The Ambient Intelligent Classroom, Matthew Montebello
Автор: Judea Pearl Название: Probabilistic Reasoning in Intelligent Systems, ISBN: 1558604790 ISBN-13(EAN): 9781558604797 Издательство: Elsevier Science Рейтинг: Цена: 9599.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic.
The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information.
Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Описание: This book presents recent research in intelligent information and database systems. The carefully selected contributions were initially accepted for presentation as posters at the 9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017) held from to 5 April 2017 in Kanazawa, Japan. While the contributions are of an advanced scientific level, several are accessible for non-expert readers.
The book brings together 47 chapters divided into six main parts:* Part I. From Machine Learning to Data Mining.* Part II. Big Data and Collaborative Decision Support Systems,* Part III.
Computer Vision Analysis, Detection, Tracking and Recognition,* Part IV. Data-Intensive Text Processing,* Part V. Innovations in Web and Internet Technologies, and* Part VI.
New Methods and Applications in Information and Software Engineering. The book is an excellent resource for researchers and those working in algorithmics, artificial and computational intelligence, collaborative systems, decision management and support systems, natural language processing, image and text processing, Internet technologies, and information and software engineering, as well as for students interested in such research areas.
Автор: Sabu M. Thampi; Sushmita Mitra; Jayanta Mukhopadhy Название: Intelligent Systems Technologies and Applications ISBN: 3319683845 ISBN-13(EAN): 9783319683843 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed post-conference proceedings of the third International Symposium on Intelligent Systems Technologies and Applications (ISTA`17), September 13-16, 2017, Manipal, Karnataka, India. This proceedings contains 34 papers selected for presentation at the Symposium.
1 Introduction.- 1.1 Introduction.- 1.2 Teacher-Centred Pedagogy.- 1.3 Student-Centred and Reflexive Methodologies.- 1.4 Learning Modalities and Affordances.- 1.5 Conclusion.- References.- 2 Ambient Intelligence.- 2.1 Introduction.- 2.2 Historical Background.- 2.2.1 Ubiquitous and Pervasive.- 2.2.2 Internet of Things.- 2.2.3 Smart and Calm Computing.- 2.3 Enabling Technologies.- 2.3.1 Techniques.- 2.3.2 Sensors.- 2.3.3 Setups.- 2.4 AmI in Action.- 2.4.1 Assisted Living.- 2.4.2 Transportation.- 2.4.3 Civic Environments.- 2.5 Case for the Classroom.- 2.5.1 Social Dimension.- 2.5.2 Technological Dimension.- 2.5.3 Educational Dimension.- 2.6 Conclusion.- References.- 3 Social Aspect.- 3.1 Introduction.- 3.2 Human Aspect of a Classroom.- 3.2.1 Multidimensionality.- 3.2.2 Simultaneity.- 3.2.3 Immediacy.- 3.2.4 Unpredictability.- 3.2.5 Publicness.- 3.2.6 History.- 3.3 Connectivism Learning Theory.- 3.4 Related Work .- 3.5 Implications to the AmI Classroom.- 3.6 Conclusion.- References.- 4 Technological Aspect.- 4.1 Introduction.- 4.2 Technology in Education.- 4.3 Adaptive Learning Theory.- 4.4 Related Work.- 4.4.1 The 'Intelligent Classroom'.- 4.4.2 iClass.- 4.4.3 ClassMATE.- 4.5 Implications to the AmI Classroom.- 4.5.1 Unobtrusive Hardware.- 4.5.2 Seamless Communication Infrastructure.- 4.5.3 Distributed Device Network.- 4.5.4 Intuitive User Interface.- 4.5.5 Dependable and Secure.- 4.5.6 Learner Profile and the Educator.- 4.5.7 Compatibility and Scope.- 4.5.8 Fruitfulness and Role.- 4.5.9 Student Outcome and Clarity.- 4.6 Conclusion.- References.- 5 Educational Aspect.- 5.1 Introduction.- 5.2 Learning Models.- 5.2.1 New Learning Affordances.- 5.2.2 Modalities and Spaces within a School Environment.- 5.2.3 Merging Models.- 5.3 Personal Learning Environment.- 5.3.1 Personal Learning Network.- 5.3.2 Personal Learning Portfolio.- 5.3.3 Ambient Intelligent PLE.- 5.4 Related Work.- 5.4.1 Psychological Type Model.- 5.4.2 Learner Type Model.- 5.4.3 Experiential Type Model.- 5.4.4 Personality Type Model.- 5.4.5 Experiences Type Model.- 5.5 Implications to the AmI Classroom.- 5.6 Conclusion.- References.- 6 The Ambient Intelligent Classroom.- 6.1 Introduction.- 6.2 Background Rationale.- 6.2.1 Scenario Description.- 6.2.2 Virtual Space.- 6.2.3 Physical Space.- 6.2.4 Converging Technologies .- 6.3 Architectural Design.- 6.3.1 AmI-PLE.- 6.3.2 Smart Classroom.- 6.3.3 Combined Educational Environment.- 6.4 Implementation Details.- 6.4.1 Software Development.- 6.4.2 Classroom Setup.- 6.4.3 Interoperability Affairs.- 6.5 Empirical Testing.- 6.5.1 The Human Aspect.- 6.5.2 The Software Aspect.- 6.5.3 The Physical Aspect.- 6.6 Conclusion.- References.- 7 Future Directions.- 7.1 Introduction.- 7.2 Learning 4.0.- 7.2.1 Complete Automation.- 7.2.2 Global Knowledge.- 7.2.3 Assessment Repurposed.- 7.3 Evolving Educator.- 7.3.1 Digital Educator.- 7.3.2 Social Advocate.- 7.3.3 LifeLong Learner.- 7.4 Digital Learners.- 7.4.1 Technology Adopter.- 7.4.2 Social Player.- 7.4.3 New Skills Assessed.- 7.5 Education Environments.- 7.5.1 AI Enabled.- 7.5.2 Authenticating Sources.- 7.5.3 Holistic Skills.- 7.6 Conclusion.- References.- Glossary.- References.
Автор: Wim Verhaegh; Emile Aarts; Jan Korst Название: Intelligent Algorithms in Ambient and Biomedical Computing ISBN: 9400787286 ISBN-13(EAN): 9789400787285 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The rapid growth in electronic systems in the past decade has boosted - search in the area of computational intelligence. As it has become increasingly easy to generate, collect, transport, process, and store huge amounts of data, the role of intelligent algorithms has become prominent in order to visualize, manipulate, retrieve, and interpret the data. For instance, intelligent search techniques have been developed to search for relevant items in huge coll- tions of web pages, and data mining and interpretation techniques play a very important role in making sense out of huge amounts of biomolecular measu- ments. As a result, the added value of many modern systems is no longer determined by hardware only, but increasingly by the intelligent software that supports and facilitates the user in realizing his or her objectives. Overthepastyears, considerableprogresshasbeenmadeintheareaofc- putational intelligence, which can be positioned at the intersection of computer science, discrete mathematics, and cognitive science. This has led to a gr- ing community of practitioners within Philips Research that develop, analyze, and apply intelligent algorithms. The Symposium on Intelligent Algorithms (SOIA) intends to provide this community of practitioners with a platform to exchange information. The ?rst edition of SOIA, held in 2002, addressed the topic of intelligent algorithms in ambient intelligence.
Автор: Kiran Kumar Ravulakollu; Mohammad Ayoub Khan; Ajit Название: Trends in Ambient Intelligent Systems ISBN: 3319301829 ISBN-13(EAN): 9783319301822 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book demonstratesthe success of Ambient Intelligence in providing possible solutions for the dailyneeds of humans.
Electric vehicles are changing transportation dramatically and this unique book merges the many disciplines that contribute research to make EV possible, so the reader is informed about all the underlying science and technologies driving the change.
An emission-free mobility system is the only way to save the world from the greenhouse effect and other ecological issues. This belief has led to a tremendous growth in the demand for electric vehicles (EV) and hybrid electric vehicles (HEV), which are predicted to have a promising future based on the goals fixed by the European Commission's Horizon 2020 program.
This book brings together the research that has been carried out in the EV/HEV sector and the leading role of advanced optimization techniques with artificial intelligence (AI). This is achieved by compiling the findings of various studies in the electrical, electronics, computer, and mechanical domains for the EV/HEV system. In addition to acting as a hub for information on these research findings, the book also addresses the challenges in the EV/HEV sector and provides proven solutions that involve the most promising AI techniques. Since the commercialization of EVs/HEVs still remains a challenge in industries in terms of performance and cost, these are the two tradeoffs which need to be researched in order to arrive at an optimal solution. Therefore, this book focuses on the convergence of various technologies involved in EVs/HEVs. Since all countries will gradually shift from conventional internal combustion (IC) engine-based vehicles to EVs/HEVs in the near future, it also serves as a useful reliable resource for multidisciplinary researchers and industry teams.
Описание: This book provides a practical guide to applying soft-computing methods to interpret geophysical data. It discusses the design of neural networks with Matlab for geophysical data, as well as fuzzy logic and neuro-fuzzy concepts and their applications. In addition, it describes genetic algorithms for the automatic and/or intelligent processing and interpretation of geophysical data.
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