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Sanghee Kim, Donghyuk Jung, Ju-Yong Kim and Ju-Hyun Mun
Although accurately estimating the early age compressive strength of concrete is essential for the timely removal of formwork and the advancement of construction processes, it is challenging to estimate it in cool, cold, hot, or unmanaged conditions. Var...
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Jiayu Huang, Feng Diao, Shifeng Ding, Sen Han, Pentti Kujala and Li Zhou
In previous studies of ship?ice interactions, most studies focused on ship?level ice interactions, overlooking potential rafted ice conditions in extreme ice conditions. The purpose of this study is to develop a numerical model for predicting ship resist...
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Håkon Harnes and Donn Morrison
WebAssembly is a low-level bytecode language that enables high-level languages like C, C++, and Rust to be executed in the browser at near-native performance. In recent years, WebAssembly has gained widespread adoption and is now natively supported by al...
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Maria Goufa, Evaggelos Makeroufas, Maria Gerakari, Efi Sarri, Athanasios Ragkos, Penelope J. Bebeli, Alma Balestrazzi and Eleni Tani
Little progress has been made in translating the increased awareness of neglected and underutilized crops into a viable tool for advancing not just sustainable development in rural areas but also sustainable agricultural and secured food systems. This is...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Shih-Hsien Hsu, Fu-Ming Tzu, Yi-Dong Chen and Chun-Wei Huang
This paper addresses the growing concern over air pollutant emissions (NOx, SOx, PM, CO2) from ocean-going vessels in harbor areas and the role of Onshore Power Supply (OPS) systems in mitigating these emissions during vessel berthing. However, the slow ...
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Xiaoou Li
This paper tackles the challenge of time series forecasting in the presence of missing data. Traditional methods often struggle with such data, which leads to inaccurate predictions. We propose a novel framework that combines the strengths of Generative ...
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George Westergaard, Utku Erden, Omar Abdallah Mateo, Sullaiman Musah Lampo, Tahir Cetin Akinci and Oguzhan Topsakal
Automated Machine Learning (AutoML) tools are revolutionizing the field of machine learning by significantly reducing the need for deep computer science expertise. Designed to make ML more accessible, they enable users to build high-performing models wit...
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John E. Marthinsen and Steven R. Gordon
The failure of major banks in 2023, such as Silicon Valley Bank (SVB), Signature Bank, First Republic Bank, and Credit Suisse, points to the continuing need for financial institutions to price liquidity risk properly and for financial systems to find alt...
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Majid Zamiri and Ali Esmaeili
In an era marked by swift technological advancements and an escalating emphasis on collaborative learning, understanding effective methods and technologies for sharing knowledge is imperative to optimize educational outcomes. This study delves into the v...
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