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In this paper, a novel fusion network for automatic modulation classification (AMC) is proposed in underwater acoustic communication, which consists of a Transformer and depth-wise convolution (DWC) network. Transformer breaks the limitation of sequential signal input and establishes the connection between different modulations in a parallel manner. Its attention mechanism can improve the modulation recognition ability by focusing on the key information. DWC is regularly inserted in the Transformer network to constitute a spatial-temporal structure, which can enhance the classification results at lower signal-to-noise ratios (SNRs). The proposed method can obtain more deep features of underwater acoustic signals. The experiment results achieve an average of 92.1% at −4 dB ≤ SNR ≤ 0 dB, which exceed other state-of-the-art neural networks.

Since the industrial revolution the ocean has become noisier. The global increase in shipping is one of the main contributors to this. In some regions, shipping contributed to an increase in ambient noise of several decibels, especially at low frequencies (10 to 100 Hz). Such an increase can have a substantial negative impact on fish, invertebrates, marine mammals and birds interfering with key life functions (e.g. foraging, mating, resting, etc.). Consequently, engineers are investigating ways to reduce the noise emitted by vessels when designing new ships. At the same time, since the industrial revolution (starting around 1760) greenhouse gas emissions have increased the atmospheric carbon dioxide fraction x(CO2) by more than 100 μmol mol-1. The ocean uptake of approximately one third of the emitted CO2 decreased the average global surface ocean pH from 8.21 to 8.10. This decrease is modifying sound propagation, especially sound absorption at the frequencies affected by shipping noise lower than 10 kHz, making the future ocean potentially noisier. There are also other climate change effects that may influence sound propagation. Sea surface warming might alter the depth of the deep sound speed channel, ice melting could locally decrease salinity and more frequent storms and higher wind speed alter the depth of the thermocline. In particular, modification of the sound speed profile can lead to the appearance of new ducts making specific depths noisier. In addition, ice melting and the increase in seawater temperature will open new shipping routes at the poles increasing anthropogenic noise in these regions. This review aims to discuss parameters that might change in the coming decades, focusing on the contribution of shipping, climate change and economic and technical developments to the future underwater soundscape in the ocean. Examples are given, contrasting the open ocean and the shallow seas. Apart from the changes in sound propagation, this review will also d

Adverse weather conditions such as rain and haze often lead to a degradation in the quality of maritime images, which is crucial for activities like navigation, fishing, and search and rescue. Therefore, it is of great interest to develop an effective algorithm to recover high-quality maritime images under adverse weather conditions. This paper proposes a prompt-based learning method with degradation perception for maritime image restoration, which contains two key components: a restoration module and a prompting module. The former is employed for image restoration, whereas the latter encodes weather-related degradation-specific information to modulate the restoration module, enhancing the recovery process for improved results. Inspired by the recent trend of prompt learning in artificial intelligence, this paper adopts soft-prompt technology to generate learnable visual prompt parameters for better perceiving the degradation-conditioned cues. Extensive experimental results on several benchmarks show that our approach achieves superior restoration performance in maritime image dehazing and deraining tasks.

Excessive CO2 emissions and increased total costs of liner shipping are the two main problems affecting the environmental and economic benefits of liner companies under the European Union Emission Trading System (EU ETS). To address the upcoming EU ETS, we propose a carbon and cost accounting model for liner shipping that accurately calculates CO2 emissions and total cost of liner shipping. We conduct a case study that a containership operates on the liner route from the Far East to Northwest Europe. The results show that the sailing stage plays a pivotal role in CO2 emissions from liner shipping, accounting for 94.70% of CO2 emissions. Among four types of fuel, CO2 emissions from liner shipping using MGO is the largest, while CO2 emissions from liner shipping using methanol is the smallest. Methanol, as an alternative fuel, proves to be a better choice than LNG for CO2 control of liner shipping. The relationship between sailing speed and CO2 emissions follows a U-shaped curve for the selected containership. Notably, speed reduction is effective in carbon control of liner shipping only when the sailing speed exceeds 8.29 knots. Under the EU ETS, sailing speed is a key variable affecting the total cost of liner shipping. Speed reduction may not always be cost-effective. When keeping the total cost of liner shipping unchanged, sailing speed should be reduced as the EU allowance (EUA) price rises within a certain range. For the selected containership using MGO and HFO, the most economical sailing speed is 8.29 knots, corresponding to the increase in EUA price of 304.95% and 261.21%, respectively. If EUA price continues to rise, speed reduction will become ineffective in controlling the total cost of liner shipping. This model can enhance the environmental and economic benefits of liner companies, meet compliance requirements of the EU ETS, and provide a new perspective for carbon and cost control of liner shipping.

The Kyrenia Ship, found off the north coast of Cyprus, is a key vessel in the history of scientific underwater excavations and in the history of Greek shipbuilding. The first volume of the site's final publication appeared in 2023 and provides detailed archaeological information tightly constraining the dating of the ship. A very specific date range is proposed: ca. 294-290 BCE, but is based on a less than certain reading of one coin recovered from the ship. While there is clear benefit to finding high-precision dates for the Kyrenia Ship and its rich assemblage using independent scientific dating (combined with Bayesian chronological modeling), efforts to do so proved more challenging and complex than initially anticipated. Strikingly, extensive radiocarbon dating on both wooden materials from the ship and on short-lived contents from the final use of the ship fail to offer dates using the IntCal20 calibration curve-the current Northern Hemisphere radiocarbon calibration curve at the time of writing-that correspond with the archaeological constraints. The issue rests with a segment of IntCal20 ca. 350-250 BCE reliant on legacy pre-AMS radiocarbon data. We therefore measured new known-age tree-ring samples 350-250 BCE, and, integrating another series of new known-age tree-ring data, we obtained a redefined and more accurate calibration record for the period 433-250 BCE. These new data permit a satisfactory dating solution for the ship and may even indicate a date that is a (very) few years more recent than current estimations. These new data in addition confirm and only very slightly modify the dating recently published for the Mazotos ship, another Greek merchant ship from the southern coast of Cyprus. Our work further investigated whether ship wood samples impregnated with a common preservative, polyethylene glycol (PEG), can be cleaned successfully, including a known-age test.

7 survive 20 hours at sea clinging to boat, cooler.

Oil-slick ship at risk of breaking up: NZealand PM.