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Institution

Northeastern University (China)

EducationShenyang, China
About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).


Papers
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Journal ArticleDOI
01 Apr 2013-Carbon
TL;DR: These CNPs have a distinct pH-sensitive feature that gives them the potential to serve as a proton sensor in monitoring cell metabolization process with proton release and exhibit low cytotoxicity and favorable biocompatibility.

197 citations

Proceedings ArticleDOI
03 Nov 2014
TL;DR: A system AutoCog is presented to automatically assess description-to-permission fidelity of applications and outperforms other related work on both performance of detection and ability of generalization over various permissions by a large extent.
Abstract: The booming popularity of smartphones is partly a result of application markets where users can easily download wide range of third-party applications. However, due to the open nature of markets, especially on Android, there have been several privacy and security concerns with these applications. On Google Play, as with most other markets, users have direct access to natural-language descriptions of those applications, which give an intuitive idea of the functionality including the security-related information of those applications. Google Play also provides the permissions requested by applications to access security and privacy-sensitive APIs on the devices. Users may use such a list to evaluate the risks of using these applications. To best assist the end users, the descriptions should reflect the need for permissions, which we term description-to-permission fidelity. In this paper, we present a system AutoCog to automatically assess description-to-permission fidelity of applications. AutoCog employs state-of-the-art techniques in natural language processing and our own learning-based algorithm to relate description with permissions. In our evaluation, AutoCog outperforms other related work on both performance of detection and ability of generalization over various permissions by a large extent. On an evaluation of eleven permissions, we achieve an average precision of 92.6% and an average recall of 92.0%. Our large-scale measurements over 45,811 applications demonstrate the severity of the problem of low description-to-permission fidelity. AutoCog helps bridge the long-lasting usability gap between security techniques and average users.

196 citations

Journal ArticleDOI
TL;DR: It is proved that the overall closed-loop system is stable in the sense of semi-globally uniformly ultimately bounded in mean square, and the output of the switched system converges to a small neighborhood of the origin with appropriate choice of design parameters.
Abstract: This paper considers the problem of adaptive fuzzy backstepping-based output-feedback controller design for a class of uncertain switched nonlinear stochastic systems in lower-triangular form without the measurements of the system states. By combining fuzzy logic systems’ universal approximation ability and dynamic surface control technique in the adaptive backstepping recursive design with a modified average dwell-time scheme, a new adaptive fuzzy control approach is presented for the switched system. More specifically, a switched observer is constructed to reduce the conservativeness aroused by the employ of a common observer, and individual coordinate transformations for subsystems are given up by adopting a common coordinate transformation of all subsystems. It is proved that the overall closed-loop system is stable in the sense of semi-globally uniformly ultimately bounded in mean square, and the output of the switched system converges to a small neighborhood of the origin with appropriate choice of design parameters. Finally, simulation studies are provided to demonstrate the validity of the proposed control method.

195 citations

Journal ArticleDOI
TL;DR: A classifier trained by SVM (Support Vector Machine) is used to recognize pedestrians, the recognition performance is further improved with the aid of tracking results, and the pedestrian recognition and tracking system is integrated with the autonomous vehicle platform which provides timely prediction of pedestrian motions.

195 citations

Journal ArticleDOI
TL;DR: In the proposed IFFO, a new control parameter is introduced to tune the search scope around its swarm location adaptively and a new solution generating method is developed to enhance accuracy and convergence rate of the algorithm.
Abstract: This paper presents an improved fruit fly optimization (IFFO) algorithm for solving continuous function optimization problems. In the proposed IFFO, a new control parameter is introduced to tune the search scope around its swarm location adaptively. A new solution generating method is developed to enhance accuracy and convergence rate of the algorithm. Extensive computational experiments and comparisons are carried out based on a set of 29 benchmark functions from the literature. The computational results show that the proposed IFFO not only significantly improves the basic fruit fly optimization algorithm but also performs much better than five state-of-the-art harmony search algorithms.

194 citations


Authors

Showing all 36436 results

NameH-indexPapersCitations
Rui Zhang1512625107917
Hui-Ming Cheng147880111921
Yonggang Huang13679769290
Yang Liu1292506122380
Tao Zhang123277283866
J. R. Dahn12083266025
Terence G. Langdon117115861603
Frank L. Lewis114104560497
Xin Li114277871389
Peng Wang108167254529
David J. Hill107136457746
Jian Zhang107306469715
Xuemin Shen106122144959
Yi Zhang102181753417
Tao Li102248360947
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023166
2022906
20214,689
20204,118
20193,653
20182,878