Augmented Reality in Education [[electronic resource] ] : A New Technology for Teaching and Learning / / edited by Vladimir Geroimenko

• Record Nr.: UNISA996465343403316
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
• ISBN: 3-030-42156-2
• Edizione: [1st ed. 2020.]
• Descrizione fisica: 1 online resource (422 pages)
• Collana: Springer Series on Cultural Computing, , 2195-9056
• Disciplina: 371.33468
• Soggetti: User interfaces (Computer systems); Educational technology; Education—Data processing; Special purpose computers; User Interfaces and Human Computer Interaction; Technology and Digital Education; Computers and Education; Special Purpose and Application-Based Systems
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Part 1: General Aspects of Educational Augmented Reality -- Augmented Reality in Education: Current Status and Advancement of the Field -- Designing Augmented Reality Applications as Learning Activity -- An Online Platform for Enhancing Learning Experiences with Web-based Augmented Reality and Pictorial Bar Code -- The Concept of ‘Bringing Your Own Device’ in Scaffolded and Augmented Education -- The FeDiNAR Project: Using Augmented Reality to Turn Mistakes into Learning Opportunities -- Choral Konsult: Augmented Reality for Electrate Learning -- Part II: Augmented Reality in Teaching Medicine and Science -- Augmented Reality in Medical Education and Training: From Physicians to Patients -- The Usage of Augmented Reality in Dental Education -- The Development of Augmented Reality Applications for Chemistry Learning -- Mixed Reality Books: Applying Augmented and Virtual Reality in Mining Engineering Education -- Part ; III: Educational Augmented Reality in Humanities and Art -- Beyond Historical Books, Names and Dates: Leveraging Augmented Reality to Promote Knowledge, Reasoning and Emotional Engagement -- Design and Implementation of Augmented Reality for English Language Education -- Iberian Cultures and Augmented Reality: Studies in Elementary School Education and Initial Teacher Training -- The Educational Use of the ‘Harry Potter: Wizards Unite’ Augmented Reality Application -- Making Inside the Augment: Augmented Reality and Art/Design Education -- The ‘Romantic App’: Augmented Reality in Fine Art Education -- Part IV: Augmented Reality in Environmental and Special Education -- Augmented Reality for Outdoor Environmental Education -- Augmented Reality in Environmental Humanities Education -- Interacting Across Contexts: Augmented Reality Applications for Developing the Understanding of the Anthropocene -- Alaskan Timeosaurs and Interplanetary Human Spaghetti: A Regional Look at Augmented Reality in Special Classrooms -- Concluding Remarks.
• Sommario/riassunto: This is the first comprehensive research monograph devoted to the use of augmented reality in education. It is written by a team of 58 world-leading researchers, practitioners and artists from 15 countries, pioneering in employing augmented reality as a new teaching and learning technology and tool. The authors explore the state of the art in educational augmented reality and its usage in a large variety of particular areas, such as medical education and training, English language education, chemistry learning, environmental and special education, dental training, mining engineering teaching, historical and fine art education. Augmented Reality in Education: A New Technology for Teaching and Learning is essential reading not only for educators of all types and levels, educational researchers and technology developers, but also for students (both graduates and undergraduates) and anyone who is interested in the educational use of emerging augmented reality technology.

Artificial Intelligence : First International Conference, AI4S 2023, Pune, India, September 4-5, 2023, Proceedings

• Record Nr.: UNISA996565862603316
• Autore: Tiwari Sanju
• Pubbl/distr/stampa: Cham : , : Springer International Publishing AG, , 2023; ©2023
• ISBN: 3-031-47997-1
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (234 pages)
• Collana: Communications in Computer and Information Science Series ; ; v.1907
• Altri autori (Persone): Ortiz-RodríguezFernando; MishraSashikala; VakajEdlira; KotechaKetan
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Preface -- Organization -- Keynote Abstracts -- Data Analytics for Sustainable Global Supply Chains -- Building Trustworthy Neuro-Symbolic AI Systems with Explainability and Safety: Knowledge is the Key -- Contents -- An Approach Towards Mitigation of Renewable Energy Curtailment -- 1 Introduction -- 2 Test Case Modifications and Assumptions -- 2.1 Test Case and Modifications -- 2.2 Assumptions -- 3 Solution Methodologies and Cases -- 3.1 Solution Methodology -- 3.2 Configuration of Cases -- 4 Results and Discussion -- 4.1 Results -- 4.2 Discussion -- 5 Conclusion and Future Scope -- References -- ESG and IoT: Ensuring Sustainability and Social Responsibility in the Digital Age -- 1 Introduction -- 2 Overview of ESG and Sustainability -- 2.1 Environmental, Social and Governance Impacts of IoT -- 2.2 The Contribution of Artificial Intelligence to ESG -- 2.3 Industry 4.0 and Its Potential Impact on ESG -- 3 Proposed Approach -- 3.1 Proposed Architecture -- 3.2 SAS® Intelligent Monitoring: Product Overview -- 4 Possible Applications -- 5 Future Work -- 6 Conclusion -- References -- AI and Assistive Technologies for Persons with Disabilities - Worldwide Trends in the Scientific Production Using Bibliometrix R Tool -- 1 Introduction ; -- 1.1 Background -- 1.2 Problem Statement -- 2 Methodology -- 2.1 Data Collection -- 2.2 Analysis -- 3 Results and Discussion -- 3.1 Production -- 3.2 Sources -- 3.3 Authors -- 3.4 Documents -- 4 Conclusion -- 4.1 Limitations and Future Research Directions -- Appendix A: -- References -- Leaf Disease Detection Using Transfer Learning -- 1 Introduction -- 2 Related Work -- 3 Model Architecture and Design -- 3.1 ResNet -- 3.2 MobileNet -- 3.3 VGG16 -- 3.4 Design Consideration -- 4 Dataset Preparation and Training -- 4.1 Kaggle Dataset: Potato, Tomato, and Pepper Black Diseases -- 4.2 Training the Models.; 5 Results -- 5.1 VGG16 Model -- 5.2 ResNet Model -- 5.3 MobileNet Model -- 5.4 Performance Comparison -- 6 Conclusion -- References -- Automated Scene Recognition for Environmental Monitoring: A Cluster Analysis Approach using Intel Image Classification Dataset -- 1 Introduction -- 2 Literature Review -- 3 Data Preprocessing and EDA -- 3.1 About the Dataset -- 3.2 Data Transformation -- 3.3 Dimensionality Reduction with PCA for Improved Clustering Efficiency -- 4 Clustering Methods for Scene Recognition -- 4.1 K Means Clustering Technique -- 4.2 Agglomerative Clustering -- 4.3 BIRCH (Balanced Iterative Reducing and Clustering Using Hierarchies) -- 4.4 DBSCAN (Density Based Spatial Clustering of Applications with Noise) -- 4.5 Spectral -- 5 Evaluation of Clustering Algorithms -- 5.1 Silhouette Score -- 5.2 Davis-Bouldin Score -- 5.3 Calinski-Harabasz Score -- 6 Conclusion and Future Scope -- References -- Unveiling the Potentials of Deep Learning Techniques for Accurate Alzheimer's Disease Neuro Image Classification -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 The Proposed Bi-LSTM-AJSO Model Development -- 5 Experimentation -- 5.1 Datasets Used and Model Training and Testing -- 5.2 Comparison with Other Machine and Deep Learning Approaches -- 5.3 Execution Time Comparisons -- 5.4 Interpretability Analysis and Significance -- 6 Conclusion and Future Directions -- References -- Food Composition Knowledge Extraction from Scientific Literature -- 1 Introduction -- 2 Food Composition Knowledge -- 3 Food Composition Knowledge Extraction from Scientific Papers -- 3.1 Knowledge Sources -- 3.2 Knowledge Extraction -- 4 Knowledge Validation -- 4.1 Matching to Existing Vocabularies -- 5 Conclusion -- References -- Design and Analysis of an Algorithm Based on Biometric Block Chain for Efficient data sharing in VANET -- 1 Introduction.; 2 Literature Review -- 3 Proposed Work -- 4 Experimental Result -- 5 Conclusion -- References -- An Improved Deep Learning Model Implementation for Pest Species Detection -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Deep Learning -- 3.3 Data Augmentation -- 3.4 Model Architecture -- 3.5 Classification -- 4 Results -- 5 Conclusion -- References -- Identification of Diseases Affecting Mango Leaves Using Deep Learning Models -- 1 Introduction -- 2 Literature Survey -- 2.1 Disease Affecting Mango Leaves -- 2.2 Factor Influencing Fungal Diseases -- 3 Dataset Description -- 4 Methodology -- 4.1 Feature Extraction -- 4.2 Classification -- 4.3 Model Evaluation -- 4.4 Prediction -- 5 Results and Discussion -- 6 Conclusion -- References -- RWNR: Radial Basis Feed Forward Neural Network Driven Semantically Inclined Strategy for Web 3.0 Compliant News Recommendation -- 1 Introduction -- 2 Related Works -- 3 Proposed Architecture -- 4 Implementation -- 5 Results and Performance Evaluation -- 6 Conclusion -- References -- WDNRegClass - A Hybrid ANN + Bayesian Learning Model to Reduce Temporal Predictive In-Variance Towards Mitigation of WDN Revenue Losses -- 1 Introduction -- 2 Literature Study -- 2.1 Leak Identification ; Using Hydraulic Model Parameters: -- 2.2 Data-Driven Approaches with Sequential or Temporal Data: -- 2.3 The Integration of Bayesian Belief Propagation: -- 3 Proposed Work -- 4 Result and Discussion -- 5 Conclusion -- References -- Real-Time Birds Shadow Detection for Autonomous UAVs -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Acquiring a Sample Dataset -- 3.2 Shadow Generation -- 3.3 Data Cleaning -- 3.4 Post-processing -- 3.5 Detection Model Training -- 4 Results and Discussion -- 5 Conclusion -- References.; Knowledge Graph for Fraud Detection: Case of Fraudulent Transactions Detection in Kenyan SACCOs -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 4 Results -- 4.1 Sample Fraudulent Funds Movement Detection -- 5 Conclusion and Future Work -- References -- Conceptual Framework for Representing Knowledge in the Energy Sector -- 1 Introduction -- 2 State of the Art -- 3 Methodology for Semantic Data Model Design and Construction -- 3.1 Step 1: Ontology Requirements Specification -- 3.2 Step 2: Ontology Analysis -- 3.3 Step 3: Overview of Ontological Modules -- 3.4 Step 4: Interaction with Stakeholders and Ontology Formalization -- 4 Overview of Main Pilots' Topics -- 5 Methodology Application -- 5.1 Application of Step 1 - Ontology Requirements Specification -- 5.2 Application of Step 2 - Ontology Analysis -- 5.3 Application of Step 3 - Overview of Ontological Model -- 5.4 Application of Step 4 - Formalization of Semantic Data Models -- 5.5 Use Case Instantiation with an Illustrative Example -- 6 Discussion -- 7 Conclusion -- References -- Semantic Carbon Footprint of Food Supply Chain Management -- 1 Introduction -- 2 Ontology Methodology -- 2.1 Ontology Requirements Specification -- 2.2 Competency Questions -- 2.3 Users -- 2.4 Intended Use -- 3 Ontology Design -- 3.1 Data Sources -- 3.2 Evaluation -- 4 Conclusion -- References -- Author Index.