A topological insight into restricted Boltzmann machines
Journal Article
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...
CACA-UAN: a context-aware communication approach to efficient and reliable underwater acoustic sensor networks
Journal Article
Liu, Q., Chen, X., Liu, X., & Linge, N. (2018)
CACA-UAN: a context-aware communication approach to efficient and reliable underwater acoustic sensor networks. International Journal of Sensor Networks, 26(1), 1. https://doi.org/10.1504/ijsnet.2018.088364
Underwater Acoustic Sensor Networks (UANs) have emerged as a promising technology recently which can be applied in many areas such as military and civil, where the communicati...
Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach
Journal Article
Di Mauro, M., & Liotta, A. (2019)
Statistical Assessment of IP Multimedia Subsystem in a Softwarized Environment: a Queueing Networks Approach. IEEE Transactions on Network and Service Management, 16(4), 1493-1506. https://doi.org/10.1109/tnsm.2019.2943776
The Next Generation 5G Networks can greatly benefit from the synergy between virtualization paradigms, such as the Network Function Virtualization (NFV), and service provision...
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
Journal Article
Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, P. H., Gibescu, M., & Liotta, A. (2018)
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science. Nature Communications, 9(1), 1-12. https://doi.org/10.1038/s41467-018-04316-3
Through the success of deep learning in various domains, artificial neural networks are currently among the most used artificial intelligence methods. Taking inspiration from ...
Interference graphs to monitor and control schedules in low-power WPAN
Journal Article
van der Lee, T., Liotta, A., & Exarchakos, G. (2019)
Interference graphs to monitor and control schedules in low-power WPAN. Future Generation Computer Systems, 93, 111-120. https://doi.org/10.1016/j.future.2018.10.014
Highlights
• This study presents the complete and slotted interference graph model.
• The service uses the complete interference graph to evaluate the network.
• Slotted int...
Grid Routing: An Energy-Efficient Routing Protocol for WSNs with Single Mobile Sink
Journal Article
Liu, Q., Zhang, K., Liu, X., & Linge, N. (2017)
Grid Routing: An Energy-Efficient Routing Protocol for WSNs with Single Mobile Sink. International Journal of Sensor Networks, 25(2), 1. https://doi.org/10.1504/ijsnet.2017.10007397
In a traditional wireless sensor network with static sinks, sensor nodes close to the sink run out of their batteries quicker than other nodes due to the increased data traffi...
An AI approach to Collecting and Analyzing Human Interactions with Urban Environments
Journal Article
Ferrara, E., Fragale, L., Fortino, G., Song, W., Perra, C., di Mauro, M., & Liotta, A. (2019)
An AI approach to Collecting and Analyzing Human Interactions with Urban Environments. IEEE Access, 7, 141476-141486. https://doi.org/10.1109/access.2019.2943845
Thanks to advances in Internet of Things and crowd-sensing, it is possible to collect vast amounts of urban data, to better understand how citizens interact with cities and, i...
Self-Learning Power Control in Wireless Sensor Networks
Journal Article
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...
Dual-band planar inverted F-L antenna structure for bluetooth and ZigBee applications
Book Chapter
See, C. H., Oguntala, G. A., Shuaieb, W., Noras, J. M., & Excell, P. S. (2018)
Dual-band planar inverted F-L antenna structure for bluetooth and ZigBee applications. In I. Elfergani, A. Hussaini, J. Rodriguez, & R. Abd-Alhameed (Eds.), Antenna Fundamentals for Legacy Mobile Applications and Beyond, 39-52. Springer Verlag. https://doi.org/10.1007/978-3-319-63967-3_2
This chapter will present and analyse a compact and dual frequency inverted L-F antennas for the operating frequency bands to meet the requirement for IEEE 802.11a/b/g, Blueto...
On-Line Building Energy Optimization Using Deep Reinforcement Learning
Journal Article
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 ...