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Research on concreting equipment planning of ship lift boat cab segment in Three Gorges Project

Huang Jiaquan,Ma Shaofu,Yu Yongjun

Strategic Study of CAE 2013, Volume 15, Issue 9, Pages 59-63

Abstract: justify;">This paper describes the selection process on concrete construction equipment of ship lift boatcab segment in Three Gorges Project in detail, including analysis on the characteristics of concreteconstruction in boat cab segment, selection argumentation of construction equipment at the tender stagecab section effectively covers all pouring surface, meeting the warehousing strength requirements inThe concreting equipments of Three Gorges Project ship lift boat cab segment have been pre-rational planned

Keywords： construction equipment equipment layout concrete pouring boat cab Three Gorges Project ship lift

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A convolutional neural network based approach to sea clutter suppression for small boat detection

Guan-qing Li, Zhi-yong Song, Qiang Fu,liguanqing09@nudt.edu.cn,songzhiyong08@nudt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 10, Pages 1413-1534 doi: 10.1631/FITEE.1900523

Abstract: Current methods for radar target detection usually work on the basis of high signal-to-clutter ratios. In this paper we propose a novel convolutional neural network based dual-activated clutter suppression algorithm, to solve the problem caused by low signal-to-clutter ratios in actual situations on the sea surface. Dual activation has two steps. First, we multiply the activated weights of the last dense layer with the activated feature maps from the upsample layer. Through this, we can obtain the s (CAMs), which correspond to the positive region of the sea clutter. Second, we obtain the suppression coefficients by mapping the CAM inversely to the sea clutter spectrum. Then, we obtain the activated range-Doppler maps by multiplying the coefficients with the raw range-Doppler maps. In addition, we propose a sampling-based data augmentation method and an effective multiclass coding method to improve the prediction accuracy. Measurement on real datasets verified the effectiveness of the proposed method.