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Institution

Southeast University

EducationNanjing, China
About: Southeast University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Computer science & MIMO. The organization has 66363 authors who have published 79434 publications receiving 1170576 citations. The organization is also known as: SEU.


Papers
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Journal ArticleDOI
TL;DR: This paper designs a centralized switching consensus protocol such that the finite-time consensus can be realized in a fast speed, and provides two numerical examples to illustrate the superiority of the proposed protocol and design method.
Abstract: In this paper, we study the problem of finite-time consensus of multiagent systems on a fixed directed interaction graph with a new protocol. Existing finite-time consensus protocols can be divided into two types: 1) continuous and 2) discontinuous, which were studied separately in the past. In this paper, we deal with both continuous and discontinuous protocols simultaneously, and design a centralized switching consensus protocol such that the finite-time consensus can be realized in a fast speed. The switching protocol depends on the range of the initial disagreement of the agents, for which we derive an exact bound to indicate at what time a continuous or a discontinuous protocol should be selected to use. Finally, we provide two numerical examples to illustrate the superiority of the proposed protocol and design method.

175 citations

Proceedings ArticleDOI
15 Jun 2019
TL;DR: Wang et al. as discussed by the authors proposed a multi-granularity generator (MGG) to perform the temporal action proposal from different granularity perspectives, relying on the video visual features equipped with the position embedding information.
Abstract: Temporal action proposal generation is an important task, aiming to localize the video segments containing human actions in an untrimmed video. In this paper, we propose a multi-granularity generator (MGG) to perform the temporal action proposal from different granularity perspectives, relying on the video visual features equipped with the position embedding information. First, we propose to use a bilinear matching model to exploit the rich local information within the video sequence. Afterwards, two components, namely segment proposal producer (SPP) and frame actionness producer (FAP), are combined to perform the task of temporal action proposal at two distinct granularities. SPP considers the whole video in the form of feature pyramid and generates segment proposals from one coarse perspective, while FAP carries out a finer actionness evaluation for each video frame. Our proposed MGG can be trained in an end-to-end fashion. Through temporally adjusting the segment proposals with fine-grained information based on frame actionness, MGG achieves the superior performance over state-of-the-art methods on the public THUMOS-14 and ActivityNet-1.3 datasets. Moreover, we employ existing action classifiers to perform the classification of the proposals generated by MGG, leading to significant improvements compared against the competing methods for the video detection task.

175 citations

Journal ArticleDOI
TL;DR: In this article, the concept of high-temperature air/steam-blown gasification technology for converting coal into low-caloric-value gas for power generation is proposed and evaluated experimentally.
Abstract: The concept of high-temperature air/steam-blown gasification technology for converting coal into low-caloric-value gas for power generation is proposed and evaluated experimentally. Preliminary experiments are performed in a 0.1 MW thermal input pressurized spout-fluid bed gasifier. The influences of the gasifying agent preheat temperature, the gasification temperature and pressure, the equivalence ratio, the ratio of steam-to-coal on gas composition, gas higher heating value, carbon conversion, and cold gas efficiency are examined. The experimental results prove the feasibility of high-temperature air/steam-blown gasification process. The gas heating value is increased by 23%, when the gasifying agent temperature is increased from 300 to 700 °C. For the operation conditions studied, the results show that gasification temperature is the most important factor influencing coal gasification in the spout-fluid bed. The gasifier performance is improved at elevated pressure mainly due to the better fluidization...

175 citations

Journal ArticleDOI
TL;DR: In this article, a finite element investigation into interfacial stresses in reinforced concrete (RC) beams strengthened with a bonded soffit plate is presented, with the aims of assessing the accuracy of existing approximate closed-form analytical solutions based on simplifying assumptions and highlighting aspects which are omitted by them.

175 citations

Journal ArticleDOI
Heng-Yun Ye1, Da-Wei Fu1, Yi Zhang1, Wen Zhang1, Ren-Gen Xiong1, Songping D. Huang1 
TL;DR: Cobalt(II) (R)-2-methylpiperazine (MPPA) trichloride is the first example of ferroelectric MOC that can really reach the spontaneous polarization status and opens up a new avenue to explore novel MOC-based ferroelectrics.
Abstract: Metal−organic coordination (MOC)-type ferroelectrics, cobalt(II) (R)-2-methylpiperazine (MPPA) trichloride [CoIICl3(H-MPPA)], was constructed through hydrogen bonds. It is a good ferroelectric candidate with a Ps = 6.8 μC·cm−2 as high as almost twice that of triglycine sulfate (Ps = 3.5 μC·cm−2) and significantly larger than that of KH2PO4 at the low-temperature ferroelectric phase Fdd2. [CoIICl3(H-MPPA)] is the first example of ferroelectric MOC that can really reach the spontaneous polarization status and opens up a new avenue to explore novel MOC-based ferroelectrics.

175 citations


Authors

Showing all 66906 results

NameH-indexPapersCitations
H. S. Chen1792401178529
Yang Yang1712644153049
Gang Chen1673372149819
Xiang Zhang1541733117576
Rui Zhang1512625107917
Yi Yang143245692268
Guanrong Chen141165292218
Wei Huang139241793522
Jun Chen136185677368
Jian Li133286387131
Xiaoou Tang13255394555
Zhen Li127171271351
Tao Zhang123277283866
Bo Wang119290584863
Jinde Cao117143057881
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023228
20221,302
20219,150
20208,667
20197,684
20186,464