Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel and Amazon can be interpreted using this book.

During these uncertain and turbulent times, intelligent technologies including artificial neural networks (ANN) and machine learning (ML) have played an incredible role in being able to predict, analyze, and navigate unprecedented circumstances across a number of industries, ranging from healthcare to hospitality. Multi-factor prediction in particular has been especially helpful in dealing with the most current pressing issues such as COVID-19 prediction, pneumonia detection, cardiovascular diagnosis and disease management, automobile accident prediction, and vacation rental listing analysis. To date, there has not been much research content readily available in these areas, especially content written extensively from a user perspective. Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning is designed to cover a brief and focused range of essential topics in the field with perspectives, models, and first-hand experiences shared by prominent researchers, discussing applications of artificial neural networks (ANN) and machine learning (ML) for biomedical and business applications and a listing of current open-source software for neural networks, machine learning, and artificial intelligence. It also presents summaries of currently available open source software that utilize neural networks and machine learning. The book is ideal for professionals, researchers, students, and practitioners who want to more fully understand in a brief and concise format the realm and technologies of artificial neural networks (ANN) and machine learning (ML) and how they have been used for prediction of multi-disciplinary research problems in a multitude of disciplines.

Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and deep neural network (DNN), the book addresses how they have evolved to deal with multichannel and single-channel source separation.

Due to the increasing availability of affordable internet services, the number of users, and the need for a wider range of multimedia-based applications, internet usage is on the rise. With so many users and such a large amount of data, the requirements of analyzing large data sets leads to the need for further advancements to information processing. Big Data Processing with Hadoop is an essential reference source that discusses possible solutions for millions of users working with a variety of data applications, who expect fast turnaround responses, but encounter issues with processing data at the rate it comes in. Featuring research on topics such as market basket analytics, scheduler load simulator, and writing YARN applications, this book is ideally designed for IoT professionals, students, and engineers seeking coverage on many of the real-world challenges regarding big data.

Data is the most important commodity, which is why data protection has become a global priority. Data breaches and security flaws can jeopardize the global economy. Organizations face a greater risk of failing to achieve strategy and business goals as cyber threat behavior grows in frequency, sophistication, and destructiveness. A breach can result in data loss, business interruption, brand and reputation harm, as well as regulatory and legal consequences. A company needs a well-thought-out cybersecurity strategy to secure its critical infrastructure and information systems in order to overcome these challenges. Cross-Industry Applications of Cyber Security Frameworks provides an understanding of the specific, standards-based security controls that make up a best practice cybersecurity program. It is equipped with cross-industry applications of cybersecurity frameworks, best practices for common practices, and suggestions that may be highly relevant or appropriate in every case. Covering topics such as legal frameworks, cybersecurity in FinTech, and open banking, this premier reference source is an essential resource for executives, business leaders, managers, entrepreneurs, IT professionals, government officials, hospital administrators, educational administrators, privacy specialists, researchers, and academicians.

Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts. New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students.

The proliferation of wireless communications has led to mobile computing, a new era in data communication and processing allowing people to access information anywhere and anytime using lightweight computer devices. Aligned with this phenomenon, a vast number of mobile solutions, systems, and applications have been continuously developed. However, despite the opportunities, there exist constraints, challenges, and complexities in realizing the full potential of mobile computing, requiring research and experimentation. Algorithms, Methods, and Applications in Mobile Computing and Communications is a critical scholarly publication that examines the various aspects of mobile computing and communications from engineering, business, and organizational perspectives. The book details current research involving mobility challenges that hinder service applicability, mobile money transfer services and anomaly detection, and mobile fog environments. As a resource rich in information about mobile devices, wireless broadcast databases, and machine communications, it is an ideal source for computer scientists, IT specialists, service providers, information technology professionals, academicians, and researchers interested in the field of mobile computing.

Changing business environments and information technology advancements fundamentally reshaped the traditional information landscape in our contemporary society, urging companies to seek innovative ways to diffuse and manage assets on a global scale. It is crucial for society to understand the new methodologies and common practices that organizations can utilize to leverage their knowledge into practice. Global Information Diffusion and Management in Contemporary Society is an essential reference source featuring research on the development and implementation of contemporary global information management initiatives in organizations. Including coverage on a multitude of topics such as data security, global manufacturing, and information governance, this book explores the importance of information management in a global context. This book is ideally designed for managers, information systems specialists, professionals, researchers, and administrators seeking current research on the theories and applications of global information management.

With the leverage of digital reproducibility, historical messages of hate are finding new recipients with breathtaking speed and scope. The rapid growth in popularity of right-wing extremist groups in response to transnational economic crises underscores the importance of examining in detail the language and political mobilization strategies of the New Right. In Europe, for example, populist right-wing activists organized around an anti-immigration agenda are becoming more vocal, providing pushback against the increase in migration flows from North Africa and Eastern Europe and countering support for integration with a categorical rejection of multiculturalism. In the United States, anti-immigration sentiment provides a rallying point for political and personal agendas that connect the rhetoric of borders with national, racial, and security issues. Digital Media Strategies of the Far Right in Europe and the United States is an effort to examine and understand these issues, informed by the conviction that an interdisciplinary and transnational approach can allow productive comparison of far-right propaganda strategies in Europe and the United States. With a special emphasis on performing ideology in the far-right music scene, on violent anti-immigrant stances, and on the far right's skillful creation and manipulation of virtual communities, the contributions foreground the cultural shibboleths that are exchanged among far-right supporters on the Internet, which serve to generate a sense of group belonging and the illusion of power far greater that the known numbers of neo-Nazis in any one country might suggest. Moreover, with attention to transatlantic right-wing movements and their use of particularly digital media, the essays in this volume put pressure on the similarities among the various national agents, while accommodating differences in the virtual and sometimes violent identities created and nurtured online.

Harden your business against internal and external cybersecurity threats with a single accessible resource. In 8 Steps to Better Security: A Simple Cyber Resilience Guide for Business, cybersecurity researcher and writer Kim Crawley delivers a grounded and practical roadmap to cyber resilience in any organization. Offering you the lessons she learned while working for major tech companies like Sophos, AT&T, BlackBerry Cylance, Tripwire, and Venafi, Crawley condenses the essence of business cybersecurity into eight steps. Written to be accessible to non-technical businesspeople as well as security professionals, and with insights from other security industry leaders, this important book will walk you through how to: Foster a strong security culture that extends from the custodial team to the C-suite Build an effective security team, regardless of the size or nature of your business Comply with regulatory requirements, including general data privacy rules and industry-specific legislation Test your cybersecurity, including third-party penetration testing and internal red team specialists Perfect for CISOs, security leaders, non-technical businesspeople, and managers at any level, 8 Steps to Better Security is also a must-have resource for companies of all sizes, and in all industries.

In a world dependent on digital technologies, business corporations continually try to stay ahead of their competitors by adopting the most updated technology into their business processes. Many companies are adopting digital transformation models, data analytics, big data, data empowerment, and data sharing as key strategies and as service disruptors for information delivery and record management. Higher education institutions have adopted digital service innovation as a core to driving their business processes. Such services are key to ensuring efficiency and improving organizational performance. Digital Transformation and Innovative Services for Business and Learning is a collection of innovative research on the latest digital services and their role in supporting the digital transformation of businesses and education. While highlighting topics including brand equality, digital banking, and generational workforce, this book is ideally designed for managers, executives, IT consultants, industry professionals, academicians, researchers, and students.

The digital transformation of healthcare delivery is in full swing. Health monitoring is increasingly becoming more effective, efficient, and timely through mobile devices that are now widely available. This, as well as wireless technology, is essential to assessing, diagnosing, and treating medical ailments. However, systems and applications that boost wellness must be properly designed and regulated in order to protect the patient and provide the best care. Optimizing Health Monitoring Systems With Wireless Technology is an essential publication that focuses on critical issues related to the design, development, and deployment of wireless technology solutions for healthcare and wellness. Highlighting a broad range of topics including solution evaluation, privacy and security, and policy and regulation, this book is ideally designed for clinicians, hospital directors, hospital managers, consultants, health IT developers, healthcare providers, engineers, software developers, policymakers, researchers, academicians, and students.