Active Learning has always played an important part of seamen’s education. Transfer of experience have from ancient time been practiced in an active learner-centered field where unexperienced seamen got involved in their own learning by being supervised by experienced seamen, when practicing seaman related activities. This learning practice was supreme before the introduction of “modern” maritime ...

Due to the growing rate of energy consumption, it is necessary to develop frameworks for enhancing ship energy efficiency. This paper proposes a solution for this issue by introducing a digital twin framework for quantifying ship performance. For this purpose, extensive low-level clustering is performed using Gaussian Mixture Models (GMM) with the Expectation Maximization algorithm on a dataset ...

The machine learning approach is a new hot topic in recent years that are widely used in different sections, including industries, economy, disaster prediction and politics. After decades’ of development, the available machine learning algorithms are numerous and diverse. Traditional methods such as regression, classical statistical methods, are unfortunately laid aside as non-mainstream. This paper ...

This study presents a deep learning framework to support regional ship behavior prediction using historical AIS data. The framework is meant to aid in proactive collision avoidance, in order to enhance the safety of maritime transportation systems. In this study, it is suggested to decompose the historical ship behavior in a given geographical region into clusters. Each cluster will contain trajectories ...

Abstract To investigate temporal patterns, pollution concentrations and the health effects of air pollutants in Beijing we carried out time-series analyses on daily concentrations of ambient air pollutants and daily numbers of outpatient visits for otolaryngology over 2 years (2011– 2012) to identify possible health effects of air pollutants. The results showed that PM10 was the major air ...

This paper presents analytical and case studies of sandwich structures. In this study, the Euler-Bernoulli beam equation is solved analytically for a four-point bending problem. Appropriate initial and boundary conditions are specified to enclose the problem. In addition, the balance coefficient is calculated and the Rule of Mixtures is applied. The focus of this study is to determine the effective ...

Environmental data exhibits as huge amount and complex dependency. Utilizing these data to detect anomaly is beneficial to the disaster prevention. Big data approach using the machine learning method has the advantage not requiring the geophysical and geochemical knowledge to detect anomaly. This paper using the popular support vector regression (SVR ) to model the correlation between factors. ...

The article discusses China’s policies in and towards the Arctic and Africa within a comparative perspective. To what extent is China’s policy adaptable to different conditions? What does this adaptability tell us about China’s ascendant great-power role in the world in general? What is the message to the Arctic and Africa respectively? The article concludes that China’s regional strategies aptly ...

Mapping Arctic renewable energy resources, particularly wind, is important to ensure the transition into renewable energy in this environmentally vulnerable region. The statistical characterisation of wind is critical for effectively assessing energy potential and planning wind park sites and is, therefore, an important input for wind power policymaking. In this article, different probability density ...