This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

The success of any organization is largely dependent on positive feedback and repeat business from patrons. By utilizing acquired marketing data, business professionals can more accurately assess practices, services, and products that their customers find appealing. The Handbook of Research on Intelligent Techniques and Modeling Applications in Marketing Analytics features innovative research and implementation practices of analytics in marketing research. Highlighting various techniques in acquiring and deciphering marketing data, this publication is a pivotal reference for professionals, managers, market researchers, and practitioners interested in the observation and utilization of data on marketing trends to promote positive business practices.

Although recommendation systems have become a vital research area in the fields of cognitive science, approximation theory, information retrieval and management sciences, they still require improvements to make recommendation methods more effective and intelligent. Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods is a comprehensive collection of research on the latest advancements of intelligence techniques and their application to recommendation systems and how this could improve this field of study.

"This book focuses on environment information scanning and organization-wide support for strategic intelligence. It also provides practical guidance to organizations for developing effective approaches, mechanisms, and systems to scan, refine, and support strategic information provision"--Provided by publisher.

Computational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and much more. The concepts of expert systems, case-based reasoning, fuzzy logic, genetic algorithms, swarm computing, and rough sets are introduced with their applications in software engineering. The field of knowledge discovery is explored using neural networks and data mining techniques by determining the underlying and hidden patterns in software data sets. Aimed at graduate students and researchers in computer science engineering, software engineering, information technology, this book: Covers various aspects of in-depth solutions of software engineering problems using computational intelligence techniques Discusses the latest evolutionary approaches to preliminary theory of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to provide better and optimized solutions Illustrates applications including software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, and more Highlights swarm intelligence-based optimization solutions for software testing and reliability problems

Artificial Intelligence Techniques in IoT Sensor Networks is a technical book which can be read by researchers, academicians, students and professionals interested in artificial intelligence (AI), sensor networks and Internet of Things (IoT). This book is intended to develop a shared understanding of applications of AI techniques in the present and near term. The book maps the technical impacts of AI technologies, applications and their implications on the design of solutions for sensor networks. This text introduces researchers and aspiring academicians to the latest developments and trends in AI applications for sensor networks in a clear and well-organized manner. It is mainly useful for research scholars in sensor networks and AI techniques. In addition, professionals and practitioners working on the design of real-time applications for sensor networks may benefit directly from this book. Moreover, graduate and master’s students of any departments related to AI, IoT and sensor networks can find this book fascinating for developing expert systems or real-time applications. This book is written in a simple and easy language, discussing the fundamentals, which relieves the requirement of having early backgrounds in the field. From this expectation and experience, many libraries will be interested in owning copies of this work.

Augmented intelligence is an alternate approach of artificial intelligence (AI), which emphasizes AI’s assistive role. Augmented intelligence enhances human skills of reasoning in a robotic system or software by simulating expectancy, educational mining, problem solving, recollection, sequencing, and decision-making capabilities. It is based on a combination of techniques such as machine learning, deep learning and cognitive computing. This book explains artificial intelligence models that support assistive processes in different situations. The contributors aim to provide information to a diverse audience with groundbreaking developments in mathematical computing. The book presents 8 chapters on these topics: - Educational data mining in augmented reality virtual learning environment - Brain and computer interfaces - Tree-based tools for chemometric analysis of infrared spectra - Applications of deep learning in medical engineering - Bankruptcy prediction model using an enhanced boosting classifier - Reputation systems for mobile agent security - The crow search algorithm - COVID-19 diagnosis and treatment The contents attempt to integrate various facets of augmented Intelligence, by describing recent research developments and advanced topics of interest to academicians and researchers working on machine learning problems and AI.

President Putin’s explicit declaration that the country that makes progress in artificial intelligence will rule the world has launched a new race for dominance. In this era of cognitive competition and total automation, every country understands that it must rapidly adopt AI or go bust. To stay competitive a country must have a strategy. But how should a government proceed? What areas it must focus on? Where should it even start? This book provides answers to these important, yet pertinent, questions and more. Presenting the viewpoints of global experts and thought leaders on key issues relating to AI and government policies, this book directs us to the future.

New Directions in the Future of Work explores vital research and industrial issues that are central to understanding the concepts of the Future of Work and address key challenges in this evolving area of debate.

This is an open access book. As the process of social modernization continues to advance, people realize that the key to social modernization is the modernization of people, and the modernization of people is inseparable from the modernization of education. It can be seen that education modernization is the foundation of social modernization. Education modernization is an important reform direction of education development, including modernization of education concept, modernization of education content, modernization of education equipment, modernization of teachers and modernization of education management. And information management is one of the important methods to realize education modernization Information management is the social activity of planning, organizing, leading and controlling information resources by means of modern information technology in order to effectively develop and utilize information resources. Simply put, information management is the management of information resources and information activities by human beings. Information management is a general term for the information that people collect, process and input and output in the whole management process. The process of information management includes information collection, information transmission, information processing and information storage. Using the new generation of information management technology to enhance the digitalization, networking and intelligence of education management, promote the transformation of education decision-making from experience-driven to data-driven, education management from one-way management to collaborative governance, education service from passive response to active service, and support the modernization of education governance system and governance capacity with information technology. Focusing on education and information management with modernization, this conference provides a platform for scholars in related fields to exchange and share information, discuss how the two affect each other, and: Promote the modernization of education by studying certain educational issues that exist. Open up new perspectives, broaden horizons, and examine the issues under discussion by participants. Create a forum for sharing, research and exchange at an international level, where participants will be informed of the latest research directions, results and content in different fields, thus inspiring them to come up with new research ideas. For those who cannot attend the conference, papers in the social sciences and humanities will be accepted and published in the form of conference proceedings.