A5034690093- Maritime Navigation and Safety
- Risk and Safety Analysis
- Maritime Ports and Logistics
- Structural Integrity and Reliability Analysis
- Maritime Transport Emissions and Efficiency
- Supply Chain Resilience and Risk Management
- Maritime Security and History
- Occupational Health and Safety Research
- Multi-Criteria Decision Making
- Infrastructure Resilience and Vulnerability Analysis
- Marine and Coastal Research
- Ship Hydrodynamics and Maneuverability
- Human-Automation Interaction and Safety
- Transportation Planning and Optimization
- Outsourcing and Supply Chain Management
- Vehicle Routing Optimization Methods
- Urban and Freight Transport Logistics
- Evacuation and Crowd Dynamics
- Bayesian Modeling and Causal Inference
- Law, logistics, and international trade
- Transportation and Mobility Innovations
- Reliability and Maintenance Optimization
- Advanced Manufacturing and Logistics Optimization
- Traffic Prediction and Management Techniques
- Traffic and Road Safety
Liverpool John Moores University
2016-2025
Dalian Maritime University
2016-2025
Lanzhou University
2025
Lanzhou University Second Hospital
2025
Tianjin University
2025
The University of Texas at Austin
2025
IQVIA (United Kingdom)
2025
Henan Academy of Agricultural Sciences
2025
National Engineering Research Center for Information Technology in Agriculture
2025
Southeast University
2024
PAML, currently in version 1.2, is a package of programs for phylogenetic analyses DNA and protein sequences using the method maximum likelihood (ML).The can be used (i) estimation evolutionary parameters such as branch lengths tree, transition/transversion rate ratio, shape parameter gamma distribution variable rates at sites, different genes; (ii) ratio test hypotheses concerning sequence evolution, constancy independence among sites lineages (the molecular clock); (iii) calculation...
This paper presents a novel, efficient fuzzy rule-based Bayesian reasoning ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FuRBaR</i> ) approach for prioritizing failures in failure mode and effects analysis xmlns:xlink="http://www.w3.org/1999/xlink">FMEA</i> ). The technique is specifically intended to deal with some of the drawbacks concerning use conventional logic (i.e. rule-based) methods . In proposed approach, subjective belief degrees...
Maritime risk research often suffers from insufficient data for accurate prediction and analysis. This paper aims to conduct a new analysis by incorporating the latest maritime accident into Bayesian network (BN) model analyze key influential factors (RIFs) in sector. It makes important contributions terms of novel database, RIFs, findings, implications. More specifically, 2017 2021 is collected both Global Integrated Shipping Information System (GISIS) Lloyd's Register Fairplay (LRF)...
In order to analyse the research evolution and knowledge frontier in of marine accidents, 491 literatures on accidents Web Science database from 2000 2022 are taken as data sources. Integrated with literature analysis traditional method, CiteSpace VOSviewer then jointly used for development network map cluster analysis, map, hotpots, frontiers is obtained. It found that there a close cooperative relationship among journals, researchers, institutions countries or regions. According subjects...
In maritime transport, evacuation, escape and rescue play a crucial role in protecting people's lives when passenger ship is involved serious accident. The study aims to develop new method identify hazards, quantify rank the associated risks process of Human Evacuation from Passenger Ships (HEPS). Firstly, based on extensive literature review marine accident investigation reports, risk factors affecting evacuation were analysed identified, an analysis framework Human, Ship, Environment...
Maritime transport faces new safety challenges in an increasingly complex traffic environment caused by large-scale and high-speed ships, particularly with the introduction of intelligent autonomous ships. It is evident that Automatic Identification System (AIS) data-driven ship trajectory prediction can effectively aid identifying abnormal behaviours reducing maritime risks such as collision, stranding, contact. Furthermore, widely recognised one critical technologies for realising safe...
Maritime Autonomous Surface Ships (MASS) are deemed as the future of maritime transport. Although showing attractiveness in terms solutions to emerging challenges such carbon emission and insufficient labor caused by black swan events COVID-19, applications MASS have revealed problems practice, among which navigation safety presents a prioritized concern. To ensure safety, rational route planning for is evident most critical step avoiding any relevant collision accidents. This paper aims...
Cybersecurity risks present a growing concern in the maritime industry, especially due to fast development of digitalised technologies, also vis-à-vis autonomous shipping. Research on cybersecurity is receiving increased attention. This paper aims assess sector and improve safety at sea coastal areas. First, we identify all concerned cyber threats based literature review expert opinion. A novel risk assessment framework threats, which combines Failure Mode Effects Analysis (FMEA) with...
Human errors significantly contribute to transport accidents. performance measurement (HPM) is crucial ensure human reliability and reduce errors. However, how address the subjective bias introduced by assessors in HPM seafarer certification remains a key research challenge. This paper aims develop new psychophysiological data-driven machine learning method realize effective maritime sector. It conducts experiments using functional Near-Infrared Spectroscopy (fNIRS) technology compares of...
Reinforcement learning (RL) has shown superior performance in solving sequential decision problems. In recent years, RL is gradually being used to solve unmanned driving collision avoidance decision-making problems complex scenarios. However, ships encounter many scenarios, and the differences scenarios will seriously hinder application of at sea. Moreover, iterative speed trial-and-error for multi-ship slow. To this problem, study develops a novel intelligent algorithm based on approximate...
Maritime situational awareness (MSA) has long been a critical focus within the domain of maritime traffic surveillance and management. The increasing complexities ship traffic, originating from sophisticated multi-attribute interactions among multiple ships, coupled with continuous evolution dynamics, pose significant challenges in attaining accurate MSA, particularly complex port waters. This study is dedicated to establishing an advanced methodology for partitioning aimed at enhancing...
Although many studies have focused on the occurrence likelihood of marine accidents, few analysis severity consequences, and even fewer prediction severity. To this end, a new research framework is proposed in study to accurately predict accidents. First, novel two-stage feature selection (FS) method was developed select rank Risk Influential Factors (RIFs) improve accuracy Machine Learning (ML) model interpretability FS. Second, comprehensive evaluation measure performance FS methods based...