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ED-WAVE is an electronic learning tool created under the Asia-Link Programme, a programme dedicated to the promotion of regional and multilateral networking between higher education institutions in European Union (EU) member states and South-East Asia and China. ED-WAVE has been developed by a consortium of three Asian and three European universities. It is an innovative product of high interdisciplinary action providing theoretical information, worked out examples, computer graphics, case study database and case base reasoning in the field of wastewater treatment and water reclamation. ED-WAVE aims also to provide a sustainable platform for ongoing learning on technologies improving water quality and efficiency by exposing the target groups to real-life applications through virtual industrial and municipal environments. The target groups involve students at undergraduate and graduate level, educators and young professionals working hi water and related industries. The tool is going to be used in select courses in each institution as part of curriculum development. [ABSTRACT FROM AUTHOR]

Introduction: Around 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected early enough. Vision screening in childhood is an evidence-based and cost-effective way to detect visual disorders. However, current screening programmes face several limitations: training required to perform them efficiently, lack of accurate screening tools and poor collaboration from young children.Some of these limitations can be overcome by new digital tools. Implementing a system based on artificial intelligence systems avoid the challenge of interpreting visual outcomes.The objective of the TrackAI Project is to develop a system to identify children with visual disorders. The system will have two main components: a novel visual test implemented in a digital device, DIVE (Device for an Integral Visual Examination); and artificial intelligence algorithms that will run on a smartphone to analyse automatically the visual data gathered by DIVE., Methods and Analysis: This is a multicentre study, with at least five centres located in five geographically diverse study sites participating in the recruitment, covering Europe, USA and Asia.The study will include children aged between 6 months and 14 years, both with normal or abnormal visual development.The project will be divided in two consecutive phases: design and training of an artificial intelligence (AI) algorithm to identify visual problems, and system development and validation. The study protocol will consist of a comprehensive ophthalmological examination, performed by an experienced paediatric ophthalmologist, and an exam of the visual function using a DIVE.For the first part of the study, diagnostic labels will be given to each DIVE exam to train the neural network. For the validation, diagnosis provided by ophthalmologists will be compared with AI system outcomes., Ethics and Dissemination: The study will be conducted in accordance with the principles of Good Clinical Practice. This protocol was approved by the Clinical Research Ethics Committee of Aragón, CEICA, on January 2019 (Code PI18/346).Results will be published in peer-reviewed journals and disseminated in scientific meetings., Trial Registration Number: ISRCTN17316993., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)