Data-Driven Analysis for Safe Ship Operation in Ports Using Quantile Regression Based on Generalized Additive Models and Deep Neural Network

Marine accidents in ports can cause loss of human life and property and have negative material and environmental impacts. In South Korea, due to a pier collision accident of a large container ship in Busan New Port of South Korea, the need for safe ship operation guidelines in ports emerged. Therefore, to support quantitative safe ship operation guidelines, ship trajectory data based on automatic information system information have been used. However, because this trajectory information is variable and uncertain due to various situations arising during a ship’s navigation, there is a limit to deriving results through traditional regression analysis. Considering the characteristics of these data, we analyzed ship trajectories through quantile regression using two models based on generalized additive models and neural networks corresponding to deep learning. Among the automatic information system information, the speed over ground, course over ground, and ship’s position were analyzed, and the model was evaluated based on quantile loss. Based on this study, it is possible to suggest safe operation guidelines for the position, speed, and course of the ship. In addition, the results of this work can be further developed as a manual for the in-port-autonomous operation of ships in the future.

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75 anniversary of the university Library of the Agricultural University – Plovdiv

Agricultural sciences ◽

10.22620/agrisci.2021.30.014 ◽

2021 ◽

Vol 13 (30) ◽

pp. 106-114

Author(s):

Petya Georgieva ◽

Keyword(s):

Information System ◽

75Th Anniversary ◽

University Library ◽

Automatic Information ◽

The University ◽

Automatic Information System

The article presents the history and the development of the University Library of the Agricultural University – Plovdiv for a period of 75 years from its establishment until the present day. It is one of the oldest specialized agricultural libraries in Bulgaria. The University Library was opened in 1945, together with the opening of the University of Plovdiv. The Library of the Agricultural University – Plovdiv is the first university library in Bulgaria that has begun introducing ICT in its activities. Since 1978 the Library has used an Automatic information system for Bibliographical references. In 1986 the automation of the library processes began. In 2020 the Agricultural University – Plovdiv celebrated its 75th anniversary and its Library gradually established itself as one of the richest specialized agricultural libraries in Bulgaria.

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Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea

10.1101/2020.05.27.20114819 ◽

2020 ◽

Author(s):

Xinhua Yu ◽

Jiasong Duan ◽

Yu Jiang ◽

Hongmei Zhang

Keyword(s):

South Korea ◽

Elderly People ◽

Negative Binomial ◽

Generalized Additive Models ◽

Age Groups ◽

Additive Models ◽

Age And Gender ◽

Epidemic Dynamics ◽

And Gender ◽

Gender Groups

AbstractObjectivesElderly people had suffered disproportional burden of COVID-19. We hypothesized that males and females in different age groups might have different epidemic trajectories.MethodsUsing publicly available data from South Korea, daily new COVID-19 cases were fitted with generalized additive models, assuming Poisson and negative binomial distributions. Epidemic dynamics by age and gender groups were explored with interactions between smoothed time terms and age and gender.ResultsA negative binomial distribution fitted the daily case counts best. Interaction between the dynamic patterns of daily new cases and age groups was statistically significant (p<0.001), but not with gender group. People aged 20-39 years led the epidemic processes in the society with two peaks: one major peak around March 1 and a smaller peak around April 7, 2020. The epidemic process among people aged 60 or above was trailing behind that of younger people with smaller magnitude. After March 15, there was a consistent decline of daily new cases among elderly people, despite large fluctuations of case counts among young adults.ConclusionsAlthough young people drove the COVID-19 epidemic in the whole society with multiple rebounds, elderly people could still be protected from virus infection after the peak of epidemic.

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