Publications by authors named "Mahdi H Al-Badrawi"

Tracking species with expanding ranges is crucial to conservation efforts and some typically temperate marine species are spreading northward into the Arctic Ocean. Risso's (Gg) and Pacific white-sided (Lo) dolphins have been documented spreading poleward. Further, they make very similar sounds, so it is difficult for both human analysts and classification algorithms to tell them apart.

View Article and Find Full Text PDF

A previous analysis of 1977 passive acoustic recordings in the Indian Ocean focused on sound pressure levels (SPLs) and showed that SPLs were slightly depth dependent and highly influenced by shipping activities [Wagstaff and Aitkenhead, IEEE J. Ocean. Eng.

View Article and Find Full Text PDF

Detecting marine mammal vocalizations in underwater acoustic environments and classifying them to species level is typically an arduous manual analysis task for skilled bioacousticians. In recent years, machine learning and other automated algorithms have been explored for quickly detecting and classifying all sound sources in an ambient acoustic environment, but many of these still require a large training dataset compiled through time-intensive manual pre-processing. Here, an application of the signal decomposition technique Empirical Mode Decomposition (EMD) is presented, which does not require knowledge and quickly detects all sound sources in a given recording.

View Article and Find Full Text PDF