This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments.
Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people's imaginations as to what a fully connected world can offer.
Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions.
The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.
Автор: Jac Fitz?€“enz,John Mattox II Название: Predictive Analytics for Human Resources ISBN: 1118893670 ISBN-13(EAN): 9781118893678 Издательство: Wiley Рейтинг: Цена: 41190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Create and run a human resource analytics project with confidence For any human resource professional that wants to harness the power of analytics, this essential resource answers the questions: "Where do I start?" and "What tools are available?" Predictive Analytics for Human Resources is designed to answer these and other vital questions.
Автор: Wei Lee Woon; Zeyar Aung; Oliver Kramer; Stuart Ma Название: Data Analytics for Renewable Energy Integration ISBN: 3319509462 ISBN-13(EAN): 9783319509464 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes revised selected papers from the 4th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2016, held in Riva del Garda, Italy, in September 2016.
Автор: Fusheng Wang; Lixia Yao; Gang Luo Название: Data Management and Analytics for Medicine and Healthcare ISBN: 3319577409 ISBN-13(EAN): 9783319577401 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2016, in New Delhi, India, in September 2016, held in conjunction with the 42nd International Conference on Very Large Data Bases, VLDB 2016.
Автор: Anupam Chattopadhyay; Chip Hong Chang; Hao Yu Название: Emerging Technology and Architecture for Big-data Analytics ISBN: 3319548395 ISBN-13(EAN): 9783319548395 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Part I State-of-the-Art Architectures and Automation for Data-analytics.- Chapter 1. Scaling the Java Virtual Machine on a Many-core System.- Chapter 2.Scaling the Java Virtual Machine on a Many-core System.- Chapter 3.Least-squares based Machine Learning Accelerator for Big-data Analytics in Smart Buildings.- Chapter 4.Compute-in-memory Architecture for Data-Intensive Kernels.- Chapter 5. New Solutions for Cross-Layer System-Level and High-Level Synthesis.- Part II New Solutions for Cross-Layer System-Level and High-Level Synthesis.- Chapter 6.Side Channel Attacks and Efficient Countermeasures on Residue Number System Multipliers.- Chapter 7. Ultra-Low-Power Biomedical Circuit Design and Optimization: Catching The Don't Cares.- Chapter 8.Acceleration of MapReduce Framework on a Multicore Processor.- Chapter 9. Adaptive dynamic range compression for improving envelope-based speech perception: Implications for cochlear implants.- Part III Emerging Technology, Circuits and Systems for Data-analytics.- Chapter 10. Emerging Technology, Circuits and Systems for Data-analytics.- Chapter 11. Energy Efficient Spiking Neural Network Design with RRAM Devices.- Chapter 12. Efficient Neuromorphic Systems and Emerging Technologies - Prospects and Perspectives.- Chapter 13. In-memory Data Compression Using ReRAMs.- Chapter 14. In-memory Data Compression Using ReRAMs.- Chapter 15.Data Analytics in Quantum Paradigm - An Introduction.
Автор: Leonid Kalinichenko; Sergei O. Kuznetsov; Yannis M Название: Data Analytics and Management in Data Intensive Domains ISBN: 3319571346 ISBN-13(EAN): 9783319571348 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This book constitutes the refereed proceedings of the 28th International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2016, held in Ershovo, Moscow, Russia, in October 2016.
The 16 revised full papers presented together with one invited talk and two keynote papers were carefully reviewed and selected from 57 submissions. The papers are organized in topical sections on semantic modeling in data intensive domains; knowledge and learning management; text mining; data infrastructures in astrophysics; data analysis; research infrastructures; position paper.
Автор: Ladjel Bellatreche; Sharma Chakravarthy Название: Big Data Analytics and Knowledge Discovery ISBN: 3319642820 ISBN-13(EAN): 9783319642826 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017. The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions.
Автор: Gabriele Meiselwitz Название: Social Computing and Social Media. Applications and Analytics ISBN: 3319585614 ISBN-13(EAN): 9783319585611 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the proceedings of the 9th International Conference on Social Computing and Social Media, SCSM 2017, held as part of the 19th International Conference on Human-Computer Interaction, HCII 2017, held in Vancouver, Canada, in July 2017.
Автор: Alejandra Gonz?lez-Beltr?n; Francesco Osborne; Sil Название: Semantics, Analytics, Visualization. Enhancing Scholarly Data ISBN: 3319536362 ISBN-13(EAN): 9783319536361 Издательство: Springer Рейтинг: Цена: 39130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the Second International Workshop on Semantics, Analytics, Visualization,- Enhancing Scholarly Data,- SAVE-SD 2016, held in Montreal, QC, Canada, in April 2016.
Автор: Iv?n Palomares Carrascosa; Harsha Kumara Kalutarag Название: Data Analytics and Decision Support for Cybersecurity ISBN: 3319594389 ISBN-13(EAN): 9783319594385 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The book illustrates the inter-relationship between several data management, analytics and decision support techniques and methods commonly adopted in Cybersecurity-oriented frameworks. The recent advent of Big Data paradigms and the use of data science methods, has resulted in a higher demand for effective data-driven models that support decision-making at a strategic level. This motivates the need for defining novel data analytics and decision support approaches in a myriad of real-life scenarios and problems, with Cybersecurity-related domains being no exception.
This contributed volume comprises nine chapters, written by leading international researchers, covering a compilation of recent advances in Cybersecurity-related applications of data analytics and decision support approaches. In addition to theoretical studies and overviews of existing relevant literature, this book comprises a selection of application-oriented research contributions. The investigations undertaken across these chapters focus on diverse and critical Cybersecurity problems, such as Intrusion Detection, Insider Threats, Insider Threats, Collusion Detection, Run-Time Malware Detection, Intrusion Detection, E-Learning, Online Examinations, Cybersecurity noisy data removal, Secure Smart Power Systems, Security Visualization and Monitoring.
Researchers and professionals alike will find the chapters an essential read for further research on the topic.
Автор: Andrea Cal?; Peter Wood; Nigel Martin; Alexandra P Название: Data Analytics ISBN: 3319607944 ISBN-13(EAN): 9783319607948 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The papers cover a wide range of topics such as data cleansing, data integration, data wrangling, data mining and knowledge discovery, graph data and knowledge graphs, intelligent data analysis, approximate and flexible querying, data provenance and ontology-based data access.
Автор: Sourav Mazumder; Robin Singh Bhadoria; Ganesh Chan Название: Distributed Computing in Big Data Analytics ISBN: 3319598333 ISBN-13(EAN): 9783319598338 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: However, the current literature available in big data analytics needs a holistic perspective to highlight the relation between big data analytics and distributed processing for ease of understanding and practitioner use.This book fills the literature gap by addressing key aspects of distributed processing in big data analytics.
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