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Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities
With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities...
Deep Learning Applications for Cyber-Physical Systems
Big data generates around us constantly from daily business, custom use, engineering, and science activities. Sensory data is collected from the internet of things (IoT) and cyber-physical systems (CPS). Merely storing such a massive amount of data is meaningless, as the key point is to identify, locate, and extract valuable knowledge from big data to forecast and support services. Such extracted valuable knowledge is usually referred to as smart data. It is vital to providing suitable decisions in business, science, and engineering applications. Deep Learning Applications for Cyber-Physical Systems provides researchers a platform to present state-of-the-art innovations, research, and design...
Guide to High Performance Distributed Computing
This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Features: describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing; presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution; Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case studies on approaches to clustering, data classification and regression analysis; Explains the process of creating a working recommender system using Scalding and Spark.
Advances in Distance Learning in Times of Pandemic
The book Advances in Distance Learning in Times of Pandemic is devoted to the issues and challenges faced by universities in the field of distance learning in COVID-19 times. It covers both the theoretical and practical aspects connected to distance education. It elaborates on issues regarding distance learning, its challenges, assessment by students and their expectations, the use of tools to improve distance learning, and the functioning of e-learning in the industry 4.0 and society 5.0 eras. The book also devotes a lot of space to the issues of Web 3.0 in university e-learning, quality assurance, and knowledge management. The aim and scope of this book is to draw a holistic picture of ong...
Research Anthology on Bioinformatics, Genomics, and Computational Biology
In the evolving environment of bioinformatics, genomics, and computational biology, academic scholars are facing a challenging challenge – keeping informed about the latest research trends and findings. With unprecedented advancements in sequencing technologies, computational algorithms, and machine learning, these fields have become indispensable tools for drug discovery, disease research, genome sequencing, and more. As scholars strive to decode the language of DNA, predict protein structures, and navigate the complexities of biological data analysis, the need for a comprehensive and up-to-date resource becomes paramount. The Research Anthology on Bioinformatics, Genomics, and Computatio...
Handbook of Research on Cloud Infrastructures for Big Data Analytics
Clouds are being positioned as the next-generation consolidated, centralized, yet federated IT infrastructure for hosting all kinds of IT platforms and for deploying, maintaining, and managing a wider variety of personal, as well as professional applications and services. Handbook of Research on Cloud Infrastructures for Big Data Analytics focuses exclusively on the topic of cloud-sponsored big data analytics for creating flexible and futuristic organizations. This book helps researchers and practitioners, as well as business entrepreneurs, to make informed decisions and consider appropriate action to simplify and streamline the arduous journey towards smarter enterprises.
Big Data Analytics
Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes. Chapters examining analytics for decision-making cover such topics as: Big data analytics for gathering business intelligence Data analytics and consumer behavior The role of big data analytics in organizational decision-making This book also looks at digital marketing and focuses on such areas as: The prediction of marketing by consumer analytics Web analytics for digital marketing Smart retailing Leveraging web analytics for optimizing digital marketing strategies Big Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making.
Python programming for Data Scientists
Python programming language is an open source programming language which can be used under different operating system. Python programming redefined the programming concepts with its important features like flexibility, adaptability and reusability of codes. Python programming language has numerous libraries or modules which helps the programmer to save their time. The book starts with the overview of basic Python topics such as data structures, data types, conditions and controls, functions, lists, file handling and handling external datasets and database connections. The book also covers the topics in data science such as graphical and chart visualization, statistical modeling, text mining ...
Securing the Internet of Things: Concepts, Methodologies, Tools, and Applications
The ubiquity of modern technologies has allowed for increased connectivity between people and devices across the globe. This connected infrastructure of networks creates numerous opportunities for applications and uses. As the applications of the internet of things continue to progress so do the security concerns for this technology. The study of threat prevention in the internet of things is necessary as security breaches in this field can ruin industries and lives. Securing the Internet of Things: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines recent developments and emerging trends in security and privacy for the internet of things through new models, practical solutions, and technological advancements related to security. Highlighting a range of topics such as cloud security, threat detection, and open source software, this multi-volume book is ideally designed for engineers, IT consultants, ICT procurement managers, network system integrators, infrastructure service providers, researchers, academics, and professionals interested in current research on security practices pertaining to the internet of things.
Blockchain for Industry 4.0
This reference text provides the theoretical foundations, the emergence, and the application areas of Blockchain in an easy-to-understand manner that would be highly helpful for the researchers, academicians, and industry professionals to understand the disruptive potentials of Blockchain. It explains Blockchain concepts related to Industry 4.0, Smart Healthcare, and the Internet of Things (IoT) and explores Smart Contracts and Consensus algorithms. This book will serve as an ideal reference text for graduate students and academic researchers in electrical engineering, electronics and communication engineering, computer engineering, and information technology. This book • Discusses applica...
