Siti Julia Rosli^1,2, Hasliza A Rahim^1,2,*, Khairul Najmy Abdul Rani^1,2, Ruzelita Ngadiran^2,3, Wan Azani Mustafa^3,4, Muzammil Jusoh^1,2, Mohd Najib Mohd Yasin^1,2, Thennarasan Sabapathy^1,2, Mohamedfareq Abdulmalek⁵, Wan Suryani Firuz Wan Ariffin², Ahmed Alkhayyat⁶

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2571-2571, 2023, DOI:10.32604/cmc.2023.045533 - 30 August 2023

Abstract This article has no abstract. More >

Siti Julia Rosli^1,2, Hasliza A Rahim^1,2,*, Khairul Najmy Abdul Rani^1,2, Ruzelita Ngadiran^2,3, Wan Azani Mustafa^3,4, Muzammil Jusoh^1,2, Mohd Najib Mohd Yasin^1,2, Thennarasan Sabapathy^1,2, Mohamedfareq Abdulmalek⁵, Wan Suryani Firuz Wan Ariffin², Ahmed Alkhayyat⁶

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3533-3556, 2022, DOI:10.32604/cmc.2022.021719 - 07 December 2021

Abstract The essential purpose of radar is to detect a target of interest and provide information concerning the target's location, motion, size, and other parameters. The knowledge about the pulse trains’ properties shows that a class of signals is mainly well suited to digital processing of increasing practical importance. A low autocorrelation binary sequence (LABS) is a complex combinatorial problem. The main problems of LABS are low Merit Factor (MF) and shorter length sequences. Besides, the maximum possible MF equals 12.3248 as infinity length is unable to be achieved. Therefore, this study implemented two techniques to… More >

Hongshuo Zhang¹, Bo Zhu^1,*, Kaimin Pang¹, Chunmei Chen¹, Yuwei Wan²

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 797-810, 2021, DOI:10.32604/iasc.2021.017232 - 20 April 2021

Abstract Using machine learning method to recognize abnormal patterns covers the shortage of traditional control charts for autocorrelation processes, which violate the applicable conditions of the control chart, i.e., the independent identically distributed (IID) assumption. In this study, we propose a recognition model based on support vector machine (SVM) for the AR (1) type of autocorrelation process. For achieving a higher recognition performance, the cuckoo search algorithm (CS) is used to optimize the two hyper-parameters of SVM, namely the penalty parameter c and the radial basis kernel parameter g. By using Monte Carlo simulation methods, the data… More >

Guoqing Yang¹, Baotong Li^2,3, Yang Wang², Jun Hong²

CMES-Computer Modeling in Engineering & Sciences, Vol.103, No.4, pp. 251-279, 2014, DOI:10.3970/cmes.2014.103.251

Abstract Mechanical behaviors arising at the contact interface largely depend on its surface topographies, particularly when it comes to rough surfaces. A numerical simulation based on an appropriate characterization of rough surfaces especially in terms of three dimensional can be of great significance when it comes to capturing the deformation patterns of micro-scale contacts. In this paper, a simple and practical scheme is developed to generate 3D rough surfaces and to analyze and evaluate the contact characteristics. Firstly amplitude and spatial statistical characterizations of asperities are introduced to avert from the redundancy of topography data caused… More >

H.K. Mebatsion¹, P. Verboven¹, Q. T. Ho¹, F. Mendoza¹, B. E. Verlinden², T. A. Nguyen¹, B. M. Nicolaï^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.14, No.1, pp. 1-14, 2006, DOI:10.3970/cmes.2006.014.001

Abstract Modeling plant microstructure is of great interest to food engineers to study and explain material properties related to mass transfer and mechanical deformation. In this paper, a novel ellipse tessellation algorithm to generate a 2D geometrical model of apple tissue is presented. Ellipses were used to quantify the orientation and aspect ratio of cells on a microscopic image. The cell areas and centroids of each cell were also determined by means of a numerical procedure. These characteristic quantities were then described by means of probability density functions. The model tissue geometry was generated from the… More >