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Outputs (59)

Sensitive data discovery in care pathways using Business Process Modelling and HL7-CDA (2019)
Journal Article
Essefi, I., Rahmouni, H. B., & Ladeb, M. F. (2019). Sensitive data discovery in care pathways using Business Process Modelling and HL7-CDA. International Journal on Advances in Life Sciences, 11(2), 56-67

Medical data communication is an important process enabling collaboration between healthcare professionals. The use of patient Electronic Health Record (EHR) ensures an enhanced continuity of care since it provides a centralized patient information a... Read More about Sensitive data discovery in care pathways using Business Process Modelling and HL7-CDA.

A two-stage approach for social identity linkage based on an enhanced weighted graph model (2019)
Journal Article
Qin, T., Liu, Z., Li, S., & Guan, X. (2020). A two-stage approach for social identity linkage based on an enhanced weighted graph model. Mobile Networks and Applications, 25, 1364 - 1375. https://doi.org/10.1007/s11036-019-01456-8

Social identity linkage refers to identify the accounts belong to the same person across different social networks. This work can assist in building more complete social profiles, which is valuable for many social-powered applications. In this paper,... Read More about A two-stage approach for social identity linkage based on an enhanced weighted graph model.

A stream processing framework based on linked data for information collaborating of regional energy networks (2019)
Journal Article
Yu, H., Da Xu, L., Cai, H., Li, S., Xu, B., & Jiang, L. (2021). A stream processing framework based on linked data for information collaborating of regional energy networks. IEEE Transactions on Industrial Informatics, 17(1), 179-188. https://doi.org/10.1109/tii.2019.2957517

© 2005-2012 IEEE. Coordinating of energy networks to form a city-level multidimensional integrated energy system becomes a new trend in Energy Internet (EI). The collaborating in the information layer is a core issue to achieve smart integration. How... Read More about A stream processing framework based on linked data for information collaborating of regional energy networks.

A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation (2019)
Journal Article
Polatidis, N., Pimenidis, E., Fish, A., & Kapetanakis, S. (2019). A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation. International Journal on Artificial Intelligence Tools, 28(8), Article 1960011. https://doi.org/10.1142/S021821301960011X

Recommender systems' evaluation is usually based on predictive accuracy and information retrieval metrics, with better scores meaning recommendations are of higher quality. However, new algorithms are constantly developed and the comparison of result... Read More about A guideline-based approach for assisting with the reproducibility of experiments in recommender systems evaluation.

An analytical framework for high-speed hardware particle swarm optimization (2019)
Journal Article
Damaj, I., Elshafei, M., El-Abd, M., & Aydin, M. E. (2020). An analytical framework for high-speed hardware particle swarm optimization. Microprocessors and Microsystems, 72, 102949. https://doi.org/10.1016/j.micpro.2019.102949

Engineering optimization techniques are computationally intensive and can challenge implementations on tightly-constrained embedded systems. Particle Swarm Optimization (PSO) is a well-known bio-inspired algorithm that is adopted in various applicati... Read More about An analytical framework for high-speed hardware particle swarm optimization.

Spatial-temporal data-driven service recommendation with privacy-preservation (2019)
Journal Article
Zhang, X., Qi, L., Li, S., Wan, S., Wen, Y., & Gong, W. (2020). Spatial-temporal data-driven service recommendation with privacy-preservation. Information Sciences, 515, 91-102. https://doi.org/10.1016/j.ins.2019.11.021

© 2019 Elsevier Inc. The ever-increasing popularity of web service sharing communities have produced a considerable amount of web services that share similar functionalities but vary in Quality of Services (QoS) performances. To alleviate the heavy s... Read More about Spatial-temporal data-driven service recommendation with privacy-preservation.

Contactless sensing of liquid marbles for detection, characterisation & computing (2019)
Journal Article
Draper, T. C., Phillips, N., Weerasekera, R., Mayne, R., Fullarton, C., de Lacy Costello, B., & Adamatzky, A. (2020). Contactless sensing of liquid marbles for detection, characterisation & computing. Lab on a Chip, 20(1), 136-146. https://doi.org/10.1039/c9lc01001g

Liquid marbles (LMs) are of growing interest in many fields, including microfluidics, microreactors, sensors, and signal carriers. The generation of LMs is generally performed manually, although there has recently been a burst of publications involvi... Read More about Contactless sensing of liquid marbles for detection, characterisation & computing.

Blockchain and edge computing–based architecture for participatory smart city applications (2019)
Journal Article
Khan, Z., Abbasi, A. G., & Pervez, Z. (2020). Blockchain and edge computing–based architecture for participatory smart city applications. Concurrency and Computation: Practice and Experience, 32(12), Article e5566. https://doi.org/10.1002/cpe.5566

© 2019 John Wiley & Sons, Ltd. Smart cities aim to provide smart governance with the emphasis on gaining high transparency and trust in public services and enabling citizen participation in decision making processes. This means on the one hand data... Read More about Blockchain and edge computing–based architecture for participatory smart city applications.

Predicting environmental features by learning spatiotemporal embeddings from social media (2019)
Journal Article
Jeawak, S. S., Jones, C. B., & Schockaert, S. (2020). Predicting environmental features by learning spatiotemporal embeddings from social media. Ecological Informatics, 55, https://doi.org/10.1016/j.ecoinf.2019.101031

Spatiotemporal modelling is an important task for ecology. Social media tags have been found to have great potential to assist in predicting aspects of the natural environment, particularly through the use of machine learning methods. Here we propose... Read More about Predicting environmental features by learning spatiotemporal embeddings from social media.