Search

Your search keyword '"Zheng, Mingjie"' showing total 7 results
Start Over Author "Zheng, Mingjie" Publication Year Range This year
7 results on '"Zheng, Mingjie"'

1. A Storage Method of Online Educational Resources for College Courses Based on Artificial Intelligence Technology

Author

Zheng, Mingjie, Wang, Xu, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Yun, Lin, editor, Han, Jiang, editor, and Han, Yu, editor

Published
2024
Full Text
View/download PDF

2. Intelligent Library Educational Information Digital Resources Retrieval Based on Ant Colony Algorithm

Author

Wang, Xu, Zheng, Mingjie, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Yun, Lin, editor, Han, Jiang, editor, and Han, Yu, editor

Published
2024
Full Text
View/download PDF

5. PiezoClimber: Versatile and Self‐Transitional Climbing Soft Robot with Bioinspired Highly Directional Footpads.

Author

Zheng, Mingjie, Wang, Dongkai, Zhu, Dekuan, Cao, Shuhong, Wang, Xiaohao, and Zhang, Min

Subjects
*STATURE, *ROUGH surfaces, *SURFACE roughness, *PIEZOELECTRIC actuators, *BIOLOGICALLY inspired computing
Abstract

The ability to climb is crucial for terrestrial robots to expand their scope of application with improved navigation capacity. While some soft climbing devices are available, they often lack versatility when it comes to adapting to rough surfaces and changes in terrains. In this regard, a piezo‐based soft robot with bioinspired footpads has been developed that can deliver superior climbing performance. Through their unprecedented directional friction, these footpads enable the robot to complete rigorous climbing tasks on surfaces with a climbing angle of 0–180° and a variety of roughness from ultra‐smooth to millimeter‐scale. With a unique slide‐swing gait, the robot is able to complete fast climbing on a 90° substrate at a speed of 1.4 body lengths per second (BL/s) and self‐transitional climbing on surfaces with a roughness difference of 11 µm and an angle change of 60° in 5 s without active control. A scaled down version of this climber is also presented with increased mobility to traverse steps of 3 body heights and slits of 0.75 BH effectively. In summary, the development of this soft robot with highly directional footpads paves the way for soft robots to navigate varied surfaces and ascend challenging terrains with improved mobility. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

6. The miR‐17‐92 cluster in cardiac health and disease.

Author

Cao, Yuhan, Zheng, Mingjie, Sewani, Maham A., and Wang, Jun

Abstract

MicroRNAs (miRs) are small noncoding RNAs that play important roles in both physiological and pathological processes through post‐transcriptional regulation. The miR‐17‐92 cluster includes six individual members: miR‐17, miR‐18a, miR‐19a, miR‐19b‐1, miR‐20a, and miR‐92a‐1. The miR‐17‐92 cluster has been extensively studied and reported to broadly function in cancer biology, immunology, neurology, pulmonology, and cardiology. This review focuses on its roles in heart development and cardiac diseases. We briefly introduce the nature of the miR‐17‐92 cluster and its crucial roles in both normal development and the pathogenesis of various diseases. We summarize the recent progress in understanding the versatile roles of miR‐17‐92 during cardiac development, regeneration, and aging. Additionally, we highlight the indispensable roles of the miR‐17‐92 cluster in pathogenesis and therapeutic potential in cardiac birth defects and adult cardiac diseases. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

7. An Adaptive False Target Suppression and Radial Velocity Estimation Method of Moving Targets Based on Image-Domain for High-Resolution and Wide-Swath SAR

Author

Ren, Yuwei, Zheng, Mingjie, Zhang, Lei, Fan, Huaitao, and Xie, Yuhong

Abstract

For azimuth multichannel (AMC) high-resolution and wide-swath (HRWS) synthetic aperture radar (SAR) systems, nonuniformly sampled signals will lead to false targets appearing in the image, which has a great impact on image quality and target detection. Many spectrum reconstruction methods for stationary scenes have been proposed to obtain images without false targets, but it is ineffective for moving targets due to the phase error caused by radial velocity. To present the radial velocity effect on the reconstructed image clearly, we establish a precise relation between the characteristics (imaging position, residual RCM, and amplitude) of false targets and radial velocity from the Doppler domain perspective. According to the effect analysis, we propose an image-domain false target suppression and radial velocity estimation method for moving targets. First, obtain multiple images through imaging preprocessing. Second, estimate and compensate the phase error of false targets based on the least $L^{1}$ -norm optimization model to suppress false targets. Third, estimate the radial velocity of real moving targets based on the cross correlation method. Compared to the existing methods, the proposed method is processed in the image domain which has a high signal-to-noise ratio (SNR) with the advantages of not requiring recognition and extraction of targets, lower computational complexity, and applicability for slow targets, fast targets, and multiple targets of the same range cell. The simulated SAR data and GaoFen-3 SAR data are processed to demonstrate the effectiveness of the proposed method. Furthermore, the radial velocity estimation method is verified by automatic identification system (AIS) information.

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results