Xidian University

About: Xidian University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Antenna (radio) & Synthetic aperture radar. The organization has 32099 authors who have published 38961 publications receiving 431820 citations. The organization is also known as: University of Electronic Science and Technology at Xi'an & Xīān Diànzǐ Kējì Dàxué.

A Fast and Robust Level Set Method for Image Segmentation Using Fuzzy Clustering and Lattice Boltzmann Method

Abstract: In the last decades, due to the development of the parallel programming, the lattice Boltzmann method (LBM) has attracted much attention as a fast alternative approach for solving partial differential equations In this paper, we first designed an energy functional based on the fuzzy c -means objective function which incorporates the bias field that accounts for the intensity inhomogeneity of the real-world image Using the gradient descent method, we obtained the corresponding level set equation from which we deduce a fuzzy external force for the LBM solver based on the model by Zhao The method is fast, robust against noise, independent to the position of the initial contour, effective in the presence of intensity inhomogeneity, highly parallelizable and can detect objects with or without edges Experiments on medical and real-world images demonstrate the performance of the proposed method in terms of speed and efficiency

Physically Transient Resistive Switching Memory Based on Silk Protein.

Abstract: Physically transient resistive switching devices based on silk protein are successfully demonstrated. The devices can be absolutely dissolved in deionized water or in phosphate-buffered saline in 2 h. At the same time, a reasonable resistance OFF/ON ratio of larger than 10(2) and a retention time of more than 10(4) s are achieved for nonvolatile memory applications.

Joint Placement of Controllers and Gateways in SDN-Enabled 5G-Satellite Integrated Network

Abstract: Leveraging the concept of software-defined network (SDN), the integration of terrestrial 5G and satellite networks brings us lots of benefits. The placement problem of controllers and satellite gateways is of fundamental importance for design of such SDN-enabled integrated network, especially, for the network reliability and latency, since different placement schemes would produce various network performances. To the best of our knowledge, it is an entirely new problem. Toward this end, in this paper, we first explore the satellite gateway placement problem to obtain the minimum average latency. A simulated annealing based approximate solution (SAA), is developed for this problem, which is able to achieve a near-optimal latency. Based on the analysis of latency, we further investigate a more challenging problem, i.e., the joint placement of controllers and gateways, for the maximum network reliability while satisfying the latency constraint. A simulated annealing and clustering hybrid algorithm (SACA) is proposed to solve this problem. Extensive experiments based on real world online network topologies have been conducted and as validated by our numerical results, enumeration algorithms are able to produce optimal results but having extremely long running time, while SAA and SACA can achieve approximate optimal performances with much lower computational complexity.

Bayesian Face Sketch Synthesis

Abstract: Exemplar-based face sketch synthesis has been widely applied to both digital entertainment and law enforcement. In this paper, we propose a Bayesian framework for face sketch synthesis, which provides a systematic interpretation for understanding the common properties and intrinsic difference in different methods from the perspective of probabilistic graphical models. The proposed Bayesian framework consists of two parts: the neighbor selection model and the weight computation model. Within the proposed framework, we further propose a Bayesian face sketch synthesis method. The essential rationale behind the proposed Bayesian method is that we take the spatial neighboring constraint between adjacent image patches into consideration for both aforementioned models, while the state-of-the-art methods neglect the constraint either in the neighbor selection model or in the weight computation model. Extensive experiments on the Chinese University of Hong Kong face sketch database demonstrate that the proposed Bayesian method could achieve superior performance compared with the state-of-the-art methods in terms of both subjective perceptions and objective evaluations.

Improved Fuzzy Bayesian Network-Based Risk Analysis With Interval-Valued Fuzzy Sets and D–S Evidence Theory

Abstract: A novel risk analysis approach is developed by merging interval-valued fuzzy sets (IVFSs), improved Dempster–Shafer (D–S) evidence theory, and fuzzy Bayesian networks (BNs), acting as a systematic decision support approach for safety insurance for the entire life cycle of a complex system under uncertainty. Aiming to alleviate the problem of insufficient and imprecise data collected from the complicated environment, the expert judgment in linguistic expressions is employed to describe the risk levels for all risk factors, which are represented by IVFSs using Gaussian membership function to fully consider such fuzziness and uncertainty. In regard to interval fusion and highly conflicting data, an improved combination rule based on the D–S evidence theory is developed. Then, fuzzy prior probability for each risk factor can be generated from fused intervals and fed into a fuzzy BN model for fuzzy-based Bayesian inference, including predictive, sensitivity, and diagnosis analysis. Furthermore, a case study is used to demonstrate the feasibility of the proposed risk analysis. A comparison of risk analysis based upon the hybrid improved D–S, classical D–S, and arithmetic average method is illustrated to show the outstanding performance of the developed approach in fusing multisource information with ubiquitous uncertainty and conflicts in an efficient manner, leading to more reliable risk evaluation. It is concluded that the proposed risk analysis provides a deep insight on risk control, especially for complex project environment, which enables to not only reduce the likelihood of failure ahead of time but also mitigate risk magnitudes to some degree after the occurrence of a failure.