Gamification is being used everywhere; despite its apparent plethora of benefits, the unbalanced use of its main mechanics can end up in catastrophic results for a company or institution. Currently, there is a lack of knowledge of what it is, leading to its unregulated and ad hoc use without any prior planning. This unbalanced use prejudices the achievement of the initial goals and impairs the user's evolution, bringing potential negative reflections. Currently, there are few specifications and modeling languages that allow the creation of a system of rules to serve as the basis for a gamification engine. Consequently, programmers implement gamification in a variety of ways, undermining any attempt at reuse and negatively affecting interoperability. Next-Generation Applications and Implementations of Gamification Systems synthesizes all the trends, best practices, methodologies, languages, and tools that are used to implement gamification. It also discusses how to put gamification in action by linking academic and informatics researchers with professionals who use gamification in their daily work to disseminate and exchange the knowledge, information, and technology provided by the international communities in the area of gamification throughout the 21st century. Covering topics such as applied and cloud gamification, chatbots, deep learning, and certifications and frameworks, this book is ideal for programmers, computer scientists, software engineers, practitioners of technological companies, managers, academicians, researchers, and students.

Advances in Mathematics for Industry 4.0 examines key tools, techniques, strategies, and methods in engineering applications. By covering the latest knowledge in technology for engineering design and manufacture, chapters provide systematic and comprehensive coverage of key drivers in rapid economic development. Written by leading industry experts, chapter authors explore managing big data in processing information and helping in decision-making, including mathematical and optimization techniques for dealing with large amounts of data in short periods.

Superlubricity - the state between sliding systems where friction is reduced to almost immeasurable amounts - holds great potential for improving both the economic and environmental credentials of moving mechanical systems. Research in this field has progressed tremendously in recent years, and there now exist several theoretical models, recognised techniques for computational simulations and interesting experimental evidence of superlubricity in practise. Superlubricity, Second Edition, presents an extensively revised and updated overview of these important developments, providing a comprehensive guide to the physical chemistry underpinning molecular mechanisms of friction and lubrication, current theoretical models used to explore and assess superlubricity, examples of its achievement in experimental systems, and discussion of potential future applications. Drawing on the extensive knowledge of its expert editors and global team of authors from across academia and industry, Superlubricity, Second Edition, is a great resource for all those with a need to understand, model or manipulate surface interactions for improved performance.

The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient's life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics.

The security of an organizational information system with the invention of next-generation technologies is a prime focus these days. The industries and institutions in the field of computing and communication, especially in internet of things, cloud computing, mobile networks, next-generation networks, the energy market, banking sector, government sector, and many more, are primarily focused on these security and privacy issues. Blockchain is a new technology that has changed the scenario when it comes to addressing security concerns and resolving traditional safety issues. These industries have started developing applications based on the blockchain underlying platform to tap into this unlimited potential. Blockchain technologies have a great future, but there are still many challenges and issues to resolve for optimal design and utilization of the technology. Revolutionary Applications of Blockchain-Enabled Privacy and Access Control focuses on the recent challenges, design, and issues in the field of blockchain technologies-enabled privacy and advanced security practices in computing and communication. This book provides the latest research findings, solutions, and relevant theoretical frameworks in blockchain technologies, information security, and privacy in computing and communication. While highlighting the technology itself along with its applications and future outlook, this book is ideal for IT specialists, security analysts, cybersecurity professionals, researchers, academicians, students, scientists, and IT sector industry practitioners looking for research exposure and new ideas in the field of blockchain.

Usability Testing for Survey Research provides researchers with a guide to the tools necessary to evaluate, test, and modify surveys in an iterative method during the survey pretesting process. It includes examples that apply usability to any type of survey during any stage of development, along with tactics on how to tailor usability testing to meet budget and scheduling constraints. The book's authors distill their experience to provide tips on how usability testing can be applied to paper surveys, mixed-mode surveys, interviewer-administered tools, and additional products. Readers will gain an understanding of usability and usability testing and why it is needed for survey research, along with guidance on how to design and conduct usability tests, analyze and report findings, ideas for how to tailor usability testing to meet budget and schedule constraints, and new knowledge on how to apply usability testing to other survey-related products, such as project websites and interviewer administered tools.

The amalgamation of post-quantum cryptography in cyber-physical systems makes the computing system secure and also generates opportunities in areas like smart contracts, quantum blockchain, and smart security solutions. Sooner or later, all computing and security systems are going to adopt quantum-proof cryptography to safeguard these systems from quantum attacks. Post-quantum cryptography has tremendous potential in various domains and must be researched and explored further to be utilized successfully. Advancements in Quantum Blockchain With Real-Time Applications considers various concepts of computing such as quantum computing, post-quantum cryptography, quantum attack-resistant blockchain, quantum blockchains, and multidisciplinary applications and real-world use cases. The book also discusses solutions to various real-world problems within the industry. Covering key topics such as cybersecurity, data management, and smart society, this reference work is ideal for computer scientists, industry professionals, academicians, practitioners, scholars, researchers, instructors, and students.

Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study-driven best practices, including renewable energy sources, the smart grid, and the finances around spot markets, and forecasting.

Blockchain is the most disruptive technology to emerge in the last decade. The evolution of cryptocurrencies has carried with it a revolution in digital economics that has catapulted the application of blockchain technology to a new level across a variety of industries, including banking, security, networking, and more. Blockchain Technology and Computational Excellence for Society 5.0 closes the gap in existing literature by presenting a selection of chapters that not only shape the research domain, but also present supportive real-life problems and pragmatic solutions. This book presents a variety of highly relevant themes, concepts, and applications in blockchain, discussing topics such as cyber security, digital currencies, and intelligent networks, fueling awareness and interest. With its insight into various platforms, techniques, and tools, this book serves as a valuable resource for academicians, researchers, research scholars, postgraduates, professors, computer scientists, and technology enthusiasts.

Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences, the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including a historical review on the development of machine learning, machine learning to investigate fault rupture on various scales, a review on machine learning techniques to describe fractured media, signal augmentation to improve the generalization of deep neural networks, deep generator priors for Bayesian seismic inversion, as well as a review on homogenization for seismology, and more.

Security in IoT Social Networks takes a deep dive into security threats and risks, focusing on real-world social and financial effects. Mining and analyzing enormously vast networks is a vital part of exploiting Big Data. This book provides insight into the technological aspects of modeling, searching, and mining for corresponding research issues, as well as designing and analyzing models for resolving such challenges. The book will help start-ups grow, providing research directions concerning security mechanisms and protocols for social information networks. The book covers structural analysis of large social information networks, elucidating models and algorithms and their fundamental properties. Moreover, this book includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models. This book is a detailed reference for academicians, professionals, and young researchers. The wide range of topics provides extensive information and data for future research challenges in present-day social information networks.