Institution
Fu Jen Catholic University
Education•Taipei, Taiwan•
About: Fu Jen Catholic University is a education organization based out in Taipei, Taiwan. It is known for research contribution in the topics: Population & Medicine. The organization has 6842 authors who have published 9512 publications receiving 171005 citations. The organization is also known as: FJU & Fu Jen.
Topics: Population, Medicine, Cancer, Hazard ratio, Apoptosis
Papers published on a yearly basis
Papers
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TL;DR: Li et al. as discussed by the authors measured the environmental efficiency of China based on environmental super-efficiency data envelopment analysis (SEDEA) model by using data of 30 provinces in China during the period of 2000-2010.
180 citations
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TL;DR: Of the various extraction solvent systems, the best extraction efficiency of carotenoids in tomato juice was achieved by employing ethanol-hexane (4:3, v/v), and Lycopene was found to be present in largest amount in tomato Juice, followed by beta-carotene and lutein.
179 citations
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TL;DR: In this article, the relationship between leptin and major depressive disorder was investigated, and the relationship of the serum leptin concentration, cholesterol, and BMI between patients with major depressive disorders, schizophrenic patients and healthy control subjects was investigated.
178 citations
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TL;DR: In this paper, a search for the lepton flavor violating τ−→μ−γ and τ −→e−γ decays based on 535 fb−1 of data accumulated at the Belle experiment is reported.
178 citations
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01 Aug 2002
TL;DR: A novel adaptive fuzzy-neural sliding-mode controller with H(infinity) tracking performance for uncertain nonlinear systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors.
Abstract: A novel adaptive fuzzy-neural sliding-mode controller with H/sub /spl infin// tracking performance for uncertain nonlinear systems is proposed to attenuate the effects caused by unmodeled dynamics, disturbances and approximate errors. Because of the advantages of fuzzy-neural systems, which can uniformly approximate nonlinear continuous functions to arbitrary accuracy, adaptive fuzzy-neural control theory is then employed to derive the update laws for approximating the uncertain nonlinear functions of the dynamical system. Furthermore, the H/sub /spl infin// tracking design technique and the sliding-mode control method are incorporated into the adaptive fuzzy-neural control scheme so that the derived controller is robust with respect to unmodeled dynamics, disturbances and approximate errors. Compared with conventional methods, the proposed approach not only assures closed-loop stability, but also guarantees an H/sub /spl infin// tracking performance for the overall system based on a much relaxed assumption without prior knowledge on the upper bound of the lumped uncertainties. Simulation results have demonstrated that the effect of the lumped uncertainties on tracking error is efficiently attenuated, and chattering of the control input is significantly reduced by using the proposed approach.
177 citations
Authors
Showing all 6861 results
Name | H-index | Papers | Citations |
---|---|---|---|
P. Chang | 170 | 2154 | 151783 |
Christian Guilleminault | 133 | 897 | 68844 |
Pan-Chyr Yang | 102 | 786 | 46731 |
Po-Ren Hsueh | 92 | 1030 | 38811 |
Shyi-Ming Chen | 90 | 425 | 22172 |
Peter J. Rossky | 74 | 280 | 21183 |
Chong-Jen Yu | 72 | 577 | 22940 |
Shuu Jiun Wang | 71 | 502 | 24800 |
Jaw-Town Lin | 67 | 434 | 15482 |
Lung Chi Chen | 63 | 267 | 13929 |
Ronald E. Taam | 59 | 290 | 12383 |
Jiann T. Lin | 58 | 190 | 10801 |
Yueh-Hsiung Kuo | 57 | 618 | 12204 |
San Lin You | 55 | 178 | 16572 |
Liang-Gee Chen | 54 | 582 | 12073 |