Handbook is designed with a multi-disciplinary perspective in mind and draws upon perspectives from, inter alia, human resource management, psychology, and strategy to chart the topography of the area of talent management and to establish the base of knowledge in the field. Furthermore, each chapter concludes by identifying key gaps in our understanding of the area of focus. The Handbook is ambitious in its scope, with 28 chapters structured around five sections. These include the context of talent management, talent and performance, talent teams and networks, managing talent flows, and contemporary issues in talent management. Each chapter is written by a leading international scholar in the area and thus the volume represents the authoritative reference for anyone working in the area of talent management.

• Author : Roberto Moreno-Díaz,Franz Pichler,Alexis Quesada-Arencibia
• Publisher : Springer Nature
• Release Date : 2020-04-15
• Total pages : 518
• ISBN : 9783030450939
• File Size : 32,9 Mb
• Total Download : 745
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Download Computer Aided Systems Theory – EUROCAST 2019 in PDF, Epub, and Kindle

The two-volume set LNCS 12013 and 12014 constitutes the thoroughly refereed proceedings of the 17th International Conference on Computer Aided Systems Theory, EUROCAST 2019, held in Las Palmas de Gran Canaria, Spain, in February 2019. The 123 full papers presented were carefully reviewed and selected from 172 submissions. The papers are organized in the following topical sections: Part I: systems theory and applications; pioneers and landmarks in the development of information and communication technologies; stochastic models and applications to natural, social and technical systems; theory and applications of metaheuristic algorithms; model-based system design, verification and simulation. Part II: applications of signal processing technology; artificial intelligence and data mining for intelligent transportation systems and smart mobility; computer vision, machine learning for image analysis and applications; computer and systems based methods and electronic technologies in medicine; advances in biomedical signal and image processing; systems concepts and methods in touristic flows; systems in industrial robotics, automation and IoT.

• Author : Scott Tonidandel,Eden B. King,Jose M. Cortina
• Publisher : Routledge
• Release Date : 2015-11-06
• Total pages : 382
• ISBN : 9781317702702
• File Size : 39,7 Mb
• Total Download : 878
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Download Big Data at Work in PDF, Epub, and Kindle

The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.

• Author : Management Association, Information Resources
• Publisher : IGI Global
• Release Date : 2021-05-28
• Total pages : 1538
• ISBN : 9781799890249
• File Size : 48,7 Mb
• Total Download : 415
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Download Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering in PDF, Epub, and Kindle

Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries.

• Author : Sherif Sakr
• Publisher : Springer Nature
• Release Date : 2020-07-09
• Total pages : 145
• ISBN : 9783030441876
• File Size : 42,8 Mb
• Total Download : 588
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Download Big Data 2.0 Processing Systems in PDF, Epub, and Kindle

This book provides readers the “big picture” and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems. After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Next, Chapter 6 focuses on covering the emerging frameworks and systems in the domain of scalable machine learning and deep learning processing. Lastly, Chapter 7 shares conclusions and an outlook on future research challenges. This new and considerably enlarged second edition not only contains the completely new chapter 6, but also offers a refreshed content for the state-of-the-art in all domains of big data processing over the last years. Overall, the book offers a valuable reference guide for professional, students, and researchers in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.

• Author : Yuri A. Vershinin,Fedor Pashchenko,Cristina Olaverri-Monreal
• Publisher : Springer Nature
• Release Date : 2022-08-18
• Total pages : 180
• ISBN : 9783031055164
• File Size : 18,6 Mb
• Total Download : 517
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Download Technologies for Smart Cities in PDF, Epub, and Kindle

This book gives readers an overview about technologies that are useful for developments related to Smart Cities. Some technologies are already available, such for example, as smart meters for electricity and gas in buildings. But there are possibilities to incorporate existing devices into wider networks with other smart devices that currently operate independently. This in turn will considerably improve the reduction of the energy consumption in buildings, reduction of emission pollutions in cities and improvement of the well-being of people. The other objective of this book is to introduce readers to new technologies which are not yet implemented in areas related to the efficient functioning of cities. For example, areas related to Intelligent Transport Systems are mostly developed for the optimization of the traffic flow, reduction of accidents on roads, improvement of the safety of drivers and related to road transportation problems. The rapid advances in Blockchain technologies are also covered.

• Author : Shiyan Hu,Bei Yu
• Publisher : Springer Nature
• Release Date : 2020-06-25
• Total pages : 270
• ISBN : 9783030434946
• File Size : 15,9 Mb
• Total Download : 754
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Download Big Data Analytics for Cyber-Physical Systems in PDF, Epub, and Kindle

This book highlights research and survey articles dedicated to big data techniques for cyber-physical system (CPS), which addresses the close interactions and feedback controls between cyber components and physical components. The book first discusses some fundamental big data problems and solutions in large scale distributed CPSs. The book then addresses the design and control challenges in multiple CPS domains such as vehicular system, smart city, smart building, and digital microfluidic biochips. This book also presents the recent advances and trends in the maritime simulation system and the flood defence system.

• Author : G. Fox,V. Getov,L. Grandinetti
• Publisher : IOS Press
• Release Date : 2017-11-14
• Total pages : 272
• ISBN : 9781614998167
• File Size : 45,6 Mb
• Total Download : 532
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Download New Frontiers in High Performance Computing and Big Data in PDF, Epub, and Kindle

For the last four decades, parallel computing platforms have increasingly formed the basis for the development of high performance systems primarily aimed at the solution of intensive computing problems, and the application of parallel computing systems has also become a major factor in furthering scientific research. But such systems also offer the possibility of solving the problems encountered in the processing of large-scale scientific data sets, as well as in the analysis of Big Data in the fields of medicine, social media, marketing, economics etc. This book presents papers from the International Research Workshop on Advanced High Performance Computing Systems, held in Cetraro, Italy, in July 2016. The workshop covered a wide range of topics and new developments related to the solution of intensive and large-scale computing problems, and the contributions included in this volume cover aspects of the evolution of parallel platforms and highlight some of the problems encountered with the development of ever more powerful computing systems. The importance of future large-scale data science applications is also discussed. The book will be of particular interest to all those involved in the development or application of parallel computing systems.