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Institution

Beihang University

EducationBeijing, China
About: Beihang University is a education organization based out in Beijing, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 67002 authors who have published 73507 publications receiving 975691 citations. The organization is also known as: Beijing University of Aeronautics and Astronautics.


Papers
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Journal ArticleDOI
TL;DR: This review highlights the recent research efforts toward the synthesis of noble metal-free electrocatalysts, especially at the nanoscale, and their catalytic properties for the hydrogen evolution reaction (HER), and summarizes some important examples showing that non-Pt HER electrocatsalysts could serve as efficient cocatalysts for promoting direct solar-to-hydrogen conversion in both photochemical and photoelectrochemical water splitting systems, when combined with suitable semiconductor photocatalyst.
Abstract: Sustainable hydrogen production is an essential prerequisite of a future hydrogen economy. Water electrolysis driven by renewable resource-derived electricity and direct solar-to-hydrogen conversion based on photochemical and photoelectrochemical water splitting are promising pathways for sustainable hydrogen production. All these techniques require, among many things, highly active noble metal-free hydrogen evolution catalysts to make the water splitting process more energy-efficient and economical. In this review, we highlight the recent research efforts toward the synthesis of noble metal-free electrocatalysts, especially at the nanoscale, and their catalytic properties for the hydrogen evolution reaction (HER). We review several important kinds of heterogeneous non-precious metal electrocatalysts, including metal sulfides, metal selenides, metal carbides, metal nitrides, metal phosphides, and heteroatom-doped nanocarbons. In the discussion, emphasis is given to the synthetic methods of these HER electrocatalysts, the strategies of performance improvement, and the structure/composition-catalytic activity relationship. We also summarize some important examples showing that non-Pt HER electrocatalysts could serve as efficient cocatalysts for promoting direct solar-to-hydrogen conversion in both photochemical and photoelectrochemical water splitting systems, when combined with suitable semiconductor photocatalysts.

4,351 citations

Journal ArticleDOI
TL;DR: This work introduces a comprehensive secure federated-learning framework, which includes horizontal federated learning, vertical federatedLearning, and federated transfer learning, and provides a comprehensive survey of existing works on this subject.
Abstract: Today’s artificial intelligence still faces two major challenges. One is that, in most industries, data exists in the form of isolated islands. The other is the strengthening of data privacy and security. We propose a possible solution to these challenges: secure federated learning. Beyond the federated-learning framework first proposed by Google in 2016, we introduce a comprehensive secure federated-learning framework, which includes horizontal federated learning, vertical federated learning, and federated transfer learning. We provide definitions, architectures, and applications for the federated-learning framework, and provide a comprehensive survey of existing works on this subject. In addition, we propose building data networks among organizations based on federated mechanisms as an effective solution to allowing knowledge to be shared without compromising user privacy.

2,593 citations

Proceedings ArticleDOI
18 Jun 2018
TL;DR: The Siamese region proposal network (Siamese-RPN) is proposed which is end-to-end trained off-line with large-scale image pairs for visual object tracking and consists of SiAMESe subnetwork for feature extraction and region proposal subnetwork including the classification branch and regression branch.
Abstract: Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks. However, most of these trackers can hardly get top performance with real-time speed. In this paper, we propose the Siamese region proposal network (Siamese-RPN) which is end-to-end trained off-line with large-scale image pairs. Specifically, it consists of Siamese subnetwork for feature extraction and region proposal subnetwork including the classification branch and regression branch. In the inference phase, the proposed framework is formulated as a local one-shot detection task. We can pre-compute the template branch of the Siamese subnetwork and formulate the correlation layers as trivial convolution layers to perform online tracking. Benefit from the proposal refinement, traditional multi-scale test and online fine-tuning can be discarded. The Siamese-RPN runs at 160 FPS while achieving leading performance in VOT2015, VOT2016 and VOT2017 real-time challenges.

2,016 citations

Journal ArticleDOI
TL;DR: This survey gives a systematic and comprehensive tutorial and summary on the existing disturbance/uncertainty estimation and attenuation techniques, most notably, DOBC, active disturbance rejection control, disturbance accommodation control, and composite hierarchical antidisturbance control.
Abstract: Disturbance-observer-based control (DOBC) and related methods have been researched and applied in various industrial sectors in the last four decades. This survey, at first time, gives a systematic and comprehensive tutorial and summary on the existing disturbance/uncertainty estimation and attenuation techniques, most notably, DOBC, active disturbance rejection control, disturbance accommodation control, and composite hierarchical antidisturbance control. In all of these methods, disturbance and uncertainty are, in general, lumped together, and an observation mechanism is employed to estimate the total disturbance. This paper first reviews a number of widely used linear and nonlinear disturbance/uncertainty estimation techniques and then discusses and compares various compensation techniques and the procedures of integrating disturbance/uncertainty compensation with a (predesigned) linear/nonlinear controller. It also provides concise tutorials of the main methods in this area with clear descriptions of their features. The application of this group of methods in various industrial sections is reviewed, with emphasis on the commercialization of some algorithms. The survey is ended with the discussion of future directions.

1,849 citations

Journal ArticleDOI
TL;DR: This review aims to summarize major developments in the field of lithium-sulfur batteries, starting from an overview of their electrochemistry, technical challenges and potential solutions, along with some theoretical calculation results to advance the understanding of the material interactions involved.
Abstract: Due to their high energy density and low material cost, lithium–sulfur batteries represent a promising energy storage system for a multitude of emerging applications, ranging from stationary grid storage to mobile electric vehicles. This review aims to summarize major developments in the field of lithium–sulfur batteries, starting from an overview of their electrochemistry, technical challenges and potential solutions, along with some theoretical calculation results to advance our understanding of the material interactions involved. Next, we examine the most extensively-used design strategy: encapsulation of sulfur cathodes in carbon host materials. Other emerging host materials, such as polymeric and inorganic materials, are discussed as well. This is followed by a survey of novel battery configurations, including the use of lithium sulfide cathodes and lithium polysulfide catholytes, as well as recent burgeoning efforts in the modification of separators and protection of lithium metal anodes. Finally, we conclude with an outlook section to offer some insight on the future directions and prospects of lithium–sulfur batteries.

1,816 citations


Authors

Showing all 67500 results

NameH-indexPapersCitations
Liang Wang98171845600
Shuzhi Sam Ge9788340865
Xiang Li97147242301
Stan Z. Li9753241793
Bo Huang9772840135
Tieniu Tan9670439487
Zhiyong Tang9634034277
Jing Zhang95127142163
Albert Fert9541046732
Yan Yu9347828789
Wenping Hu9381235413
Xiaojun Wu91108831687
Hao Wang89159943904
Yanlin Song8959330929
Peng Zhang88157833705
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023205
20221,178
20216,767
20206,916
20197,080