Human Behavior And Another Kind In Consciousness Emerging Research And Opportunities

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 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.

Why is there so much chaos and suffering in the world today? Are we sliding towards dystopia and perhaps extinction, or is there hope for a better future? What happened in the human lineage over the last three million years that made us into a near-geologic force capable of altering the face of our planet and threatening our own existence? In Emerging World, Roger Briggs explores the evolution of consciousness and shows that this is behind everything humans have done, are now doing, and are capable of in the future. By bringing together the best knowledge from paleoanthropology, cultural philosophy, cognitive psychology, and evolutionary theory, Briggs makes the case that humanity is now on the verge of a major transformation, a monumental turning point in our story. Foreseen by many sages and scholars, this anticipated leap promises a new era of history and culture, and a new civilization on Earth in which the needs of all people are met and we become stewards of our living planet. Yet this is by no means guaranteed. Emerging World offers a new understanding of our crisis today and points the way to a bright future for humanity and life on our planet.

Consciousness is a quality of the mind generally regarded to comprise qualities such as subjectivity, self-awareness, sentience, sapience, and the ability to perceive the relationship between oneself and one's environment. It is a subject of much research in philosophy of the mind, psychology, neurology, and cognitive science. This book presents a compilation of new and significant research on the many facets of consciousness. These include psychoenergetic studies, neurobiological hypothesis, theories on unconsciousness and psychoanalytic theories relating to sexual experiences.

This book constitutes the refereed proceedings of the Second International Workshop on Distributed Computing for Emerging Smart Networks, DiCES-N 2020, held in Bizerte, Tunisia, in December 2020. Due to the COVID-19 pandemic the conference was held online. The 8 full papers included in this volume were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: ​intelligent transportation systems; emerging networking technologies; artificial intelligence and internet of things.