Institution
Nanjing University of Information Science and Technology
Education•Nanjing, China•
About: Nanjing University of Information Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Precipitation & Aerosol. The organization has 14129 authors who have published 17985 publications receiving 267578 citations. The organization is also known as: Nan Xin Da.
Papers published on a yearly basis
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TL;DR: A well-structured questionnaire was used to collect data of 360 domestic buffalo farms from Punjab Pakistan during May-July 2017 as discussed by the authors, which revealed that milk production was mainly dependent on renewable energy inputs, particularly millet, minerals, concentrates, and sorghum.
84 citations
TL;DR: A chaotic oscillator utilizing a flux-controlled memristor to produce a signal that grows in amplitude and frequency over time is introduced and a new regime of homogenous multistability was found.
Abstract: A chaotic oscillator utilizing a flux-controlled memristor to produce a signal that grows in amplitude and frequency over time is introduced in this paper. It was found that the initial condition can be used to change the starting oscillation as well as the amplitude and frequency. From this, a new regime of homogenous multistability was found, where various attractors with different initial conditions are of the same type but have different amplitudes and frequencies.
84 citations
TL;DR: An adaptive control method is utilized, together with a parameter separation technique, to construct an adaptive output feedback controller to regulate the whole systems of nonlinearly parameterized stochastic nonholonomic systems.
84 citations
TL;DR: A RDH algorithm based on prediction-error expansion that can enhance the prediction accuracy in one color channel through exploiting the edge information from another channel is proposed that outperforms the traditional RDH methods independently embedding data into each channel.
84 citations
TL;DR: In this article, the authors identify a common error pattern in climate models that resembles the IO dipole (IOD) mode of interannual variability in nature, with a strong equatorial easterly wind bias during boreal autumn accompanied by physically consistent biases in precipitation, sea surface temperature (SST), and subsurface ocean temperature.
Abstract: Long-standing biases of climate models limit the skills of climate prediction and projection. Overlooked are tropical Indian Ocean (IO) errors. Based on the phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble, the present study identifies a common error pattern in climate models that resembles the IO dipole (IOD) mode of interannual variability in nature, with a strong equatorial easterly wind bias during boreal autumn accompanied by physically consistent biases in precipitation, sea surface temperature (SST), and subsurface ocean temperature. The analyses show that such IOD-like biases can be traced back to errors in the South Asian summer monsoon. A southwest summer monsoon that is too weak over the Arabian Sea generates a warm SST bias over the western equatorial IO. In boreal autumn, Bjerknes feedback helps amplify the error into an IOD-like bias pattern in wind, precipitation, SST, and subsurface ocean temperature. Such mean state biases result in an interannual I...
84 citations
Authors
Showing all 14448 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Ashok Kumar | 151 | 5654 | 164086 |
| Lei Zhang | 135 | 2240 | 99365 |
| Bin Wang | 126 | 2226 | 74364 |
| Shuicheng Yan | 123 | 810 | 66192 |
| Zeshui Xu | 113 | 752 | 48543 |
| Xiaoming Li | 113 | 1932 | 72445 |
| Qiang Yang | 112 | 1117 | 71540 |
| Yan Zhang | 107 | 2410 | 57758 |
| Fei Wang | 107 | 1824 | 53587 |
| Yongfa Zhu | 105 | 355 | 33765 |
| James C. McWilliams | 104 | 535 | 47577 |
| Zhi-Hua Zhou | 102 | 626 | 52850 |
| Tao Li | 102 | 2483 | 60947 |
| Lei Liu | 98 | 2041 | 51163 |
| Jian Feng Ma | 97 | 305 | 32310 |