Current directory

Advances in Virtual Reality for Eating Disorders and Obesity

Abstract

Introduction

Information and Communication Technology Applications for the Eating Disorder and Obesity Fields

The Use of VR in the Treatment of ED and Obesity

Body Image Treatment by Means of VR

Normalization of the Eating Pattern by Means of VR

Conclusion

Acknowledgments

References

Interactive Games Set with the Movement Sensor Kinect® as a Tool for Cerebral Palsy Rehabilitation

Abstract

Introduction

Materials and Method

Virtual Reality: Possibilities and Limitations for Cerebral Palsy Rehabilitation

Kinect®

The Movement Sensor Kinect® as a Tool for Cerebral Palsy Rehabilitation

The Effects of an Intervention Based on the Interactive Game Set with the Movement Sensor Kinect®

Conclusion

References

On the Use of Virtual Reality in Sport and Exercise: Applications and Research Findings

Abstract

Introduction

Defining Virtual Reality in Sport and Exercise

Virtual Reality Systems in Sport and Exercise

Effects of Virtual Reality on Sport and Exercise Outcomes

Variables That Influence the Effects of Virtual Reality on Sport and Exercise Outcomes

Theoretical Approaches to Understanding Virtual Reality in Sport and Exercise

Future Research Directions

Conclusion

References

Deep Learning Using Unconventional Paradigms

Abstract

Introduction

Deep Learning Approaches

Traditional Deep Architecture-Based Approaches

Convolutional Deep Belief Networks (CDBN)

Deep Kernel Machine (DKM)

Deep Coding Network

Deep Stacking Networks

Spike-and-Slab RBM (ssRBM)

Machine-Learning-Based Deep Learning Approaches

Deep Q-Networks (DQN)

Deep Support Vector Machines

Evolutionary Computation-Based Deep Learning

Deep Learning Using Genetic Algorithm

Genetic Algorithm-Assisted Deep Learning

Neuroevolution for Deep Learning

What’s Next

References

Deep Learning in Open Source Learning Streams

Abstract

1. Introduction

2. Context of the Research

2.1. Defining an Open Source Learning Stream

2.2. Philosophy of Science

3. Methodology

4. Data Analysis

5. Findings

5.1. Deep Learning and Distributed Cognition

5.2. Discussion of Findings

Conclusion

References

Applying Artificial Neural Networks to Deep Learning and Predictive Analysis in Semantic TCM Telemedicine Systems

Abstract

1. Introduction

2. The Knowledge Consultation

3. Major Aspects of the Ontology-Based TCM Telemedicine System

3.1. Ontology Modelling

3.2. Ontology Implementation Tool

3.3. Internet Capability

3.4. Cross-Layer Logical Transitivity

3.5. Automatic System Generation

3.6. Pervasive Support

3.7. Ontology Evolution Approach

4. Overview of the Ontology-Based Automatic System Generation (ASG/C)

5. Deep Learning and Predictive Analysis

Conclusion

References