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  • Open Access

    ARTICLE

    Assessing the Performance of Some Ranked Set Sampling Designs Using HybridApproach

    Mohamed. A. H. Sabry1,*, Ehab M. Almetwally2, Hisham M. Almongy3, Gamal M. Ibrahim4

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3737-3753, 2021, DOI:10.32604/cmc.2021.017510 - 06 May 2021

    Abstract In this paper, a joint analysis consisting of goodness-of-fit tests and Markov chain Monte Carlo simulations are used to assess the performance of some ranked set sampling designs. The Markov chain Monte Carlo simulations are conducted when Bayesian methods with Jeffery’s priors of the unknown parameters of Weibull distribution are used, while the goodness of fit analysis is conducted when the likelihood estimators are used and the corresponding empirical distributions are obtained. The ranked set sampling designs considered in this research are the usual ranked set sampling, extreme ranked set sampling, median ranked set sampling, More >

  • Open Access

    ARTICLE

    L-Moments Based Calibrated Variance Estimators Using Double Stratified Sampling

    Usman Shahzad1,2,*, Ishfaq Ahmad1, Ibrahim Mufrah Almanjahie3,4, Nadia H.Al –Noor5

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3411-3430, 2021, DOI:10.32604/cmc.2021.017046 - 06 May 2021

    Abstract Variance is one of the most vital measures of dispersion widely employed in practical aspects. A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the presence of extreme values, and thus its results cannot be relied on. Finding momentum from Koyuncu’s recent work, the present paper focuses first on proposing two classes of variance estimators based on linear moments (L-moments), and then employing them with auxiliary data under double stratified sampling to introduce a new class of calibration variance estimators using important properties of L-moments (L-location, More >

  • Open Access

    ABSTRACT

    Phase analysis for out-of-plane displacement measurement using laser lines generated in camera with diffraction grating

    Wei Jiang1,*, Takuya Hara1, Motoharu Fujigaki1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.23, No.1, pp. 22-23, 2021, DOI:10.32604/icces.2021.08551

    Abstract In this study, a sampling moire method in which parallel laser lines were generated in a camera using a diffraction grating was proposed. A green laser of line projection function, a diffraction grating and an industrial camera were used as an experimental device. Object images with laser line projection before and after displacement were taken by the camera. Displacements that calculated by a sampling moire method and a method of averaging center-ofgravity were be compared. Results show that the proposed method is more precision than method of averaging center-of-gravity. More >

  • Open Access

    ARTICLE

    Dealing with the Class Imbalance Problem in the Detection of Fake Job Descriptions

    Minh Thanh Vo1, Anh H. Vo2, Trang Nguyen3, Rohit Sharma4, Tuong Le2,5,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 521-535, 2021, DOI:10.32604/cmc.2021.015645 - 22 March 2021

    Abstract In recent years, the detection of fake job descriptions has become increasingly necessary because social networking has changed the way people access burgeoning information in the internet age. Identifying fraud in job descriptions can help jobseekers to avoid many of the risks of job hunting. However, the problem of detecting fake job descriptions comes up against the problem of class imbalance when the number of genuine jobs exceeds the number of fake jobs. This causes a reduction in the predictability and performance of traditional machine learning models. We therefore present an efficient framework that uses… More >

  • Open Access

    ARTICLE

    New Improved Ranked Set Sampling Designs with an Application to Real Data

    Amer Ibrahim Al-Omari1, Ibrahim M. Almanjahie2,3,*

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1503-1522, 2021, DOI:10.32604/cmc.2021.015047 - 05 February 2021

    Abstract This article proposes two new Ranked Set Sampling (RSS) designs for estimating the population parameters: Simple Z Ranked Set Sampling (SZRSS) and Generalized Z Ranked Set Sampling (GZRSS). These designs provide unbiased estimators for the mean of symmetric distributions. It is shown that for non-uniform symmetric distributions, the estimators of the mean under the suggested designs are more efficient than those obtained by RSS, Simple Random Sampling (SRS), extreme RSS and truncation based RSS designs. Also, the proposed RSS schemes outperform other RSS schemes and provide more efficient estimates than their competitors under imperfect rankings. More >

  • Open Access

    ARTICLE

    Power Inverted Topp–Leone Distribution in Acceptance Sampling Plans

    Tahani A. Abushal1, Amal S. Hassan2, Ahmed R. El-Saeed3, Said G. Nassr4,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 991-1011, 2021, DOI:10.32604/cmc.2021.014620 - 12 January 2021

    Abstract We introduce a new two-parameter model related to the inverted Topp–Leone distribution called the power inverted Topp–Leone (PITL) distribution. Major properties of the PITL distribution are stated; including; quantile measures, moments, moment generating function, probability weighted moments, Bonferroni and Lorenz curve, stochastic ordering, incomplete moments, residual life function, and entropy measure. Acceptance sampling plans are developed for the PITL distribution, when the life test is truncated at a pre-specified time. The truncation time is assumed to be the median lifetime of the PITL distribution with pre-specified factors. The minimum sample size necessary to ensure the… More >

  • Open Access

    ARTICLE

    Acceptance Sampling Plans with Truncated Life Tests for the Length-Biased Weighted Lomax Distribution

    Amer Ibrahim Al-Omari1,*, Ibrahim M. Almanjahie2,3, Olena Kravchuk4

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 285-301, 2021, DOI:10.32604/cmc.2021.014537 - 12 January 2021

    Abstract In this paper, we considered the Length-biased weighted Lomax distribution and constructed new acceptance sampling plans (ASPs) where the life test is assumed to be truncated at a pre-assigned time. For the new suggested ASPs, the tables of the minimum samples sizes needed to assert a specific mean life of the test units are obtained. In addition, the values of the corresponding operating characteristic function and the associated producer’s risks are calculated. Analyses of two real data sets are presented to investigate the applicability of the proposed acceptance sampling plans; one data set contains the More >

  • Open Access

    ARTICLE

    Intelligent Fusion of Infrared and Visible Image Data Based on Convolutional Sparse Representation and Improved Pulse-Coupled Neural Network

    Jingming Xia1, Yi Lu1, Ling Tan2,*, Ping Jiang3

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 613-624, 2021, DOI:10.32604/cmc.2021.013457 - 12 January 2021

    Abstract Multi-source information can be obtained through the fusion of infrared images and visible light images, which have the characteristics of complementary information. However, the existing acquisition methods of fusion images have disadvantages such as blurred edges, low contrast, and loss of details. Based on convolution sparse representation and improved pulse-coupled neural network this paper proposes an image fusion algorithm that decompose the source images into high-frequency and low-frequency subbands by non-subsampled Shearlet Transform (NSST). Furthermore, the low-frequency subbands were fused by convolutional sparse representation (CSR), and the high-frequency subbands were fused by an improved pulse More >

  • Open Access

    ARTICLE

    A New Class of L-Moments Based Calibration Variance Estimators

    Usman Shahzad1,2,*, Ishfaq Ahmad1, Ibrahim Mufrah Almanjahie3,4, Nadia H. Al Noor5, Muhammad Hanif2

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3013-3028, 2021, DOI:10.32604/cmc.2021.014101 - 28 December 2020

    Abstract Variance is one of the most important measures of descriptive statistics and commonly used for statistical analysis. The traditional second-order central moment based variance estimation is a widely utilized methodology. However, traditional variance estimator is highly affected in the presence of extreme values. So this paper initially, proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics (L-location, L-scale, L-CV) and auxiliary information. It is demonstrated that the proposed L-Moments based calibration variance… More >

  • Open Access

    ARTICLE

    Sensitivity of Sample for Simulation-Based Reliability Analysis Methods

    Xiukai Yuan1,2,*, Jian Gu1, Shaolong Liu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 331-357, 2021, DOI:10.32604/cmes.2021.010482 - 22 December 2020

    Abstract In structural reliability analysis, simulation methods are widely used. The statistical characteristics of failure probability estimate of these methods have been well investigated. In this study, the sensitivities of the failure probability estimate and its statistical characteristics with regard to sample, called ‘contribution indexes’, are proposed to measure the contribution of sample. The contribution indexes in four widely simulation methods, i.e., Monte Carlo simulation (MCS), importance sampling (IS), line sampling (LS) and subset simulation (SS) are derived and analyzed. The proposed contribution indexes of sample can provide valuable information understanding the methods deeply, and enlighten More >

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