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  • Open Access

    ARTICLE

    LDPC Code’s Decoding Algorithms for Wireless Sensor Network: a Brief Review

    Weidong Fang1, Wuxiong Zhang1,2, Lianhai Shan1,*, Biruk Assefa3, Wei Chen4

    Journal of New Media, Vol.1, No.1, pp. 45-50, 2019, DOI:10.32604/jnm.2019.05786

    Abstract As an effective error correction technology, the Low Density Parity Check Code (LDPC) has been researched and applied by many scholars. Meanwhile, LDPC codes have some prominent performances, which involves close to the Shannon limit, achieving a higher bit rate and a fast decoding. However, whether these excellent characteristics are suitable for the resource-constrained Wireless Sensor Network (WSN), it seems to be seldom concerned. In this article, we review the LDPC code’s structure brief.ly, and them classify and summarize the LDPC codes’ construction and decoding algorithms, finally, analyze the applications of LDPC code for WSN. We believe that our contributions… More >

  • Open Access

    ARTICLE

    Crack Detection and Localization on Wind Turbine Blade Using Machine Learning Algorithms: A Data Mining Approach

    A. Joshuva1, V. Sugumaran2

    Structural Durability & Health Monitoring, Vol.13, No.2, pp. 181-203, 2019, DOI:10.32604/sdhm.2019.00287

    Abstract Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however, blade get damaged due to wind gusts, bad weather conditions, unpredictable aerodynamic forces, lightning strikes and gravitational loads which causes crack on the surface of wind turbine blade. It is very much essential to identify the damage on blade before it crashes catastrophically which might possibly destroy the complete wind turbine. In this paper, a fifteen tree classification based machine learning algorithms were modelled for identifying and detecting the crack on wind turbine blades. The models are built based on… More >

  • Open Access

    ARTICLE

    Delamination Identification for FRP Composites with Emphasis on Frequency-Based Vibration Monitoring-A Review

    Mengyue He1, Zhifang Zhang1,*, Karthik Ram Ramakrishnan2

    Structural Durability & Health Monitoring, Vol.12, No.4, pp. 213-256, 2018, DOI:10.32604/sdhm.2018.05122

    Abstract Fibre reinforced polymer (FRP) composite laminates are now commonly used in many structural applications, especially in the aerospace industry, where margins of safety are kept low in order to minimise weight. Timely detection and assessment of damage (in particular delaminations) in composite laminates are therefore critical, as they can cause loss of structural integrity affecting the safe operation of the composite structures. The current trend is towards implementation of structural health monitoring (SHM) systems which can monitor the structures in situ without down time. In this paper, first, the current available SHM techniques for delamination detection in FRP composites are… More >

  • Open Access

    ARTICLE

    Radial Basis Function and Genetic Algorithms for Parameter Identification to Some Groundwater Flow Problems

    B. Amaziane1, A. Naji2, D. Ouazar3

    CMC-Computers, Materials & Continua, Vol.1, No.2, pp. 117-128, 2004, DOI:10.3970/cmc.2004.001.117

    Abstract In this paper, a meshless method based on Radial Basis Functions (RBF) is coupled with genetic algorithms for parameter identification to some selected groundwater flow applications. The treated examples are generated by the diffusion equation with some specific boundary conditions describing the groundwater fluctuation in a leaky confined aquifer system near open tidal water. To select the best radial function interpolation and show the powerful of the method in comparison to domain based discretization methods, Multiquadric (MQ), Thin-Plate Spline (TPS) and Conical type functions are investigated and compared to finite difference results or analytical one. Through two sample problems in… More >

  • Open Access

    ARTICLE

    Context-Based Intelligent Scheduling and Knowledge Push Algorithms for AR-Assist Communication Network Maintenance

    Lanlan Rui1, Yabin Qin1,*, Biyao Li1, Zhipeng Gao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 291-315, 2019, DOI:10.31614/cmes.2018.04240

    Abstract Maintenance is an important aspect in the lifecycle of communication network devices. Prevalent problems in the maintenance of communication networks include inconvenient data carrying and sub-optimal scheduling of work orders, which significantly restrict the efficiency of maintenance work. Moreover, most maintenance systems are still based on cloud architectures that slow down data transfer. With a focus on the completion time, quality, and load balancing of maintenance work, we propose in this paper a learning-based virus evolutionary genetic algorithm with multiple quality-of-service (QoS) constraints to implement intelligent scheduling in an edge network. The algorithm maintains the diversity of the population and… More >

  • Open Access

    ARTICLE

    A Survey of Image Information Hiding Algorithms Based on Deep Learning

    Ruohan Meng1,2,*, Qi Cui1,2, Chengsheng Yuan1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.3, pp. 425-454, 2018, DOI:10.31614/cmes.2018.04765

    Abstract With the development of data science and technology, information security has been further concerned. In order to solve privacy problems such as personal privacy being peeped and copyright being infringed, information hiding algorithms has been developed. Image information hiding is to make use of the redundancy of the cover image to hide secret information in it. Ensuring that the stego image cannot be distinguished from the cover image, and sending secret information to receiver through the transmission of the stego image. At present, the model based on deep learning is also widely applied to the field of information hiding. This… More >

  • Open Access

    ARTICLE

    Grey Wolf Optimizer to Real Power Dispatch with Non-Linear Constraints

    G. R. Venkatakrishnan1,*, R. Rengaraj2, S. Salivahanan3

    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 25-45, 2018, DOI:10.3970/cmes.2018.115.025

    Abstract A new and efficient Grey Wolf Optimization (GWO) algorithm is implemented to solve real power economic dispatch (RPED) problems in this paper. The nonlinear RPED problem is one the most important and fundamental optimization problem which reduces the total cost in generating real power without violating the constraints. Conventional methods can solve the ELD problem with good solution quality with assumptions assigned to fuel cost curves without which these methods lead to suboptimal or infeasible solutions. The behavior of grey wolves which is mimicked in the GWO algorithm are leadership hierarchy and hunting mechanism. The leadership hierarchy is simulated using… More >

  • Open Access

    ARTICLE

    Double Optimal Regularization Algorithms for Solving Ill-Posed Linear Problems under Large Noise

    Chein-Shan Liu1, Satya N. Atluri2

    CMES-Computer Modeling in Engineering & Sciences, Vol.104, No.1, pp. 1-39, 2015, DOI:10.3970/cmes.2015.104.001

    Abstract A double optimal solution of an n-dimensional system of linear equations Ax = b has been derived in an affine m « n. We further develop a double optimal iterative algorithm (DOIA), with the descent direction z being solved from the residual equation Az = r0 by using its double optimal solution, to solve ill-posed linear problem under large noise. The DOIA is proven to be absolutely convergent step-by-step with the square residual error ||r||2 = ||b - Ax||2 being reduced by a positive quantity ||Azk||2 at each iteration step, which is found to be better than those algorithms based… More >

  • Open Access

    ARTICLE

    Novel Iterative Algorithms Based on Regularization Total Least Squares for Solving the Numerical Solution of Discrete Fredholm Integral Equation

    Zichun Yang1,2,3, Lei Zhang1,4, Yueyun Cao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.97, No.2, pp. 101-130, 2014, DOI:10.3970/cmes.2014.097.101

    Abstract Discretization of inverse problems often leads to systems of linear equations with a highly ill-conditioned coefficient matrix. To find meaningful solutions of such systems, one kind of prevailing and representative approaches is the so-called regularized total least squares (TLS) method when both the system matrix and the observation term are contaminated by some noises. We will survey two such regularization methods in the TLS setting. One is the iterative truncated TLS (TTLS) method which can solve a convergent sequence of projected linear systems generated by Lanczos bidiagonalization. The other one is to convert the Tikhonov regularization TLS problem to an… More >

  • Open Access

    ARTICLE

    A Systematic Review of Algorithms with Linear-time Behaviour to Generate Delaunay and Voronoi Tessellations

    S,erson L. Gonzaga de Oliveira1, Jéssica Renata Nogueira1, João Manuel R. S. Tavares2

    CMES-Computer Modeling in Engineering & Sciences, Vol.100, No.1, pp. 31-57, 2014, DOI:10.3970/cmes.2014.100.031

    Abstract Triangulations and tetrahedrizations are important geometrical discretization procedures applied to several areas, such as the reconstruction of surfaces and data visualization. Delaunay and Voronoi tessellations are discretization structures of domains with desirable geometrical properties. In this work, a systematic review of algorithms with linear-time behaviour to generate 2D/3D Delaunay and/or Voronoi tessellations is presented. More >

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