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Journal of Marine Science and Engineering · 2026 · Vol. 14 · Issue 16 · MDPI
With the continuous expansion of deep-sea resource exploration, marine environmental monitoring, and underwater operations, Autonomous Underwater Vehicles (AUVs) have been increasingly widely applied. Aiming at the demand for high-performance main propulsion systems of Autonomous Underwater Vehicles (AUVs), this paper conducts research on the structural design and hydrodynamic performance of a 30 kW rim-driven thruster (RDT) a...
Journal of Marine Science and Engineering · 2026 · Vol. 14 · Issue 15 · MDPI
An underwater towed vehicle serves as an effective and widely applicable mobile marine observation platform. Existing towed vehicles rely heavily on cables for depth adjustment. They also suffer from poor hydrodynamic efficiency and insufficient instrument space. To address these limitations, this study developed a novel compensation control system. This system regulates the vehicle’s vertical movement and cable deployment by...
Frontiers in Marine Science · 2025 · Vol. 11 · Frontiers
The motion of waves in water causes the slow movement of drifting sea targets—a phenomenon usually ignored in target-drift prediction models for maritime search and rescue (SAR). This study examined the wave-induced drift’s influence on field-observation experiments involving two common, differently sized SAR targets—an offshore fishing vessel (OFV) and a person in the water (PIW)—using parameter stepwise calibration and machi...
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Science China Life Sciences · 2023 · Vol. 66 · Issue 5 · Springer
Hainan Bao; Jiani Cao; Mengting Chen; Min Chen; Wei Chen; Xiao Chen; Yanhao Chen; Yu Chen; Yutian Chen; Zhiyang Chen; Jagadish K. Chhetri; Yingjie Ding; Junlin Feng; Jun Guo; Mengmeng Guo; Chuting He; Yujuan Jia; Haiping Jiang; Ying Jing; Dingfeng Li; Jiaming Li; Jingyi Li; Qinhao Liang; Rui Liang; Feng Liu; Xiaoqian Liu; Zuojun Liu; Oscar Junhong Luo; Jianwei Lv; Jingyi Ma; Kehang Mao; Jiawei Nie; Xinhua Qiao; Xinpei Sun; Xiaoqiang Tang; Jianfang Wang; Qiaoran Wang; Siyuan Wang; Xuan Wang; Yaning Wang; Yuhan Wang; Rimo Wu; Kai Xia; Fu-Hui Xiao; Lingyan Xu; Yingying Xu; Haoteng Yan; Liang Yang; Ruici Yang; Yuanxin Yang; Yilin Ying; Le Zhang; Weiwei Zhang; Wenwan Zhang; Xing Zhang; Zhuo Zhang; Min Zhou; Rui Zhou; Qingchen Zhu; Zhengmao Zhu; Feng Cao; Zhongwei Cao; Piu Chan; Chang Chen; Guobing Chen; Hou-Zao Chen; Jun Chen; Weimin Ci; Bi-Sen Ding; Qiurong Ding; Feng Gao; Jing-Dong J. Han; Kai Huang; Zhenyu Ju; Qing-Peng Kong; Ji Li; Jian Li; Xin Li; Baohua Liu; Feng Liu; Lin Liu; Qiang Liu; Qiang Liu; Xingguo Liu; Yong Liu; Xianghang Luo; Shuai Ma; Xinran Ma; Zhiyong Mao; Jing Nie; Yaojin Peng; Jing Qu; Jie Ren; Ruibao Ren; Moshi Song; Zhou Songyang; Yi Eve Sun; Yu Sun; Mei Tian; Shusen Wang; Si Wang; Xia Wang; Xiaoning Wang; Yan-Jiang Wang; Yunfang Wang; Catherine C. L. Wong; Andy Peng Xiang; Yichuan Xiao; Zhengwei Xie; Daichao Xu; Jing Ye; Rui Yue; Cuntai Zhang; Hongbo Zhang; Liang Zhang; Weiqi Zhang; Yong Zhang; Yun-Wu Zhang; Zhuohua Zhang; Tongbiao Zhao; Yuzheng Zhao; Dahai Zhu; Weiguo Zou; Gang Pei; Guang-Hui Liu
Frontiers in Marine Science · 2022 · Vol. 9 · Frontiers
The presence of clouds interferes with optical remote sensing monitoring of macroalgae blooms. To solve this problem, we propose a simple method for estimating macroalgae area under clouds (Area _cloud_GT ) on MODIS imagery using the principle behind the lowpass filter. The method is based on a rectangle with clouds and eight identical adjacent rectangles surrounding it that contain macroalgae. The cloud rectangle is a central...