Location-based service (LBS) has been widely used in various fields of industry, and become a vital part of people's daily life. However, while providing great convenience for users, LBS results in a serious threat on users' location privacy, due to its more and more untrusted server-side. In this paper, we propose a location privacy-preserving system for LBS by constructing “cover-up ranges” to protect the query ranges associated with a location query sequence. Firstly, we present a client-based system framework for location privacy protection in LBS, which requires no compromise to the accuracy and usability of LBS. Secondly, based on the framework, we introduce a location privacy model to formulate the constraints that ideal cover-up ranges should satisfy, so as to improve the efficiency of location services and the security of location privacy. Finally, we describe an implementation algorithm to well meet the location privacy model. Both theoretical analysis and experimental evaluation demonstrate the effectiveness of our system, which can improve the security of users' location privacy on the untrusted server-side, without compromising the accuracy and usability of LBS.

Permanent magnet brakes (PMBs) have diverse applications in automotive, robotics, medical devices, and aerospace industries. However, evaluating the reliability of PMBs is challenging due to their complex construction and limited data availability. This article proposes a bivariate Wiener model to capture the degradation patterns of two key performance characteristics of PMBs, and introduces an objective Bayesian method to analyze degradation data with small sample sizes. The derivation of Jeffery prior and reference priors for different ordering groups, along with the verification of posterior propriety, are presented. A rejection sampling embedded Monte Carlo algorithm is employed to obtain Bayesian estimates of model parameters, reliability, and mean-time-to-failure of PMBs. Simulation study results demonstrate the superiority of the objective Bayesian method over the maximum likelihood approach, particularly when dealing with small sample sizes. Finally, the proposed method is applied to assess the reliability of PMBs.

We establish an SEIQRS epidemic model with periodic transmission rate to investigate the spread of seasonal HFMD in Wenzhou. The value of this study lies in two aspects. Mathematically, we show that the global dynamics of the HFMD model can be governed by its reproduction numberR0; ifR0<1, the disease-free equilibrium of the model is globally asymptotically stable, which means that the disease will vanish after some period of time; while ifR0>1, the model has at least one positive periodic solution and is uniformly persistent, which indicates that HFMD becomes an endemic disease. Epidemiologically, based on the statistical data of HFMD in Wenzhou, we find that the HFMD becomes an endemic disease and will break out in Wenzhou. One of the most interesting findings is that, for controlling the HFMD spread, we must increase the quarantined rate or decrease the treatment cycle.

In this paper, we consider a Leslie–Gower cross diffusion predator–prey model with a strong Allee effect and hunting cooperation. We mainly investigate the effects of self diffusion and cross diffusion on the stability of the homogeneous state point and processes of pattern formation. Using eigenvalue theory and Routh–Hurwitz criterion, we analyze the local stability of positive equilibrium solutions. We give the conditions of Turing instability caused by self diffusion and cross diffusion in detail. In order to discuss the influence of self diffusion and cross diffusion, we choose self diffusion coefficient and cross diffusion coefficient as the main control parameters. Through a series of numerical simulations, rich Turing structures in the parameter space were obtained, including hole pattern, strip pattern and dot pattern. Furthermore, We illustrate the spatial pattern through numerical simulation. The results show that the dynamics of the model exhibits that the self diffusion and cross diffusion control not only form the growth of dots, stripes, and holes, but also self replicating spiral pattern growth. These results indicate that self diffusion and cross diffusion have important effects on the formation of spatial patterns.