Big Data Optimization: Recent Developments and Challenges

Big Data Optimization: Recent Developments and Challenges

Author: Ali Emrouznejad

Publisher: Springer

ISBN: 9783319302652

Category: Technology & Engineering

Page: 487

View: 412

The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

Big Data and Blockchain for Service Operations Management

Big Data and Blockchain for Service Operations Management

Author: Ali Emrouznejad

Publisher: Springer Nature

ISBN: 9783030873042

Category: Artificial intelligence

Page: 350

View: 266

This book aims to provide the necessary background to work with big data blockchain by introducing some novel applications in service operations for both academics and interested practitioners, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book intends to cover theory, research, development, and applications of big data and blockchain, as embedded in the fields of mathematics, engineering, computer science, physics, economics, business, management, and life sciences, to help service operations management.

Big Data Analytics in Future Power Systems

Big Data Analytics in Future Power Systems

Author: Ahmed F. Zobaa

Publisher: CRC Press

ISBN: 9781351601290

Category: Science

Page: 174

View: 119

Power systems are increasingly collecting large amounts of data due to the expansion of the Internet of Things into power grids. In a smart grids scenario, a huge number of intelligent devices will be connected with almost no human intervention characterizing a machine-to-machine scenario, which is one of the pillars of the Internet of Things. The book characterizes and evaluates how the emerging growth of data in communications networks applied to smart grids will impact the grid efficiency and reliability. Additionally, this book discusses the various security concerns that become manifest with Big Data and expanded communications in power grids. Provide a general description and definition of big data, which has been gaining significant attention in the research community. Introduces a comprehensive overview of big data optimization methods in power system. Reviews the communication devices used in critical infrastructure, especially power systems; security methods available to vet the identity of devices; and general security threats in CI networks. Presents applications in power systems, such as power flow and protection. Reviews electricity theft concerns and the wide variety of data-driven techniques and applications developed for electricity theft detection.

Big Data Analytics in Supply Chain Management

Big Data Analytics in Supply Chain Management

Author: Iman Rahimi

Publisher: CRC Press

ISBN: 9781000326918

Category: Technology & Engineering

Page: 194

View: 109

In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.

Big Data Optimization: Recent Developments and Challenges

Big Data Optimization: Recent Developments and Challenges

Author: Ali Emrouznejad

Publisher: Springer

ISBN: 3319302639

Category: Computers

Page: 470

View: 177

The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

Optimization and Control for Systems in the Big-Data Era

Optimization and Control for Systems in the Big-Data Era

Author: Tsan-Ming Choi

Publisher: Springer

ISBN: 9783319535180

Category: Business & Economics

Page: 280

View: 605

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This “big data” provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

Cyber Defense Mechanisms

Cyber Defense Mechanisms

Author: Gautam Kumar

Publisher: CRC Press

ISBN: 9781000171983

Category: Computers

Page: 978

View: 589

This book discusses the evolution of security and privacy issues and brings related technological tools, techniques, and solutions into one single source. The book will take readers on a journey to understanding the security issues and possible solutions involving various threats, attacks, and defense mechanisms, which include IoT, cloud computing, Big Data, lightweight cryptography for blockchain, and data-intensive techniques, and how it can be applied to various applications for general and specific use. Graduate and postgraduate students, researchers, and those working in this industry will find this book easy to understand and use for security applications and privacy issues.

Big Data for Remote Sensing: Visualization, Analysis and Interpretation

Big Data for Remote Sensing: Visualization, Analysis and Interpretation

Author: Nilanjan Dey

Publisher: Springer

ISBN: 9783319899237

Category: Science

Page: 154

View: 328

This book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science. Remote sensing is considered a significant information source for monitoring and mapping natural and man-made land through the development of sensor resolutions that committed different Earth observation platforms. The book includes related topics for the different systems, models, and approaches used in the visualization of remote sensing images. It offers flexible and sophisticated solutions for removing uncertainty from the satellite data. It introduces real time big data analytics to derive intelligence systems in enterprise earth science applications. Furthermore, the book integrates statistical concepts with computer-based geographic information systems (GIS). It focuses on image processing techniques for observing data together with uncertainty information raised by spectral, spatial, and positional accuracy of GPS data. The book addresses several advanced improvement models to guide the engineers in developing different remote sensing visualization and analysis schemes. Highlights on the advanced improvement models of the supervised/unsupervised classification algorithms, support vector machines, artificial neural networks, fuzzy logic, decision-making algorithms, and Time Series Model and Forecasting are addressed. This book guides engineers, designers, and researchers to exploit the intrinsic design remote sensing systems. The book gathers remarkable material from an international experts' panel to guide the readers during the development of earth big data analytics and their challenges.

Optimizing Student Engagement in Online Learning Environments

Optimizing Student Engagement in Online Learning Environments

Author: Kumar, A.V. Senthil

Publisher: IGI Global

ISBN: 9781522536352

Category: Education

Page: 338

View: 868

Digital classrooms have become a common addition to curriculums in higher education; however, such learning systems are only successful if students are properly motivated to learn. Optimizing Student Engagement in Online Learning Environments is a critical scholarly resource that examines the importance of motivation in digital classrooms and outlines methods to reengage learners. Featuring coverage on a broad range of topics such as motivational strategies, learning assessment, and student involvement, this book is geared toward academicians, researchers, and students seeking current research on the importance of maintaining ambition among learners in digital classrooms.

Handbook of Research on Reinventing Economies and Organizations Following a Global Health Crisis

Handbook of Research on Reinventing Economies and Organizations Following a Global Health Crisis

Author: Costa, Teresa Gomes da

Publisher: IGI Global

ISBN: 9781799869276

Category: Business & Economics

Page: 554

View: 226

Due to the global health crisis, economies had to adapt to combat pandemic situations. In the present pandemic crisis, new legislation, methods, labor approaches, values, and social behaviors have emerged with a huge impact in all organizations. However, countries have applied different solutions, procedures, and rules to deal with crises. Therefore, the impact has been different per country. Organizations need to understand their customers and businesses not only to increase operational efficiency but also to increase stakeholder’s satisfaction and their competitiveness in a sustainable way. Customers are becoming more exigent and markets more complex, calling for the need for higher differentiation. This was enhanced in this pandemic situation, and to survive, organizations needed to change and adapt to the new normal. The Handbook of Research on Reinventing Economies and Organizations Following a Global Health Crisis deals with management and economic issues, particularly with the reinvention of businesses and economies due to the pandemic situation and the relevance of entrepreneurship, innovation, and intensive knowledge used to deal with these changes. This book emphasizes the challenges, difficulties, and opportunities for the success of businesses and economies in periods of crisis and provides information for dealing with entrepreneurship and innovation, networks, and complementarities to recover businesses. The chapters also point out possible opportunities, challenges, and risks in the process of recovery highlighting innovation, internationalization, technology, and intensive knowledge in promoting economies and companies’ competitiveness. This book is ideal for entrepreneurs, managers, economists, directors, shareholders, researchers, academicians, and students interested in how businesses reinvent and recover following a global health crisis.

Innovative Systems for Intelligent Health Informatics

Innovative Systems for Intelligent Health Informatics

Author: Faisal Saeed

Publisher: Springer Nature

ISBN: 9783030707132

Category: Computers

Page: 1262

View: 650

This book presents the papers included in the proceedings of the 5th International Conference of Reliable Information and Communication Technology 2020 (IRICT 2020) that was held virtually on December 21–22, 2020. The main theme of the book is “Innovative Systems for Intelligent Health Informatics”. A total of 140 papers were submitted to the conference, but only 111 papers were published in this book. The book presents several hot research topics which include health informatics, bioinformatics, information retrieval, artificial intelligence, soft computing, data science, big data analytics, Internet of things (IoT), intelligent communication systems, information security, information systems, and software engineering.

Social Big Data Analytics

Social Big Data Analytics

Author: Bilal Abu-Salih

Publisher: Springer Nature

ISBN: 9789813366527

Category: Business & Economics

Page: 218

View: 222

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.