相关论文: Long term object drift in the ocean with tide and …

We present a new adaptive algorithm for learning discrete distributions under distribution drift. In this setting, we observe a sequence of independent samples from a discrete distribution that is changing over time, and the goal is to…

Drifters designed to mimic floating marine debris and small patches of pelagic \emph{Sargassum} were satellite tracked in four regions across the North Atlantic. Though subjected to the same initial conditions at each site, the tracks of…

The objective of this paper is to employ machine learning (ML) and deep learning (DL) techniques to obtain from input data (storm features) available in or derived from the HURDAT2 database models capable of simulating important hurricane…

The sea breeze is a phenomenon frequently impacting Long Island, New York, especially during the spring and early summer, when land surface temperatures can exceed ocean temperatures considerably. The sea breeze influences daily weather…

In the framework of Monitoring by Ocean Drifters (MONDO) Project, a set of Lagrangian drifters were released in proximity of the Brazil Current, the western branch of the Subtropical Gyre in the South Atlantic Ocean. The experimental…

The relativistic timing affects of tidally redistributed ocean mass are investigated. The Sun, Moon, and Earth hurl through space, and their gravitational fields cause the tides which is a slight redistribution of ocean mass. This…

The impact of a turbulent flow on wind-driven oceanic near-inertial waves is examined using a linearised shallow-water model of the mixed layer. Modelling the flow as a homogeneous and stationary random process with spatial scales…

The ability of three wave theories to predict statistics and the crest kinematics of a seaway is quantified. The three wave theories are high-order spectral (HOS) theory, free-surface mapping (FSM), and volume-of-fluid (VOF). Issues…

The notion of concept drift refers to the phenomenon that the distribution, which is underlying the observed data, changes over time. We are interested in an identification of those features, that are most relevant for the observed drift.…

We introduce a Monte-Carlo algorithm for the simulation of charged particles moving in the continuum. Electrostatic interactions are not instantaneous as in conventional approaches, but are mediated by a constrained, diffusing electric…

We compare two methods for making predictions of the climatological distribution of the number of hurricanes making landfall along short sections of the North American coastline. The first method uses local data, and the second method uses…

Simulating oil transport in the ocean can be done successfully provided that accurate ocean currents and surface winds are available -- this is often too big of a challenge. Deficient ocean currents can sometimes be remediated by…

Motion prediction of surrounding vehicles is one of the most important tasks handled by a self-driving vehicle, and represents a critical step in the autonomous system necessary to ensure safety for all the involved traffic actors. Recently…

In this paper, we introduce a new technique that combines two popular methods to estimate uncertainty in object detection. Quantifying uncertainty is critical in real-world robotic applications. Traditional detection models can be ambiguous…

Research on the statistics of extreme events using deterministic wave group methods has largely been simplified to vessels at zero or constant speed and heading. In contrast, free-running vessels move with six degrees-of-freedom (6-DoF),…

There exists a large body of work on online drift detection with the goal of dynamically finding and maintaining changes in data streams. In this paper, we adopt a query-based approach to drift detection. Our approach relies on {\em a drift…

A stochastic approach is implemented to address the problem of a marine structure exposed to water wave impacts. The focus is on (i) the average frequency of wave impacts, and (ii) the related probability distribution of impact kinematic…

This paper introduces a new technique for learning probabilistic models of mass and friction distributions of unknown objects, and performing robust sliding actions by using the learned models. The proposed method is executed in two…

Global return values of marine wind speed and significant wave height are estimated from very large aggregates of archived ensemble forecasts at +240-h lead time. Long lead time ensures that the forecasts represent independent draws from…

A novel approach for robust state estimation of marine vessels in rough water is proposed in this paper to enable tight collaboration between Unmanned Aerial Vehicles (UAVs) and a marine vessel, such as cooperative landing or object…