Search Results (73)

The growth and sustainability of today’s global economy heavily relies on smooth maritime operations. The increasing security concerns to marine environments pose complex security challenges, such as smuggling, illegal fishing, human trafficking, and environmental threats, for traditional surveillance methods due to their limitations. Artificial intelligence (AI), particularly deep learning, has offered strong capabilities for automating object detection, anomaly identification, and situational awareness in maritime environments. In this paper, we have reviewed the state-of-the-art deep learning models mainly proposed in recent literature (2020–2025), including convolutional neural networks, recurrent neural networks, Transformers, and multimodal fusion architectures. We have highlighted their success in processing diverse data sources such as satellite imagery, AIS, SAR, radar, and sensor inputs from UxVs. Additionally, multimodal data fusion techniques enhance robustness by integrating complementary data, yielding more detection accuracy. There still exist challenges in detecting small or occluded objects, handling cluttered scenes, and interpreting unusual vessel behaviours, especially under adverse sea conditions. Additionally, explainability and real-time deployment of AI models in operational settings are open research areas. Overall, the review of existing maritime literature suggests that deep learning is rapidly transforming maritime domain awareness and response, with significant potential to improve global maritime security and operational efficiency. We have also provided key datasets for deep learning models in the maritime security domain. Full article

Detection of small vessels is of great significance for maritime safety assurance, abnormal vessel tracking, illegal fishing supervision, and combating smuggling. However, the radar reflection intensity of small vessels is low, making them difficult to detected with the radar’s constant false-alarm rate (CFAR) algorithm. To enhance the detection capability for small vessels, we propose an improved CFAR scheme. Specifically, we first compared traditional CFAR processing results of radar data with automatic identification system (AIS) data to identify some special targets. These special targets, which possessed AIS information, but remained undetected by radar, enabled an iTransformer model to generate more reasonable CFAR threshold adjustments. iTransformer adaptively lowered the threshold of the areas around these targets until they were detected by radar. This process made it easier to discover the small boats in the surrounding area. Experimental results showed that our method reduces the missed detection rate of small vessels by 73.4% and the false-alarm rate by 60.7% in simulated scenarios, significantly enhancing the CFAR detection capability. Overall, our study provides a new solution for ensuring maritime navigation safety and strengthening illegal supervision, while also offering new technical references for the field of radar detection. Full article

The white snook (Centropomus viridis) is an emerging aquaculture species with high market acceptance, exhibiting catadromous and protandric hermaphroditic characteristics in adulthood. This study aimed to preliminarily characterize certain hematological and biochemical parameters, as well as blood cell morphology, for identifying possible variations between sexes maintained under aquaculture recirculating system (RAS) conditions. The white snook broodstock was anesthetized with clove oil, and biometric values, as well as sex classification, were measured. Then, blood samples were collected from 14 females (7132 ± 1610 g) and 20 males (2200 ± 0.963 g) via caudal vessel puncture to analyze selected hematological parameters, blood biochemistry, and cellular morphology. Fulton’s condition factor (K) showed no differences between sexes, indicating a healthy fish status. Females showed significantly higher serum cholesterol, glucose, and triglyceride levels than males. Also, hematocrit (HCT) and mean corpuscular volume (MCV) were elevated in females. No sex-related differences were observed in red or white cell counts or in blood cell dimensions. Morphological characterization identified erythrocytes, thrombocytes, and three types of leukocytes: lymphocytes (small and large lymphocytes), neutrophils, and monocytes, with no eosinophils or basophils detected in either sex. These findings provide fundamental reference values for the hematological and biochemical profiles of C. viridis broodstock in captivity and highlight sex-specific differences relevant for reproductive and health monitoring. However, it should be considered that the sample size used to establish reference ranges for the species is small, so it is recommended to implement a monitoring plan for this and other broodstocks of this emerging species. Full article

Recently, as carbon emission regulations enforced by the International Maritime Organization (IMO) have become stricter and pressure from the World Trade Organization (WTO) to abolish tax-free fuel subsidies has increased, the demand for electric propulsion systems in the marine sector has grown. Most small domestic fishing vessels rely on tax-free fuel and have limited cruising ranges and constant-speed operation, which makes them well-suited for electric propulsion. This paper proposes replacing the internal combustion engine system of such vessels with an electric propulsion system. Based on real operating conditions, an Interior Permanent Magnet Synchronous Motor (IPMSM) was designed and optimized. The Savitsky method was used to calculate total resistance at a typical cruising speed, from which the required torque and output were determined. To reduce torque ripple, an asymmetric dummy slot structure was proposed, with two dummy slots of different widths and depths placed in each stator slot. These dimensions, along with the magnet angle, were set as optimization parameters, and a metamodel-based optimal design was carried out. As a result, while meeting the design constraints, torque ripple decreased by 2.91% and the total harmonic distortion (THD) of the back-EMF was lowered by 1.32%. Full article

This study investigated the status of anchors for small fishing vessels that correspond with the risk factors of submarine cables, which are essential elements for offshore wind farms. As for target vessels, small coastal fishing vessels of less than ten tons were divided into four categories by tonnage, and 71 locations were compared from a total of 59 fishing vessels. In the results, the shank showed a difference of approximately 18.2% from 119.3 to 145.8 cm on average, while the stock exhibited a difference of approximately 18.9% from 130.3 to 160.6 cm. The size of the anchor, however, was not proportional to the increase in the tonnage of the fishing vessel, and the anchors were produced in their own forms, based on the experience of the crew in many cases. In the statistical processing results, significant differences occurred in all areas except for the fluke. The stock and shank, which affect the dragging anchor, showed significant differences at a level of p < 0.05 while the bill, bill to bill, and bill to shank exhibited differences at a level of p < 0.01. This indicates that standardized criteria are required for the anchors of small coastal fishing vessels of less than ten tons, and that design standards for materials and reinforcements also need to be prepared as thin rebars or wooden columns are used, in addition to steel pipes, as the materials of the stock in many cases. Full article

With the rapid development and accelerated utilization of marine resources, multi-body floating systems have become extensively used in practical applications. This study examines the coupled motions of a side-by-side anchoring system for five fishing vessels in a harbor using ANSYS-AQWA. The system is connected by hawsers and equipped with fenders to reduce collisions between the vessels. It is designed to operate in the sheltered wind-wave combined environment within Ningbo Zhoushan Port, China. Considering the diverse types and quantities of fishing vessels in the anchorage area, this paper proposes a mixed arrangement of three large-scale fishing vessels in the middle and two small-scale vessels on both sides. The time-domain analysis is performed on this system under the combined effects of wind and waves, calculating the motion responses of the five fishing vessels along with the mechanical loads at the hawsers, fenders, and moorings. The results indicate that the maximum loads on these mechanical components remain well within the safe working limits, ensuring reliable operation. In addition, the impact of varying wind-wave angles on the coupled motions of the fishing vessel system are studied. As the wind-wave angle increases, the surge motion of the fishing vessels gradually decreases, while the sway motion intensifies. The forces on the hawsers, fenders, and mooring system exhibit distinct characteristics at different angles. Full article

The existing vacuum fish pump is too large and difficult to move, which is difficult to apply to small fishing vessels. However, the development of a small vacuum fish pump is not a single scaling of the existing vacuum fish pump but requires the support of relevant experiments and simulation theories. In this study, a vacuum fish pump suitable for small fishing vessels was developed. Firstly, a numerical model of the internal flow field during the vacuum fish pump’s working process was established using computational fluid dynamics (CFDs) and verified its effectiveness by physical experiments. It is found that the VOF model can well predict the variation of the volume fraction of the liquid phase in the whole calculation area with time during the suction or drainage process of the vacuum fish pump. Then, the internal flow field characteristics of the fish pump under different working conditions were simulated, and the rationality of the design of the fish pump was evaluated according to the numerical results. Finally, a separate physical experiment was carried out on grass carp, carp, crucian carp, silver carp, and bighead carp, respectively, and the capture efficiency and corresponding fish damage rate for different fish were analyzed. The experimental and numerical results show that the vacuum suction fish pump can achieve efficient and automatic suction and transport of live fish. Full article

The article describes the use of deep neural networks to detect small floating objects located in a vessel’s path. The research aimed to evaluate the performance of deep neural networks by classifying sea surface images and assigning the level of threat resulting from the detection of objects floating on the water, such as fishing nets, plastic debris, or buoys. Such a solution could function as a decision support system capable of detecting and informing the watch officer or helmsman about possible threats and reducing the risk of overlooking them at a critical moment. Several neural network structures were compared to find the most efficient solution, taking into account the speed and efficiency of network training and its performance during testing. Additional time measurements have been made to test the real-time capabilities of the system. The research results confirm that it is possible to create a practical lightweight detection system with convolutional neural networks that calculates safety level in real time. Full article

Understanding the dynamic spatial distribution and characteristics of fishing activities is crucial for fisheries management and sustainable development. In recent years, small pelagic fish and cephalopods in the Arabian Sea have become new targets for light purse seine fishing; however, there is a lack of publicly available reports. This study uses automatic identification system (AIS) data from January to May and October to December of 2021 to 2022 in the region between 58°–70° E and 10°–22° N to extract spatial distribution information through three methods. The results show that with a spatial resolution of 0.25° × 0.25°, the spatial similarity index between the fishing ground information extracted in 2022 and catch data was consistently above 0.60, reaching 0.76 in March 2021 and 0.79 in November 2022, while the spatial similarity index in March 2022 exceeded 0.71. The spatial distribution of fishing effort and kernel density was similar to that of the fishing grounds, and the fishing intensity information exhibited the highest spatiotemporal similarity with commercial catch data, making it more suitable as a substitute for fishery data. Therefore, effective international cooperation and efficient joint management mechanisms for fishing vessels are needed to enhance the regulatory oversight of fishing vessels in this region. Integrating AIS data with other technological methods is crucial for more effective monitoring and management of fishing vessels. The findings presented in this paper provide both quantitative and qualitative scientific support for resource conservation and sustainable development in the region. Full article

The timely and accurate monitoring of high-seas fisheries is essential for effective management. However, efforts to monitor industry fishing vessels in the central-eastern North Pacific have been hampered by frequent cloud cover and solar illumination interference. In this study, enhanced fishing extraction algorithms based on computer vision were developed and tested. The results showed that YOLO-based computer vision models effectively detected dense small fishing targets, with original YOLOv8 achieving a precision (P) of 89% and a recall (R) of 79%, while refined versions improved these metrics to 93% and 99%, respectively. Compared with traditional threshold methods, the YOLO-based enhanced models showed significantly higher accuracy. While the threshold method could identify similar trend changes, it lacked precision in detecting individual targets, especially in blurry scenarios. Using our trained computer vision model, we established a dataset of dynamic changes in fishing vessels over the past decade. This research provides an accurate and reproducible process for precise monitoring of lit fisheries in the North Pacific, leveraging the operational and near-real-time capabilities of Google Earth Engine and computer vision. The approach can also be applied to dynamic monitoring of industrial lit fishing vessels in other regions. Full article

This study proposes an enhanced ship-type classification model that employs a sequential processing methodology integrating hidden Markov model (HMM), deep neural network (DNN), and convolutional neural network (CNN) techniques. Four different ship types—fishing boat, passenger, container, and other ship—were classified using multiple ship trajectory features extracted from the automatic identification system (AIS) and small fishing vessel tracking system. For model optimization, both ship datasets were transformed into various formats corresponding to multiple models, incorporating data enhancement and augmentation approaches. Speed over ground, course over ground, rate of turn, rate of turn in speed, berth distance, latitude/longitude, and heading were used as input parameters. The HMM–DNN–CNN combination was obtained as the optimal model (average F-1 score: 97.54%), achieving individual classification performances of 99.03%, 97.46%, and 95.83% for fishing boats, passenger ships, and container ships, respectively. The proposed approach outperformed previous approaches in prediction accuracy, with further improvements anticipated when implemented on a large-scale real-time data collection system. Full article

Background: Understanding the causal relations between dietary habits and stroke is crucial for prioritizing public health interventions and developing effective health strategies. This study utilized Mendelian randomization (MR) analysis to examine the causal associations between 20 dietary habits and various stroke subtypes, aiming to identify potential mediators and evaluate the proportions of mediation. Methods: A two-sample MR analysis was conducted to examine the causal relationships between dietary habits and stroke incidence. Mediation analysis, two-step MR (TSMR), and multivariable MR (MVMR) were employed to identify potential mediators. Genetic data pertaining to dietary habits and stroke were obtained from extensive genome-wide association study (GWAS) consortia. The inverse variance-weighted (IVW) method served as the primary analytical approach, with the additional scrutiny of significant correlations conducted through the Egger regression, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO), and weighted median techniques. Results: Our analyses indicated that genetically predicted intakes of dried fruits, cheese, cereal, oily fish, and hot drink temperatures were protective against stroke, whereas higher intakes of lamb/mutton, poultry, and added salt significantly elevated stroke risk. Specifically, dried fruit consumption demonstrated a protective effect against total stroke (β = −0.009, p = 0.013), ischemic stroke (β = −0.475, p = 0.003), and small-vessel ischemic stroke (β = −0.682, p = 0.033) through reductions in BMI levels, accounting for mediated proportions of 3.2%, 17.1%, and 8.5%, respectively. Furthermore, cheese intake provided a protective effect against ischemic stroke (β = −0.275, p = 0.003) by decreasing BMI and increasing HDL-C levels, with mediated proportions of 30.5% and 6.5%. Together, BMI and HDL-C accounted for 34.9% of the beneficial effect of cheese intake on reducing the risk of ischemic stroke. In contrast, an increased salt intake exhibited a positive association with large-artery ischemic stroke (β = 0.432, p = 0.033) through BMI elevation, with a mediated proportion of 10.9%. Conclusions: Our findings provide compelling evidence supporting causal relationships between dietary habits and stroke subtypes, while identifying mediators and evaluating the proportions of mediation. Adhering to a low-calorie, nutrient-dense diet enriched with dried fruits, cheese, and cereal, along with reduced salt and poultry consumption, could potentially mitigate stroke risk. Full article

Sea fog reduces visibility to less than 1 km and is a major cause of maritime accidents, particularly affecting the navigation of small fishing vessels as it forms when warm, moist air moves over cold water, making it difficult to predict. Traditional visibility measurement tools are costly and limited in their real-time monitoring capabilities, which has led to the development of video-based algorithms using cameras. This study introduces the Approximating and Eliminating the Airlight–Reduced DCP (AEA-RDCP) algorithm, designed to address the issue where sunlight reflections are mistakenly recognized as fog in existing video-based sea fog intensity measurement algorithms, thereby improving performance. The dataset used in the experiment is categorized into two types: one consisting of images unaffected by sunlight and another consisting of maritime images heavily influenced by sunlight. The AEA-RDCP algorithm enhances the previously researched RDCP algorithm by effectively eliminating the influence of atmospheric light, utilizing the initial stages of the Dark Channel Prior (DCP) process to generate the Dark Channel image. While the DCP algorithm is typically used for dehazing, this study employs it only to the point of generating the Dark Channel, reducing computational complexity. The generated image is then used to estimate visibility based on a threshold for fog density estimation, maintaining accuracy while reducing computational demands, thereby allowing for the real-time monitoring of sea conditions, enhancing maritime safety, and preventing accidents. Full article

With an estimated 32,000 annual fatalities, fishing vessel accidents are 100-fold deadlier than those involving merchant ships. Despite ongoing safety training, accident rates remain high. Since most fishing vessel accidents occur in small fishing vessels (<12 m) and are primarily attributable to human elements, this study focuses on small fishing vessel accidents where the human element is the primary cause, exploring preventive measures for major accident types and performing a type-specific risk assessment. First, we performed a quantitative analysis of frequently occurring accidents and the indirect factors influencing the human element using maritime accident statistics and surveys, respectively. Next, we employed the fault tree analysis technique proposed by the International Maritime Organization in its Formal Safety Assessment to quantitatively assess the rate of accidents caused by the human element attributable to various indirect factors. The primary indirect factors most significantly impacting the human element were ship factors (22.8%), people factors (18.9%), and organization on board (17.4%). Secondary factors included personal negligence (14.1%), aging equipment and poor maintenance (10.3%), and harsh natural conditions such as rough waves (9.6%). Eliminating the top three secondary indirect factors reduced accidents due to the human element by 15.4% (64.5−49.1%). Full article

This study presents new records of three Critically Endangered angel shark species (Family: Squatinidae) occurring in the Eastern Mediterranean—Smoothback Angelshark S. oculata Bonaye, 1840, Sawback Angelshark S. aculeata Cuvier, 1829, and Angelshark S. squatina (Linnaeus, 1758). The supporting data serves to highlight three potential Critical Angel Shark Areas (CASAs) in Türkiye: Fethiye Bay, Çanakkale Strait (i.e., Dardanelles), and Antalya Bay. These data also demonstrate that female S. oculata may mature at a smaller size than prior published estimates of length at first maturity. This new dataset provides details of 23 S. squatina specimens, 52 S. oculata specimens, and 5 S. aculeata specimens, totalling 80 recent angel shark specimens found in Turkish waters mostly sent to us from small-scale fishers who had incidentally caught angel sharks. Also presented are four capture-induced parturition events in Turkish waters onboard fishing vessels, thus providing details on internal yolk sacs, reproductive habitats, and indications of spawning season. Our dataset presented here spans from 2018 to 2023 and suggests that mature adults of S. squatina and S. oculata still occur in Turkish waters, in Fethiye Bay and Çanakkale, respectively. Due to elevated chances of fishers encountering Critically Endangered angel sharks in Türkiye, we suggest that fishers are trained in handling and safe-release methods, to ensure reduced incidents of capture-induced parturition, and improved post-release survival. This study demonstrates that bottom set nets set by small-scale fishers pose less risk to mortality for angel sharks as they are almost always encountered alive after a usual 12 h soak time, suggesting that bottom trawling in critical habitats should be better regulated (or phased out) to help improve national angel shark conservation initiatives. Full article