Universal flux-fluctuation law in small systems

We thank Dr. DeMenezes for providing the microchip data. This work was partially supported by the NSF of China under Grant Nos. 11135001, 11275003. Y.C.L. was supported by ARO under Grant No. W911NF-14-1-0504.Peer reviewedPublisher PD

A Morphological Approach to the Pulsed Emission from Soft Gamma Repeaters

We present a geometrical methodology to interpret the periodical light curves of Soft Gamma Repeaters based on the magnetar model and the numerical arithmetic of the three-dimensional magnetosphere model for the young pulsars. The hot plasma released by the star quake is trapped in the magnetosphere and photons are emitted tangent to the local magnetic field lines. The variety of radiation morphologies in the burst tails and the persistent stages could be well explained by the trapped fireballs on different sites inside the closed field lines. Furthermore, our numerical results suggests that the pulse profile evolution of SGR 1806-20 during the 27 December 2004 giant flare is due to a lateral drift of the emitting region in the magnetosphere.Comment: 7 figures, accepted by Ap

Web3D learning framework for 3D shape retrieval based on hybrid convolutional neural networks

With the rapid development of Web3D technologies, sketch-based model retrieval has become an increasingly important challenge, while the application of Virtual Reality and 3D technologies has made shape retrieval of furniture over a web browser feasible. In this paper, we propose a learning framework for shape retrieval based on two Siamese VGG-16 Convolutional Neural Networks (CNNs), and a CNN-based hybrid learning algorithm to select the best view for a shape. In this algorithm, the AlexNet and VGG-16 CNN architectures are used to perform classification tasks and to extract features, respectively. In addition, a feature fusion method is used to measure the similarity relation of the output features from the two Siamese networks. The proposed framework can provide new alternatives for furniture retrieval in the Web3D environment. The primary innovation is in the employment of deep learning methods to solve the challenge of obtaining the best view of 3D furniture, and to address cross-domain feature learning problems. We conduct an experiment to verify the feasibility of the framework and the results show our approach to be superior in comparison to many mainstream state-of-the-art approaches

Parameter estimation of fractional uncertain differential equations via Adams method

Parameter estimation of uncertain differential equations becomes popular very recently. This paper suggests a new method based on fractional uncertain differential equations for the first time, which hold more parameter freedom degrees. The Adams numerical method and Adam algorithm are adopted for the optimization problems. The estimation results are compared to show a better forecast. Finally, the predictor–corrector method is adopted to solve the fractional uncertain differential equations. Numerical solutions are demonstrated with varied α-paths