Outputs (11)

Impact of Ubiquitous Real-Time Information on Bus Passenger Route Choice (2018)
Thesis
Islam, M. F. Impact of Ubiquitous Real-Time Information on Bus Passenger Route Choice. (Thesis). Edinburgh Napier University. http://researchrepository.napier.ac.uk/Output/1508471

Over the last decade, Ubiquitous Real-time Passenger Information (URTPI) has become popular among public transport passengers. The effectiveness of URTPI and hence the value of the investments into the necessary systems can be increased with a clear... Read More about Impact of Ubiquitous Real-Time Information on Bus Passenger Route Choice.

Energy consumption and modelling of the climate control system in the electric vehicle (2018)
Journal Article
Doyle, A., & Muneer, T. (2018). Energy consumption and modelling of the climate control system in the electric vehicle. Energy Exploration and Exploitation, https://doi.org/10.1177/0144598718806458

With the introduction of electric vehicles in the automobile market, limited information is available on how the battery’s energy consumption is distributed. This paper focuses on the energy
consumption of the vehicle when the heating and cooling sy... Read More about Energy consumption and modelling of the climate control system in the electric vehicle.

Interference graphs to monitor and control schedules in low-power WPAN (2018)
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 interference graphs are used to reschedule problematic connections.
• Rea... Read More about Interference graphs to monitor and control schedules in low-power WPAN.

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science (2018)
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), Article 2383. 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 the network properties of biological neural networks (e.g. sparsity, scale-... Read More about Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science.

An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0 (2018)
Journal Article
Pace, P., Aloi, G., Gravina, R., Caliciuri, G., Fortino, G., & Liotta, A. (2019). An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0. IEEE Transactions on Industrial Informatics, 15(1), 481-489. https://doi.org/10.1109/tii.2018.2843169

Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard cloud-based approaches to reduce the interaction timing and the huge amount of data coming from Internet of Things (IoT) devices toward... Read More about An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0.

On-Line Building Energy Optimization Using Deep Reinforcement Learning (2018)
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 future power systems and to help customers transition from a passive to an... Read More about On-Line Building Energy Optimization Using Deep Reinforcement Learning.

A Review of Predictive Quality of Experience Management in Video Streaming Services (2018)
Journal Article
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 also to exert real-time control, addressing the user's quality of experience (... Read More about A Review of Predictive Quality of Experience Management in Video Streaming Services.

Recovery time and propagation effects of passenger transport disruptions (2018)
Journal Article
Malandri, C., Malandria, C., Fonzone, A., & Cats, O. (2018). Recovery time and propagation effects of passenger transport disruptions. Physica A: Statistical Mechanics and its Applications, 505, 7-17. https://doi.org/10.1016/j.physa.2018.03.028

We propose a method to evaluate public transport network vulnerability. We study the evolution of the passenger Volume Over Capacity (VOC) ratio throughout the network to measure the spatial and temporal extent of the impacts caused by an unplanned s... Read More about Recovery time and propagation effects of passenger transport disruptions.

Self-Learning Power Control in Wireless Sensor Networks (2018)
Journal Article
Chincoli, M., & Liotta, A. (2018). Self-Learning Power Control in Wireless Sensor Networks. Sensors, 18(2), Article 375. 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 aggravates the already over-congested unlicensed radio bands, calling for... Read More about Self-Learning Power Control in Wireless Sensor Networks.

Decentralized dynamic understanding of hidden relations in complex networks (2018)
Journal Article
Mocanu, D. C., Exarchakos, G., & Liotta, A. (2018). Decentralized dynamic understanding of hidden relations in complex networks. Scientific Reports, 8(1), https://doi.org/10.1038/s41598-018-19356-4

Almost all the natural or human made systems can be understood and controlled using complex networks. This is a difficult problem due to the very large number of elements in such networks, on the order of billions and higher, which makes it impossibl... Read More about Decentralized dynamic understanding of hidden relations in complex networks.

Resilience of Video Streaming Services to Network Impairments (2018)
Journal Article
Torres Vega, M., Perra, C., & Liotta, A. (2018). Resilience of Video Streaming Services to Network Impairments. IEEE Transactions on Broadcasting, 64(2), 220-234. https://doi.org/10.1109/tbc.2017.2781125

When dealing with networks, performance management through conventional quality of service (QoS)-based methods becomes difficult and is often ineffective. In fact, quality emerges as an end-to-end factor, for it is particularly sensitive to the end-u... Read More about Resilience of Video Streaming Services to Network Impairments.