Satellite communications in the new space era: A survey and future challenges

O Kodheli, E Lagunas, N Maturo… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Satellite communications (SatComs) have recently entered a period of renewed interest
motivated by technological advances and nurtured through private investment and ventures …

Applications of smart technologies in logistics and transport: A review

SH Chung - Transportation Research Part E: Logistics and …, 2021 - Elsevier
The emergence of smart technologies (STs) is inducing significant transformation in logistics
and transport nowadays. STs refer to the applications of artificial intelligence and data …

Big data and artificial intelligence in the maritime industry: a bibliometric review and future research directions

ZH Munim, M Dushenko, VJ Jimenez… - Maritime Policy & …, 2020 - Taylor & Francis
This study provides a bibliometric review of 279 studies on the applications of big data and
artificial intelligence (AI) in the maritime industry, published in 214 academic outlets …

[HTML][HTML] A machine learning method for the prediction of ship motion trajectories in real operational conditions

M Zhang, P Kujala, M Musharraf, J Zhang, S Hirdaris - Ocean Engineering, 2023 - Elsevier
This paper presents a big data analytics method for the proactive mitigation of grounding
risk. The model encompasses the dynamics of ship motion trajectories while accounting for …

[PDF][PDF] Time Management as a Critical Success Factor in the Oil Industry of Basra Governorate: An Accounting Information Systems Study

HN Hussain, TTY Alabdullah… - International Journal of …, 2023 - researchgate.net
This study looks into the importance of time management to the oil sector activities in Basra
Governorate. The purpose of this study is to investigate how 200 oil companies'(OC) time …

Applications of machine learning methods in port operations–A systematic literature review

S Filom, AM Amiri, S Razavi - Transportation Research Part E: Logistics and …, 2022 - Elsevier
Ports are pivotal nodes in supply chain and transportation networks, in which most of the
existing data remain underutilized. Machine learning methods are versatile tools to utilize …

[HTML][HTML] A machine learning method for the evaluation of ship grounding risk in real operational conditions

M Zhang, P Kujala, S Hirdaris - Reliability Engineering & System Safety, 2022 - Elsevier
Ship groundings may often lead to damages resulting in oil spills or ship flooding and
subsequent capsizing. Risks can be estimated qualitatively through experts' judgment or …

Unsupervised hierarchical methodology of maritime traffic pattern extraction for knowledge discovery

H Li, JSL Lam, Z Yang, J Liu, RW Liu, M Liang… - … Research Part C …, 2022 - Elsevier
Owing to the space–air–ground integrated networks (SAGIN), seaborne shipping has
attracted increasing interest in the research on the motion behavior knowledge extraction …

An interpretable knowledge-based decision support method for ship collision avoidance using AIS data

J Zhang, J Liu, S Hirdaris, M Zhang, W Tian - Reliability Engineering & …, 2023 - Elsevier
AIS data include ship spatial-temporal and motion parameters which can be used to
excavate the deep-seated information. In this article, an interpretable knowledge-based …

Data analytics for fuel consumption management in maritime transportation: Status and perspectives

R Yan, S Wang, HN Psaraftis - … Part E: Logistics and Transportation Review, 2021 - Elsevier
The shipping industry is associated with approximately three quarters of all world trade. In
recent years, the sustainability of shipping has become a public concern, and various …