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This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: • Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; • Using learning analytics to predict student performance; • Using learning analytics to create learning materials and educational courses; and • Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.
Praise for the Series:"This book will be a useful reference to control engineers and researchers. The papers contained cover well the recent advances in the field of modern control theory."--IEEE Group Correspondence"This book will help all those researchers who valiantly try to keep abreast of what is new in the theory and practice of optimal control."--Control
The combination of different intelligent methods is a very active research area in Artificial Intelligence (AI). The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing efforts combine soft computing methods either among themselves or with more traditional AI methods such as logic and rules. Another stream of efforts integrates machine learning with soft-computing or traditional AI methods. Yet another integrates agent-based approaches with logic and also non-symbolic approaches. Some of the combinations have been quite important and more extensively used, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-ba...
Mechatronic design processes have become shorter and more parallelized, induced by growing time-to-market pressure. Methods that enable quantitative analysis in early design stages are required, should dependability analyses aim to influence the design. Due to the limited amount of data in this phase, the level of uncertainty is high and explicit modeling of these uncertainties becomes necessary. This work introduces new uncertainty-preserving dependability methods for early design stages. These include the propagation of uncertainty through dependability models, the activation of data from similar components for analyses and the integration of uncertain dependability predictions into an optimization framework. It is shown that Dempster-Shafer theory can be an alternative to probability theory in early design stage dependability predictions. Expert estimates can be represented, input uncertainty is propagated through the system and prediction uncertainty can be measured and interpreted. The resulting coherent methodology can be applied to represent the uncertainty in dependability models.
The three volume set LNAI 4251, LNAI 4252, and LNAI 4253 constitutes the refereed proceedings of the 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006, held in Bournemouth, UK in October 2006. The 480 revised papers presented were carefully reviewed and selected from about 1400 submissions. The papers present a wealth of original research results from the field of intelligent information processing.
This volume consists of the papers presented at the 6th International Workshop on Scattering Theory and Biomedical Engineering. Organized every two years, this workshop provides an overview of the hot topics in scattering theory and biomedical technology, and brings together young researchers and senior scientists, creating a forum for the exchange of new scientific ideas. At the sixth meeting, all the invited speakers, who are recognized as being eminent in their field and, more important, as being stimulating speakers, presented their latest achievements. The proceedings have been selected for coverage in: . OCo Index to Scientific & Technical Proceedings- (ISTP- / ISI Proceedings). OCo In...
This book examines the conflicts arising from the implementation of privacy principles enshrined in the GDPR, and most particularly of the ``Right to be Forgotten'', on a wide range of contemporary organizational processes, business practices, and emerging computing platforms and decentralized technologies. Among others, we study two ground-breaking innovations of our distributed era: the ubiquitous mobile computing and the decentralized p2p networks such as the blockchain and the IPFS, and we explore their risks to privacy in relation to the principles stipulated by the GDPR. In that context, we identify major inconsistencies between these state-of-the-art technologies with the GDPR and we propose efficient solutions to mitigate their conflicts while safeguarding the privacy and data protection rights. Last but not least, we analyse the security and privacy challenges arising from the COVID-19 pandemic during which digital technologies are extensively utilized to surveil people’s lives.
The main aim of this research book is to report a sample of the most recent advances in the field of intelligent interactive systems in knowledge-based environment. The contents of this book include: Introduction to intelligent interactive systems Affective bi-modal intelligent tutoring system Estimation of development costs in intelligent systems Narrative interactive learning Knowledge acquisition for configurable products and services Interaction modalities in mobile contexts Face images classification for human-computer interactions Users modelling for distance learning Group adaptation and group modelling A personalized news aggregator on the web. This book would prove useful to the researchers, professors, research students and practitioners as it reports novel research work on innovative topics in the area of intelligent interactive systems.
This book constitutes the refereed proceedings of the Second Hellenic Conference on Artificial Intelligence, SETN 2002, held in Thessaloniki, Greece, in April 2002. The 42 revised full papers presented together with two invited contributions were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on knowledge representation and reasoning, logic programming and constraint satisfaction, planning and scheduling, natural language processing, human-computer interaction, machine learning, intelligent Internet and multiagent systems, and intelligent applications.
This book constitutes the refereed proceedings of the 11th International Conference on User Modeling, UM 2007, held in Corfu, Greece in July 2007. Coverage includes evaluating user/student modeling techniques, data mining and machine learning for user modeling, user adaptation and usability, modeling affect and meta-cognition, as well as intelligent information retrieval, information filtering and content personalization.