A rapid and widespread institutionalization of climate security is underway, led by powerful states and international organizations. Recognition of the climate crisis by security actors as a serious threat to humanity is long overdue, but it is imperative that this institutionalization is critically scrutinized. This commentary highlights specific dangers that accompany the institutional mainstreaming ...

Representing the entire operational range of an ocean-going vessel with linear equations is often a formidable task. In this research study, a datadriven localized model is presented for ship performance prediction as a part of the digital twin development. For this purpose, different operational conditions of the vessel, i.e., data clusters, are identified using the Gaussian Mixture Models (GMM) ...

In many machine learning applications, there are many scenarios when performance is not satisfactory by single classifiers. In this case, an ensemble classification is constructed using several weak base learners to achieve satisfactory performance. Unluckily, the construction of the ensemble classification is empirical, i.e., to try an ensemble classification and if performance is not ...

Autonomous driving has sparked an entire revolution in the vehicle sector, offering to increase the safety for road users, productivity, and convenience. However, using autonomous driving vehicles in hostile environments like the Arctic present’s challenges because of the bad weather, lack of infrastructure, rough terrain, poor vision, icy and unreliable road surfaces, and inaccessible locations. ...

With the progress of innovative technologies, ships in future with different autonomy levels are anticipated to enter the realm of maritime transportation. As a result, the scenarios of multi-ship encounters at sea can become more complex and the risk of potential collisions can be difficult to elevate. To support navigation safety and guarantee the required situation awareness level, it is ...

To navigate, Maritime Autonomous Surface Ships (MASSs) must be able to determine their states. i.e., the positions and velocities, etc., by utilizing onboard IoT, and ship intelligence systems. Autonomous ship navigation can heavily rely on machine learning algorithms that can predict how vessels will maneuver in the future, based on past behavior, where vessel state estimation can play a main role. ...

Nowadays, the maritime industry, like other industries, is incorporating Machine Learning (ML) and Artificial Intelligence (AI) approaches in their applications. Since the rise of Maritime Autonomous Surface Ships (MASS) is on the horizon, such intelligent algorithms would replace conventional ship navigation with a higher level of autonomy. In other words, a digital navigator can be developed based ...

Sea ice exhibits time-dependent non-linear behaviour. This is evidenced by both lab and field experiments with known phenomena such as creep and stress relaxation. This time-dependent material behaviour becomes particularly pronounced at larger temporal scales. In this study, we present a novel approach to simulate time-dependent fractures in sea ice using peridynamics (PD), a particle integral ...

Terrorism is typically included among the grave societal challenges resulting from radicalisation of certain groups. The phrase ‘radical converts’ typically evokes an image of a convert to Islam, whereas an individual converting from Islam to other religions is not associated with a terrorist threat. When it comes to threat assessment, the conversion of Christianity to Islam is typically deemed a ...

Liquid injection optimization is key to enhance the efficiency of many processes in a wide variety of fields. Combustion processes are one of the most challenging ones, due to the direct emissions and greenhouse gases implications. This work aims at studying the external two-phase flow produced when injecting fuel with a pressure-swirl atomizer in an operating condition typical of an academic ...