A level of decision making is concerned with deciding the organization's objectives, resources, and policies. A significant problem at this decision-making level is predicting the organization's future and its environment as well as matching the organization's characteristics to that environment. This process generally involves technology and knowledge from the market and clients. In the current era, the implementation of marketing information systems supported with AI techniques is crucial to being a unique opportunity to leverage marketing strategies with cutting-edge technologies. Global Perspectives on the Strategic Role of Marketing Information Systems communicates the recent advances in marketing information systems. Covering topics such as digital entrepreneurship, international business, and micro and small enterprises, this premier reference source is a cutting-edge resource for marketers, entrepreneurs, business leaders and managers, IT managers, students and educators of higher education, librarians, researchers, and academicians.

Network Science Network Science offers comprehensive insight on network analysis and network optimization algorithms, with simple step-by-step guides and examples throughout, and a thorough introduction and history of network science, explaining the key concepts and the type of data needed for network analysis, ensuring a smooth learning experience for readers. It also includes a detailed introduction to multiple network optimization algorithms, including linear assignment, network flow and routing problems. The text is comprised of five chapters, focusing on subgraphs, network analysis, network optimization, and includes a list of case studies, those of which include influence factors in telecommunications, fraud detection in taxpayers, identifying the viral effect in purchasing, finding optimal routes considering public transportation systems, among many others. This insightful book shows how to apply algorithms to solve complex problems in real-life scenarios and shows the math behind these algorithms, enabling readers to learn how to develop them and scrutinize the results. Written by a highly qualified author with significant experience in the field, Network Science also includes information on: Sub-networks, covering connected components, bi-connected components, community detection, k-core decomposition, reach network, projection, nodes similarity and pattern matching Network centrality measures, covering degree, influence, clustering coefficient, closeness, betweenness, eigenvector, PageRank, hub and authority Network optimization, covering clique, cycle, linear assignment, minimum-cost network flow, maximum network flow problem, minimum cut, minimum spanning tree, path, shortest path, transitive closure, traveling salesman problem, vehicle routing problem and topological sort With in-depth and authoritative coverage of the subject and many case studies to convey concepts clearly, Network Science is a helpful training resource for professional and industry workers in, telecommunications, insurance, retail, banking, healthcare, public sector, among others, plus as a supplementary reading for an introductory Network Science course for undergraduate students.

This book will help you become the trader you want to be, but it won't happen automatically. You won't be immediately successful the moment you finish reading.

Earning money with day trading is possible, but it takes time, discipline, effort and commitment on your part.Let me explain. Throughout the book, you will learn key concepts that you can apply to your trading right away. The knowledge you accumulate is essential because it is what you base your trading decisions on, the decisions that will determine your ultimate success or failure.

One of my key goals in this book is to help you expand your tradingknowledge to make informed decisions. I will provide you with many valuable resources to help you learn what you need to know.At the end of each chapter you will find "Action Actions", exercises related to the topics recently covered. If you want to get the most out of this book, take a few minutes to complete these Actions. The results you will get will, in most cases, be directly proportional to the effort and commitment you invest in creating them.

I am committed to helping you become the best trader you can be, but I will need your help to do so.

Intelligent Nanotechnology: Merging Nanoscience and Artificial Intelligence provides an overview of advances in science and technology made possible by the convergence of nanotechnology and artificial intelligence (AI). Sections focus on AI-enhanced design, characterization and manufacturing and the use of AI to improve important material properties, with an emphasis on mechanical, photonic, electronic and magnetic properties. Designing benign nanomaterials through the prediction of their impact on biology and the environment is also discussed. Other sections cover the use of AI in the acquisition and analysis of data in experiments and AI technologies that have been enhanced through nanotechnology platforms. Final sections review advances in applications enabled by the merging of nanotechnology and artificial intelligence, including examples from biomedicine, chemistry and automated research.

Case Studies in Geospatial Applications to Groundwater Resources provides thorough the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, through detailed case studies that prove real-world applications of remote sensing applications to this subject. Groundwater is the primary source of fresh water in many parts of the world, while come regions are becoming overly dependent on it, consuming groundwater faster than it is naturally replenished and causing water tables to decline unremittingly. India is the largest user of groundwater in the world followed by China and the USA, with developing countries using groundwater at an unsustainable rate. Systematic planning of groundwater usage using modern techniques is essential for the proper utilization, management and modeling of this precious but shrinking natural resource. With the advent of powerful and highspeed personal computers, efficient techniques for water management have evolved, of which remote sensing, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Geostatistical techniques are of great significance. This book advances the scientific understanding, development, and application of geospatial technologies related to water resource management. Case Studies in Geospatial Applications to Groundwater Resources is a valuable reference for researchers and postgraduate students in Earth and Environmental Sciences, especially GIS, agriculture, hydrology, natural resources, and soil science, who need to be able to apply the latest technologies in groundwater research in a practical manner.

The Beginnings of Electron Microscopy - Part 2, Volume 221 in the Advances in Imaging and Electron Physics series, highlights new advances in the field, with this new volume presenting interesting chapters on Recollections from the Early Years: Canada-USA, My Recollection of the Early History of Our Work on Electron Optics and the Electron Microscope, Walter Hoppe (1917-1986), Reminiscences of the Development of Electron Optics and Electron Microscope Instrumentation in Japan, Early Electron Microscopy in The Netherlands, L. L. Marton, 1901-1979, The Invention of the Electron Fresnel Interference Biprism, The Development of the Scanning Electron Microscope, and much more.

Advances in Computers, Volume 127 presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on Edge AI, Edge Computing, Edge Analytics, Edge Data Analytics, Edge Native Applications, Edge Platforms, Edge Computing, IoT, Internet of Things, etc.

Cyber security is a key focus in the modern world as more private information is stored and saved online. In order to ensure vital information is protected from various cyber threats, it is essential to develop a thorough understanding of technologies that can address cyber security challenges. Artificial intelligence has been recognized as an important technology that can be employed successfully in the cyber security sector. Due to this, further study on the potential uses of artificial intelligence is required. The Handbook of Research on Cyber Security Intelligence and Analytics discusses critical artificial intelligence technologies that are utilized in cyber security and considers various cyber security issues and their optimal solutions supported by artificial intelligence. Covering a range of topics such as malware, smart grid, data breachers, and machine learning, this major reference work is ideal for security analysts, cyber security specialists, data analysts, security professionals, computer scientists, government officials, researchers, scholars, academicians, practitioners, instructors, and students.

There has been an increased use of technology in educational settings since the start of the COVID-19 pandemic. Despite the benefits of including such technologies to support education, there is still the need for vigilance to counter the inherent risk that comes with the use of such technologies as the protection of students and their information is paramount to the effective deployment of any technology in education. Current Trends in Cybersecurity and Educational Technology explores the full spectrum of cybersecurity and educational technology today and brings awareness to the recent developments and use cases for emergent educational technology. Covering key topics such as artificial intelligence, gamification, robotics, and online learning, this premier reference source is ideal for computer scientists, industry professionals, policymakers, administrators, researchers, academicians, scholars, practitioners, instructors, and students.

Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis.

Digital evolution has become increasingly present in our lives, whether on cellphones, computers, watches, or other appliances. As a result of the wide access we have to the digital world, the amount of data generated daily is vast. This density of information generated at every moment can be the insight needed for the success of an organization. Much is said about data-based decision-making to generate the best results. The new capabilities of data intelligence unleashed by the emergence of cloud computing and artificial intelligence make it one of the most promising areas of digital transformation change management. Enhancing Business Communications and Collaboration Through Data Science Applications provides relevant theoretical frameworks and the latest empirical research findings in the area. It is written for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. Covering topics such as data science, online business communication, and user-centered design, this premier reference source is an ideal resource for business managers and leaders, entrepreneurs, data scientists, data analysts, sociologists, students and educators of higher education, librarians, researchers, and academicians.

There has been a multitude of studies focused on the COVID-19 pandemic across fields and disciplines as all sectors of life have had to adjust the way things are done and adapt to the constantly shifting environment. These studies are crucial as they provide support and perspectives on how things are changing and what needs to be done to stay afloat. Connecting COVID-19-related studies and big data analytics is crucial for the advancement of industrial applications and research areas. Applied Big Data Analytics and Its Role in COVID-19 Research introduces the most recent industrial applications and research topics on COVID-19 with big data analytics. Featuring coverage on a broad range of big data technologies such as data gathering, artificial intelligence, smart diagnostics, and mining mobility, this publication provides concrete examples and cases of usage of data-driven projects in COVID-19 research. This reference work is a vital resource for data scientists, technical managers, researchers, scholars, practitioners, academicians, instructors, and students.

In this book, I am going to show you everything you need to know:

1. Exactly how to set up your own portfolio of dividend stocks
2. Where to open up a brokerage account
3. How to never pay a commission when you buy or sell a stock
4. Which dividend stocks are the safest
5. Which dividend stocks to avoid (don't start investing until you read this)
6. How to super-charge your returns
7. How to profit from a bear market

And much, much more...

The Handbook on Socially Interactive Agents provides a comprehensive overview of the research fields of Embodied Conversational Agents Intelligent Virtual Agents and Social Robotics. Socially Interactive Agents (SIAs) whether virtually or physically embodied are autonomous agents that are able to perceive an environment including people or other agents reason decide how to interact and express attitudes such as emotions engagement or empathy. They are capable of interacting with people and one another in a socially intelligent manner using multimodal communicative behaviors with the goal to support humans in various domains.Written by international experts in their respective fields the book summarizes research in the many important research communities pertinent for SIAs while discussing current challenges and future directions. The handbook provides easy access to modeling and studying SIAs for researchers and students and aims at further bridging the gap between the research communities involved. In two volumes the book clearly structures the vast body of research. The first volume starts by introducing what is involved in SIAs research in particular research methodologies and ethical implications of developing SIAs. It further examines research on appearance and behavior focusing on multimodality. Finally social cognition for SIAs is investigated using different theoretical models and phenomena such as theory of mind or pro-sociality. The second volume starts with perspectives on interaction examined from different angles such as interaction in social space group interaction or long-term interaction. It also includes an extensive overview summarizing research and systems of human-agent platforms and of some of the major application areas of SIAs such as education aging support autism and games.

Adversarial Robustness for Machine Learning summarizes the recent progress on this topic and introduces popular algorithms on adversarial attack, defense and veri?cation. Sections cover adversarial attack, veri?cation and defense, mainly focusing on image classi?cation applications which are the standard benchmark considered in the adversarial robustness community. Other sections discuss adversarial examples beyond image classification, other threat models beyond testing time attack, and applications on adversarial robustness. For researchers, this book provides a thorough literature review that summarizes latest progress in the area, which can be a good reference for conducting future research. In addition, the book can also be used as a textbook for graduate courses on adversarial robustness or trustworthy machine learning. While machine learning (ML) algorithms have achieved remarkable performance in many applications, recent studies have demonstrated their lack of robustness against adversarial disturbance. The lack of robustness brings security concerns in ML models for real applications such as self-driving cars, robotics controls and healthcare systems.

Recent years have seen a proliferation of cybersecurity guidance in the form of government regulations and standards with which organizations must comply. As society becomes more heavily dependent on cyberspace, increasing levels of security measures will need to be established and maintained to protect the confidentiality, integrity, and availability of information; the privacy of consumers; and the continuity of economic activity. Compliance is a measure of the extent to which a current state is in conformance with a desired state. The desired state is commonly operationalized through specific business objectives, professional standards, and regulations. Assurance services provide a means of evaluating the level of compliance with various cybersecurity requirements. The proposed book will summarize current cybersecurity guidance and provide a compendium of innovative and state-of-the-art compliance and assurance practices and tools that can function both as a reference and pedagogical source for practitioners and educators. This publication will provide a synopsis of current cybersecurity guidance that organizations should consider in establishing and updating their cybersecurity systems. Assurance services will also be addressed so that management and their auditors can regularly evaluate their extent of compliance. This book should be published because its theme will provide company management, practitioners, and academics with a good summary of current guidance and how to conduct assurance of appropriate compliance.