185 research outputs found
UNDERSTANDING USAGE OF PUBLIC BIKE SHARING SYSTEM : CITI BIKE AS AN EXAMPLE
In recent years, bike sharing systems ushered in the explosive growth. The growth of bike sharing systems brings both health benefits and environmental benefits.This study is a data analysis project that investigate the usage pattern of bike sharing system using Citi Bike open source data. This study provide a demand prediction and gender prediction model. Also, this study studied the influence of weather and date on the demand of bike usage, and compare the characteristic usage pattern of two different gender group. With the comparison on usage of NY taxi, this study analysis when people prefer Citi Bike and verify that Citi Bike can be an ideal alternative transportation to taxis.Master of Science in Information Scienc
Practical Blind Denoising via Swin-Conv-UNet and Data Synthesis
While recent years have witnessed a dramatic upsurge of exploiting deep
neural networks toward solving image denoising, existing methods mostly rely on
simple noise assumptions, such as additive white Gaussian noise (AWGN), JPEG
compression noise and camera sensor noise, and a general-purpose blind
denoising method for real images remains unsolved. In this paper, we attempt to
solve this problem from the perspective of network architecture design and
training data synthesis. Specifically, for the network architecture design, we
propose a swin-conv block to incorporate the local modeling ability of residual
convolutional layer and non-local modeling ability of swin transformer block,
and then plug it as the main building block into the widely-used image-to-image
translation UNet architecture. For the training data synthesis, we design a
practical noise degradation model which takes into consideration different
kinds of noise (including Gaussian, Poisson, speckle, JPEG compression, and
processed camera sensor noises) and resizing, and also involves a random
shuffle strategy and a double degradation strategy. Extensive experiments on
AGWN removal and real image denoising demonstrate that the new network
architecture design achieves state-of-the-art performance and the new
degradation model can help to significantly improve the practicability. We
believe our work can provide useful insights into current denoising research.Comment: Codes: https://github.com/cszn/SCUNe
Dynamics Analysis of Neuron Bursting under the Modulation of Periodic Stimulation
A nonsmooth neuron model with periodic excitation which can reproduce spiking and bursting behavior of cortical neurons is investigated in this paper. Based on nonsmooth bifurcation analysis, the mechanism of the bursting behavior induced by slow-changing periodical stimulation as well as the associated evolution with the variation of the stimulation is explored. The modulating character of the external excitation and the effect of the bifurcation occurring at the switching boundary of the vector field are presented
Highly efficient and enantioselective hydrogenation of quinolines and pyridines with Ir-Difluorphos catalyst
The combination of the readily available chiral bisphosphine ligand Difluorphos with [Ir(COD)Cl] 2 in THF resulted in a highly efficient catalyst system for asymmetric hydrogenation of quinolines at quite low catalyst loadings (0.05-0.002 mol%), affording the corresponding products with high enantioselectivities (up to 96%), excellent catalytic activities (TOF up to 3510 h -1 ) and productivities (TON up to 43000). The same catalyst was also successfully applied to the asymmetric hydrogenation of trisubstituted pyridines with nearly quantitative yields and up to 98% ee. In these two reactions, the addition of I 2 additive is indispensable; but the amount of I 2 has a different effect on catalytic performance
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