Experimental investigation of the normal spectral emissivity and other thermophysical properties of pulse-heated Ni-Ti and Au-Ni alloys into the liquid phase

In a previous paper it was shown that the normal spectral emissivity at 684.5 nm of a binary alloy can be lower than that of the pure constituent components. For the actual probes it was found that the observed values of normal spectral emissivity of the alloys are in between or higher than those of the pure constituent components. Experiments were conducted on the alloy systems Ni-Ti and Au-Ni. Their emissivity as well as electrical resistivity and enthalpy as a function of temperature is presented.

Generating Cartoon Images from Face Photos with Cycle-Consistent Adversarial Networks

The generative adversarial network(GAN)is first proposed in 2014,and this kind of network model is machine learning systems that can learn to measure a given distribution of data,one of the most important applications is style transfer.Style transfer is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image.CYCLE-GAN is a classic GAN model,which has a wide range of scenarios in style transfer.Considering its unsupervised learning characteristics,the mapping is easy to be learned between an input image and an output image.However,it is difficult for CYCLE-GAN to converge and generate high-quality images.In order to solve this problem,spectral normalization is introduced into each convolutional kernel of the discriminator.Every convolutional kernel reaches Lipschitz stability constraint with adding spectral normalization and the value of the convolutional kernel is limited to[0,1],which promotes the training process of the proposed model.Besides,we use pretrained model(VGG16)to control the loss of image content in the position of l1 regularization.To avoid overfitting,l1 regularization term and l2 regularization term are both used in the object loss function.In terms of Frechet Inception Distance(FID)score evaluation,our proposed model achieves outstanding performance and preserves more discriminative features.Experimental results show that the proposed model converges faster and achieves better FID scores than the state of the art.

Study of Thermal Radiation Properties of Pyrolytic Carbon Protective Coatings for Monocrystalline Silicon Furnace

The thermal radiation properties of pyrolytic carbon(PyC)protective coatings for monocrystalline silicon furnace prepared by different processes were tested.The changes of normal emissivity of carbon materials caused by PyC protective coatings were discussed,and the influence of phase structure and surface appearance on the thermal radiation properties was investigated.The results show that the thermal radiation properties of PyC protective coatings with the wave band of 5-25μm are better than C/C substrate,further,normal spectral emissivity of CVD PyC coating remains basically at 0.85-0.90,and the normal total emissivity can reach0.89,which shows high thermal radiation performance.For resin PyC coating and CVD PyC coating,the degree of graphitization are 44.53%and 16.28%respectively,and the R value of Raman spectrum are 0.964and 1.384 respectively.Relatively disorder graphite structure of the latter causes various vibration modes,and the spectral emissivity is better,so the thermal radiation property of CVD PyC coating is excellent.A lot of spherical particles exists on the surface of the CVD PyC coating,and the more interface and spacing of particles reduce the number of particles per unit volume.Therefore,the scattering of thermal radiation is strongly strengthened,and the spectral emissivity is higher.

On the Second Smallest and the Largest Normalized Laplacian Eigenvalues of a Graph

Let G be a simple connected graph with order n.Let L(G)and Q(G)be the normalized Laplacian and normalized signless Laplacian matrices of G,respectively.Letλk(G)be the k-th smallest normalized Laplacian eigenvalue of G.Denote byρ(A)the spectral radius of the matrix A.In this paper,we study the behaviors ofλ2(G)andρ(L(G))when the graph is perturbed by three operations.We also study the properties ofρ(L(G))and X for the connected bipartite graphs,where X is a unit eigenvector of L(G)corresponding toρ(L(G)).Meanwhile we characterize all the simple connected graphs withρ(L(G))=ρ(Q(G)).