A Review and Analysis of Localization Techniques in Underwater Wireless Sensor Networks

In recent years,there has been a rapid growth in Underwater Wireless Sensor Networks(UWSNs).The focus of research in this area is now on solving the problems associated with large-scale UWSN.One of the major issues in such a network is the localization of underwater nodes.Localization is required for tracking objects and detecting the target.It is also considered tagging of data where sensed contents are not found of any use without localization.This is useless for application until the position of sensed content is confirmed.This article’s major goal is to review and analyze underwater node localization to solve the localization issues in UWSN.The present paper describes various existing localization schemes and broadly categorizes these schemes as Centralized and Distributed localization schemes underwater.Also,a detailed subdivision of these localization schemes is given.Further,these localization schemes are compared from different perspectives.The detailed analysis of these schemes in terms of certain performance metrics has been discussed in this paper.At the end,the paper addresses several future directions for potential research in improving localization problems of UWSN.

High-Order Decoupled and Bound Preserving Local Discontinuous Galerkin Methods for a Class of Chemotaxis Models

In this paper,we explore bound preserving and high-order accurate local discontinuous Galerkin(LDG)schemes to solve a class of chemotaxis models,including the classical Keller-Segel(KS)model and two other density-dependent problems.We use the convex splitting method,the variant energy quadratization method,and the scalar auxiliary variable method coupled with the LDG method to construct first-order temporal accurate schemes based on the gradient flow structure of the models.These semi-implicit schemes are decoupled,energy stable,and can be extended to high accuracy schemes using the semi-implicit spectral deferred correction method.Many bound preserving DG discretizations are only worked on explicit time integration methods and are difficult to get high-order accuracy.To overcome these difficulties,we use the Lagrange multipliers to enforce the implicit or semi-implicit LDG schemes to satisfy the bound constraints at each time step.This bound preserving limiter results in the Karush-Kuhn-Tucker condition,which can be solved by an efficient active set semi-smooth Newton method.Various numerical experiments illustrate the high-order accuracy and the effect of bound preserving.

A local energy-preserving scheme for Zakharov system

In this paper, we propose a local conservation law for the Zakharov system. The property is held in any local time- space region which is independent of the boundary condition and more essential than the global energy conservation law. Based on the rule that the numerical methods should preserve the intrinsic properties as much as possible, we propose a local energy-preserving （LEP） scheme for the system. The merit of the proposed scheme is that the local energy conservation law can be conserved exactly in any time-space region. With homogeneous Dirchlet boundary conditions, the proposed LEP scheme also possesses the discrete global mass and energy conservation laws. The theoretical properties are verified by numerical results.

Local Discontinuous Galerkin Scheme for Space Fractional Allen–Cahn Equation

This paper is concerned with the efficient numerical solution for a space fractional Allen–Cahn(AC)equation.Based on the features of the fractional derivative,we design and analyze a semi-discrete local discontinuous Galerkin(LDG)scheme for the initial-boundary problem of the space fractional AC equation.We prove the optimal convergence rates of the semi-discrete LDG approximation for smooth solutions.Finally,we test the accuracy and efficiency of the designed numerical scheme on a uniform grid by three examples.Numerical simulations show that the space fractional AC equation displays abundant dynamical behaviors.

DIFFERENCE SCHEMES BASING ON COEFFICIENT APPROXIMATION

In respect of variable coefficient differential equations, the equations of coefficient function approximation were more accurate than the coefficient to be frozen as a constant in every discrete subinterval. Usually, the difference schemes constructed based on Taylor expansion approximation of the solution do not suit the solution with sharp function. Introducing into local bases to be combined with coefficient function approximation, the difference can well depict more complex physical phenomena, for example, boundary layer as well as high oscillatory,with sharp behavior. The numerical test shows the method is more effective than the traditional one.

LOCAL ONE-DIMENSIONAL ASE-I SCHEME FOR 2D DIFFUSION EQUATION

A local alternating segment explicit - implicit method for the solution of 2D diffusion equations is presented in this paper .The method is unconditionally stable and has the obvious property of parallelism. Some numerical experiments show the method is not only simple but also more accurate.

A class of fully third-order accurate projection methods for solving the incompressible Navier-Stokes equations

In this paper, a fully third-order accurate projection method for solving the incompressible Navier-Stokes equations is proposed. To construct the scheme, a continuous projection procedure is firstly presented. We then derive a sufficient condition for the continuous projection equations to be temporally third-order accurate approximations of the original Navier-Stokes equations by means of the localtruncation-error-analysis technique. The continuous projection equations are discretized temporally and spatially to third-order accuracy on the staggered grids, resulting in a fully third-order discrete projection scheme. The possibility to design higher-order projection methods is thus demonstrated in the present paper. A heuristic stability analysis is performed on this projection method showing the probability of its being stable. The stability of the present scheme is further verified through numerical tests. The third-order accuracy of the present projection method is validated by several numerical test cases.

Mapping and analyzing the local climate zones in China’s 32 major cities using Landsat imagery based on a novel convolutional neural network

The Local Climate Zone(LCZ)scheme provides researchers with a standard method to monitor the Urban Heat Island(UHI)effect and conduct temperature studies.How to generate reliable LCZ maps has therefore become a research focus.In recent years,researchers have attempted to use Landsat imagery to delineate LCZs and generate maps worldwide based on the World Urban Database and Access Portal Tools(WUDAPT).However,the mapping results obtained by the WUDAPT method are not satisfactory.In this paper,to generate more accurate LCZ maps,we propose a novel Convolutional Neural Network(CNN)model(namely,LCZ-CNN),which is designed to cope with the issues of LCZ classification using Landsat imagery.Furthermore,in this study,we applied the LCZ-CNN model to generate LCZ mapping results for China’s 32 major cities distributed in various climatic zones,achieving a significantly better accuracy than the traditional classification strategies and a satisfactory computational efficiency.The pro-posed LCZ-CNN model achieved satisfactory classification accuracies in all 32 cities,and the Overall Accuracies(OAs)of more than half of the cities were higher than 80%.We also designed a series of experiments to comprehensively analyze the proposed LCZ-CNN model,with regard to the transferability of the network and the effectiveness of multiseasonal information.It was found that the first convolutional stage,corresponding to low-level features,shows better transferability than the second and third convolutional stages,which extract high-level and more image-or task-oriented features.It was also confirmed that the multi-seasonal information can improve the accuracy of LCZ classifica-tion.The thermal characteristics of the different LCZ classes were also analyzed based on the mapping results for China’s 32 major cities,and the experimental results confirmed the close relationship between the LCZ classes and the magnitude of the Land Surface Temperature(LST).

Privacy Preserving Query over Encrypted Multidimensional Massive Data in Cloud Storage

Cloud storage is widely used in massive data outsourcing, but how to efficiently query encrypted multidimensional data stored in an untrusted cloud environment remains a research challenge. We propose a high performance and privacy-preserving query（p LSH-PPQ） scheme over encrypted multidimensional data to address this challenge. In our scheme, for a given query, the proxy server will return K top similar data object identifiers. An enhanced Ciphertext-Policy Attribute-Based Encryption（CP-ABE）policy is used to control access to the search results. Therefore, only the requester with the permission attribute can obtain correct secret keys to decrypt the data. Security analysis proves that the p LSH-PPQ scheme achieves data confidentiality and reserves the data owner＇s privacy in a semi-trusted cloud. In addition, evaluations demonstrate that the p LSH-PPQ scheme can significantly reduce response time and provide high search efficiency without compromising on search quality.