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Abstract To better understand spawning vocalizations of Norwegian coastal cod (Gadus morhua), a prototype eight-element coherent hydrophone array was deployed in stationary vertical and towed horizontal modes to monitor cod sounds during an experiment in spring 2019. Depth distribution of cod aggregations was monitored concurrently with an ultrasonic echosounder. Cod vocalizations recorded on the hydrophone array are analysed to provide time–frequency characteristics, and source level distribution after correcting for one-way transmission losses from cod locations to the hydrophone array. The recorded cod vocalization frequencies range from ∼20 to 600 Hz with a peak power frequency of ∼60 Hz, average duration of 300 ms, and mean source level of 163.5 ± 7.9 dB re 1 μPa at 1 m. Spatial dependence of received cod vocalization rates is estimated using hydrophone array measurements as the array is towed horizontally from deeper surrounding waters to shallow water inlet areas of the experimental site. The bathymetric-dependent probability of detection regions for cod vocalizations are quantified and are found to be significantly reduced in shallow-water areas of the inlet. We show that the towable hydrophone array deployed from a moving vessel is invaluable because it can survey cod vocalization activity at multiple locations, providing continuous spatial coverage that is complementary to fixed sensor systems that provide continuous temporal coverage at a given location. 

The time-dependent spectral characteristics of underwater sound radiated by an ocean vessel has complex dependencies on ship machinery, propeller dynamics, hydrodynamics of ship exhaust and motion, as well as ship board activities. Here the underwater sound radiated by a ship equipped with a controllable pitch propeller (CPP) is analyzed and quantified via its (i) power spectral density for signal energetics, (ii) temporal coherence for machinery tonal sound, and (iii) spectral coherence for propeller amplitude-modulated cavitation noise. Frequency-modulated (FM) tonal signals are also characterized in terms of their frequency variations. These characteristics are compared for different propeller pitch ratios ranging from 20% to 82% at fixed propeller revolutions per minute (RPM). The efficacy and robustness of ship parameter estimation at different pitches are discussed. Finally, analysis of one special measurement is provided, when ship changes speed, propeller pitch and RPM over the duration of the measurement. The 50% pitch is found to be a crucial point for this ship about which tonal characteristics of its underwater radiated sound attain their peak values, while broadband sound and associated spectral coherences are at a minimum. The findings here elucidate the effects of pitch variation on underwater sound radiated by ships with controllable pitch propellers and has applications in ship design and underwater noise mitigation. 

Software applications in educational technology have been a strong driving force for the success of online learning at all levels. These applications are created for various purposes and are used by a range of experts. The development of a successful educational technology software takes a deliberate team effort and thoughtful project management. This interpretive case study details the processes, successes, and challenges determined throughout the development of an educational web application, the Social Performance Optimization Tool (SPOT). In describing the evolution of SPOT, and the processes the heterogeneous team followed in the development of the web application, this study provides analysis and guidance to educational researchers who are interested in developing educational web applications in the future. The study described how authors mindfully adopted software design models, team management techniques, and communication tools. Additionally, the paper highlights practical and unique implications developers must account for when working in higher education contexts. 

Humpback whale behavior, population distribution and structure can be inferred from long term underwater passive acoustic monitoring of their vocalizations. Here we develop automatic approaches for classifying humpback whale vocalizations into the two categories of song and non-song, employing machine learning techniques. The vocalization behavior of humpback whales was monitored over instantaneous vast areas of the Gulf of Maine using a large aperture coherent hydrophone array system via the passive ocean acoustic waveguide remote sensing technique over multiple diel cycles in Fall 2006. We use wavelet signal denoising and coherent array processing to enhance the signal-to-noise ratio. To build features vector for every time sequence of the beamformed signals, we employ Bag of Words approach to time-frequency features. Finally, we apply Support Vector Machine (SVM), Neural Networks, and Naive Bayes to classify the acoustic data and compare their performances. Best results are obtained using Mel Frequency Cepstrum Coefficient (MFCC) features and SVM which leads to 94% accuracy and 72.73% F1-score for humpback whale song versus non-song vocalization classification, showing effectiveness of the proposed approach for real-time classification at sea. 

Airgun source systems generate low frequency underwater sound used in reflection and refraction seismology for mapping ocean bottom stratigraphy with important applications in ocean geosciences, such as understanding plate tectonics, ascertaining ocean geological history and climate change, and offshore hydrocarbon prospecting. Seismo-acoustic airgun signals from geophysical surveying activity were recorded at very long ranges, spanning roughly 175-195 km, on a large-aperture densely-populated linear coherent hydrophone array in the Norwegian Sea during Spring 2014. Off the coast of Alesund, airgun signals were detected with 8 s inter-pulse intervals for 3 to 24 hour time periods per day over the 4 days of hydrophone array operation in that region. Here we provide a time-frequency characterization and bearing-time estimation of the received airgun pulses. By correcting for transmission losses in the range- and depth-dependent Norwegian Sea environment, we estimate the source level distribution back projected to a distance of 1 m from the airgun source system. This back-projected source level distribution is then applied to model the Probability of Detection (PoD) region for the airgun signals with the coherent hydrophone array as the receiver in the Norwegian Sea employing the passive ocean acoustic waveguide remote sensing (POAWRS) technique. The estimates of back-projected source level distribution and PoD region provide an understanding of the horizontal spatial propagation extent of the signals from the airgun source system in the shallow and deep water regions of the Norwegian Sea. These results can also be applied to studies of the potential impact of airgun signals on marine organisms. 

Multiple mechanized ocean vessels, including both surface ships and submerged vehicles, can be simultaneously monitored over instantaneous continental-shelf scale regions >10,000 km 2 via passive ocean acoustic waveguide remote sensing. A large-aperture densely-sampled coherent hydrophone array system is employed in the Norwegian Sea in Spring 2014 to provide directional sensing in 360 degree horizontal azimuth and to significantly enhance the signal-to-noise ratio (SNR) of ship-radiated underwater sound, which improves ship detection ranges by roughly two orders of magnitude over that of a single hydrophone. Here, 30 mechanized ocean vessels spanning ranges from nearby to over 150 km from the coherent hydrophone array, are detected, localized and classified. The vessels are comprised of 20 identified commercial ships and 10 unidentified vehicles present in 8 h/day of Passive Ocean Acoustic Waveguide Remote Sensing (POAWRS) observation for two days. The underwater sounds from each of these ocean vessels received by the coherent hydrophone array are dominated by narrowband signals that are either constant frequency tonals or have frequencies that waver or oscillate slightly in time. The estimated bearing-time trajectory of a sequence of detections obtained from coherent beamforming are employed to determine the horizontal location of each vessel using the Moving Array Triangulation (MAT) technique. For commercial ships present in the region, the estimated horizontal positions obtained from passive acoustic sensing are verified by Global Positioning System (GPS) measurements of the ship locations found in a historical Automatic Identification System (AIS) database. We provide time-frequency characterizations of the underwater sounds radiated from the commercial ships and the unidentified vessels. The time-frequency features along with the bearing-time trajectory of the detected signals are applied to simultaneously track and distinguish these vessels.