Attractors for second order nonautonomous lattice system with dispersive term

In this paper, we prove the existence of pullback attractor, pullback exponential attractor and uniform attractor for second order non-autonomous lattice system with dispersive term and time-dependent forces. Then we prove the existence of uniform exponential attractor for the system driven by quasi-periodic external forces

Limiting behavior of a global attractor for lattice nonclassical parabolic equations

AbstractWe prove the upper semicontinuity of the global attractor corresponding to a class of lattice nonclassical parabolic equations

Asymptotic behavior for second order lattice dynamical systems

We consider the existence of the global attractor for a second order lattice dynamical systems

Traveling wavefronts of a prey–predator diffusion system with stage-structure and harvesting

AbstractFrom a biological point of view, we consider a prey–predator-type free diffusion fishery model with stage-structure and harvesting. First, we study the stability of the nonnegative constant equilibria. In particular, the effect of harvesting on the stability of equilibria is discussed and supported with numerical simulation. Then, employing the upper and lower solution method, we show that when the wave speed is large enough there exists a traveling wavefront connecting the zero solution to the positive equilibrium of the system. Numerical simulation is also carried out to illustrate the main result

Oscillation for a class of neutral parabolic differential equations

AbstractSome sufficient conditions are established for the oscillation of a class of neutral parabolic differential equations of the form,∂N(u(x,t)−∑k=1rλku(x,t−ρk))∂tN−a(t)Δu+∑i=1npi(x,t)u(x,t−σi)−∑j=1mqj(x,t)u(x,t−τj)+h(t)f(u(x,t−r1),,u(x,t−rl))=0,(x,t)∈Ω×[t0,+∞)≡G,t0∈R+,where N is an odd number, Ω is a bounded domain in RM with a smooth boundary ∂Ω, and Δ is the Laplacian operation with three different boundary conditions. We obtained some new oscillatory conditions for the odd-order neutral parabolic differential equation. To some extent, our results are new oscillatory conditions, and extended some oscillatory results of some references

Efficient Fully Convolution Neural Network for Generating Pixel Wise Robotic Grasps With High Resolution Images

This paper presents an efficient neural network model to generate robotic grasps with high resolution images. The proposed model uses fully convolution neural network to generate robotic grasps for each pixel using 400 $\times$ 400 high resolution RGB-D images. It first down-sample the images to get features and then up-sample those features to the original size of the input as well as combines local and global features from different feature maps. Compared to other regression or classification methods for detecting robotic grasps, our method looks more like the segmentation methods which solves the problem through pixel-wise ways. We use Cornell Grasp Dataset to train and evaluate the model and get high accuracy about 94.42% for image-wise and 91.02% for object-wise and fast prediction time about 8ms. We also demonstrate that without training on the multiple objects dataset, our model can directly output robotic grasps candidates for different objects because of the pixel wise implementation.Comment: Submitted to ROBIO 201