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Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G...
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Jun Yeong Kim, Chang Geun Song, Jung Lee, Jong-Hyun Kim, Jong Wan Lee and Sun-Jeong Kim
In this paper, we propose a learning model for tracking the isolines of fluid based on the physical properties of particles in particle-based fluid simulations. Our method involves analyzing which weights, closely related to surface tracking among the va...
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Chi Gao, Xiaofei Xu, Zhizou Yang, Liwei Lin and Jian Li
In recent decades, memory-intensive applications have experienced a boom, e.g., machine learning, natural language processing (NLP), and big data analytics. Such applications often experience out-of-memory (OOM) errors, which cause unexpected processes t...
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Preethika Kasu, Prince Hamandawana and Tae-Sun Chung
Various components are involved in the end-to-end path of data transfer. Protecting data integrity from failures in these intermediate components is a key feature of big data transfer tools. Although most of these components provide some degree of data i...
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Guowei Hua, Shijie Wang, Meng Xiao and Shaohua Hu
Dam safety is considerably affected by seepage, and uplift pressure is a key indicator of dam seepage. Thus, making accurate predictions of uplift pressure trends can improve dam hazard forecasting. In this study, a convolutional neural network, (CNN)-ga...
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Yang Chao, Chaoning Lin, Tongchun Li, Huijun Qi, Dongming Li and Siyu Chen
Aiming to investigate the problem that dam-monitoring data are difficult to analyze in a timely and accurate automated manner, in this paper, we propose an automated framework for dam health monitoring based on data microservices. The framework consists ...
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Sérgio Branco, Ertugrul Dogruluk, João G. Carvalho, Marco S. Reis and Jorge Cabral
As more and more devices are being deployed across networks to gather data and use them to perform intelligent tasks, it is vital to have a tool to perform real-time data analysis. Data are the backbone of Machine Learning models, the core of intelligent...
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Jiao Shi, Tianyun Su, Xinfang Li, Fuwei Wang, Jingjing Cui, Zhendong Liu and Jie Wang
Significant wave height (SWH) is a key parameter for monitoring the state of waves. Accurate and long-term SWH forecasting is significant to maritime shipping and coastal engineering. This study proposes a transformer model based on an attention mechanis...
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Song Hu, Qi Shao, Wei Li, Guijun Han, Qingyu Zheng, Ru Wang and Hanyu Liu
Data-driven predictions of marine environmental variables are typically focused on single variables. However, in real marine environments, there are correlations among different oceanic variables. Additionally, sea?air interactions play a significant rol...
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Renteng Yuan, Shengxuan Ding and Chenzhu Wang
Accurate detection and prediction of the lane-change (LC) processes can help autonomous vehicles better understand their surrounding environment, recognize potential safety hazards, and improve traffic safety. This study focuses on the LC process, using ...
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