Optimized Gated Deep Learning Architectures for Sensor Fusion

Sensor fusion is a key technology that integrates various sensory inputs to allow for robust decision making in many applications such as autonomous driving and robot control. Deep neural networks have been adopted for sensor fusion in a body of recent studies. Among these, the so-called netgated architecture was proposed, which has demonstrated improved performances over the conventional convolutional neural networks (CNN). In this paper, we address several limitations of the baseline negated architecture by proposing two further optimized architectures: a coarser-grained gated architecture employing (feature) group-level fusion weights and a two-stage gated architectures leveraging both the group-level and feature level fusion weights. Using driving mode prediction and human activity recognition datasets, we demonstrate the significant performance improvements brought by the proposed gated architectures and also their robustness in the presence of sensor noise and failures.Comment: 10 pages, 5 figures. Submitted to ICLR 201

Investigating the physiological underpinnings of proactive and reactive behavioural types in grey seals (Halichoerus grypus): Trial deployment of a minimally invasive data logger for recording heart rate and heart rate variability in a wild free-ranging breeding pinniped species

Individuals differ non-randomly in their responses to stressors, exhibiting consistent individual differences (CIDs) in behavioural and physiological coping mechanisms commonly referred to as coping styles. Grey seals (Halichoerus grypus) are one of the few mammal species in which CIDs in stress responses have been documented in wild populations, though evidence thus far has been purely behavioural. Physiologically, coping styles can be distinguished by differences in the autonomic regulation of cardiac activity, which can be measured using heart rate variability (HRV). The objectives of this study were two-fold. First, to assess the suitability of Polar® RS800CX monitors and H2/H3 sensors for conducting HRV analyses in grey seals. Second, to quantify inter-individual variation, repeatability, and reproductive performance correlates of baseline HRV. Polar® devices were deployed successfully during the 2013 breeding season on female grey seals (N = 15) on the Isle of May, Scotland, and were capable of recording HR patterns that characterise phocid seals at rest on land. However, artefacts were widespread and biased HRV metrics. Filtration and correction protocols were able to counteract the effects of artefacts, but severely limited the amount of data available for analysis. There were significant inter-individual differences in baseline HRV, which could not be explained by factors associated with the breeding season (e.g. percentage mass loss, day of lactation), diurnal rhythms (e.g. time of day), or stressors (e.g. days since capture). These differences in baseline HRV showed consistency across early and late lactation. Individuals appeared to separate into two groups: those with consistently lower or higher baseline HRV, characteristic of proactive and reactive coping styles, respectively. Furthermore, females with lower baseline HRV showed greater maternal transfer efficiency – though there were no associations between baseline HRV and maternal expenditure (i.e. maternal mass loss, kgday–1) or fitness outcomes (i.e. pup mass gain, kgday–1). These findings build upon previous studies on behavioural CIDs in female grey seals by providing the first preliminary evidence for physiological CIDs that are associated with maternal investment. However, due to small sample sizes, further studies are required to determine whether these findings are truly indicative of coping styles. In their current form, the use of Polar® devices requires several caveats and further studies are needed to fully realise their potential. Future research should focus on validation against simultaneously recorded ECGs to improve artefact detection and correction, and modification to minimise the occurrence of artefacts. Despite their limitations, Polar® devices have immense potential as a minimally invasive research tool for conducting HRV analyses in the field

Closing the loop of SIEM analysis to Secure Critical Infrastructures

Critical Infrastructure Protection is one of the main challenges of last years. Security Information and Event Management (SIEM) systems are widely used for coping with this challenge. However, they currently present several limitations that have to be overcome. In this paper we propose an enhanced SIEM system in which we have introduced novel components to i) enable multiple layer data analysis; ii) resolve conflicts among security policies, and discover unauthorized data paths in such a way to be able to reconfigure network devices. Furthermore, the system is enriched by a Resilient Event Storage that ensures integrity and unforgeability of events stored.Comment: EDCC-2014, BIG4CIP-2014, Security Information and Event Management, Decision Support System, Hydroelectric Da

Listening for Sirens: Locating and Classifying Acoustic Alarms in City Scenes

This paper is about alerting acoustic event detection and sound source localisation in an urban scenario. Specifically, we are interested in spotting the presence of horns, and sirens of emergency vehicles. In order to obtain a reliable system able to operate robustly despite the presence of traffic noise, which can be copious, unstructured and unpredictable, we propose to treat the spectrograms of incoming stereo signals as images, and apply semantic segmentation, based on a Unet architecture, to extract the target sound from the background noise. In a multi-task learning scheme, together with signal denoising, we perform acoustic event classification to identify the nature of the alerting sound. Lastly, we use the denoised signals to localise the acoustic source on the horizon plane, by regressing the direction of arrival of the sound through a CNN architecture. Our experimental evaluation shows an average classification rate of 94%, and a median absolute error on the localisation of 7.5{\deg} when operating on audio frames of 0.5s, and of 2.5{\deg} when operating on frames of 2.5s. The system offers excellent performance in particularly challenging scenarios, where the noise level is remarkably high.Comment: 6 pages, 9 figure