Real-World Applications

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1. Diet/ Healthcare/ Travel

(1) Adaptive personalized diet linguistic recommendation mechanism based on type-2 fuzzy sets and genetic fuzzy markup language, IEEE Trans. on Fuzzy Systems, vol. 23, no. 5, pp. 1777-1802, 2015.

(2) Healthy diet assessment mechanism based on fuzzy markup language for Japanese food, Soft Computing, vol. 20, no 1, pp 359-376, 2016.

(3) A novel genetic fuzzy markup language and its application to healthy diet assessment, International Journal of Uncertainty, Fuzziness, and Knowledge-Based Systems, vol. 20, no. 2, pp. 247-278, 2012.

(4) Evaluating cardiac health through semantic soft computing techniques, Soft Computing, vol.16, no. 7, pp. 1165-1181, 2012.

(5) Diet assessment based on type-2 fuzzy ontology and fuzzy markup language, International Journal of Intelligent System, vol. 25, no. 12, pp. 1187-1216, 2010.

(6) Ontology-based multi-agents for intelligent healthcare applications, Journal of Ambient Intelligence and Humanized Computing, vol. 1, no. 2, pp. 111-131, 2010.

2. E-Learning/ Education/ IRT/ Ontology Construction

(1) Performance Verification Mechanism for Adaptive Assessment e-Platform and e-Navigation Application, International Journal of e-Navigation and Maritime Economy, vol. 2, pp. 47-62, 2015.

(2) T2FS-based adaptive linguistic assessment system for semantic analysis and human performance evaluation on game of Go, IEEE Trans. on Fuzzy Systems, vol. 23, no. 2, pp. 400-420, 2015.

3. Game/ Go

(1) T2FS-based adaptive linguistic assessment system for semantic analysis and human performance evaluation on game of Go, IEEE Trans. on Fuzzy Systems, vol. 23, no. 2, pp. 400-420, 2015.

(2) Soft-Computing-based emotional expression mechanism for game of Computer Go, Soft Computing, vol. 17, no. 7, pp. 1263-1282, 2013.

(3) Genetic fuzzy markup language for game of NoGo, Knowledge-Based Systems, vol. 34, pp. 64- 80, 2012.

(4) An ontology-based fuzzy inference system for computer Go applications, International Journal of Fuzzy Systems, vol. 12, no. 2, pp. 103-115, 2010.

4. Energy Management

(1) An optimization model for FML-based decision support system on energy management, in Proceeding of 2014 IEEE International Conference on Fuzzy Systems, Beijing, China, 6-11, 2014, pp. 850-856.

(2) FML-based decision support system for solar energy supply and demand analysis, 2013 IEEE International Conference on Fuzzy Systems, Hyderabad, India, 7-10, 2013.

5. Patent Evaluation

(1) Fuzzy markup language with genetic learning mechanism for invention patent quality evaluation, in Proceeding of 2015 IEEE Congress on Evolutionary Computation, Sendai, Japan, 25-28, 2015, pp. 251-258.

6. Information Security

(1) IT2FS-based ontology with soft-computing mechanism for malware behavior analysis, Soft Computing, vol. 18, no. 2, pp. 267-284, 2014.

7. University Assessment

(1) Apply fuzzy ontology and FML to knowledge extraction for university governance and management, Journal of Ambient Intelligence and Humanized Computing, vol. 4, no. 4, pp. 493- 513, 2013.

8. Children with Autism based on Kinect and JFML

Juan Carlos Gámez-Granados, Francisco Javier Rodriguez-Lozano, Giovanni Acampora, and Jose Manuel Soto-Hidalgo

Motor therapies can be considered as one of the social challenges that have a great impact nowadays. Traditionally, exercises and activities have been used to mitigate and to rehabilitate problems related to gross motor skills. Nevertheless, from the perspective of children, these therapies are often repetitive and boring. A new challenge in this line is related with the integration of 3D sensors and computer based games as therapies. Fuzzy systems based on the IEEE1855-2016 standard and the library JFML to support experts' decision making in therapies on the basis of fuzzy rules is the core of this research line. A software, named JKinect is now starting to develop.

Designing Activity Module Interface

Game Interface

9. Teaching Explainable Artificial Intelligence to High School Students

Artificial Intelligence (AI) is part of our everyday life and has become one of the most outstanding and strategic technologies. Explainable AI (XAI) is expected to endow intelligent systems with fairness, accountability, transparency and explanation ability when interacting with humans. This paper describes how to teach fundamentals of XAI to high school students who take part in interactive workshop activities at CiTIUS-USC. These workshop activities are carried out in the context of a strategic plan for promoting careers on Science, Technology, Engineering and Mathematics. Students learn (1) how to build datasets free of bias, (2) how to build interpretable classifiers and (3) how to build multi-modal explanations.

10. Edge Computing and Stream Processing

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