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Institution

General Electric

CompanyBoston, Massachusetts, United States
About: General Electric is a company organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Turbine & Signal. The organization has 76365 authors who have published 110557 publications receiving 1885108 citations. The organization is also known as: General Electric Company & GE.
Topics: Turbine, Signal, Rotor (electric), Coating, Combustor


Papers
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Journal ArticleDOI
TL;DR: In this article, the dendritic stability criterion measured is 2 αd 0 / VR 2 = 0.0195, where V is the growth velocity, R is the dandritic tip radius, a is the liquid thermal diffusivity, and d 0 is a capillary length defined in the text.

492 citations

Journal ArticleDOI
TL;DR: In this article, the authors discuss the current status, development needs and future potential to build or engineer nanostructured materials for dielectric applications in the electrical power industry.
Abstract: While specialty applications of nanotechnology in the photonics and electronics areas have seen a tremendous growth in the past several years, the use of nanodielectrics in the electrical industry (high power density and high voltage) has not shown the same level of activity. In addition to a review of nanodielectrics, we discuss in this paper, our perspective on the current status, development needs and future potential to build or engineer nanostructured materials for dielectric applications in the electrical power industry. Short and long-term future research and development needs are considered from the point of view of industrial applications.

489 citations

Journal ArticleDOI

487 citations

Proceedings ArticleDOI
Matej Kristan1, Ales Leonardis2, Jiri Matas3, Michael Felsberg4, Roman Pflugfelder5, Luka Čehovin Zajc1, Tomas Vojir3, Gustav Häger4, Alan Lukezic1, Abdelrahman Eldesokey4, Gustavo Fernandez5, Alvaro Garcia-Martin6, Andrej Muhič1, Alfredo Petrosino7, Alireza Memarmoghadam8, Andrea Vedaldi9, Antoine Manzanera10, Antoine Tran10, A. Aydin Alatan11, Bogdan Mocanu, Boyu Chen12, Chang Huang, Changsheng Xu13, Chong Sun12, Dalong Du, David Zhang, Dawei Du13, Deepak Mishra, Erhan Gundogdu11, Erhan Gundogdu14, Erik Velasco-Salido, Fahad Shahbaz Khan4, Francesco Battistone, Gorthi R. K. Sai Subrahmanyam, Goutam Bhat4, Guan Huang, Guilherme Sousa Bastos, Guna Seetharaman15, Hongliang Zhang16, Houqiang Li17, Huchuan Lu12, Isabela Drummond, Jack Valmadre9, Jae-chan Jeong18, Jaeil Cho18, Jae-Yeong Lee18, Jana Noskova, Jianke Zhu19, Jin Gao13, Jingyu Liu13, Ji-Wan Kim18, João F. Henriques9, José M. Martínez, Junfei Zhuang20, Junliang Xing13, Junyu Gao13, Kai Chen21, Kannappan Palaniappan22, Karel Lebeda, Ke Gao22, Kris M. Kitani23, Lei Zhang, Lijun Wang12, Lingxiao Yang, Longyin Wen24, Luca Bertinetto9, Mahdieh Poostchi22, Martin Danelljan4, Matthias Mueller25, Mengdan Zhang13, Ming-Hsuan Yang26, Nianhao Xie16, Ning Wang17, Ondrej Miksik9, Payman Moallem8, Pallavi Venugopal M, Pedro Senna, Philip H. S. Torr9, Qiang Wang13, Qifeng Yu16, Qingming Huang13, Rafael Martin-Nieto, Richard Bowden27, Risheng Liu12, Ruxandra Tapu, Simon Hadfield27, Siwei Lyu28, Stuart Golodetz9, Sunglok Choi18, Tianzhu Zhang13, Titus Zaharia, Vincenzo Santopietro, Wei Zou13, Weiming Hu13, Wenbing Tao21, Wenbo Li28, Wengang Zhou17, Xianguo Yu16, Xiao Bian24, Yang Li19, Yifan Xing23, Yingruo Fan20, Zheng Zhu13, Zhipeng Zhang13, Zhiqun He20 
01 Jul 2017
TL;DR: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative; results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years.
Abstract: The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new "real-time" experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.

485 citations

Journal ArticleDOI
TL;DR: A state-feedback quasi-static SRF-PLL model is proposed, which can identify and quantify the inherent frequency self-synchronization mechanism in the converter control system and explain the PLL instability issues and the related islanding-detection methods in early publications and industry reports.
Abstract: Synchronous reference frame (SRF) phase-locked loop (PLL) is a critical component for the control and grid synchronization of three-phase grid-connected power converters. The PLL behaviors, especially its low-frequency dynamics, influenced by different grid and load impedances as well as operation mode have not been investigated yet, which may not be captured by conventional linear PLL models. In this paper, we propose a state-feedback quasi-static SRF-PLL model, which can identify and quantify the inherent frequency self-synchronization mechanism in the converter control system. This self-synchronization effect is essentially due to the converter interactions with grid impedance and power flow directions. The low-frequency nonlinear behaviors of the PLL under different grid impedance conditions are then analyzed, which forms the framework of evaluating the impacts of the large penetration level of distributed generation units, weak grid, microgrid, and large reactive power consumption in terms of the frequency stability of PLL. Specifically, the PLL behavior of the converter system under islanded condition is investigated to explain the PLL instability issues and the related islanding-detection methods in early publications and industry reports.

482 citations


Authors

Showing all 76370 results

NameH-indexPapersCitations
Cornelia M. van Duijn1831030146009
Krzysztof Matyjaszewski1691431128585
Gary H. Glover12948677009
Mark E. Thompson12852777399
Ron Kikinis12668463398
James E. Rothman12535860655
Bo Wang119290584863
Wei Lu111197361911
Harold J. Vinegar10837930430
Peng Wang108167254529
Hans-Joachim Freund10696246693
Carl R. Woese10527256448
William J. Koros10455038676
Thomas A. Lipo10368243110
Gene H. Golub10034257361
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20231
202216
2021415
20201,027
20191,418
20181,862