New technological communication methods have created new kinds of interactions among us that have allowed people across the globe to become closer, but they have also created more complex global dynamics. These dynamics have expanded the workings of human behavior, making human-seeming artificial intelligence a more difficult goal to achieve. Human Behavior and Another Kind in Consciousness: Emerging Research and Opportunities is a crucial reference book that examines human consciousness and how it can translate into artificial intelligence. Covering important topics such as cloud computing, human behavior, and intelligent systems, this book is ideal for engineers, researchers, academicians, and students in the fields of computer science, artificial intelligence, operations research, and intelligent systems.

Advances in technological innovations, automation, and the latest developments in artificial intelligence (AI) have revolutionized the nature of work and created a demand for a new set of skills to navigate the Fourth Industrial Revolution (Industry 4.0). Therefore, it is necessary to equip displaced workers with a new set of skills that are essential for conversion into technical or other functional areas of business. Human Capital Formation for the Fourth Industrial Revolution is an essential research publication that recognizes the need to revitalize human capital formation for graduate employability in Industry 4.0 and discusses new skills and competencies needed to cope with the challenges present within this industrial revolution. The book seeks to provide a basis for curriculum design in line with the advances in technological innovations, automation, and artificial intelligence to enhance current and future employment. Featuring an array of topics such as curriculum design, emotional intelligence, and healthcare, this book is ideal for human resource managers, development specialists, training officers, teachers, universities, practitioners, academicians, researchers, managers, policymakers, and students.

Deep learning, often known as DL, is an approach to machine learning that is increasingly seen as the way of the future. Because of its impressive power of learning high-level abstract characteristics from enormous amounts of data, DL garners a lot of interest and also has a lot of success in pattern recognition, computer vision, data mining, and knowledge discovery. This is why DL is so successful in these areas. This book will not only seek to give a basic roadmap or direction to the existing deep learning approaches, but it will also highlight the problems and imagine fresh views that can lead to additional advancements in this subject. One of the most talked about topics in data science today is deep learning. Deep learning is a subfield of machine learning that makes use of sophisticated algorithms that take their cues from the way our own neural networks are wired and operate. The goal of this book is to provide a thorough introduction to deep learning, including an examination of its underlying algorithms, a presentation of its most recent theoretical advancements, a discussion of the most popular deep learning platforms and data sets, and an account of the significant advances made by a wide range of deep learning methodologies in areas such as text, video, image, speech, and audio processing.

More complex computing approaches have grown in popularity as technology has improved and big data has emerged. Increasing customer demand for better goods, as well as firms trying to better exploit their resources, have been driving this trend. Machine learning is a field that combines statistics, mathematics, and computer science to create and analyze algorithms that improve their own behavior in an iterative fashion by design. Initially, the discipline was committed to the development of artificial intelligence, but owing to the constraints of theory and technology at the time, it became more reasonable to concentrate these algorithms on particular tasks. Deep learning is a sort of machine learning and artificial intelligence (AI) that mimics how people acquire certain types of knowledge. Deep learning is a critical component of data science, which also covers statistics and predictive modeling. Deep learning is particularly advantageous to data scientists who are responsible with gathering, analyzing, and interpreting massive volumes of data; deep learning speeds up and simplifies this process. In this book the concept of deep learning under the machine learning is explained in every aspect. Whether, it's their fundamental concepts or the application of deep learning on daily basis.

The psychology classic—a detailed study of scientific theories of human nature and the possible ways in which human behavior can be predicted and controlled—from one of the most influential behaviorists of the twentieth century and the author of Walden Two. “This is an important book, exceptionally well written, and logically consistent with the basic premise of the unitary nature of science. Many students of society and culture would take violent issue with most of the things that Skinner has to say, but even those who disagree most will find this a stimulating book.” —Samuel M. Strong, The American Journal of Sociology “This is a remarkable book—remarkable in that it presents a strong, consistent, and all but exhaustive case for a natural science of human behavior…It ought to be…valuable for those whose preferences lie with, as well as those whose preferences stand against, a behavioristic approach to human activity.” —Harry Prosch, Ethics

The basic book about the controversial philosophy known as behaviorism, written by its leading exponent.

The state of college students’ mental health is a growing phenomenon across university campuses. Educators often watch students struggle with academic, social, financial, and familial issues. Over the past decade, these issues have led to an increasing number of students exhibiting behavior related to anxiety, depression, and other mental health disorders. Raising Mental Health Awareness in Higher Education: Emerging Research and Opportunities describes the current state of college students’ mental health in the United States, influences that contribute to wavering mental health, factors that promote flourishing mental health, and interventions that support mental health. While highlighting present programs and activities, readers will find new methods that can be implemented to support the needs of college students. This book is an important resource for staff and faculty in postsecondary institutions seeking current research on the growing problem of mental health in higher education.