This special compendium provides a concise and unified vision of facial image processing. It addresses a collection of state-of-the-art techniques, covering the most important areas for facial biometrics and behavior analysis. These techniques also converge to serve an emerging practical application of interactive distance learning.Readers will get a broad picture of the fundamental science of the field and technical details that make the research interesting. Moreover, the intellectual investigation motivated by the demand of real-life application will make this volume an inspiring read for current and prospective researchers and engineers in the fields of computer vision, machine learning and image processing.

"This book seeks to examine the efforts made to bridge the gap between student and educator with computer applications through an in-depth discussion of applications employed to overcome the problems encountered during educational processes"--Provided by publisher.

"This comprehensive, six-volume collection addresses all aspects of online and distance learning, including information communication technologies applied to education, virtual classrooms, pedagogical systems, Web-based learning, library information systems, virtual universities, and more. It enables libraries to provide a foundational reference to meet the information needs of researchers, educators, practitioners, administrators, and other stakeholders in online and distance learning"--Provided by publisher.

This special compendium provides a concise and unified vision of facial image processing. It addresses a collection of state-of-the-art techniques, covering the most important areas for facial biometrics and behavior analysis. These techniques also converge to serve an emerging practical application of interactive distance learning. Readers will get a broad picture of the fundamental science of the field and technical details that make the research interesting. Moreover, the intellectual investigation motivated by the demand of real-life application will make this volume an inspiring read for current and prospective researchers and engineers in the fields of computer vision, machine learning and image processing.

This book addresses main issues concerned with the future learning, learning and academic analytics, virtual world and smart user interface, and mobile learning. This book gathers the newest research results of smart learning environments from the aspects of learning, pedagogies, and technologies in learning. It examines the advances in technology development and changes in the field of education that has been affecting and reshaping the learning environment. Then, it proposes that under the changed technological situations, smart learning systems, no matter what platforms (i.e., personal computers, smart phones, and tablets) they are running at, should be aware of the preferences and needs that their users (i.e., the learners and teachers) have, be capable of providing their users with the most appropriate services, helps to enhance the users' learning experiences, and to make the learning efficient.

As digital transformation becomes increasingly central to effective corporate strategy, today’s students must understand information systems’ role as the backbone to all organizations. Known for its rich Canadian content and focus on active learning, Introduction to Information Systems, Fifth Canadian Edition shows students how they can use IS to help their employers increase profitability, improve customer service, manage daily operations, and drive impact in their markets. The popular What’s in IT for Me framework empowers students in accounting, finance, marketing, human resources, production/operations management, and management information systems (MIS) to connect their majors to specific IT topics demonstrate value in the organizations they join.

This book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications. This book represents a guideline for building a data analysis workflow from scratch. Each chapter presents a step of the entire workflow, starting from an available dataset and continuing with building interpretable models, enhancing models, and tackling aspects of evaluating engagement and usability. The related work shows that many papers have focused on machine learning usage and advancement within e-learning systems. However, limited discussions have been found on presenting a detailed complete roadmap from the raw dataset up to the engagement and usability issues. Practical examples and guidelines are provided for designing and implementing new algorithms that address specific problems or functionalities. This roadmap represents a potential resource for various advances of researchers and practitioners in educational data mining and learning analytics.