This paper presents a scenario evolution model for maritime accidents using Bayesian networks (BN) to predict the most likely causes of specific types of maritime incidents. The BN nodes encompass accident type, life loss contingency, accident severity, the quarter and time period of the accident, and the type and gross tonnage of the ships involved. We analyzed 5,660 global maritime accidents from 2005 to 2020. Using Netica software, we constructed a Tree Augmented Network (TAN) model, accounting for interdependencies among risk influencing factors. We validated the results through sensitivity analysis and historical accident records. Forward causal inference and reverse diagnostic inference were then performed on each node variable to investigate the accident development trend and evolution process under predetermined conditions. The findings indicate that the model can effectively predict the likelihood of various accident scenarios under specific conditions, as well as the extrapolation of accident consequences. Forward causal reasoning reveals that general cargo ships with a gross tonnage of 1-18,500 t are most likely to experience collision, grounding, and stranding accidents in the first quarter. Reverse diagnostic reasoning indicates that during early morning hours, container ships, general cargo ships, and chemical ships with a tonnage of 1-18,500 t are less likely to involve life loss in the event of collision accidents.

Several disruptive attacks against companies in the maritime industry have led experts to consider the increased risk imposed by cyber threats as a major obstacle to undergoing digitization. The industry is heading toward increased automation and connectivity, leading to reduced human involvement in the different navigational functions and increased reliance on sensor data and software for more autonomous modes of operations. To meet the objectives of increased automation under the threat of cyber attacks, the different software modules that are expected to be involved in different navigational functions need to be prepared to detect such attacks utilizing suitable detection techniques. Therefore, we propose a systematic approach for analyzing the navigational NMEA messages carrying the data of the different sensors, their possible anomalies, malicious causes of such anomalies as well as the appropriate detection algorithms. The proposed approach is evaluated through two use cases, traditional Integrated Navigation System (INS) and Autonomous Passenger Ship (APS). The results reflect the utility of specification and frequency-based detection in detecting the identified anomalies with high confidence. Also, the analysis is found to facilitate the communication of threats through indicating the possible impact of the identified anomalies against the navigational operations. Moreover, we have developed a testing environment that facilitates conducting the analysis. The environment includes a developed tool, NMEA−Manipulator that enables the invocation of the identified anomalies through a group of cyber attacks on sensor data. Our work paves the way for future work in the analysis of NMEA anomalies toward the development of an NMEA intrusion detection system.

Lignocellulosic biomass fractionation is typically performed using methods that are somehow harsh to the environment, such as in the case of the kraft pulping. In recent years, the development of new sustainable and environmentally friendly alternatives has grown significantly. Among the developed systems, bio-based solvents emerge as promising alternatives for biomass processing. Therefore, in the present work, the bio-based and renewable chemicals, levulinic acid (LA) and formic acid (FA), were combined to fractionate lignocellulosic waste (i.e., Maritime pine sawdust) and isolate lignin. Different parameters, such as LA/FA ratio, temperature, and extraction time, were optimized to boost the yield and purity of extracted lignin. The LA/FA ratio was found to be crucial regarding the superior lignin extraction from the waste biomass. Moreover, the increase in temperature and extraction time enhances the amount of extracted residue but compromises the lignin purity and reduces its molecular weight. The electron microscopy images revealed that biomass samples suffer significant structural and morphological changes, which further suggests the suitability of the new developed bio-fractionation process. Same was concluded by the FTIR analysis, in which no remaining lignin was detected in the cellulose-rich fraction. Overall, the novel combination of bio-sourced FA and LA has shown to be a very promising system for lignin extraction of high purity from biomass waste, thus contributing to extend the opportunities of lignin manipulation and valorisation into novel added-value biomaterials.

Changes in crude oil price affect the shipping freight market in three different channels. This study explores the dependence structure between oil prices and maritime freight rates to identify the strongest channel. Therefore, it investigates the relationship between oil prices and three major maritime freight rates; the Baltic Dry Index (BDI), the Baltic Dirty Tanker Index (BDTI), and the Baltic Clean Tanker Index (BCTI). We employ the decomposition method, not studied in the existing literature. The copula approach identifies the time-varying effects and asymmetry in the tail dependence structure between oil prices and freight rates. The main results of this analysis are as follows. The decomposed components display different conditional dependence patterns, and asymmetry is revealed in the upper and lower tail dependence. In the long run, we find more dependence in extreme periods like the financial crises. In short-run fluctuations, we find the dependence increases in an economic boom. The implications of the results suggest that dependence can vary over time and may change depending on extreme events, implying that the complementary strategies of the long run and short run should be different.

Merchant marine fleet is under inspections by several parties to ensure maritime regulation compliance. One of the major effects on implementation of regulations by International Maritime Organization (IMO) is indeed Port State Control. This article aims to analyze Paris Memoranda of Understanding (MOU) all detention remarks from 2013 to 2019 for EU15 countries (except Luxemburg and Austria) through an approach based on Analytical Hierarchy Process and demonstrate the results on Geographic Information System (GIS) to guide marine industry on detainable Port State Control remarks and country risk profile. While Analytical Hierarchy Process Approach has been used to indicate the ranking of basic maritime regulations from the perspective of the port state control , GIS help us to demonstrate the regional dispersion amongst EU15. The data of the detained vessel taken from the public website of Paris MOU and each report considered as a professional judgement that causes detention. It has been shown that almost all countries top priorities for regulation are Safety of Life at Sea (SOLAS) and Fire Safety Systems (FSS). Consequently, the results of the study can assist Port State Officers, ship crew, ship owners and managers presenting the facts of their inspection and able to improve themselves. The spatial analysis also expected to guide ship owners and managers to focus their vessel’s deficiencies to prevent sub-standardization.

Considering the concerns for emissions reduction in the maritime sector, the present paper evaluates, through modeling and simulation, the oxy-fuel combustion in a two-stroke ship engine (2SE) and the best production system configuration to obtain the required oxygen (O2). An initial model of a ship engine is calibrated with the engine manufacturer’s data, and then adapted to work with O2 as the oxidant to eliminate nitrogen oxides (NOx) emissions and with exhaust gas recirculation (EGR) to control the in-cylinder combustion temperature. Mixed Ionic-Electronic Conducting (MIEC) membranes produce the necessary O2 from the ambient air, which is heated up and pressurized by a heat exchanger and turbocharging coupled system to provide the air conditions required for the proper operation of the MIEC. Several layouts of this system are evaluated for the full load engine operating point to find the optimum O2 production system configuration. Results reveal that the engine operating under oxy-fuel combustion conditions avoids NOx emissions at the expense of higher brake specific fuel consumption (BSFC) to obtain the original brake torque, and also expels a stream composed exclusively of CO2 and H2O, what facilitates the separation of CO2 from exhaust gases.

Maritime search and rescue is a crucial component of the national emergency response system, which currently mainly relies on Unmanned Aerial Vehicles (UAVs) to detect the objects. Most traditional object detection methods focus on boosting the detection accuracy while neglecting the detection speed of the heavy model. However, it is also essential to improve the detection speed which can provide timely maritime search and rescue. To address the issues, we propose a lightweight object detector named Shuffle-GhostNet-based detector (SG-Det). First, we construct a lightweight backbone, named Shuffle-GhostNet, which enhances the information flow between channel groups by redesigning the correlation group convolution and introducing the channel shuffle operation. Second, we propose an improved feature pyramid model, namely BiFPN-tiny, which has a lighter structure while being capable of reinforcing small object features. Furthermore, we incorporate the atrous spatial pyramid pooling module (ASPP) to the network, which employs atrous convolution with different sampling rates to obtain multi-scale information. Finally, we generate three sets of bounding boxes at different scales – large, medium, and small – to detect objects of different sizes. Compared with other lightweight detectors, SG-Det achieves better tradeoffs across performance metrics, and enables real-time detection with an accuracy rate of over 90% for maritime objects, which shows that it can be better meet the actual requirements of maritime search and rescue.

Recent maritime legislations demand the transformation of the sector to greener and more energy efficient transportation. Liquified Natural Gas (LNG) seems a promising alternative fuel solution that could replace the conventional fuel sources. Various studies have been focused on the prediction of LNG price, however, no previous work has been made on the forecast of spot charter rate of LNG carrier ships. An important knowledge for the maritime industries and companies when it comes to decision-making. Therefore, this study is focused on the development of a machine learning pipeline to address the aforementioned problem by: (i) forming a dataset with variables relevant to LNG; (ii) identifying the variables that impact on the freight price of LNG carrier; (iii) developing and evaluating regression models for short and mid-term forecast. The results showed that the General Regression Neural Network presented a stable overall performance for 2, 4 and 6 months forecast.

Understanding and evaluating urban investment environment is essential for effectively improving the efficiency of resource allocation between cities and promoting overall development of the regional economy. This paper takes 15 node cities on maritime Silk Road covered by the “Belt and Road” as the research object, establishes a dynamic evaluation index system for investment environment, and uses projection pursuit cluster to analyze and evaluate the investment environment of the cities. It is found that the investment environment potential of a city is directly related to the level of social development, economic development, and the degree of opening to the outside world. It is recommended that node cities should seize the important opportunity of the construction of the Maritime Silk Road, introduce world-wide human, financial and material resources to promote regional resources allocation and flow, and continuously improve and upgrade the investment environment quality.

Port state control inspections implemented under the Paris Memorandum of Understanding (MoU) have become known as one of the best instruments for maritime administrations in European Union (EU) Member States to ensure that the ships docked in their ports comply with all maritime safety requirements. This paper focuses on the analysis of all inspections made between 2013 and 2018 in the top ten EU ports incorporated in the Paris MoU (17,880 inspections). The methodology consists of a multivariate statistical information system (STATIS) analysis using the inspected ship’s characteristics as explanatory variables. The variables used describe both the inspected ships (classification society, flag, age and gross tonnage) and the inspection (type of inspection and number of deficiencies), yielding a dataset with more than 600,000 elements in the data matrix. The most important results are that the classifications obtained match the performance lists published annually by the Paris MoU and the classification societies. Therefore, the approach is a potentially valid classification method and would then be useful to maritime authorities as an additional indicator of a ship’s risk profile to decide inspection priorities and as a tool to measure the evolution in the risk profile of flag over time.

Whereas bait and pitfall trappings are two of the most commonly used techniques for sampling ant assemblages, they have not been properly compared in temperate open habitats. In this study, taking advantage of a large-scale project of heathland restoration (3 sites along the French Atlantic Coast forming a north-south gradient), we evaluated the relative efficiency of these two methods for assessing both taxonomic and functional diversities of ants while accounting for a north south diversity gradient. Ants were collected and identified to species level, and 6 traits related to morphology, behavior (including diet, dispersal and maximum foraging distance) and social life (colony size and dominance type) were attributed to all 23 species. Both observed and estimated species were significantly higher in pitfalls compared to spatially pair-matched bait traps. Functional diversity followed the same pattern, with consistent results for both community weighted mean (CWM) and Rao’s quadratic entropy. Taxonomic and functional diversities from pitfall assemblages increased from North to South locations, following a frequently reported pattern at larger spatial scales. Bait traps can hardly be considered a complementary method to pitfall traps for sampling ants in open temperate habitats, as it appears basically redundant with pitfall traps at least on maritime cliff-tops of the East-Atlantic coast.

Taking into account the increase in the emission of greenhouse gases produced by ships, during navigation and maneuvering in the port, a direct consequence of the increase in maritime traffic, the international community has developed a broad set of regulations to limit such emissions. The installation in commercial ports of automatic mooring systems by means of vacuum suction cups (AMS), thus reducing considerably the time required to carry out the mooring and unmooring maneuvers of ships, is a factor that is considerably influencing the decrease in Emissions of polluting gases in commercial ports with high traffic. The objective of the present work is to verify the influence of the use of the AMS on the emissions of polluting gases produced in the facilities destined to the traffic of container ships. It examines the CO2 emissions of container ships that call in the only three container ports equipped with AMS: Salalah (Oman), Beirut (Lebanon) and Ngqura (South Africa). Between them, these three ports supported the transit of 6 million TEUS in 2017. The calculation of emissions is made taking into account the time saved when performing the mooring maneuvers using the new AMS system compared with when it is not used. To do this, two different calculation methods are used: EPA and ENTEC to then compare the results of the two and thus obtain the reduction in emissions per TEU in these terminals during the mooring maneuvers. The paper concludes with a discussion on the values of the reductions in emissions obtained and the advantages of the installation of AMS in commercial ports located near population centres.

Various UAV applications, especially those based on reconnaissance and observation missions, often require an unlimited time of flight. This is possible only when a UAV is being continuously power supplied from the ground power source, and that is why tethered UAV systems were developed. Tethered UAV systems are based on multicopters which can hover above the landing pad, or track its position in the case it is movable. The presented research is about the development of a large C3 class hexacopter having a maximal payload of about 1 kg, and takeoff mass of 16 kg, which was tested in maritime conditions during the ferry’s cruise. The main purpose of the hexacopter is the continuous observation of the area ahead of a vessel to detect and localize obstacles in the water. During experimental tests critical phases of flight were identified, the AC-DC power supply unit as well as the power cord unwinder were tested, and the power taken by six BLDC motors was registered. The obtained results can be useful in future work on tethered UAV systems used in windy maritime conditions.

This paper presents an analysis of the sensitivity of controlling an autonomous surface object among a group of encountered objects to the inaccuracy of state control process data. For this purpose, a safe and optimal model of the control process was defined. An algorithm for determining the optimal and safe trajectory of an object, based on the multi-object game model, was developed; for comparative analysis, an algorithm for calculating only the optimal trajectory, not taking into account the maneuverability of other objects, was additionally developed. First, simulation-based studies of the algorithms enabled a comparative analysis of a number of different acceptable strategies for optimally shifting the trajectory of maneuvering objects from a single initial direction. Thereafter, the main goal of this paper was implemented: an analysis of the sensitivity characteristics of safe control, assessed with the risk of collision, both on the inaccuracy of navigation data and on the number of possible control strategies. Finally, final conclusions and a plan for further research on the subject of the paper were formulated.

The purpose of this study was to report data analysis results from the International Health Regulations (2005) Ship Sanitation Certificates (SSC), recorded in the European Information System (EIS). International sea trade and population movements by ships can contribute to the global spread of diseases. SSC are issued to ensure the implementation of control measures if public health risk exists on board. EIS designed according to the World Health Organization (WHO) “Handbook for Inspection of Ships and Issuance of SSC”. Inspection data were recorded and SSC issued by inspectors working at European ports were analysed. From July 2011-February 2017, 107 inspectors working at 54 ports in 11 countries inspected 5579 ships. Of these, there were 29 types under 85 flags (including 19 EU flags). As per IHR (2005) 10,281 Ship Sanitation Control Exception Certificates (SSCEC) and 296 Ship Sanitation Control Certificates (SSCC) were issued, 74 extensions to existing SSC were given, 7565 inspection findings were recorded, and 47 inspections were recorded without issuing an SSC. The most frequent inspection findings were the lack of potable water quality monitoring reports (23%). Ships aged ≥12 years (Odds Ratio, OR = 1.77, 95%Confidence Intervals, CI = 1.37–2.29) with an absence of cargo at time of inspection (OR = 3.36, 95%CI = 2.51–4.50) had a higher probability of receiving an SSCC, while ships under the EU flag had a lower probability of having inspection findings (OR = 0.72, 95%CI = 0.66–0.79). Risk factors to prioritise the inspections according to IHR were identified by using the EIS. A global information system, or connection of national or regional information systems and data exchange, could help to better implement SSC using common standards and procedures.

The levels of informatization, automation, and intelligence are continuously improving; however, the risks due to the increased design and operational complexity of ship systems are increasing. Large-scale ship accidents occur for various reasons. Existing accident analysis methods that examine marine accidents from the perspective of causal one-to-one correspondence have limitations in systematically analyzing complex marine risks when identifying their causes for the prevention of similar accidents. This study focuses on a systematic causality analysis of the factors related to human errors in marine accidents that may occur during the arrival and departure of mega container ships. In particular, a representative case of the Milano Bridge crane contact accident at Busan New Port is considered. To explore the complex organizational–technical, human–technical, and organizational–human relationships relevant to this case, human factors (seafarer, pilot, etc) that are closely related to the linked causes were analyzed using the functional resonance analysis method. This study aims to reduce human error and prevent marine accidents including pilotage.

Maritime transport has become very important due to its ability to internationally unite all continents. In turn, during the last two years, we have observed that the increase of consumer goods has resulted in global shipping deadlocks. In addition, the future goes through the role of ports and efficiency in maritime transport, with the aim of decarbonizing its impact on the environment. In order to improve the economy and people's lives, in this work, we propose to enhance services offered in maritime logistics. To do this, a communications system is designed on the deck of ships to transmit data through a constellation of satellites using interconnected smart devices based on IoT. Among the services, we highlight the monitoring and tracking of refrigerated containers, the transmission of geolocation data from GPS, and security through AIS. This information will be used for a fleet of ships to make better decisions and help guarantee the status of the cargo, as well as maritime safety on the routes. The system design, network dimensioning, and a communications protocol for decision-making will be presented.

Microgrid is one of the promising green transition technologies that will provide enormous benefit to the seaport, as a solution to the major concerns in this sector, namely energy crisis, economical and environmental pollution. However, finest design of the microgrid is a challenging task considering different objectives, constraints and uncertainties involved. To ensure the optimal operation of the system, determining the right configuration framework and size for each component in the seaport microgrid at the minimum cost is a vital decision at the design stage. This paper aims to design a hybrid system of seaport microgrid with optimally sized component .The selected case study is the Port of Aalborg, Denmark. The proposed grid-connected structure consists of renewable energy sources (photovoltaic system and wind turbines), an energy storage system and cold ironing as seaport’ loads. The architecture is then optimized by utilizing HOMER to meet the maximum load demand by considering a few parameters such as solar global horizontal irradiance, temperature and wind resources. Then, the best configuration framework is analyzed in terms of economic feasibility, energy reliability and environmental impact.

Seaports are well known as the medium that has evolved into the central link between sea and land for complex marine activities. The growth in maritime logistics especially necessitates a large volume of energy supply to maintain the operation of sea trade, resulting in an imbalance between the generation and demand sides. Future projections for three major concerns show an increase in load demand, cost of operation, and environmental issues. In order to overcome these problems, integrating microgrids as an innovative technology in the seaport power system appears to be a vital strategy. It is believed that microgrids enhance the seaport operation by providing sustainable, environmentally friendly, and cost-effective energy. Despite the fact that microgrids are well established and widely used in a variety of operations on land, their incorporation into the seaport is still limited. The involvement of a variety of heavy loads such as all-electric ships, cranes, cold ironing, and buildings infrastructure makes it a complicated arrangement task in several aspects, which necessitate further research and leave space for improvement. In this paper, an overview of the seaport microgrids in terms of their concepts, requirements, and operation management is presented. It provides the perspectives of integrating the microgrid concept into a seaport from both shore side and seaside as a smart initiative for the green ports vision. Future research directions are discussed towards the development of more efficient marine power system.

A severe flash flood hit Luwu, Sulawesi, Indonesia, on 13 July 2020. This flood was preceded by persistent heavy rainfall from 11 to 13 July 2020. In this study, we explore both the physical and dynamical processes that caused the heavy rainfall using a convection-permitting model with 1-km resolution. The heavy rainfall was modulated by the development of a pair of Mesoscale Convective Complexes (MCCs) during the night. The pair of MCCs was triggered by an anti-cyclonic vorticity anomaly over the Makassar Strait and was maintained by the warm front passing between the sea and land over central Sulawesi. This front was characterized by moist-warm and cold-dry low-level air, which may have helped to extend the lifetime of the MCCs. The northwestward propagation of the MCCs was due to the interaction between predominantly southeasterly monsoon and sea surface temperature anomalies.

Rather high speed of modern water bikes that they develop using only human muscle power increases their popularity. For example, the maximum speed of prototypes reaches the value 3 m/s. Similar vehicles can be used not only for recreation and fitness, but also for transportation. To increase their speed and tonnage, we recommend improving the pontoon shape and using electrical power. The total drag and maximal speeds of the vehicles with the human muscle and electrical power are estimated. Expected success in improving the pontoon shape opens wide prospects for the use of these special shaped hulls in shipbuilding.

In the framework of maritime surveillance, vessel detection techniques based on spaceborne Synthetic Aperture Radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. The paper deal with this topic presenting a novel approach exploiting a cascade application of a pre-screening, and discrimination phase. The latter leverage the SAR spectrum by means of sub-looks analysis. For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images. For a future syngergic exploitation of more SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM and COSMO-SkyMed images, is comprehensive of multiple images gathered over the same area with short time lag (below 15 minutes). Finally, the diversified processing chains and the results for each mission product and scenarios are discussed. Being the first dataset of SLC (Single Look Complex) SAR multi-frequency data, the present work intends to encourage additional research in this promising field of research.

The use of digital twins for the development of Autonomous Maritime Surface Vessels (AMSVs) has enormous potential to resolve the increasing need for water-based navigation and safety at the seas. Aiming at the problem of lack of broad and integrated digital twin implementations with live data along with the absence of a digital twin-driven framework for AMSV design and development, an application framework for the development of a fully autonomous vessel using an integrated digital twin in a 3D simulation environment has been presented. Our framework has four layers to ensure that the simulation and the real-world boat as well as the environment are as close as possible. Åboat, an experimental research platform for maritime automation and autonomous surface ship applications, equipped with two trolling electric motors, cameras, LiDARs, IMU and GPS has been used as the case study to provide a proof of concept. Åboat and its sensors, alongwith the environment have been replicated in a 3D simulation environment. Using the proposed application framework, we develop obstacle detection and path planning systems based on machine learning which leverage live data from a 3D simulation environment to mirror the complex dynamics of the real world.

Maritime Continent (MC) positions in between Asian and Australian summer monsoons zone. Its complex topography and shallow seas around it is a major challenge for the climate researchers to model and understand it. Monsoon in this area is affected by inter-scale ocean-atmospheric interactions like El-Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden-Julian Oscillation. Monsoon rainfall in MC (especially in Indonesia and Malaysia) profoundly exhibits its variability dependency on ocean-atmospheric phenomena in this region. This monsoon shift often introduces to dreadful events like biomass burning (BB) in Southeast Asia (SEA) which sometimes leads to severe trans-boundary haze pollution. In this study, the episode of BB in 2015 of SEA is highlighted and discussed. Observational satellite datasets are tested by performing simulations with numerical weather prediction (NWP) model using WRF-ARW (Advanced research WRF). Observed and model datasets are compared to study the sea surface temperature (SST) and precipitation (rainfall) anomalies influenced by ENSO, IOD and MJO. Correlations have been recognised which explains the delayed rainfall of regular monsoon in MC due to the influence of ENSO, IOD and MJO during 2015 BB episode, eventually leading to intensification of fire and severe haze.

Many causal factors to marine traffic accidents (MTA) influence each other and have associated effects. It is necessary to quantify the correlation path mode of these factors to improve accident prevention measures and their effects. In the application of human factors to the accident mechanisms, the complex structural chains on causes to MTA systems were analyzed combining the Human Failure Analysis and Classification System (HFACS) with theoretical Structural Equation Modeling (SEM). First, the accident causation model was established as a human error analysis classification in sight of MTA, and the constituent elements of the causes of accident was conducted. Second, a hypothetical model of Human factors classification was proposed applying the practice of the structural model. Third, with the data resource from ship accident cases, this hypothetical model was discussed and simulated, and as a result the relationship path dependency mode between the latent independent variable of the accident was quantitatively analyzed based on the observed dependent variable of human behaviors. Application examples show that relationships in HFACS are verified and in line with the path developing mode, and resource management factors have a pronounced influence and a strong relevance to the causal chain of the accidents. Appropriate algorithms for the theoretical model can be used to numerically understand the safety performance of marine traffic systems under different parameters through mathematical analysis. Hierarchical assumptions in the HFACS model are quantitatively verified.

Using the culture-work-health model, this study investigates the factors influencing the quality of life of maritime workers. This study conducted a survey of 320 maritime workers who have experience living and working on a ship for more than six months. This self-administered questionnaire included questions on organizational culture and support, self-efficacy, perceived fatigue, as well as the quality of work life. Organizational culture and self-efficacy were identified as factors affecting the quality of work life, while organizational support was found to have an indirect effect after passing through self-efficacy and perceived fatigue. The final model accounts for 63.1% of the variance in maritime workers’ quality of life. As such, this study shows that self-efficacy is important for the quality of life of maritime workers, having both direct and indirect effects. Moreover, organizational support may prove the primary intervention point for relieving perceived fatigue and enhancing self-efficacy, thus improving the quality of work life.

In various domains such as energy, manufacturing, and maritime, cyber-physical systems (CPS) have seen increased interest. Both academia and industry have focused on the cybersecurity aspects of such systems. The assessment of cyber risks in CPS is a popular research area with many existing approaches that aim to suggest relevant methods and practices. However, few works have addressed the extensive and objective evaluation of the proposed approaches. In this paper, a standard-aligned evaluation methodology is presented and empirically conducted to evaluate a newly proposed cyber risk assessment approach for CPS. The approach, which is called FMECA-ATT&CK is based on Failure Mode, Effects & Criticality Analysis (FMECA) risk assessment process and enriched with the semantics and encoded knowledge in the Adversarial Tactics, Techniques, and Common Knowledge framework (ATT&CK). Several experts were involved in conducting two risk assessment processes, FMECA-ATT\&CK and Bow-Tie, against two use cases in different application domains, particularly an autonomous passenger ship (APS) as a maritime use case and a digital substation as an energy use case. This allows for the evaluation of the approach based on a group of characteristics, namely, applicability, feasibility, accuracy, comprehensiveness, adaptability, scalability, and usability. The results highlight the positive utility of FMECA-ATT&CK in model-based, design-level, and component-level cyber risk assessment of CPS with several identified directions for improvements. Moreover, the standard-aligned evaluation method and the evaluation characteristics have been demonstrated as enablers for the thorough evaluation of cyber risk assessment methods.

Current trends in industrial development strive for maximum digitalization. The digital industrial revolution has been going on for more than a dozen years, Industry 4.0 and the idea of digital twins (DT) is becoming the focus of virtually all industrial sectors. Some sectors are more predisposed to digitalization, for others the process is much more difficult. This depends mainly on the specific characteristics and susceptibility of a given industry, including the current degree of digitalization of enterprises, as well as the knowledge and mental readiness of employees. The individual characteristics of an industry are important. Shipyards belong to the industry with a traditional approach, where the degree of digitalization remains low. As a result, the efficiency of shipbuilding processes and the quality of ships built are not sufficiently controlled. The article addresses this problem, reviews work in the field of digitalization of shipbuilding processes and points out the needs and challenges in this area. The article proposes the concept of a DT system for the entire ship design and production process. Key areas of digitalization of actual processes were defined, and a division was made into planning, monitoring and process analysis activities. Special attention was paid to the area of dimensional quality control and the Dimensional Quality Management Metasystem (DQMM) was featured in the comprehensive DT system. The requirements were defined and the limitations of the proposed solution were identified, taking into account a number of external factors including the degree of readiness of the manufacturer – the shipyard. The developed DT system concept was tested on the example of the construction process of a simplified ship. Practical aspects of the implementation of the proposed solution, in particular DQMM, were indicated.

Software is playing the most important role in recent vehicle innovation, and consequently the amount of software has been rapidly growing last decades. Safety-critical nature of ships, one sort of vehicles, makes Software Quality Assurance (SQA) has gotten to be a fundamental prerequisite. Just-In-Time Software Defect Prediction (JIT-SDP) aims to conduct software defect prediction (SDP) on commit-level code changes to achieve effective SQA resource allocation. The first case study of SDP in maritime domain reported feasible prediction performance. However, we still consider that the prediction model has still rooms for improvement since the parameters of the model are not optimized yet. Harmony Search (HS) is a widely used music-inspired meta-heuristic optimization algorithm. In this article, we demonstrated that JIT-SDP can produce the better performance of prediction by applying HS-based parameter optimization with balanced fitness value. Using two real-world datasets from the maritime software project, we obtained an optimized model that meets the performance criterion beyond baseline of previous case study throughout various defect to non-defect class imbalance ratio of datasets. Experiments with open source software also showed better recall for all datasets despite we considered balance as performance index. HS-based parameter optimized JIT-SDP can be applied to the maritime domain software with high class imbalance ratio. Finally, we expect that our research can be extended to improve performance of JIT-SDP not only in maritime domain software but also in open source software.

Based on the observation and reanalysis data, the relationship between Madden-Julian Oscillation (MJO) over the Maritime Continent (MC) and the tropical Pacific-Indian Ocean temperature anomaly mode is analyzed. The results showed that the MJO over the MC region (100°-140°E, 10°S-5°N) (referred to as MC-MJO) possesses prominent interannual and interdecadal variations and seasonally "phase-locked" features. MC-MJO is strongest in the boreal winter and weakest in the boreal summer. Winter MC-MJO kinetic energy variation has significant relationships with the El Niño-Southern Oscillation (ENSO) in winter and the Indian Ocean Dipole (IOD) in autumn, but it correlates better with the tropical Pacific-Indian Ocean associated mode (PIOAM). The correlation coefficient between the winter MC-MJO kinetic energy index and the autumn PIOAM index is as high as -0.43. This means that when the positive (negative) autumn PIOAM anomaly strengthens, the MJO kinetic energy over the winter MC region weakens (strengthens). However, the correlation between the MC-MJO convection and PIOAM in winter is significantly weaker. The propagation of MJO over the Maritime Continent differs significantly in the contrast phases of PIOAM. During the positive phase of the PIOAM, the eastward propagation of the winter MJO kinetic energy always fails to move across the MC region and cannot enter the western Pacific. However, during the negative phase of the PIOAM, the anomalies of MJO kinetic energy over the MC is not significantly. MJO can propagate farther eastward and enter the western Pacific. One thing must be pointed out that there is a significant difference between the propagation of MJO convection over the MC region in winter and that of the MJO kinetic energy. That said, the MJO convection is more likely to extend to the western Pacific in the positive phases of PIOAM than in the negative phases

Appropriate governance structures are extremely important for the fishery dependent communities to develop integrated territorial development strategies and adaptive capacity to change, including the climate one. This paper assesses to what extent fisheries co-management schemes (e.g Fisheries LAGs, being regional/local governance instruments in fishing communities) are strengthening sustainability. The latter includes improving energy efficiency, promoting renewable energy sources (RES), coping with climate crisis, minimizing environmental impacts, and promoting sustainable blue economy. For detecting policy aspects of aligning climate neutrality and sustainable blue economy, the research lens focuses on the Greek Fisheries Local Action Groups (FLAGs) given that these are mostly located in coastal/marine and insular territories with significant blue growth potential. To map and assess their capacity and efficiency in pursuing Green Deal objectives, a co-development process with FLAG managers was put in place. The results and findings of this process reveal the scarcity of sustainability and blue economy related strategies. Key conclusion is that transition to a post-carbon blue economy on a local level, requires the understanding of the evolutionary dynamics of fisheries co-management schemes. The latter, being multi-sectoral structures, may boost dialogue and cooperation to harmonize local development strategies and EU policies. Maritime Spatial Planning (MSP) as an evolutionary governance process itself, can be a driver for making FLAGs evolve, and strengthen commonization and blue justice and equity for fishers.