Search Results (267)

The adoption of technological innovations in the maritime industry is of interest to business, policy, and academic communities. In the last group, this interest has translated into the publication of a large but scattered literature, making it difficult to compare findings and identify the dynamics, structures, and patterns that might inform future research. A comprehensive review of past research on this topic might help achieve this. To date, no such review has been carried out, which is an important gap in the literature that this paper contributes to bridging. Two bibliometric review techniques—co-citation analysis of cited references and bibliographic coupling of documents—are applied to 171 journal articles published between 1999 and February 2025 to answer the following questions: 1. What is the knowledge base of this literature? 2. What are the recent research trends (research fronts) in this literature? The analysis reveals that research on “shore power” dominates both the knowledge base and research fronts. Other key research themes centre on “autonomous shipping”, “blockchain”, and “alternative fuels”. Based on these results, implications for future research are drawn. Full article

The accurate extraction of navigational regions from images of navigational waters plays a key role in ensuring on-water safety and the automation of unmanned vessels. Nonetheless, current technological methods encounter significant challenges in addressing fluctuations in water surface illumination, reflective disturbances, and surface undulations, among other disruptions, in turn making it challenging to achieve rapid and precise boundary segmentation. To cope with these challenges, in this paper, we propose a coordinate-aware multi-scale feature network (GASF-ResNet) method for water segmentation. The method integrates the attention module Global Grouping Coordinate Attention (GGCA) in the four downsampling branches of ResNet-50, thus enhancing the model’s ability to capture target features and improving the feature representation. To expand the model’s receptive field and boost its capability in extracting features of multi-scale targets, the Avoidance Spatial Pyramid Pooling (ASPP) technique is used. Combined with multi-scale feature fusion, this effectively enhances the expression of semantic information at different scales and improves the segmentation accuracy of the model in complex water environments. The experimental results show that the average pixel accuracy (mPA) and average intersection and union ratio (mIoU) of the proposed method on the self-made dataset and on the USVInaland unmanned ship dataset are 99.31% and 98.61%, and 98.55% and 99.27%, respectively, significantly better results than those obtained for the existing mainstream models. These results are helpful in overcoming the background interference caused by water surface reflection and uneven lighting in the aquatic environment and in realizing the accurate segmentation of the water area for the safe navigation of unmanned vessels, which is of great value for the stable operation of unmanned vessels in complex environments. Full article

Ornamental fish shipped by road or rail may spend days in transit without food, leading to a reduction in somatic growth after transportation and during acclimatization. In the present study, a time-series (0, 2, 4, 6, 8, 10, and 12 days) experiment was conducted to investigate the growth recovery of male Siamese fighting fish (Betta splendens, 1.56 ± 0.02 g body weight, n = 15 per group) transported by road for two days. Biometric changes, nesting activity, skin pigmentation, digestive enzyme activity, muscle quality, and whole-body composition, were compared across all fish groups. The recovery in growth, as indicated by final body weight, increased with post-transportation time (p < 0.05), causing a significant reversal of weight loss with a proportionally stable condition factor from day 8 until the end of observation (p > 0.05). During this time period, the fish exhibited similar bubble-nest building activity to the control group that was not transported (p > 0.05). Color parameters, digestive enzyme activities, muscle quality, and whole-body composition of fish 8 days after shipping were comparable to the control fish group (p > 0.05). Our findings indicate that an 8-day recovery time is an appropriate protocol for Siamese fighting fish acclimatization following overland shipping. Full article

This study investigates the hydrodynamic performance of ships entering a ship lift compartment that is under the influence of upstream channel geometry and proposes a mechanical traction scheme to enhance operational safety and efficiency. Utilizing a Reynolds-averaged Navier–Stokes (RANS)-based computational fluid dynamics (CFD) approach with overlapping grid technology, numerical simulations were conducted for both single and grouped ships navigating through varying water depths, speeds, and shore distances. The results revealed significant transverse force oscillations near the floating navigation wall due to unilateral shore effects, posing risks of deviation. The cargo ship experienced drastic resistance fluctuations in shallow-to-very-shallow-water transitions, while tugboats were notably affected by hydrodynamic interactions during group entry. A mechanical traction system with a four-link robotic arm was designed and analyzed kinematically and statically, demonstrating structural feasibility under converted real-ship traction forces (55.1 kN). The key findings emphasize the need for collision avoidance measures in wall sections and validate the proposed traction scheme for safe and efficient ship entry/exit. This research provides critical insights for optimizing ship lift operations in restricted waters. Full article

Drag embedment anchors (DEAs) provide reliable and cost-effective mooring solutions for floating structures, e.g., platforms, ships, offshore wind turbines, etc., in offshore engineering. Structural stability and operational safety require accurate predictions of their penetration depths and holding capacities across various seabed conditions. In this study, explicit linear regression (LR) models were developed for the first time to predict the penetration depth and holding capacity of DEAs on clay and sand seabed. Buckingham’s theorem was also applied to identify dimensionless groups of parameters that influence DEA behavior, e.g., the penetration depth and holding capacity of the DEAs. LR models were developed and validated against experimental data from the literature for both clay and sand seabed. To evaluate model performance and identify the most accurate LR models to predict DEA behavior, comprehensive sensitivity, error, and uncertainty analyses were performed. Additionally, LR analysis revealed the most influential input parameters impacting penetration depth and holding capacity. Regarding offshore mooring design and geotechnical engineering applications, the proposed LR models offered a practical and efficient approach to estimating DEA performance across various seabed conditions. Full article

In order to improve energy utilization efficiency and the flexibility of resource transfer in oceanic-island-group microgrids, a water–electricity–hydrogen flexible scheduling strategy based on a multi-rate hydrogen-powered ship is proposed. First, the characteristics of the seawater desalination unit (SDU), proton exchange membrane electrolyzer (PEMEL), and battery system (BS) in consuming surplus renewable energy on resource islands are analyzed. The variable-efficiency operation characteristics of the SDU and PEMEL are established, and the effect of battery life loss is also taken into account. Second, a spatio-temporal model for the multi-rate hydrogen-powered ship is proposed to incorporate speed adjustment into the system optimization framework for flexible resource transfer among islands. Finally, with the goal of minimizing the total cost of the system, a flexible water–electricity–hydrogen hybrid resource transfer model is constructed, and a certain island group in the South China Sea is used as an example for simulation and analysis. The results show that the proposed scheduling strategy can effectively reduce energy loss, promote renewable energy absorption, and improve the flexibility of resource transfer. Full article

With the increasing demands of long-term overseas assignments, workers in isolated environments, such as maritime crews, often experience heightened psychological stress and a lack of accessible emotional support. This study investigates the effectiveness of online song intervention program based on contextual support model in reducing work-related distress and enhancing psychological resilience among the ship crews dispatched for an extensive period for work. Eighteen overseas workers participated in a four-week intervention that included both individual and group sessions, where they engaged with songs to cultivate personal and interpersonal resources. A deductive content analysis following the intervention revealed 3 main categories, 6 generic categories, and 14 subcategories. The three main categories identified were relationships, autonomy, and mood regulation. The relationships category encompassed support systems and bonding, focusing on empathy, consolation, positive perspective, vicarious empowerment, trust, and changes of perspective. Autonomy involved fostering a sense of control and fulfillment through determination, anticipation, motivation, and achievement. Mood regulation was divided into grounding and emotional resolution, which included containment, sedation, externalization, and ventilation. The findings highlight that song lyrics offer valuable insights for developing resources aimed at mood regulation, social support, and self-efficacy, helping to alleviate work-related stress during dispatch periods. Songs also foster a sense of control, competence, and relational connectedness, with mood regulation emerging as a key feature of their emotional impact. These results suggest that incorporating songs with lyrics focused on personal and interpersonal resources could be an effective strategy to support remotely dispatched workers. Furthermore, this approach appears to be a viable and scalable solution for online programs. Full article

In this study, we propose an end-to-end detection model based on cascaded spatial priors and dynamic upsampling for ship detection tasks in day–night transition environments, named the Cascaded Group and Dynamic Upsample-DEtection TRansformer (CGDU-DETR). To address the limitations of traditional methods in complex lighting conditions (e.g., strong reflections, low light), we designed a novel CG-Net model based on cascaded group attention and introduced a dynamic feature upsampling algorithm, effectively enhancing the model’s ability to extract multi-scale features and detect targets in complex backgrounds. The experimental results show that the CGDU-DETR achieves an AP of 93.4% on the day–night transition dataset, representing a 2.86% improvement over YOLOv12, and a recall of 95.2%, representing a 24.44% improvement over YOLOv12. Particularly for complex categories such as cargo ships and law enforcement vessels, the CGDU-DETR significantly outperforms YOLOv12, with improvements of 35.9% in AP and 63.7% in recall. Moreover, generalization experiments on the WSODD public dataset further validate the robustness of the model, with the CGDU-DETR achieving an AP of 95.1%, representing an 11.6% improvement over YOLOv12. These results demonstrate that the CGDU-DETR has significant advantages in ship detection tasks under day–night transition environments, effectively handling complex lighting and background interference, and providing reliable technical support for all-weather maritime surveillance. Full article

Efficient ship scheduling in inland waterways is critical for maritime transportation safety and economic viability. However, traditional scheduling methods, primarily based on First Come First Served (FCFS) principles, often produce suboptimal results due to their inability to account for complex spatial–temporal dependencies, directional asymmetries, and varying ship characteristics. This paper introduces SSRL (Ship Scheduling through Reinforcement Learning), a novel framework that addresses these limitations by integrating three complementary components: (1) a Q-learning framework that discovers optimal scheduling policies through environmental interaction rather than predefined rules; (2) a clustering mechanism that reduces the high-dimensional state space by grouping similar ship states; and (3) a sliding window approach that decomposes the scheduling problem into manageable subproblems, enabling real-time decision-making. We evaluated SSRL through extensive experiments using both simulated scenarios and real-world data from the Xiaziliang Restricted Waterway in China. Results demonstrate that SSRL reduces total ship waiting time by 90.6% compared with TSRS, 48.4% compared with FAHP-ES, and 32.6% compared with OSS-SW, with an average reduction of 57.2% across these baseline methods. SSRL maintains superior performance across varying traffic densities and uncertainty conditions, with the optimal information window length of 13–14 ships providing the best balance between solution quality and computational efficiency. Beyond performance improvements, SSRL offers significant practical advantages: it requires minimal computation for online implementation, adapts to dynamic maritime environments without manual reconfiguration, and can potentially be extended to other complex transportation scheduling domains. Full article

The maritime industry is rapidly advancing toward the initial stages of the digitised era of shipping, characterised by considerable advances in maritime autonomous technology in recent times. This study examines the effectiveness of training packages and the impact of rank during the failure of a sophisticated autopilot control system. For this study, the fault recognition and diagnostic skills of 60 navigational seafarers conducting a navigational watch in a full mission bridge watchkeeping simulator were analysed. Participants had either significant experience as qualified navigational officers of the watch or were navigational officers of the watch cadets with 12 months’ watchkeeping experience. These groups were subdivided into those who were given a training package focused on behavioural aspects of managing automation, such as maintaining situational awareness, and those given a technical training package. The findings were analysed using an Event Tree Analysis method to assess the participants’ performance in diagnosing a navigation fault. Additionally, the fault recognition skills were assessed between groups of training and rank. The study found that participants who received the behavioural training were more successful in both recognising and diagnosing the fault during the exercise. Behavioural training groups outperformed technical training groups, even when technical training participants were experienced seafarers. This difference in performance occurred without any apparent differences in workload or secondary task performance. Understanding the data gathered from the study could lead to the development of future training regimes for navigational officers of the watch and help to optimise the evolution of the seafaring role. Full article

In order to improve the efficiency of the deep network model in processing the radiated noise signals of underwater acoustic targets, this paper introduces a Singular Spectrum Analysis and Channel Attention Convolutional Neural Network (SSA-CACNN) model. The front end of the model is designed as an SSA filter, and its input is the time-domain signal that has undergone simple preprocessing. The SSA method is utilized to separate the noise efficiently and reliably from useful signals. The first three orders of useful signals are then fed into the CACNN model, which has a convolutional layer set up at the beginning of the model to further remove noise from the signal. Then, the attention of the model to the feature signal channels is enhanced through the combination of multiple groups of convolutional operations and the channel attention mechanism, which facilitates the model’s ability to discern the essential characteristics of the underwater acoustic signals and improve the target recognition rate. Experimental Results: The signal reconstructed by the first three-order waveforms at the front end of the SSA-CACNN model proposed in this paper can retain most of the features of the target. In the experimental verification using the ShipsEar dataset, the model achieved a recognition accuracy of 98.64%. The model’s parameter count of 0.26 M was notably lower than that of other comparable deep models, indicating a more efficient use of resources. Additionally, the SSA-CACNN model had a certain degree of robustness to noise, with a correct recognition rate of 84.61% maintained when the signal-to-noise ratio (SNR) was −10 dB. Finally, the pre-trained SSA-CACNN model on the ShipsEar dataset was transferred to the DeepShip dataset with a recognition accuracy of 94.98%. Full article

This article proposes a close reading of Rivers Solomon’s 2019 novella The Deep, a recent eco-story about water, memory, and survival. Solomon’s work is inspired by a song called “The Deep” from experimental hip-hop group clipping, a dark science fiction tale about the underwater-dwelling descendants of African women thrown off slave ships during the Middle Passage. This imaginative alternate history, or counter-mythology, was invented by the Detroit techno band Drexciya, which, in a series of releases between 1992 and 2002, tells us the story of an underwater realm in the mid-Atlantic, where merpeople and their descendants establish a utopian society in the sea, free from the war and racism on the surface. My analysis uses Saidiya Hartman’s “critical fabulation” to make productive sense of the gaps in the archive of trans-Atlantic slavery that silence the voices of enslaved women, listening to the voices of water to imagine not only what was but also what could be. Moreover, this article examines The Deep through a trajectory that moves from the ocean as a space that reproduces death only to the ocean as a generative force for posthuman and multispecies kinship. Using Black hydrocriticism, hydrofeminism, and econarratology, I will argue that this transition is made possible by the “despatialization” of the ocean—a concept introduced by Erin James—where the ocean is conceived not as a fixed or stable environment, but as a space in constant flux, defying stability, and the subsequent immersion in its waters. Full article

Digitalization is gaining its popularity in the maritime logistics sector due to its potential to enhance information sharing and automation. These advantages can significantly improve efficiency and have the potential to replace complex manual tasks. However, the diffusion of digitalization faces certain challenges, which, in turn, has drawn the attention of researchers. Implementing digitalization is a complex process, as it is affected by various enablers and barriers, while research providing a comprehensive overview of digitalization in the maritime logistics sector is limited. This study aims to fill the gap by conducting a literature review that reveals digitalization’s enablers and barriers in the maritime logistics sector and constructs a theoretical framework. It analyzes 117 articles that have made significant contributions to this field. The development of innovative technologies, such as blockchain, digital twins, and autonomous shipping, fosters digitalization in maritime logistics. Conversely, barriers like the lack of awareness about the benefits of digitalization can slow down its progress. In total, this paper identifies 19 enablers of and 10 barriers to digitalization in the maritime logistics sector. These enablers and barriers are classified into three groups–technology, organization, and environment–following the Technology–Organization–Environment (TOE) framework. We develop a theoretical framework accordingly using, as its basis, relevant innovation diffusion theories and studies. This study contributes to the development of effective digitalization strategies for maritime organizations and provides a theoretical foundation for future research. Full article

Ships and offshore equipment operating in marine environments often face issues such as seawater corrosion and biofouling, leading to significant economic losses. To address the corrosion problems of ships and offshore equipment, heavy-duty anticorrosive coatings are widely used for corrosion protection in marine environments due to their long-term effectiveness, cost-efficiency, and excellent applicability. In this study, silane coupling agent (KH-560) was employed to modify sodium silicate, and the modified sodium silicate was then incorporated as a reinforcing phase into polyurethane to ultimately prepare a modified sodium silicate/polyurethane coating. The feasibility of the modified sodium silicate/polyurethane coating was investigated by characterizing its conventional physicochemical properties, weather resistance, acid and alkali resistance, and salt spray corrosion resistance. Experimental results indicate that the silane coupling agent acts as a bridge between the organic and inorganic interfaces through the hydrolysis and condensation reactions of its bifunctional groups, forming an interfacial layer connected by hydrogen bonds and covalent bonds, thereby improving the compatibility between the organic resin and inorganic sodium silicate. Comprehensive performance analysis revealed that when the content of modified sodium silicate was 60 wt%, the coating hardness reached 4H. Additionally, electrochemical tests demonstrated that the coating exhibited higher impedance (9.62 × 10⁴ Ω/cm²) and lower corrosion current density (5.82 × 10⁻⁷ A/cm²). This study provides a theoretical and experimental basis for the development of high-performance anticorrosive coatings for marine applications. Full article

Cruise ship tourism in port cities, while offering opportunities, has brought its own challenges, including overcrowding, disruption to local community mobility, and growing resident concerns, which recently escalated to anti-tourism activities. This article aims to understand the mobility patterns, transportation preferences, and spatial behaviors of cruise ship passengers within the City of Barcelona (Spain). The study is based on a survey conducted with cruise ship tourists visiting the city (n = 793). The key findings reveal the concentration of tourist activity in the old part of the city, and the similarity in spatial behaviors within the city, while the primary mode of exploration is walking, supported by motorized modes of transfer to access distant attractions. Socio-demographic factors and visit characteristics, such as age, group composition, and expenditure levels, are associated with mobility and spatial behavior. This article adds new evidence on the mobility patterns and spatial behaviors of cruise ship tourists visiting a major tourist city. With better knowledge of where cruise ship passengers concentrate, what activity patterns they show, and their preferred modes of transport, policymakers can manage more effectively the influx during peak times and in high-density areas. Strategies to distribute visitors more evenly across the city could be devised to alleviate pressure on heavily frequented zones. Full article