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This study develops a novel non-parametric vibration-based deep learning technique to detect and diagnose damage to coastal structures, whereas wharves and jetties are the selected objects. To overcome the challenges of a large number of sensor points, we connect the sensor values at each location into a map containing ridges first, then we combine the Fast Marching Algorithm (FMA) with a Single-input Convolutional Neural Network (SCNN) to propose an FMA-SCNN method. Therefore, the created ridge images are processed with the SCNN to determine the parameters of deviation from the alarm state. During the testing phase, the optimization function’s Multiple Damage Guarantee Criteria (MDGC) is maximized by the set of damage variables offered for assessment, based on the dissimilarity coefficient Dw between the maps and the acceleration of the ridge tops. Also, the damage level DH(χ) allows us to accurately evaluate the structure’s current state, from healthy to serious levels. In comparison to previous CNN applications, the proposed algorithms demonstrated outstanding efficiency and achieved the highest accuracy of 98.26 % on embedded Python 3.6 testing. After applying the FMA-SCNN, the optimization function of MDGC enables early damage prediction, helping evaluate the overall structure effectiveness. [ABSTRACT FROM AUTHOR]

Based on multi-station spatial diversity capability, GEO-UAV distributed radar could achieve high-precision aerial target localization with the single-transmitting and multiple-receiving configuration. However, the actual observation area can hardly be covered by several receiving stations simultaneously. Thus, it is necessary to explore a novel target localization method under a single receiving station condition. In this manuscript, an aerial target localization method with GEO-UAV bistatic configuration is presented, where ТOА and AOA measurements are employed. Firstly, measurement models, including bistatic range-delay, pitching AOA, and azimuth AOA, are established using the spatial geometric relationship between the bistatic radar and the target. Then, the receiving range can be estimated using digital beamforming technology based on the receiving array antenna, where the antenna beam coverage information and the prior target altitude information are combined. Finally, the three-dimensional target localization is skillfully derived according to the bistatic configuration, and thus to avoid the parameter unrecognizable problem caused by insufficient degrees of freedom. The proposed algorithm fully exploits the intrinsic correlation characteristics between the measurement information and the bistatic configuration, which provides an effective way for aerial target localization. Simulation results verify the effectiveness of the proposed algorithm.

Detecting oil spills in marine environments is crucial for avoiding environmental damage and facilitating rapid response efforts. In this study, we propose a robust method for oil spill detection leveraging state-of-the-art (SOTA) deep learning techniques. We constructed an extensive dataset comprising images and frames extracted from video sourced from Google, significantly augmenting the dataset through frame extraction techniques. Each image is meticulously labeled to ensure high-quality training data. Utilizing the Yolov8 segmentation model, we trained our oil spill detection model to accurately identify and segment oil spills in ocean environments. K-means and Truncated Linear Stretching algorithms are combined with trained model weight to increase model detection accuracy. The model demonstrated exceptional performance, yielding high detection accuracy and precise segmentation capabilities. Our results indicate that this approach is highly effective for real-time oil spill detection, offering a promising tool for environmental monitoring and disaster management. In training metrics, the model reached over 97% accuracy in 100 epochs. In evaluation, model achieved its best detection rates by 94% accuracy in F1, 93.9% accuracy in Precision, and 95.5% mAP@0.5 accuracy in Recall curves. [ABSTRACT FROM AUTHOR]

Offshore wind energy production has seen a significant expansion in recent years. With technologies rapidly improving and prices dropping, it is now one of the key instruments in the green energy transition. The implications of offshore wind farm expansion for maritime security and ocean governance have, so far, received sparse attention in the literature. This article offers one of the first thorough analyses of the security of offshore wind farms and related installations, such as underwater electricity cables, energy islands, and hydrogen plants. The technical vulnerabilities of wind farm systems is reviewed and threats from terrorism, crime and State hostilities, including physical and cyber risk scenarios, are discussed. The expansion of green offshore energy production must keep pace with the changing threat landscape that follows from it. Prospective solutions for the protection of wind farms systems, including surveillance, patrols and self-protection are discussed. The current repertoire of maritime security solutions is in many ways capable of dealing with the threats and risks effectively if adjusted accordingly. The analysis builds important new bridges between debates in energy security and maritime security, as well as the implications of climate change adaption and mitigation for security at sea. [ABSTRACT FROM AUTHOR]

Detecting oil spills in marine environments is crucial for avoiding environmental damage and facilitating rapid response efforts. In this study, we propose a robust method for oil spill detection leveraging state-of-the-art (SOTA) deep learning techniques. We constructed an extensive dataset comprising images and frames extracted from video sourced from Google, significantly augmenting the dataset through frame extraction techniques. Each image is meticulously labeled to ensure high-quality training data. Utilizing the Yolov8 segmentation model, we trained our oil spill detection model to accurately identify and segment oil spills in ocean environments. K-means and Truncated Linear Stretching algorithms are combined with trained model weight to increase model detection accuracy. The model demonstrated exceptional performance, yielding high detection accuracy and precise segmentation capabilities. Our results indicate that this approach is highly effective for real-time oil spill detection, offering a promising tool for environmental monitoring and disaster management. In training metrics, the model reached over 97% accuracy in 100 epochs. In evaluation, model achieved its best detection rates by 94% accuracy in F1, 93.9% accuracy in Precision, and 95.5% mAP@0.5 accuracy in Recall curves.

This paper presents the improvement of the wave maker control system. The wave maker is a facility widely used in hydromechanics laboratories to generate waves in towing tanks. It is equipped with an electrohydraulic drive and an actuator submerged into water. The waves are generated to model the environmental conditions for physical experiments, performed on reduced-scale models of maritime objects. The physical experiments allow to predict the behaviour of full-scale objects and prove the results of numerical analyses. The overriding goal of the fluid dynamics experiments is to improve the human safety and survivability of constructions. The reported investigation and application works were vital for the improvement of physical model tests. The optimization of the proportional controllers was performed in terms of the Integral of Squared Error (ISE). The final evaluation was performed in terms of the frequency response characteristic. The results of the proportional control optimization were evaluated versus the previously applied control. The experimental research was conducted in the real towing tank located at the Maritime Advanced Research Centre. The investigation has shown the advantage of the ISE optimized conventional proportional control. It has particularly proven the affordability and swiftness of the optimization process. It also proved a more efficient frequency response of the wave maker obtained within a required and reasonable lead time. The performed investigation has greatly contributed to the development of a new method of physical experiments in white noise waves. The results related to this new more efficient method are presented as well.

Rip currents are like rivers of fast-moving water that can quickly carry the unwary out to sea. They are not easy to recognize, especially to the untrained observer. Other than in-situ current measurements, there exists a number of methods that analyzes images and videos to detect rip currents. Most of these techniques base their detection on the appearance of rip currents such as foamy pattern, discoloration of water, and locations of breaking waves. Leading methods use either image processing or machine learning of images and/or video input. In this paper, we analyze the behavior of water movement rather than simply its appearance to detect rip currents. Specifically, we investigated several flow visualization methods and tune them to detect rip currents. Based on our study, we recommend two methods that allowed us to detect rip currents where other methods have failed. And because the methods originated as visualization techniques, any presence of rip currents are automatically highlighted. We also evaluated these two methods against previously annotated results by rip current experts, and found that our detections were sufficiently sensitive that some expert annotations were relabeled.

Maneuvers of human-operated and autonomous marine vessels in the safety zone of drilling rigs, wind farms and other installations present a risk of collision. This article proposes an algorithmic toolkit that ensures maneuver safety, taking into account the restrictions imposed by ship dynamics. The algorithms can be used for anomaly detection, decision making by a human operator or an unmanned vehicle guidance system. We also consider a response to failures in the vessel’s control systems and emergency escape maneuvers. Data used by the algorithms come from the vessel’s dynamic positioning control system and positional survey charts of the marine installations. [ABSTRACT FROM AUTHOR]

The diversity and non-uniformity of the positioning systems available in maritime navigation systems often impede the watchkeeping officer in the selection of the appropriate positioning system, in particular, in restricted basins. Thus, it is necessary to introduce a mathematical apparatus to suggest, in an automated manner, which of the available systems should be used at the given moment of a sea trip. Proper selection of the positioning system is particularly important in integrated navigation systems, in which the excess of navigation information may impede the final determinations. In this article, the authors propose the use of the decision-robustness function to assist in the process of selecting the appropriate positioning system and reduce the impact of navigation observations encumbered with large errors in self-positioning accuracy. The authors present a mathematical apparatus describing the decision function (a priori object), with the determination of decision-assistance criteria, and the robustness function (a posteriori object), with different types of attenuation function. In addition, the authors present a computer application integrating both objects in the decision-robustness function. The study was concluded by a test showing the practical application of the decision-robustness function proposed in the title. [ABSTRACT FROM AUTHOR]

The normal functioning of the respiratory system is a leading factor, both for the survival of people caught in an aquatic environment in a marine casualty and for the effectiveness of the assistance activities. In view of this, in 2020 a team of researchers from Varna Medical University, the Naval Academy Varna and the Bulgarian Red Cross set out to study some physiological respiratory parameters and related anthropometric data of 51 individuals, 41 men and 10 women aged between 17 and 48 years of age. The subjects were divided into two groups: 1) trainees in the water rescue courses conducted at BRC-Varna and 2) 1st - year students of the Naval Academy. All participants in the study are non-smokers. The examination of the respiratory indicators is performed according to a standardized methodology with the same spirometer, which is able to measure and register over 30 indicators. Of these, three were analyzed in the present study: forced expiratory volume for 1 s (FEV1), forced vital capacity (FVC), and their FEV1/FVC percentage (Tiffeneau index). The results show that, according to anthropometric data, FVC and FEV1 are higher in water rescue trainees than in Naval Academy cadets. The Tiffeneau index is higher than the reference values ​​of the participants in both study groups, but the results are better in the group of naval cadets. As far as the functional capabilities of the respiratory system are essential for the activity of marine professionals, it can be assumed that the high results obtained from the spirometric examination of the participants from both groups are a prerequisite for higher efficiency of rescue operations and improvement of their personal safety. when working in a marine environment. The prospect is that after collecting a statistically significant amount of data combined with results obtained from other types of functional tests, to create better safety practices for people who are professionally engaged in maritime activities. As far as the functional capabilities of the respiratory system are essential for the activity of marine professionals, it can be assumed that the high results of the spirometric study in all study participants are a prerequisite for improving both their personal safety when working in the marine environment and for higher efficiency and success of rescue operations. The perspective is, after collecting a statistically significant volume of data and in combination with other functional studies, to create good practices to improve the safety systems of people in contact with the marine environment .

Joint aeronautical and maritime search and rescue is the most effective way of performing rescues at sea. The value and effectiveness of a search and rescue (SAR) are far greater when using a coordinated air-maritime search than when using only vessels or aircraft. However, the harmonization of aeronautical and maritime SAR is complex and potentially life-threatening. When the location of the target in distress is unknown, the search process must be carried out. As the sole way to locate and rescue survivors, the search process is the most costly, hazardous, and complicated part of the whole SAR operation. This article focuses on the key problem of the optimal selection of search facilities, that is often encountered in large-area maritime search practice and urgently needs to be solved in joint aeronautical and maritime search operations. The problem may be abstracted into an optimization model with vessel and aircraft quantitative constraints that fully considers the area of the sea region to be searched, maximum speeds, search capabilities, initial distances of vessels and aircraft from the search area, and maximum endurance of aircraft. By introducing 0-1 decision variables, the search facility selection can be judged and optimized directly and effectively. By analyzing the results with different vessel and aircraft quantities, and taking the relationship between search coverage time and the number of search facilities (cost) into account, the optimal (most economic and feasible) search facility selection scheme can be produced.

This paper aims to present an approach to investigate cyber risk perception with use of recognized psychological models, and to give an overview of state-of-the-art research within the field of cyber risk perception in general and in the context of the maritime domain. The focus will be on determinative dimensions within the psychometric paradigm and cognitive biases, and to give recommendations on further research within these fields. Okoli and Schabram’s eight-step guide to plan, select, extract, and execute a systematic literature review is used as guidance. The search process resulted in 25 relevant articles which describes 24 dimensions of cyber risk perception in different online environments. Research within the area of maritime cyber security is increasing, however, no studies relevant for our literature review were found within the maritime domain. The nine dimensions in the psychometric model, perceived benefit and the optimistic bias is presented and discussed in a maritime context. Cyber risk perception is a complex research-area where both determinative factors and other cognitive processes can be influenced by each other. This can indicate that the dimensions differ across populations and professions, creating grounds for why context-specific studies are important. Further research may benefit from more multidisciplinary, descriptive, and inductive approaches, and contextual studies within maritime cyber risk perception can contribute to develop targeted tools for risk mitigation to enhance safety at sea.

The development of coastal infrastructure and related maritime transport necessitatesthe intensification of vessel traffic monitoring. Navigation systems used in this research are traditionally based on the information transmitted by radio waves. Marine traffic safety requires constant supervision carried out by dedicated systems, the operation of which may be limitedby difficult environmental conditions. The possibilities of supporting navigation systems with underwater observation systems are explored here. The research was carried out using an underwater measurement system. Local disturbances of the hydroacoustic and hydrodynamic field from the moving vessels were analysed. The potential for identifying a moving vessel, for example for offshore infrastructure security purposes, is demonstrated.

In order to efficiently cover maritime areas at over the horizon (OTH) distances and thus increase marine safety in a nation's exclusive economic zone (EEZ), a network of maritime sensors built around High Frequency Surface Wave Radars (HFSWR) can be an excellent choice. The critical parameter for success of the deployed sensor network is a real time tracking of all detected vessels. During the tracking process, data association (DA) is the first step and it defines the complexity and thus the speed of the whole tracking process. This paper presents a density based clustering DA procedure where the cluster complexity determines the applied DA procedure within the cluster itself. It is demonstrated that the great majority of clusters (over 98 % of all clusters in the worst case) may be processed in a timely manner with an optimal DA procedure, or more precisely, a Joint Probability Data Association (JPDA). However, a small number of unusually large clusters (less than 2 % of all clusters) requires the application of a sub-optimal DA procedure, more accurately, the Roecker's suboptimal JPDA algorithm, in order to maintain real time performance of the whole tracking process. Moreover, unlike standard JPDA procedure which tends to be inapplicable for real time tracking in heavily cluttered environment, the density based clustering DA procedure presented here provides real time performances in the very same environment. The whole analysis is done on real HFSWR data obtained from two HFSWR, located in the Gulf of Guinea. The data set used for the experiments includes data obtained during a month and a half of constant HFSWR operation.

In this paper, an area decomposition algorithm is presented that is suitable for multiple vessels and multiple aircraft participating in maritime searches over a large region. The algorithm can decompose the entire sea region to be searched (deemed as polygonal area) into nonoverlapping subpolygons (search subareas) according to the sizes of the areas covered by various search facilities while considering their search capabilities as well as their corresponding commence search points. The algorithm draws on the concept of a polygon division algorithm in computational geometry. The main novelty in this study is the optimization of the classic polygon division algorithm by introducing a “maximizing-minimum-angle” strategy, which can effectively compensate for the deficiency of the traditional algorithm, as reflected in the area decomposition result. This improved algorithm can produce rectangle-like subareas, especially for a rectangular search region, which is commonly used in maritime search operations. For nonrectangular search regions, a right-angle division can be achieved so that the shapes of the search subareas are more conducive to planning specific search routes for search facilities. Fast maritime search coverage over a large region can be achieved. The effectiveness of the algorithm is validated by comparing decomposition results before and after the improvement.

Coral reefs are the sub-aqueous calcium carbonate structures collected by the invertebrates known as corals. The charm and beauty of coral reefs attract tourists, and they play a vital role in preserving biodiversity, ceasing coastal erosion, and promoting business trade. However, they are declining because of over-exploitation, damaging fishery, marine pollution, and global climate changes. Also, coral reefs help treat human immune-deficiency virus (HIV), heart disease, and coastal erosion. The corals of Australia’s great barrier reef have started bleaching due to the ocean acidification, and global warming, which is an alarming threat to the earth’s ecosystem. Many techniques have been developed to address such issues. However, each method has a limitation due to the low resolution of images, diverse weather conditions, etc. In this paper, we propose a bag of features (BoF) based approach that can detect and localize the bleached corals before the safety measures are applied. The dataset contains images of bleached and unbleached corals, and various kernels are used to support the vector machine so that extracted features can be classified. The accuracy of handcrafted descriptors and deep convolutional neural networks is analyzed and provided in detail with comparison to the current method. Various handcrafted descriptors like local binary pattern, a histogram of an oriented gradient, locally encoded transform feature histogram, gray level co-occurrence matrix, and completed joint scale local binary pattern are used for feature extraction. Specific deep convolutional neural networks such as AlexNet, GoogLeNet, VGG-19, ResNet-50, Inception v3, and CoralNet are being used for feature extraction. From experimental analysis and results, the proposed technique outperforms in comparison to the current state-of-the-art methods. The proposed technique achieves 99.08% accuracy with a classification error of 0.92%. A novel bleached coral positioning algorithm is also proposed to locate bleached corals in the coral reef images. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to develop a customized diving computer that is interlocked with a textile type sensor attached to a suit to enhance the safety factor of a diver and a monitoring system to help diver safety management. The development of this diving computer is largely divided into three stages. The first is to develop a function to check the status of the diver in conjunction with the textile type wearable sensor attached to the suit. Second, the development of a diving computer is based on Android OS based on the existing closed OS. The third is the development of actual diving computer hardware focusing on waterproof function. This course aims to focus on safety factors of the diver, to collect biometric information through a wearable sensor attached to the diver suit, to analyze it in the diving computer, and to provide a customized diving guide. The performance evaluation of the result was conducted through the usability evaluation of the diving computer, and the safety and efficiency were verified through the overall satisfaction and the functional evaluation of 92.7%. Future research will focus on the safety factors to ensure differentiation from the existing products, and we will carry out ongoing research.

The diversity and non-uniformity of the positioning systems available in maritime navigation systems often impede the watchkeeping officer in the selection of the appropriate positioning system, in particular, in restricted basins. Thus, it is necessary to introduce a mathematical apparatus to suggest, in an automated manner, which of the available systems should be used at the given moment of a sea trip. Proper selection of the positioning system is particularly important in integrated navigation systems, in which the excess of navigation information may impede the final determinations. In this article, the authors propose the use of the decision-robustness function to assist in the process of selecting the appropriate positioning system and reduce the impact of navigation observations encumbered with large errors in self-positioning accuracy. The authors present a mathematical apparatus describing the decision function (a priori object), with the determination of decision-assistance criteria, and the robustness function (a posteriori object), with different types of attenuation function. In addition, the authors present a computer application integrating both objects in the decision-robustness function. The study was concluded by a test showing the practical application of the decision-robustness function proposed in the title.

Maritime transportation which mediates the transmission of major part of the world's trading volume is a type of transportation with high probability of encountering dangerous situations due to the instability of its conditions. In the past years, it became clear that the even smallest negativity caused perilous results. Thus, accurate implementation and evaluation of sea accident analysis is important to establish a policy for developing preventive measures and increasing awareness by determining the reason of accident. Analysis of sea accidents forms the fundamental subject of the study with data mining method which allow us to make estimated and definitive interpretations with computer programs by accessing significant information within large data stacks. In this study sea accidents occurring in Turkish territorial waters have been reviewed. In this context, the purpose of the study consists of determining which factors conduct together in sea accidents by association rule which is one of analysis methods of data mining. As a result of analysis, it has been determined that ship's loading condition, existence of maritime pilot in the ship, conditions of equipments such as bow thruster and quarterdeck thruster, ship flag and type and meteorological elements have been effective factors on the subject. [ABSTRACT FROM AUTHOR]

The Drake Passage is an ocean area between South America and Antarctica with very extreme wind and wave climates. The quality of forecasts of surface winds and significant wave heights is analyzed in the present paper, in order to study the error and distribution of model uncertainties as a function of forecast range, severity, location, and numerical model. The operational metocean forecasts selected are run twice a day by the Brazilian Navy and the forecast horizon analyzed is five days. A period of 1 year (2017) is considered for the assessment. Observations consist of four satellite missions: JASON2, JASON3, CRYOSAT, and SARAL. The atmospheric models with 10-m winds are Global Forecast System (GFS) and Icosahedral Nonhydrostatic Model (icon). They are used as inputs to force the wave model WAVEWATCH III with a mosaic of two grids. Results show that under calm to moderate conditions, within the first 2 days of forecast, the wind and wave model skill is very high. However, above the 90th percentile and beyond the third forecast day, the predictability drops significantly. It highlights specific contours of forecast range versus percentiles where the wind and wave modelers should focus, in order to anticipate and to improve the predictability of extreme events at the Drake Passage. [ABSTRACT FROM AUTHOR]

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Coral reefs are the sub-aqueous calcium carbonate structures collected by the invertebrates known as corals. The charm and beauty of coral reefs attract tourists, and they play a vital role in preserving biodiversity, ceasing coastal erosion, and promoting business trade. However, they are declining because of over-exploitation, damaging fishery, marine pollution, and global climate changes. Also, coral reefs help treat human immune-deficiency virus (HIV), heart disease, and coastal erosion. The corals of Australia’s great barrier reef have started bleaching due to the ocean acidification, and global warming, which is an alarming threat to the earth’s ecosystem. Many techniques have been developed to address such issues. However, each method has a limitation due to the low resolution of images, diverse weather conditions, etc. In this paper, we propose a bag of features (BoF) based approach that can detect and localize the bleached corals before the safety measures are applied. The dataset contains images of bleached and unbleached corals, and various kernels are used to support the vector machine so that extracted features can be classified. The accuracy of handcrafted descriptors and deep convolutional neural networks is analyzed and provided in detail with comparison to the current method. Various handcrafted descriptors like local binary pattern, a histogram of an oriented gradient, locally encoded transform feature histogram, gray level co-occurrence matrix, and completed joint scale local binary pattern are used for feature extraction. Specific deep convolutional neural networks such as AlexNet, GoogLeNet, VGG-19, ResNet-50, Inception v3, and CoralNet are being used for feature extraction. From experimental analysis and results, the proposed technique outperforms in comparison to the current state-of-the-art methods. The proposed technique achieves 99.08% accuracy with a classification error of 0.92%. A novel bleached coral positioning algorithm is also proposed to locate bleached corals in the coral reef images.

To enhance the immediacy and accuracy of search and rescue missions conducted by Taiwan Coast Guard Administration (TCGA), this study examines the characteristics of ocean currents and estimates the drifting trajectory of objects for two cases of marine incidents. Two methods are used to predict object's drift tracks: the first one is simply calculating the advection driven by currents and the second method adopts a Monte Carlo based software, SARMAP. Ocean currents data from a high-frequency radar system comprised of 18 radar units surrounding Taiwan supplemented by bottom-mounted Acoustic Doppler Current Profilers (ADCP) data and wind data are used as the primary oceanic environment data. The estimated ending points of drifting for both cases of missing persons in water by using both methods are consistent with the actual recovery locations. Our analyses demonstrate that ocean currents data, if properly used, can be very useful for rapid response in marine search and rescue. [ABSTRACT FROM AUTHOR]

Vessel risk analysis is critical for safe ship navigation and maritime safety management. Near-miss collisions by ships comprise an significant risk, which may be complicated by factors, such as the ship conditions, waterway environment, and driving behavior of any ships encountered. Previous studies have rarely considered how to automatically and adaptively estimate the risk of near-miss collisions for different situations, particularly in port areas. In this paper, we propose an automatic identification system-based approach for adaptively calibrating near-miss collision risk model and assessing a ship’s near-miss collision risk by using the vessel’s speed and course patterns to obtain a robust estimate of the collision risk. Six measures are employed to determine the hierarchical geographical distribution of the near-miss collision risk for ships in port areas and to identify the high-risk areas. Some predicted high-risk areas were validated as official precautionary areas in the Xiamen Port area. All predicted areas may help the port administration to plan monitoring areas to ensure safe traffic flow in the port. [ABSTRACT FROM AUTHOR]

In this study, numerical simulations are conducted in order to analyze the capsizing of roll-on/roll-off passenger ship, Sewol, which occurred on 16 April 2014. Since little is known about the reason of ship capsize, numerical simulation aims to the finding of possible scenarios which can cause this tragic accident. To this end, 4-degree-of-freedom (surge, sway, yaw, and roll motions) maneuvering equations are solved. The hydrodynamic coefficients obtained from a similar ship are applied and the WISH-Maneuver program of Seoul National University is used to perform the numerical simulation. The present analysis utilizes the probabilistic approach, which considers various physical variables and involves the simulation of a large number of cases using different combinations of the variables. The total number of simulation cases is over 70 millions, and the simulation results that are close to the conditions of the actual accident situation are selected. Through this process, the effects of the simulation variables are investigated and the potential causes of the accident are identified. The results show the hydrostatic instability of the ship in the operational condition owing to cargo overload and insufficient ballast water, which raised the vertical center of gravity. The reduced stability combined with large starboard steering angle and cargo movement during large heel may have been the decisive reason of capsizing. [ABSTRACT FROM AUTHOR]

This study investigated the factors influencing the implementation of a port state control (PSC) system. The analytical hierarchy process (AHP) was employed to develop a framework including 4 dimensions and 14 factors for assessing the priority of the major factors and subfactors. An expert questionnaire was conducted in Taiwan. The priority levels of the factors in influencing PSC operation are presented herein. In addition, conclusions were derived from an empirical case study of Taiwan. Some challenges are also discussed to reveal the common problems and special difficulties faced by independent PSC regimes that remain excluded from regional memoranda of understanding.

A very significant number of marine accidents occur because of human errors. This study aimed to prevent ship collisions by identifying types of navigators’ errors. Based on Reason’s classification theory, the possible human errors are classified into skill-based slips (SBSs) (errors caused by the lack of skills), rule-based mistakes (RBMs) (errors caused by the misapplication of rules), and knowledge-based mistakes (KBMs) (errors caused by the lack of navigator’s knowledge). For this study, a scenario-based experiment using a ship-handling simulator was conducted with 50 recruited student navigators. The results revealed two primary human errors of accidents, namely lack of knowledge and misapplication of rules. The results suggest that a collision can be minimized when a navigator has sufficient knowledge of an appropriate course of action and a deep understanding of safety rules. Accidents cannot be prevented by identifying errors, but steps can be taken to narrow the knowledge gap. Based on the results, we proposed a simulation training on navigator error in an unfamiliar situation. The results are expected to reduce errors in the maritime sector using a human-centric work system.

The reliability of marine diesel engines is extremely important for a safe navigation. For the condition monitoring of diesels engines, the independent component analysis (ICA) has been proven to be effective in separating useful vibration sources from the engine vibration signals. However, ICA still needs expert knowledge to identify the source of interest. To avoid human factors in ICA, an automatic vibration-source extraction and feature visualization method is proposed in this paper for fault detection of marine diesel engines. In this method, the Stockwell transform was used to construct a time-frequency reference signal to guide the separation process of the kernel ICA. Only the fault-related source was separated by this improved time-frequency supervised kernel ICA (TFSKICA). Then the t-distributed stochastic neighbor embedding (t-SNE) was employed to extract and visualize the fault features. Lastly, the extreme learning machine (ELM) based classifier was built to identify the engine faults in an intelligent manner. Experimental data acquired from a commercial diesel engine was used to evaluate the performance of the proposed method. The analysis results demonstrate that the TFSKICA is able to separate the vibration source of interest for distinct fault feature extraction by the t-SNE in a visualization manner. The fault recognition rate of the proposed method is also better than that of some existing approaches. [ABSTRACT FROM AUTHOR]

Seafarers are required to make quick decisions to avoid accidents in case of emergencies. However, officers with anxiety generally have a high probability of making wrong decisions that threaten safety and security during the voyage. With the help of a shiphandling simulator, this study aims to investigate the emotional changes of seafarers under simulated scenarios of emergencies. The State-Trait Anxiety Inventory (S-TAI) scale and electrocardiograph (ECG) signal are adopted to evaluate the emotions of the participant seafarers. To classify the anxiety state of the participants, a support vector machine-based method is applied to establish an anxiety recognition model. Classification results reveal that this proposed model can effectively identify different emotions of participants based on ECG features (cross-validation accuracy: 86.0%; test accuracy: 92.3%). The experimental results show that poor visibility could cause the greatest impact on the anxiety of seafarers. In addition, navigational officers and marine pilots react differently in case of emergencies. Seafarers tend to experience more anxiety when dealing with emergency situations, while marine pilots experience more anxiety during multi-ship encounter periods. Consequently, the findings of this study aid to effectively identify the scenarios that cause anxiety emotion of different professional seafarers, providing the corresponding reference for the training of seafarers. This could help prevent catastrophic accidents that pose a threat to oceans and coasts caused by human error. [ABSTRACT FROM AUTHOR]

This study reveals the most important role of effective marine accident investigation in the improvement of maritime safety through prevention similar casualties from occurring in the future, explores the legal obligations of all parties under different international maritime conventions, and codes. As most of marine accidents resulted from shortage in applying international regulations related to maritime safety, so this research determines, the shortage of application of the international regulations adopted by IMO related to maritime safety, and the shortage of legal measures to support safety at sea and protection or reduce marine pollution. This research also aims to improve special measures for procedures of marine accident investigation, with case study are highlighted, and the importance of identifying the liability. Finally the shortage of civil liability of damage resulting from marine accident under International and National Jurisdiction are discussed with some illustrative cases.

Acharya, T.D.; Yoo, K.W., and Lee, D.H., 2017. GIS-based spatio-temporal analysis of marine accidents database in the coastal zone of Korea. In: Lee, J.L.; Griffiths, T.; Lotan, A.; Suh, K.-S., and Lee, J. (eds.), The 2nd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 79, pp. 114-118. Coconut Creek (Florida), ISSN 0749-0208. Maritime transportation, including the use of boats, ferries and ships for the transportation, fishing and recreational activities, currently plays an important factor in global economy and is increasing annually. With increase of maritime transportation, the occurrences of marine accident are also increased. Based on worldwide statistical database of marine accidents, Marine Casualties and Incidents (MCI) module published by Global Integrated Shipping Information System (GISIS), the second highest number of accidents have occurred in the coastal zone around East Asian countries, China, Japan and Korea. Especially in Korea, there are many major accidents such as sinking, collision, capsizing, stranding, grounding and explosion etc. which can cause huge damage of human life and property. This study analyses the spatial distribution of marine accidents in more details for coastal zone of Korea in order to illustrate and predict the vulnerable coastal zone for improving costal safety management, planning and decision making. A detailed database with major and minor accidents around coastal zone in Korea collected by the office of Korea Coast Guard (KCG) from 2007 to 2014 were used for the geo-spatial analysis in Geographic Information System (GIS) environment. Two types of spatial analysis, Buffer and Cluster analysis, were performed to visualize the distribution of marine accidents and then to determine the high accident and safety deficient areas. The results from this study can help to determine the common reasons of marine accidents in the coastal zone of Korea, with high vulnerable zone of accident, for risk management, accident prevention and response planning in the future. [ABSTRACT FROM AUTHOR]

In a maritime domain awareness scenario, two main areas of interest can be recognized, specifically harbour protection and navigation safety. Harbour protection is currently a main concern and it is aimed at controlling the risk associated with possible attacks or illegal activities which can take place in the marine access areas. On the other hand, the objectives of the navigation safety are essentially connected to achieve an improved maritime navigational awareness by providing information on collision avoidance and general guidance to the navigators [1]. [ABSTRACT FROM PUBLISHER]

This study reveals the most important role of effective marine accident investigation in the improvement of maritime safety through prevention similar casualties from occurring in the future, explores the legal obligations of all parties under different international maritime conventions, and codes. As most of marine accidents resulted from shortage in applying international regulations related to maritime safety, so this research determines, the shortage of application of the international regulations adopted by IMO related to maritime safety, and the shortage of legal measures to support safety at sea and protection or reduce marine pollution. This research also aims to improve special measures for procedures of marine accident investigation, with case study are highlighted, and the importance of identifying the liability. Finally the shortage of civil liability of damage resulting from marine accident under International and National Jurisdiction are discussed with some illustrative cases. [ABSTRACT FROM AUTHOR]

Accidents that result in personnel injury or death occur in lifeboats, which are some of the most reliable means of abandoning a ship during drills, routine maintenance, and tests. Comprehensive research on lifeboat accidents is non-existent in literature. This article aims to prioritize the factors responsible for lifeboat accidents and to provide comprehensive recommendations for managers, policymakers, and seafarers. For this purpose, the Fuzzy Delphi method was used in the study. Twelve lifeboat accidents reported by flag states were examined, and detailed accident analyses were made by 12 field experts. As a result of the study, human errors, equipment unsuitability, lack of knowledge, and language problems of the personnel were determined as the most important factors in the causes of lifeboat accidents. • The Fuzzy Delphi method has been demonstrated to be effective in evaluating and prioritizing the factors that contribute to ship accidents through the incorporation of expert input. • This study fills the gap in the literature on the investigation of lifeboat accidents on ships. • Human error, equipment unsuitability and lack of knowledge have been identified as the primary causes of lifeboat accidents. [ABSTRACT FROM AUTHOR]

Kajian keselamatan aktivitas transportasi laut terhadap tubrukan kapal merupakan hal yang penting dilakukan bukan hanya untuk mengetahui safety level pada sebuah alur pelayaran, namun juga untuk mengurangi potensi kejadian tubrukan. Pelabuhan Tanjung Perak, Pelabuhan Gresik dan Pelabuhan Teluk Lamong, Jawa Timur, yang berada di Alur Pelayaran Barat Surabaya memiliki peranan yang besar dalam aktivitas ekspor impor dan perdagangan nasional jalur laut. Untuk lebih mengembangkan perekonomian nasional, Kementerian Perhubungan Republik Indonesia akan mengembangkan Rencana Induk Pelabuhan Tanjung Perak dan Sekitarnya Secara Terintegrasi, dimana salah satu pengembangannya adalah pembangunan dermaga yang akan dikelola oleh PT. Berlian Manyar Sejahtera, yang berada di sekitar Bouy No.15. Pada skripsi ini menyajikan kajian keselamatan terhadap tubrukan kapal di Bouy No.15 Alur Pelayaran Barat Surabaya dengan metode IWRAP dan simulasi impak hasil tubrukan dilakukan dengan metode Finite Element Analysis. Penilaian ini bertujuan untuk mengetahui batas aman jumlah kapal yang diperbolehkan beroperasi di APBS setiap tahunnya. Data jumlah kapal yang berlayar di APBS didapatkan dari Pelindo sebagai Otoritas Pelabuhan di Indonesia. Hasil yang didapatkan berdasarkan analisis yang telah dilakukan terhadap head on collision, drifting collision, overtaking collision, dan crossing collision adalah sebesar 0.420, 0.940, 0.940, dan 0.605 secara berurutan, yang berarti frekuensi dari masing-masing jenis tubrukan dapat diterima jika mengacu pada keadaan future condition dimana frekuensi tubrukan dapat diterima bila bernilai dibawah satu. Dari analisis perhitungan yang telah dilakukan didapatkan kesimpulan bahwa jumlah maksimal kapal yang dapat berlayar di Alur Pelayaran Barat Surabaya pada future condition adalah sebanyak 49.640 kapal/tahun

In the context of the melting icecap and the growing shipping activity in the Arctic, the International Maritime Organization (IMO) spent several years preparing polar navigation rules aimed at providing appropriate safety and environmental protection standards. The rules underwent several transformations before emerging as the binding International Code for Ships Operating in Polar Waters (Polar Code). The Polar Code is expected to enter into force on 1 January 2017. This paper examines the formation and development of the Polar Code and its principles and provisions, expounds upon the unique characteristics of the Code, and discusses expected future practices. [ABSTRACT FROM AUTHOR]

Ship collision is a hazardous event within the chain of maritime transport. Collisions may result in human losses, adverse economic consequences, and environmental damages causing significant impact to local societies and related activities. A major factor in any risk analysis concerning ship collisions is the probability of these collisions occurring. The purpose of this study is to assess the probability of ship-to-ship collision in the Aegean Sea. The basic concept of the developed model is to (statistically) simulate traffic flow in the area of interest and determine the collision candidates; this will be implemented in a pilot study in a segment of the Aegean Sea. The input of this effort is based on values that are extracted from statistical analysis of the international fleet in combination with the study of maps depicting traffic flow in the studied area. Hence, it does not employ detailed AIS data. The obtained results are presented and their agreement with actual incidents is discussed in depth. The paper concludes with interesting insights of the aforementioned tasks. [ABSTRACT FROM AUTHOR]

Marine shipping is a high-risk mode of transportation in a complex environment. Most risk analyses of marine shipping are based on historical accident statistics or expert opinions rather than available evidences that reflect more realistic scenarios. In this paper, an evidence-based Fuzzy Bayesian Network approach was proposed to construct probabilistic models of marine accidents. Marine accident reports from 2001 to 2020 were utilized to build causal networks from a systematic perspective. The quantitative relationships of contributing factors in the accident networks were evaluated by experts with different backgrounds. The reliability of the Fuzzy Bayesian Networks of accidents was also verified by three axioms. The results of the sensitivity analysis revealed that distraction, heavy weather, inadequate safety/risk awareness, and maintenance failure are closely related to a majority of high-consequence marine accidents. In particular, the occurrence of heavy weather has a relatively higher impact on contact, flooding/foundering, and grounding. Overall, this paper contributes to a practical direction of ocean and coastal shipping safety management strategies and the quantitative effects of safety measures considering the allocation of limited resources. [ABSTRACT FROM AUTHOR]

Primary injury prevention strategies are needed to improve worker safety in the fishing industry by reducing the occurrence of vessel disasters. In 2006, the United States Coast Guard (USCG) implemented a novel safety policy intervention for two fleets of freezer-trawlers and freezer-longliners in Alaska. The Alternate Compliance and Safety Agreement (ACSA) set standards for vessel stability, watertight integrity, hull condition, and other critical vessel components. To determine if ACSA has been an effective primary prevention intervention for improving safety in the fishing industry, a longitudinal study was conducted using retrospective data on vessel casualties during 2003-2012. On both types of vessels, reported rates of serious vessel casualties decreased after the vessels reached compliance with ACSA requirements, suggesting that ACSA has had a positive effect on vessel safety in the freezer-trawl and freezer-longline fleets. These results support the premise that primary prevention policies can contribute to worker safety by reducing the occurrence of vessel disasters. Future USCG safety policies should be patterned after ACSA and improved by following the recommendations outlined in this study. [ABSTRACT FROM AUTHOR]

Fault diagnosis of the marine power station is essential to ensure the normal electric supply for the whole ship. In this paper, a new faults diagnosis technique for the power station using the data fusion technique has been proposed. The vibration signals of the power station were recorded by the multi-channel sensors. The independent component analysis (ICA) was adopted as the data fusion approach to find the characteristic vibration signals of the power station faults. Then the wavelet packet was employed to extract the feature vector of the fused vibration signals. In addition, the oil particle features has been extracted using the oil analysis. Lastly, the least square support vector machines (LS-SVM) was used to recognize the fault patterns of the power station. Moreover, the improved particle swarm optimization (PSO) was employed to enhance the learning ability of the LS-SVM. The experimental tests were implemented in a real ship to evaluate the effectiveness of the proposed diagnosis approach. The diagnosis results have shown that distinguished fault features have been extracted and the fault identification accuracy is acceptable. In addition, the classification rate of the proposed method is superior to the traditional SVM based method. [ABSTRACT FROM AUTHOR]

Maritime emergencies often occur rapidly in unpredictable circumstances. In a scenario where it becomes necessary to abandon a vessel or offshore platform evacuation, personal flotation and thermal protection greatly increase chances of survival for individuals escaping directly into water. Marine abandonment immersion suits, intended to be quickly donned in the case of an emergency, can provide effective protection against dangers of cold shock and prolonged immersion. The ability to locate and correctly don an immersion suit prior to abandoning is critical. Canadian Standard CAN/CGSB-65.16-2005 dictates that an immersion suit must be unpacked and properly donned without assistance within two minutes. Tests are performed on a fixed, stable deck. No empirical investigation has been conducted on time required to don immersion suits in a dynamic environment. Thirty-two participants, with similar knowledge and training, performed immersion suit donning tasks using two types of suit. Trials were performed on a motion bed that simulated maritime conditions with varying combinations of platform motions and levels of ambient illumination. Participant donning times and donning task errors were recorded for each trial. Across all conditions the mean donning time was 102.7 seconds (SD = 39.6 sec). There was a significant difference between donning time and suit manufacturer (p < .0001). Although overall mean donning time was within the two-minute requirement, in total there was a 26.1% failure rate in the completion of full donning tasks within two minutes. Donning task error rates were recorded as high as 56.3% per donning attempt. Results indicate that training standards need to more adequately reflect realistic environmental conditions and demands. Performance-based standards will more likely ensure that all personnel are better educated and prepared to don an abandonment suit successfully within the required time period, and thus increase chances of survival and rescue. Performance-based standards that include reference to donning suits in a dynamic environment will be more likely to lead to the development of suits and training that meet the needs of users in real conditions. [ABSTRACT FROM AUTHOR]

Variety of objects found on the sea floor need to be inspected for the presence of materials that represent threat to the environment and human safety. We have demonstrated that a sealed tube 14 MeV neutron generator, with the detection of associated alpha particles, can be used underwater when mounted inside a remotely operated vehicle equipped with hydraulic legs and a variety of sensors for the inspection of such objects for the presence of threat materials. [ABSTRACT FROM AUTHOR]

In this research, the safety/risk level of a liquefied natural gas (LNG) carrier system is investigated through the application of a fuzzy evidential reasoning (FER) method to uncertainty treatment of its failure modes. A fuzzy set manipulation formula with multiple parameters such as consequence severity, failure consequence probability, and failure likelihood is used to assess the safety/risk levels of failure modes of the system. Such failure estimations are synthesized to evaluate the whole system’s safety/risk level using an evidential reasoning (ER) approach. Risk control options (RCOs) are developed for reduction/control of high-risk level of the system. The best RCO, which is the one with the highest preference degree, is used to improve the safety level of the system. [ABSTRACT FROM PUBLISHER]

Abstract: Canada is considering the development of a new standard for infant/child life jackets. Eight currently available (approved and non-approved) infant/child life jackets were procured for evaluation. Fifty-six participants were chosen as a sample of convenience from the general public for testing. The life jackets were divided into two groups of four, which were donned on a soft infant manikin procured from the Red Cross. In 224 attempts at donning, only 43 (19%) attempts resulted in the life jacket being donned correctly in less than 1 min. Only one life jacket came close to a good design and passed the life jacket standard for donning time and accuracy. Failure rates were observed across all the participants irrespective of age, gender, experience with children and experience with recreational marine equipment. Accuracy and speed of donning the life jacket were hampered as the number of donning sub-tasks increased. It was concluded that it is possible to design a life jacket that can be donned correctly in under 1 min. The life jacket must be of simple, intuitive design and fall naturally into the anatomical shape of the child. A minimum number of ties, zips and clips should be used in the design, and if such connectors are used they should be color coded or of different shapes and sizes to avoid confusion. [ABSTRACT FROM AUTHOR]

Marine stingers hospitalize approximately 100 people annually in tropical Australian waters, and are known to have caused at least 73 fatalities. Elsewhere in the tropical and temperate seas of the world, marine stingers pose a similar threat to human safety, and reported sting numbers are on the rise. Lycra body suits ("stinger suits") have been used for stinger protection since the early 1980s, but have not been formally tested as a barrier against Irukandji (Carukia barnesi) tentacles. Other products are being used and developed; however, no safety standards currently exist for this widely used form of protective equipment. Eight products were tested with live C. barnesi: a Lycra stinger suit used by Surf Life Saving, a product developed by ROBIS Pty. Ltd. and marketed as "The Stinger Suit", three different styles of nylon pantyhose, two sport products designed to "wick away" moisture and keep the wearer cooler, and a 0.5-mm neoprene wetsuit. Products were evaluated for seven common concerns relating to safety and practical wearability. Primary concerns, i.e., those relating to performance of the fabric in preventing stings, include: ease of penetration by jellyfish tentacles, adherence of tentacles or body to fabric, and potential for crushing through the fabric. Secondary concerns, i.e., those relating to overall usage as stinger-preventative clothing, include: durability or integrity of the barrier, whether the product is available as a one-piece garment, heat-retention properties, and product cost. In general, the tighter the fabric weave, the better tentacle exclusion, and the smoother the fabric, the more resistant to adherence. Lycra is vulnerable to crushing of tentacles through the fabric, but appears to be the best choice for routine-use stinger-protective clothing. Recommendations are made for safe use of protective clothing, as a basis for development of an Australian Standard in protective clothing for marine stinger safety. [ABSTRACT FROM AUTHOR]

Abstract: Recreational boating is a popular leisure time activity in many countries. It is estimated that, in Australia, boating incidents cause more harm than rail and air crashes combined and, in terms of transport, are second only to motor vehicle crashes as a cause of serious injury. The consumption of alcohol among recreational boaters is considered an important risk factor for fatalities and injuries among both operators and passengers. Using a database of all recreational vessels registered in Western Australia (WA), a sample of 500 adult boaters was recruited to participate in a telephone survey. The effects of demographic variables and boating characteristics upon the use of alcohol among recreational boaters on their last trip were explored using logistic regression. The odds of not having a drink were associated, after adjusting for age, with having completed a boating education course and with carrying children less than 12 years on board. The use of alcohol was not found to be prevalent among WA recreational boat owners. Based on these findings, it is recommended that efforts to decrease boating-related incidents, such as through education and legislation measures, be monitored over time to determine the effects of these strategies upon safety behaviours. [Copyright &y& Elsevier]