Safe Navigation Distance Between Marine Routes and Aquaculture Farms in South Korea Using Gaussian Mixture Model

Abstract

The purpose of this study was to determine the minimum separation distance between aquaculture farms and ship traffic to prevent damage to either the farms or the vessels. A high-risk area in South Korea was selected for the study by overlapping shipping routes with fisheries using satellite and aerial photographs. The annual frequency of damage was calculated based on a probability distribution applied to the sea area, and a safe distance between the aquaculture farms and the traffic was derived. The Kolmogorov–Smirnov (KS) test was conducted to determine whether the Gaussian mixture model (GMM) follows the data of this study. It was found that a safe distance of at least 1000 m is needed to avoid farm or vessel damage. Then, it is possible to prevent damage to vessel propellers and fisheries locating aquaculture farms at the minimum safe distance from the traffic routes. For protection and security of these structures, the installation of a set of wirelessly Internet of Underwater Things (IoUT) sensors that can transmit the farm location to the ship’s navigator were suggested.

Design of Athlete’s Running Information Capture System in Space-Time Domain Based on Virtual Reality

“…In comparison, EM is a regression analysis algorithm for incomplete data sets based on the principle of Maximum Likelihood Estimator (MLE). When the data is incomplete, the iterative algorithm for solving the maximum likelihood estimation of the parameters of the distribution density function, which greatly reduces the computational complexity of the maximum likelihood estimation, is conducive to improving the accuracy of the athlete's motion information capture [35,36].…”