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Kefei Zhu, Xu Yang, Yanbo Zhang, Mengkun Liang and Jun Wu
With the rising popularity of the Advanced Driver Assistance System (ADAS), there is an increasing demand for more human-like car-following performance. In this paper, we consider the role of heterogeneity in car-following behavior within car-following m...
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Xiaoqiang Zhu, Guobin Wang, Jieyun Xie, Ya Zhao and Donghui Liang
The main goal of this article is to elucidate the SDZ and TN removal characteristics and mechanisms of a saline-resistant strain of Acinetobacter sp. RT-6. The SDZ and TN removal characteristics indicated that SDZ and TN removal were significantly affect...
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Ce Liang, Jun Zhu, Jinbin Zhang, Qing Zhu, Jingyi Lu, Jianbo Lai and Jianlin Wu
It is essential to establish a digital twin scene, which helps to depict the dynamically changing geographical environment accurately. Digital twins could improve the refined management level of intelligent tunnel construction; however, research on geogr...
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Bangchu Zhang, Yiyong Liang, Shuitao Rao, Yu Kuang and Weiyu Zhu
In hypersonic flight control, characterized by challenges posed by input saturation, model parameter uncertainties, and external disturbances, this paper introduces a pioneering anti-input saturation control method based on RBFNN adaptivity. We have deve...
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Zengyu Cai, Chunchen Tan, Jianwei Zhang, Liang Zhu and Yuan Feng
As network technology continues to develop, the popularity of various intelligent terminals has accelerated, leading to a rapid growth in the scale of wireless network traffic. This growth has resulted in significant pressure on resource consumption and ...
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Xiaomeng Shi, Jinglai Sun, Yi Qi, Xiangyang Zhu, Xueming Zhang, Ruisong Liang and Hongjiang Chen
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Xiaojun Zhu, Longji Dang, Shuting Liang, Ming Zhang, Jian Yang and Xin Dai
To investigate the hysteretic behavior of an X-shaped metal damper (XMD) with an oblique angle, cyclic loading tests were carried out on nine specimens, including two XMDs without buckling-restrained devices, four XMDs with stiffening ribs, and three XMD...
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Liang Du, Jie Dou, Hideki Mizunaga, Zhongling Zong, Wenjin Zhu, Xiaotian Dong and Wenbo Wu
Water percolation usually occurs in soil, making it highly challenging to simultaneously monitor and verify the water percolation process in real-time. We propose employing electrical resistivity tomography and the photography technique, respectively, to...
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Yifan Liang, Chuhan Ying, Jianyu Zhu, Qian Zhou, Kuan Sun, Yajun Tian and Jun Li
Microplastics (MPs), as vectors for various pollutants in the environment, have been arousing public concern in recent years. The extensive use of antibiotics has led to their frequent detection in water environments, where they inevitably coexist with M...
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Wenjie Zhang, Liang Zhu, Qifeng Zhuang, Dong Chen and Tao Sun
Nitrogen (N) and phosphorus (P) are primary indicators of soil nutrients in agriculture. Accurate management of these nutrients is essential for ensuring food security. High-resolution, multi-spectral remote sensing images can provide crucial information...
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Chunhua Zhu, Jiarui Liang and Fei Zhou
Stemming from the overlap of objects and undertraining due to few samples, road dense object detection is confronted with poor object identification performance and the inability to recognize edge objects. Based on this, one transfer learning-based YOLOv...
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Liang Chi, Mengshuai Zhu, Chen Shen, Jing Zhang, Liwei Xing and Xiangyang Zhou
This paper explores the impact of e-commerce on profit margin from the perspective of scale using nation-level survey data from China. The results show that e-commerce can increase the profit margin of cooperatives, and that a higher proportion of sales ...
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Liang Zhao, Qing Yun, Fucai Yuan, Xu Ren, Junwei Jin and Xianchao Zhu
Underwater target detection plays a crucial role in marine environmental monitoring and early warning systems. It involves utilizing optical images acquired from underwater imaging devices to locate and identify aquatic organisms in challenging environme...
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Wanlu Zhu, Tianwen Gu, Jie Wu and Zhengzhuo Liang
In instances where vessels encounter impacts or other factors leading to communication impairments, the status of electrical equipment becomes inaccessible through standard communication lines for the controllers. Consequently, the shipboard power system...
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Chengxi Wu, Yuewei Dai, Liang Shan and Zhiyu Zhu
This paper focuses on developing a data-driven trajectory tracking control approach for autonomous underwater vehicles (AUV) under uncertain external disturbance and time-delay. A novel model-free adaptive predictive control (MFAPC) approach based on a f...
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Man Zhu, Wuqiang Sun, Yuanqiao Wen and Liang Huang
Identification of parameters involved in the linear response model with high precision is a highly cost-effective, as well as a challenging task, in developing a suitable model for the verification and validation (V+V) of some key techniques for autonomo...
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Dongfang Liang, Jie Huang, Jingxin Zhang, Shujing Shi, Nichenggong Zhu and Jun Chen
In the past few decades, there have been many numerical studies on the scour around offshore pipelines, most of which concern two-dimensional setups, with the pipeline infinitely long and the flow perpendicular to the pipeline. Based on the Ansys FLUENT ...
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Wanlu Zhu, Chunpeng Jin and Zhengzhuo Liang
The complex dynamic characteristics of a shipboard power system (SPS) are not only related to its continuous dynamics but also influenced by discrete control behavior. Especially, during combat mission execution of high-power pulse loads (HPPLs), their o...
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Minglong Zhang, Liang Huang, Yuanqiao Wen, Jinfen Zhang, Yamin Huang and Man Zhu
The prediction of ship location has become an increasingly popular research hotspot in the field of maritime transportation engineering, which benefits maritime safety supervision and security. Existing methods of ship location prediction based on motion...
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Qianqian Tong, Guannan Liang, Jiahao Ding, Tan Zhu, Miao Pan and Jinbo Bi
Regularized sparse learning with the l0
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-norm is important in many areas, including statistical learning and signal processing. Iterative hard thresholding (IHT) methods are the state-of-the-art for nonconvex-constrained sparse learning due to their ...
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