Real Time Data Analytics For Large Scale Sensor Data

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• Author : Himansu Das,Nilanjan Dey,Valentina Emilia Balas
• Publisher : Academic Press
• Release Date : 2019-08-31
• Total pages : 298
• ISBN : 9780128182420
• File Size : 18,5 Mb
• Total Download : 687
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Download Real-Time Data Analytics for Large Scale Sensor Data in PDF, Epub, and Kindle

Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, and more. Examines IoT applications, the design of real-time intelligent systems, and how to manage the rapid growth of the large volume of sensor data Discusses intelligent management systems for applications such as healthcare, robotics and environment modeling Provides a focused approach towards the design and implementation of real-time intelligent systems for the management of sensor data in large-scale environments

• Author : Jonas Traub
• Publisher : BoD – Books on Demand
• Release Date : 2021-04-09
• Total pages : 208
• ISBN : 9783752671254
• File Size : 11,5 Mb
• Total Download : 876
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Download Demand-based Data Stream Gathering, Processing, and Transmission in PDF, Epub, and Kindle

This book presents an end-to-end architecture for demand-based data stream gathering, processing, and transmission. The Internet of Things (IoT) consists of billions of devices which form a cloud of network connected sensor nodes. These sensor nodes supply a vast number of data streams with massive amounts of sensor data. Real-time sensor data enables diverse applications including traffic-aware navigation, machine monitoring, and home automation. Current stream processing pipelines are demand-oblivious, which means that they gather, transmit, and process as much data as possible. In contrast, a demand-based processing pipeline uses requirement specifications of data consumers, such as failure tolerances and latency limitations, to save resources. Our solution unifies the way applications express their data demands, i.e., their requirements with respect to their input streams. This unification allows for multiplexing the data demands of all concurrently running applications. On sensor nodes, we schedule sensor reads based on the data demands of all applications, which saves up to 87% in sensor reads and data transfers in our experiments with real-world sensor data. Our demand-based control layer optimizes the data acquisition from thousands of sensors. We introduce time coherence as a fundamental data characteristic. Time coherence is the delay between the first and the last sensor read that contribute values to a tuple. A large scale parameter exploration shows that our solution scales to large numbers of sensors and operates reliably under varying latency and coherence constraints. On stream analysis systems, we tackle the problem of efficient window aggregation. We contribute a general aggregation technique, which adapts to four key workload characteristics: Stream (dis)order, aggregation types, window types, and window measures. Our experiments show that our solution outperforms alternative solutions by an order of magnitude in throughput, which prevents expensive system scale-out. We further derive data demands from visualization needs of applications and make these data demands available to streaming systems such as Apache Flink. This enables streaming systems to pre-process data with respect to changing visualization needs. Experiments show that our solution reliably prevents overloads when data rates increase.

• Author : Samee U. Khan,Albert Y. Zomaya,Assad Abbas
• Publisher : Springer
• Release Date : 2017-08-07
• Total pages : 635
• ISBN : 9783319582801
• File Size : 47,7 Mb
• Total Download : 854
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Download Handbook of Large-Scale Distributed Computing in Smart Healthcare in PDF, Epub, and Kindle

This volume offers readers various perspectives and visions for cutting-edge research in ubiquitous healthcare. The topics emphasize large-scale architectures and high performance solutions for smart healthcare, healthcare monitoring using large-scale computing techniques, Internet of Things (IoT) and big data analytics for healthcare, Fog Computing, mobile health, large-scale medical data mining, advanced machine learning methods for mining multidimensional sensor data, smart homes, and resource allocation methods for the BANs. The book contains high quality chapters contributed by leading international researchers working in domains, such as e-Health, pervasive and context-aware computing, cloud, grid, cluster, and big-data computing. We are optimistic that the topics included in this book will provide a multidisciplinary research platform to the researchers, practitioners, and students from biomedical engineering, health informatics, computer science, and computer engineering.

• Author : Vijayan Sugumaran,Arun Kumar Sangaiah,Arunkumar Thangavelu
• Publisher : CRC Press
• Release Date : 2017-06-26
• Total pages : 362
• ISBN : 9781351720250
• File Size : 34,6 Mb
• Total Download : 565
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Download Computational Intelligence Applications in Business Intelligence and Big Data Analytics in PDF, Epub, and Kindle

There are a number of books on computational intelligence (CI), but they tend to cover a broad range of CI paradigms and algorithms rather than provide an in-depth exploration in learning and adaptive mechanisms. This book sets its focus on CI based architectures, modeling, case studies and applications in big data analytics, and business intelligence. The intended audiences of this book are scientists, professionals, researchers, and academicians who deal with the new challenges and advances in the specific areas mentioned above. Designers and developers of applications in these areas can learn from other experts and colleagues through this book.

• Author : Sami Yangui,Ismael Bouassida Rodriguez,Khalil Drira,Zahir Tari
• Publisher : Springer Nature
• Release Date : 2019-10-25
• Total pages : 583
• ISBN : 9783030337025
• File Size : 26,8 Mb
• Total Download : 160
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Download Service-Oriented Computing in PDF, Epub, and Kindle

This book constitutes the proceedings of the 17th International Conference on Service-Oriented Computing, ICSOC 2019, held in Toulouse, France, in October 2019. The 28 full and 12 short papers presented together with 7 poster and 2 invited papers in this volume were carefully reviewed and selected from 181 submissions. The papers have been organized in the following topical sections: Service Engineering; Run-time Service Operations and Management; Services and Data; Services in the Cloud; Services on the Internet of Things; Services in Organizations, Business and Society; and Services at the Edge.

• Author : K. Shankar,Eswaran Perumal,Deepak Gupta
• Publisher : CRC Press
• Release Date : 2021-05-10
• Total pages : 216
• ISBN : 9781000374292
• File Size : 11,7 Mb
• Total Download : 828
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Download Artificial Intelligence for the Internet of Health Things in PDF, Epub, and Kindle

This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions. This book features a wide range of topics such as AI techniques, IoT, cloud, wearables, and secured data transmission. Written for a broad audience, this book will be useful for clinicians, health professionals, engineers, technology developers, IT consultants, researchers, and students interested in the AI-based healthcare applications. Provides a deeper understanding of key AI algorithms and their use and implementation within the wider healthcare sector Explores different disease diagnosis models using machine learning, deep learning, healthcare data analysis, including machine learning, and data mining and soft computing algorithms Discusses detailed IoT, wearables, and cloud-based disease diagnosis model for intelligent systems and healthcare Reviews different applications and challenges across the design, implementation, and management of intelligent systems and healthcare data networks Introduces a new applications and case studies across all areas of AI in healthcare data K. Shankar (Member, IEEE) is a Postdoctoral Fellow of the Department of Computer Applications, Alagappa University, Karaikudi, India. Eswaran Perumal is an Assistant Professor of the Department of Computer Applications, Alagappa University, Karaikudi, India. Dr. Deepak Gupta is an Assistant Professor of the Department Computer Science & Engineering, Maharaja Agrasen Institute of Technology (GGSIPU), Delhi, India.

• Author : Robert C. Qiu,Paul Antonik
• Publisher : John Wiley & Sons
• Release Date : 2017-04-17
• Total pages : 626
• ISBN : 9781118494059
• File Size : 52,7 Mb
• Total Download : 658
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Download Smart Grid using Big Data Analytics in PDF, Epub, and Kindle

This book is aimed at students in communications and signal processing who want to extend their skills in the energy area. It describes power systems and why these backgrounds are so useful to smart grid, wireless communications being very different to traditional wireline communications.

• Author : Carlos Guedes Soares,T.A. Santos
• Publisher : CRC Press
• Release Date : 2016-12-01
• Total pages : 1208
• ISBN : 9781498795937
• File Size : 47,5 Mb
• Total Download : 493
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Download Maritime Technology and Engineering III in PDF, Epub, and Kindle

Maritime Technology and Engineering 3 is a collection of papers presented at the 3rd International Conference on Maritime Technology and Engineering (MARTECH 2016, Lisbon, Portugal, 4-6 July 2016). The MARTECH Conferences series evolved from biannual national conferences in Portugal, thus reflecting the internationalization of the maritime sector. The keynote lectures and the papers, making up nearly 150 contributions, came from an international group of authors focused on different subjects in a variety of fields: Maritime Transportation, Energy Efficiency, Ships in Ports, Ship Hydrodynamics, Ship Structures, Ship Design, Ship Machinery, Shipyard Technology, afety & Reliability, Fisheries, Oil & Gas, Marine Environment, Renewable Energy and Coastal Structures. This book will appeal to academics, engineers and professionals interested or involved in these fields.

• Author : Jitendra Kumar Rout,Minakhi Rout,Himansu Das
• Publisher : Springer Nature
• Release Date : 2020-04-02
• Total pages : 209
• ISBN : 9789811536892
• File Size : 31,9 Mb
• Total Download : 703
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Download Machine Learning for Intelligent Decision Science in PDF, Epub, and Kindle

The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.

• Author : Kuan-Ching Li,Hai Jiang,Albert Y. Zomaya
• Publisher : CRC Press
• Release Date : 2017-05-19
• Total pages : 469
• ISBN : 9781498768085
• File Size : 50,6 Mb
• Total Download : 710
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Download Big Data Management and Processing in PDF, Epub, and Kindle

From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions. The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.

• Author : Himansu Das,Jitendra Kumar Rout,Suresh Chandra Moharana,Nilanjan Dey
• Publisher : CRC Press
• Release Date : 2020-11-18
• Total pages : 252
• ISBN : 9781000208542
• File Size : 49,8 Mb
• Total Download : 635
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Download Applied Intelligent Decision Making in Machine Learning in PDF, Epub, and Kindle

The objective of this edited book is to share the outcomes from various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances in machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation systems, forecasting air quality, healthcare, exchange rate prediction, and image dehazing. It also provides a premier interdisciplinary platform for scientists, researchers, practitioners, and educators to share their thoughts in the context of recent innovations, trends, developments, practical challenges, and advancements in the field of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in the decision-making process in several aspects. To address these objectives, this edited book includes a dozen chapters contributed by authors from around the globe. The authors attempt to solve these complex problems using several intelligent machine-learning techniques. This allows researchers to understand the mechanism needed to harness the decision-making process using machine-learning techniques for their own respective endeavors.

• Author : Sushma Dave,Jayashankar Das,Sougata Ghosh
• Publisher : Elsevier
• Release Date : 2022-03-11
• Total pages : 596
• ISBN : 9780323900669
• File Size : 25,9 Mb
• Total Download : 307
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Download Advanced Nanomaterials for Point of Care Diagnosis and Therapy in PDF, Epub, and Kindle

Advanced Nanomaterials for Point of Care Diagnosis and Therapy provides an overview of technological and emerging novel trends in how point-of-care diagnostic devices are designed, miniaturized built, and delivered at different healthcare set ups. It describes the significant technological advances in fundamental diagnostic components and recent advances in fully integrated devices designed for specific clinical use. The book covers state-of-the-art fabrication of advances materials with broad spectrum therapeutic applications. It includes drug delivery, biosensing, bioimaging and targeting, and outlines the development of inexpensive, effective and portable in vitro diagnostics tools for any purpose that can be used onsite. Sections also discuss drug delivery, biosensing, bioimaging and targeting and various metal, metal oxide and non-metal-based nanomaterials that are developed, surface modified, and are being explored for diagnosis, targeting, drug delivery, drug release and imaging. The book concludes with current needs and future challenges in the field. Outlines the needs and challenges of point-of-care diagnostics Describes the fundamentals of application of nanomaterials as interesting building blocks for biosensing Overviews the different detection methods offered by using nanomaterials Explains the advantages and drawbacks of nanomaterial-based sensing strategies Describes the opportunities offered by technology as a cost-efficient biosensing platform

• Author : Amir Alavi,William G. Buttlar
• Publisher : CRC Press
• Release Date : 2018-10-26
• Total pages : 240
• ISBN : 9780429786631
• File Size : 28,6 Mb
• Total Download : 163
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Download Data Analytics for Smart Cities in PDF, Epub, and Kindle

The development of smart cities is one of the most important challenges over the next few decades. Governments and companies are leveraging billions of dollars in public and private funds for smart cities. Next generation smart cities are heavily dependent on distributed smart sensing systems and devices to monitor the urban infrastructure. The smart sensor networks serve as autonomous intelligent nodes to measure a variety of physical or environmental parameters. They should react in time, establish automated control, and collect information for intelligent decision-making. In this context, one of the major tasks is to develop advanced frameworks for the interpretation of the huge amount of information provided by the emerging testing and monitoring systems. Data Analytics for Smart Cities brings together some of the most exciting new developments in the area of integrating advanced data analytics systems into smart cities along with complementary technological paradigms such as cloud computing and Internet of Things (IoT). The book serves as a reference for researchers and engineers in domains of advanced computation, optimization, and data mining for smart civil infrastructure condition assessment, dynamic visualization, intelligent transportation systems (ITS), cyber-physical systems, and smart construction technologies. The chapters are presented in a hands-on manner to facilitate researchers in tackling applications. Arguably, data analytics technologies play a key role in tackling the challenge of creating smart cities. Data analytics applications involve collecting, integrating, and preparing time- and space-dependent data produced by sensors, complex engineered systems, and physical assets, followed by developing and testing analytical models to verify the accuracy of results. This book covers this multidisciplinary field and examines multiple paradigms such as machine learning, pattern recognition, statistics, intelligent databases, knowledge acquisition, data visualization, high performance computing, and expert systems. The book explores new territory by discussing the cutting-edge concept of Big Data analytics for interpreting massive amounts of data in smart city applications.

• Author : Pooja Singh,Omprakash Kaiwartya,Nidhi Sindhwani,Vishal Jain,Rohit Anand
• Publisher : CRC Press
• Release Date : 2022-12-20
• Total pages : 398
• ISBN : 9781000798791
• File Size : 43,6 Mb
• Total Download : 420
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Download Networking Technologies in Smart Healthcare in PDF, Epub, and Kindle

This text provides novel smart network systems, wireless telecommunications infrastructures, and computing capabilities to help healthcare systems using computing techniques like IoT, cloud computing, machine and deep learning Big Data along with smart wireless networks. It discusses important topics, including robotics manipulation and analysis in smart healthcare industries, smart telemedicine framework using machine learning and deep learning, role of UAV and drones in smart hospitals, virtual reality based on 5G/6G and augmented reality in healthcare systems, data privacy and security, nanomedicine, and cloud-based artificial intelligence in healthcare systems. The book: • Discusses intelligent computing through IoT and Big Data in secure and smart healthcare systems. • Covers algorithms, including deterministic algorithms, randomized algorithms, iterative algorithms, and recursive algorithms. • Discusses remote sensing devices in hospitals and local health facilities for patient evaluation and care. • Covers wearable technology applications such as weight control and physical activity tracking for disease prevention and smart healthcare. This book will be useful for senior undergraduate, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and information technology. Discussing concepts of smart networks, advanced wireless communication, and technologies in setting up smart healthcare services, this text will be useful for senior undergraduate, graduate students, and academic researchers in areas such as electrical engineering, electronics and communication engineering, computer science, and information technology. It covers internet of things (IoT) implementation and challenges in healthcare industries, wireless network, and communication-based optimization algorithms for smart healthcare devices.

• Author : Ying Tan,Yuhui Shi
• Publisher : Springer
• Release Date : 2016-07-04
• Total pages : 569
• ISBN : 9783319409733
• File Size : 22,6 Mb
• Total Download : 403
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Download Data Mining and Big Data in PDF, Epub, and Kindle

The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016. The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions. The theme of DMBD 2016 is "Serving Life with Data Science". Data mining refers to the activity of going through big data sets to look for relevant or pertinent information.The papers are organized in 10 cohesive sections covering all major topics of the research and development of data mining and big data and one Workshop on Computational Aspects of Pattern Recognition and Computer Vision.

• Author : Silvia Nittel,Alexandros Labrinidis,Anthony Stefanidis
• Publisher : Springer
• Release Date : 2008-08-15
• Total pages : 271
• ISBN : 9783540799962
• File Size : 32,9 Mb
• Total Download : 506
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Download GeoSensor Networks in PDF, Epub, and Kindle

This volume serves as the post-conference proceedings for the Second GeoSensor Networks Conference that was held in Boston, Massachusetts in October 2006. The conference addressed issues related to the collection, management, processing, ana- sis, and delivery of real-time geospatial data using distributed geosensor networks. This represents an evolution of the traditional static and centralized geocomputational paradigm, to support the collection of both temporally and spatially high-resolution, up-to-date data over a broad geographic area, and to use sensor networks as actuators in geographic space. Sensors in these environments can be static or mobile, and can be used to passively collect information about the environment or, eventually, to actively influence it. The research challenges behind this novel paradigm extend the frontiers of tra- tional GIS research further into computer science, addressing issues like data stream processing, mobile computing, location-based services, temporal-spatial queries over geosensor networks, adaptable middleware, sensor data integration and mining, au- mated updating of geospatial databases, VR modeling, and computer vision. In order to address these topics, the GSN 2006 conference brought together leading experts in these fields, and provided a three-day forum to present papers and exchange ideas.

• Author : Rajaa Saidi,Brahim El Bhiri,Yassine Maleh,Ayman Mosallam,Mohammed Essaaidi
• Publisher : Springer Nature
• Release Date : 2022-01-29
• Total pages : 555
• ISBN : 9783030941888
• File Size : 28,8 Mb
• Total Download : 434
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Download Advanced Technologies for Humanity in PDF, Epub, and Kindle

This book gathers the proceedings of the International Conference on Advanced Technologies for Humanity (ICATH’2021), held on November 26-27, 2021, in INSEA, Rabat, Morocco. ICATH’2021 was jointly co-organized by the National Institute of Statistics and Applied Economics (INSEA) in collaboration with the Moroccan School of Engineering Sciences (EMSI), the Hassan II Institute of Agronomy and Veterinary Medicine (IAV-Hassan II), the National Institute of Posts and Telecommunications (INPT), the National School of Mineral Industry (ENSMR), the Faculty of Sciences of Rabat (UM5-FSR), the National School of Applied Sciences of Kenitra (ENSAK) and the Future University in Egypt (FUE). ICATH’2021 was devoted to practical models and industrial applications related to advanced technologies for Humanity. It was considered as a meeting point for researchers and practitioners to enable the implementation of advanced information technologies into various industries. This book is helpful for PhD students as well as researchers. The 48 full papers were carefully reviewed and selected from 105 submissions. The papers presented in the volume are organized in topical sections on synergies between (i) smart and sustainable cities, (ii) communication systems, signal and image processing for humanity, (iii) cybersecurity, database and language processing for human applications, (iV) renewable and sustainable energies, (V) civil engineering and structures for sustainable constructions, (Vi) materials and smart buildings and (Vii) Industry 4.0 for smart factories. All contributions were subject to a double-blind review. The review process was highly competitive. We had to review 105 submissions from 12 countries. A team of over 100 program committee members and reviewers did this terrific job. Our special thanks go to all of them.

• Author : Charu C. Aggarwal
• Publisher : Springer Science & Business Media
• Release Date : 2013-01-15
• Total pages : 534
• ISBN : 9781461463092
• File Size : 41,9 Mb
• Total Download : 736
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Download Managing and Mining Sensor Data in PDF, Epub, and Kindle

Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.

• Author : Patrick Bangert
• Publisher : Gulf Professional Publishing
• Release Date : 2021-03-04
• Total pages : 306
• ISBN : 9780128209141
• File Size : 30,5 Mb
• Total Download : 257
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Download Machine Learning and Data Science in the Oil and Gas Industry in PDF, Epub, and Kindle

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful Gain practical understanding of machine learning used in oil and gas operations through contributed case studies Learn change management skills that will help gain confidence in pursuing the technology Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

• Author : Bhavani Thuraisingham,Pallabi Parveen,Mohammad Mehedy Masud,Latifur Khan
• Publisher : CRC Press
• Release Date : 2017-11-22
• Total pages : 544
• ISBN : 9781498705486
• File Size : 32,6 Mb
• Total Download : 379
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Download Big Data Analytics with Applications in Insider Threat Detection in PDF, Epub, and Kindle

Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

• Author : Monika Mangla,Ashok Kumar,Vaishali Mehta,Megha Bhushan,Sachi Nandan Mohanty
• Publisher : CRC Press
• Release Date : 2022-08-01
• Total pages : 551
• ISBN : 9781000565508
• File Size : 25,8 Mb
• Total Download : 439
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Download Real-Life Applications of the Internet of Things in PDF, Epub, and Kindle

This new volume provides an overview of the Internet of Things along with its architectures, its vital technologies, and their uses in our daily life. The book explores the integration of IoT with other emerging technologies, such as blockchain and cloud. Topics in the volume cover the many powerful features and applications of IoT, such as for weather forecasting, in agriculture, in medical science, in surveillance systems, and much more. The first section of the book covers many of the issues and challenges that arise from the Internet of Things (IoT), exploring security challenges, such as attack detection and prevention systems, as well as energy efficiency and resource management in IoT. The volume also introduces the use of IoT and smart technology in agricultural management, in healthcare diagnosis and monitoring, and in the financial industry. Chapters also focus on surveillance network technology, the technology shift from television to video streaming apps, using IoT–fog computing for smart healthcare, detection of anomalies in climate conditions, and even detection of illegal wood logging activity.