Network Science Models For Data Analytics Automation

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Network Science Models for Data Analytics Automation

Author : Xin W. Chen
Publisher : Springer Nature
ISBN 13 : 3030964701
Total Pages : 126 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Network Science Models for Data Analytics Automation by : Xin W. Chen

Download or read book Network Science Models for Data Analytics Automation written by Xin W. Chen and published by Springer Nature. This book was released on 2022-02-21 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains network science and its applications in data analytics for critical infrastructures, engineered systems, and knowledge acquisition. Each chapter describes step-by-step processes of how network science enables and automates data analytics through examples. The book not only dissects modeling techniques and analytical results but also explores the intrinsic development of these models and analyses. This unique approach bridges the gap between theory and practice and channels’ managerial and problem-solving skills. Engineers, researchers, and managers would benefit from the extensive theoretical background and practical examples discussed in this book. Advanced undergraduate students and graduate students in mathematics, statistics, engineering, business, public health, and social science may use this book as a one-semester textbook or a reference book. Readers who are more interested in applications may skip Chapter 1 and peruse through the rest of the book with ease.

Systems Collaboration and Integration

Author : Chin-Yin Huang
Publisher : Springer Nature
ISBN 13 : 303144373X
Total Pages : 500 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Systems Collaboration and Integration by : Chin-Yin Huang

Download or read book Systems Collaboration and Integration written by Chin-Yin Huang and published by Springer Nature. This book was released on 2023-10-17 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a groundbreaking exploration of the historical and contemporary challenges in systems collaboration and integration. This exceptional book delves into engineering design, planning, control, and management, offering invaluable insights into the evolving nature of systems and networks. In an era defined by the ongoing cyber and digital transformation, coupled with artificial intelligence and machine learning, this book offers insights into the future of systems collaboration and integration. Over the past three decades, the PRISM Center and its affiliated PRISM Global Research Network (PGRN) have spearheaded pioneering theories, technologies, and applications in the realm of systems collaboration and integration. Their research, driven by the motto “Knowledge through information; Wisdom through collaboration,” has yielded remarkable advancements. Those achievements and papers presented and updated by the PGRN scholars in the 26th ICPR are included in this book.

Data Analytics for IT Networks

Author : John Garrett
Publisher : Cisco Press
ISBN 13 : 0135183448
Total Pages : 743 pages
Book Rating : 4.1/5 (351 download)

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Book Synopsis Data Analytics for IT Networks by : John Garrett

Download or read book Data Analytics for IT Networks written by John Garrett and published by Cisco Press. This book was released on 2018-10-24 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use data analytics to drive innovation and value throughout your network infrastructure Network and IT professionals capture immense amounts of data from their networks. Buried in this data are multiple opportunities to solve and avoid problems, strengthen security, and improve network performance. To achieve these goals, IT networking experts need a solid understanding of data science, and data scientists need a firm grasp of modern networking concepts. Data Analytics for IT Networks fills these knowledge gaps, allowing both groups to drive unprecedented value from telemetry, event analytics, network infrastructure metadata, and other network data sources. Drawing on his pioneering experience applying data science to large-scale Cisco networks, John Garrett introduces the specific data science methodologies and algorithms network and IT professionals need, and helps data scientists understand contemporary network technologies, applications, and data sources. After establishing this shared understanding, Garrett shows how to uncover innovative use cases that integrate data science algorithms with network data. He concludes with several hands-on, Python-based case studies reflecting Cisco Customer Experience (CX) engineers’ supporting its largest customers. These are designed to serve as templates for developing custom solutions ranging from advanced troubleshooting to service assurance. Understand the data analytics landscape and its opportunities in Networking See how elements of an analytics solution come together in the practical use cases Explore and access network data sources, and choose the right data for your problem Innovate more successfully by understanding mental models and cognitive biases Walk through common analytics use cases from many industries, and adapt them to your environment Uncover new data science use cases for optimizing large networks Master proven algorithms, models, and methodologies for solving network problems Adapt use cases built with traditional statistical methods Use data science to improve network infrastructure analysisAnalyze control and data planes with greater sophistication Fully leverage your existing Cisco tools to collect, analyze, and visualize data

Springer Handbook of Automation

Author : Shimon Y. Nof
Publisher : Springer Nature
ISBN 13 : 3030967298
Total Pages : 1533 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Springer Handbook of Automation by : Shimon Y. Nof

Download or read book Springer Handbook of Automation written by Shimon Y. Nof and published by Springer Nature. This book was released on 2023-06-16 with total page 1533 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook incorporates new developments in automation. It also presents a widespread and well-structured conglomeration of new emerging application areas, such as medical systems and health, transportation, security and maintenance, service, construction and retail as well as production or logistics. The handbook is not only an ideal resource for automation experts but also for people new to this expanding field.

Web and Network Data Science

Author : Thomas W. Miller
Publisher : Pearson Education
ISBN 13 : 0133886441
Total Pages : 370 pages
Book Rating : 4.1/5 (338 download)

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Book Synopsis Web and Network Data Science by : Thomas W. Miller

Download or read book Web and Network Data Science written by Thomas W. Miller and published by Pearson Education. This book was released on 2015 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master modern web and network data modeling: both theory and applications. InWeb and Network Data Science, a top faculty member of Northwestern University's prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theoryin the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

Soft Computing for Data Analytics, Classification Model, and Control

Author : Deepak Gupta
Publisher : Springer Nature
ISBN 13 : 3030920267
Total Pages : 165 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Soft Computing for Data Analytics, Classification Model, and Control by : Deepak Gupta

Download or read book Soft Computing for Data Analytics, Classification Model, and Control written by Deepak Gupta and published by Springer Nature. This book was released on 2022-01-30 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a set of soft computing approaches and their application in data analytics, classification model, and control. The basics of fuzzy logic implementation for advanced hybrid fuzzy driven optimization methods has been covered in the book. The various soft computing techniques, including Fuzzy Logic, Rough Sets, Neutrosophic Sets, Type-2 Fuzzy logic, Neural Networks, Generative Adversarial Networks, and Evolutionary Computation have been discussed and they are used on variety of applications including data analytics, classification model, and control. The book is divided into two thematic parts. The first thematic section covers the various soft computing approaches for text classification and data analysis, while the second section focuses on the fuzzy driven optimization methods for the control systems. The chapters has been written and edited by active researchers, which cover hypotheses and practical considerations; provide insights into the design of hybrid algorithms for applications in data analytics, classification model, and engineering control.

Big Data of Complex Networks

Author : Matthias Dehmer
Publisher : CRC Press
ISBN 13 : 1315353598
Total Pages : 290 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Big Data of Complex Networks by : Matthias Dehmer

Download or read book Big Data of Complex Networks written by Matthias Dehmer and published by CRC Press. This book was released on 2016-08-19 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: Provides a complete discussion of both the hardware and software used to organize big data Describes a wide range of useful applications for managing big data and resultant data sets Maintains a firm focus on massive data and large networks Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology.

Data Analytics, Computational Statistics, and Operations Research for Engineers

Author : Debabrata Samanta
Publisher : CRC Press
ISBN 13 : 1000550427
Total Pages : 296 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Data Analytics, Computational Statistics, and Operations Research for Engineers by : Debabrata Samanta

Download or read book Data Analytics, Computational Statistics, and Operations Research for Engineers written by Debabrata Samanta and published by CRC Press. This book was released on 2022-04-05 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.

A First Course in Network Science

Author : Filippo Menczer
Publisher : Cambridge University Press
ISBN 13 : 1108579612
Total Pages : 275 pages
Book Rating : 4.1/5 (85 download)

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Book Synopsis A First Course in Network Science by : Filippo Menczer

Download or read book A First Course in Network Science written by Filippo Menczer and published by Cambridge University Press. This book was released on 2020-01-30 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.

AI and Analytics for Public Health

Author : Hui Yang
Publisher : Springer Nature
ISBN 13 : 303075166X
Total Pages : 474 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis AI and Analytics for Public Health by : Hui Yang

Download or read book AI and Analytics for Public Health written by Hui Yang and published by Springer Nature. This book was released on 2022-01-03 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers the state-of-the-art research and developments in service science and related research, education and practice areas. It showcases emerging technology and applications in fields including healthcare, energy, finance, information technology, transportation, sports, logistics, and public services. Regardless of size and service, a service organization is a service system. Because of the socio-technical nature of a service system, a systems approach must be adopted to design, develop, and deliver services, aimed at meeting end users’ both utilitarian and socio-psychological needs. Effective understanding of service and service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions. Chapters highlight ways to approach such technical challenges in service science and are based on submissions from the 2020 INFORMS International Conference on Service Science.

Technology Innovation for Business Intelligence and Analytics (TIBIA)

Author : Haitham M. Alzoubi
Publisher : Springer Nature
ISBN 13 : 3031552210
Total Pages : 503 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Technology Innovation for Business Intelligence and Analytics (TIBIA) by : Haitham M. Alzoubi

Download or read book Technology Innovation for Business Intelligence and Analytics (TIBIA) written by Haitham M. Alzoubi and published by Springer Nature. This book was released on with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Learning Using Neural Networks

Author : Basilio de Braganca Pereira
Publisher : CRC Press
ISBN 13 : 0429775555
Total Pages : 234 pages
Book Rating : 4.4/5 (297 download)

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Book Synopsis Statistical Learning Using Neural Networks by : Basilio de Braganca Pereira

Download or read book Statistical Learning Using Neural Networks written by Basilio de Braganca Pereira and published by CRC Press. This book was released on 2020-09-01 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples. It presents a wide range of widely used statistical methodologies, applied in several research areas with Python code examples, which are available online. It is suitable for scientists and developers as well as graduate students. Key Features: Discusses applications in several research areas Covers a wide range of widely used statistical methodologies Includes Python code examples Gives numerous neural network models This book covers fundamental concepts on Neural Networks including Multivariate Statistics Neural Networks, Regression Neural Network Models, Survival Analysis Networks, Time Series Forecasting Networks, Control Chart Networks, and Statistical Inference Results. This book is suitable for both teaching and research. It introduces neural networks and is a guide for outsiders of academia working in data mining and artificial intelligence (AI). This book brings together data analysis from statistics to computer science using neural networks.

Data Science and Big Data Analytics in Smart Environments

Author : Marta Chinnici
Publisher : CRC Press
ISBN 13 : 1000386015
Total Pages : 305 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Data Science and Big Data Analytics in Smart Environments by : Marta Chinnici

Download or read book Data Science and Big Data Analytics in Smart Environments written by Marta Chinnici and published by CRC Press. This book was released on 2021-07-28 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.

Automation in Proteomics and Genomics

Author : Gil Alterovitz
Publisher : John Wiley & Sons
ISBN 13 : 9780470741177
Total Pages : 340 pages
Book Rating : 4.7/5 (411 download)

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Book Synopsis Automation in Proteomics and Genomics by : Gil Alterovitz

Download or read book Automation in Proteomics and Genomics written by Gil Alterovitz and published by John Wiley & Sons. This book was released on 2009-03-16 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade DNA sequencing costs have decreased over a magnitude, largely because of increasing throughput by incremental advances in tools, technologies and process improvements. Further cost reductions in this and in related proteomics technologies are expected as a result of the development of new high-throughput techniques and the computational machinery needed to analyze data generated. Automation in Proteomics & Genomics: An Engineering Case-Based Approach describes the automation technology currently in the areas of analysis, design, and integration, as well as providing basic biology concepts behind proteomics and genomics. The book also discusses the current technological limitations that can be viewed as an emerging market rather than a research bottleneck. Topics covered include: molecular biology fundamentals: from ‘blueprint’ (DNA) to ‘task list’ (RNA) to ‘molecular machine’ (protein); proteomics methods and technologies; modelling protein networks and interactions analysis via automation: DNA sequencing; microarrays and other parallelization technologies; protein characterization and identification; protein interaction and gene regulatory networks design via automation: DNA synthesis; RNA by design; building protein libraries; synthetic networks integration: multiple modalities; computational and experimental methods; trends in automation for genomics and proteomics new enabling technologies and future applications Automation in Proteomics & Genomics: An Engineering Case-Based Approach is an essential guide to the current capabilities and challenges of high-throughput analysis of genes and proteins for bioinformaticians, engineers, chemists, and biologists interested in developing a cross-discipline problem-solving based approach to systems biology.

TRIVERGENCE

Author : Bob Tapscott
Publisher : John Wiley & Sons
ISBN 13 : 1394226624
Total Pages : 166 pages
Book Rating : 4.3/5 (942 download)

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Book Synopsis TRIVERGENCE by : Bob Tapscott

Download or read book TRIVERGENCE written by Bob Tapscott and published by John Wiley & Sons. This book was released on 2024-01-15 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Breakthrough Introduction to The Next Phase of the Digital Age In Trivergence, Bob Tapscott, writer, speaker, complex system designer, and former CIO introduces an exciting new concept in explaining how the intersection of artificial intelligence (AI), blockchain, and the Internet of Things (IoT) will transform business and society. He explains the synergies between these technologies and the disruptive potential that they will offer, as well as the challenges and risks to making it happen. He offers an insightful guide through the difficult decisions that businesses and society must make to thrive in a new era where decisions will be difficult, and uncertainties abound. You'll discover how and why AI's power is now exploding, its growth driven by smarter approaches to neural networks trained on a new hardware architecture that can derive its intelligence from ever more massive datasets. You'll also find: Discussions of the multiplicative and exponential power of trivergence on the core technologies discussed in the book Explorations of IoT's tendency to bring the physical world to life as it harnesses the capabilities of AI and the blockchain How trivergence morphs Big Data into something new he calls “Infinite Data”, where thinking machines consider trillions of data points to generate their own content, value, and perspectives without programmed code or human intervention A fresh and innovative guide, rich with case stories, on how the most critical technologies of this new phase in the digital age are combining to drive business transformation, Trivergence will become a critical handbook for forward-looking leaders, and anyone interested in the intersection of cutting-edge tech and business.

Statistical Analysis of Network Data

Author : Eric D. Kolaczyk
Publisher : Springer Science & Business Media
ISBN 13 : 0387881468
Total Pages : 397 pages
Book Rating : 4.3/5 (878 download)

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Book Synopsis Statistical Analysis of Network Data by : Eric D. Kolaczyk

Download or read book Statistical Analysis of Network Data written by Eric D. Kolaczyk and published by Springer Science & Business Media. This book was released on 2009-04-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.

Social Networks: Models of Information Influence, Control and Confrontation

Author : Alexander G. Chkhartishvili
Publisher : Springer
ISBN 13 : 3030054292
Total Pages : 158 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Social Networks: Models of Information Influence, Control and Confrontation by : Alexander G. Chkhartishvili

Download or read book Social Networks: Models of Information Influence, Control and Confrontation written by Alexander G. Chkhartishvili and published by Springer. This book was released on 2018-12-30 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys the well-known results and also presents a series of original results on the mathematical modeling of social networks, focusing on models of informational influence, control and confrontation. Online social networks are intended for communication, opinion exchange and information acquisition for their members, but recently, online social networks have been intensively used as the objects and means of informational control and an arena of informational confrontation. They have become a powerful informational influence tool, particularly for the manipulation of individuals, social groups and society as a whole, as well as a battlefield of information warfare (cyberwars). This book aimed at under- and postgraduate university students as well as experts in information technology and modeling of social systems and processes.