scispace - formally typeset
Search or ask a question
Institution

National University of Defense Technology

EducationChangsha, China
About: National University of Defense Technology is a education organization based out in Changsha, China. It is known for research contribution in the topics: Radar & Synthetic aperture radar. The organization has 39430 authors who have published 40181 publications receiving 358979 citations. The organization is also known as: Guófáng Kēxuéjìshù Dàxué & NUDT.


Papers
More filters
Journal ArticleDOI
TL;DR: A novel scheduling strategy-adaptive energy-efficient scheduling or AEES-for aperiodic and independent real-time tasks on heterogeneous clusters with dynamic voltage scaling for energy conservation and schedulability is proposed.

89 citations

Journal ArticleDOI
26 Sep 2012-PLOS ONE
TL;DR: The results not only provide initial steps toward the development of neurobiological diagnostic markers for major depressive disorder, but also suggest that abnormal cortical-limbic anatomical networks may contribute to the anatomical basis of emotional dysregulation and cognitive impairments associated with this disease.
Abstract: Magnetic resonance imaging studies have reported significant functional and structural differences between depressed patients and controls. Little attention has been given, however, to the abnormalities in anatomical connectivity in depressed patients. In the present study, we aim to investigate the alterations in connectivity of whole-brain anatomical networks in those suffering from major depression by using machine learning approaches. Brain anatomical networks were extracted from diffusion magnetic resonance images obtained from both 22 first-episode, treatment-naive adults with major depressive disorder and 26 matched healthy controls. Using machine learning approaches, we differentiated depressed patients from healthy controls based on their whole-brain anatomical connectivity patterns and identified the most discriminating features that represent between-group differences. Classification results showed that 91.7% (patients = 86.4%, controls = 96.2%; permutation test, p<0.0001) of subjects were correctly classified via leave-one-out cross-validation. Moreover, the strengths of all the most discriminating connections were increased in depressed patients relative to the controls, and these connections were primarily located within the cortical-limbic network, especially the frontal-limbic network. These results not only provide initial steps toward the development of neurobiological diagnostic markers for major depressive disorder, but also suggest that abnormal cortical-limbic anatomical networks may contribute to the anatomical basis of emotional dysregulation and cognitive impairments associated with this disease.

89 citations

Journal ArticleDOI
TL;DR: In this paper, two kinds of event-based protocols based on local sampled information are designed, without the need to solve any matrix equation or inequality, which guarantee the achievement of consensus and the exclusion of Zeno behaviors for jointly connected undirected switching graphs.
Abstract: This paper investigates the distributed event-based consensus problem of switching networks satisfying the jointly connected condition. Both the state consensus of homogeneous linear networks and the output consensus of heterogeneous networks are studied. Two kinds of event-based protocols based on local sampled information are designed, without the need to solve any matrix equation or inequality. Theoretical analysis indicates that the proposed event-based protocols guarantee the achievement of consensus and the exclusion of Zeno behaviors for jointly connected undirected switching graphs. These protocols, relying on no global knowledge of the network topology and independent of switching rules, can be devised and utilized in a completely distributed manner. They are able to avoid continuous information exchanges for either controllers’ updating or triggering functions’ monitoring, which ensures the feasibility of the presented protocols.

89 citations

Journal ArticleDOI
TL;DR: This paper proposes a graph learning framework to preserve both the local and global structure of data that uses the self-expressiveness of samples to capture the global structure and adaptive neighbor approach to respect the local structure.

89 citations

Journal ArticleDOI
TL;DR: This paper proposes an energy efficient and balanced cluster-based data aggregation algorithm (EEBCDA) that can remarkably enhance energy efficiency, balance energy dissipation and prolong network lifetime in clusterbased WSNs.

89 citations


Authors

Showing all 39659 results

NameH-indexPapersCitations
Rui Zhang1512625107917
Jian Li133286387131
Chi Lin1251313102710
Wei Xu103149249624
Lei Liu98204151163
Xiang Li97147242301
Chang Liu97109939573
Jian Huang97118940362
Tao Wang97272055280
Wei Liu96153842459
Jian Chen96171852917
Wei Wang95354459660
Peng Li95154845198
Jianhong Wu9372636427
Jianhua Zhang9241528085
Network Information
Related Institutions (5)
Harbin Institute of Technology
109.2K papers, 1.6M citations

94% related

Tsinghua University
200.5K papers, 4.5M citations

91% related

University of Science and Technology of China
101K papers, 2.4M citations

90% related

City University of Hong Kong
60.1K papers, 1.7M citations

89% related

Dalian University of Technology
71.9K papers, 1.1M citations

89% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202397
2022468
20212,986
20203,468
20193,695