Ethical assessment in e-Health
Gonzalez-Pinto, A., Ruiz de Azua, S., Mival, O. H., Thuernmler, C., Jumelle, A. K. L., Ispas, I., …González-Pinto, A. (2015)
Ethical assessment in e-Health. In 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom), 262-268. https://doi.org/10.1109/healthcom.2014.7001852
While innovative e-Health and m-Health technologies and solutions will eventually change the way health and social care are delivered, it raises many challenges regarding what...
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines
Mocanu, D. C., Bou Ammar, H., Puig, L., Eaton, E., & Liotta, A. (2017)
Estimating 3D trajectories from 2D projections via disjunctive factored four-way conditional restricted Boltzmann machines. Pattern Recognition, 69, 325-335. https://doi.org/10.1016/j.patcog.2017.04.017
Estimation, recognition, and near-future prediction of 3D trajectories based on their two dimensional projections available from one camera source is an exceptionally difficul...
Machine Learning for Health and Social Care Demographics in Scotland
Presentation / Conference
Buchanan, W. J., Smales, A., Lawson, A., & Chute, C. (2019, November)
Machine Learning for Health and Social Care Demographics in Scotland. Paper presented at HEALTHINFO 2019, Valencia, Spain
This paper outlines an extensive study of applying machine learning to the analysis of publicly available health and social care data within Scotland, with a focus on learning...
Enhancing Big Data Security with Collaborative Intrusion Detection
Tan, Z., Nagar, U. T., He, X., Nanda, P., Liu, R. P., Wang, S., & Hu, J. (2014)
Enhancing Big Data Security with Collaborative Intrusion Detection. IEEE cloud computing, 1(3), 27-33. https://doi.org/10.1109/mcc.2014.53
Big data, often stored in cloud networks, is changing our business models and applications. Rich information residing in big data is driving business decision making to be a d...
Spatial anomaly detection in sensor networks using neighborhood information
Bosman, H. H., Iacca, G., Tejada, A., Wörtche, H. J., & Liotta, A. (2017)
Spatial anomaly detection in sensor networks using neighborhood information. Information Fusion, 33, 41-56. https://doi.org/10.1016/j.inffus.2016.04.007
The field of wireless sensor networks (WSNs), embedded systems with sensing and networking capability, has now matured after a decade-long research effort and technological ad...
A Review of Predictive Quality of Experience Management in Video Streaming Services
Torres Vega, M., Perra, C., De Turck, F., & Liotta, A. (2018)
A Review of Predictive Quality of Experience Management in Video Streaming Services. IEEE Transactions on Broadcasting, 64(2), 432-445. https://doi.org/10.1109/tbc.2018.2822869
Satisfying the requirements of devices and users of online video streaming services is a challenging task. It requires not only managing the network quality of service but als...
Self-Learning Power Control in Wireless Sensor Networks
Chincoli, M., & Liotta, A. (2018)
Self-Learning Power Control in Wireless Sensor Networks. Sensors, 18(2), 1-29. https://doi.org/10.3390/s18020375
Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This...
Higher-order statistics-based nonlinear speech analysis
Soraghan, J. J., Hussain, A., Alkulabi, A., & Durrani, T. (2002)
Higher-order statistics-based nonlinear speech analysis. Control and Intelligent Systems, 30, 11-18
A fast and robust three-level binary higher order statistics (HOS) based algorithm for simultaneous voiced/unvoiced detection and pitch estimation of speech signals in coloure...
On-Line Building Energy Optimization Using Deep Reinforcement Learning
Mocanu, E., Mocanu, D. C., Nguyen, P. H., Liotta, A., Webber, M. E., Gibescu, M., & Slootweg, J. G. (2019)
On-Line Building Energy Optimization Using Deep Reinforcement Learning. IEEE Transactions on Smart Grid, 10(4), 3698-3708. https://doi.org/10.1109/tsg.2018.2834219
Unprecedented high volumes of data are becoming available with the growth of the advanced metering infrastructure. These are expected to benefit planning and operation of the ...
A topological insight into restricted Boltzmann machines
Mocanu, D. C., Mocanu, E., Nguyen, P. H., Gibescu, M., & Liotta, A. (2016)
A topological insight into restricted Boltzmann machines. Machine Learning, 104(2-3), 243-270. https://doi.org/10.1007/s10994-016-5570-z
Restricted Boltzmann Machines (RBMs) and models derived from them have been successfully used as basic building blocks in deep artificial neural networks for automatic feature...