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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
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Proceedings ArticleDOI
10 Apr 2011
TL;DR: IMDGuard is introduced, a comprehensive security scheme for heart-related IMDs to fulfill the requirement to remain operable in an emergency when appropriate security credentials may be unavailable and incorporates two techniques tailored to provide desirable protections for IMDs.
Abstract: Recent studies have revealed security vulnerabilities in implantable medical devices (IMDs). Security design for IMDs is complicated by the requirement that IMDs remain operable in an emergency when appropriate security credentials may be unavailable. In this paper, we introduce IMDGuard, a comprehensive security scheme for heart-related IMDs to fulfill this requirement. IMDGuard incorporates two techniques tailored to provide desirable protections for IMDs. One is an ECG based key establishment without prior shared secrets, and the other is an access control mechanism resilient to adversary spoofing attacks. The security and performance of IMDGuard are evaluated on our prototype implementation.

240 citations

Journal ArticleDOI
D. Adey, F. P. An1, A. B. Balantekin2, H. R. Band3  +204 moreInstitutions (39)
TL;DR: A measurement of electron antineutrino oscillation from the Daya Bay Reactor Neutrinos Experiment with nearly 4 million reactor ν[over ¯]_{e} inverse β decay candidates observed over 1958 days of data collection is reported.
Abstract: We report a measurement of electron antineutrino oscillation from the Daya Bay Reactor Neutrino Experiment with nearly 4 million reactor ν[over ¯]_{e} inverse β decay candidates observed over 1958 days of data collection. The installation of a flash analog-to-digital converter readout system and a special calibration campaign using different source enclosures reduce uncertainties in the absolute energy calibration to less than 0.5% for visible energies larger than 2 MeV. The uncertainty in the cosmogenic ^{9}Li and ^{8}He background is reduced from 45% to 30% in the near detectors. A detailed investigation of the spent nuclear fuel history improves its uncertainty from 100% to 30%. Analysis of the relative ν[over ¯]_{e} rates and energy spectra among detectors yields sin^{2}2θ_{13}=0.0856±0.0029 and Δm_{32}^{2}=(2.471_{-0.070}^{+0.068})×10^{-3} eV^{2} assuming the normal hierarchy, and Δm_{32}^{2}=-(2.575_{-0.070}^{+0.068})×10^{-3} eV^{2} assuming the inverted hierarchy.

239 citations

Journal ArticleDOI
TL;DR: In this article, the authors provide detailed discussion on important topics in tau-charm physics that will be explored during the next few years at \bes3. Both theoretical and experimental issues are covered, including extensive reviews of recent theoretical developments and experimental techniques.
Abstract: This physics book provides detailed discussions on important topics in $\tau$-charm physics that will be explored during the next few years at \bes3 . Both theoretical and experimental issues are covered, including extensive reviews of recent theoretical developments and experimental techniques. Among the subjects covered are: innovations in Partial Wave Analysis (PWA), theoretical and experimental techniques for Dalitz-plot analyses, analysis tools to extract absolute branching fractions and measurements of decay constants, form factors, and CP-violation and \DzDzb-oscillation parameters. Programs of QCD studies and near-threshold tau-lepton physics measurements are also discussed.

238 citations

Journal ArticleDOI
TL;DR: The experimental results demonstrated capabilities and effectiveness of the proposed trajectory planning framework and algorithms to safely handle a variety of typical driving scenarios, such as static and moving objects avoidance, lane keeping, and vehicle following, while respecting the traffic rules.
Abstract: This paper focuses on the real-time trajectory planning problem for autonomous vehicles driving in realistic urban environments. To solve the complex navigation problem, we adopt a hierarchical motion planning framework. First, a rough reference path is extracted from the digital map using commands from the high-level behavioral planner. The conjugate gradient nonlinear optimization algorithm and the cubic B-spline curve are employed to smoothen and interpolate the reference path sequentially. To follow the refined reference path as well as handle both static and moving objects, the trajectory planning task is decoupled into lateral and longitudinal planning problems within the curvilinear coordinate framework. A rich set of kinematically feasible path candidates are generated to deal with the dynamic traffic both deliberatively and reactively. In the meanwhile, the velocity profile generation is performed to improve driving safety and comfort. After that, the generated trajectories are carefully evaluated by an objective function, which combines behavioral decisions by reasoning about the traffic situations. The optimal collision-free, smooth, and dynamically feasible trajectory is selected and transformed into commands executed by the low-level lateral and longitudinal controllers. Field experiments have been carried out with our test autonomous vehicle on the realistic inner-city roads. The experimental results demonstrated capabilities and effectiveness of the proposed trajectory planning framework and algorithms to safely handle a variety of typical driving scenarios, such as static and moving objects avoidance, lane keeping, and vehicle following, while respecting the traffic rules.

237 citations

Proceedings ArticleDOI
03 Apr 2019
TL;DR: A new framework named correlation congruence for knowledge distillation (CCKD), which transfers not only the instance-level information but also the correlation between instances, and a generalized kernel method based on Taylor series expansion is proposed to better capture the correlationBetween instances.
Abstract: Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level. However, they usually ignore the correlation between multiple instances, which is also valuable for knowledge transfer. In this work, we propose a new framework named correlation congruence for knowledge distillation (CCKD), which transfers not only the instance-level information but also the correlation between instances. Furthermore, a generalized kernel method based on Taylor series expansion is proposed to better capture the correlation between instances. Empirical experiments and ablation studies on image classification tasks (including CIFAR-100, ImageNet-1K) and metric learning tasks (including ReID and Face Recognition) show that the proposed CCKD substantially outperforms the original KD and other SOTA KD-based methods. The CCKD can be easily deployed in the majority of the teacher-student framework such as KD and hint-based learning methods.

236 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
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202397
2022468
20212,986
20203,468
20193,695