Decay estimates for Schrödinger systems with time-dependent potentials in 2D

We consider the Cauchy problem for systems of nonlinear Schrödinger equations with time-dependent potentials in 2D. Under assumptions about mass resonances and potentials, we prove the global existence of the nonlinear Schrödinger systems with small initial data. In particular, by analyzing the operator $\Delta$ and time-dependent potentials ${V_{j}}$ separately, we show that the small global solutions satisfy time decay estimates of order $O((t\log{t})^{-1})$ when $p = 2$, and the small global solutions satisfy time decay estimates of order $O({t}^{-1})$ when p > 2

Ubiquitous one-time password service using generic authentication architecture

Abstract. In this paper we exploit GAA to build a scheme that converts a simple static password authentication mechanism into a one-time password (OTP) system. The scheme employs a GAA-enabled user device with a display and an input capability (e.g. a 3G mobile phone) and a GAA-aware server. Most importantly, the device does not need to be user or server specific, and can be used in the protocol with no registration or configuration (except for the installation of the necessary application software). The system also fits well to the multi-institution scenario and hence enables the provision of ubiquitous and on-demand OTP services. Keywords: One-time password, Generic Authentication Architecture, mobile securit

SegViT: Semantic Segmentation with Plain Vision Transformers

We explore the capability of plain Vision Transformers (ViTs) for semantic segmentation and propose the SegVit. Previous ViT-based segmentation networks usually learn a pixel-level representation from the output of the ViT. Differently, we make use of the fundamental component -- attention mechanism, to generate masks for semantic segmentation. Specifically, we propose the Attention-to-Mask (ATM) module, in which the similarity maps between a set of learnable class tokens and the spatial feature maps are transferred to the segmentation masks. Experiments show that our proposed SegVit using the ATM module outperforms its counterparts using the plain ViT backbone on the ADE20K dataset and achieves new state-of-the-art performance on COCO-Stuff-10K and PASCAL-Context datasets. Furthermore, to reduce the computational cost of the ViT backbone, we propose query-based down-sampling (QD) and query-based up-sampling (QU) to build a Shrunk structure. With the proposed Shrunk structure, the model can save up to $40\%$ computations while maintaining competitive performance.Comment: 9 Pages, NeurIPS 202

State transition algorithm for traveling salesman problem

Discrete version of state transition algorithm is proposed in order to solve the traveling salesman problem. Three special operators for discrete optimization problem named swap, shift and symmetry transformations are presented. Convergence analysis and time complexity of the algorithm are also considered. To make the algorithm simple and efficient, no parameter adjusting is suggested in current version. Experiments are carried out to test the performance of the strategy, and comparisons with simulated annealing and ant colony optimization have demonstrated the effectiveness of the proposed algorithm. The results also show that the discrete state transition algorithm consumes much less time and has better search ability than its counterparts, which indicates that state transition algorithm is with strong adaptability. © 2012 Chinese Assoc of Automati